CN100459934C - Identity identifying method and system - Google Patents
Identity identifying method and system Download PDFInfo
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- CN100459934C CN100459934C CNB2006101136771A CN200610113677A CN100459934C CN 100459934 C CN100459934 C CN 100459934C CN B2006101136771 A CNB2006101136771 A CN B2006101136771A CN 200610113677 A CN200610113677 A CN 200610113677A CN 100459934 C CN100459934 C CN 100459934C
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Abstract
The present invention discloses one kind of identity identifying method and system. The identity identifying method includes obtaining the bioelectric signal of the person to be identified, treating the bioelectric signal into bioelectric characteristic vector, matching and comparing the bioelectric characteristic vector with that in the preset template, and confirming the identified person when the matching result meets the set conditions. The present invention can identify identity in high reliability and high safety.
Description
Technical field
The present invention relates to the identity authentication field, particularly relate to a kind of identity identifying method and system.
Background technology
Identity authentication is uniqueness and the legitimacy that is used to confirm identity.Have quite widely in information such as bank, CA center, public security system and security fields and to use.For strengthening safety, increase work efficiency, require identity authentication must discern quickly and accurately by assessor's characteristic information, checking is by assessor's true identity.
In the prior art, the identity authentication technology mainly contains password authentication technology and biological characteristic authenticate technology.The password authentication Technology Need is by assessor's input input identification number and password in identification systems, according to identification number and password whether mate determine whether legal by assessor's identity, during evaluation, only need to be inputed correct identification number and password can obtain identity validation, have advantage fast, easily by the assessor.But the password authentication technological deficiency is very obvious.Mainly be that safety is not high, identification number and password be one group of data for being edited by the assessor just, unauthorized person can adopt pilferage, spies on, and the online means such as software of decoding get access to these data, like this, when unauthorized person uses identification number that undesired means obtain and password, it is legal to be confirmed as identity by mistake, the infringement client interests of just can following one's bent.In the reality, this type of incident also often takes place.
Human biology feature or behavioral trait are applied to identity authentication, then can overcome the deficiency of password authentication technology to a certain extent.Through scientific appraisal, everyone biological property is unique, and its multiple probability can be ignored.Utilizing the human biology feature to carry out identity authentication at present mainly is to utilize features such as human body face picture, iris, fingerprint, palmmprint, sound, person's handwriting, gait.
Consult Fig. 1, carry out the method flow diagram of identity authentication for utilizing fingerprint in the prior art, concrete steps are as follows:
But utilizing fingerprint technique to carry out identification also has its deficiency, may copy fingerprint as high-tech biotechnology, or conceal fingerprint in latex, and this can bring certain hidden danger to fingerprint identification technology.Other all exists by counterfeit hidden danger to a certain extent as utilizing recognition technologies such as people's face, sound, gait, can play tricks by photo such as people's face, and sound and notes can be imitated.Therefore, above-mentioned identity authentication technology is all deposited certain potential safety hazard, and its reliability and safety remain defective.
Summary of the invention
In view of this, the invention provides a kind of identity identifying method and system, be used to improve the reliability and the safety of identity authentication.
A kind of identity identifying method of the present invention obtains by assessor's bioelectrical signals, and described bioelectrical signals comprises myocardium bioelectrical signals and eeg signal; By processing and amplifying, Filtering Processing and analog/digital conversion, the described processing of bioelectric signals is become the bio electricity characteristic parameter; Calculation of characteristic parameters bio electricity characteristic vector according to bioelectrical signals; Described bio electricity characteristic vector and the individual features vector template that prestores are carried out matching ratio; As mate comparative result and reach pre-conditioned, confirm that this is legal by assessor's identity;
Wherein, extracting the bio electricity characteristic parameter in the described bioelectrical signals after processing comprises:
Calculate the slope in wave period of bioelectrical signals;
Calculate time to peak in wave period of bioelectrical signals;
Calculate the variance of sampling point value in the bioelectrical signals periodic waveform;
Calculate the High Order Moment of bioelectrical signals periodic waveform;
Calculate the covariance of bioelectrical signals periodic waveform.
Preferably, the slope in wave period of described calculating bioelectrical signals comprises: the rate of rise of waveform from starting point to first crest of calculating interior bioelectrical signals of each cycle in the bioelectrical signals; The rate of rise from first trough to the second crest; Descending slope from the crest to the minimum point; The rate of rise of last crest.
Preferably, time to peak comprises in wave period of described calculating bioelectrical signals: the waveform that calculates bioelectrical signals in each cycle from starting point to the used time of first crest; From first crest to the last time that crest is used.
Preferably, the variance of sampling point value comprises in the described calculating bioelectrical signals periodic waveform: calculate the variance of sampling point value in preceding n the periodic waveform signal, and calculate the meansigma methods of n variance.
Preferably, the High Order Moment of described calculating bioelectrical signals periodic waveform comprises: calculate the 4 rank squares in each cycle in preceding n the periodic waveform signal, and calculate the meansigma methods of preceding n waveshape signal cycle 4 rank squares.
Preferably, the covariance of described calculating bioelectrical signals periodic waveform comprises: the covariance in n adjacent two cycles of periodic waveform signal before calculating.
Preferably, described method according to characteristic parameter generating feature vector is that characteristic parameter is arranged in sequence.
Preferably, adopt vector quantization method, hidden Markov model method, genetic algorithm, dynamic time warping method or neutral net method to carry out matching ratio.
Preferably, the potential difference of passing through to measure between human body two handss of described bioelectrical signals is obtained.
Preferably, describedly obtain bioelectrical signals, comprising: obtain by assessor's bioelectrical signals, obtain simultaneously by assessor's resistance, body temperature and/or moisture signal by the assessor; After resistance, body temperature and/or moisture signal and the stack of above-mentioned bioelectrical signals, as by assessor's bioelectrical signals.
Compared with prior art, the present invention has the following advantages:
The present invention is used for identity authentication with bioelectrical signals, and bioelectrical signals is everyone exclusive biological property, its repeatably probability can ignore fully, and can not be counterfeit, fully guarantee the reliability and security of identity authentication.
Preferably, the present invention adopts myocardium bioelectrical signals and eeg signal, and myocardium bioelectrical signals and eeg signal feature are obvious, is easy to obtain and handle.
Preferably, the present invention can obtain simultaneously by assessor's resistance, body temperature and/or moisture signal.After resistance, body temperature and/or moisture signal and bioelectrical signals stack,,, further strengthen the reliability and the safety of identity authentication in conjunction with being identified by the multiple biological characteristic of assessor as by assessor's bioelectrical signals.
Description of drawings
Fig. 1 utilizes fingerprint to carry out the method flow diagram of identity authentication in the prior art;
Fig. 2 is the flow chart of identity identifying method embodiment of the present invention;
Fig. 3 behaves body-centered flesh bioelectrical signals at one-period potential difference sketch map over time;
Fig. 4 is by the oscillogram of assessor's myocardium bioelectrical signals;
Fig. 5 is by the oscillogram of assessor's myocardium bioelectrical signals;
The behave principal character parameter detecting sketch map of body-centered flesh bioelectrical signals of Fig. 6;
Fig. 7 is the sketch map of identity authentication system embodiment of the present invention;
Fig. 8 is the circuit diagram of signal amplification unit embodiment of the present invention.
The specific embodiment
For above-mentioned purpose of the present invention, feature and advantage can be become apparent more, the present invention is further detailed explanation below in conjunction with the drawings and specific embodiments.
Core concept of the present invention is that bioelectrical signals is used for identity authentication, and bioelectrical signals is everyone exclusive biological property, its repeatably probability can ignore fully, and can not be counterfeit, fully guarantee the reliability and security of identity authentication.
Bio electricity is the electrical phenomena that organism presents.Produce bioelectric basis from the potential difference inside and outside the cell membrane.When quiet, be in nagative potential in the cell, the extracellular is in nagative potential, claims " resting potential "; Excitation time, intracellular current potential raise and surpassed the extracellular and relatively become positive potential moment, and is just outer negative in temporarily can be changed into, and claims " action potential " that the variation of this current potential only continues several milliseconds, excitedly recovers later original state again.The complicated electricity that organ such as brain and heart is showed changes, and is the summation of their composition cell electricity variation, the bioelectrical signals basically identical of single individuality, and there is bigger difference in the bioelectrical signals of Different Individual.
Identify it is to adopt everyone unique biological characteristic to verify the legitimacy of its identity based on bioelectric biometric identity.In theory, biological characteristic authentication is reliable identity authentication mode, because the intravital biological characteristic signal of its direct end user is represented everyone identity, different people has the probability of identical biological characteristic and can ignore, and can not be by counterfeit, therefore, have high reliability and safety.
The present invention obtains the bioelectrical signals by the assessor by the instrument of special use, and bioelectrical signals can have the semaphore of strong feature for people body-centered flesh bioelectrical signals, eeg signal etc.To obtain again by assessor's bioelectrical signals amplify, after the Filtering Processing, figure after processing carries out particular point A/D (mould/number) conversion, extraction is generated by assessor's bio electricity characteristic vector according to the bio electricity calculation of characteristic parameters then by the characteristic parameter of assessor's bioelectrical signals.
The present invention will be mated by assessor's bio electricity characteristic vector and this bio electricity feature templates signal by the assessor that is stored among the data base in advance.When coupling met or exceeded default threshold value, it was legal by assessor's identity to confirm; When coupling does not does not meet or exceed default threshold value, confirm illegal by assessor's identity.
Consult Fig. 2, be the flow chart of identity identifying method embodiment of the present invention, concrete steps are as follows:
Imported oneself identification numbers such as name, ID (identity number) card No. or numbering by the assessor, so that in the data base, find out bio electricity template signal corresponding with it.
Step 202, obtain by assessor's myocardium bioelectrical signals;
Need be fixed on the collection of being carried out myocardium bioelectrical signals by assessor's finger tip with finger-clipped bioelectrical signals detector when obtaining.Can obtain myocardium bioelectrical signals by the potential difference of measuring between human body two handss.
Human body cardiac muscle bio electricity be the sinuatrial node by heart send once excited, by certain approach and process, pass successively to atrium and ventricle, cause the excitement of whole heart; Therefore, in each cardiac cycle, all there are certain rules electric change propagation direction, approach, order and the time etc. that occur in the heart each several part process of excitation.This bio electricity changes by conductive tissue and body fluid around the heart, is reflected to body surface, and electricity changes to make parts of body also all take place clocklike in each cardiac cycle.Measurement electrode is placed on the cardiac electric change curve that certain position of human body surface writes down out can reflects that the bio electricity in generation, conduction and the recovery process of heart excitement changes system.And the human biological signal of this change curve reflection can be detected through after the amplification of bioelectric amplifier.
See also Fig. 3, Fig. 3 behaves body-centered flesh bioelectrical signals at one-period potential difference (y axle) the variation sketch map of (t axle) in time, and waveform shown in this figure is the oscillogram of a typical bioelectrical signals.Fig. 4, Fig. 5 are that two differences are by the oscillogram of assessor's myocardium bioelectrical signals, through contrast as can be seen, though the feature of the myocardium bioelectrical signals of each individuality can be along with detecting the position and detecting variation constantly and difference to some extent, but, same individual's myocardium bioelectrical signals kept stable, but there is bigger difference in the myocardium bioelectrical signals of Different Individual.Therefore, be easier to discern Different Individual by myocardium bioelectrical signals ratio.
Step 203, to myocardium bioelectrical signals amplify, the conversion of Filtering Processing, analog quantity/digital quantity;
The myocardium bioelectrical signals that collects is amplified by the myocardial electrical signals amplifier, and the myocardium bioelectrical signals after will amplifying carries out Filtering Processing.
Step 204, the myocardium bioelectrical signals after handling is carried out particular point detect, and calculate its characteristic parameter;
The extraction of cardiac muscle bio electricity characteristic parameter is meant the basic feature of extracting bioelectrical signals signal invading the exterior traveller on a long journey, the feature of choosing must be distinguished different from the assessor effectively, and same variation by the assessor is kept relative stability, require calculation of characteristic parameters easy simultaneously, efficient fast algorithm is preferably arranged, to guarantee the real-time of identification.
Fig. 6 is the principal character parameter detecting sketch map to human body cardiac muscle bioelectrical signals, the characteristic parameter of cardiac muscle bioelectrical signals comprises the summit and the valley point of bioelectrical signals, characteristic parameter on the other side comprises: rising and descending slope k1, k2, k3, k4, interval t1, t2 are embodied in:
Calculate the slope in wave period of bioelectrical signals;
Calculate time to peak in wave period of bioelectrical signals;
Calculate the variance of sampling point value in the bioelectrical signals periodic waveform;
Calculate the High Order Moment of bioelectrical signals periodic waveform;
Calculate the covariance of bioelectrical signals periodic waveform.
Slope in wave period of described calculating bioelectrical signals comprises: the rate of rise of waveform from starting point to first crest of calculating interior bioelectrical signals of each cycle in the bioelectrical signals; The rate of rise from first trough to the second crest; Descending slope from the crest to the minimum point; The rate of rise of last crest;
Time to peak comprises in wave period of described calculating bioelectrical signals: the waveform that calculates bioelectrical signals in each cycle from starting point to the used time of first crest; From first crest to the last time that crest is used;
The variance of sampling point value comprises in the described calculating bioelectrical signals periodic waveform: calculate the variance of sampling point value in preceding n the periodic waveform signal, and calculate the meansigma methods of n variance;
The High Order Moment of described calculating bioelectrical signals periodic waveform comprises: calculate the 4 rank squares in each cycle in preceding n the periodic waveform signal, and calculate the meansigma methods of preceding n waveshape signal cycle 4 rank squares.
The covariance of described calculating bioelectrical signals periodic waveform comprises: the covariance in n adjacent two cycles of periodic waveform signal before calculating.
With the characteristic parameter of the result after calculating as myocardium bioelectrical signals.
Step 205, according to the calculation of characteristic parameters bio electricity characteristic vector of bioelectrical signals;
The characteristic parameter of bioelectrical signals arranged in certain sequence can form bioelectric characteristic vector.
Step 206, according to searched corresponding myocardium bio electricity Template Information by assessor's identification number;
Its myocardium bio electricity Template Information might certified crowd be preset to the data base by identification number in institute, the characteristic vector of the myocardium bio electricity Template Information record counterpart personnel's of institute myocardium bioelectrical signals.When needing coupling, access corresponding myocardium bioelectric Template Information according to the identification number of being imported by the assessor.
Step 207, will be compared with Template Information, and determine whether to mate according to the result relatively by the characteristic vector of assessor cardiac muscle bioelectrical signals.
Coupling is meant whether the result of comparison surpasses preset condition, pre-conditionedly can be fixed threshold value, if surpass, represents that then this is passed through identity authentication by the assessor.If do not surpass, represent that then this user does not pass through identity authentication.
In the present embodiment, the coupling comparative approach can adopt vector quantization method, hidden Markov model method, dynamic time warping method or artificial neural network method to carry out matching ratio, and said method has sophisticated application at audio area, and its reliability is very high.
Present embodiment when obtaining by assessor cardiac muscle bioelectrical signals, also can obtain some physiological feature signals by the assessor simultaneously in step 201, as resistance, body temperature and humidity or the like:
With above-mentioned signal with superposeed by assessor's bioelectrical signals after, be processed into the bio electricity characteristic vector by the described method of embodiment again, carry out matching ratio with the bio electricity Template Information, further improve the reliability and the safety of identification.
Identity identifying method based on human biological electricity proposed by the invention can also be realized the identity authentication of multi-biological characteristic information in conjunction with some other biometric technology.
Consult Fig. 7, be the sketch map of a kind of identity authentication system embodiment of the present invention, this system comprises acquiring unit 701, signal processing unit 702, coupling computing unit 703, confirmation unit 704.
Acquiring unit 701 obtains the bioelectrical signals by the assessor by the instrument of special use, and bioelectrical signals can have the semaphore of strong feature for people body-centered flesh bioelectrical signals, eeg signal etc.Acquiring unit 701 obtains bioelectrical signals by the potential difference of measuring between human body two handss.Acquiring unit 701 is sent to signal processing unit 702 with the bioelectrical signals that obtains.
Signal amplification unit 70211 amplifies the bioelectrical signals that collects, and the bioelectrical signals after will amplifying is sent to filter unit 7022.
Analog/digital conversion unit 7023 is characteristic parameter according to extraordinary electro-detection method with the Bioelectrical Wave conversion of signals, as:
Calculate the slope in wave period of bioelectrical signals;
Calculate time to peak in wave period of bioelectrical signals;
Calculate the variance of sampling point value in the bioelectrical signals periodic waveform;
Calculate the High Order Moment of bioelectrical signals periodic waveform;
Calculate the covariance of bioelectrical signals periodic waveform.
Slope in wave period of described calculating bioelectrical signals comprises: the rate of rise of waveform from starting point to first crest of calculating interior bioelectrical signals of each cycle in the bioelectrical signals; The rate of rise from first trough to the second crest; Descending slope from the crest to the minimum point; The rate of rise of last crest.
Time to peak comprises in wave period of described calculating bioelectrical signals: the waveform that calculates bioelectrical signals in each cycle from starting point to the used time of first crest; From first crest to the last time that crest is used.
The variance of sampling point value comprises in the described calculating bioelectrical signals periodic waveform: calculate the variance of sampling point value in preceding n the periodic waveform signal, and calculate the meansigma methods of n variance.
The High Order Moment of described calculating bioelectrical signals periodic waveform comprises: calculate the 4 rank squares in each cycle in preceding n the periodic waveform signal, and calculate the meansigma methods of preceding n waveshape signal cycle 4 rank squares.
The covariance of described calculating bioelectrical signals periodic waveform comprises: the covariance in n adjacent two cycles of periodic waveform signal before calculating.
With the characteristic parameter of above-mentioned inspection result, and characteristic parameter is sent to characteristic vector generation unit 7024 as bioelectrical signals.
Characteristic vector generation unit 7024 is arranged characteristic parameter in certain sequence can form bioelectric characteristic vector, and the bio electricity characteristic vector is sent to coupling computing unit 703.
Acquiring unit 701 also is used to obtain by assessor's resistance, body temperature and moisture signal, and signal processing unit 702 also is used for resistance, body temperature and/or moisture signal and above-mentioned bioelectrical signals stack post processing.
Because bioelectrical signals is very faint, has powerful interference in the detection of biological signal of telecommunication, therefore, designing high-quality signal amplification unit 7021 has many technical difficulties, and requirement must possess following characteristic usually:
1, high input impedance, the bioelectrical signals of human body cardiac muscle are the small-signal sources of high impedance, so the input impedance of bioelectric amplifier must be than higher, thereby reduce the influence of genertor impedance to bioelectric amplifier.
2, high cmrr (CMRR) in order to suppress that the entrained power frequency of human body is disturbed and the interference of other physiological actions that measured parameter is outer, must select for use difference to amplify form.
3, low noise, low drift, for obtain certain letter/make an uproar than input signal, the low-noise performance of pair amplifier has strict requirement.Ideal bioelectric amplifier, can suppressing external interference, to make its intrinsic noise that is attenuated to amplifier be the same order of magnitude.
4, enough big amplification and low-power consumption are arranged.
Consult Fig. 8, be the circuit diagram of signal amplification unit embodiment of the present invention, signal amplification unit 7021 comprises prime difference amplifying unit, DC compensation amplifying unit and back level amplifying unit.
Prime difference amplifying unit comprises operational amplifier A 1 and connects the resistance R 1 and the resistance R 2. of its input
The DC compensation amplifying unit comprises operational amplifier A 2, capacitor C 1, capacitor C 2, resistance R 5, resistance R 6, and the negative input end of operational amplifier A 2 links to each other with the outfan of operational amplifier A 1 by R6 resistance; The outfan of operational amplifier A 2 links to each other with operational amplifier A 1 with resistance R 5 by capacitor C 1 in parallel; The outfan of operational amplifier A 2 links to each other by capacitor C 2 with negative input end.
Back level amplifying unit comprises operational amplifier A 3, capacitor C 3, R7 resistance, resistance R 8, and the negative input end of operational amplifier A 3 is by the outfan of R7 resistance concatenation operation amplifier A1; Parallel resistance R8 and the 3rd capacitor C 3 between the negative input end of operational amplifier A 3 and the outfan.
The polarizing voltage maximum of this circuit can reach 300mV, and the influence that reduces polarizing voltage in the AC coupled of place is necessary.In this circuit, adopted the DC compensation amplifier to offset dc offset.Integrated instrumentation amplifier is during as bioelectrical preamplifier, because the existence of polarizing voltage, the gain of preamplifier can only be in tens times, and the common mode rejection ratio when this just makes integrated amplifier as preamplifier can not reach the highest.
In this circuit, the flip-flop in the prime amplifying signal (input offset voltage that comprises polarizing voltage and instrumentation amplifier) is eliminated by DC offset circuit.Post-amplifier is being born main amplification task, requires amplifier that very low input offset voltage is arranged, in order to avoid after the high-gain amplification, influence output signal.
More than a kind of identity identifying method provided by the present invention and system are described in detail, used specific case herein principle of the present invention and embodiment are set forth, the explanation of above embodiment just is used for helping to understand method of the present invention and core concept thereof; Simultaneously, for one of ordinary skill in the art, according to thought of the present invention, the part that all can change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention.
Claims (10)
1. an identity identifying method is characterized in that, comprising:
Obtain by assessor's bioelectrical signals, described bioelectrical signals comprises myocardium bioelectrical signals and eeg signal;
By processing and amplifying, Filtering Processing and analog/digital conversion, the described processing of bioelectric signals is become the bio electricity characteristic parameter;
Calculation of characteristic parameters bio electricity characteristic vector according to bioelectrical signals;
Described bio electricity characteristic vector and the individual features vector template that prestores are carried out matching ratio;
As mate comparative result and reach pre-conditioned, confirm that this is legal by assessor's identity;
Wherein, the described processing of bioelectric signals is become the bio electricity characteristic parameter, further comprises:
Calculate the slope in wave period of bioelectrical signals;
Calculate time to peak in wave period of bioelectrical signals;
Calculate the variance of sampling point value in the bioelectrical signals periodic waveform;
Calculate the High Order Moment of bioelectrical signals periodic waveform;
Calculate the covariance of bioelectrical signals periodic waveform.
2. method according to claim 1 is characterized in that, the slope in wave period of described calculating bioelectrical signals comprises: the rate of rise of waveform from starting point to first crest of calculating interior bioelectrical signals of each cycle in the bioelectrical signals; The rate of rise from first trough to the second crest; Descending slope from the crest to the minimum point; The rate of rise of last crest.
3. method according to claim 1 is characterized in that, time to peak comprises in wave period of described calculating bioelectrical signals: the waveform that calculates bioelectrical signals in each cycle from starting point to the used time of first crest; From first crest to the last time that crest is used.
4. method according to claim 1 is characterized in that, the variance of sampling point value comprises in the described calculating bioelectrical signals periodic waveform: calculate the variance of sampling point value in preceding n the periodic waveform signal, and calculate the meansigma methods of n variance.
5. method according to claim 1 is characterized in that, the High Order Moment of described calculating bioelectrical signals periodic waveform comprises: calculate the 4 rank squares in each cycle in preceding n the periodic waveform signal, and calculate the meansigma methods of preceding n waveshape signal cycle 4 rank squares.
6. method according to claim 1 is characterized in that, the covariance of described calculating bioelectrical signals periodic waveform comprises: the covariance in n adjacent two cycles of periodic waveform signal before calculating.
7. method according to claim 1 is characterized in that, described method according to characteristic parameter generating feature vector is that characteristic parameter is arranged in sequence.
8. according to each described method in the claim 1 to 7, it is characterized in that, adopt vector quantization method, hidden Markov model method, genetic algorithm, dynamic time warping method or neutral net method to carry out matching ratio.
9. according to each described method in the claim 1 to 7, it is characterized in that described myocardium bioelectrical signals obtains by the potential difference of measuring between human body two handss.
10. according to each described method in the claim 1 to 7, it is characterized in that, describedly obtain bioelectrical signals, comprising by the assessor:
Obtain by assessor's bioelectrical signals, obtain simultaneously by assessor's resistance, body temperature and/or moisture signal;
With resistance, body temperature and/or moisture signal and above-mentioned bioelectrical signals jointly as by assessor's bioelectrical signals.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN101773394B (en) * | 2010-01-06 | 2011-09-07 | 中国航天员科研训练中心 | Identification method and identification system using identification method |
| CN102441229A (en) * | 2010-09-30 | 2012-05-09 | 鼎迈医疗科技(苏州)有限公司 | Patient controller with security confidentiality function and implanted medical system |
| CN103729586A (en) * | 2013-12-20 | 2014-04-16 | 北京握奇数据系统有限公司 | Method and system for authenticating passwords on basis of brain wave signals |
| CN105389004A (en) * | 2015-10-22 | 2016-03-09 | 上海斐讯数据通信技术有限公司 | Brain wave unlocking terminal screen system and method |
| CN107411734A (en) * | 2017-03-06 | 2017-12-01 | 华斌 | A kind of device that user characteristics is obtained according to human-body biological electromagnetic wave |
| CN108784650A (en) | 2017-05-03 | 2018-11-13 | 深圳迈瑞生物医疗电子股份有限公司 | The homology recognition methods of physiological signal and device |
| CN107169432A (en) * | 2017-05-09 | 2017-09-15 | 深圳市科迈爱康科技有限公司 | Biometric discrimination method, terminal and computer-readable recording medium based on myoelectricity |
| CN112261323A (en) * | 2020-10-21 | 2021-01-22 | 淮北市盛世昊明科技服务有限公司 | Network security protection system based on big data platform |
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