WO2001060252A1 - Monitoring electrical activity - Google Patents
Monitoring electrical activity Download PDFInfo
- Publication number
- WO2001060252A1 WO2001060252A1 PCT/GB2001/000629 GB0100629W WO0160252A1 WO 2001060252 A1 WO2001060252 A1 WO 2001060252A1 GB 0100629 W GB0100629 W GB 0100629W WO 0160252 A1 WO0160252 A1 WO 0160252A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- yule
- walker
- output signal
- autocorrelation
- power density
- Prior art date
Links
Classifications
-
- 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
- A61B5/4821—Determining level or depth of anaesthesia
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
- A61B5/372—Analysis of electroencephalograms
- A61B5/374—Detecting the frequency distribution of signals, e.g. detecting delta, theta, alpha, beta or gamma waves
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/30—Input circuits therefor
- A61B5/301—Input circuits therefor providing electrical separation, e.g. by using isolating transformers or optocouplers
Definitions
- the present invention relates to a method of monitoring electrical activity in an animal, especially human brain waves, and apparatus for carrying out the method such as an electroencephalograph.
- the occurrence of new frequencies lower than the alpha band such as delta, induced by the anaesthetic agent can be used to detect the undesirable presence of true anaesthesia if the intention is to maintain a state of sedation.
- the present invention seeks to provide an apparatus and a method, of analysing brain waves which permits these rhythms to be detected when they are very weak. This then permits an indication of the anaesthesia or sedation level to be determined.
- the present invention is not limited to detection of alpha and lower rhythms and could be used to detect other components such as epileptic spikes in the brain wave signal.
- electrical activity is detected and produces a corresponding output signal
- the output signal is combined with a random noise signal to produce a modified signal
- the modified signal is analysed using an autocorrelation technique to detect the relative power density values at a plurality of different frequencies.
- the autocorrelation technique involves use of the Yule- Walker algorithm.
- the ratio of the sum of one or more values of D / at or about the frequencies of the particular rhythms are compared with the sum of the values of D over a wider range of values, and the changes in that ratio may be used to detect the emergence of these rhythms.
- the maximum frequency of the wider range will be at least approximately double that of the maximum frequencies of the rhythms under consideration.
- Yule-Walker methods from which the Yule-Walker coefficients referred to in Equation 1 above are obtained, are a known type of frequency analysis method.
- Yule-Walker methods reference may be made to the book "Digital Signal Processing” (second edition) by J G Proakis and D G Manolakis published by McMillan publishing company, New York.
- the present invention also consists in an electroencephalograph which monitors brain waves using the method discussed above, to indicate the emergence of specific rhythms, and also consists in a method of operation such as an electroencephalograph.
- the present invention further proposes that a series of autocorrelation products be derived from the brain wave signals. These autocorrelation products may then be used directly, to derive the Yule -Walker coefficients, but it is preferable that an averaging technique is applied to them. It would be possible to determine the autocorrelation direct over a relatively long time period, but it is preferable to use a shorter time period and average over those time periods. The advantage of this is that short bursts of noise are then not carried over from one period to the next. Averaging in this way has the disadvantage of slowing detection of trends, and therefore there is the need to compromise between these factors.
- an electroencephalograph preferably converts the brain wave signals to digital signals, to enable those signals to be analysed by a suitably programmed processor.
- the analysis of the relative power density values may then be used to generate a suitable display and/or audible signal, and/or a control signal for other equipment.
- the value corresponding to the comparison of relative power densities discussed above is converted to an index value which is a non-linear function of the initial value, to emphasise changes at low values of the specific rhythm.
- FIG 1 shows an electroencephalograph being an embodiment of the present invention
- Figure 2 shows part of the electroencephalograph of Figure 1.
- an electroencephalograph amplifier unit 10 generates electrical signals corresponding to the brain waves, and passes those signals to an analogue-to-digital converter 11.
- the resulting digital signals are passed to a processor 12, in which they are processed using a Yule- Walker method, as will be described in more detail later.
- the input protection circuitry unit 21 may also act to protect the person to whom the electrodes 20 are connected from failures within the electroencephalograph.
- the input protection circuitry unit 21 is also connected to ground, so that it passes differential signals to an amplifier unit 22.
- That amplifier unit removes common mode noise, and produces a single signal from the input thereto which is then passed to a gain and filter unit 23.
- the gain and filter unit 23 removes high frequency and DC components from the signal, and further amplifies the signal before it is passed to an isolation amplifier unit 24.
- That isolation amplifier unit 24 acts as a isolation barrier between the electroencephalograph amplifier 10 and the analogue to digital converter 11.
- the processor 12 is powered from a power supply unit 13, which may contain a mains connection and a battery back-up so that the power is uninterruptable.
- the program for controlling the processor 12 during operation is stored in a memory unit 14.
- the processor 12 may be connected to a second electroencephalograph amplifier unit 15, by the analogue digital converter 11. That second electroencephalograph amplifier 15 may have the same structure as shown in Figure 2.
- Two auxiliary inputs 16,17 may be provided to allow digitisation of non- isolated inputs from a CAPNOGRAPH or similar equipment.
- FIG 1 also shows that a signal is passed from the processor 12 to the electroencephalograph amplifiers 10, 15.
- This signal is an enabling signal which is passed via an opto-isolator unit 25 (see Figure 2) to an impedance checker oscillator 26 of the electroencephalograph amplifier 10,15.
- the opto-isolator unit 25 thus provides electrical safety isolation between the processor 12 and the electroencephalograph amplifier unit 10,15, in a similar way to the isolation amplifier unit 24.
- the impedance checker oscillator 26 When the impedance checker oscillator 26 is enabled by the signal from the processor 12, it outputs a frequency signal of between e.g. 5 and 10 Hz which is passed via two operational amplifiers 27,28 to generate two signals which are passed via transmission gates 29 to respective resistors Rl, R2.
- the resulting signal may be used to assess the input impedance of the electrodes 20.
- the transmission gates 29 are enabled by the signal from the processor 12, which is output from the opto-isolator 25.
- the processing carried out by the processor 12 will now be described in more detail.
- the present invention makes use of a Yule- Walker method to derive relative power density values.
- theoretical frequency analysis using such methods normally assume steady state conditions, which do not apply to brain wave signals.
- the consistent frequencies of such signals are often strongly amplitude modulated. Irregular waxing and waning occurs for some or all of the frequencies with successive maxima intervals varying within a range of half a second to two seconds.
- the processor 12 analyses the signals corresponding to the brain waves in a series of time periods (epochs).
- the length of time period need not be fixed, and indeed an electroencephalograph according to the present invention may permit the duration of the epochs to be varied. However, an epoch of about 1.5s duration has been found to be suitable. Assuming that the sampling rate of the processor 12 was e.g. 128 Hz, this would result in 192 sample values. This can be generalised, however, to N sample values per epoch, being:
- a modified sampled value a' k may be obtained, as follows.
- a TM* is the numerically greatest sampled value in the epoch
- random (1000) is a random positive integer in the range of 0 to 1000. Such a random positive integer may be obtained from a pseudo-random program of the processor 12.
- this DC component may include a drift component.
- the average value of a' over all the n values is subtracted from each value a'k to derive a further modified value a'V. This process can be carried out for each epoch, and it should be noted that the addition of the random value discussed above does not introduce a further bias.
- each autocorrelation product x p is given by equation 3 below:
- p is the number of the autocorrelation product, varying between 0 and m.
- the values of x p are then a measure in the time domain of the periodic components of the brain wave signals.
- Equation 5 can be solved in any satisfactory way, it has been found that the Levinson-Durbin solution algorithm may be used, as this enables the equation to be solved rapidly. If the sampling rate is at 128 points per second, as previously mentioned, the relative power density D f at a frequency f is then given by Equation 6 below.
- the numerator represents the sum of the relative power density values within the 8 to 12 Hz frequency range in which alpha rhythms occur, whilst the denominator is a sum of the relative power density values over a frequency range of 0.5 to 24 Hz.
- ⁇ r gives a measure of the power density within the range corresponding to alpha rhythms, relative to a much wider frequency range encompassing the range of frequencies corresponding to the alpha rhythms.
- variations in a r represent variations in the power present in alpha rhythms.
- the processor may derive a value oti which is a non linear function of ⁇ r according to Equation 8. Equation 8
- Equation 8 S is a sensitivity factor. If S equals l, ⁇ , and ⁇ r would be the same. In practice, S equals 0.4 is a suitable value.
- ⁇ may be used to control, a display which the operator of the encephalograph may use to detect the emergence of a rhythm.
- a signal may be passed to a LED display 30 which displays the current value of ⁇ ,.
- ⁇ may be presented as a vertical bar on an LCD screen 31 , to give a graphical indication of variations in that value.
- Information may also be passed via a printer port 32 either directly to a printer, or to a suitable computer for further analysis.
- Figure 1 also shows that the processor 12 is connected to a key board 33 which permits the operator to control the electroencephalograph, for example to input parameters such as the duration of each epoch.
- the processor 12 is also connected to a dram memory 34 which permits some data to be stored whilst the electroencephalograph is powered up.
- Equation 5 Equation 5
- Equation 7 it can be seen from Equation 7 that suitable selection of the ranges of the values k in the numerator and denominator of that equation will enable the power of other frequency components to be investigated.
- the present invention has been developed primarily to detect alpha rhythms occurring in the 8 to 12 Hz frequency range, the present invention may be applied to the analysis of other frequency components.
Abstract
Description
Claims
Priority Applications (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE60118705T DE60118705T2 (en) | 2000-02-17 | 2001-02-16 | MONITORING ELECTRICAL ACTIVITY |
EP01905887A EP1255486B1 (en) | 2000-02-17 | 2001-02-16 | Monitoring electrical activity |
US10/203,954 US6748263B2 (en) | 2000-02-17 | 2001-02-16 | Monitoring electrical activity |
AU2001233857A AU2001233857A1 (en) | 2000-02-17 | 2001-02-16 | Monitoring electrical activity |
CA002400348A CA2400348A1 (en) | 2000-02-17 | 2001-02-16 | Monitoring electrical activity |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
GB0003665.7 | 2000-02-17 | ||
GB0003665A GB2359367B (en) | 2000-02-17 | 2000-02-17 | Monitoring electrical activity |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2001060252A1 true WO2001060252A1 (en) | 2001-08-23 |
Family
ID=9885786
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/GB2001/000629 WO2001060252A1 (en) | 2000-02-17 | 2001-02-16 | Monitoring electrical activity |
Country Status (8)
Country | Link |
---|---|
US (1) | US6748263B2 (en) |
EP (1) | EP1255486B1 (en) |
AT (1) | ATE322861T1 (en) |
AU (1) | AU2001233857A1 (en) |
CA (1) | CA2400348A1 (en) |
DE (1) | DE60118705T2 (en) |
GB (1) | GB2359367B (en) |
WO (1) | WO2001060252A1 (en) |
Families Citing this family (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DK2076173T3 (en) * | 2006-09-29 | 2015-02-09 | Univ California | Burst suppression monitoring in induced coma |
US8444559B2 (en) * | 2007-05-04 | 2013-05-21 | Reproductive Research Technologies, Lp | Skin impedance matching system and method for skin/electrode interface |
WO2011119757A2 (en) * | 2010-03-23 | 2011-09-29 | The Reproductive Research Technologies, Lp | Noninvasive measurement of uterine emg propagation and power spectrum frequency to predict true preterm labor and delivery |
US8386026B2 (en) * | 2010-04-12 | 2013-02-26 | Reproductive Research Technologies, L.P. | System and method for acquiring and displaying abdominal EMG signals |
JP5710767B2 (en) | 2010-09-28 | 2015-04-30 | マシモ コーポレイション | Depth of consciousness monitor including oximeter |
US9775545B2 (en) | 2010-09-28 | 2017-10-03 | Masimo Corporation | Magnetic electrical connector for patient monitors |
GB201209638D0 (en) * | 2012-05-30 | 2012-07-11 | Isis Innovation | Perception loss detection |
WO2016057553A1 (en) | 2014-10-07 | 2016-04-14 | Masimo Corporation | Modular physiological sensors |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4846190A (en) * | 1983-08-23 | 1989-07-11 | John Erwin R | Electroencephalographic system data display |
US5211179A (en) * | 1989-07-14 | 1993-05-18 | Ralph Haberl | System and method for analyzing selected signal components in electrocardiographic signals, particularly late potentials in electrocardiograms |
US5299118A (en) * | 1987-06-26 | 1994-03-29 | Nicolet Instrument Corporation | Method and system for analysis of long term physiological polygraphic recordings |
US5458117A (en) * | 1991-10-25 | 1995-10-17 | Aspect Medical Systems, Inc. | Cerebral biopotential analysis system and method |
US5765128A (en) * | 1994-12-21 | 1998-06-09 | Fujitsu Limited | Apparatus for synchronizing a voice coder and a voice decoder of a vector-coding type |
US6011990A (en) * | 1995-10-19 | 2000-01-04 | Arthur Schultz | Method and device for evaluating an EEG carried out in the context of anaesthesia or intensive care |
Family Cites Families (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4616659A (en) * | 1985-05-06 | 1986-10-14 | At&T Bell Laboratories | Heart rate detection utilizing autoregressive analysis |
US4974162A (en) * | 1987-03-13 | 1990-11-27 | University Of Maryland | Advanced signal processing methodology for the detection, localization and quantification of acute myocardial ischemia |
US5010891A (en) * | 1987-10-09 | 1991-04-30 | Biometrak Corporation | Cerebral biopotential analysis system and method |
US5109863A (en) * | 1989-10-26 | 1992-05-05 | Rutgers, The State University Of New Jersey | Noninvasive diagnostic system for coronary artery disease |
US5792062A (en) * | 1996-05-14 | 1998-08-11 | Massachusetts Institute Of Technology | Method and apparatus for detecting nonlinearity in an electrocardiographic signal |
US5940798A (en) * | 1997-12-31 | 1999-08-17 | Scientific Learning Corporation | Feedback modification for reducing stuttering |
-
2000
- 2000-02-17 GB GB0003665A patent/GB2359367B/en not_active Expired - Fee Related
-
2001
- 2001-02-16 CA CA002400348A patent/CA2400348A1/en not_active Abandoned
- 2001-02-16 EP EP01905887A patent/EP1255486B1/en not_active Expired - Lifetime
- 2001-02-16 AT AT01905887T patent/ATE322861T1/en not_active IP Right Cessation
- 2001-02-16 WO PCT/GB2001/000629 patent/WO2001060252A1/en active IP Right Grant
- 2001-02-16 AU AU2001233857A patent/AU2001233857A1/en not_active Abandoned
- 2001-02-16 US US10/203,954 patent/US6748263B2/en not_active Expired - Fee Related
- 2001-02-16 DE DE60118705T patent/DE60118705T2/en not_active Expired - Lifetime
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4846190A (en) * | 1983-08-23 | 1989-07-11 | John Erwin R | Electroencephalographic system data display |
US5299118A (en) * | 1987-06-26 | 1994-03-29 | Nicolet Instrument Corporation | Method and system for analysis of long term physiological polygraphic recordings |
US5211179A (en) * | 1989-07-14 | 1993-05-18 | Ralph Haberl | System and method for analyzing selected signal components in electrocardiographic signals, particularly late potentials in electrocardiograms |
US5458117A (en) * | 1991-10-25 | 1995-10-17 | Aspect Medical Systems, Inc. | Cerebral biopotential analysis system and method |
US5765128A (en) * | 1994-12-21 | 1998-06-09 | Fujitsu Limited | Apparatus for synchronizing a voice coder and a voice decoder of a vector-coding type |
US6011990A (en) * | 1995-10-19 | 2000-01-04 | Arthur Schultz | Method and device for evaluating an EEG carried out in the context of anaesthesia or intensive care |
Also Published As
Publication number | Publication date |
---|---|
EP1255486B1 (en) | 2006-04-12 |
DE60118705D1 (en) | 2006-05-24 |
EP1255486A1 (en) | 2002-11-13 |
AU2001233857A1 (en) | 2001-08-27 |
GB2359367B (en) | 2003-11-05 |
GB0003665D0 (en) | 2000-04-05 |
US20030109796A1 (en) | 2003-06-12 |
CA2400348A1 (en) | 2001-08-23 |
US6748263B2 (en) | 2004-06-08 |
ATE322861T1 (en) | 2006-04-15 |
DE60118705T2 (en) | 2007-04-12 |
GB2359367A (en) | 2001-08-22 |
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