WO2018212380A1 - Procédé par lequel un dispositif vestimentaire détecte un modèle d'ecg pour une authentification personnelle - Google Patents
Procédé par lequel un dispositif vestimentaire détecte un modèle d'ecg pour une authentification personnelle Download PDFInfo
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- WO2018212380A1 WO2018212380A1 PCT/KR2017/005222 KR2017005222W WO2018212380A1 WO 2018212380 A1 WO2018212380 A1 WO 2018212380A1 KR 2017005222 W KR2017005222 W KR 2017005222W WO 2018212380 A1 WO2018212380 A1 WO 2018212380A1
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- biosignal
- template
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- peak value
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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
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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
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
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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
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
- A61B5/346—Analysis of electrocardiograms
- A61B5/349—Detecting specific parameters of the electrocardiograph cycle
-
- 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
- A61B5/7246—Details of waveform analysis using correlation, e.g. template matching or determination of similarity
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
- G06F1/16—Constructional details or arrangements
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
- G06F1/16—Constructional details or arrangements
- G06F1/1613—Constructional details or arrangements for portable computers
- G06F1/163—Wearable computers, e.g. on a belt
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/45—Structures or tools for the administration of authentication
Definitions
- the present invention relates to a method for detecting an ECG template, which is a feature that distinguishes individuals from a wearable device that performs personal authentication using an ECG signal, which is a kind of biosignal.
- biometric information such as iris and fingerprint recognition
- Fintech such as being used for financial transactions centering on smartphones.
- biometric information such as iris and fingerprint recognition
- conventional techniques based on biometric information, such as iris and fingerprint recognition have the disadvantage of easily forgery by others.
- fingerprints are vulnerable to theft because they can be obtained in various ways without the consent of the individual, and even in iris recognition, the basic principle is to photograph the iris of the subject.
- ECG-based personal authentication can be divided into on-line and off-line methods.
- the online method performs signal processing while acquiring ECG samples and obtains the final ECG template for authentication. Since the signal processing is performed on a per-sample basis, it has an advantage of easily responding to signal changes, but has a detection threshold. There is a disadvantage in that the convergence of parameters for detection is slow.
- the offline method has the advantage that it is easy to grasp the characteristics of the entire signal by acquiring the ECG samples in advance and storing them in a memory as much as the length (time) to be processed, so that the determination of the detection parameters can be performed quickly. This has the advantage, but it requires a larger amount of memory than the online approach.
- FIG. 1 is a block diagram illustrating a QRS detector for typical ECG template acquisition.
- ECG signals are classified based on the inflection points designated P, Q, R, S, and T.
- the R peak expresses a large value compared to other waves so that it can be distinguished by the naked eye.
- the interval between the R peak and the next R peak determines the heart rate.
- the ECG template is extracted around the R peak through pre-treatment and post-treatment.
- the Pan-Tompkins algorithm based on the first derivative filter is mainly used.
- FIG. 2 illustrates a process of detecting an R peak.
- the Pan-Tompkins algorithm can be said that the R peak exists in the region between the point where the threshold crosses upward and the point which crosses downward, as shown in the following figure. Find. After searching for the R peak, an ECG template including P, Q, R, S, and T waves is detected around the R peak.
- the threshold for determining the threshold is generally the output of the moving average value, the total sample of x ma [n], and the average value for N.
- ⁇ represents a weight
- the threshold-based detection method of Equation 1 preferentially detects a large signal. Therefore, when the acquired signal is distorted due to movement or the like during measurement as shown in FIGS. 3 and 4, the normal R peak is not detected, and abnormal peaks are detected, and thus, detection fails. In the registration process, a signal of 20 seconds or more is usually acquired after processing to reduce noise. If a motion occurs during this 20 seconds, the detection may be affected.
- wearable devices adopting a method of briefly contacting dry electrodes only with a finger when needed may cause unstable contact, and may cause large noise even in fine movements. have.
- the present invention has been made to solve the above problems, an object of the present invention, in the wearable device for performing personal authentication using an ECG signal which is a kind of bio-signal, a signal distorted to extract a stable ECG template
- the present invention provides a method for detecting and removing a region.
- a biosignal template detection method includes: detecting a biosignal template candidate corresponding to a feature for distinguishing an individual; Calculating peak values and positions of the detected biosignal template candidates; And when the position of the biosignal template candidate and the position of the biosignal template satisfy the first condition and the peak value of the biosignal template candidate and the peak value of the biosignal template satisfy the second condition, It includes; adding as a template.
- the first condition is LL p > T i , where L is the position of the biosignal template candidate, L p is the position of the biosignal template, T i is the critical interval, and the second condition is abs ( RR p ) ⁇ R p , where R is the peak value of the biosignal template candidate, R p is the peak value of the biosignal template, and may be 0 ⁇ ⁇ 1.
- the method may further include removing the biosignal template candidate if the first condition or the second condition is not satisfied.
- the detecting step, the calculating step, and the additional step may be repeated until the number of biosignal templates becomes a predetermined number.
- the biosignal template may be a candidate biosignal template having a median peak value among the plurality of candidate biosignal templates.
- the plurality of candidate biosignal templates may be candidate biosignal templates that are less than a predetermined threshold interval apart from an adjacent candidate biosignal template.
- the method for detecting a biosignal template includes: setting a temporary threshold; If the interval between the indexes intersecting the temporary threshold upwards and the indexes intersecting downwards is greater than a predetermined first interval, adding a region between the indexes to the distortion region; and the detecting step includes: The biosignal template candidate may be detected in the excluded region.
- the first region and the second region Can be considered an area.
- the setting step and the additional step may be repeated if there is no distortion area to be added, if the moving average value is within a specific error with the previously calculated moving average value in the area excluding the distortion area, or if the maximum repetition number is repeated. You can stop.
- the personal authentication device detects a biosignal template candidate corresponding to a feature for distinguishing individuals, calculates a peak value and a position of the detected biosignal template candidate, and calculates a biosignal template If the position of the candidate and the position of the biosignal template satisfy the first condition and the peak value of the biosignal template candidate and the peak value of the biosignal template satisfy the second condition, the biosignal template candidate is added to the biosignal template.
- Detection unit And an operation unit configured to perform personal authentication using the biosignal templates detected by the detection unit.
- the position of the biosignal template candidate and the position of the biosignal template satisfy the first condition, and the peak value of the biosignal template candidate and the biosignal template If the peak value satisfies the second condition, adding the biosignal template candidate to the biosignal template; And if the first condition or the second condition is not satisfied, removing the biosignal template candidate.
- the position of the biosignal template candidate and the position of the biosignal template satisfy the first condition, and the peak value of the biosignal template candidate and the peak value of the biosignal template
- an operation unit configured to perform personal authentication using the biosignal templates detected by the detection unit.
- the wearable device when the wearable device is commercialized, it is possible to provide an authentication means with low risk of theft, and may be applied to an electronic employee card, a door lock, a financial field, and the like.
- the risk of theft when used in combination with a relatively high theft risk but provides a superior performance, such as the existing fingerprint and iris has the advantage of lowering the probability of false positives.
- stable performance may be provided even in an embedded system in which a computational capability such as a wearable device is limited.
- FIG. 3 is a diagram illustrating instantaneous noise causing a detection failure
- FIG. 4 is a diagram illustrating a region distortion causing a detection failure
- FIG. 7 is a signal after the distortion region is removed by FIG. 6,
- FIG. 8 is a flowchart of a distortion area detection method according to another embodiment of the present invention.
- FIG. 9 is a block diagram of a wearable device for personal authentication based on ECG according to another embodiment of the present invention.
- An embodiment of the present invention provides a method of effectively detecting and removing signal distortion due to unstable contact when an ECG template is acquired and used for personal authentication in a system that acquires an ECG signal by using a dry electrode such as a wearable device. .
- the distortion of the ECG signal due to movement can be classified into the instantaneous noise generated with a very narrow width and the noise with a wide distortion of a specific region as described above.
- the embodiment of the present invention proposes a method capable of detecting and removing both noise sources alone and in combination.
- FIG. 5 is a flowchart provided to explain an instantaneous noise removing method according to an embodiment of the present invention.
- the R peak is detected based on the threshold value, and the ECG template is not immediately acquired through this, and it is designated as a candidate template first, and whether the template is a normal signal or a signal distorted by noise is determined. The determination is made based on the peak value.
- the first template since the ECG template detected immediately before is assumed to be a normal signal, in order to apply the method according to the embodiment of the present invention, the first template must be a normal ECG template. To ensure this, the following initialization process is performed.
- t bc is smaller than T i (S115-No)
- the c template is discarded and the newly detected ECG template is named c and the interval is compared with the b template (S120, S110, S115). If it is still small (S115-No), the process of detecting a new ECG template again and comparing it with the c template is repeated.
- the R peaks of the three templates for which the interval verification has been completed are compared.
- the median value of the three templates is calculated (S125), and the peak larger than ⁇ times larger than the median value is removed (S130).
- the peak value and the peak position of the median template are defined as R p and L p (S135).
- T i is the minimum spacing between two adjacent R peaks
- ⁇ is a value between 0 and 1 as the ratio of the allowable difference of R peaks.
- a temporary threshold value is set based on the threshold value of Equation 1.
- ⁇ means a positive real number greater than one.
- D L d -L u is larger than a predetermined D T when defining the index L u which intersects this temporary threshold upward and the cross index L d downward, respectively. Determining that it is an area of interest and adding between L u and L d to the removal list.
- the optimal D T and D i can be determined through experiments, but empirically, D i ⁇ 800 ⁇ s, D T ⁇ 400 ⁇ s can be set.
- the area is represented by a set of integer values in the start index and the end index.
- ⁇ is an element that can add a margin to the detected distortion region and is expressed as an integer greater than or equal to zero.
- the above method may be extended by sequentially canceling the distortion area.
- 8 is a flowchart illustrating a method for detecting a repeated distortion region.
- the threshold calculation of Equation 1 is modified as follows.
- the distortion area of Equation 3 is detected by detecting the distortion area (S250).
- the distortion region is removed again through Equation 4, and the average value is newly reset, and the temporary threshold value is updated again through Equations 5 and 2 (S220 to S250). If the stop condition is satisfied (S260-No), the algorithm is stopped, and if it does not converge to the stop condition (S260-Yes), only the number of times set as the maximum repetition number (K max ) is repeated and forcedly terminated (S280).
- Detection thresholds can be set for regions other than this region, and ECG templates can be extracted in the same manner as in the prior art.
- the instantaneous noise elimination method deteriorates performance when a large area is distorted, and the instantaneous noise having a narrow generation range cannot be detected in the distortion area elimination method. Therefore, in order to detect and remove both noise sources, two methods according to an embodiment of the present invention must be combined.
- the instantaneous noise and the residual distortion areas are removed through the instantaneous noise removal method shown in FIG. 5.
- the wearable device includes an input unit 110, a signal processor 120, a detector 130, a calculator 140, a storage 150, and a communicator 160.
- the input unit 110 receives the ECG signal and applies it to the signal processor 120.
- the signal processor 120 performs filtering on the applied ECG signal and removes the distortion region from the ECG signal according to the algorithm shown in FIG. 8.
- the detector 130 detects ECG templates according to the algorithm shown in FIG. 5.
- the calculator 140 registers the ECG templates detected by the detector 130 in the storage 150 or transmits the ECG templates to a server (not shown) through the communicator 160. In addition, the calculator 140 compares the ECG templates detected by the detector 130 with ECG templates stored in the storage 150 or transmits them to the server through the communication unit 160 to perform a personal authentication procedure.
- a gyro sensor or an instantaneous noise and distortion region that distorts a threshold value and fails to detect the ECG template.
- the ECG mentioned in the above embodiment is an example of a biosignal. Therefore, the technical idea of the present invention can be applied to replacing ECG with EEG, EMG as well as other types of bio signals.
- wearable device is also only one example for convenience of description. Of course, other types of devices other than wearable devices are included in the scope of the present invention.
- the technical idea of the present invention can be applied to a computer-readable recording medium containing a computer program for performing the functions of the apparatus and method according to the present embodiment.
- the technical idea according to various embodiments of the present disclosure may be implemented in the form of computer readable codes recorded on a computer readable recording medium.
- the computer-readable recording medium can be any data storage device that can be read by a computer and can store data.
- the computer-readable recording medium may be a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical disk, a hard disk drive, or the like.
- the computer-readable code or program stored in the computer-readable recording medium may be transmitted through a network connected between the computers.
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Abstract
L'invention concerne un procédé par lequel un dispositif vestimentaire détecte un modèle d'ECG pour une authentification personnelle. Selon un mode de réalisation de la présente invention, un procédé de détection de modèle de signal biologique détecte un modèle candidat de signal biologique correspondant à une caractéristique par laquelle un individu est identifié, calcule une valeur de crête et un emplacement du modèle candidat détecté de signal biologique, et ajoute le modèle candidat de signal biologique en tant que modèle de signal biologique lorsque l'emplacement du modèle candidat de signal biologique et un emplacement du modèle de signal biologique satisfont une condition spécifique, et lorsque la valeur de crête du modèle candidat de signal biologique et une valeur de crête du modèle de signal biologique satisfont une condition spécifique. Par conséquent, un modèle d'ECG stable peut être extrait.
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KR1020170062119A KR101957019B1 (ko) | 2017-05-19 | 2017-05-19 | 개인인증을 위한 웨어러블 디바이스의 ecg 템플릿 검출 방법 |
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Cited By (1)
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GB2570749A (en) * | 2017-09-05 | 2019-08-07 | B Secur Ltd | Wearable authentication device to prevent transfer of authentication |
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KR20210027785A (ko) | 2019-09-03 | 2021-03-11 | 삼성전자주식회사 | 생체 신호 측정용 전자 장치 |
KR20210048930A (ko) * | 2019-10-24 | 2021-05-04 | 삼성전자주식회사 | 심전도 데이터를 이용한 사용자 검증 장치 및 그 방법 |
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Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20060053812A (ko) * | 2004-11-17 | 2006-05-22 | 삼성전자주식회사 | 생체신호를 이용한 생체 인식 장치 및 방법 |
KR100718125B1 (ko) * | 2005-03-25 | 2007-05-15 | 삼성전자주식회사 | 생체신호와 인공신경회로망을 이용한 생체인식 장치 및방법 |
JP2010504793A (ja) * | 2006-09-29 | 2010-02-18 | コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ | Ecg/ppgベースのバイオメトリクスのためのテンプレート合成 |
KR20130072728A (ko) * | 2011-12-22 | 2013-07-02 | 삼성전자주식회사 | R-피크 검출 장치 및 그 제어 방법 |
US20150373019A1 (en) * | 2014-06-24 | 2015-12-24 | Abdulmotaleb El Saddik | Electrocardiogram (ecg) biometric authentication |
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KR101454790B1 (ko) * | 2013-02-20 | 2014-10-28 | 동서대학교산학협력단 | 템플릿 기반 심전도 신호 압축 및 복원 방법 |
KR102257300B1 (ko) * | 2014-09-01 | 2021-05-27 | 삼성전자주식회사 | 심전도 신호를 이용한 사용자 인증 방법 및 장치 |
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Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20060053812A (ko) * | 2004-11-17 | 2006-05-22 | 삼성전자주식회사 | 생체신호를 이용한 생체 인식 장치 및 방법 |
KR100718125B1 (ko) * | 2005-03-25 | 2007-05-15 | 삼성전자주식회사 | 생체신호와 인공신경회로망을 이용한 생체인식 장치 및방법 |
JP2010504793A (ja) * | 2006-09-29 | 2010-02-18 | コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ | Ecg/ppgベースのバイオメトリクスのためのテンプレート合成 |
KR20130072728A (ko) * | 2011-12-22 | 2013-07-02 | 삼성전자주식회사 | R-피크 검출 장치 및 그 제어 방법 |
US20150373019A1 (en) * | 2014-06-24 | 2015-12-24 | Abdulmotaleb El Saddik | Electrocardiogram (ecg) biometric authentication |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
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GB2570749A (en) * | 2017-09-05 | 2019-08-07 | B Secur Ltd | Wearable authentication device to prevent transfer of authentication |
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