WO1999009884A1 - Procede et appareil de mesure, de detection et de diagnostic d'un signal impulsionnel, de la fonction cardiaque et de l'intensite de mouvement - Google Patents
Procede et appareil de mesure, de detection et de diagnostic d'un signal impulsionnel, de la fonction cardiaque et de l'intensite de mouvement Download PDFInfo
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- WO1999009884A1 WO1999009884A1 PCT/JP1998/002706 JP9802706W WO9909884A1 WO 1999009884 A1 WO1999009884 A1 WO 1999009884A1 JP 9802706 W JP9802706 W JP 9802706W WO 9909884 A1 WO9909884 A1 WO 9909884A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/02028—Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
- A61B5/02108—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/026—Measuring blood flow
- A61B5/0295—Measuring blood flow using plethysmography, i.e. measuring the variations in the volume of a body part as modified by the circulation of blood therethrough, e.g. impedance plethysmography
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4854—Diagnosis based on concepts of traditional oriental medicine
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6813—Specially adapted to be attached to a specific body part
- A61B5/6814—Head
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
- A61B5/7207—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal of noise induced by motion artifacts
- A61B5/721—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal of noise induced by motion artifacts using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7253—Details of waveform analysis characterised by using transforms
- A61B5/726—Details of waveform analysis characterised by using transforms using Wavelet transforms
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/026—Measuring blood flow
- A61B5/029—Measuring or recording blood output from the heart, e.g. minute volume
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7239—Details of waveform analysis using differentiation including higher order derivatives
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7253—Details of waveform analysis characterised by using transforms
- A61B5/7257—Details of waveform analysis characterised by using transforms using Fourier transforms
Definitions
- the present invention relates to an apparatus for extracting information related to the state of a living body from a pulse wave and measuring the state of the living body based on the extracted information, and to a diagnostic apparatus and a Foda method.
- a diagnostic apparatus and a Foda method In diagnosing the state of the circulatory system of the human body, blood pressure and heart rate are probably the most commonly used. Therefore, as an indicator for grasping the state of the circulatory system and, in a broader sense, physical condition, an index that can easily measure blood pressure values such as systolic blood pressure and diastolic blood pressure and pulse rate taken from the human body It has been heavily used. Since this index is a value obtained by measuring the pulse during a certain time, it can be said that it is a representative value during the measurement time.
- the pulse wave is a blood wave that is emitted from the heart and propagates through the blood vessels, and it is known that various medical information can be obtained by detecting and analyzing the pulse wave.
- a doctor presses the radial artery with a finger, and diagnoses the condition of the living body based on the pulse felt by the finger.
- Typical pulse waveforms include pulse veins, smooth veins, and chord veins.
- pulse diagnosis diagnoses the state of a living body by the subtle tactile sensation felt by a human finger, and it is difficult to convey and learn such skills from humans. It takes a long time to train. In addition, if there is body motion in the living body, it is difficult to specify an accurate pulse because the blood flow changes.
- Exercise at a certain intensity is often performed for various types of training. Exercise intensity at that time was determined from subjective evaluations such as “tight” and “easy”.
- an index focusing on the volume of blood pumped from the heart may be used.
- stroke volume SV and cardiac output CO correspond to such an index.
- An object of the present invention is to provide the following device while considering such a state of a living body.
- a first invention relates to a pulse wave diagnostic apparatus, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body; and a wavelet conversion to the pulse wave waveform detected by the pulse wave detecting means. And a wavelet transforming means for generating pulse wave analysis data for each frequency domain; Pulse data generating means for generating pulse data indicating the type of wave waveform.
- the second invention relates to a pulse wave diagnostic apparatus, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body; and a wavelet conversion to the pulse wave waveform detected by the pulse wave detecting means.
- First wavelet conversion means for generating pulse wave analysis data for each frequency domain
- body movement detection means for detecting the body movement of the living body and outputting a body movement waveform
- body movement Second wavelet conversion means for subjecting the body motion waveform detected by the detection means to wavelet conversion to generate body motion analysis data for each frequency domain
- Mask means for subtracting the motion analysis data to generate a corrected pulse wave data from which the body motion has been removed; and performing an arithmetic process on the corrected pulse wave data generated by the mask means to obtain the pulse wave waveform.
- Pulse indicating the type of And it is characterized by a Myakuzode Isseki generating means for generating data.
- a third invention relates to a pulse wave diagnostic apparatus, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body; and a wavelet conversion to the pulse wave waveform detected by the pulse wave detecting means.
- Wavelet transform means for generating pulse wave analysis data for each frequency domain, and correcting the pulse wave analysis data to normalize the power per frequency based on each corresponding frequency.
- Frequency pulse generating means for generating corrected pulse wave data, and pulse data generating means for performing arithmetic processing on the corrected pulse wave data to generate pulse data indicating the type of the pulse waveform. It is characterized by the following.
- a fourth invention relates to a pulse wave diagnostic apparatus, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body; and a wavelet conversion to the pulse wave waveform detected by the pulse wave detecting means. And a first wavelet transform means for generating pulse wave analysis data for each frequency domain, and normalizing the power per frequency in the pulse wave analysis data based on each corresponding frequency.
- First frequency correction means for performing correction as described above and generating corrected pulse wave data
- body motion detection means for detecting the body movement of the living body and outputting a body movement waveform
- the body movement detection means A second wavelet transform unit that performs a wavelet transform on the detected body motion waveform to generate body motion analysis data for each frequency domain, and the body motion analysis data based on each corresponding frequency.
- a second frequency correction means for performing correction so as to normalize the power per frequency to generate body motion correction data, and subtracting the body motion correction data from the corrected pulse wave data to calculate a body motion.
- Mask means for generating the corrected pulse wave data removed; and performing arithmetic processing on the corrected pulse wave data generated by the mask means to generate a pulse wave data indicating the type of the pulse wave waveform. And pulse data generation means.
- a fifth invention relates to a pulse wave diagnostic apparatus, comprising: a pulse wave detecting means for detecting a wave shape from a detection part of a living body; and a wavelet for the pulse wave shape detected by the pulse wave detecting means.
- First wavelet conversion means for performing conversion to generate pulse wave analysis data for each frequency domain; body movement detection means for detecting body movement of the living body and outputting a body movement waveform;
- a second wavelet transforming means for subjecting the body motion waveform detected by the motion detecting means to a wavelet transform to generate body motion analysis data for each frequency domain; and
- Mask means for subtracting the motion analysis data to generate pulse wave data from which body motion has been removed for each frequency domain; and normalizing the power per frequency in the pulse wave data based on each corresponding frequency.
- a sixth invention relates to a pulse wave diagnostic apparatus, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body; and a wavelet conversion to the pulse wave waveform detected by the pulse wave detecting means.
- Wavelet transform means for generating pulse wave analysis data for each frequency domain, and generating a pulse wave analysis data by removing a frequency component corresponding to a body movement from the pulse wave analysis data.
- Body movement separating means frequency correction means for performing correction on the pulse wave analysis data generated by the body movement separating means in accordance with the corresponding frequency, and generating corrected pulse wave data;
- Pulse wave data generating means for performing arithmetic processing on the pulse wave data to generate pulse data indicating the type of the pulse wave waveform.
- a seventh invention relates to a pulse wave diagnostic apparatus, wherein the pulse image data generation means performs an inverse wavelet transform on the corrected pulse wave data to remove a pulse wave from which a body motion has been removed.
- An inverse wavelet transform unit for generating data; and a data generating unit for generating the pulse data based on each peak information of the pulse wave data.
- An eighth invention relates to a pulse wave diagnostic apparatus, wherein state detection means for detecting a movement state of a living body based on a body movement waveform detected by the body movement detection means, Control means for controlling the first wavelet transform means so as to vary a frequency region to be subjected to frequency analysis in accordance with the above.
- a ninth invention relates to a pulse wave diagnostic apparatus, wherein the control means includes: a storage means for storing in advance a relationship between a movement state of the living body and a frequency domain to be subjected to frequency analysis; Reading means for reading a frequency region to be subjected to frequency analysis based on the motion state of the living body detected by the means, and controlling the frequency region to be subjected to frequency analysis based on the read result.
- a tenth aspect of the present invention relates to a pulse wave diagnostic apparatus, comprising: a pulse wave period detecting unit that detects a period of the pulse wave waveform, wherein the wavelet transform unit is configured to generate a wave in synchronization with the detected period. Characteristic conversion is performed.
- the eleventh invention relates to a pulse wave diagnostic apparatus, comprising: a pulse wave cycle detecting means for detecting a cycle of the pulse wave waveform; the first wavelet converting means; and the second wavelet.
- the conversion means performs a wavelet conversion in synchronization with the detected period.
- a twelfth invention is characterized in that it comprises a notifying means for notifying the pulse data generated by the pulse data generating means.
- a thirteenth invention relates to a pulse wave diagnostic apparatus, wherein the pulse wave detecting means comprises a pressure sensor for detecting pulsation of an artery of a living body by pressure.
- a fifteenth invention relates to a pulse wave diagnostic apparatus, wherein the pulse wave detection means is obtained when a detection site of a living body is irradiated with light having a wavelength of 300 nm to 700 nm. And detecting a received light signal that has received the reflected light as a pulse waveform.
- a fifteenth invention relates to a pulse wave diagnostic apparatus, wherein the pulse wave detecting means is obtained when a detection site of a living body is irradiated with light having a wavelength of 600 nm to 100 nm. And detecting a received light signal having received the transmitted light as a pulse waveform.
- a sixteenth invention relates to a pulse data generation method, comprising: a first step of detecting a pulse wave waveform from a detection portion of a living body; and performing a wavelet transform on the detected pulse wave waveform.
- a seventeenth invention relates to a pulse data generation method, comprising: a first step of detecting a pulse waveform from a detection portion of a living body; and the pulse waveform detected by the first step.
- the eighteenth invention relates to a pulse data generation method, comprising: a first step of detecting a pulse wave waveform from a detection part of a living body; and a step of adding a wave to the pulse wave waveform detected in the first step.
- a second step of performing pulse transformation to generate pulse wave analysis data for each frequency domain, and normalizing power per frequency to the pulse wave analysis data based on each corresponding frequency A third step of performing correction as described above to generate a corrected pulse wave data, and a fourth step of performing arithmetic processing on the corrected pulse wave data to generate pulse image data indicating the type of the pulse wave waveform. And the following steps.
- the nineteenth invention relates to a pulse data generation method, comprising: a first step of detecting a pulse waveform from a detection part of a living body; A second step of performing pulse transformation to generate pulse wave analysis data for each frequency domain, and normalizing the power per frequency to the pulse wave analysis data based on each corresponding frequency.
- a third step of generating corrected pulse wave data by performing correction to generate a body motion waveform by detecting body motion of the living body A fourth step of performing a wavelet transform on the body motion waveform detected in the fourth step to generate body motion analysis data for each frequency domain, and a corresponding frequency
- an eighth step A third step of generating corrected pulse wave data by performing correction to generate a body motion waveform by detecting body motion of the living body.
- a twenty-second invention relates to a pulse data generation method, comprising: a first step of detecting a pulse wave waveform from a detection part of a living body; and performing a wavelet transform on the pulse wave waveform, and A second step of generating pulse wave analysis data, a third step of detecting a body motion of the living body and generating a body motion waveform, and a step of generating the body motion waveform detected by the third step.
- Myakuzode Isseki generating method is characterized in that a seventh step of generating a pulse elephant data indicating the type of the pulse waveform.
- a twenty-first invention relates to a pulse data generation method, comprising: a first step of detecting a pulse waveform from a detection part of a living body; and performing a wavelet transform on the pulse waveform, and A second step of generating pulse wave analysis data, a third step of generating a pulse wave analysis data by removing a frequency component corresponding to a body motion from the pulse wave analysis data, A fourth step of performing correction on the pulse wave analysis data to generate corrected pulse wave data in accordance with the frequency, and performing an arithmetic process on the corrected pulse wave data, A fifth step of generating pulse data indicating the type.
- the second invention relates to a movement index measuring device, and includes a pulse rate detecting means for detecting a subject's beat rate, a pitch detecting means for detecting a subject's exercise pitch, a detected beat rate and a detected beat rate. Determining means for determining points at which the determined exercise pitches are substantially the same as each other; first calculating means for determining the exercise intensity corresponding to the determined points; and first means for notifying the determined exercise intensity as an exercise index. Notification means.
- a twenty-third invention relates to a movement index measuring device, wherein the determination means is the same if the difference between the detected number of beats and the detected movement pitch is within a range of 10%. Is determined.
- a twenty-fourth invention relates to an exercise index measuring device, wherein first exercise means for storing exercise intensity obtained by the first calculation means in association with time, and A second notification means for notifying the content stored in the first storage means along with the transition of time is provided.
- a twenty-fifth invention relates to a movement index measuring device, wherein the second calculation means determines the exercise intensity at that time from the detected movement pitch or the number of beats, and the second calculation means determines the exercise intensity at that time. And third notification means for notifying the exercise intensity.
- a twenty-sixth invention relates to a movement index measuring device, wherein a beat rate detecting means for detecting a subject's beat rate, a pitch detecting means for detecting a subject's exercise pitch, and detected by the beat rate detecting means A first comparison means for obtaining a difference between the detected beat count and the pitch detected by the pitch detection means, obtaining a difference between the difference and the degree of the beat count or the pitch, and obtaining the difference by the comparison means. And a fourth notifying means for notifying the result of the comparison.
- a twenty-seventh invention relates to a movement index measurement device, wherein the beat rate detection means detects a subject's beat rate, a pitch detection means detects a subject's exercise pitch, and the beat rate detection means detects Second comparing means for comparing the detected number of beats and the pitch detected by the pitch detecting means, and fifth notifying means for notifying a motion instruction in a direction to eliminate the difference between the two based on the comparison result by the comparing means. It is characterized by having Sign.
- a twenty-eighth invention relates to an exercise index measurement device, wherein the exercise performed by the subject is a running exercise, and the exercise apparatus includes second storage means for storing a step length of the subject in advance, and wherein the pitch detection means
- the first or second calculating means detects a running pitch, and the first or second calculating means multiplies the step length stored in the second storage means by the running pitch detected by the pitch detecting means, and converts It is characterized by being obtained as strength.
- the twentieth invention relates to a movement index measuring device, and comprises a correction means for correcting a stride stored in the second storage means in accordance with a change in a running pitch or a pulse rate of a subject.
- a thirtieth aspect of the present invention relates to a movement index measuring device, and comprises a communication means for exchanging information with an external device.
- a thirty-first invention relates to a movement index measuring device, wherein the number of beats detected by the number of beats detecting means, the pitch detected by the pitch detecting means, or the number of beats corrected by the correcting means is corrected. It is characterized by comprising: third storage means for storing at least one or more data indicating a stride; and communication means for transmitting the data stored in the third storage means to an external device.
- a thirty-second invention relates to a movement index measuring device, wherein the communication means receives at least one or more data indicating the number of beats, pitch, or stride set by an external device.
- the 33rd invention relates to a method for measuring a movement index, wherein the second step of detecting the movement pitch of the subject and the point where the detected number of beats and the detected movement pitch are substantially the same as each other are described.
- a thirty-fourth invention relates to an exercise index measuring method, wherein a sixth step of storing the exercise intensity in association with time, and a seventh step of notifying the stored contents together with a transition of time. Characterized by comprising the following steps:
- a thirty-fifth invention relates to a method for measuring a movement index, wherein the third step In addition to the step and the fourth step, the method further comprises a step of obtaining the exercise intensity at that time from the detected exercise pitch or beat count.
- a thirty-sixth invention relates to a movement index measuring method, wherein a first step of detecting a subject's beat rate, a second step of detecting a subject's exercise pitch, and a detected beat rate And a third step of obtaining a difference between the detected pitches and obtaining a difference between the difference and the number of beats or pitches, and a fourth step of notifying the result of the comparison. I do.
- a thirty-seventh invention relates to a movement index measurement method, wherein a first step of detecting a subject's beat rate, a second step of detecting a subject's exercise pitch, and a detected beat rate And a third step of comparing the detected pitches, and a fourth step of notifying a motion instruction in a direction that eliminates the difference between the two based on the comparison result.
- a thirty-eighth invention relates to an exercise intensity detecting device, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body, and a body for detecting a body movement waveform indicating the body movement of the living body
- a motion detecting means generating a body motion component in the pulse wave waveform based on the body motion waveform, and removing the body motion component from the pulse wave waveform to generate a body motion removed pulse wave waveform.
- a degree intensity generating means is provided.
- a thirty-ninth invention relates to an exercise intensity detecting apparatus, wherein the respiratory component extracting means performs a wavelet transform on the body motion removal pulse wave waveform to generate a body motion removal pulse wave analysis data.
- a respiratory waveform generation unit that generates a respiratory component.
- a 40th invention relates to an exercise intensity detection device, wherein the fortitude intensity generation means includes a ratio of a frequency component obtained by performing frequency analysis on the respiratory component extracted by the respiratory component extraction means. The exercise intensity is calculated based on the calculated exercise intensity.
- a forty-first invention relates to an exercise intensity detecting device, wherein the fortitude intensity generating means performs distortion analysis on each frequency component obtained by performing frequency analysis on the respiratory component extracted by the respiratory component extracting means. And calculating the exercise intensity based on the distortion rate.
- a forty-second invention relates to an exercise intensity detection device, wherein the fortitude intensity generation unit includes a fundamental frequency component obtained by performing a frequency analysis on a respiratory component extracted by the respiratory component extraction unit. It is characterized in that the ratio of the third harmonic component is calculated, and the exercise intensity is calculated based on the ratio.
- a forty-third invention relates to an exercise intensity detecting device, wherein the respiratory component extracting means extracts a respiratory waveform as the respiratory component, and the fortitude intensity generating means is extracted by the respiratory component extracting means. Detecting a duty ratio of the respiratory waveform, and generating the exercise intensity based on the duty ratio.
- a forty-fourth invention relates to an exercise intensity detection device, wherein the body motion removing means comprises: a first frequency analysis unit for analyzing a frequency spectrum of the pulse wave waveform; and a frequency spectrum of the body motion waveform.
- a second frequency analysis unit to be analyzed; and a frequency spectrum identical to the frequency spectrum analyzed by the second frequency analysis unit are removed from the frequency spectrum analyzed by the first frequency analysis unit.
- a body motion removing unit that generates a body motion removing spectrum from which the body motion has been removed, wherein the respiratory component extracting means corresponds to a fundamental wave component of a respiratory component from the body motion removing spectrum.
- a frequency spectrum is extracted, and the exercise intensity generating means generates a frequency spectrum level corresponding to a fundamental component of the respiratory component and a frequency spectrum corresponding to a harmonic component thereof. Based on the level of the beam, and calculates the exercise intensity.
- a forty-fifth invention relates to an exercise intensity detecting device, wherein the respiratory component extracting means specifies a band determined according to a pulse rate from the body motion removal spectrum, and within this band The frequency spectrum corresponding to the fundamental component of the respiratory component is extracted from the frequency spectrum of the above.
- a forty-sixth invention relates to an exercise intensity detecting device, wherein the fortitude intensity generating means corresponds to a spectrum level corresponding to a fundamental component of the respiratory component and a harmonic component thereof. Based on the spectrum level, calculate the distortion rate of the respiratory waveform, The exercise intensity is calculated based on the distortion rate.
- a forty-seventh invention relates to an exercise intensity detecting device, wherein the fortitude intensity generating means includes a spectrum level corresponding to a fundamental component of the respiratory component and a spectrum corresponding to a third harmonic component thereof.
- the exercise intensity is calculated based on the ratio of the exercise level.
- a forty-eighth invention relates to an exercise intensity detecting device, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body, and a respiratory component extracting means for extracting a respiratory component from the pulse wave waveform And fortune intensity generating means for calculating exercise intensity based on the respiratory component extracted by the respiratory component extracting means.
- a 49th invention relates to an exercise intensity detection device, wherein the respiratory component extraction means performs a frequency analysis on the pulse wave waveform to generate pulse wave analysis data, and the pulse wave
- a pulse wave component removing unit that removes a pulse wave component from the analysis data, a fundamental frequency table storing a relationship between a body motion fundamental wave frequency and a respiratory fundamental wave frequency in advance and a reference to the fundamental wave frequency table.
- a frequency specifying unit that specifies a respiratory fundamental frequency and a body motion fundamental frequency from the analysis data, and based on the respiratory fundamental frequency specified by the frequency specifying unit, An extractor for calculating and extracting a respiratory component.
- a fiftyth invention relates to an exercise intensity detection device, wherein the fortitude intensity generation means includes a spectrum level corresponding to a fundamental component of the respiratory component and a spectrum level corresponding to a harmonic component thereof.
- a distortion rate of the respiratory waveform is calculated based on the level, and the exercise intensity is calculated based on the distortion rate.
- a fifty-first invention relates to an exercise intensity detecting device, wherein the fortitude intensity generating means includes a spectrum level corresponding to a fundamental component of the respiratory component and a spectrum corresponding to a third harmonic component thereof. It is characterized in that a ratio with the level of the spectrum is obtained, and the exercise intensity is calculated based on the ratio.
- a fifty-second invention relates to an exercise intensity detection device, and is characterized by comprising a notifying means for notifying the exercise intensity generated by the fortitude intensity generating means.
- a fifty-third invention relates to an exercise intensity detection method, wherein a detection part of a living body A first step of detecting a pulse wave waveform from the body, a second step of detecting a body movement waveform indicating the body movement of the living body, and a body movement component in the pulse wave waveform based on the body movement waveform. A third step of generating; a fourth step of removing the body motion component from the pulse wave waveform to generate a body motion removal pulse wave waveform; and a respiratory component based on the body motion removal pulse wave waveform. A fifth step of extracting, and a sixth step of calculating exercise intensity based on the extracted respiratory component are provided.
- a fifty-fourth invention relates to an exercise intensity detection method, wherein the fifth step performs a wavelet transform on the body motion removal pulse wave waveform to generate a body motion removal pulse wave analysis data. Removing the frequency component corresponding to the pulse wave component from the body motion removal pulse wave analysis data to generate respiratory waveform analysis data, applying inverse wave to the respiratory waveform analysis data, and forming the respiratory waveform. Generating as the respiratory component.
- a fifty-fifth invention relates to an exercise intensity detection method, wherein the sixth step is based on a ratio of frequency components obtained by performing a frequency analysis on the extracted respiratory components. Is calculated.
- a fifth invention relates to an exercise intensity detection apparatus, wherein the fifth step extracts a respiration waveform from the body motion-removed pulse wave waveform as the respiration component, and the sixth step includes: A duty ratio of the obtained respiratory waveform is detected, and the exercise intensity is generated based on the duty ratio.
- a fifty-seventh invention relates to an exercise intensity detection method, wherein a first step of detecting a pulse wave waveform from a detection part of a living body and a second step of analyzing a frequency spectrum of the pulse wave waveform A third step for detecting a body motion waveform indicating the body motion of the living body; a fourth step for analyzing a frequency spectrum of the body motion waveform; and a frequency step of the analyzed body motion waveform.
- a fifty-eighth invention relates to an exercise intensity detection method, comprising: a first step of detecting a pulse waveform from a detection part of a living body; and a second step of extracting a respiratory component from the pulse waveform. And a third step of calculating exercise intensity based on the extracted respiratory component.
- a fifty-ninth invention relates to an exercise intensity detection method, wherein the third step is a step of storing the relationship between the fundamental frequency of the body motion and the fundamental frequency of the respiration in advance in association with each other; Performing a frequency analysis on the wave waveform to generate pulse wave analysis data; removing a pulse wave component from the pulse wave analysis data; and respiring from the analysis data with reference to the stored contents.
- the following invention relates to an apparatus and a method for measuring stroke volume and cardiac output.
- a 60th invention relates to an exercise intensity detecting device, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body, and a body for detecting a body movement waveform indicating the body movement of the living body Motion detection means, a body motion component that generates a body motion component in the pulse wave waveform based on the body motion waveform, and removes the body motion component from the pulse wave waveform to generate a body motion removal pulse wave waveform Means, a heart rate detecting means for detecting the heart rate of the living body, an ejection period detecting means for detecting an ejection period of the heart based on the body motion removal pulse wave waveform, and an ejection period for the heart And a cardiac output calculating means for calculating a cardiac output based on the heart rate.
- a sixty-first invention relates to an exercise intensity detecting device, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body, and a body for detecting a body movement waveform indicating the body movement of the living body Motion detection means, a body motion component that generates a body motion component in the pulse wave waveform based on the body motion waveform, and removes the body motion component from the pulse wave waveform to generate a body motion removal pulse wave waveform Means, a heart rate detecting means for detecting the heart rate of the living body, an ejection period detecting means for detecting an ejection period of the heart based on the body motion removal pulse wave waveform, and an ejection period for the heart Calculating the cardiac output based on the pulse wave waveform and the heart rate at A cardiac output calculator.
- the 62nd invention relates to an exercise intensity detecting device, and 62.
- a determining means for determining the presence or absence of body movement of the living body based on a body movement waveform detected by the body movement detecting means.
- the body movement removing unit stops the body movement removing operation, and replaces the body movement removed pulse wave waveform with the pulse wave waveform. It is characterized by outputting.
- a sixth invention relates to an exercise intensity detection device, wherein the heart rate detection means obtains the heart rate based on the periodicity of the electrocardiographic waveform of the heart or the pulse wave waveform of body movement removal. It is characterized by the following.
- a sixty-fourth invention relates to an exercise intensity detecting device, wherein the heart rate detecting means performs frequency analysis on the electrocardiographic waveform of the heart or the pulse wave waveform from which the body movement has been removed, and The heart rate is determined based on the heart rate.
- a sixty-fifth invention relates to an exercise intensity detection device, wherein the ejection period detection means detects each peak of the body motion removal pulse wave waveform, and detects the first or second from the maximum peak.
- the ejection period is detected by specifying a negative peak and a minimum peak that appear second.
- a sixth invention relates to an exercise intensity detecting device, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body, and a body for detecting a body movement waveform indicating the body movement of the living body Motion detection means, a body motion component that generates a body motion component in the pulse wave waveform based on the body motion waveform, and removes the body motion component from the pulse wave waveform to generate a body motion removal pulse wave waveform Means, wavelet transform means for performing wavelet transform on the body motion-removed pulse wave waveform to generate body motion-removed pulse wave analysis data in which body motion has been removed for each frequency domain; and Heart rate detection means for detecting a heart rate based on data; ejection duration detection means for detecting an ejection duration of the heart based on the body motion removal pulse wave analysis data; and ejection duration of the heart Based on the pulse wave waveform and the heart rate And a cardiac output calculating means for calculating a cardiac output.
- a sixth aspect of the present invention relates to an exercise intensity detecting apparatus, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body, and a body for detecting a body movement waveform indicating the body movement of the living body Motion detection means, generating a body motion component in the pulse wave waveform based on the body motion waveform, A body motion removing unit that removes the body motion component from the pulse wave waveform to generate a body motion-removed pulse waveform, and performs a wavelet transform on the body motion-removed pulse waveform to perform body motion for each frequency region.
- a body movement removing means for generating the removed body movement removed pulse wave analysis data, and a correction pulse for correcting the body movement removed pulse wave analysis data to normalize the power per frequency based on each corresponding frequency.
- Frequency correction means for generating wave data; heart rate detection means for detecting a heart rate based on the corrected pulse wave data; and heart ejection period detected based on the corrected pulse wave data.
- Ejection duration detecting means, and a cardiac output calculating means for calculating a cardiac output based on the pulse wave waveform and the heart rate during the ejection period of the heart.
- a sixth invention relates to an exercise intensity detecting apparatus, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body; and performing a wavelet transform on the pulse wave waveform to perform each frequency domain.
- First wavelet transform means for generating pulse wave analysis data every time
- body motion detecting means for detecting a body motion waveform indicating the body motion of the living body, and performing a wavelet transform on the body motion waveform for each frequency.
- Second wavelet transform means for generating body motion analysis data for each region; and subtracting the body motion analysis data from the pulse wave analysis data to generate body motion removed pulse wave analysis data from which body motion has been removed.
- Body movement removing means for detecting a heart rate based on the body movement removed pulse wave analysis data, and detecting a cardiac ejection period based on the body movement removed pulse wave analysis data Before and after A cardiac output calculating means for calculating a cardiac output based on a result obtained by adding the body motion removal pulse wave analysis data in each frequency region during a cardiac ejection period and the heart rate.
- a sixty-ninth invention relates to an exercise intensity detecting apparatus, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body; First wavelet conversion means for generating pulse wave analysis data for each pulse, and correction of pulse wave analysis data based on each corresponding frequency so that power per frequency is normalized.
- a first frequency correction means for generating data; a body movement detecting means for detecting a body movement waveform indicating the body movement of the living body; and a body movement for each frequency domain by performing a wavelet transform on the body movement waveform.
- Second wavelet transformation means for generating analysis data and body motion analysis data based on each corresponding frequency Second frequency correction means for performing correction so as to normalize power per frequency to generate corrected body motion analysis data, and subtracting the corrected body motion analysis data from the corrected pulse wave analysis data
- Body movement removing means for generating body movement removed pulse wave analysis data from which movement has been removed
- heart rate detecting means for detecting a heart rate based on the body movement removed pulse wave analysis data
- body movement removed pulse wave analysis An ejection period detecting means for detecting an ejection period of the heart based on the data, and a result obtained by adding the body motion removal pulse wave analysis data of each frequency region in the ejection period of the heart and the heart rate.
- a cardiac output calculating means for calculating a cardiac output based on the output.
- a 70th invention relates to an exercise intensity detecting apparatus, wherein the first double transform unit and the second wavelet transform unit perform wavelet transform in synchronization with each other. .
- a seventy-first invention relates to an exercise intensity detection device, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body; and a pulse wave waveform detected by the pulse wave detecting means.
- a wavelet transform means for performing a wavelet transform to generate pulse wave analysis data for each frequency domain; and removing a frequency component corresponding to a predetermined body motion from the pulse wave analysis data, Body movement removing means for generating motion removal pulse wave analysis data; heart rate detection means for detecting a heart rate based on the body motion removal pulse wave analysis data; and An ejection period detection means for detecting an ejection period of the heart; a cardiac output based on the heart rate and a result obtained by adding the body motion removal pulse wave analysis data of each frequency region in the ejection period of the heart. Heart rate to calculate Characterized in that a quantity calculating means.
- a seventy-second invention relates to an exercise intensity detection device, comprising: a pulse wave detection means for detecting a pulse wave waveform from a detection part of a living body; and a pulse wave waveform detected by the pulse wave detection means.
- a wavelet transform unit for performing a wavelet transform to generate pulse wave analysis data for each frequency domain; and removing a frequency component corresponding to a predetermined body motion from the pulse wave analysis data to obtain a body motion.
- the body movement removing means for generating the removed pulse wave analysis data, and correcting the body movement removed pulse wave analysis data so that the power per frequency is normalized based on each corresponding frequency, and converting the corrected pulse wave analysis data Generating a frequency correction means, and a heart rate for detecting a heart rate based on the corrected pulse wave analysis data.
- Number detection means, Ejection period detection means for detecting an ejection period of the heart based on the corrected pulse wave analysis data, and The corrected pulse wave analysis data of each frequency region in the ejection period of the heart are added.
- a cardiac output calculating means for calculating a cardiac output based on the result and the heart rate.
- a seventy-third invention relates to an exercise intensity detecting device, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body, and the pulse wave waveform detected by the pulse wave detecting means.
- a wavelet transform unit for performing a wavelet transform to generate pulse wave analysis data for each frequency domain; and removing a frequency component corresponding to a predetermined body motion from the pulse wave analysis data, thereby Body movement removing means for generating removed pulse wave analysis data; inverse wavelet transform means for performing inverse wavelet transform on the body movement removed analysis pulse wave data to generate a body removal pulse wave waveform;
- Heart rate detection means for detecting a heart rate based on a pulse wave waveform; ejection duration detection means for detecting an ejection duration of a heart based on the body motion removal pulse wave waveform; and ejection of the heart Before the period Based the body movement eliminated pulse wave waveform to the heart rate, characterized in that a cardiac output calculating means for calculating cardiac output.
- a seventy-fourth invention relates to an exercise intensity detection device, wherein the cardiac output calculation means integrates a body movement removal pulse wave waveform during the ejection period of the heart, thereby corresponding to the period. It is characterized in that the area of the body motion removal pulse wave waveform is calculated, and the cardiac output is calculated based on the calculated area.
- a seventy-fifth invention relates to an exercise intensity detection device, wherein the cardiac output calculating means corresponds to the period based on each peak value of the body motion removal pulse wave waveform during the ejection period of the heart. Calculating the area of the body motion removal pulse wave waveform to be calculated, and calculating the cardiac output based on the area.
- a 76th invention relates to an exercise intensity detecting device, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body, a heart rate detecting means for detecting a heart rate of the living body, Ejection period detection means for detecting the ejection period of the heart based on the pulse wave waveform, and storage storing in advance the stroke output corresponding to the ejection period of the heart and the heart rate of the living body.
- a storage unit based on an ejection period of the heart detected by the ejection period detection unit and a heart rate detected by the heart rate detection unit.
- a cardiac output calculating means for calculating the cardiac output by multiplying the cardiac output by the cardiac output and the heart rate.
- a 77th invention relates to an exercise intensity detecting device, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body, a heart rate detecting means for detecting a heart rate of the living body, An ejection period detecting means for detecting an ejection period of the heart based on the pulse wave waveform; and the pulse wave corresponding to the ejection period based on each peak value of the pulse waveform in the ejection period of the heart.
- a cardiac output calculating means for calculating an area of the waveform and calculating the cardiac output based on the area.
- the 78th invention relates to an exercise intensity detecting device, and corrects a ratio between a reference cardiac output measured by a reference device and the cardiac output measured by the cardiac output calculating means.
- a storage unit for storing the coefficient as a coefficient; multiplying the correction coefficient read from the storage unit by the cardiac output calculated by the cardiac output calculation unit; and outputting the multiplication result as a cardiac output.
- a seventy-ninth invention is a cardiac function diagnostic device provided with a cardiac output detection device, characterized by comprising a notifying means for notifying the cardiac output detected by the cardiac output detection device.
- An 80th invention is a cardiac function diagnostic apparatus including a cardiac output detection device, wherein the cardiac output detected by the cardiac output detection device is compared with each threshold value, and an evaluation index is set. It is characterized by comprising evaluation means for generating, and a notification means for notifying the evaluation index generated by the evaluation means.
- An eighteenth invention is a cardiac function diagnostic device provided with a cardiac output detection device, wherein the evaluation means changes each of the thresholds according to the heart rate detected by the heart rate detection means.
- a change unit is provided.
- An eighty-second invention is a cardiac function diagnostic apparatus provided with a cardiac output detection device, wherein the evaluation means comprises: an input unit for inputting a parameter for calculating a body surface area of a subject; It is characterized by comprising: a calculation unit that calculates a body surface area based on the parameters; and a change unit that changes each of the thresholds based on the calculated body surface area.
- the 83rd invention is a cardiac output detection method, wherein a pulse wave waveform is obtained from a detection part of a living body.
- a first step of detecting, a second step of detecting a body motion waveform indicating the body motion of the living body, and a third step of generating a body motion component in the pulse wave waveform based on the body motion waveform A fourth step of removing the body motion component from the pulse wave waveform to generate a body motion-removed pulse wave waveform; a fifth step of detecting the heart rate of the living body;
- An eighty-fourth invention is a cardiac output detection method, wherein, instead of the seventh step, a heart rate is calculated based on the body motion removal pulse wave waveform and the heart rate during the ejection period of the heart.
- the method further comprises the step of calculating the output.
- An eighty-fifth invention is a cardiac output detection method, comprising: a first step of detecting a pulse wave waveform from a detection part of a living body; and a second step of detecting a body movement waveform indicating the body movement of the living body.
- a fifth step of performing a wavelet transform on the body motion-removed pulse wave waveform to generate body motion-removed pulse wave analysis data in which body motion has been removed for each frequency domain
- An eighth step for calculating cardiac output is provided.
- An eighty-sixth invention is a cardiac output detection method, comprising: a first step of detecting a pulse wave waveform from a detection part of a living body; and a second step of detecting a body movement waveform indicating the body movement of the living body.
- a fourth step of performing a wavelet transform on the body motion-removed pulse waveform to generate body motion-removed pulse wave analysis data in which a body motion has been removed for each frequency domain A sixth step of correcting the body motion removal pulse wave analysis data to normalize the power per frequency based on each corresponding frequency to generate corrected pulse wave data; and A seventh step of detecting a heart rate based on the Detecting a cardiac ejection period based on the corrected pulse wave data; and calculating a cardiac output based on the body motion removal pulse wave waveform and the heart rate during the cardiac ejection period.
- the 87th invention is a cardiac output detection method, comprising: a first step of detecting a pulse wave waveform from a detection part of a living body; and performing a wavelet transform on the pulse wave waveform to perform a frequency conversion for each frequency region.
- a second step of generating pulse wave analysis data a third step of detecting a body motion waveform indicating the body motion of the living body, and performing a wavelet transform on the body motion waveform for each frequency region.
- An eighth step of calculating a cardiac output based on the result of adding the body motion removal pulse wave analysis data and the heart rate is provided.
- An eighty-eighth invention is a cardiac output detection method, comprising: a first step of detecting a pulse wave waveform from a detection portion of a living body; The second step is to generate pulse wave analysis data, and the corrected pulse wave analysis data is generated by correcting the pulse wave analysis data to normalize the power per frequency based on each corresponding frequency.
- a step of generating the corrected body motion analysis data by performing a correction on the body motion analysis data to normalize the power per frequency based on each corresponding frequency; and Wave analysis data A seventh step of subtracting the body motion analysis data to generate body motion-removed pulse wave analysis data from which the body motion has been removed, and a step of detecting a heart rate based on the body motion-removed pulse wave analysis data Eighth step, a ninth step of detecting a cardiac ejection period based on the body motion removal pulse wave analysis data, and the body motion removal pulse wave of each frequency region during the heart ejection period.
- An 89th invention is a cardiac output detection method, comprising: a first step of detecting a pulse wave waveform from a detection part of a living body; and performing a wavelet transform on the pulse wave waveform, and A second step of generating pulse wave analysis data, and removing a frequency component corresponding to a predetermined body motion from the pulse wave analysis data to generate a body motion removal pulse wave analysis data.
- a 90th invention is a cardiac output detection method, comprising: a first step of detecting a pulse wave waveform from a detection part of a living body; and performing a wavelet transform on the pulse wave waveform to obtain a frequency region.
- a ninth invention is a cardiac output detection method, comprising: a first step of detecting a pulse wave waveform from a detection part of a living body; and performing a wavelet transform on the pulse wave waveform, for each frequency region.
- Step 3 a fourth step of performing an inverse ⁇ - ⁇ ⁇ transform on the body movement removal analysis pulse wave data to generate a body movement removal pulse wave waveform, and calculating a heart rate based on the body movement removal pulse wave waveform.
- a ninth invention is a cardiac output detection method, comprising: a first step of detecting a pulse wave waveform from a detection site of a living body; a second step of detecting a heart rate of the living body; A third step of detecting an ejection period of the heart based on the pulse wave waveform, and a fourth step of previously storing a stroke output corresponding to the ejection period of the heart and the heart rate of the living body. And a fifth step of reading the stroke output from the storage content stored in the fourth step based on the detected ejection period and the detected heart rate. A sixth step of calculating the cardiac output by multiplying the single stroke output by the heart rate.
- a ninth invention is a cardiac output detection method, comprising: a first step of detecting a pulse wave waveform from a detection site of a living body; a second step of detecting a heart rate of the living body; A third step of detecting an ejection period of the heart based on the pulse wave waveform, and a step of detecting the ejection period of the heart based on each peak value of the pulse wave waveform during the ejection period of the heart. A fourth step of calculating an area; and a fifth step of calculating the cardiac output based on a calculation result of the fourth step.
- a ninety-fourth invention is a cardiac function measurement method for measuring cardiac function based on the heart rate detected by the cardiac output detection method, comprising: It is characterized by comprising a step of generating an index and a step of notifying the evaluation index.
- a ninety-fifth invention relates to a stroke volume detection device, which detects a pulse wave waveform from a detection portion of a living body, and detects a body movement waveform indicating the body movement of the living body.
- a body movement detecting unit a body movement that generates a body movement component in the pulse wave waveform based on the body movement waveform, and that removes the body movement component from the pulse wave waveform to generate a body movement removed pulse wave waveform.
- Removing means Removing means, ejection period detecting means for detecting an ejection period of the heart based on the body movement removed pulse wave waveform, and heartbeat period calculation for calculating a heartbeat period based on the body movement removed pulse wave waveform Means, and a stroke volume calculating means for calculating a stroke volume based on the ejection period of the heart and the heartbeat period.
- the ninth invention relates to a stroke volume detection device, and a detection part of a living body.
- Pulse wave detection means for detecting a pulse wave waveform from the body
- body movement detection means for detecting a body movement waveform indicating the body movement of the living body, and generating a body movement component in the pulse wave waveform based on the body movement waveform
- a body movement removing unit configured to remove the body movement component from the pulse wave waveform to generate a body movement removed pulse wave waveform
- a drive unit that detects a cardiac ejection period based on the body movement removed pulse wave waveform.
- An output period detecting unit, and a stroke volume calculating unit that calculates a stroke volume based on the body movement-removed pulse wave waveform during the ejection period of the heart.
- a ninety-seventh invention relates to a stroke volume detection device, and a determination means for determining the presence or absence of body movement of the living body based on a body movement waveform detected by the body movement detecting means.
- the body movement removing means stops the body movement removing operation, and replaces the body movement removing pulse wave waveform with the pulse wave waveform. It is characterized by outputting.
- a ninth invention relates to a stroke volume detection device, wherein the ejection period detection means detects each peak of the body movement-removed pulse wave waveform, and detects the first or the largest from the maximum peak.
- the ejection period is detected by specifying a second negative peak and a minimum peak.
- a ninth invention relates to a stroke volume detection device, which detects a pulse wave waveform from a detection portion of a living body, and detects a body movement waveform indicating the body movement of the living body.
- a body movement detecting unit a body movement that generates a body movement component in the pulse wave waveform based on the body movement waveform, and that removes the body movement component from the pulse wave waveform to generate a body movement removed pulse wave waveform.
- Removing means a wavelet transform means for performing a wavelet transform on the body motion removal pulse wave waveform to generate body motion removal pulse wave analysis data in which body motion has been removed for each frequency region;
- An ejection period detecting means for detecting an ejection period of the heart based on the pulse wave analysis data, and calculating a stroke volume based on the body motion removal pulse wave waveform during the ejection period of the heart.
- a circuit for calculating a stroke volume.
- the 100th invention relates to a stroke volume detection device, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detecting portion of a living body; and a body movement waveform indicating the body movement of the living body.
- a body movement detecting means for detecting, a body movement component in the pulse wave waveform based on the body movement waveform, and a body movement removed pulse wave waveform by removing the body movement component from the pulse wave waveform.
- Body motion elimination means that generates body motion elimination pulse wave analysis data from which body motion has been eliminated for each area, and normalizes the power per frequency in the body motion elimination pulse wave analysis data based on each corresponding frequency
- Frequency correction means for performing correction so as to generate corrected pulse wave data
- ejection period detection means for detecting an ejection period of the heart based on the corrected pulse wave data, and ejection period of the heart
- a stroke volume calculating means for calculating a stroke volume based on the body motion-removed pulse wave waveform in (1).
- the tenth invention relates to a stroke volume detection device, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detecting portion of a living body; and performing a wavelet conversion on the pulse wave waveform.
- First wavelet transform means for generating pulse wave analysis data for each frequency domain
- body motion detecting means for detecting a body motion waveform indicating the body motion of the living body
- performing a wavelet transform on the body motion waveform To generate a body motion analysis data for each frequency domain
- An ejection period detecting means for detecting an ejection period of the heart based on the wave analysis data, and a pulse wave analysis data for each of the frequency regions during the ejection period of the heart.
- a stroke volume calculating means for calculating a stroke volume.
- the tenth invention relates to a stroke volume detection device, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detecting portion of a living body; and performing a wavelet transform on the pulse wave waveform.
- a first wavelet transform means for generating pulse wave analysis data for each frequency domain, and a correction pulse for correcting the pulse wave analysis data to normalize the power per frequency based on each corresponding frequency.
- First frequency correction means for generating wave analysis data
- body movement detection means for detecting a body movement waveform indicating the body movement of the living body, and performing a wavelet transform on the body movement waveform to obtain a body for each frequency region.
- the 103rd invention relates to a single stroke volume detection device, wherein the first wavelet conversion means and the second wavelet conversion means perform a wavelet conversion in synchronization with each other. It is characterized by the following.
- the 104th invention relates to a stroke volume detection device, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detecting portion of a living body, and the pulse detected by the pulse wave detecting means.
- a wavelet transform means for performing a wavelet transform on the wave waveform to generate pulse wave analysis data for each frequency domain; and a predetermined body motion corresponding to the pulse wave analysis data in the pulse wave analysis data.
- Body movement removing means for removing the frequency component to generate body movement removed pulse wave analysis data
- ejection period detection for detecting a cardiac ejection period based on the body movement removed pulse wave analysis data Means
- stroke volume calculating means for calculating a stroke volume based on a result of adding the body motion removal pulse wave analysis data of each frequency region during the ejection period of the heart. It is characterized by.
- a first aspect of the present invention relates to a stroke volume detecting device, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detecting part of a living body, and the pulse detected by the pulse wave detecting means.
- a wavelet transform means for performing a wavelet transform on the wave waveform to generate pulse wave analysis data for each frequency domain; and a frequency component corresponding to a predetermined body motion in the pulse wave analysis data.
- Body motion removal means for generating the body motion removal pulse wave analysis data, and correcting the power per frequency to the body removal pulse wave analysis data based on each corresponding frequency.
- Frequency correction means for generating correction pulse wave analysis data by applying the correction pulse wave analysis data, ejection period detection means for detecting an ejection period of the heart based on the correction pulse wave analysis data, and each frequency region in the ejection period of the heart. Said corrected pulse wave Based on the result of adding the analysis data, characterized by comprising a stroke volume calculation means for calculating the stroke volume.
- the 106th invention relates to a stroke volume detection device, wherein a pulse wave detecting means for detecting a pulse wave waveform from a detecting portion of a living body, and the pulse detected by the pulse wave detecting means.
- Wavelet transform is performed on the wave waveform, and the pulse wave analysis data is A wavelet transforming means for generating evening; a body motion removing means for removing a frequency component corresponding to a predetermined body motion from the pulse wave analysis data to generate body motion removed pulse wave analysis data;
- Inverse wavelet transform means for performing an inverse wavelet transform on the body motion removal analysis pulse wave data to generate a body motion removal pulse wave waveform, and detecting a cardiac ejection period based on the body motion removal pulse wave waveform Ejection stroke detecting means, and stroke volume calculating means for calculating stroke volume on the basis of the body movement-removed pulse waveform during the ejection period of the heart.
- the 107th invention relates to a stroke volume detection device, wherein the stroke volume calculation means integrates a pulse wave waveform from the body motion removal during the ejection period of the heart. An area of the body motion removal pulse wave waveform corresponding to the period is calculated, and the stroke volume is calculated based on the area.
- the 108th invention relates to a stroke volume detection device, wherein the stroke volume calculation means is based on each peak value of the body motion removal pulse wave waveform during the ejection period of the heart. Then, the area of the body motion removal pulse wave waveform corresponding to the period is calculated, and the stroke volume is calculated based on the area.
- the first invention relates to a stroke volume detection device, comprising: a pulse wave detecting means for detecting a pulse wave waveform from a detecting portion of a living body; and a heart rate detecting device for detecting a heart rate of the living body.
- Means an ejection period detection means for detecting an ejection period of the heart based on the pulse wave waveform, and a stroke output corresponding to the ejection period of the heart and the heart rate of the living body.
- a storage unit that stores the first heart rate from the storage unit based on the ejection period of the heart detected by the ejection period detection unit and the heart rate detected by the heart rate detection unit.
- a stroke volume calculating means for calculating a stroke volume by reading the stroke volume;
- the eleventh invention is a pulse wave detecting means for detecting a pulse wave waveform from a detection part of a living body; a heart rate detecting means for detecting a heart rate of the living body; An ejection period detecting means for detecting an ejection period; and calculating, based on each peak value of the pulse wave waveform during the ejection period of the heart, an area of the pulse wave waveform corresponding to the period, based on the area. And a stroke volume calculating means for calculating the stroke volume.
- the eleventh invention relates to a stroke volume detection device, wherein the reference stroke volume measured by the reference device and the stroke volume calculation means are measured.
- Correction coefficient calculating means for calculating a ratio to the stroke volume as a correction coefficient; storage means for storing the correction coefficient in association with the heart rate of the living body; A correction coefficient is read out from the storage means, the read out correction coefficient is multiplied by the stroke volume calculated by the stroke volume calculation means, and the multiplication result is output as a stroke volume. And a multiplying means for performing the operation.
- the eleventh invention is a cardiac function diagnostic apparatus provided with a stroke volume detection device, and a notification means for reporting a stroke volume detected by the stroke volume detection device. It is characterized by having.
- a thirteenth aspect of the present invention is a cardiac function diagnostic apparatus provided with a stroke volume detector, wherein the stroke volume detected by the stroke volume detector is compared with each threshold value. And evaluation means for generating an evaluation index, and notification means for notifying the evaluation index generated by the evaluation means.
- a fourteenth aspect of the present invention is a cardiac function diagnostic apparatus provided with a stroke volume detection device, wherein the change rate calculating means for calculating a rate of change of the stroke volume, An evaluation means for comparing the rate of change of the amount with each threshold value to generate an evaluation index, and a notifying means for notifying the evaluation index generated by the evaluation means are provided.
- a fifteenth aspect of the present invention is a cardiac function diagnostic apparatus including a stroke volume detection device, wherein the evaluation means includes a changing unit that changes each of the thresholds according to the heart rate of the living body. It is characterized by.
- An eleventh aspect of the present invention is a cardiac function diagnostic apparatus provided with a stroke volume detection device, wherein the evaluation means includes an input unit for inputting a parameter for calculating a body surface area of the subject. A calculating unit for calculating a body surface area based on the input parameters; and a changing unit for changing each of the thresholds based on the calculated body surface area.
- the eleventh invention relates to a stroke volume detection method, comprising: a first step of detecting a pulse wave waveform from a detection portion of a living body; and detecting a body movement waveform indicating the body movement of the living body.
- a second step of performing, based on the body motion waveform, A third step of generating, a fourth step of removing the body motion component from the pulse wave waveform to generate a body motion removal pulse wave waveform, and a drive of the heart based on the body motion removal pulse wave waveform.
- the first invention relates to a stroke volume detection method, comprising: a first step of detecting a pulse wave waveform from a detection part of a living body; and detecting a body movement waveform indicating the body movement of the living body.
- the first invention relates to a stroke volume detection method, comprising: a first step of detecting a pulse wave waveform from a detection part of a living body; and detecting a body movement waveform indicating the body movement of the living body.
- the 120th invention relates to a stroke volume detection method, comprising: a first step of detecting a pulse wave waveform from a detection part of a living body; and detecting a body movement waveform indicating the body movement of the living body. A second step of generating a body motion component in the pulse wave waveform based on the body motion waveform; and a body motion removal pulse wave by removing the body motion component from the pulse wave waveform.
- An eighth step is provided.
- the twenty-first invention relates to a stroke volume detection method, comprising: a first step of detecting a pulse waveform from a detection portion of a living body; A second step of generating pulse wave analysis data for each region, a third step of detecting a body motion waveform indicating the body motion of the living body, and applying a wavelet transform to the body motion waveform to each frequency region A fourth step of generating a body motion analysis data every time; and a fifth step of subtracting the body motion analysis data from the pulse wave analysis data to generate body motion removal pulse wave analysis data from which the body motion has been removed.
- the first and second inventions relate to a stroke volume detection method, comprising: a first step of detecting a pulse waveform from a detection part of a living body; The second step of generating pulse wave analysis data for each area, and correcting the pulse wave analysis data based on the corresponding frequency so that the power per frequency is normalized.
- a fourth step of detecting a body motion waveform indicating the body motion of the living body, and performing a wavelet transform on the body motion waveform to generate body motion analysis data for each frequency domain A fifth step of performing correction to normalize the power per frequency in the body motion analysis data based on each corresponding frequency to generate corrected body motion analysis data; and Corrected pulse wave analysis data
- An eighth step of detecting an ejection period, and a ninth step of calculating a stroke volume based on a result obtained by adding the body motion removal pulse wave analysis data in each frequency region during the ejection period of the heart And the following steps.
- the 123rd invention relates to a stroke volume detection method, comprising: a first step of detecting a pulse waveform from a detection portion of a living body; and performing a wavelet transform on the pulse waveform, A second step of generating pulse wave analysis data for each frequency domain; and removing a frequency component corresponding to a predetermined body motion from the pulse wave analysis data to generate body motion removed pulse wave analysis data. A fourth step of detecting the ejection period of the heart based on the pulse wave analysis data for removing the motion, and removing the motion of each frequency region during the ejection period of the heart. A fifth step of calculating a stroke volume based on a result of adding the pulse wave analysis data.
- the first invention relates to a stroke volume detection method, comprising a first step of detecting a pulse waveform from a detection part of a living body, and performing a wavelet transform on the pulse waveform, A second step of generating a pulse wave analysis data for each frequency domain; and removing a frequency component corresponding to a predetermined body motion from the pulse wave analysis data to obtain a body motion-removed pulse wave analysis data. A third step of generating the corrected pulse wave analysis data by correcting the body motion removal pulse wave analysis data to normalize the power per frequency based on each corresponding frequency. A fifth step of detecting a cardiac ejection period based on the corrected pulse wave analysis data, and adding the corrected pulse wave analysis data of each frequency region in the cardiac ejection period. Based on the result, stroke volume Characterized by comprising a sixth step of calculating.
- the first invention relates to a stroke volume detection method, comprising: a first step of detecting a pulse wave waveform from a detection portion of a living body; and performing a wavelet transform on the pulse wave waveform.
- a sixth step of calculating a stroke volume based on the pulse waveform of the body motion removal during the ejection period of the heart And characterized in that:
- the 126th invention relates to a stroke volume detection method, comprising: a first step of detecting a pulse wave waveform from a detection portion of a living body; and a second step of detecting a heart rate of the living body. And a third step of detecting an ejection period of the heart based on the pulse wave waveform. A stroke output corresponding to the ejection period of the heart and the heart rate of the living body is determined in advance. Reading the stroke volume from the stored content stored in the fourth step based on a fourth step of storing and a detected ejection period of the heart and a detected heart rate. And a fifth step of calculating a stroke volume.
- the 127th invention relates to a stroke volume detection method, comprising: a first step of detecting a pulse waveform from a detection portion of a living body; and a second step of detecting a heart rate of the living body.
- the invention of the first aspect is a cardiac function measuring method for measuring cardiac function based on the stroke volume detected by a stroke volume method, wherein the stroke volume is compared with each threshold value. Then, the method includes a step of generating an evaluation index, and a step of notifying the evaluation index.
- the 129th invention is a cardiac function measuring method for measuring cardiac function based on the stroke volume detected by a stroke volume method, wherein the rate of change in stroke volume is , Calculating the change rate of the stroke volume with each threshold value to generate an evaluation index, and notifying the evaluation index.
- FIG. 1 is a functional block diagram showing the functional configuration of the pulse wave diagnostic device shown in Chapter 1.
- FIG. 2 is a perspective view showing an external configuration of the pulse wave diagnostic apparatus according to the first embodiment of the same chapter.
- FIG. 3 is a circuit diagram of a pulse wave detection sensor unit 130 according to the same embodiment in the same chapter.
- FIG. 4 is a block diagram showing an electrical configuration of the pulse wave diagnostic apparatus according to the embodiment of the same chapter.
- FIG. 4 is a block diagram showing an electrical configuration of the pulse wave diagnostic apparatus according to the embodiment of the same chapter.
- FIG. 5 is a block diagram of the wavelet transform unit 10 according to the same embodiment in the same chapter.
- FIG. 6 is a block diagram of the waveform shaping unit 100 according to the same embodiment in the same chapter.
- FIG. 7 is a timing chart for explaining the operation of the wavelet transform unit 10 according to the same embodiment in the same chapter.
- FIG. 8 shows pulse wave analysis data M generated in one heartbeat in the same embodiment of the same chapter.
- FIG. 9 is a block diagram of the pulse image data generation unit 12 according to the same embodiment in the same chapter.
- FIG. 10 is a diagram showing the average value of the pulse wave correction data MKD ′ stored in the memory 124 according to the same embodiment of the same chapter.
- FIG. 11 is a diagram showing a relationship between a typical waveform of a chord vein and an average value in the same embodiment of the same chapter.
- FIG. 12 is a diagram showing a relationship between a representative waveform of a normal pulse and an average value according to the embodiment of the same chapter.
- FIG. 13 is a diagram showing a relationship between a representative waveform of a smooth pulse and an average value according to the embodiment of the same chapter.
- FIG. 14 is a block diagram showing another configuration example of the pulse image data generation section 12 according to the same embodiment in the same chapter.
- FIG. 15 is a block diagram of a pulse wave diagnostic apparatus according to the second embodiment of the same chapter.
- FIG. 16 is a timing chart for explaining the operation of the pulse wave diagnostic apparatus according to the same embodiment in the same chapter.
- FIG. 17 is a diagram showing pulse wave correction data MKD ′ during a period Tc in the same embodiment of the same chapter.
- FIG. 18 is a diagram showing body motion correction data TKD ′ in a period Tc in the same embodiment of the same chapter.
- FIG. 19 is a diagram showing pulse wave correction data MK D ′ ′ from which a body motion component has been removed in the same embodiment of the same chapter.
- FIG. 20 is a block diagram of a pulse wave diagnostic device according to the third embodiment of the same chapter.
- FIG. 21 is a block diagram of a pulse wave diagnostic device according to the fourth embodiment of the same chapter.
- FIG. 22 is a detailed block diagram of the body movement separating section 19 according to the embodiment of the same chapter.
- FIG. 23 is a diagram showing an example of a body motion separated pulse wave data TBD according to the embodiment of the same chapter.
- FIG. 24 is a block diagram of a pulse wave diagnostic apparatus according to the fifth embodiment of the same chapter.
- FIG. 25 is a diagram showing an example of a pulse wave waveform TMH of body motion separation for one beat according to the embodiment of the same chapter.
- FIG. 26 is a block diagram illustrating a configuration of the pulse image determination unit 22 according to the embodiment of the same chapter.
- FIG. 27 is a diagram showing an example of a pulse waveform according to the same embodiment in the same chapter.
- FIG. 28 is a diagram showing the contents of peak information according to the same embodiment in the same chapter.
- FIG. 29 is a flowchart for explaining the operation of the same embodiment in the same chapter.
- FIG. 30 is a block diagram showing an example in a case where the wavelet transform is configured by a filter bank in a modification of the same chapter.
- FIG. 31 is a block diagram showing an example in which the inverse wavelet transform is configured by a filter bank in the modification of the same chapter.
- FIG. 32 is a diagram showing an example of a transmitted light type pulse wave sensor according to a modification of the same chapter.
- FIG. 33 is a perspective view showing an external configuration of a pulse wave diagnostic apparatus using a pressure sensor in a modified example of the same chapter.
- FIG. 34 is a diagram showing an example in which the photoelectric pulse wave sensor is applied to glasses in a modified example of the same chapter.
- FIG. 35 is a diagram showing an example in which a photoelectric pulse wave sensor is applied to a necklace in a modified example of the same chapter.
- FIG. 36 is a diagram showing an example in which a piezoelectric microphone sensor is applied to a card in a modified example of the same chapter.
- FIG. 37 is a diagram showing an example in which the photoelectric pulse wave sensor is applied to a pedometer in a modification of the same chapter.
- Fig. 38 shows the configuration of the first wavelet converter 1OA according to the modification of the same chapter.
- FIG. 39 shows the heartbeats on the electrocardiogram and the RR intervals obtained from the waveforms of these heartbeats in the modified example of the same chapter.
- FIG. 40 is a diagram showing a relationship between an electrocardiogram and blood pressure in a modified example of the same chapter.
- (a) is a diagram showing a variation waveform of the RR interval of the measured pulse wave, and a waveform of each variation component when the variation waveform is decomposed into the above three frequency components.
- (B) is the result of the spectrum analysis of the RR interval fluctuation waveform shown in (a).
- FIG. 42 is a block diagram showing a functional configuration of the exercise index measuring device according to the first embodiment in Chapter 2.
- FIG. 43 is a block diagram showing an electrical configuration of the same device in the same chapter.
- FIG. 44 is a diagram showing the experimental results that are the premise of the movement index measurement device in the same chapter.
- FIG. 45 is a diagram for explaining the scoring of the subjective exercise intensity.
- FIG. 46 is a diagram showing an external configuration of the exercise index measuring device in the same chapter.
- Fig. 47 is a diagram showing the configuration of the exercise index measurement device of the same chapter and external devices for exchanging various information.
- FIG. 48 is a flowchart showing basic processing (1) performed by the exercise index measuring device in the same chapter.
- FIG. 49 is a flowchart showing an interrupt processing (1) executed by the exercise index measuring device in the same chapter.
- FIG. 50 is a flowchart showing the basic processing (1) or (3) executed by the exercise index measuring device in the same chapter.
- FIG. 51 is a flowchart showing an interrupt processing (1) executed by the exercise index measuring device in the same chapter.
- Fig. 52 is a flowchart showing the interrupt processing (3) executed by the exercise index measuring device.
- FIG. 53 is a flowchart showing the basic processing (1) or (2) executed by the exercise index measuring device in the same chapter.
- Fig. 54 is a flowchart showing the interrupt processing (1) executed by the exercise index measurement device in the same chapter. It's a trick.
- FIG. 55 is a flowchart showing an interrupt processing (1) executed by the exercise index measuring device in the same chapter.
- FIG. 56 is a diagram showing an example of a display on the display unit in the exercise index measurement device of the same chapter.
- FIG. 57 is a diagram showing an example of display on the display unit in the exercise index measurement device of the same chapter.
- FIG. 58 is a block diagram showing a functional configuration of the exercise index measuring device according to the second embodiment of the same chapter.
- FIG. 59 is a diagram showing the contents of a table in the same embodiment in the same chapter.
- FIG. 60 is a diagram showing the relationship between exercise intensity and respiratory waveform in Chapter 3.
- FIG. 61 is a functional block diagram of the exercise intensity detection device according to the embodiment of the same chapter.
- FIG. 62 is a block diagram showing an electrical configuration of the exercise intensity detection device according to the first embodiment of the same chapter.
- FIG. 63 is a diagram showing a result of performing FFT processing on the pulse wave data MH 'for removing body motion in the same chapter.
- FIG. 64 is an enlarged view of the low frequency region LF in FIG.
- FIG. 65 is a face chart showing one mode of the display unit of the embodiment in the same chapter.
- FIG. 66 is a flowchart showing the operation of the exercise intensity detecting apparatus according to the same embodiment in the same chapter.
- FIG. 67 is a block diagram showing an internal configuration of a respiratory component extraction unit and an evaluation unit according to the second embodiment of the same chapter.
- FIG. 68 is a diagram illustrating an example of a pulse wave analysis data MKD for body motion removal according to the same embodiment of the same chapter.
- FIG. 69 is a diagram showing the maximum energy region of the body motion-removed pulse wave analysis MKD shown in FIG.
- FIG. 70 is a diagram showing an example of respiratory waveform analysis data V KD according to the same embodiment in the same chapter.
- FIG. 71 is a circuit diagram of a zero-cross comparator according to the same embodiment in the same chapter.
- FIG. 72 is a circuit diagram of a duty ratio detection unit according to the same embodiment in the same chapter.
- FIG. 73 is a timing chart of the duty ratio detection unit according to the same embodiment in the same chapter.
- FIG. 74 is a flowchart showing the operation of the exercise intensity detecting device according to the same embodiment in the same chapter.
- FIG. 75 is a block diagram showing an electrical configuration of the exercise intensity detection device according to the third embodiment of the same chapter.
- FIG. 76 is a flowchart showing the operation of the exercise intensity detecting apparatus according to the same embodiment in the same chapter.
- FIG. 77 is a diagram showing an example of a relationship between the pulse wave analysis data MFD, the body motion analysis data TFD, and the body motion removal pulse wave analysis data MKD according to the same embodiment of the same chapter.
- FIG. 78 is a block diagram showing an electrical configuration of an exercise intensity detection device according to the fourth embodiment of the same chapter.
- FIG. 79 is a diagram illustrating an example of a relationship between the pulse wave analysis data MFD and the cutoff frequency fc according to the same embodiment in the same chapter.
- FIG. 80 is a diagram showing an example of a pulse wave component removal analysis MD ′ according to the same embodiment of the same chapter.
- FIG. 81 is a block diagram showing a detailed configuration of a respiratory component extraction unit 13 ′ according to the same embodiment in the same chapter.
- FIG. 82 is a diagram showing the result of actually measuring the relationship between the running pitch and the respiratory rate in the same embodiment of the same chapter.
- FIG. 83 is a graph showing the relationship between the fundamental frequency Ft1 of the body motion component and the fundamental frequency Fvl of the respiratory component in the same embodiment of the same chapter.
- FIG. 84 is a diagram showing the relationship between the respiratory rate and the pulse rate in the same chapter.
- Fig. 85 is a diagram showing the change in the amount of single applause caused by a change in posture in a heart transplant recipient and a healthy subject in Chapter 4.
- Figure 86 is a diagram illustrating the systolic area method of the same chapter.
- FIG. 3 is a functional block diagram showing
- Figure 88 shows the relationship between the ECG waveform, the aortic blood pressure waveform, and the peripheral pulse waveform in the same chapter.
- FIG. 89 is a block diagram showing an electrical configuration of the cardiac function diagnostic device according to the first embodiment of the same chapter.
- FIG. 90 is a block diagram showing an electrical configuration of a cardiac function diagnostic device according to the second embodiment of the same chapter.
- FIG. 91 shows pulse wave analysis data for a partial period of the pulse wave waveform according to the same embodiment of the same chapter.
- FIG. 92 is a diagram for explaining the operation of the stroke volume calculation unit in the same embodiment of the same chapter.
- FIG. 93 is a block diagram of a cardiac function diagnostic apparatus according to the third embodiment of the same chapter.
- FIG. 94 is a block diagram of a cardiac function diagnostic apparatus according to the fourth embodiment of the same chapter.
- FIG. 95 is a detailed block diagram of a body motion removing unit 411 according to the same embodiment in the same chapter.
- FIG. 96 is a diagram showing an example of a body motion removal pulse wave MKD ′ ′ according to the same embodiment of the same chapter.
- FIG. 97 is a block diagram illustrating a configuration of a stroke volume calculation unit according to the fifth embodiment of the same chapter.
- FIG. 98 is a block diagram showing a cardiac output table according to the embodiment in the same chapter.
- FIG. 99 is a block diagram of the stroke volume corrector 424 according to the sixth embodiment of the same chapter.
- FIG. 100 is a block diagram of the evaluator 4 16 according to the seventh embodiment of the same chapter.
- FIG. 101 is a functional block diagram showing a functional configuration of a cardiac function diagnostic device using a stroke volume detection device in the same chapter.
- FIG. 102 is a block diagram showing an electrical configuration of the cardiac function diagnostic apparatus according to the same embodiment in the same chapter.
- FIG. 103 shows an electrical configuration of a cardiac function diagnostic apparatus according to the ninth embodiment of the same chapter. It is a block diagram.
- FIG. 104 is a block diagram of a cardiac function diagnostic apparatus according to the tenth embodiment of the same chapter.
- FIG. 105 is a block diagram of a cardiac function diagnostic apparatus according to the eleventh embodiment of the same chapter.
- FIG. 106 is a diagram showing a waveform of a pulse waveform corresponding to the exercise intensity in the same chapter.
- FIG. 107 is a diagram schematically showing a waveform of a pulse wave waveform according to the exercise intensity in the same chapter.
- FIG. 108 is a block diagram showing a configuration of a stroke volume calculation unit according to the second mode of the twelfth embodiment of the same chapter.
- FIG. 109 is a block diagram showing a configuration of a stroke volume calculation section according to a third mode of the embodiment in the same chapter.
- FIG. 110 is a block diagram of the evaluation unit 16 according to the fourteenth embodiment of the same chapter.
- BEST MODE FOR CARRYING OUT THE INVENTION the best mode for carrying out the present invention will be described with reference to the drawings. This embodiment is divided into the following sections so that those skilled in the art can easily implement the present invention.
- Chapter 1 describes a pulse wave diagnostic device used to identify the type of a person's pulse. In this case, it is necessary to classify the pulse wave waveform into pulse phenomena such as normal pulse, smooth pulse, and chord vein. At this time, the characteristics of the pulse waveform are appropriately extracted by using a wavelet transform or the like. In addition, we will disclose a device that is convenient to carry so that people can know the pulse in daily life, and mention technology that removes the effects of body movement.
- Chapter 2 describes an exercise index measurement device that measures the exercise intensity of training necessary to increase whole-body endurance and announces it as an exercise index.
- the exercise intensity used here is based on the overall consideration of the physical and mental strength of the subject during exercise.
- Chapter 3 describes an exercise intensity detection device that calculates exercise intensity based on a respiratory component extracted from a pulse waveform.
- Chapter 4 describes a device for detecting stroke volume or cardiac output based on a pulse waveform, and a device for diagnosing cardiac function.
- Typical pulse waveforms include pulse veins such as flat veins, smooth veins, and chord veins.
- Ping mai is a pattern of “penetration”, that is, a normal healthy person. Ping mai is characterized by a slow and relaxed rhythm, a constant rhythm and little disturbance.
- the synovial vein is caused by abnormal blood flow conditions, and is caused by swelling, hepato-renal disease, respiratory disease, gastrointestinal disease, inflammatory disease, etc., resulting in extremely smooth and smooth flow of the pulse. You.
- chord vein is caused by tension and aging of the blood vessel wall, and appears in diseases such as hepatobiliary disease, skin disease, hypertension, and painful disease. This is probably because the elasticity of the blood vessel wall decreased, and the effect of the pulsation of the pumped blood became less apparent.
- the characteristic feature of the pulse waveform is that it rapidly rises, does not immediately fall, and remains at a high pressure for a certain period of time. The finger feels like a long pulse that stretches straight and straight.
- pulse diagnosis diagnoses the state of a living body by the subtle tactile sensation that can be felt with the finger of a person, so it is difficult to convey and learn such skills from a person. It takes a long time.
- pulse diagnosis diagnoses the state of a living body by the subtle tactile sensation that can be felt with the finger of a person, so it is difficult to convey and learn such skills from a person. It takes a long time.
- body movement in the living body it is difficult to specify an accurate pulse because the blood flow changes.
- Chapter 1 describes a pulse wave diagnostic device that can objectively identify a pulse even if a body motion occurs.
- FIG. 1 is a functional block diagram of the pulse wave diagnostic device according to the present embodiment.
- f1 is a pulse wave detecting means for detecting a pulse wave waveform.
- the pulse waveform For example, it is detected by pressing the radial artery from above the skin.
- f2 is first wavelet transform means, which performs a wavelet transform on the pulse wave waveform detected by the pulse wave detecting means f1 to generate pulse wave analysis data for each frequency region.
- f3 is first frequency correction means, which performs correction based on each corresponding frequency so that the power density per frequency is constant in the pulse wave analysis data. Generate data. This makes it possible to compare wavelets detected in different frequency / time domains.
- f4 is a body movement detecting means, which detects body movement and outputs a body movement waveform. This makes it possible to detect that a person has moved.
- F5 is a second wavelet transforming means, which performs a wavelet transform on the body motion waveform detected by the body motion detecting means f4 to generate body motion analysis data for each frequency domain .
- f6 is a second frequency correction means, which performs correction based on each corresponding frequency so that the power density per frequency is constant in the body motion analysis data, Generate day and night. Since the body motion correction data thus calculated has been subjected to frequency correction, it can be compared with the pulse wave correction data.
- f7 is a mask means that subtracts the body motion correction data from the pulse wave correction data to generate pulse wave correction data from which the body motion has been removed.
- f8 is pulse data generation means, which generates pulse data indicating pulse by analyzing the pulse wave correction data generated by the mask means f7 for each frequency region. Examples of the type of pulse include a string pulse, a flat pulse, and a smooth pulse.
- body movement detection means f4 When detecting an arrhythmia at rest, such as during sleep, there is no need to detect body movements.Therefore, body movement detection means f4, second wavelet transform means f5, second frequency correction means f6, and mask Means f7 can be omitted. Further, a frequency correcting means may be provided at the subsequent stage of the mask means f7 instead of the first frequency correcting means f3 and the second frequency correcting means, thereby simplifying the configuration. Further, all frequency correction means may be omitted.
- f9 is a notifying means for notifying a pulse based on the pulse data generated by the pulse data generating means f8. This allows a third party, such as a user or a doctor, to recognize the pulse.
- FIG. 2 is a perspective view showing an external configuration of the pulse wave diagnostic device according to the first embodiment.
- a pulse wave diagnostic apparatus 1 of the present example includes an apparatus main body 110 having a wristwatch structure, a cable 120 connected to the apparatus main body 110, and a distal end side of the cable 120.
- a pulse wave detection sensor unit 13 0 is provided, which is roughly composed of: a connector piece 80 at the distal end of the cable 120, and the connector piece 80 is connected to the device body 1 1 It is detachable from the connector 70 that is configured on the 0 o'clock side at 6 o'clock.
- the main body 110 of the wristwatch is provided with a wristband 60 that is wound around the wrist from the 12 o'clock direction and is fixed at the 6 o'clock direction. It is removable.
- the pulse wave detection sensor 130 is attached to the base of the index finger while being shielded from light by the sensor fixing band 140. In this way, when the pulse wave detection sensor unit 130 is attached to the base of the finger, the cable 120 can be shortened, so that the cable 120 is not in the way during the running.
- the pulse wave detection sensor unit 130 is attached to the base of the finger, the pulse rate and the like can be accurately measured even when running outdoors on a cold day.
- the main body 110 of the apparatus is provided with a watch case 200 (body case) made of resin.
- the watch case 200 can be used for traveling or walking.
- a liquid crystal display device 210 with an EL backlight is configured to display pulse wave information such as a pitch at the time and a pulse rate.
- the liquid crystal display device 210 includes a dot display area in addition to the segment display area, and in the dot display area, various kinds of information can be graphically displayed.
- the pulse waveform and the change in the pulse rate are determined based on the pulse wave waveform MH measured by the pulse wave detection sensor unit 130, and the results are displayed on the liquid crystal display device 210.
- Microcontroller that performs various controls and data processing to display A control unit including a computer or the like is configured.
- the control unit also includes a timekeeping circuit, so that the normal time, lap time, split time, and the like can be displayed on the liquid crystal display device 210.
- button switches 111 to 115 for performing external operations such as time adjustment and switching of display modes are configured.
- the pulse wave detection sensor unit 130 includes an LED 32 and a phototransistor 33 as shown in FIG.
- the switch SW When the switch SW is in the 0n state and the power supply voltage is applied, light is emitted from the LED 32, reflected by blood vessels and tissues, received by the phototransistor 33, and the pulse wave signal M is detected.
- the emission wavelength of the LED is selected near the absorption wavelength peak of hemoglobin in blood. Therefore, the light reception level changes according to the blood flow. Therefore, the pulse wave waveform can be detected by detecting the light receiving level.
- an InGaN-based (indium-gallium-nitrogen-based) blue LED is preferable.
- the emission spectrum of a blue LED has an emission peak at, for example, 450 nm, and its emission wavelength range is from 350 nm to 600 nm.
- a GaAs P-based (gallium-arsenic-phosphorus-based) phototransistor may be used as the phototransistor 33 corresponding to the LED having such light emission characteristics.
- the main sensitivity region is in a range from 300 nm to 600 nm, and there is a sensitivity region even below 300 nm.
- hemoglobin in blood has a large extinction coefficient for light with a wavelength between 300 nm and 700 nm, and is several times to about 100 times larger than the extinction coefficient for light with a wavelength of 880 nm. Therefore, as shown in this example, if light in the wavelength region (300 nm to 700 nm) with a large light absorption characteristic is used as detection light in accordance with the light absorption characteristic of hemoglobin, the detection value will change according to the change in blood volume. Since the change is performed with high sensitivity, the SZN ratio of the pulse wave waveform MH based on the change in blood volume can be increased.
- FIG. 4 is a block diagram showing the electrical configuration of the pulse wave diagnostic device.
- the pulse wave diagnostic device 1 includes the following parts.
- Reference numeral 10 denotes a wavelet conversion unit that performs a well-known wavelet conversion on the pulse wave waveform MH output from the pulse wave detection sensor unit 130 to generate a pulse wave analysis data MKD.
- a wavelet In general, in time-frequency analysis that simultaneously captures a signal from both time and frequency, a wavelet is a unit that cuts out the signal part.
- the wavelet transform represents the size of each part of the signal extracted in this unit.
- a function (X) that is localized both in time and frequency is introduced as a mother wavelet as a basis function.
- the wavelet transformation of the function f (x) by the mother-by-bret (X) is defined as follows.
- Equation 1 b is the parameter used when translating (translating) the mother wavelet (X), while a is the parameter used when scaling (stretching). Therefore, in Equation 1, the wavelet ((x-b) / a) is obtained by translating the mother wavelet (X) by b and expanding and contracting by a. In this case, the mother wave corresponding to the scale parameter a Since the width of to (x) is expanded, lZa corresponds to the frequency. The detailed configuration of the wavelet transform unit 10 will be described later.
- 11 is a frequency correction unit that performs frequency correction on the pulse wave analysis data MKD.
- Equation 1 there is a term “lZa 1/2 ” corresponding to the frequency, but when comparing data between different frequency regions, it is necessary to correct the effect of this term.
- the frequency correction unit 11 is provided for this purpose, and generates a pulse wave correction data MKD 'by multiplying the wavelet data WD by the coefficient a1 / 2 . This makes it possible to perform correction based on each corresponding frequency so that the power density per frequency becomes constant.
- reference numeral 12 denotes a pulse data generation unit which identifies pulse waves such as a flat pulse, a chord pulse, and a smooth pulse based on the pulse wave correction data MKD ', and generates a pulse data pulse ZD indicating the pulse data.
- Reference numeral 13 denotes a display unit, which is composed of an R ⁇ M, a control circuit, a liquid crystal display device, and the like. When the pulse data ZD is supplied to the display unit 13, the control circuit detects this, reads the character stored in the ROM, and displays the character on the liquid crystal display. Characters include "Heart vein”, "String vein”,
- FIG. 5 is a block diagram of the wavelet transform unit 10 according to the first embodiment.
- the pulse wave waveform MH is supplied to the waveform shaping unit 100 and the AZD converter 220.
- Waveform shaping section 100 generates control signal CS and clock CK synchronized with pulse waveform MH.
- FIG. 6 is a block diagram of the waveform shaping unit 100.
- a ringing filter 101 is a filter having a high Q value with a center frequency of 2.2 Hz and a pass band of 0.8 Hz to 3.5 Hz. Since the fundamental wave component of the pulse wave waveform is usually in the range of 8 Hz to 3.5 Hz, when the pulse wave waveform MH passes through the ringing filter 101, the fundamental wave component is extracted. For example, when the pulse wave waveform MH shown in FIG.
- the zero-cross detection circuit 102 includes a comparator or the like, and compares the output signal of the ringing filter 101 with the ground level to generate a square wave. This square wave is synchronized with the heartbeat. For example, if the output signal of the ringing filter 101 is as shown in FIG. 7B, the output signal of the zero-cross detection circuit 102 is as shown in FIG. 7C.
- the comparator 103, the loop fill 104, the voltage controlled oscillator 105, and the frequency divider 106 form a phase locked loop.
- the comparator 103 When the output signal of the zero-cross detection circuit 102 is supplied to one input of the comparator 103 and the output signal of the frequency divider 106 is supplied to the other input, the comparator 103 generates an error corresponding to the phase difference between the two. Output signal.
- the error signal is supplied to the voltage controlled oscillation circuit 105 via the loop filter 104, the voltage controlled oscillation circuit 105 outputs the clock CK. Then, the clock CK is frequency-divided by 18 in the frequency divider circuit 106 and fed back to the other input of the comparator 103.
- the frequency of the clock CK is eight times the frequency of the output signal of the zero-cross detection circuit 102 as shown in FIG. 7D. Thereafter, the clock CK is frequency-divided by 1Z2 in the frequency dividing circuit 107 and output as the control signal CS shown in FIG.
- the pulse wave waveform MH shown in FIG. 5 is converted into a digital signal by the AZD converter 220, and then stored in the first memory 221 and the second memory 222.
- the control signal CS is directly supplied to the write enable terminal of the first memory 221, and the control signal CS inverted by the inverter 223 is supplied to the light enable terminal of the second memory 222. Is supplied.
- the first and second memories 221 and 222 store the pulse waveform MH alternately in clock cycle units.
- a multiplexer 224 selects pulse wave data MD read alternately from the first and second memories 221, 222 and outputs the selected data to the basis function developing unit W.
- the pulse wave data MD is read from the second memory 222 during the writing period of the first memory 221, and the pulse wave data MD is written to the second memory 222 during the reading period of the first memory 221. .
- the basis function expansion unit W is configured to perform the arithmetic processing of Equation 1 described above.
- the clock CK described above is supplied, and arithmetic processing is performed in the clock cycle.
- the basis function expansion unit W is a basis function storage unit Wl that stores the mother wavelet ( ⁇ ), a scale conversion unit W2 that converts the scale parameter a, a buffer memory W3, and a translation unit that performs translation. W 4 and a multiplication unit W 5.
- the mother and wavelet (x) stored in the basis function storage unit W1 in addition to the Gabor wavelet, a Mexican hat, a Haar wavelet, a M eyer wavelet, a Shannon wavelet, and the like can be applied. .
- the scale conversion unit W2 converts the scale parameter a.
- the scale parameter a corresponds to the period, as a increases, the mother wavelet wave (x) is expanded on the time axis.
- the amount of mother wavelet ( ⁇ ⁇ ) stored in the basis function storage unit W1 is constant, the data amount per unit time decreases as a increases.
- the scale conversion unit W2 performs an interpolation process to compensate for this, and when the value of a becomes small, performs a thinning process to generate a function (x / a). This data is temporarily stored in the buffer memory W3.
- the translation unit W 4 reads the function (xZa) from the buffer memory W3 at a timing corresponding to the translation parameter b, thereby performing the translation of the function (x / a) and performing the function (X—bZa) Generate
- the multiplying unit W4 multiplies the variable lZa1 / 2 , the function (xb / a) and the pulse wave data MD to perform a wavelet transform in units of heartbeat, and generates a pulse wave data MKD.
- the pulse wave analysis data MKD is 0 Hz to 0.5 Hz, 0.5 Hz to 1.0 Hz, 1.0 Hz to 1.5 Hz, 1.5 Hz to 2.0 Hz,
- the output is divided into frequency ranges such as 3.5 Hz to 4.0 Hz. Further, the base function expansion unit W performs the arithmetic processing at the clock cycle as described above, and the clock frequency is set to be eight times the fundamental frequency of the pulse wave waveform MH, so that one heartbeat
- the pulse wave analysis data MKD generated by the above becomes data M11 to M88 as shown in FIG. 1-3-1-4: Pulse data generator
- FIG. 9 is a block diagram of the pulse data generator 12 according to the present embodiment.
- an adder 121, coefficient circuits 122, 124 and a memory 123 are circuits for calculating the average value of the pulse wave correction data MKD 'for each frequency region.
- the coefficient of the coefficient circuit 122 is 1ZK + 1, and the coefficient of the coefficient circuit 124 is K.
- the adder 121 adds the pulse wave correction data MKD 'and the output of the coefficient circuit 124, and the output data of the adder 121 is stored in the memory 123 via the coefficient circuit 122.
- the memory 123 outputs the input data with a delay of eight clock cycles.
- the cycle of the heartbeat is t
- the current time is T
- the data stored in the memory 123 is Ma
- the data Ma (T) at the time T is given by the following equation.
- Ma (T-t) represents data that is past by time t, that is, data one heart beat ago. Therefore, data Ma (T) is the weighted average of past data and current data. Since this processing is repeatedly performed at every t time, the memory 123 stores the average value of the pulse wave correction data MKD '. Also, since the pulse wave correction data MKD 'is generated for each frequency domain, the average value is calculated for each frequency domain. For this reason, the memory 123 stores the average values Mai 1 to Ma 88 of the pulse wave correction data MKD 'in 0.5 Hz units as shown in FIG. In this sense, the memory 123 functions as an average value table.
- the arithmetic unit 125 generates pulse image data ZD based on the average values Mai 1 to Ma 88 stored in the memory 123.
- the relationship between typical waveforms of chord veins, flat veins, and smooth veins and average values will be described.
- the fundamental frequency of the pulse waveform MH is 1.3 Hz.
- the pulse wave waveform MH is composed of the main wave wf 1 due to the first ascending and descending, followed by the pre-multiple beat wf 2, the descending narrow wf 3, and the multi-beat wave wf 4 as shown in FIG. .
- the main wave wf 1 corresponds to the acute ejection phase of the left ventricle.
- the prepulse wave wf 2 is composed of the interrelation of elastic expansion of the aorta and peripheral reflected waves.
- Descending narrow wf 3 is left ventricular dilation It represents the pressure of the aorta during the diastole and corresponds to the diastolic pressure.
- the double beat wave wf 4 is a wave due to the regurgitation of the outer blood flow accompanying the aortic valve closure.
- FIG. 11 shows the relationship between typical waveforms of chord veins and the average values Mai 1 to Ma 88.
- the vein is characterized by the point that the pre-major wave w f 2 is fused with the main wave w f 1 and the consequent narrowing w f 3 does not appear during descending. That is, the characteristics of the waveform appear in the periods t2 and t3.
- the pre-major wave wf 2 or the descending narrow wf 3 clearly appears, the second harmonic component and the third harmonic component are larger than the fundamental component of the pulse waveform MH. .
- the frequency components above 2 Hz tend to be relatively small in the periods t2 and t3.
- the sum S 1 of the frequency components of 2 Hz or more for the periods t 2 and t 3 is “7”. Note that S 1 is defined by the following equation.
- FIG. 12 shows the relationship between a typical waveform of a normal pulse and an average value.
- Ping mai is characterized by a trimodal wave consisting of the main wave w f 1, the pre-multiple beat wf 2, and the multi-beat wf 4.
- the characteristics appear in the periods t2 and t3.
- the pre-major wave wf 2 and the descending narrow wf 3 and wf 4 clearly appear, the second harmonic component and the third harmonic component of the fundamental wave of the pulse waveform MH increased.
- the frequency components of 2 Hz or more tend to be relatively large in the periods t2 and t3.
- the high frequency component is present in the period t2 because the peak of the double beat wf2 is present in the period t2.
- the total S 1 of the frequency components of 2 Hz or more for the periods t 2 and t 3 is “25”.
- the sum S 2 of the frequency components of 4.0 to 3.0 Hz for the period t 2 is “1 2”
- the sum S 3 of the frequency components of 4.0 to 3.0 Hz for the period t 3 is “7”. It becomes.
- S2 and S3 are defined by the following equations.
- Fig. 13 shows the relationship between the typical waveform of the smooth pulse and the average value.
- the unique feature of the smooth vein is that it consists of a bimodal wave in which the main wave wf 1 and the pre-multiple wave wf 2 almost overlap. That is, the characteristics appear in the periods t 2 and t 3.
- the pre-major wave wf 2 hardly appears, the narrowing wf 3 clearly appears during descending, so that the second harmonic component and the third harmonic component of the fundamental wave of the pulse waveform MH increase.
- the frequency components above 2 Hz tend to be relatively large in the periods t2 and t3.
- the period t 3 has more high frequency components.
- the total S1 of the frequency components of 2 Hz or more for the periods t2 and t3 is both "24".
- the sum S 2 of the frequency components of 4.0 to 3.0 Hz for the period t 2 is “6”
- the sum S 3 of the frequency components of 4.0 to 3.0 Hz for the period t 3 is “10”.
- each pulse has a characteristic portion.
- attention is paid to this point, and the pulse is determined based on the following criteria.
- the calculating means 125 For periods t2 and t3, if the total S I force of 2.0 Hz or more “S 1 ⁇ 15”, it is determined to be a vein. In this case, the calculating means 125 generates data Dg indicating a chordal vein as the pulse data ZD.
- the calculating means 125 For periods t2 and t3, the total S1 force S over 2.0Hz S “S1 ⁇ 15”, and for period t2, the sum of the frequency components from 4.0 to 3.0Hz S2 and period About t 3 When the sum S 3 of the frequency components of 4.0 to 3.0 Hz is in the relationship of “S 2 ⁇ S 3”, it is determined to be a normal pulse. In this case, the calculating means 125 generates data Dh indicating that the pulse is a vein as pulse data ZD.
- the total S1 force over 2.0 Hz is S s "S1 ⁇ 15", and for period t2, the sum of the frequency components from 4.0 to 3.0 Hz S2 If the sum S 3 of the frequency components of 4.0 to 3.0 Hz for the period t 3 is in the relation of “S 2 ⁇ S 3”, it is determined to be a smooth pulse.
- the calculating means 125 generates a data Dk indicating that it is a smooth pulse as the pulse data ZD. 1 -3- 1-5:
- FIG. 14 is a block diagram showing another configuration example of the pulse generation unit.
- the memory 123 functions as an average value table, and the evaluation function calculator 126 generates evaluation data QDg, QDh, and QDk based on the average value stored therein.
- the evaluation function operation unit 126 has a memory.
- the results of performing a wavelet transform on typical pulse wave waveforms corresponding to the chord vein, the normal pulse, and the smooth pulse, respectively, are stored in advance in the same format as the average value table.
- Data corresponding to typical pulse wave waveforms of chord vein are represented by Mgll to Mg88
- data corresponding to typical pulse wave waveforms of normal pulse are represented by Mh11 to Mh88
- typical pulse wave Data corresponding to various pulse waveforms are represented by Mkll to Mk88.
- the evaluation data QDg is a data showing the degree to which the measured pulse waveform MH matches the pulse waveform of a typical chord, and is generated by calculating the following equation. .
- the evaluation data QDh is the measured pulse wave waveform MH This is a summary of how much they match, and is generated by calculating the following equation.
- the evaluation data QDk is the measured pulse wave waveform. This is data indicating how much the shape matches, and is generated by calculating the following formula.
- Pij is a coefficient, but is set to “0” in the time-frequency domain with no features. It is set to “1” only for the relevant part.
- the coefficients are set in this way because the characteristic portion of the pulse waveform has a large energy, and thus the pulse can be determined based on this portion. This is because if the pulse is discriminated, accurate discrimination cannot be performed because the SN ratio is poor.
- the comparing unit 127 compares the magnitudes of the evaluation data QDg, QDh, and QDk, and determines the pulse corresponding to the evaluation data indicating the smallest value with the pulse of the measured pulse wave waveform MH. And generate pulse data ZD.
- one pulse wave waveform is divided into a plurality of frequency-time regions by performing a wavelet conversion in synchronization with the pulse wave waveform MH, and the pulse wave Since a portion that characteristically is extracted is extracted, and a pulse is specified based on the extracted portion, the pulse can be accurately determined.
- the pulse wave diagnostic apparatus is based on the premise that the user is in a resting state. By the way, since the heart rate increases in response to the movement of a person, when the user walks or grasps an object, the pulse waveform fluctuates under the influence of body movement. For this reason, it is difficult for the pulse wave diagnostic apparatus according to the first embodiment to accurately detect a pulse image when there is a body motion.
- the second embodiment has been made in view of this point, and provides a pulse wave diagnostic apparatus capable of accurately detecting a pulse image even when a body motion occurs by canceling a body motion component from the pulse wave waveform. Is what you do.
- the external configuration of the second embodiment is the same as the external configuration of the first embodiment shown in FIG.
- the pulse wave diagnostic device according to the second embodiment is provided with an acceleration sensor 21 inside the device main body 110.
- FIG. 15 is a block diagram of a pulse wave diagnostic device according to the second embodiment.
- the first wavelet transform unit 1OA and the first frequency correction unit 11A have the same configurations as the wavelet transform unit 10 and the frequency correction unit 11 of the first embodiment described above, respectively.
- Pulse wave correction data MKD ' is output from the first frequency correction unit 11A.
- the body motion analysis data T KD is composed of frequency components obtained by dividing the frequency range of 0 to 4 Hz into 0.5 Hz.
- the mask unit 18 subtracts the body motion correction data TKD from the pulse wave correction data MKD to generate pulse wave correction data MKD '' from which the body motion component has been removed.
- the pulse data generation unit 12 generates pulse image data ZD based on the pulse wave correction data MKD ′′ in the same manner as in the first embodiment.
- the display unit 13 displays the pulse based on the pulse data ZD.
- the body motion waveform TH starts to increase from time T1, becomes a positive peak at time T2, then gradually decreases, passes level 0 at time T2, and becomes a negative peak at time T3. And has returned to level 0 at time T4.
- time T3 corresponds to the time when the user lifts the cup to the maximum
- time T1 corresponds to the lifting start time
- the time T4 corresponds to the lifting end time. Therefore, a period from time T1 to time T4 is a period in which the body motion exists.
- FIG. 16 (c) shows a pulse wave waveform MH 'when there is no body movement.
- the fundamental frequency of the pulse waveform MH is 1.3 Hz.
- FIG. 16 shows the pulse wave diagnostic apparatus'during the period Tc
- Fig. 18 shows the body motion correction data TKD' during the period Tc. From this figure, it can be seen that the body motion waveform TH has a relatively large level of frequency components in the frequency range of 0.0 ⁇ to 1.0 Hz.
- the mask unit 18 converts the pulse wave correction data MKD 'to the body motion correction data TKD'. Is subtracted to generate the pulse wave correction data MKD '' from which the body motion component shown in Fig. 19 has been removed. As a result, even if there is a body motion, it is possible to cancel the effect and obtain pulse wave correction data MKD ′ ′ similar to the pulse wave correction data MKD ′ obtained from the pulse waveform at rest.
- the pulse data generation unit 12 determines the pulse based on the pulse wave correction data MKD ′′.
- the total S 1 at 2.0 Hz or higher is 28, so “S 1 ⁇ 15”.
- the sum S 2 of the frequency components of 4.0 to 3.0 Hz for the period t 2 is 9.
- the total S3 of the frequency components of 4.0 to 3.0 Hz for the period t3 is 13. Therefore, “S 2 ⁇ S 3”. Therefore, according to the above-described criterion, it is determined to be a smooth vein, and the pulse data generation unit 12 generates a pulse Dk indicating that the pulse is a smooth pulse as the pulse data ZD.
- the body motion waveform TH is also subjected to the wavelet transform, and the body motion component is canceled based on the wavelet TH. Can be accurately detected.
- the wavelet of the pulse waveform and the wavelet of the body motion waveform are respectively subjected to frequency correction, and then the wavelet of the pulse waveform is masked by the wavelet of the body motion waveform.
- two types of frequency correction units are required, and the configuration becomes complicated.
- the third embodiment has been made in view of this point.
- the external configuration of the third embodiment is the same as the external configuration of the first embodiment shown in FIG. However, in the pulse wave diagnostic device according to the third embodiment, an acceleration sensor 21 is provided inside the device main body 110 as in the second embodiment.
- FIG. 20 is a block diagram of the pulse wave diagnostic device according to the third embodiment.
- the first and second wavelet transform units 10A and 10B and the frequency correction unit 11 have the same configurations as the wavelet transform unit 10 and the frequency correction unit 11 of the first embodiment described above. It is.
- the mask unit 18 subtracts the body motion analysis data TKD from the pulse wave analysis data MKD to generate a body motion removal pulse wave data in which the body motion component is canceled. You. Thereafter, the frequency correction unit 11 performs frequency correction on the body motion removal pulse wave data so that the power density per frequency becomes constant, and generates a pulse wave correction data MKD ′ ′. This makes it possible to compare levels between different frequency components.
- the pulse data generation unit 12 generates pulse data overnight ZD based on the pulse wave correction data MKD ′′
- the pulse data ZD is displayed on the display unit 13.
- the frequency correction unit 11 is provided at the subsequent stage of the mask unit 18, so that the configuration of the pulse wave diagnostic apparatus can be simplified and even if there is a body motion. It is possible to specify the context.
- the body motion waveform TH is detected by the acceleration sensor 21 and a wavelet transform is applied to the body motion waveform TH. Then, the result of the wavelet conversion of the pulse wave waveform MH is compared with the result of the wavelet conversion of the body motion waveform TH to cancel the body motion component included in the frequency component of the pulse wave waveform MH.
- the context was identified. However, the configuration becomes complicated because the acceleration sensor 21 and the second wavelet converter 10B are required.
- the fourth embodiment has been made in view of this point, and provides a pulse wave diagnostic apparatus capable of accurately specifying a pulse even if there is a body movement despite a simple configuration. is there.
- FIG. 21 is a block diagram of the pulse wave diagnostic apparatus according to the fourth embodiment.
- FIG. 21 shows that a body motion separation unit 19 is newly provided between the frequency correction unit 11 and the pulse data generation unit 12. Except for this, it is the same as FIG. 4 described in the first embodiment. Hereinafter, the differences will be described.
- the body motion separation unit 19 separates and removes the body motion component from the pulse wave correction data MK D 'to generate body motion separated pulse wave data TBD.
- the body motion separation unit 19 utilizes the properties of body motion described below.
- Body motion is caused by the vertical movement of the arm or the swing of the arm during running.
- the human body In daily life, the human body rarely moves instantaneously. Because of this, in everyday life, the body
- the frequency component of the dynamic waveform TH is not very high and is usually in the range 0 Hz to 1 Hz.
- the fundamental frequency of the pulse waveform MH is often in the range of 1 1 to 2 ⁇ . Therefore, in daily life, the frequency component of the body motion waveform TH is in a frequency region lower than the fundamental frequency of the pulse waveform MH.
- the frequency component of the body motion waveform TH increases somewhat due to the effects of arm swing and the like, but the pulse rate increases because the number of beats increases according to the amount of exercise.
- the fundamental frequency of the waveform MH also increases at the same time. For this reason, even during sports, the frequency component of the body motion waveform TH is usually in a frequency region lower than the fundamental frequency of the pulse waveform MH.
- the body motion separating section 19 separates the body motion component, and is configured to ignore a frequency region lower than the fundamental wave component of the pulse waveform MH. In this case, if the body motion component exists in a frequency region higher than the fundamental wave component of the pulse waveform MH, the detection accuracy of the pulse image decreases. However, as described above, since the body motion component is more likely to be in a lower frequency region than the fundamental wave component of the pulse wave waveform MH, the pulse image can be detected with high accuracy.
- FIG. 22 is a detailed block diagram of the body movement separating unit 19.
- the waveform shaping section 191 performs waveform shaping on the pulse waveform MH, and generates a reset pulse synchronized with the pulse waveform MH.
- the average value calculation circuit 193 calculates the average value of the count value of the count 1992. Specifically, it may be configured by the adder 121, the coefficient circuits 122, 123, the memory 123 shown in FIG. In this case, the average value calculated by the average value calculation circuit 193 corresponds to the average period of the pulse wave waveform MH. Therefore, the fundamental frequency of the pulse waveform MH can be detected by referring to the average value.
- the replacement circuit 194 specifies a frequency region including the fundamental frequency of the pulse waveform MH based on the average value. For example, when the average value indicates 0.71 seconds, the fundamental frequency is 1.4 Hz, and the specified frequency region is 1 Hz to: 0.5 Hz. After this, the replacement circuit 1994 sets the frequency range Then, the pulse wave correction data MKD 'is replaced with “0” to generate body motion separated pulse wave data TBD. As a result, components in the frequency region lower than the fundamental frequency of the pulse waveform MH are ignored in determining the pulse. In this case, the pulse wave component is replaced with “0” together with the body motion component.However, the characteristic portion of the pulse wave waveform MH exists in a frequency region higher than the fundamental frequency, and thus “0”. Substituting with has almost no effect on the judgment of the pulse.
- the pulse data generation unit 12 shown in FIG. 21 determines the pulse and generates pulse data ZD.
- the display unit 13 displays, for example, characters such as “flat pulse”, “string pulse”, and “smooth pulse”, as well as specific symbols and icons. .
- the pulse wave detection sensor unit 130 detects the pulse wave waveform MH (fundamental frequency 1.3 Hz) shown in FIG. 16A
- the pulse wave correction data MKD for the period Tc is used. 'Is as shown in Figure 17.
- the frequency range specified by the replacement circuit 194 is 1.0 ⁇ to 1.5 Hz, and the frequency range to be replaced is Mal 2 to Ma 82 corresponding to 0.5 Hz to 1.0 Hz. M a 1 1 to M a 81 corresponding to 0 Hz to 0.5 Hz. Therefore, the data Ma12 to Ma82 and Ma11 to Ma81 of the pulse wave correction data MKD 'are replaced with "0", and the body motion separated pulse wave data TBD shown in FIG. 23 is generated.
- the pulse data generation unit 12 determines the pulse based on the body motion separated pulse wave data TBD.
- the pulse is determined to be a smooth pulse, and the pulse data generation unit 12 generates data Dk indicating that the pulse is a smooth pulse as the pulse data overnight ZD.
- the body motion component is the fundamental frequency component of the pulse waveform MH.
- the configuration of the acceleration sensor 21 and the second wavelet transform unit 10B required in the second and third embodiments can be omitted, and even if there is a body motion, the pulse can be accurately detected.
- the pulse wave waveform MH is subjected to the wavelet transform to remove the body motion component from the result of the transform, and the pulse wave is specified based on the energy level in the time frequency domain.
- wavelet processing it is known that a signal on the time axis can be reproduced by performing an inverse wavelet transform on a transform result obtained by performing a wavelet transform.
- a wavelet transform result obtained by removing a body motion component is subjected to inverse wavelet transform to specify a pulse on a time axis.
- the external configuration of the pulse wave diagnostic apparatus according to the fifth embodiment is the same as the external configuration of the first embodiment shown in FIG. 2, and thus the description thereof is omitted here, and the electrical configuration will be described.
- the case where the inverse wavelet transform is applied to the above-described fourth embodiment will be described as an example.However, the inverse wavelet transform is applied to the second and third embodiments, and this is applied on the time axis.
- the image may be specified.
- FIG. 24 shows a block diagram of a pulse wave diagnostic device according to the fifth embodiment.
- the pulse wave diagnostic apparatus according to the fifth embodiment is characterized in that the frequency correction unit 11 is not used, the pulse image data generation unit 12 is replaced with a pulse image determination unit 22,
- the difference from the pulse wave diagnostic device of the fourth embodiment shown in FIG. 21 is that an inverse wavelet transforming unit 20 is provided between the separating unit 19 and the pulse image judging unit 22.
- the differences will be described.
- the frequency correction unit 11 is not provided.
- the pulse waveform is specified from the signal waveform on the time axis, so that it is not necessary to compare the conversion results of the wavelet conversion for each time-frequency domain. It is.
- the inverse wavelet transform processes the result of the wavelet transform to reproduce the signal waveform on the time axis, so if the frequency correction is applied, the signal waveform will not be accurately reproduced. is there.
- the inverse wavelet converter 20 has a complementary relationship with the wavelet converter 10 and calculates the following equation (2).
- a body motion separation pulse wave waveform TMH is obtained based on the body motion separation pulse wave data TBD.
- the pulse wave waveform MH shown in FIG. 16 (a) is detected by the pulse wave detection sensor unit 1330, the pulse wave analysis data MKD shown in FIG. 17 during the period Tc.
- the body motion separation pulse wave data TBD shown in FIG. 23 is obtained.
- the inverse wavelet transform is performed by the inverse wavelet transform unit 20
- the pulse wave waveform MH 'shown in FIG. 16 (c) is generated as the body motion separated pulse wave waveform TMH.
- the pulse determination unit 22 first extracts a waveform parameter that specifies the shape of the body motion separation pulse waveform TMH in order to specify the pulse.
- a waveform parameter that specifies the shape of the body motion separation pulse waveform TMH in order to specify the pulse.
- the waveform parameters are defined as follows. In FIG. 21, the vertical axis represents blood pressure, and the horizontal axis represents time.
- FIG. 26 is a block diagram showing the configuration of the pulse image determination unit 22.
- reference numeral 181 denotes a microcomputer which controls each component. 1 8 4 is by Ram
- the waveform memory W is configured to capture the waveform value W of the body motion separated pulse wave waveform TMH via the AZD converter 182 and store it sequentially.
- Reference numeral 195 denotes a waveform value address. The period in which the microcomputer 18 1 outputs the waveform sampling instruction START is counted, the sampling clock ⁇ is counted, and the count result is a waveform to which the waveform value W is to be written. Output as value address ADR 1. This waveform value address ADR 1 is monitored by the microcomputer 18 1.
- Reference numeral 196 denotes a selector.
- the waveform value address ADR 1 output from the waveform value address counter 195 is selected to store the waveform memory 18 4 Supply to the address input terminal.
- the select signal S1 is output from the microcomputer 181
- the read address ADR4 output from the microcomputer 181 is selected and the waveform memory 184 is inputted to the address input terminal of the memory 184. Supply.
- Reference numeral 201 denotes a differentiating circuit which calculates and outputs the time derivative of the waveform value W sequentially output from the low-pass filter 183.
- Reference numeral 202 denotes a zero-crossing detection circuit, which outputs a zero-crossing detection pulse Z when the time derivative of the waveform value W becomes 0 due to the waveform value W becoming a maximum value or a minimum value. More specifically, the zero cross detection circuit 202 is a circuit provided for detecting peak points P l, P 2,..., In the waveform of the pulse wave illustrated in FIG. When a waveform value W corresponding to these peak points is input, a zero-cross detection pulse Z is output.
- Numeral 203 denotes a peak address count, which counts the zero-crossing detection pulse Z while the microcomputer 181 is outputting the waveform sampling instruction ST ART, and outputs the count result as the peak address ADR2.
- Reference numeral 204 denotes a moving average calculation circuit, which calculates the average value of the time differential value of a predetermined number of waveform values W output from the differentiating circuit 201 up to the present time, and outputs the result up to the present time. Output as slope information SLP indicating the slope of pulse wave.
- Reference numeral 205 denotes a peak information memory provided for storing peak information described below. Here, the details of the peak information will be described below. That is, details of the contents of the peak information shown in FIG. 28 are as listed below. 1 Waveform value address ADR 1
- the counting of the sampling clock ⁇ is started by the waveform value address counter 195, and the count value is supplied to the waveform memory 184 via the selector 196 as the waveform value address ADR1.
- the pulse wave signal detected from the human body is input to the AZD converter 182, sequentially converted to a digital signal according to the sampling clock ⁇ , and sequentially output as a waveform value W via the low-pass filter 183.
- the waveform values W output in this manner are sequentially supplied to the waveform memory 184, and are written to the storage area specified by the waveform value address ADR1 at that time.
- a series of waveform values W corresponding to the pulse waveform illustrated in FIG. 27 are stored in the waveform memory 184.
- detection of peak information and writing to the peak information memory 205 are performed as described below.
- the time derivative of the waveform value W of the body motion separated pulse wave waveform TMH is calculated by the differentiating circuit 201, and the time derivative is input to the zero cross detection circuit 202 and the moving average calculation circuit 204.
- the moving average calculation circuit 204 calculates the average value (ie, moving average value) of a predetermined number of time differential values in the past each time the time differential value of the waveform value W is supplied in this way, and slopes the calculation result.
- Information S Output as LP.
- a positive value is output as the slope information SLP if the waveform value W is rising or has finished rising and has reached a maximum state, and if the waveform value W has reached a minimum state after falling or has finished falling and has a slope.
- Information A negative value is output as SLP.
- the waveform value W corresponding to the local maximum point P 1 shown in FIG. 27 is output from the mouth-to-pass filter 183, 0 is output from the differentiating circuit 201 as the time derivative, and the zero cross detection circuit 202 outputs zero.
- the cross detection pulse Z is output.
- the microcomputer 181 the waveform address ADR1, which is the count value of the waveform address address 195 at that time, the waveform value W, and the peak address ADR2, which is the count value of the peak address count, are stored.
- a DR 2 0) and the slope information SLP are captured.
- the output of the zero-crossing detection pulse Z becomes the count value ADR2 of the peak address counter 203.
- the microcomputer 1811 creates the peak type BZT based on the sign of the acquired slope information SLP.
- the microphone computer 181 maps the value of the peak information BZT to the maximum value. It shall be done.
- the obtained waveform address ADR1, peak type BZT, and slope information SLP are written to the peak information memory 205 as the first peak information.
- the stroke information STRK is created and written because there is no previous peak information. Is not included.
- the microcomputer 18 1 determines the peak type B / T (in this case, “B”) based on the inclination information S LP. Further, the microcomputer 181 supplies an address smaller than the peak address ADR 2 by 1 to the peak information memory 205 as the read address ADR 3, and reads the first written waveform value W. Then, the microcomputer 18 1 calculates a difference between the waveform value W fetched this time from the one-pass filter 183 and the first waveform value W read out from the peak information memory 205, and obtains stroke information STRK.
- the microcomputer 18 1 determines the peak type B / T (in this case, “B”) based on the inclination information S LP. Further, the microcomputer 181 supplies an address smaller than the peak address ADR 2 by 1 to the peak information memory 205 as the read address ADR 3, and reads the first written waveform value W. Then, the microcomputer 18 1 calculates a difference between the waveform value W fetched this time from the one-pass filter 183 and the first wave
- the output of the waveform sampling instruction START is stopped by the microcomputer 181, and the sampling of the waveform value W and the peak information ends.
- the microcomputer 181 performs a process for specifying information corresponding to a waveform for one beat, from which various waveform parameters are collected, among various information stored in the peak information memory 205.
- the slope information S LP and the stroke information STRK corresponding to each peak point P 1, P 2,... are sequentially read from the peak information memory 205.
- stroke information corresponding to a positive slope that is, the corresponding slope information SLP has a positive value
- the information corresponding to the median is selected from the selected stroke information STRK.
- the stroke information of the rising part of the pulse wave for one beat from which the extraction of the waveform parameters should be extracted (for example, the rising part indicated by the symbol STRKM in FIG. 27) is obtained.
- a peak address that is one before the peak address of the stroke information that is, the peak address of the start point P6 of the pulse wave for one beat at which the extraction of the waveform parameter should be performed) is obtained.
- the microcomputer 181 calculates each waveform parameter by referring to each piece of the peak information corresponding to the one-pulse wave stored in the peak information memory 205. This processing is obtained, for example, as follows.
- the waveform values corresponding to peak point P 7 ⁇ P 1 1 respectively y, and ⁇ y 5.
- the waveform address corresponding to the peak point P6 is subtracted from the waveform address corresponding to the peak point P7, and the result is multiplied by the period of the sampling clock ⁇ to calculate t.
- the peak information includes time tl to t5, blood pressure yl to y4, and one cycle t6 of the waveform for the waveform peaks P1 to P5 shown in FIG.
- the pulse waveform is the main wave of the first rise and fall (corresponding to peak point P 1), followed by the prepulse wave (corresponding to peak point P 3), descending narrow (peak point P 3 to peak point P 4 ) And double beats (corresponding to peak point P5).
- the main wave corresponds to the acute ejection phase of the left ventricle.
- Prepulse waves are related to elastic expansion of the aorta and peripheral reflected waves Be composed.
- Descending narrowing represents the pressure of the aorta during left ventricular diastole and corresponds to the diastolic pressure. Furthermore, the dichotomy is a wave due to the regurgitation of the outer blood flow associated with aortic valve closure.
- the microcomputer 181 determines the type of the pulse wave based on the peak information as described below. Prior to this, the microcomputer 181 calculates Wt shown in FIG. Wt is the waveform width at the position of the main wave height y1 to 1Z3. In FIG. 21, the microcomputer 181 calculates 2 * ylZ3 (step S300), and sequentially compares the calculated result with the peak value read from the waveform memory 184. Then, the waveform address at the time when they match is stored in a buffer memory in the microcomputer 181 (step S301). Thus, the times of the points Qa and Qb are obtained, and the difference between the two is calculated to calculate the waveform width Wt of the main wave (step S302).
- the microcomputer 181 determines the type of the pulse as follows. (1) As shown in Fig. 11, the prepulse wave is fused with the main wave in the chord vein, so 1) the main wave is wider and 2) the height of the main wave is higher than the main wave. Are relatively high. For this reason, the microcomputer 181 calculates the following relational expressions (55) to (59), and determines that a sinus vein is obtained when these are satisfied (step S303).
- the Ping mai is a trimodal wave consisting of a main wave, a pre-double beat, and a beat wave. For this reason, the microcomputer 181 calculates the following relational expressions (60) to (64), and determines that it is a normal pulse when these are satisfied (step S304).
- the smooth vein is a bimodal wave in which the main wave and the prepulse wave almost overlap.
- the microcomputer 181 calculates the following relational expressions (65) to (68), and determines that it is a smooth vein if these are satisfied (step S305).
- the pulse determining unit 22 When the type of the pulse is specified in this way, the pulse determining unit 22 generates a pulse de-evening ZD indicating the pulse (step S306). If none of the above-mentioned chord veins, flat veins, or smooth veins, it is processed as an error (step S306).
- the pulse wave waveform MH is subjected to the wavelet transform, the body motion component is separated by skillfully utilizing the characteristics of the body motion, and the body motion separated pulse wave waveform TMH is reproduced again. Configured. As a result, a body motion component acting as a noise component can be removed, and even if there is a body motion, it is possible to accurately detect a pulse using a signal waveform.
- the frequency correction unit is used to compare the energy in different frequency regions. However, focusing on a certain frequency region, a pulse is generated based on the energy level. It may be specified.
- the AB conversion unit when the frequency correction unit is omitted, performs a wavelet conversion on the pulse wave waveform MH detected by the pulse wave detection sensor unit 130, and performs a wavelet conversion for each frequency region.
- the pulse wave analysis data MKD may be generated in advance, and the pulse wave analysis data MKD may be subjected to arithmetic processing to generate pulse image data ZD indicating the type of pulse wave waveform.
- the frequency correction means when the pulse wave waveform MH is detected by the pulse wave detection sensor unit 130, the first waveform is obtained.
- the wavelet transform unit 1OA performs a wavelet transform on the pulse wave waveform MH to generate pulse wave analysis data MKD for each frequency region.
- the second wavelet transform unit 10B performs a wavelet transform on the body motion waveform TH to obtain the body motion analysis data TKD for each frequency domain.
- the mask unit 18 subtracts the body motion analysis data T KD from the pulse wave analysis data MKD to generate corrected pulse wave data MKD '' from which the body motion has been removed.
- a calculation process may be performed on the corrected pulse wave data MKD ′′ to generate a pulse image data ZD indicating the type of the pulse waveform MH.
- the output of the body motion separation unit 19 is subjected to an inverse wavelet transform to generate the body motion separation pulse wave waveform TMH.
- the present invention reconstructs the gesture from which the body motion has been removed.
- the present invention is not limited to this, and any method may be used as long as an inverse wavelet is applied based on a wavelet from which body motion has been removed. Is also good.
- the first wavelet conversion unit 1OA performs a wavelet conversion on the pulse wave waveform MH and outputs a pulse wave for each frequency region. Generate analysis data MKD.
- the second wavelet transformer 10B When the body motion waveform TH is detected by the acceleration sensor 21, the second wavelet transformer 10B performs a wavelet transform on the body motion waveform TH to generate body motion analysis data TKD for each frequency domain. . Thereafter, the mask unit 19 subtracts the body motion analysis data TKD from the pulse wave analysis data MKD to generate a corrected pulse wave data MKD ′ ′ with the body motion removed, and performs inverse wavelet transform on this. May be applied.
- each of the wavelet transform units 10, 10A, and 10B includes the basis function expanding unit W, and performs the wavelet transform by using the basis function expanding unit W.
- the present invention is not limited to this. May be realized by the Phil Evening Bank.
- Fig. 30 shows a configuration example of the filter bank.
- the filter bank is composed of three stages, the basic units of which are high-pass filter 1 A and a decision filter, low-pass filter 1 B and a decision filter. Evening is 1C.
- the high-pass filter 1A and the low-pass filter 1B divide a predetermined frequency band and output a high-frequency component and a low-frequency component, respectively.
- the frequency band of the pulse wave data MD is assumed to be 0 Hz to 4 Hz, so the pass band of the first-stage high-pass filter 1 A is set to 2 Hz to 4 Hz.
- the passband of the first low-pass filter 1B is set to 0Hz to 2Hz.
- Decimation Fill 1C thins out every other sample.
- the high-pass filter 1A and the low-pass filter 1B may be composed of a transversal filter including a delay element (D flip-flop) therein.
- the pulse rate of a person is in the range of 40 to 200, and the fundamental frequency of the pulse waveform MH fluctuates every moment according to the state of the living body.
- the band to be divided can be changed in synchronization with the fundamental frequency, information that follows a dynamic biological state can be obtained. Therefore, the frequency band to be divided may be adaptively changed by setting the clock supplied to the transfill filter to the pulse waveform MH.
- the pulse wave analysis data MKD representative frequency components representing the characteristics of the pulse wave waveform MH are the fundamental wave, the second harmonic, and the third harmonic. Therefore, the pulse may be determined using a part of the output data M * 1 to M * 8 of the filter bank. In this case, if the filter bank is configured to be synchronized with the pulse waveform MH as described above, the high-pass filter 1A, the low-pass filter IB, and part of the decimation filter 1C are omitted, and Can be simplified.
- the inverse wavelet transform unit 20 may be configured by the filter bank illustrated in FIG.
- the filter bank is composed of three stages, the basic units of which are high-pass filter 2A and interpolation filter 2C, low-pass filter 1B and interpolation filter 2C, and adder 2D. is there.
- High pass filter 2 A The low-pass filter 2B divides a predetermined frequency band and outputs a high-pass frequency component and a low-pass frequency component, respectively.
- the interpolation filter 2C interpolates one sample every two samples.
- the characteristics of the high-pass filters 1A and 2A and the low-pass filters 1B and 2B need to have the following relationship.
- the high-pass filter 2A and the low-pass filter 2B may be composed of transversal filters including delay elements (D flip-flops) therein. Note that, in order to synchronize the filter bank used in the avelet conversion unit 10 with the fundamental frequency of the pulse waveform MH and to vary the band to be divided, when the supplied clock is synchronized with the pulse waveform MH, May supply this clock to high-pass filter 2A and low-pass filter 2B.
- the body motion waveform TH is detected by the acceleration sensor 21.
- the fundamental frequency of the pulse wave waveform MH increases.
- the pulse wave waveform MH is frequency-analyzed by the first wavelet transform unit 1 OA. If the frequency region to be subjected to the frequency analysis is fixed, the characteristic portion of the pulse wave waveform MH is sufficiently analyzed. It becomes difficult. For example, suppose that a person whose pulse wave waveform MH had a fundamental frequency of 1 Hz in a resting state ran and changed the fundamental wave frequency of the pulse waveform MH to 2 Hz (corresponding to a pulse rate of 120). .
- the frequency analysis can be performed up to the third harmonic of the pulse wave waveform MH by performing the wavelet conversion in the range of 0 to 4 Hz as described in the second embodiment.
- the third harmonic is 6 Hz, so that frequency analysis cannot be performed.
- the momentum is obtained based on the body motion waveform TH, and the first and the second are to shift the frequency region for performing the wavelet transform to a higher region as the momentum increases.
- the wavelet converters 1 OA and 10 B may be controlled.
- first and second wavelet transform units 10A and 10B are configured by the above-mentioned filter banks, their clock frequencies may be controlled according to the momentum. That is, well-known feedback control may be performed so as to increase the clock frequency as the momentum increases.
- the pitch of the body motion waveform TH indicates the reciprocating pitch of the arm, and has a fixed relationship with the sliding pitch of the foot. Normally, two steps are performed for each swing of the arm. is there. In addition, the amount of exercise can be expressed by the product of the running speed and the step length. Generally, the pitch tends to increase as the running speed increases, and the stride tends to decrease. Therefore, there is a certain relationship between the pitch of the body motion waveform TH and the momentum. For example, FIG. 32 shows, on the same diagram, firstly the relationship between the running speed and the number of beats in the ground running, and secondly, the relationship between the running speed and the running pitch.
- the subject's pulse rate and running pitch increase with the running speed.
- the amount of exercise and the number of beats increase accordingly. Therefore, the relationship between the pitch of the body motion waveform TH and the amount of exercise may be measured in advance, and this may be stored in a table, and the amount of exercise may be calculated with reference to this table.
- the display unit 13 has been described as an example of a notifying unit.
- the following unit may be used. It is considered appropriate to classify these measures based on the five senses.
- these means may be used alone or in combination with a plurality of means. As described below, for example, if a means other than hearing is used, even a visually impaired person can understand the contents of the notification. Can be notified, and a device that is friendly to users with disabilities can be configured.
- the level of information such as volume shown below may be changed according to the content of the information to be conveyed. For example, pitch, volume, timbre, voice, and music type (eg, song number).
- the visual notification means is used for the purpose of notifying various messages and measurement results from the device, or for giving a warning.
- the following equipment can be considered as a means for that. Examples include display devices, CRTs (cathode ray tube display devices), LCDs (liquid crystal display displays), printers, XY projectors, and lamps. Note that there is an eyeglass-type projector as a special display device.
- the following variations can be considered for notification.
- a face chart for example, the face of an old man may correspond to a chord vein, the face of a healthy middle-aged man may correspond to a flat vein, and the face of an unhealthy middle-aged man may correspond to a smooth pulse.
- tactile means of notification may be used for warning purposes.
- a mechanical stimulus that stimulates the projection (for example, a less sharp needle) from the back of a portable device such as a wristwatch.
- the notification means that appeals to the sense of smell may be configured such that the device to be provided with a discharge mechanism for fragrance or the like, the content to be notified corresponds to the fragrance, and the fragrance is discharged according to the content of the notification. good.
- a micropump or the like is the most suitable for the spouting mechanism.
- the pulse wave detecting section f1 is an example of the pulse wave detecting means f1.
- the pulse wave detection sensor unit 130 uses reflected light, it may use transmitted light.
- transmitted light light having a wavelength region of 700 nm or less tends to hardly penetrate finger tissues. Therefore, when using transmitted light, light with a wavelength of 600 nm to 1000 nm is emitted from the light emitting part, the irradiated light is transmitted in the order of tissue-blood vessel-tissue, and a change in the amount of transmitted light is detected. Since transmitted light is absorbed by hemoglobin in blood, a pulse wave waveform can be detected by detecting a change in the amount of transmitted light.
- an InGaAs-based (indium-gallium-arsenic) or GaAs-based (gallium-arsenic) laser-light emitting diode is suitable for the light emitting section.
- the external light having a wavelength of 600 nm to 1000 nm easily passes through the tissue, when the external light enters the light receiving portion, the SZN of the pulse wave signal is degraded. Therefore, a single laser beam may be emitted from the light emitting unit, and the transmitted light may be received by the light receiving unit via the polarizing filter. As a result, a pulse wave signal can be detected with a good SZN ratio without being affected by external light.
- the light emitting section 230 is provided on the tightening side of the fastener 145, and the light receiving section 231 is provided on the timepiece main body side.
- the light emitted from the light emitting unit 200 passes through the blood vessel 143, passes between the radius 232 and the ulna 233, and reaches the light receiving unit 231.
- the wavelength is preferably 600 nm to 1000 nm in consideration of tissue absorption.
- FIG. 2B shows an example in which the detection site is an earlobe.
- the gripping member 234 and the gripping member 235 are urged by a panel 237 to be able to rotate about a shaft 236.
- the holding member 234 and the holding member 235 are provided with a light emitting section 230 and a light receiving section 231.
- the earlobe is gripped by the gripping members 234 and 235 to detect a pulse wave.
- the pulse wave waveform MH may be detected from the fingertip as shown in FIG.
- FIG. 33 (a) is a perspective view showing an external configuration of a pulse wave diagnostic device using a pressure sensor.
- the pulse wave diagnostic apparatus 1 is provided with a pair of bands 144, 144, and one of the fasteners 145 is provided with an elastic rubber 13 1 of the pressure sensor 130a. Are provided to protrude.
- a band 144 having a fastener 145 is used to supply a detection signal from the pressure sensor 130 to a flexible printed circuit (FPC).
- FPC flexible printed circuit
- the structure is such that the substrate is covered with soft plastic (details are not shown).
- the watch 146 is wound around the subject's left arm 147 so that the elastic rubber 131 provided on the fastener 145 is located near the radial artery 143 as shown in FIG. 33 (b). Turned. Therefore, it is possible to constantly detect the pulse wave. Note that this winding is not different from the normal use of a wristwatch.
- the elastic rubber 131 is pressed in the vicinity of the subject's radial artery 143 in this manner, the blood flow fluctuation (that is, pulse wave) of the artery is transmitted to the pressure sensor 130a via the elastic rubber 131, and the pressure sensor 130a transmits this. Detected as blood pressure.
- the photoelectric pulse wave sensor is combined with glasses.
- a display device as a means for notifying the user is incorporated together. Therefore, the function as a display device in addition to the function as the pulse wave detection unit will be also described.
- FIG. 34 is a perspective view illustrating a state in which the device to which the pulse wave detection unit is connected is attached to eyeglasses. As shown in the figure, the main body of the device is divided into a main body 75a and a main body 75b, each of which is separately attached to the vine 76 of the spectacles. It is connected.
- the main body 75a has a built-in display control circuit, and a liquid crystal panel 78 is mounted on the entire surface of the main body 75a on the side of the lens 77, and a mirror 79 is fixed to one end of the side at a predetermined angle. Have been.
- the main body 75a includes a light source (not shown)
- a drive circuit for the liquid crystal panel 78 and a circuit for creating display data are incorporated. The light emitted from this light source is reflected by a mirror 79 via a liquid crystal panel 78 and projected on a lens 77 of the glasses.
- the main part of the device is incorporated in the main body 75b, and various buttons are provided on the upper surface thereof. The functions of these buttons 80 and 81 differ from device to device. Also.
- the LED 32 and the phototransistor 33 (see FIG. 3), which constitute the photoelectric pulse wave sensor, are built into the pads 82 and 83, and the pads 82 and 83 are fixed to the earlobe. ing. These pads 82, 83 are electrically connected by lead wires 84, 84 drawn from the main body 75b.
- reference numeral 1601 denotes a sensor pad which is formed of a sponge-like cushioning material or the like.
- a pulse wave detection sensor unit 130 is attached so as to be in contact with the skin surface.
- the pulse wave detection sensor unit 130 comes into contact with the skin behind the neck to measure the pulse wave.
- the main part of the device is incorporated in a case 1602 having a hollow part similar to a broach, and if necessary, in addition to LEDs and photodiodes for communication, A button switch or the like for making settings is provided on the back of the case 1602 in the figure (not shown).
- the pulse wave detector 101 and the case 1602 are respectively attached to a chain 1603, and a lead wire (not shown) embedded in the chain 1603 is connected to the chain 1603. It is electrically connected via
- a card type as shown in FIG. 36 is conceivable.
- This force-type device is housed in the subject's left breast pocket.
- the pulse wave detector in this embodiment is composed of a piezoelectric microphone 130b provided on the card surface, and detects the subject's heartbeat to detect the pulse rate, facing the subject's skin surface side.
- Reference numeral 208 denotes a notification unit that notifies an alarm sound or a pulse by voice. Like this When the wave detection unit is configured with a microphone or the like, if the notification unit 208 generates an alarm sound or voice, the sound is detected, so the CPU provided inside the device uses a piezoelectric device to generate the alarm sound. It should be noted that a process is required so that the number of beats is not detected by the microphone 130b.
- a pedometer type as shown in FIG. 37 (a) can be considered.
- the main body 1900 of the pedometer is attached to the subject's waist belt as shown in FIG.
- the pulse wave detection sensor unit 130 in this embodiment is worn between the base of the left index finger of the subject and the second finger joint, similarly to the wristwatch type shown in FIG. At this time, it is desirable that the cable 120 connecting the apparatus main body 1900 and the pulse wave detection sensor unit 130 be sewn into a jacket so as not to hinder the movement of the subject.
- the first wavelet transform unit 1OA may be configured as shown in FIG.
- the amplitude value PP is detected.
- This amplitude value PP is compared with reference value REF by comparator 226.
- the comparator 226 generates a control signal that goes low when the amplitude value PP is higher than the reference value REF and goes high when the amplitude value PP is lower than the reference value REF.
- This control signal indicates the presence or absence of body movement. There is no body movement during the low level period and no body movement during the high level period. In this case, the reference value REF is predetermined by an experiment so that the presence or absence of body movement can be determined.
- the gate circuit 227 gates the pulse waveform MH based on the control signal.
- the pulse waveform MH is supplied to the ringing filter while the control signal is at the high level, and the pulse waveform MH is not supplied to the ringing filter 101 while the control signal is at the low level. Thereby, the pulse wave waveform MH can be masked during the period in which there is a body motion.
- the Q value of the ringing filter 101 is set high, so that even if the supply of the pulse waveform MH is stopped for a certain period, the sine It can keep outputting waves. Therefore, even if there is a body motion, it is possible to calculate the period of the pulse wave waveform MH and perform wavelet transform based on this.
- the pulse image is determined by performing the wavelet transform on the pulse wave waveform MH.
- the conversion result of the wavelet transform may be used to obtain various information of the living body.
- the degree of relaxation may be detected by analyzing a pulse wave waveform or an electrocardiographic waveform.
- the time interval between the R wave of one heartbeat and the R wave of the next heartbeat is called the RR interval.
- This RR interval is a numerical value that is an index of the autonomic nervous function in the human body.
- Figure 39 illustrates the heartbeats on the electrocardiogram and the RR intervals obtained from the waveforms of these heartbeats. As can be seen from the figure, according to the analysis of the electrocardiogram measurement results, it is known that the RR interval fluctuates with time.
- the fluctuation of blood pressure measured in the radial artery and the like is defined as the fluctuation of systolic blood pressure and diastolic blood pressure every beat, and corresponds to the fluctuation of the RR interval in the electrocardiogram.
- FIG. 40 shows the relationship between the electrocardiogram and the blood pressure. As can be seen from this figure, the systolic and diastolic blood pressures per beat are measured as the maximum value of the arterial pressure in each RR interval and the local minimum seen immediately before the maximum value.
- H F High Frequency
- the RR interval between adjacent pulse waves is determined, and the obtained discrete value of the RR interval is determined by an appropriate method (for example, cubic spline interpolation). Interpolation (see Figure 39). Then, apply FFT processing to the interpolated curve 1
- FIG. 41 (a) shows a fluctuation waveform of the measured RR interval of the pulse wave, and a waveform of each fluctuation component when the fluctuation waveform is decomposed into the above three frequency components.
- FIG. 41 (b) shows the result of the spectrum analysis of the fluctuation waveform of the RR interval shown in FIG. 41 (a).
- the LF component indicates the degree of sympathetic tone, and the greater the amplitude of this component, the greater the tone (or the more excited state).
- the HF component represents the degree of parasympathetic tone, and the greater the amplitude of this component, the more relaxed (or sedated) the component is.
- RR50 is defined as the number of times that the absolute value of the pulse wave interval corresponding to the RR interval of two consecutive heartbeats fluctuates by 50 ms or more in the measurement of the pulse wave for a predetermined time. It has been found that the higher the value of RR50, the more sedated the subject, and the lower the value of RR50, the more excited.
- the above-described LF and HF may be calculated by performing a wavelet transformation on the electrocardiographic waveform and the pulse wave waveform, and the degree of relaxation may be calculated based on the LF and HF.
- the electrocardiogram waveform and the pulse waveform rise sharply at each heartbeat, high-frequency components increase at the rising portion when the electrocardiogram waveform and the pulse waveform are wavelet-converted. Therefore, the RR interval may be obtained from the fluctuation of the high frequency component, and the RR 50 may be calculated based on the RR interval to detect the degree of relaxation. 1-8-9-2: Preventing dozing
- Other examples are those that use the heart rate variability obtained from the measurement of the driver's ECG, and those that use the driver's respiratory variability.
- the dozing state may be detected by analyzing the arousal level of the human body from the result of the wavelet transform of the pulse wave waveform.
- the doze prevention device to which the wavelet transform is applied detects the doze state of the human body based on the correlation existing between the information contained in the pulse wave and the arousal level of the human body. At this time, some measured values obtained from the pulse wave are used as indices for judging the arousal state of the human body, and LF, HF, “LFZHF”, and RR50 are used as specific examples below. According to the above correlation, the state of the living body goes to a sedated state as the sleep becomes deeper, and it is considered that, for example, the value of RR50 gradually increases by falling asleep. Therefore, dozing can be detected by detecting changes in these indices.
- exerciser subject strength If this is the case, it is possible to exercise according to the exercise prescription, and it can be used to create a base for various competitions.
- the first is the exercise intensity that takes into account the physical and mental physical strength of the subject during exercise, and the exercise intensity of the training required to increase the endurance of the whole body.
- the present invention provides a motion index measurement device that notifies a quantified motion index, taking into account the subject's physical and mental physical strength in terms of the subject's exercise intensity.
- exercise indices that comprehensively take into account the physical and mental stamina of the subject during exercise, and can easily reach the training intensity required to increase whole body endurance Provide a measuring device.
- the present inventors conducted an experiment in which the running speed was changed stepwise and subjects collected various data in order to use it as an index of exercise intensity in ergometry. The results of this experiment will be described with reference to FIG.
- FIG. 1 (a) shows the relationship between the running speed and the number of beats in the ground running and the relationship between the running speed and the running pitch in the ground running on the same diagram. As shown in this figure, it can be seen that the subject's beat rate and running pitch increase with the running speed.
- FIG. 6B is a diagram showing the relationship between the running speed and the subject's subjective exercise intensity during ground running.
- the subjective exercise intensity is obtained by scoring what subjective sensation is involved when the subject runs at that speed, and as shown in Fig. 45, the subjective exercise intensity It is set to be high.
- Fig. 44 (b) it can be seen that as the running speed increases, the score indicating the subjective exercise intensity also increases, and the degree of "tightness" felt by the subject also increases.
- FIG. 3 (c) is a diagram showing the relationship between the running speed in ground running and the blood lactate concentration obtained by the earlobe blood sampling method. As shown in this figure, around point A, it can be seen that the blood lactate concentration of the subject starts to rise sharply.
- lactic acid is a fatigue substance, so if this concentration is increased, exercise cannot be sustained at a constant intensity. Conversely, if you only want to do sustained exercise, you should exercise at an intensity where the lactate concentration is low. On the other hand, even if the exercise intensity is such that the lactic acid concentration can be kept low, the effect of training cannot be expected if the exercise intensity is such that the subject feels comfortable. Therefore, if continuous exercise is performed in order to increase the endurance of the whole body, the exercise intensity should be in the region where the blood lactate concentration of the subject is low, and the exercise intensity that the subject feels "somewhat hard" It would be preferable to do so. Such exercise intensity corresponds to point A in the figure.
- the exercise intensity corresponding to the point A where the blood lactate concentration starts to increase is expressed as a relative intensity using the maximum oxygen intake, which is known to be approximately 50% V02 max Zwt. Is also known to be an appropriate exercise intensity for training to increase whole body endurance.
- the exercise intensity corresponding to point A is the exercise intensity that takes into account the physical and mental qualities of the subject during exercise, and should be used as an index when performing training to increase whole body endurance. It can be said that it is strength.
- the subject's exercise intensity can easily reach the exercise intensity necessary to increase the endurance of the whole body.
- the exercise index measuring device reports, as a target exercise index, an exercise intensity at which the subject's pulse rate and the running pitch are substantially the same.
- an index indicating how much the exercise intensity during actual exercise differs from the exercise intensity indicated by the exercise index is announced.
- the subject's pulse rate and pitch are compared. This is to notify a motion instruction in a direction to eliminate the difference.
- FIG. 42 is a block diagram showing the functional configuration.
- a pulse wave detection unit 211 is a sensor that detects a pulse waveform of a subject.
- the pulse wave waveform signal from the pulse wave detector 2 101 is converted into a digital signal by the AZD converter 2 102, and is further subjected to FFT (fast Fourier transform) processing by the FFT processor 103,
- the pulse rate is obtained from the processing result.
- the heart rate that is, the heart rate per unit time, is originally required, but since the heart rate is equal to the pulse rate, the obtained pulse rate is obtained indirectly as the heart rate. Therefore, the pulse wave detector 2101 may be configured to directly detect a heartbeat.
- the body motion detection unit 2111 is a sensor that detects the body motion in the motion of the subject, and is configured by, for example, an acceleration sensor.
- the body motion signal from the body motion detector 2 11 1 1 is converted into a digital signal by the AZD converter 2 1 1 2 in the same manner as the pulse wave waveform, and is further subjected to FFT processing by the FFT processor 1 13.
- the exercise pitch is obtained from the processing result. That is, the exercise in the present invention refers to a repetitive exercise having a rhythmic property performed at a constant period, and it is required how many times the repetitive exercise is performed per unit time. For example, in the case of running exercise, the number of steps per unit time (running pitch) is obtained, and in the case of swimming exercise, the number of strokes per unit time is obtained.
- the third storage unit 211 stores the set of the determined number of beats and the exercise pitch together with the passage of time and the exercise intensity.
- the determination unit 122 determines a point where the number of beats and the exercise pitch match each other from the contents of the third storage unit 212 and outputs the exercise pitch corresponding to the point as a target value. is there.
- the determination unit 2 122 determines that the point where the beat rate and the exercise pitch match each other is determined from the storage content of the third storage unit 2 121, but the determination is not limited thereto.
- the configuration may be such that the two are always compared and the coincidence point is detected.
- the determination unit 2 122 outputs the exercise pitch corresponding to the point where the beat number and the exercise pitch match each other, the determination unit 2 122 may output the beat number, or may output both.
- the second storage unit 2131 stores the weight of the subject, the amount of movement in one repetitive exercise, and the like.
- the stride is stored in the case of running exercise.
- the distance in one stroke is stored.
- the switch 2 1 3 2 is used to determine the movement pitch (input terminal a) set as the target value by the determination unit 2 1 2 2 or the current movement pitch (input terminal b) obtained by the FFT processing unit 2 13. Is selected, and the selection is instructed by the control unit 210.
- the exercise intensity calculator 2 1 3 3 calculates the exercise intensity from the exercise pitch, the amount of movement in one repetitive exercise, and the weight. Therefore, if the input terminal a is selected in the switch 2 1 3 2, the target exercise intensity is obtained.On the other hand, if the input terminal b is selected, when the subject actually exercises, Exercise intensity is now required. Here, if the form of exercise performed by the subject is running motion, the running speed is obtained by multiplying the running pitch of the subject and the stride, and the exercise intensity is obtained from the running speed and the weight of the subject. be able to.
- the exercise intensity can also be expressed using the number of beats.Therefore, the exercise intensity calculation unit 2133 inputs the number of beats obtained by the FFT processing unit 2103 instead of the running pitch. Alternatively, a configuration for calculating the exercise intensity may be used. If the exercise is running, the exercise intensity is defined as the running speed, which is the product of the running pitch and the stride, the product of the running speed and the number of beats, the product of the pitch and the number of beats, and the Since the product can be used, the exercise intensity calculation unit 2 1 3 3 may be configured to calculate these.
- the first storage unit 2 1 3 4 calculates the exercise intensity obtained by the exercise intensity calculation unit 2 1 3 3 when the input terminal a is selected, that is, the target exercise intensity.
- the data is stored together with the data indicating the date and time.
- the comparing unit 2141 compares the number of beats obtained by the FFT 210 3 with the exercise pitch obtained by the FFT processing unit 2113. The difference is obtained, and the degree of the difference in the number of beats or pitch is obtained, and grading is performed according to the degree.
- the comparing unit 2141 compares the number of beats obtained by the FFT 210 3 with the exercise pitch obtained by the FFT processing unit 2113. In comparison, a motion instruction to eliminate the difference between the two is obtained.
- the degree obtained by the comparison unit 2 141 in the fourth function indicates how much the exercise intensity at the current time differs from the target exercise intensity.
- Exercise instructions required by the function 5 are indices for approaching the target exercise intensity.
- the notification section 2 151 includes the storage contents of the first storage section 2 134, the storage contents of the third storage section 2 121, the calculation results of the exercise intensity calculation section 2 133, and the comparison section 2 Based on the comparison results of 141, the following announcements are mainly made.
- the notification unit 2 151 has a first function of displaying the set of the determined number of beats and exercise pitch in association with the passage of time, and a second function of notifying and displaying the target exercise intensity. And a third function that displays the intensity of the exercise performed by the subject at this time, and a fourth function that notifies and displays how the current exercise intensity differs from the target exercise intensity.
- the function and the fifth function that announces the instruction to approach the target exercise intensity with respect to the current exercise intensity, and the exercise intensity obtained by the second function And a sixth function that indicates whether progress has been made.
- control unit 211 controls the operation of each unit.
- FIG. 43 is a block diagram showing the configuration.
- a CPU 2201 performs control of each unit via a bus B, execution of various processes, calculation, and the like based on a basic program stored in a ROM 2202. 2103, 2113, judgment unit 2122, exercise intensity calculation unit 2133, comparison unit 2141, and control unit 2160.
- the RAM 2203 stores the set of the determined number of beats and exercise pitch in association with the lapse of time after the start of the exercise, and various data used in the control by the CPU 2201, for example, data such as the weight of the subject and the stride. Is temporarily stored, and corresponds to the first storage unit 2134, the second storage unit 2131, and the third storage unit 2121 in FIG.
- the sensor interface 2204 samples each analog output signal from the pulse wave detector 2101 and the body motion detector 211 at predetermined intervals, converts the analog output signal into a digital signal, and outputs it. 42 corresponds to the A / D conversion units 2102 and 2112 in FIG.
- the clock circuit 2205 has a function of transmitting an interrupt signal to the CPU 2201 at predetermined time intervals, in addition to a normal clocking function.
- the operation unit 2206 is for inputting the weight of the subject and the stride length, and for selecting and setting various functions (modes), and includes various button switches as described later.
- the display unit 2210 displays various information under the control of the CPU 2201, and is configured by, for example, an LCD (liquid crystal display panel).
- the alarm unit 208 generates an alarm sound under the control of the CPU 2201, and notifies the subject of various state changes.
- the display unit 2210 and the alarm unit 2208 correspond to the notification unit 2151 in FIG.
- the I / I interface 2209 has an LED and a phototransistor, which will be described later, and exchanges information with an external device.
- the motion index measuring device Although a mode can be considered, it is desirable to use a mode in which the subject is not conscious of wearing when exercising. For this reason, the appearance of the motion index measurement device is the same as that of the pulse wave diagnostic device described in Chapter 1 (see Fig. 2).
- the first to sixth functions described above are executed as one function of the wristwatch shown in FIG.
- the above-described pulse wave detection unit 2101 is configured as a pulse wave detection sensor unit 130 shown in FIG.
- button switches 116 and 117 are provided on the surface of the apparatus main body 110 on the lower and upper sides of the display unit 210, respectively. Among them, the button switch 117 is used to increment the set value by one in correcting the time, date, weight, and stride values. On the other hand, button switch 1 16 is used to reduce the set value by one in correcting the time, date, weight and stride values.
- FIG. 46 is a diagram showing an external configuration in which the connector piece 80 is removed from the connector part 70.
- an LED 507 and a phototransistor unit 508 are provided inside the connector part 70. Optical communication with external devices. That is, the LED 507 and the phototransistor 508 form a part of the IZO interface in FIG.
- the external device consists of a device main body 600, a display 601, a keyboard 602, a printer 603, etc., and is different from a normal personal computer except for the following points. Are the same.
- the device body 600 incorporates an optical interface including a transmission control unit and a reception control unit (not shown) for transmitting and receiving data by an optical signal.
- the transmission control unit has an LED 604 for transmitting an optical signal
- the reception control unit has a phototransistor 605 for receiving an optical signal.
- a near-infrared type for example, one with a center wavelength of 940 nm
- a filter for cutting off visible light for blocking visible light is provided on the front of the device main body 600 to form a communication window 606 for optical communication.
- the device main body 110 of the exercise index measuring device and the external device exchange information with each other by optical communication.
- the details of the information transfer will be described in the section on operations.
- the device main body 110 has various functions, the operation will be described for each of these functions.
- the exercise performed by the subject will be described as a running exercise, but the present invention is not limited to this.
- the operation when the first function (that is, the function of displaying the set of the determined number of beats and the running pitch in association with the passage of time) will be described.
- the CPU 2201 in FIG. 43 executes the basic processing 1 shown in FIG. After the execution, the interrupt processing 1 shown in FIG. 49 is periodically executed.
- step S a 1 the CPU 2201 inputs the body motion signal detected by the body motion detector 21 11 through the sensor interface 2204, performs an FFT process on the signal, and the subject actually starts running. Is determined. If the CPU 2201 determines that exercise has not started, it returns the processing procedure to step Sa1 again. That is, the processing procedure waits at step Sa1 until the subject starts running. Actually, when the subject starts running, the CPU 2201 clears the value of the register n to zero in step Sa2, and then permits the execution of the interrupt processing 1 in step Sa3. After that, the basic processing 1 is completed.
- the interrupt processing (1) is processing that is periodically executed, for example, every one minute by an interrupt signal from the clock circuit 222.
- step S11 the CPU 221 increments the register n by "1". Since the register n has been cleared to zero in the above-described step Sa2, the content indicates how many times the interrupt processing 1 has been executed after the subject started exercising. Further, since this interrupt processing (1) is executed at regular intervals, the register n indicates indirectly the lapse of time after the start of exercise.
- step Sa12 the CPU 222 reads the pulse wave signal detected by the pulse wave detector 211 through the sensor interface 222, and then performs FFT processing. Then, the subject's pulse rate, that is, the pulse rate [beat Z minutes] is obtained. Subsequently, in step Sa 13, the CPU 222 reads the body motion signal detected by the body motion detection unit 111 via the sensor interface 204, and performs FFT processing on the signal.
- the running pitch of the test subject is calculated.
- the exercise pitch in this case, the running pitch
- step Sa14 the CPU 2201 pairs the obtained beat count with the running pitch and stores the pair in the RAM2203 in association with the current value of the register n. For this reason, the detected beat count and the running pitch are accumulated and stored in the RAM 2203 every time the interrupt processing 1 is executed.
- step Sa 15 the CPU 222 reads out all the stored beats and running pitches from the RAM 220 3, and in step Sa 16, displays
- the section 2 210 is plotted with the read beat count and running pitch on the y-axis and the corresponding register value n on the x-axis, and is controlled to perform a two-dimensional display.
- Figure 56 shows an example of this display.
- the value of the register n indicates the lapse of time after the start of the exercise, such a display shows how the number of beats and the running pitch have changed after the start of the exercise. It will be shown as 0. Therefore, the subject can know how his or her own beat rate and running pitch are fluctuating.
- the form of the exercise index measuring device is a wristwatch type as shown in FIG.
- the display capability of the display unit 210 is necessarily limited. For this reason, as described later, it is preferable to transmit the read information to an external device and analyze it there.
- the CPU 2201 ends the current interrupt process 1 in preparation for the next execution.
- the first function executed by the functional configuration shown in FIG. 42 that is, the number of beats stored in the third storage unit 121 and
- the function of displaying the running pitch in association with the passage of time after the start of exercise is equivalently executed by the internal configuration in FIG.
- the CPU 222 in FIG. 43 executes the basic processing ⁇ shown in FIG. Subsequently, the interrupt processing 1 shown in FIG. 51 is periodically executed.
- This basic processing (1) sets information prerequisite for displaying the target exercise intensity, and permits the interrupt processing (2).
- step Sb1 the CPU 2201 executes an initial setting process such as securing a necessary area in the RAM 2203 or clearing the area.
- step Sb2 the CPU 2201 moves to one repetitive motion. It is determined whether information such as the momentum and the weight of the subject is set in the RAM 2203. Since the exercise in the present embodiment is a running exercise, the CPU 2201 determines whether or not the information on the stride and the weight of the subject is set. In the present embodiment, when the second function is executed for the first time, since no information is set in the RAM 2203, the determination in step Sb2 is performed.
- the CPU 2201 reads out the set value from the RAM 2203 in step Sb3 and displays it on the display unit 210, and changes these values in the next step Sb4. A message is displayed that prompts the subject to select whether or not to do so.
- the CPU 2201 When the subject gives an instruction not to change, the CPU 2201 resets the above information to the RAM 2203 as a default value in step Sb5.
- step Sb6 determines whether the information has been input. If not, the process returns to step S b 6 again. That is, the processing procedure waits in step Sb6 until the subject's stride or weight is input. When these pieces of information are input and changed, the CPU 2201 sets those values in the RAM 2203 in step S7.
- the subject operates the button switch 111 to set the operation mode of the apparatus main body 110 to the 'change mode'.
- the subject does not operate the potan switch 111 for a certain period of time.
- the subject sets the input 'change mode', and further changes the 'input target' with the button switch 514. After setting, it is conceivable to raise or lower the target value by one with button switch 111 or 116.
- step Sb8 the CPU 2201 determines whether the subject has actually started exercising and determines that the subject has not started exercising in the same manner as in step Sal in the basic processing 1. Then, the process returns to step Sb8. That is, the processing procedure waits in step Sb8 until the subject starts exercising.
- the CPU 2201 permits the execution of the interrupt processing (1) in step Sb9, and ends the execution of the basic processing (2).
- the interrupt processing (1) is processing that is periodically executed, for example, every two minutes by an interrupt signal from the clock circuit 205.
- step Sb11 the CPU 2201 obtains the subject's beat rate [minutes], and then obtains the subject's running pitch [time Z] in step Sb12. In this respect, it is the same as Steps Sa12 and Sa13 in the interrupt processing I. Subsequently, in step Sb13, the CPU 2201 multiplies the subject's stride stored in the RAM 2203 by the traveling pitch detected in the immediately preceding step to calculate the subject's traveling speed.
- step Sb14 the CPU 2201 stores the detected number of beats and the running pitch in the RAM 2203 in association with the running speed.
- the second function is to display the exercise intensity at the point where the beat rate and the running pitch meet as a target value.
- the beat rate and the running pitch are two points at different running speeds. Unless required, the matching point cannot be determined.
- step Sb16 ⁇ Sb22 the CPU 2201 determines that at least two sets of the number of beats and the running pitch are stored in step Sb15 and that their running speeds are not the same value, the following step Sb16 ⁇ Sb22 is executed.
- step Sb15 the CPU 2201 firstly determines the number of beats stored in the RAM 2203 in step Sb16. All the running pitches are read. Second, a regression line for the number of beats corresponding to the running speed is obtained, and similarly, a regression line for the running pitch corresponding to the running speed is obtained. Third, the intersection of the regression line of the pulse rate and the regression line of the traveling speed is determined, and the point at which the pulse rate and the traveling pitch are synchronized is obtained.
- the CPU 2201 obtains a running pitch corresponding to the obtained intersection (step Sb17), and controls the alarm unit 2208 to generate an alarm sound corresponding to the running pitch as a motion index (step Sb17).
- the alarm sound may correspond to the frequency of the running pitch, such as “beep, beep, beep”.
- the notification is not limited to the display but may be performed in various forms, such as voice synthesis and the intensity of an alarm sound.
- the CPU 2201 obtains a running speed corresponding to the obtained intersection (step Sbl9), and calculates an exercise intensity corresponding to the running speed (step Sb20). This calculation may be obtained by, for example, multiplying the running speed by the weight of the subject stored in the RAM 2203, or may be obtained from the relationship between the running speed and the exercise intensity. Then, the CPU 2201 stores the calculated exercise intensity in the RAM 2203 in association with the date of the running exercise (step Sb21), and displays the obtained exercise intensity as a target exercise index on the display unit 2210. (Step Sb22).
- the exercise intensity obtained in this way is a value at the point where the pulse rate and the running pitch are synchronized, and should be used as an index when exercising to increase the endurance of the whole body.
- the exercise intensity is obtained from the physical exercise intensity of the subject as in step Sb20, the absolute intensity of the exercise can be obtained, which is convenient for performing various comparisons. good.
- the target exercise intensity and the running pitch are indicated by the alarm unit 2208 during exercise.
- the target exercise can be achieved, which is more convenient. Therefore, in the interrupt processing (2), as described above, both the running pitch and the physical exercise intensity are notified and displayed as the exercise index.
- the exercise index may be the number of beats, and any of these may be selected to be notified and displayed.
- the subject when notifying both the pulse rate and the running pitch as the exercise index, the subject can increase or decrease the intensity of the running exercise by setting the pulse rate notified as the exercise index as the priority target and the running speed.
- the exercise intensity can be expressed as the running speed, which is the product of the running pitch and the stride, the product of the running speed and the beat, the product of the pitch and the beat, the product of the stride and the beat May be used, and these may be notified and displayed as a motion index. Since such a motion index is an index for performing efficient running, the subject may run using this as a target value.
- step Sb22 executes the current interrupt processing to prepare for the next execution. To end.
- this interrupt processing 1 is executed at regular intervals, and each time, the number of beats and the pitch stored in the RAM 222 increase. Therefore, if the traveling speed is divided into at least two stages, an opportunity will be given as the determination result of step Sb15 "Yes", and the driving index will be announced and displayed.
- the subject operates the button switch 1 1 1 to execute the third function.
- the CPU 222 in Fig. 43 executes the basic processing (3) and then periodically executes the interrupt processing (3) shown in Fig. 52.
- the basic processing (3) in this case is the same as the basic processing (2) shown in Fig. 50.
- the basic processing 3 sets information necessary for the exercise intensity calculation, sets the mode for executing the third function, and when the subject actually starts exercise, the interrupt processing 3 This is a process for permitting periodic execution.
- the CPU 2201 obtains the subject's pulse rate [beat Z] in step Sc11, and then obtains the subject's running pitch [time Z] in step Sc12. In this respect, it is the same as steps Sa12 and Sa13 in interrupt processing I.
- step Sc 13 the CPU 222 multiplies the subject's stride stored in RAM 220 3 by the running pitch detected in the immediately preceding step to calculate the subject's running speed.
- step Sc14 an exercise intensity corresponding to the running speed is obtained. This calculation is the same as in the previous step S b 20.
- step Sb21 the CPU 2201 displays the obtained exercise intensity on the display unit 210.
- the exercise intensity displayed in this way was obtained at the execution timing of the interrupting process 3 for the running exercise actually performed by the subject. That is, it indicates the intensity of the running exercise actually performed by the subject.
- the execution interval of this interrupt processing 3 is the exercise intensity sampling interval.
- the fourth function that is, the function to display how much the intensity of the exercise performed by the subject differs from the target exercise intensity. The work will be described.
- the CPU 222 in FIG. 43 executed the basic processing 1 shown in FIG. 53. After that, the interrupt processing 1 shown in Fig. 54 is periodically executed.
- the basic processing 4 is the same as the basic processing ⁇ shown in FIG. 48 except that step S a 2 is omitted.
- the basic processing ⁇ ⁇ ⁇ ⁇ when the fourth function is executed is set to a mode for executing the function, and when the subject actually starts running exercise, the periodic execution of the interrupt processing ⁇ is permitted. This is the processing to be performed.
- the CPU 221 determines the subject's pulse rate [beat Z] in step Sd11, and then determines the subject's running pitch [time] in step Sd12. In this respect, it is the same as steps Sa12 and Sa13 in interrupt processing I.
- the CPU 2201 calculates the degree G by the following equation from the obtained number of beats and the running pitch.
- step S d 14 the CPU 2 201 causes the display unit 2 210 to display a value corresponding to the value of the degree G, and then prepares for the next interrupt processing to prepare for the next execution. To end.
- the degree G obtained here indicates the ratio of the difference between the number of beats and the running pitch to the running pitch.The closer the value is to zero, the more the exercise intensity at that time increases the endurance. This indicates that the intensity is appropriate when training is performed. If the sign of degree G is minus, it indicates that the exercise intensity at that time is low for performing the training, while if the sign of degree G is plus, the exercise at that time is Indicates that the intensity is high to perform the training.
- the display content of the display unit 220 is such that the sign of the degree G and the magnitude of its value can be intuitively understood, as shown in FIG. 57, for example.
- This allows the subject to know whether or not the exercise intensity (running speed) at the current time is appropriate or not, as compared to the intensity of training to increase endurance. For example, to achieve the training intensity, how much exercise intensity It is also possible to know quantitatively whether it is necessary to increase or decrease.
- the up arrow promotes an increase in strength
- the down arrow promotes a decrease in strength
- the number of arrows indicates the degree of increase or decrease. Further, in this case, not only the display but also a configuration in which notification is made in various modes such as voice synthesis and the intensity of an alarm sound can be considered.
- the fourth function executed by the functional configuration shown in Fig. 42, that is, how much the exercise intensity at the current time is relative to the target exercise intensity
- the function of notifying / displaying the difference is equivalently and periodically executed by the internal configuration in FIG.
- the basic processing (1) in this case is the same as the basic processing (2) shown in FIG.
- the basic processing ⁇ ⁇ ⁇ ⁇ when the fifth function is executed is set to a mode for executing the function, and when the subject actually starts running, the periodic execution of the interrupt processing ⁇ is permitted. This is the processing to be performed.
- step S e11 the CPU 222 obtains the number of beats of the subject [for beat Z], and then in step S e12, obtains the running pitch of the subject [for Z times]. In this respect, it is the same as steps Sa12 and Sa13 in interrupt processing I.
- step Se 13 the CPU 2201 compares the obtained beat count with the running pitch. Then, if the beat count is smaller than the running pitch, the CPU 222 causes the display unit 210 to instruct the display section 210 to increase the pitch in step Se 14.
- step Se 15 the display unit 210 is instructed to maintain the running state, while the number of beats is If it is larger than the switch, in step Se 16, the instruction to reduce the stride is given to the display unit 2 210, and then the current interrupt processing ⁇ is finished in preparation for the next execution. .
- the case where the number of beats is smaller than the running pitch refers to the case where the running speed is low to perform training for increasing the whole body endurance, as can be seen from FIG. 44 (a). For this reason, it is necessary to notify the subject to increase the running speed.There are two ways to do this: an instruction to increase the running pitch and an instruction to increase the stride. Can be
- the case where the number of beats is greater than the running pitch means the case where the running speed is high for training to increase the endurance of the whole body, as can be seen from the figure. For this reason, it is necessary to notify the subject that the running speed should be reduced.Instructions to lower the running pitch and instructions to reduce the stride are given in two ways. Conceivable.
- the traveling pitch in the region where the traveling speed is high has not changed much compared to the increase in the traveling speed.
- the running speed is increased mainly by increasing the running pitch, but in a high running speed region, it is mainly performed by increasing the stride length.
- the number of beats in the region where the running speed is low fluctuates more rapidly than when the running pitch increases.
- the exercise corresponding to the running speed Since it is shown that the intensity is appropriate as the training intensity for performing the continuous exercise, it was decided to give an instruction to maintain the running state. In this case, the number of beats and the running pitch do not necessarily need to be the same in consideration of the measurement error. good.
- the difference between the two is extremely large, it may be instructed to change both the running pitch and the stride without making a determination as in the present embodiment.
- the fifth function executed by the functional configuration shown in FIG. 42 that is, the exercise intensity at the present time is brought closer to the target exercise intensity.
- the function of notifying the user of the instruction is equivalently and periodically executed by the internal configuration in FIG. Therefore, the subject can easily reach the target exercise intensity, that is, the optimal intensity when performing the continuous exercise, by performing the running exercise in accordance with the instruction content by executing the fifth function. .
- the CPU 2 201 When the subject operates the button switch 1 1 1 to set the mode to execute the sixth function, the CPU 2 201 in FIG. Secondly, all the stored exercise intensities are read out. Secondly, the display unit 210 is plotted with the read out exercise intensity on the y-axis and the corresponding date on the X-axis, thereby performing a two-dimensional display. Control.
- the exercise intensity displayed here is a value that synchronizes the pulse rate and the running pitch when the running is performed, and is a value used as an exercise index. It has the property of varying at the level. Therefore, when the exercise intensity is displayed in correspondence with the date, the training effect of the subject can be known with time.
- the first to sixth functions are individually executed, but after the subject starts exercising, all of the first to sixth functions are selected or selected. Then, the configuration may be such that the subject selects and executes the execution results.
- the fourth and fifth functions have similar processing contents, and are therefore desirably executed simultaneously.
- the subject when communicating with an external device, the subject removes the connector piece 80 from the connector section 70 of the device main body 110, exposes the LED 507 and the phototransistor 508, and faces the communication window 606 of the external device. .
- the following describes the function of transmitting information to an external device and the function of receiving information from an external device.
- the CPU 2201 in FIG. 43 stores in step S a 14 when the first function is executed.
- the information thus obtained that is, the information on the number of beats and the running pitch associated with the lapse of time after the start of the running exercise, is transmitted to the device body 600 via the IZO interface 2209 and the optical interface of the external device. Send.
- an optical communication protocol an IrDA (Infrared Data Association) method or the like can be used.
- the external device can determine how the subject's pulse rate and running pitch have changed since the start of running, as well as the subject, a trainer, a doctor, etc. Third parties can objectively know and accumulate and analyze such information.
- the information to be transmitted is not limited to this, and may be, for example, the information stored in step Sb21.
- the fifth function is executed in the external device.
- a target value in a running exercise for example, a running pitch
- the exercise index measuring device includes an external device.
- the target value set in the step is received and used as the target value when the subject actually starts running.
- the CPU 222 in FIG. 43 sends a signal indicating a request to the external device via the IZO interface 220 and the optical interface of the external device. To send.
- the main body 600 of the external device transmits information to be the set target value via the optical interface of the external device and the IZO interface 220.
- the CPU 2201 temporarily stored the received information in the RAM 2203, and the subject actually started running.
- the target value corresponding to the lapse of time after the start of traveling is read out and notified to the subject.
- the target value is the running pitch
- the degree of difference between the announced target value and the actual running pitch in the running motion is graded as in the fourth function. It may be displayed.
- the subject can perform the running exercise at the set running pitch even when the exercise is performed for a long period of time, and can be used for training and in creating a pace in competitions.
- the exercise index measuring device it is possible to execute the first to sixth functions and the communication function.
- the exercise intensity that should be used as an index when exercising to increase the endurance of the whole body, and the physical and mental physical strength of the subject during exercise By performing the fourth function, the exercise intensity at the present time can be quantified as to how much the exercise intensity should be to increase the endurance of the whole body.
- the fifth function it is possible to give an instruction to bring the exercise intensity at the current time closer to the target exercise intensity.
- the motion indices required in the second function are physical indices and physiological indices, such as the product of the running speed and the pulse rate, the product of the running pitch and the pulse rate, and the product of the stride and the pulse rate.
- Target finger If the notification is made based on the product of the markers, it is possible to comprehensively evaluate the physical indicators and the physiological indicators. Specifically, even if a goal is completed in the same course at the same time, the physiological index changes depending on the physical condition, so the overall evaluation with the physical index is performed. That is, the physical index and the physiological index can be evaluated with one new index.
- the exercise index measuring device has a wristwatch structure, but the present invention is not limited to this.
- the glasses type see Fig. 34
- necklace type see Fig. 35
- card type see Fig. 36
- pedometer type see Fig. 37
- the execution results of the first to fifth functions are all displayed on the display unit 220, but the present invention is not limited to this as described above. . That is, the display is not limited to the display relying on the visual sense, and can be notified in various modes. In that sense, the announcement in the present invention means something that appeals to the five senses. For example, a configuration may be adopted in which the target running pitch, the number of beats, etc. are notified by appealing to the tactile sensation by vibration or the like, or a configuration in which the result to be announced is appealed to the auditory sense by speech synthesis to be announced.
- the striding in the running exercise is considered to be short, although some individual differences may be considered.
- the stride is constant because the value set in RAM 220 3 is used as it is despite the fluctuation of the pitch. Such characteristics in running motion are not taken into account. Therefore, in this regard, the first embodiment has a disadvantage that the operation result involving the stride tends to be inaccurate.
- a table showing the relationship between the pitch and the stride correction coefficient is obtained and stored in advance, while the stride is used in the running motion.
- the stride correction coefficient corresponding to the pitch at that time is read from the table, and is corrected by multiplying the set stride to solve the above-mentioned disadvantage.
- the configuration of the motion index measuring device is as shown in FIG. 58, and is a configuration in which a table 21 35 and a correction unit 21 36 are added to the configuration shown in FIG. It has become.
- the table 2 135 stores the pitch and the stride correction coefficient in advance, and outputs the stride correction coefficient corresponding to the pitch obtained by the FFT processing section 2 113.
- 2 1 3 6 corrects the stride in accordance with the pitch by multiplying the stride stored in the second storage 1 3 1 by the stride correction coefficient output by the FFT processing section 2 1 1 3. You.
- Table 2 135 corresponds to RAM 220 3 in FIG. 43, and correction section 213 36 has a configuration corresponding to CPU 220 1. There are substantially no additional components in 3.
- the reference pitch refers to a pitch in a case where the stride in the running exercise becomes an input stride (reference stride).
- This editing function is performed as follows.
- the subject measured the stride when the pitch was increased stepwise by, for example, 10% with respect to the reference pitch, and determined the percentage of the stride compared to the reference stride. Keep it.
- the subject inputs these ratios and the ratios to the reference pitch to the apparatus main body 110 using, for example, button switches 111 to 114.
- CPU 222 performs the following operation. That is, CPU 2 2 0 1 plots the ratio of the input pitch and the ratio of the stride, and interpolates between these plots to obtain, for example, the characteristic shown by the broken line in FIG. A table is stored in a predetermined area of 03.
- the CPU 222 When the subject actually performs a running exercise and performs calculations using the stride stored in the RAM 2203, the CPU 222 firstly determines that the detected pitch is higher than the reference pitch. Secondly, a stride correction coefficient corresponding to the ratio is read out from the table, and thirdly, the coefficient is added to the reference stride read out from RAM2203. By multiplying, the stride corresponding to the running pitch is corrected. Fourth, in the calculation of the exercise intensity, the corrected stride is used.
- the stride is corrected, and the correction is performed in accordance with the characteristics of the subject.
- the operation can be performed more accurately.
- the corrected stride is associated with the current beat count and the running pitch, and is stored in association with the elapse of time after the start of the running. That is, the first function of the first embodiment is a function of displaying the corrected stride in addition to the number of beats and the running pitch after the start of running in the second embodiment. In the transmission function, the corrected stride is also transmitted to the external device.
- the stride can also be set as a target value for the running exercise by an external device in accordance with the passage of time.In the receiving function, the information of the set stride is received, and the subject actually receives the information. It is used as a target value when running motion starts.
- the stored contents of the table 2 135 may be the stride itself instead of the correction coefficient corresponding to the running pitch.
- the stride is corrected in accordance with the pitch in the running motion.
- the stride may vary not only in the pitch in the running motion but also in the number of beats.
- a configuration may be used in which a table in which the relationship between the number of beats and the stride correction coefficient is stored in advance, as in the case of Table 2 135
- the table may be two-dimensionally configured to store the stride correction coefficient with both of them as arguments (parameters).
- the number of beats obtained by the FFT processing unit 210 is supplied as an argument of the two-dimensional table 213.
- the exercise performed by the subject is run, but the present invention is not limited to this.
- the same effect can be obtained by using swimming as the exercise, inputting the stroke of one stroke in accordance with the running stride, and detecting the number of strokes per unit time in accordance with the pitch.
- a similar effect can be obtained by setting the movement as a table up / down, inputting the amount of lift once, and detecting the number of steps up / down per unit time.
- the present invention provides, as a new exercise index, the exercise intensity in which the beat rate and the exercise pitch are synchronized in all regular exercises performed at a constant rhythm, including movement exercises normally performed in daily life. .
- the exercise intensity is based on the physical and mental physical strength of the subject comprehensively during exercise, and the training for enhancing the whole body endurance is performed. It is possible to obtain and provide the exercise intensity to be used as an index when performing exercise.
- the training intensity when the subject's exercise intensity at the current time is a continuous exercise To determine whether it is appropriate or not, and if not, to quantify how much the exercise intensity must be increased or decreased to achieve training intensity for sustained exercise It is also possible to know.
- the stride is corrected according to the running pitch or the number of beats, so that the calculation result can be more accurate.
- the present inventors have repeatedly examined the index indicating the exercise intensity and found that there is a close relationship between the respiratory waveform and the exercise intensity. In this case, how to measure the respiratory waveform is an important issue.
- the frequency components of the fluctuations of the R-R cycle of the ECG of the subject in the resting state are analyzed. Then, there is a component corresponding to the respiration rate. Since the pulse wave is synchronized with the electrocardiogram, the fluctuation frequency component of the pulse wave period (or pulse wave amplitude) includes a component corresponding to the respiratory waveform.
- Japanese Patent Application Laid-Open No. Sho 62-22627 discloses a technique of measuring a series of pulse intervals, measuring a change cycle of these pulse intervals, and calculating a respiratory rate by a reciprocal of the change cycle. Have been.
- the first respiratory rate is detected based on the fluctuation period of the R-R interval of the electrocardiographic waveform or the fluctuation of the envelope of the peak value of the pulse waveform, and the subject's respiratory rate is detected.
- 6-142022 discloses a technique of multiplying a pulse rate of a subject sequentially obtained by a systolic blood pressure value and calculating a respiratory rate based on a pulsation cycle of the multiplied value.
- Japanese Utility Model Publication No. 6-222325 discloses a technique for determining a respiratory rate of a living body based on a change period of a curve connecting peak values of pulse waves.
- Chapter 3 provides an exercise intensity detection device that extracts the respiratory component from the pulse waveform and easily detects the exercise intensity based on this.
- FIG. 1 shows the respiratory waveform at rest (exercise intensity XI), and (b) shows the exercise intensity X 2 Fig. (C) shows the respiratory waveform at exercise intensity X3, Fig. (D) shows the respiratory waveform at exercise intensity X4, and exercise intensity XI to X4 has the following relationship .
- the respiratory waveform approaches a sine wave, it means that a harmonic component with respect to the fundamental component is reduced.
- the respiratory waveform changes from a sawtooth wave to a sine wave, so the third harmonic component decreases as the exercise intensity increases.
- an index of exercise intensity can be obtained by frequency analysis of the respiratory waveform.
- exercise intensity is detected by extracting a respiratory component from a pulse wave waveform and performing frequency analysis of the respiratory component.
- FIG. 61 is a functional block diagram of the exercise intensity detecting apparatus according to the present embodiment.
- f 31 is a pulse wave detecting means, which detects a pulse wave waveform from a detection part of a living body.
- f32 is a body movement detecting means for detecting a body movement waveform indicating body movement of a living body.
- An example is an acceleration sensor.
- F 33 is a body movement removing means, which generates a body movement component in the pulse wave waveform based on the body movement waveform, and removes the body movement component from the pulse wave waveform to generate a body movement removed pulse wave waveform. Generate. Specifically, appropriate waveform processing is performed on the body motion waveform, and this is subtracted from the pulse wave waveform, or the frequency spectrum of the pulse wave waveform and the frequency spectrum of the body motion waveform are each analyzed. By removing a signal having the same frequency as the frequency spectrum of the body motion waveform from the frequency spectrum of the pulse wave waveform, a body motion removal waveform can be generated.
- f34 is a respiratory component extracting means, which extracts a respiratory component based on the pulse wave waveform from which the body motion has been removed.
- the respiratory component extracting means f34 includes, for example, a wavelet transform unit that performs a wavelet transform on the pulse waveform of the body motion removal to generate a pulse wave analysis data of the body motion removal, and a pulse A respiratory waveform analysis unit that generates respiratory waveform analysis data by removing a frequency component corresponding to the wave component, performs an inverse wavelet on the respiratory waveform analysis data, and generates a respiratory waveform as the respiratory component.
- f35 is a fortitude intensity generating means, which calculates exercise intensity based on the respiratory component extracted by the respiratory component extracting means. In this case, the exercise intensity can be calculated based on the ratio of the frequency component obtained by performing the frequency analysis on the extracted respiratory component.
- the external configuration of the exercise intensity detector 3 is the same as the pulse wave diagnostic device described in Chapter 1 (see Fig. 2). That is, the exercise intensity detecting device 3 includes a device main body 110 having a wristwatch structure, a cable 120 connected to the device main body 110, and a pulse wave detecting sensor unit 130 provided on the distal end side of the cable 120. It is roughly composed of
- the circuit configuration of the pulse wave detection sensor unit 130 functioning as the pulse wave detection means f31 is the same as that of the pulse wave diagnostic device described in Chapter 1 (see FIG. 3).
- FIG. 62 shows the electrical configuration of the first embodiment.
- reference numeral 310 denotes a pulse wave detection unit, which corresponds to the above-described pulse wave detection sensor unit 130.
- Pulse wave detecting section 310 detects pulse wave waveform MH indicating the magnitude of the pulsation.
- Reference numeral 311 denotes a body motion detecting unit, which is constituted by, for example, an acceleration sensor and is provided inside the watch case 200.
- a body motion waveform TH indicating a body motion caused by the swing of the arm during running or the like is detected.
- Reference numeral 312 denotes a waveform processing unit for performing a constant waveform processing on the body motion waveform TH
- reference numeral 313 denotes a body motion removing unit.
- the reason why the waveform processing is performed is that the body motion removing unit 313 accurately removes the body motion component.
- MHt body motion component in the pulse wave waveform MH
- MH ' true pulse wave component (body motion removal pulse wave waveform)
- MH MHt + MH'.
- the body movement waveform TH is detected, for example, as the acceleration itself of the swing of the arm.
- the body movement component MHt becomes a dull body movement waveform TH.
- the waveform processing unit 312 is configured with an appropriate mouth-to-pass filter.
- the format of the low-pass filter and the coefficients are calculated from the values obtained by experiments.
- the body motion component MHt can be obtained from the body motion waveform TH.
- the body motion removing unit 313 generates a body motion removing pulse wave waveform MH 'by subtracting the body motion component MHt from the pulse wave waveform MH.
- reference numeral 314 denotes a respiratory component extraction unit, which comprises a CPU (central processing unit), an AZD converter, and the like.
- the pulsating pulse wave waveform MH ' is converted from an analog signal to a digital signal by an AZD converter, and is then captured by the CPU as a pulsating pulse wave MH'. I'm sorry.
- Respiratory component extraction section 314 performs frequency analysis by performing FFT processing on body motion removal pulse wave data MH ′.
- FIG. 63 is a view schematically showing a simplified result of performing FFT processing on the pulse wave data MH 'for removing body motion.
- the maximum peak frequency in the low frequency region LF is the fundamental frequency FV 1 of the respiratory component
- the maximum peak frequency in the high frequency region HF is the fundamental frequency component Fml of the pulse wave.
- FIG. 64 is an enlarged view of the low frequency region LF in FIG. 63. From this figure, it can be seen that the respiratory component consists of its fundamental frequency Fvl and harmonics Fv2, Fv3, Fv4 ...
- the respiratory component extraction unit 314 first performs FFT processing on the body motion removal pulse wave waveform MH 'to specify the maximum peak frequency. Since the fundamental wave component of the pulse wave is maximum, Fml is specified as the maximum peak frequency. After that, the maximum peak frequency is specified in the frequency range lower than Fml.
- the fundamental frequency Fvl of the respiration component is specified here. Thereafter, the respiratory component extraction unit 314 detects the level L1 of Fvl and the levels L2, L3, L4,... Of the harmonic frequencies Fv2, Fv3, Fv4,. What In this example, the harmonic frequency is limited to those less than Fml. This is because a pulse wave component exists above Fml, and if Fml is an integral multiple of Fvl, the respiratory component cannot be separated.
- reference numeral 315 denotes an evaluation unit, which comprises CPU, ROM, and the like.
- CPU calculates the distortion factor K of the respiratory waveform based on L1, L2, L3, L4, etc. detected by the respiratory component extraction unit 314.
- the distortion factor K is calculated according to the following calculation formula.
- the inhalation time is longer than the discharge time, but as the exercise intensity X increases, the difference between the inhalation time and the discharge time decreases, and the respiratory waveform gradually approaches a sine wave.
- the respiratory waveform becomes significantly disturbed. That is, as long as the exercise intensity X does not exceed a certain limit, as the exercise intensity X increases, the ratio of the harmonic component to the fundamental component decreases. When the exercise intensity X exceeds a certain limit, the ratio of the harmonic component to the fundamental component suddenly increases. This means that the strain rate K of the respiratory waveform has a fixed relationship with the fork intensity X.
- the strain rate K decreases as the exercise intensity X increases, and the strain rate K decreases when the exercise intensity X exceeds a certain limit. It means a surge. Therefore, if the relationship between the strain rate K and the exercise intensity X is determined in advance, the exercise intensity X can be determined from the distortion rate K.
- the exercise intensity X is stored in the ROM in association with the distortion rate K. Therefore, the exercise intensity X can be calculated by accessing the ROM with the distortion rate K as an address. In this sense, ROM functions as an exercise intensity table.
- the fortune intensity X may be graded in five or three levels. In this case, the exercise intensity X stored in the ROM may be represented by a predetermined number of steps.
- reference numeral 316 denotes a display unit, and the above-described liquid crystal display device 210 corresponds thereto.
- the display unit 316 may display the exercise intensity X as a numerical value as it is, or may display it as a bar graph or the like using a dot display area. Further, when grading is performed on the exercise intensity X in the evaluation unit 3 16, characters or symbols corresponding to the grade may be displayed. For example, the exercise intensity for walking is X1, the exercise intensity for jogging is X2, the exercise intensity for sprinting is X3, and the exercise intensity is high.
- XI is "light exercise.”
- X2 is “moderate exercise.”
- X3 is “strong exercise.”
- X4 "Dangerous.” Is displayed.
- the exercise intensity X may be displayed in association with a face chart as shown in FIG.
- FIG. 66 is a flowchart showing the operation of the first embodiment.
- the pulse wave detection unit 310 detects the pulse waveform MH ( Step S 2).
- Step S3 the waveform processing section 312 performs waveform processing on the body movement waveform TH (Step S4). Since this waveform processing is a process of converting the body motion waveform TH into the body motion component MHt in the pulse wave waveform MH as described above, by subtracting the body motion component MHt from the pulse wave waveform MH, The body movement removal unit 313 generates a body movement removal pulse wave waveform MH '.
- respiratory component extraction section 313 performs frequency analysis by performing FFT on body motion removal pulse wave waveform MH ′. Then, based on the analysis result, the maximum peak frequency is specified among the frequency components of the body motion removal pulse wave waveform MH '(step S6). In this case, the fundamental frequency Fml of the pulse wave component is specified. Thereafter, the respiratory component extraction unit 313 detects the fundamental frequency Fvl of the respiratory component by specifying the maximum peak frequency less than F ml (step S7). Next, the respiratory component extraction unit 313 calculates a respiratory frequency component. Specifically, each harmonic frequency Fv2, Fv3, Fv4 ... is detected by multiplying the fundamental frequency Fvl by an integer, and the level L corresponding to each of the fundamental frequency Fvl and each harmonic frequency Fv2, Fv3, Fv4 ... Find 1, L2, L3, L4 ...
- the evaluation unit 315 calculates the distortion factor K of the respiratory frequency component based on the respiratory frequency components LI, L2, L3, L4, ... (Step S9).
- the relationship between the distortion rate and the exercise intensity X is stored in the ROM in advance.
- the exercise intensity X is obtained by accessing (step S10). Thereafter, the exercise intensity X is displayed on the display section 316, whereby the exercise intensity X is notified to the subject.
- the body motion detecting unit 311 and the waveform processing unit 3112 generate the body motion component MHt superimposed on the pulse wave waveform MH, and remove this. Therefore, the respiratory component extraction unit 314 can extract the respiratory component even during exercise.
- the exercise intensity X is calculated based on the distortion factor K of the respiratory component, the exercise intensity X can be easily known without burdening the subject.
- the configuration of the exercise intensity detecting device 3 according to the second embodiment of the present invention will be described with reference to the drawings.
- the external configuration of the exercise intensity detection device 3 according to the second embodiment is the same as that of the first embodiment.
- the electrical configuration of the exercise intensity detection device 3 according to the second embodiment is the same as that of the first embodiment shown in FIG. 62 except for the internal configurations of the respiratory component extraction unit 314 and the evaluation unit 315. This is the same as the exercise intensity detection device 3 related to the above.
- the respiratory component extraction unit 314 and the evaluation unit 315 will be described.
- FIG. 67 is a block diagram showing the internal configuration of the respiratory component extraction unit 314 and the evaluation unit 315 according to the second embodiment.
- the respiratory component extractor 314 includes a wavelet transform unit 320, a respiratory component generator 321 and an inverse wavelet transform unit 322.
- the wavelet transform unit 320 performs a well-known wavelet transform on the body movement eliminating pulse waveform MH 'output from the body movement removing unit 3113, and performs a body movement removing pulse wave analysis data—E MK. Generate D.
- the wavelet transform is defined by Equation 1 described in Chapter 1, and the wavelet transform unit 320 is configured to be able to calculate Equation 1.
- the main part of the wavelet transform unit 320 is configured similarly to the basis function expanding unit W shown in FIG.
- the pulse wave data MH 'obtained by obtaining the pulse wave waveform MH' obtained by removing the body motion via the AZD converter is supplied instead of the pulse wave data MD.
- the body motion removal pulse wave analysis data MKD is 0 Hz to 0.5 Hz, 0.5 Hz to: L. 0 Hz, 1.0 Hz to: 1.5 Hz, 1.5 Hz to 2.0 Hz, 2.
- the output is divided into frequency ranges such as 0 Hz to 2.5 Hz, 2.5 Hz to 3.0 Hz, 3.0 Hz to 3.5 Hz, and 3.5 Hz to 4.0 Hz.
- the respiratory component generation unit 321 compares the body motion-removed pulse wave analysis data MKD in each frequency region, specifies a region having the largest energy component, removes a frequency component higher than that, and Generate waveform analysis data VKD.
- the reason why the frequency region having the maximum energy component or higher is removed is that the fundamental frequency component of the pulse wave component exists in the frequency region having the maximum energy component.
- the body motion-removed pulse wave analysis data MKD is as shown in FIG. 68, in each of the periods t1 to t8, the region shown by the oblique lines in FIG. 69 is specified as the maximum energy component. In this case, the high frequency region beyond the region indicated by the diagonal lines is replaced with “0”, and the data shown in FIG. 70 is generated as the respiratory waveform analysis data VKD.
- Equation 2 described in Chapter 1 is calculated to generate respiratory waveform data VD, which is subjected to A / D conversion, and the respiratory waveform VH is output.
- respiratory component extraction section 314 extracts respiratory waveform VH based on body motion-removed pulse wave data MH '.
- the evaluation unit 315 includes a zero-cross comparator 323, a duty ratio detection unit 324, and an exercise intensity table 325.
- the zero-cross comparator 323 includes, for example, a capacitor C and an operational amplifier OP as shown in FIG.
- the value of capacitor C is set so that the respiratory waveform VH passes sufficiently.
- the operational amplifier OP generates the square wave S by comparing the respiratory waveform VH with the zero level, but since the respiratory waveform VH is supplied to the pair via the capacitor C, the square wave S is the average value level of the respiratory waveform VH. With the threshold Waveform shaping.
- FIG. 72 shows a circuit diagram of the duty ratio detection unit 324
- FIG. 73 shows a timing chart thereof.
- the clock signal CK (see FIG. 73 (a)) is supplied to one input of the gates 241 and 242, respectively.
- the other input of the gate 241 is supplied with the square wave S (see FIG. 73 (b)), and the other input of the gate 242 is supplied with the square wave S inverted by the inverter 240.
- the output signal of the gate 241 passes the clock signal CK only during the period when the square wave S is at the high level as shown in FIG. 73 (c).
- the output signal of the gate 242 allows the clock signal CK to pass only during the period when the rectangular wave S is at the one-level.
- the count value C1 of the count 243 is a high level period of the square wave S
- the count value C2 of the count 244 is a square wave. This indicates the low level period of S.
- the divider 245 calculates C1ZC2 and outputs this as a duty ratio. Note that the division operation is performed at time T shown in FIG. 73, and the counts 243 and 244 are reset immediately thereafter.
- the operation result DR approaches “1” as the exercise intensity X increases.
- the respiratory waveform is greatly disturbed, and the calculation result DR changes drastically at such exercise intensity X.
- the duty ratio of the respiratory waveform does not suddenly change.
- the configuration described below specifies the limit value Xmax of the exercise intensity X by detecting the continuity of the operation result DR, in other words, the continuity of the duty ratio.
- the operation result DR is supplied to and stored in the memory 246.
- the contents of the memory are as follows Is updated every time the calculation result DR is output.
- the comparator 248 determines whether the subtraction result ADR is within a predetermined range. Specifically, it is determined whether or not the following expression is satisfied.
- + K, 1 ⁇ is determined so that it can be determined whether the exercise intensity X exceeds the limit value Xmax and the continuity of the duty ratio of the respiratory waveform is lost.
- the combiner 249 outputs the operation result DR when the output signal of the comparator 248 is at a high level, and on the other hand, when the output signal of the comparator 248 is at a single level, a value that the operation result DR cannot take, for example, And “0” are output.
- the exercise intensity table 325 (see FIG. 67) is composed of a ROM or the like, in which the exercise intensity X is stored in association with the calculation result DR. Therefore, by accessing the exercise intensity table 325 with reference to the calculation result DR, the exercise intensity X can be obtained.
- the limit value Xmax is output.
- the respiratory waveform is extracted from the pulse waveform, and the exercise intensity X can be obtained from the duty ratio.
- FIG. 74 is a flowchart of the exercise intensity detection device 3 according to the second embodiment.
- the processing from step S1 to step S5 is the same as the operation of the first embodiment shown in FIG. 66, the body motion waveform is removed from the pulse wave waveform, and the body motion removed pulse wave waveform MH ′ Is generated.
- the wavelet transform unit 320 performs a wavelet transform process on the body motion removal pulse wave data MH ', and generates a body movement removal pulse wave analysis data MKD.
- the body motion removal pulse wave analysis data MKD includes a pulse wave component and a respiratory component, but the pulse wave component exists in a higher frequency region than the respiratory component, and the energy of the pulse wave component is the energy of the respiratory component. Large compared to. For this reason, the respiratory component generation unit 321 generates a respiratory waveform data VKD by replacing “0” in the body energy removal pulse wave analysis data MKD with a value equal to or higher than the maximum energy frequency region (step S21).
- the inverse wavelet transform unit 322 performs an inverse wavelet transform on the respiratory waveform data VKD to generate a respiratory waveform VH
- the zero-cross comparator 323 compares the respiratory waveform VH with its average level to obtain a square wave S Generate Thereafter, the duty ratio detection unit 324 detects the duty ratio of the rectangular wave S (Step S23).
- the display unit 316 displays the exercise intensity X (step S25). Thereby, the exercise intensity X is notified to the subject.
- the body motion detecting unit 311 and the waveform processing unit 312 generate the body motion component MHt superimposed on the pulse wave waveform MH and remove it. Therefore, the respiratory component extraction unit 314 can extract a respiratory waveform using wavelet transform even during exercise. Further, since the exercise intensity X is calculated based on the duty ratio of the respiratory waveform, the exercise intensity X can be easily known without burdening the subject.
- the configuration of the exercise intensity detection device 3 according to the third embodiment of the present invention will be described with reference to the drawings.
- the external configuration of the exercise intensity detection device 3 according to the third embodiment is the same as that of the first embodiment.
- the electrical configuration of the exercise intensity detection device 3 according to the third embodiment shown in FIG. 62 is the same as that of the exercise intensity detection device 3 according to the first embodiment shown in FIG. Is the same as
- FIG. 75 is a block diagram showing the configuration of the exercise intensity detection device 3 according to the third embodiment.
- reference numerals 30 and 31 denote a first FFT processing unit and a second FFT processing unit, which are constituted by a CPU or the like.
- the first FFT processing section 330 calculates the pulse waveform M Perform FFT processing on H to generate pulse wave analysis data MFD.
- second FFT processing section 331 performs FFT processing on body motion waveform TH to generate body motion analysis data TFD.
- the body motion removing unit 313 generates a spectrum frequency component corresponding to each spectrum frequency of the body motion analysis data TFD among the respective spectrum frequency components of the pulse wave analysis data MFD.
- pulse wave analysis data MKD for removing body motion.
- the maximum peak frequency in the low frequency region is the fundamental frequency Fvl of the respiratory component
- the maximum peak frequency in the high frequency region is the fundamental frequency of the pulse wave. Fml.
- the respiratory component extraction unit 314, the evaluation unit 315, and the display unit 316 are the same as those in the first embodiment, and a description thereof will not be repeated.
- FIG. 76 is a flowchart showing the operation of the exercise intensity detection device 3 according to the third embodiment.
- step S1 when the apparatus main body is set to the exercise intensity measurement mode (step S1), the pulse wave detector 3110 detects a pulse wave waveform MH. Thereafter, first FFT processing section 330 performs FFT processing on pulse waveform MH to generate pulse wave analysis data MFD (step S2).
- the second FFT processing unit 331 performs an FFT process on the body motion waveform TH, and performs the body motion analysis data. Generate TFD.
- FIG. 77 is a diagram illustrating an example of the relationship between the pulse wave analysis data MFD, the body motion analysis data TFD, and the body motion removal pulse wave analysis data MKD. The operation of removing the body motion will be described with reference to FIG. First, Figure 7
- Fig. 77 (b) shows the contents of body motion analysis data TFD.
- the body motion removing unit 3 13 uses the body motion analysis data TFD to calculate each spectrum frequency Ftl ⁇ shown in Fig. 77 (b).
- the body motion removing unit 3 13 The spectrum frequency components corresponding to the spectrum frequencies Ftl to Ft6 are removed from the spectrum frequency components, and the body motion removal pulse wave analysis data MKD shown in FIG. 77 (c) is generated.
- the body motion waveform TH is detected as, for example, the acceleration itself of the arm swing, but since the blood flow is affected by blood vessels and tissues, the body motion component of the pulse wave analysis data MFD and the body motion analysis data TFD Does not match.
- the spectrum frequency components corresponding to the spectrum frequencies Ftl to Ft6 differ between the pulse wave analysis data MFD and the body motion analysis data TFD. For this reason, in this example, instead of subtracting the body motion analysis data TFD from the pulse wave analysis data MFD, the spectrum frequency components corresponding to the spectrum frequencies Ftl to Ft6 are removed. As a result, it is possible to generate a body motion component sufficiently removed.
- the respiratory component extracting unit 313 specifies the maximum peak frequency among the respective spectral frequency components based on the body motion removal pulse wave analysis data MKD (step S35).
- the fundamental frequency Fml of the pulse wave component is specified.
- the pulse wave waveform MH and the body movement waveform TH are each subjected to the FFT processing to remove the body movement component, and thus the waveform processing described in the first embodiment is performed.
- the part 312 can be omitted.
- the respiratory component extraction unit 314 can extract a respiratory component even during exercise.
- the exercise intensity X is calculated by the evaluation unit 315 based on the distortion factor K of the respiratory component, the exercise intensity X can be easily known without burdening the subject.
- a body movement waveform is detected using the body movement detection unit 310, and based on the detected body movement waveform, the body Although the moving component is removed, the fourth embodiment removes the body moving component without using the body motion detecting unit 310.
- FIG. 78 shows the electrical configuration of the exercise intensity detection device 3 according to the fourth embodiment.
- the same components as those shown in FIG. 75 are denoted by the same reference numerals.
- the configuration is different from that of the exercise intensity detection device 3 of the third embodiment shown in FIG. 75 in that the body motion detection unit 311 and the second FFT processing unit 331 are not provided.
- a pulse wave component removing unit 314 is provided instead of the removing unit 313, and that a respiratory component extracting unit 313 'in which the internal configuration of the respiratory component extracting unit 313 is changed is provided.
- a respiratory component extracting unit 313 'in which the internal configuration of the respiratory component extracting unit 313 is changed is provided.
- the pulse wave component removing unit 313 ' is composed of a low-pass filter, and removes a pulse wave component from the pulse wave analysis data MFD to generate pulse wave component removal analysis data MD'.
- the cutoff frequency of the low-pass filter is selected to be slightly lower than the fundamental wave frequency of the pulse wave component. The reason is that the fundamental frequency of the body motion component and the fundamental frequency of the respiration component are lower than the fundamental frequency of the pulse wave component. Specifically, the cut-off frequency is set slightly lower than the fundamental frequency of the pulse wave component measured at rest.
- the pulse wave analysis data MFD and the cut-off frequency f of the mouth-pass filter have the relationship shown in Fig. 79
- the pulse wave component removal analysis data MD ' is as shown in Fig. 80. .
- FIG. 81 is a block diagram showing a detailed functional configuration of the respiratory component extraction unit 313 '.
- the spectrum extraction unit 340 extracts two spectrum frequencies as a set from each of the spectrum frequencies of the pulse wave component removal analysis data MD ′ and outputs the lower spectrum frequency to the fundamental frequency table 341. At the same time, the higher spectrum frequency is output to difference detecting section 342.
- the pulse wave component removal analysis data MD ′ is as shown in FIG.
- the fundamental frequency table 341 is configured by a ROM or the like, and stores therein in advance the fundamental frequency Ftl of the body motion component in association with the fundamental frequency f ml of the respiratory component.
- the contents of the fundamental frequency table 341 are composed of measured values.
- the present inventors measured the relationship between the running pitch and the respiratory rate by gradually changing the running speed of the subject.
- Figure 82 shows the results of the experiment.
- the running pitch is the number of steps per unit time.
- the pulse wave detection unit 310 (pulse wave detection sensor unit 130) is attached to the base of the finger as shown in FIG. 3, so that the pulse wave waveform MH detected by this is
- the body motion component present in is dependent on the swing of the arm.
- the relationship between the arm swing and the running pitch depends on whether the player swings vigorously or smoothly, but it is usually one arm swing for two pitches.
- the period of one arm swing corresponds to one period of the body movement waveform. Therefore, assuming that the running pitch (for the repetition) is P and the respiratory rate (for the repetition Z) is V, the basic frequency Ftl of the body motion component and the basic frequency Fvl of the respiratory component are expressed as the running pitch P and the respiration rate V Is given by the following equation.
- difference detecting section 342 detects a difference between the other spectrum frequency output from spectrum extracting section 340 and the frequency output from basic frequency table 41. If the set of spectral frequencies extracted by the spectrum extracting unit 340 is the fundamental frequency Ftl of the body motion component and the fundamental frequency Fvl of the respiratory component, Fvl is supplied to the fundamental frequency table 41 and Ftl is output. Therefore, the output of the difference detection unit 342 is “0”. On the other hand, if the set of spectrum frequencies extracted by the spectrum extraction unit 340 is Fvl and F (where Fvl ⁇ F), the difference detection unit 342 Will output "
- the comparing section 343 compares the output of the difference detecting section 342 for each set of spectrum frequencies output from the spectrum extracting section 340, specifies the set having the smallest value, and configures the set. Output the lower one of the spectrum frequencies.
- the specified pair is Ftl, Fvl, and since there is a relationship of Ftl> Fvl, the comparison unit 343 outputs the fundamental frequency Fvl of the respiratory component.
- the harmonic frequency generation section 344 multiplies the fundamental frequency Fvl of the respiratory component by an integer to generate Fv2, Fv3, Fv4, and so on, and the corresponding levels L1, L2, L3, L4 ... are output as respiratory components.
- the respiratory component thus generated is supplied to the evaluation unit 315 described in the first embodiment, and the exercise intensity X is generated based on the distortion rate K, and this is displayed on the display unit 316.
- the body motion component and the respiration component are separated by the respiration component extraction unit 314 ′. Therefore, the exercise intensity X can be obtained based on the respiratory component without using the body motion detection unit 311 and the second FFT processing unit 331. As a result, the size and weight can be reduced, and the exercise intensity detection device 3 that is more convenient for the subject can be provided.
- FIG. 84 is a diagram illustrating an example of a respiratory rate and a pulse rate during running.
- a filtering process may be performed in relation to the pulse rate.
- a table storing the relationship between the respiratory rate and the pulse rate in advance is provided.
- the respiratory rate (60Z Fvl) estimated from the pulse rate (60Zfml) is calculated using this table.
- the fundamental frequency Fv1 of the respiratory component is extracted using a band-pass file having the estimated fundamental frequency of the respiratory component as the center frequency.
- the filtering process may be performed digitally.
- the exercise is performed by focusing on the third harmonic component Fv3 of the fundamental frequency Fvl.
- the strength X may be obtained.
- the respiratory component extraction unit 314 extracts the fundamental frequency Fvl and its third harmonic Fv3.
- the evaluation unit 315 calculates L3 / L1 from the levels L1 and L3 corresponding to these, and obtains the exercise intensity X by referring to the exercise intensity table in which the relationship between L3ZL1 and the exercise intensity X is stored in advance. You. As a result, it is not necessary to calculate the distortion factor K, so that the arithmetic processing can be simplified, and as a result, the processing can be performed at high speed and the load on the CPU can be reduced.
- the frequency analysis was performed using the FFT, but the present invention is not limited to this, and any method may be used as long as the frequency analysis is performed. Often, for example, a wavelet transform can be used. ⁇ In the applet transform, the frequency analysis can be performed in a short time, but the shorter the time, the coarser the frequency analysis becomes. Therefore, by taking one unit (time resolution) of the analysis time to a certain extent, the frequency domain can be made finer.
- the wavelet transform unit 320 implements the wavelet transform by expanding the basis function, but the present invention is not limited to this, and the wavelet transform is implemented by the filter bank. May be.
- the bank for example, the bank shown in FIG. 30 described in Chapter 1 may be used.
- the high-pass filter 1A and the low-pass filter 1B may be composed of a transversal filter including a delay element (D flip-flop) therein.
- D flip-flop delay element
- the clock to be supplied to the transversal filter may have a pulse wave waveform MH to adaptively change the band to be divided.
- the inverse wavelet transform unit 22 may be constituted by a filter bank.
- the filter bank shown in FIG. 31 described in Chapter 1 may be used, for example.
- the high-pass filter 2A and the low-pass filter 2B may be constituted by transversal filters including delay elements (D flip-flops) therein. 3-8-5: Modification of notification means
- the display unit 316 is described as an example of a notifying unit.
- the display unit may be modified. Of course, it may be shaped.
- the exercise intensity detecting device has a wristwatch structure.
- the present invention is not limited to this.
- the glasses type see Fig. 34
- necklace type see Fig. 35
- card type see Fig. 36
- pedometer type see Fig. 37
- the pulse wave detection sensor unit 130 has been described as an example of the pulse wave detection unit f1, but the present invention is not limited to this. Anything that can be done may be used.
- a pulse wave may be detected by a transmitted light method or a pressure sensor method.
- the heart is a muscular organ composed mainly of myocardial tissue, contracts at a certain rhythm and sends blood to the aorta.
- the heart is divided into an upper atrium and a lower ventricle.
- Atria and ventricles separated by atrial and ventricular septum Have been. Both the atrium and ventricle regularly contract and expand, but their timing is slightly off.
- the arterial valve is closed, preventing blood from the aorta from flowing into the ventricles.
- the ventricles contract and pump blood into the aorta.
- the atrioventricular valve is pushed up from the ventricle side, but the chords formed between the atrioventricular valve and the ventricle wall are in a taut state, so that the valve is not inverted.
- the ventricle contracts, the arterial valve is pressed against the arterial wall, allowing blood to pass.
- the aorta expands and stores a portion of the blood that has been pushed out of the ventricles.
- the ventricles while the ventricles are dilating, the aorta gradually contracts, pumping stored blood towards the periphery.
- blood is always flowing through the aorta, even when no blood is pumped out of the ventricles.
- the heart pumps blood into the aorta, and the volume of blood pumped by one contraction is called the stroke volume SV. Its unit is liter.
- the product of stroke volume SV and heart rate HR (time Z minutes) is called cardiac output CO.
- Cardiac output CO indicates the volume of blood per minute pumped out of the heart, and is measured in liters Z minutes.
- the stroke volume SV and the cardiac output CO reflect the quality of the heart function, and are often used as an index when evaluating the heart function.
- the heart rate HR of the heart transplanter is almost constant irrespective of each posture. This phenomenon also applies to those whose heart function is extremely deteriorated due to the elderly and the heartbeat has to rely on a pacemaker. Thus, for those who cannot control the heart rate according to the amount of blood to be pumped out of the heart, the pulse rate is, of course, not sufficient for the contractile force required of the heart muscle.
- the stroke volume SV and the cardiac output CO have the same change characteristics as the heart rate HR of the healthy person as well as the heart transplanter as well as the healthy person. . For this reason, it can be seen that it is extremely useful as an index for evaluating cardiac function not only in healthy subjects but also in those who cannot control heart rate HR such as heart transplanters.
- FIG. 86 shows a typical pulse waveform. Since the pulse waveform is a measurement of the pulsation of the blood flow caused by the contraction and expansion of the heart in the peripheral part, the waveform of the pulse reflects the movement of the heart. The ED in the figure is called the ejection period and corresponds to the time during which blood flows out of the heart during one heartbeat.
- the ejection volume is calculated by integrating the ejection period ED and the blood pressure value of the pulse wave waveform corresponding to this period to calculate the area S, and multiplying the area S by the coefficient Ksv. Calculate SV.
- the cardiac output C ⁇ is calculated by the following equation.
- the stroke volume SV and the cardiac output c ⁇ are used as evaluation indicators of cardiac function as described above, and therefore, the stroke volume SV and the cardiac output C during exercise such as running.
- Knowing ⁇ will enable scientific training. Patients suffering from heart disease may also be at risk from cardiac dysfunction during daily exertion. In such a case, the stroke volume SV and cardiac output CO decrease, so if the stroke volume SV and cardiac output co can be known during exertion, the patient's health Can be used for management.
- the method of measuring the internal pressure of the heart using a cardiac catheter is based on the assumption that the subject is in a resting state. Output CO cannot be measured.
- Chapter 4 describes a cardiac output detection device that continuously detects cardiac output CO during exercise and daily life, and a stroke volume detection device that continuously detects stroke volume SV.
- the output device will be described.
- a cardiac function diagnostic device that evaluates cardiac function based on the cardiac output C O and the stroke volume SV will also be described.
- FIG. 87 is a functional block diagram of a cardiac function diagnostic device using a cardiac output detection device.
- f41 is a pulse wave detecting means for detecting a pulse wave waveform.
- the pulse wave waveform can be obtained, for example, by detecting a blood flow in a peripheral part such as a fingertip or a finger base with an optical sensor.
- f42 is body motion detecting means for detecting body motion and outputting a body motion waveform. Thereby, it is detected that the person has moved.
- f 43 is a body movement removing means, which generates a body movement component in the pulse wave waveform based on the body movement waveform, and removes the body movement component from the pulse wave waveform to remove the body movement removal pulse wave. Generate a waveform. This makes it possible to generate a pulse waveform that is not affected by body movement even during exercise.
- f44 is a heart rate detecting means for detecting the heart rate based on the pulse wave waveform from which the body motion has been removed.
- f45 is an ejection period detection means, which is based on the pulse wave waveform from the body motion removal. Then, the ejection period of the heart is detected.
- the ejection period is the period during which the heart pumps blood into the aorta in one contraction.
- the ejection period will be described in more detail.
- Figure 88 shows the relationship between the ECG waveform, the aortic blood pressure waveform, and the peripheral pulse waveform.
- SW is the electrocardiographic waveform
- MH1 is the aortic blood pressure waveform immediately after flowing out of the heart
- MH2 is the general pulse waveform of the peripheral part (radial artery).
- the time delay associated with blood flow is ignored.
- the ejection period ED is a time interval between the aortic valve opening time t1 and the aortic valve closing time t2 in the aortic blood pressure waveform MH1, and is about 280 ms at rest.
- the notch N 2 in the peripheral pulse wave waveform MH 2 is called a decrotive notch N 2 and is generated by aortic valve closure. Therefore, the time interval from the minimum peak P0 to the peak P4 in the pulse waveform MH2 corresponds to the ejection period ED.
- the ejection period ED is a time interval from the minimum peak P0 to the peak P4.
- the period from the minimum peak P0 of the pulse wave waveform MH2 to the peak P2 of the notch N1 is called the estimated systolic time, and the theory that this time interval is regarded as the ejection period ED There is also. In any case, there is no difference in opinion that these periods are representative of the systolic period of the heart.
- the ejection duration ED used in this specification is not only the ejection duration in the strict sense, but also the ventricular systolic time (Sysolic Time) and the estimated systolic time (Estimated Sysolic Time). Time), and proceed with the following description.
- the ejection period ED is determined as the period from the minimum peak to the first or second negative peak P2 or P4 that occurs after the maximum peak P1.
- reference numeral 46 denotes a cardiac output detection means for detecting the heart rate CO.
- the stroke volume SV is calculated based on the pulse wave waveform during the ejection period, and the stroke volume C ⁇ is calculated by multiplying the stroke volume SV by the heart rate. Detected.
- f47 is an evaluation means for evaluating the state of cardiac function based on the cardiac output. That is, the evaluation of cardiac function is evaluated by the volume of blood per minute discharged from the heart.
- f48 is a notifying means for notifying the evaluation result. This allows the subject and a third-party doctor to know the subject's cardiac function.
- f49 is a determining means, which determines the presence or absence of a body movement based on the level change of the body movement waveform, and stops the operation of the body movement removing means f3 when there is no body movement. To control. As a result, the number of operations involved in the body motion removal processing can be reduced. 4-2-2: First embodiment
- the first to seventh embodiments relate to a cardiac function diagnosis device using a cardiac output detection device
- the eighth to fourteenth embodiments relate to a cardiac function diagnostic device using a stroke output detection device.
- the present invention relates to a function diagnosis device.
- the external configuration of the cardiac function diagnostic device 42 of this example is the same as that of the pulse wave diagnostic device 1 described in Chapter 1 (see FIG. 2). That is, the cardiac function diagnostic device 42 includes a device main body 110 having a wristwatch structure, a cable 120 connected to the device main body 110, and a pulse wave detection sensor unit 130 provided at the distal end of the cable 120. It is roughly composed of
- the circuit configuration of the pulse wave detecting sensor unit 130 functioning as the pulse wave detecting means f41 is the same as that of the pulse wave diagnostic device 1 described in Chapter 1 (see FIG. 3).
- FIG. 89 is a block diagram showing the electrical configuration of the cardiac function diagnostic device.
- the cardiac function diagnostic device 42 is composed of the following parts.
- Sensor unit for pulse wave detection G 130 detects the pulse wave waveform MH and outputs it to the body movement removing unit 411.
- the acceleration sensor 130 'detects a body motion as an acceleration and generates a body motion waveform TH.
- the waveform processing unit 410 performs waveform processing on the body motion waveform TH so that the body motion removing unit 411 accurately removes the body motion component.
- the body movement waveform TH is detected as the acceleration of the arm swing itself, but since the blood flow is affected by blood vessels and tissues, the body movement component MHt becomes a dull body movement waveform TH.
- the waveform processing unit 410 is formed of a mouth-to-pass filter. The format and constants of the low-pass filter are determined from the actual measured data.
- the body motion removing unit 411 subtracts the output waveform M Ht of the waveform processing unit 410 from the pulse wave waveform MH to generate a body motion removing pulse wave waveform MH ′.
- the pulse wave waveform MH 'for removing body motion is converted into a digital signal via an AZD converter (not shown), and supplied to a heart rate detecting unit 412 and an ejection period detecting unit 413.
- a determination unit 41 1 ′ determines the presence or absence of a body motion based on the body motion waveform TH and generates a control signal C. Specifically, the judgment is made by comparing the threshold value and the body motion waveform TH. This threshold is predetermined so that the presence or absence of a body motion can be determined in consideration of the noise level of the acceleration sensor 130 '.
- the operations of the waveform processing unit 410 and the body movement removing unit 411 are stopped.
- the pulse wave waveform MH is directly output from the body motion removing unit 411. This makes it possible to improve the SN ratio of the output signal of the body movement removing unit 411 and reduce the power consumption of the device.
- the heart rate detecting unit 412 and the ejection period detecting unit 413 detect the heart rate HR and the ejection period ED based on the body motion removal pulse wave waveform MH '.
- the heart rate HR and the drive are analyzed by analyzing the amplitude level of the body motion removal pulse wave waveform MH '. I'm looking for ED.
- the heart rate detecting unit 4 12 and the ejection period detecting unit 4 13 extract waveform parameters for specifying the shape of the body motion removal pulse wave waveform MH ′.
- the waveform parameters are the same as those described in Chapter 1 with reference to FIG.
- the heart rate detection unit 4 12 and the ejection period detection unit 4 13 use the information called “peak information” related to each of the above-mentioned maximum points or minimum points in order to calculate the waveform parameters. Extract.
- the peak information is the same as that described in Chapter 1 with reference to FIGS. 27 and 28.
- the heart rate detecting section 4 12 and the ejection period detecting section 4 13 are constituted by the computer system shown in FIG. 26 described in Chapter 1.
- the pulse wave waveform MH 'for removing body motion is input instead of the pulse wave waveform TMH for separating body motion.
- the peak information shown in FIG. 28 is stored in the peak information memory 205.
- Time t 6 which is calculated as a waveform parameter (see FIG. 2 5) is Ru time der of over beats.
- the microcomputer 18 1 calculates 60 / t 6 based on the time t 6 and obtains the heart rate HR.
- the microcomputer 1811 accesses the internal buffer memory and specifies the minimum peak Pmin and the maximum peak Pmax during one heartbeat based on the waveform parameters. For example, in the waveform shown in FIG. 6, P0 is specified as the minimum peak Pmin and the P1 force maximum peak Pmax.
- the first or second negative peak (notch) after the maximum peak P max identify the first or second negative peak (notch) after the maximum peak P max.
- P4 is specified as the negative peak.
- the period from the minimum peak Pmin to the negative peak P4 is the ejection period ED Is calculated as For example, in the waveform shown in FIG. 25, the period t4 is output as the ejection period ED.
- the heart rate HR and the ejection period ED are calculated.
- the stroke volume calculation unit 414 shown in FIG. 89 determines the body motion removal pulse wave waveform MH 'during the ejection period ED based on the body movement removal pulse wave waveform MH' and the ejection period ED. Then, the area S is calculated. Specifically, the area S is calculated by sequentially adding the body motion removal pulse wave waveform MH 'in each sample during the ejection period ED, thereby integrating the body movement removal pulse wave waveform MH'. Then, the stroke volume SV is calculated by multiplying the area S by the coefficient coefficient Ksv. That is, the stroke output SV is calculated by the following equation.
- the cardiac output calculator 415 calculates the cardiac output CO by multiplying the heart rate HR by the stroke volume SV. That is, the cardiac output CO is calculated by the following equation.
- the cardiac output CO may be calculated by sequentially adding the stroke output SV per minute.
- the evaluation unit 416 includes a memory 161 and a comparator 162, and evaluates a cardiac function based on the cardiac output C ⁇ to generate an evaluation index X.
- the memory 161 stores a ⁇ value used for delaying the cardiac output CO.
- the threshold is set according to the number of grayings. In this example, R1 and R2 are set as the threshold. These threshold values Rl and R2 may be stored in advance, or may be values set by a doctor or a trainer.
- the comparator 162 compares the cardiac output CO with the thresholds Rl, R2 to generate an evaluation index X.
- the evaluation index X 1 is generated when CO ⁇ R 1
- the evaluation index X 2 is generated when R 1 ⁇ CO ⁇ R 2
- the evaluation index X 3 is generated when R 2 ⁇ C ⁇ .
- the meanings of the evaluation indices X1 to X3 differ depending on how the cardiac function diagnostic device 42 is used. For example, when used for exercise training, it is a measure for maintaining appropriate exercise intensity, and is used for rehabilitation of heart disease. When monitoring cardiac function in a patient, it is a measure of the degree of recovery.
- the display unit 417 includes the liquid crystal display device 210 shown in FIG. 2 and the like, and displays a cardiac output C ⁇ , an evaluation index X, a message associated with the evaluation index X, and the like. Is done.
- a display mode there are a face chart, characters, symbols, and the like.
- the subject can be notified of the evaluation result of the cardiac function. For example, when using the cardiac function diagnostic device 42 in running, the trainer can notify the subject to maintain an appropriate cardiac output CO by setting the thresholds R l and R 2. It becomes possible.
- FIG. 90 is a block diagram of the cardiac function diagnostic device 42 according to the second embodiment.
- the body motion component MHt is detected by using the acceleration sensor 130 'and the waveform processing unit 410 as in the first embodiment, but the body motion removal and the heart rate described in the first embodiment are performed. The difference is that the ejection period is detected using wavelet transform.
- the external configuration of the second embodiment is the same as the external configuration of the first embodiment shown in FIG.
- reference numeral 420 denotes a first wavelet transform unit, which performs a well-known wavelet transform on a pulse wave waveform MH output from the pulse wave detecting sensor unit 130 to generate pulse wave analysis data MKD.
- Reference numeral 422 denotes a second wavelet transform unit, which performs a well-known wavelet transform on the body motion waveform MHt output from the acceleration sensor 130 'to obtain a body motion analysis data TKD. Generate.
- the first wavelet transformer 420 and the second wavelet The converter 422 is configured to be able to calculate Equation 1 described in Chapter 1.
- wavelet conversion is performed in units of heartbeat, and pulse wave analysis data MKD is generated.
- the pulse wave analysis data MKD is 0 Hz to 0.5 Hz, 0.5 Hz to: L. 0 Hz, 1.0 Hz to: L. 5 Hz, 1.5 Hz to 2.0 Hz, 2.0 Hz to 2.5Hz, 2.5Hz to 3.0Hz, 3.0Hz to 3.5Hz, 3.5Hz to 4.OHz
- the output is divided into frequency ranges.
- reference numeral 421 denotes a first frequency correction unit which performs frequency correction on the pulse wave analysis data MKD.
- the first frequency correction unit 421 is provided for this purpose, and generates pulse wave correction data MKD 'by multiplying the wavelet data WD by the coefficient a1 / 2 . Thereby, correction can be performed based on each corresponding frequency so that the power density per frequency becomes constant.
- Reference numeral 423 denotes a second frequency correction unit, which performs frequency correction similarly to the first frequency correction unit 421, and generates body motion correction data TKD 'from the body motion analysis data KD.
- FIG. 91 shows pulse wave analysis data MKD for a part of the pulse wave waveform MH.
- the scale of the time axis is subdivided as compared with FIG. 8 described in Chapter 1.
- the period T is near the peak P4, and the pulse wave analysis data MKD is obtained at time intervals obtained by dividing the period T into eight.
- the generated pulse wave analysis data MKD and body motion analysis data TKD are subjected to frequency correction by the first and second frequency correction units 421 and 423, and the pulse wave correction data MKD ', Is output as body motion correction data TKD'.
- body motion removing section 411 generates body motion removed pulse wave data MKD ′ ′ by subtracting body motion corrected data TKD ′ from pulse wave corrected data MKD ′.
- body motion removed pulse wave data MKD ′ ′ by subtracting body motion corrected data TKD ′ from pulse wave corrected data MKD ′.
- the pulse wave waveform MH shown in FIG. 16 (a) is detected by the pulse wave detection sensor unit 130, and at the same time, the body motion waveform MHt shown in FIG. 16 (b) is detected by the waveform processing unit 410. It shall have been done.
- the body motion waveform MH U begins to increase from time T1, becomes a positive peak at time T2, then gradually decreases, passes level 0 at time T2, and becomes negative at time T3. It reaches its peak and returns to level 0 at time T4.
- time T3 corresponds to the time when the user lifts the cup to the maximum
- time T1 corresponds to the lifting start time
- time T4 Corresponds to the lifting end time. Therefore, a period from time T1 to time T4 is a period in which the body motion exists.
- FIG. 16 (c) shows a pulse wave waveform MH 'in the case where there is no body movement.
- the fundamental frequency of the pulse waveform MH is 1.3 Hz.
- FIG. 17 shows the pulse wave correction data MKD 'during the period Tc (see FIG. 16), and FIG. 18 shows the body motion correction data TKD' during the period Tc.
- the body motion waveform TH has a relatively large level frequency component in the frequency range of 0.0 Hz to l. OHz.
- the body motion removal unit 41 1 converts the body motion correction data TKD 'from the pulse wave correction data MKD'.
- a body motion elimination pulse wave MKD '' from which the body motion component is removed as shown in Fig. 19 is generated. This makes it possible to cancel the effects of any movement.
- the determination unit 41 1 ′ compares the body movement waveform TH with a predetermined threshold to generate a control signal C indicating presence / absence of body movement, and outputs the control signal C to the waveform processing unit 410 and the second wavelet.
- the signal is supplied to the conversion unit 422 and the second frequency correction unit 423.
- the heart rate detection unit 412 calculates the heart rate based on the body motion removal pulse wave data MKD ′′.
- the heart rate detecting unit 412 specifies the maximum peak Pmax in one beat based on the body motion removal pulse wave data MKD ′ ′.
- the high-frequency component is large.
- a threshold value corresponding to the high-frequency component is determined in advance, and the threshold value is compared with the body motion removal pulse wave data MKD' '. Specify the maximum peak Pmax. Then, a time interval T between a certain maximum peak Pmax and the next maximum peak Pmax is obtained, and a heart rate HR is calculated from 60 / T.
- the ejection period detection unit 413 may be configured in the same manner as in the first embodiment, but in this example, based on the pulse wave data MKD ' Identify the peak Pmin and the second negative peak P4 (notch) after the maximum peak Pmax.
- the frequency component corresponding to the minimum peak Pmin and the frequency component corresponding to the peak P4 are stored in advance as thresholds, and these thresholds are compared with the body motion removal pulse wave data MKD ′ ′. Then, the minimum peak P min and the peak P 4 are specified, and the time interval between them is calculated as the ejection period ED.
- the stroke volume calculation unit 414 adds the body motion removal pulse wave data MKD '' of each frequency region in the ejection period ED to obtain the energy amount E in the period, and contracts based on this. Calculate the initial area S.
- the pulse wave data MKD '' in the lower frequency range (for example, 0 ⁇ to 1 ⁇ ) can be considered as noise components. Therefore, the energy amount E may be obtained by adding a part of the body motion removal pulse wave data MKD ′ ′ in all the frequency domains during the ejection period ED instead of adding them. For example, as shown in FIG. 92, if the body motion removal pulse wave data MKD '' is obtained, the body motion in the frequency range of 1 ⁇ to 4 ⁇ has many noise components in the frequency range of 0 Hz to 1 Hz. What is necessary is just to add MKD ''. Each frequency domain If the body motion removal pulse wave data MKD '' is expressed in Mnm, the energy quantity E in this case is given by the following equation.
- stroke volume SV is calculated by the following formula.
- Ke is a conversion coefficient between the energy amount E and the area S.
- the stroke volume SV is obtained while removing the noise component of the pulse waveform. Therefore, accurate cardiac output CO can be calculated.
- the first wavelet transform unit 420, the first frequency correction unit 421, the second wavelet transform unit 422, the second frequency The correction unit 423 was used.
- the third embodiment is different from the second embodiment in that the second wavelet transform unit 422 and the second frequency correction unit 423 are omitted.
- FIG. 93 is a block diagram of the cardiac function diagnostic device 42 according to the third embodiment.
- the first wavelet transform unit 420 converts the wavelet transform pulse wave waveform MH ′ into a wavelet transform. Is applied.
- the first frequency correction unit 421 performs frequency correction on the output of the first wavelet conversion unit 416 to generate body motion removal pulse wave data MKD ′′.
- the output of the first frequency correction unit 421 is equivalent to the output of the body motion removal unit 411 shown in FIG. That is, since the wavelet transform is linear, the order of processing may be changed. It is equivalent to performing the wavelet transform (third embodiment) and removing the body motion based on the wavelet-transformed pulse wave correction data MKD 'and the body motion correction data TKD' (second embodiment) because they are equivalent. It is.
- the determination unit 41 1 ′ is the same as in the first embodiment.
- the ejection period detection unit 413, the stroke volume calculation unit 414, the cardiac output calculation unit 415, the evaluation unit 416, and the display unit 417 are the same as those in the second embodiment, and thus the description is omitted. .
- the cardiac output CO can be calculated even if the second wavelet transform unit 422 and the second frequency correction unit 423 are omitted, so that it is simpler. With a simple configuration, the state of cardiac function can be diagnosed.
- the body motion waveform TH is detected by the acceleration sensor 130, the pulse wave waveform MH is compared with the body motion waveform TH, and the body included in the frequency component of the pulse wave waveform MH is detected.
- the motion component was canceled, the heart rate HR and the ejection period ED were calculated, and the state of cardiac function was diagnosed based on these.
- the acceleration sensor 130 and the waveform processing unit 410 are required, the configuration is complicated.
- the fourth embodiment has been made in view of this point, and provides a cardiac function diagnostic apparatus 42 that has a simple configuration and can accurately diagnose the state of cardiac function even when there is body movement. is there.
- FIG. 94 is a block diagram of the cardiac function diagnostic apparatus 42 according to the fourth embodiment, in which the acceleration sensor 130, the waveform processing section 410, the second wavelet transform section 422, and the second frequency correction section 423
- the configuration is the same as that of the cardiac function diagnostic apparatus 42 according to the second embodiment shown in FIG. 90 except for the omission and the internal configuration of the body movement removing section 41 1.
- the differences will be described.
- the body motion removing unit 4111 separates and removes a body motion component from the pulse wave correction data MKD 'to generate body motion separated pulse wave data TBD.
- the body motion removing unit 411 uses the following property of the body motion.
- Body motion is caused by the vertical movement of the arm or the swing of the arm during running.
- the human body In daily life, the human body rarely moves instantaneously.
- the frequency component of the body motion waveform TH is not so high, and is in the range of 0 Hz to 1 Hz. Normal.
- the fundamental frequency of the pulse waveform MH is often in the range of 1 1 to 2 ⁇ . Therefore, in daily life, the frequency component of the body motion waveform TH is in a frequency region lower than the fundamental frequency of the pulse waveform MH.
- the frequency component of the body motion waveform TH increases somewhat due to the effects of arm swing, etc., but the pulse wave waveform increases because the heart rate increases according to the amount of exercise.
- the fundamental frequency of MH also increases at the same time. For this reason, even during sports, the frequency component of the body motion waveform TH is usually in a frequency range lower than the fundamental frequency of the pulse waveform MH.
- the body motion removing unit 411 separates the body motion component, and is configured to ignore a frequency region lower than the fundamental wave component of the pulse waveform MH. In this case, if a body motion component exists in a frequency region higher than the fundamental wave component of the pulse wave waveform MH, the detection accuracy of the cardiac function decreases. However, as described above, since the body motion component is more likely to be in a lower frequency region than the fundamental wave component of the pulse waveform MH, the state of the heart function can be diagnosed with high accuracy.
- FIG. 95 is a detailed block diagram of the body movement removing unit 411.
- the waveform shaping section 4301 performs waveform shaping on the pulse waveform MH and generates a reset pulse synchronized with the pulse waveform MH.
- the counter 302 counts a clock pulse (not shown), and the count value is reset by the reset pulse.
- the average value calculation circuit 303 calculates the average value of the count values of the counter 302. In this case, the average value calculated by the average value calculation circuit 303 corresponds to the average period of the pulse wave waveform MH. Therefore, the fundamental frequency of the pulse waveform MH can be detected by referring to the average value.
- the replacement circuit 304 specifies a frequency region including the fundamental frequency of the pulse waveform MH based on the average value. For example, when the average value indicates 0.71 second, the fundamental frequency is 1.4 Hz, and the specified frequency region is 1 ⁇ to 1.5 Hz. After that, the replacement circuit 304 replaces the pulse wave correction data MKD ′ with “0” for the frequency region below the specific frequency region to generate the body motion separated pulse wave data TBD. As a result, components in a frequency region lower than the fundamental frequency of the pulse waveform MH are ignored. In this case, the pulse wave component is replaced with “0” together with the body motion component.
- the pulse wave correction data MKD 'for the period Tc is The result is shown in FIG.
- the frequency range specified by the replacement circuit 194 is 1.0 Hz to 1.5 Hz, and the frequency range to be replaced is 0.5 Hz to: Ma 12 to Ma 82 corresponding to 1.0 Hz. And Ma 1 l to Ma 81 corresponding to 0 Hz to 0.5 Hz. Accordingly, the data Ma 12 to Ma 82 and Mall to Ma 8U of the pulse wave correction data MKD 'are replaced with "0", and the body motion removal pulse wave data MKD''shown in FIG. 96 is generated.
- the heart rate detecting unit 412 and the ejection period detecting unit 413 shown in FIG. 94 detect the heart rate HR and the ejection period ED, respectively.
- the body motion component skillfully utilizes the property of the body motion that it is stochastically high in the frequency region lower than the fundamental frequency component of the pulse waveform MH. Body motion components were removed. For this reason, the configuration of the acceleration sensor 130 and the waveform processing unit 410 required in the first to third embodiments can be omitted, and the state of the heart function can be accurately diagnosed even if there is body movement. Becomes possible.
- the fifth embodiment relates to a modification of the stroke volume calculation unit 414 described in the first embodiment, and the other components are the same as in the first embodiment.
- the stroke volume calculation unit 414 of the fifth embodiment has the following modes.
- the stroke volume SV is calculated from the blood pressure values of each of the peaks P1 to P4 of the body movement-removed pulse wave waveform MH 'during the ejection period ED and their occurrence times. For example, if the body motion removal pulse wave waveform MH 'is as shown in FIG. 25 and the period from P0 to P4 is the ejection period ED, the stroke volume SV is calculated by the following equation. .
- the stroke volume SV is determined from the ejection period ED and the heart rate HR.
- the systolic area S in the systolic area method is calculated from the ejection period ED and the heart rate HR.
- the pulse waveform MH has individual differences and differences within individuals even within the same individual, the approximate shape of the pulse waveform MH at a certain heart rate HR is specified by measuring a large number of measured data. be able to. Then, when the pulse wave waveform MH is specified, the area S corresponding to the ejection period ED can be obtained.
- FIG. 97 is a block diagram of the stroke volume detection unit 414 according to the second embodiment.
- Reference numeral 4140 denotes a stroke volume table, in which a systolic area S is stored in association with a cardiac ejection period ED and a heart rate HR.
- the stroke volume table 4140 is composed of a plurality of tables TB 1, TB 2, ⁇ ⁇ provided for each heart rate HR, and each table TB I, TB 2, ⁇ ' ⁇ ⁇ . Stores the systolic area S associated with the ejection period ⁇ D. The contents of these tables are generated by a large number of actual measurements.
- Reference numeral 4141 denotes a multiplier provided at the subsequent stage of the stroke volume table 140, and calculates a stroke volume SV by multiplying the coefficient KsV by the systolic area S.
- the stroke volume detection unit 414 sets one table corresponding to the heart rate HR. Identify TB. Thereafter, when the systolic area S corresponding to the ejection period ED is read from the table TB, the multiplier 4141 calculates the stroke volume SV.
- the stroke volume SV can be calculated only from the ejection period ED and the heart rate HR, and thus the stroke volume can be calculated once in a short time with a simple configuration. The quantity SV can be determined.
- the multiplier 4141 can be omitted.
- S * KsV may be stored in each table TB1, TB2,... Bn.
- FIG. 98 is a diagram showing a cardiac output table 4140 ′.
- S * KsV * HR may be stored in each table TBI, TB2,.
- the above-described cardiac function diagnostic apparatus 42 of the first to fifth embodiments uses the systolic area method, multiplies the area S of the pulse wave waveform during the ejection period ED by a coefficient Ksv, and calculates the stroke volume SV Was calculated.
- the coefficient Ksv is strictly different for each subject. Therefore, in order to calculate an accurate stroke volume SV, it is desirable to correct the stroke volume SV obtained by the systolic area method.
- FIG. 99 is a block diagram of the stroke volume correction unit 424 according to the present embodiment.
- the stroke volume correction unit 424 includes a correction coefficient calculation unit 4240 for calculating the correction coefficient KH, a correction coefficient memory 4241 for storing the correction coefficient KH, and a multiplication unit 4242.
- the correction coefficient calculating unit 4240 is supplied with a reference stroke volume SV r precisely measured by a thermal dye dilution method or the like from an external device, and calculates the stroke volume calculated by the stroke volume calculating unit 414. Stroke volume SV is supplied.
- the correction coefficient calculation unit 4240 is composed of a divider, and when the subject operates the operation button to enter the calibration mode, calculates the SV rZS V as the correction coefficient KH.
- the calculated correction coefficient KH is stored in the correction coefficient memory 4241, read out therefrom in a normal measurement mode, and used.
- the multiplier 4242 multiplies the stroke volume SV by the correction coefficient KH. To calculate the corrected stroke volume SVh.
- the correction coefficient KH is calculated in the calibration mode, and the corrected stroke volume S Vh is calculated using the correction coefficient KH in the normal measurement mode.
- Output CO can be obtained.
- the cardiac function diagnostic device 42 of the present embodiment is suitable for, for example, health management in a hospital or health management during rehabilitation. More specifically, at the same time as measuring the accurate reference stroke volume SVr by the thermo-dye dilution method after surgery for heart disease, etc., the stroke volume SV is measured by the portable cardiac function diagnostic device 42. . Then, the correction coefficient KH calculated from these measurement results is stored, and a precise cardiac output CO is obtained using the correction coefficient KH in the normal measurement mode. This allows the patient to receive an accurate cardiac output CO-based diagnosis of cardiac function in the process of returning to health by rehabilitation.
- the seventh embodiment changes the threshold value, which is the reference of the evaluation index X, according to the body surface area, and is the same as the configurations of the first to sixth embodiments except for the configuration of the evaluation unit 416.
- the evaluation unit 416 which is a difference will be described.
- FIG. 100 is a block diagram of the evaluation unit 416 according to the seventh embodiment.
- Reference numeral 4140 denotes a body surface area calculation unit in which the weight W (kg) and the height H (cm) are input, and the body surface area TS is calculated based on these. I have.
- the body surface area TS is calculated by a well-known empirical formula called Dubois formula. The empirical formula is shown below.
- 4161 is a threshold table in which thresholds R 1 and R 2 for generating the evaluation index X are stored in association with the body surface area TS and the heart rate HR.
- This threshold table 4161 is composed of a plurality of tables ⁇ , TB 2 ′, and ⁇ T Bn, and each table stores thresholds R 1 and R 2 associated with a heart rate HR. ing.
- the body surface area TS is supplied, one table according to the body surface area TS is selected from the tables. Therefore, referring to the threshold table 4161, the body surface area TS and the heart rate H Threshold values Rl and R2 according to R can be obtained.
- reference numeral 162 denotes a comparing unit which compares the thresholds Rl, R2 with the cardiac output CO to generate an evaluation index X.
- the threshold values R1 and R2 are made variable by the body surface area TS for the following reason.
- a person with a large body surface area TS has a large body and a large cardiac output CO
- a person with a small body surface area TS tends to have a small body and a small cardiac output CO.
- the evaluation index X according to the body surface area TS is used. By doing so, it is possible to evaluate the cardiac function according to the individual's body type.
- the thresholds R 1 and R 2 are varied according to the heart rate HR for the following reasons.
- Exercise such as running, consumes a large amount of oxygen in skeletal muscle, which increases heart rate HR and cardiac output CO.
- the heart rate HR and cardiac output CO fluctuate according to the exercise intensity. Therefore, by using the evaluation index X according to the heart rate HR, the heart function can be continuously evaluated even when the exercise intensity of the subject changes.
- the threshold values Rl and R2 can be automatically changed in accordance with the body shape of the subject and the dynamically changing heart rate HR. In daily life, it is possible to continuously evaluate cardiac function.
- FIG. 101 is a functional block diagram of a cardiac function diagnostic device using a stroke volume detection device.
- f51 is a pulse wave detecting means for detecting a pulse wave waveform.
- the pulse wave waveform is obtained by detecting a blood flow in a peripheral part such as a fingertip or the base of a finger by an optical sensor.
- Obtained by f52 is a body movement detecting means, which detects body movement and outputs a body movement waveform. Thereby, it is detected that the person has moved.
- f53 is a body movement removing means, and the body movement in the pulse wave waveform is determined based on the body movement waveform. And generating a body motion-removed pulse waveform by removing the body motion component from the pulse waveform. This makes it possible to generate a pulse waveform that is not affected by body movement even during exercise.
- f54 is a determination means, which determines the presence or absence of a body movement based on the level change of the body movement waveform, and stops the operation of the body movement removing means f3 when there is no body movement. To control. As a result, the number of operations involved in the body motion removal processing can be reduced.
- f 55 is an ejection period detecting means for detecting the ejection period of the heart based on the pulse wave waveform from which the body motion has been removed.
- the ejection period is the period during which the heart pumps blood into the aorta in one contraction.
- the meaning of the ejection period ED includes not only the ejection duration in a strict sense as described above, but also the time of ventricular systole.
- reference numeral 56 denotes a stroke volume detecting means, which calculates the stroke volume SV based on the pulse waveform of the body motion removal during the ejection period.
- f57 is an evaluation means for evaluating the state of cardiac function based on stroke volume. That is, the evaluation of the heart function is evaluated by the volume of blood pumped out of a single contraction of the heart.
- F 58 is a notifying means, and notifies the evaluation result. This allows the subject and a third-party doctor to know the subject's heart function.
- cardiac function diagnostic device 43 using the stroke volume detection device will be described with reference to the drawings. Note that the cardiac function diagnostic device 43 of this example has the same external configuration as the pulse wave diagnostic device 1 of Chapter 1 as described in “4-1-2”.
- FIG. 102 is a block diagram showing an electrical configuration of the cardiac function diagnostic device 43.
- the cardiac function diagnostic device 43 shown in this figure differs from the cardiac function diagnostic device 42 shown in FIG. 89 in that a change rate calculating section 415 'is provided instead of the cardiac output calculating section 415.
- the change rate calculating section 415 ' is composed of an average value calculating section 4151 and a comparing section 41 52, and calculates a change rate SV' of the stroke volume SV.
- the average value calculator 41 51 calculates the average value SVa of the stroke volume SV.
- the timing at which the stroke volume SVn is detected may be the average of all values from the start of measurement, or may be the moving average given by the following equation.
- the comparison unit 4152 calculates SVZSVa to calculate the stroke volume change rate SV ′.
- the respiratory rate per heartbeat is usually less than four times, and the stroke volume SV is known to fluctuate in synchronization with breathing. Therefore, in order to cancel fluctuations due to respiration, the stroke volume SV may be averaged k times, and the stroke volume change rate SV 'may be calculated from the average value and SVa. . In this case, m> k ⁇ 4 should be selected.
- the evaluation unit 416 includes a memory 161 and a comparator 162, and evaluates a cardiac function based on the change rate SV to generate an evaluation index X.
- a threshold value used for delaying the change rate S is stored in association with the heart rate HR.
- the threshold corresponding to the heart rate HR at the time of detection can be read from the memory.
- the threshold is set according to the number of grades.
- R1 and R2 are set as the threshold.
- the comparator 162 generates the evaluation index X by comparing the stroke volume change rate SV ′ with the threshold values Rl and R2.
- the evaluation index X1 is generated when SV ⁇ R1
- the evaluation index X2 is generated when R1 ⁇ SV ⁇ R2
- the evaluation index 3 is generated when the scale 2 ⁇ 3.
- the meanings of the evaluation indices X1 to X3 differ depending on how the cardiac function diagnostic device 43 is used. For example, when used for exercise training, it is a measure for maintaining appropriate exercise intensity, and when monitoring cardiac function during rehabilitation of heart disease, it is a measure of the degree of recovery .
- the display unit 417 includes the above-described liquid crystal display device 210 and the like, and displays a stroke volume SV, an evaluation index X, a message associated with the evaluation index X, and the like. .
- a display mode there are a face chart, characters, symbols, and the like.
- the subject can be notified of the evaluation result of the cardiac function. For example, when using the cardiac function diagnostic device 43 in running, the trainer informs the subject to maintain an appropriate stroke volume SV by setting the thresholds Rl and R2. It becomes possible.
- a message such as "Let's increase the pace” with the evaluation index XI, "Let's keep pace” with the evaluation index X2, and "Let's reduce the pace” with the evaluation index X3.
- the sentence may be displayed on the display section 4 17.
- the self-reliance training method is also called the intensive self-relaxation method, and it is known that removing tension can help to promote and restore health.
- the challenge is to keep the mind relaxed. However, even if you want to relax, you may be nervous because you are trapped in that. In such a case, if one can know one's mental state, training can be performed effectively.
- the stroke volume change rate SV ′ described above is an index indicating the degree of relaxation. In other words, when the stroke volume change rate S V ′ becomes smaller, it means that the mind is approaching a stable and relaxed state.
- the thresholds Rl and R2 may be set so that the degree of relaxation can be determined.
- a self-sustained training physician can announce the subject's mental state by setting the thresholds R 1 and R 2.
- the evaluation index XI is "very relaxed.”
- the evaluation index X2 is “Keep this state.”
- the evaluation index X3 is "Relieve tension and feel relaxed.” Let's display a message such as "Message.”
- FIG. 103 is a block diagram of a cardiac function diagnostic device 43 according to the ninth embodiment.
- the body motion component MHt is detected by using the acceleration sensor 130 ′ and the waveform processing unit 410 as in the eighth embodiment.
- the difference is that the heart rate and the ejection period are detected by using the wavelet transform. That is, this corresponds to the second embodiment described with reference to FIG. 90, and the same components as those in FIG. 90 are denoted by the same reference numerals.
- the body motion removal unit 4 1 1 pulse wave correction obtained based on the pulse wave waveform MH The body motion removal pulse wave data MKD '' is generated by subtracting the body motion correction data TKD 'obtained based on the body motion waveform TH from the data MKD'. Then, the stroke volume SV and the like are calculated based on the body motion removal pulse wave data MKD ''. Therefore, as in the eighth embodiment, the systolic area S was calculated using the wavelet transform while removing the influence of body movement, and the stroke volume SV was calculated. The stroke volume SV can be obtained. As a result, cardiac function can be accurately evaluated.
- the frequency analysis is performed by the wavelet transform. Therefore, a first wavelet transform unit 420, a first frequency corrector 421, a second wavelet transform unit 422, and a second frequency corrector 423 were used.
- the tenth embodiment differs from the ninth embodiment in that the second wavelet transform unit 422 and the second frequency correction unit 423 are omitted. That is, the tenth embodiment corresponds to the third embodiment (see FIG. 93).
- FIG. 104 is a block diagram of the cardiac function diagnostic device 43 according to the tenth embodiment.
- the first wavelet transform unit 420 converts the body motion removal pulse wave waveform MH ′ into Performs wavelet conversion.
- First frequency correction section 421 performs frequency correction on the output of first wavelet conversion section 416 to generate body motion removal pulse wave data MKD ′ ′′.
- the body motion waveform TH is detected by the acceleration sensor 130, the pulse wave waveform MH is compared with the body motion waveform TH, and the pulse wave waveform MH is included in the frequency component of the pulse waveform MH.
- the body motion component was canceled, the heart rate HR and the ejection period ED were calculated, and the state of cardiac function was diagnosed based on these.
- the acceleration sensor 130 and And the waveform processing unit 410 and the like are required, so that the configuration is complicated.
- the eleventh embodiment has been made in view of this point, and provides a cardiac function diagnostic apparatus that has a simple configuration and can accurately diagnose the state of cardiac function even when there is body movement. is there. That is, the eleventh embodiment corresponds to the fourth embodiment described above.
Description
Claims
Priority Applications (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US09/284,932 US6361501B1 (en) | 1997-08-26 | 1998-06-18 | Pulse wave diagnosing device |
EP98928556A EP0947160B1 (en) | 1997-08-26 | 1998-06-18 | Pulse wave diagnosing device |
DE69833656T DE69833656T2 (de) | 1997-08-26 | 1998-06-18 | Vorrichtung zur diagnose von pulswellen |
CN98801587A CN1242693A (zh) | 1997-08-26 | 1998-06-18 | 脉波诊断装置、运动指标检测装置、运动强度检测装置、心输出量检测装置、每搏输出量检测装置、心功能诊断装置及其检测方法 |
Applications Claiming Priority (6)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP23007597A JP3728895B2 (ja) | 1997-08-26 | 1997-08-26 | 運動強度検出装置 |
JP9/230075 | 1997-08-26 | ||
JP9/275500 | 1997-10-08 | ||
JP27550097A JP3858379B2 (ja) | 1997-10-08 | 1997-10-08 | 心拍出量検出装置および心機能診断装置 |
JP9/301332 | 1997-10-31 | ||
JP30133297A JP3870514B2 (ja) | 1997-10-31 | 1997-10-31 | 一回拍出量検出装置および心機能診断装置 |
Publications (1)
Publication Number | Publication Date |
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WO1999009884A1 true WO1999009884A1 (fr) | 1999-03-04 |
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ID=27331606
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PCT/JP1998/002706 WO1999009884A1 (fr) | 1997-08-26 | 1998-06-18 | Procede et appareil de mesure, de detection et de diagnostic d'un signal impulsionnel, de la fonction cardiaque et de l'intensite de mouvement |
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US (1) | US6361501B1 (ja) |
EP (1) | EP0947160B1 (ja) |
CN (1) | CN1242693A (ja) |
DE (1) | DE69833656T2 (ja) |
WO (1) | WO1999009884A1 (ja) |
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KR100821409B1 (ko) * | 1999-04-27 | 2008-04-10 | 살바토어 로마노 | 심박출량 측정방법 및 측정장치 |
EP2329765A1 (en) * | 1999-04-27 | 2011-06-08 | Salvatore Romano | Method and apparatus for measuring cardiac flow output |
JP2003535137A (ja) * | 2000-06-07 | 2003-11-25 | ペプリン リサーチ プロプライエタリー リミティッド | 治療効果のある物質−i |
JP2003535136A (ja) * | 2000-06-07 | 2003-11-25 | ペプリン リサーチ プロプライエタリー リミティッド | 治療効果のある物質−iii |
CN101803911A (zh) * | 2010-04-02 | 2010-08-18 | 浙江大学 | 自组织脉搏传感器中的滤波融合方法 |
WO2017047331A1 (ja) * | 2015-09-18 | 2017-03-23 | 日本電気株式会社 | 情報処理装置、情報処理方法および情報処理プログラム |
Also Published As
Publication number | Publication date |
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DE69833656D1 (de) | 2006-04-27 |
EP0947160A4 (en) | 2002-06-26 |
EP0947160B1 (en) | 2006-03-01 |
CN1242693A (zh) | 2000-01-26 |
EP0947160A1 (en) | 1999-10-06 |
DE69833656T2 (de) | 2006-08-17 |
US6361501B1 (en) | 2002-03-26 |
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