JP6222342B2 - Personal identification device - Google Patents

Description

The present invention relates to a personal identification equipment, in particular, it relates to a personal identification equipment using a high frequency electrocardiogram.

  In recent years, for example, in the field of security systems, biometric personal authentication using biometric information possessed by individuals has been put into practical use. As such biometrics personal authentication, for example, those using organ shapes such as fingerprints and vein authentication, and those using biological signals such as voiceprints and brain waves are known. In addition, a technique for identifying an individual using an electrocardiogram (hereinafter, also referred to as “ECG (Electrocardiogram)”) as a biological signal is also known (see, for example, Patent Document 1).

  In Patent Document 1, a difference between an ECG pattern of a plurality of persons and an ECG pattern of an individual is extracted and stored in advance, and then, the measured ECG pattern of the individual to be identified and the ECG pattern of the plurality of persons are compared. There is disclosed a technique for identifying (identifying) an individual to be identified by obtaining a difference and comparing the obtained difference with an individual difference stored in advance.

  Non-Patent Document 1 proposes a personal authentication system using a high-frequency electrocardiogram (hereinafter also referred to as “HFECG (High Frequency Electrocardiogram)”) in which a low-frequency component is removed from a normal ECG. More specifically, in this personal authentication system, first, a normal ECG and a HFECG waveform obtained by removing low frequency components from the ECG are acquired. Next, the R wave of normal ECG is specified, and 0.2 sec. HFECG is cut out in the range of Then, the cut out HFECG is compared with the registration data (5-beat synchronous addition waveform) for the registered number of persons registered in advance, and the registrant who has the highest degree of coincidence is output. Here, the frequency band of normal ECG (normal electrocardiogram) is about 0.05 to 100 Hz, and the frequency band of HFECG (high frequency electrocardiogram) is about 40 to 300 Hz.

JP 2013-150806 A

Yuta Endo, Yuichi Shimatani, Masaki Kyosai, "Development of personal authentication system using high-frequency electrocardiogram-Adoption of algorithm with low processing volume", Proc. 13th SICE System Integration Division Annual Conference (SI2012), 2012 December 18th to 20th, Fukuoka, p. 0816-0819

  By the way, since the technique described in Patent Document 1 uses a normal ECG for personal identification, for example, noise of about several Hz due to body movement artifacts, etc., and commercial power supply noise (50 Hz / 60 Hz in Japan) The personal identification accuracy may be reduced. Also, in ECG, waveform distortion is likely to occur due to baseline fluctuations (1 Hz or less), and the identification accuracy deteriorates. Furthermore, the normal ECG waveform including the P wave and T wave changes depending on the heart rate, which also contributes to the deterioration of the identification accuracy.

  On the other hand, according to the personal authentication system using HFECG described in Non-Patent Document 1, since the low-frequency component of ECG is removed, for example, the influence of noise caused by body movement artifacts or the influence of baseline fluctuations Compared with the identification technique using ECG described in Patent Document 1, it is possible to improve individual identification accuracy. However, when various kinds of noise are added, the maximum value of the R wave peak is shifted from the true peak position, and thus a shift on the time axis may occur in the extracted HFECG waveform. Here, in this personal authentication system, an individual is identified based on the degree of coincidence between the extracted HFECG and registered data. Therefore, if the above-described deviation on the time axis occurs, the degree of coincidence of both decreases, and the identification accuracy is reduced. May decrease.

The present invention has been made to solve the above problems, to provide a personal identification Oite the equipment, personal identification equipment capable to improve the identification accuracy of the individual using the high frequency electrocardiogram For the purpose.

  The personal identification device according to the present invention has at least a pair of electrocardiogram electrodes, an electrocardiogram acquisition unit that acquires an electrocardiogram, and a high frequency that removes a low-frequency component from the electrocardiogram acquired by the electrocardiogram acquisition unit and acquires a high-frequency electrocardiogram An electrocardiogram acquisition means; an extraction means for differentiating the electrocardiogram to extract a zero cross point corresponding to the peak of the R wave; and a cutting means for cutting out a high frequency electrocardiogram for a predetermined range including the zero cross point extracted by the extraction means; A high-frequency electrocardiogram of a plurality of registrants cut out by the cut-out means is stored in advance as a registered high-frequency electrocardiogram, a high-frequency electrocardiogram of the identification target person cut out by the cut-out means, and a pre-stored registered high-frequency electrocardiogram An identification means for comparing an electrocardiogram and identifying a person to be identified based on the similarity between the two is provided.

  The personal identification method according to the present invention includes an electrocardiogram acquisition step of acquiring an electrocardiogram by at least a pair of electrocardiographic electrodes, and a high-frequency electrocardiogram acquisition step of removing a low-frequency component from the electrocardiogram acquired in the electrocardiogram acquisition step An extraction step for differentiating the electrocardiogram to extract a zero-cross point corresponding to the peak of the R wave, a cut-out step for cutting out a high-frequency electrocardiogram for a predetermined range including the zero-cross point extracted in the extraction step, and a cut-out step A storage step for storing the high-frequency electrocardiograms of a plurality of registrants cut out in advance as a registered high-frequency electrocardiogram, a high-frequency electrocardiogram for the identification subject cut out in the cut-out step, and a pre-stored registered high-frequency electrocardiogram An identification step for comparing and identifying the person to be identified based on the degree of similarity between the two And butterflies.

  According to the personal identification device or the personal identification method of the present invention, an electrocardiogram is differentiated, a zero cross point corresponding to the peak of the R wave is extracted, and a high frequency electrocardiogram is cut out for a predetermined range including the zero cross point. Therefore, the peak position of the R wave can be specified more accurately, and the shift on the time axis of the cut out high frequency electrocardiogram can be reduced. Therefore, it is possible to accurately match the peaks of the extracted identification target person's high-frequency electrocardiogram and the pre-stored registered high-frequency electrocardiogram, and to accurately determine the degree of similarity (matching degree) between the two. . As a result, personal identification accuracy can be further improved.

  In the personal identification device according to the present invention, the extracting means extracts the zero cross points corresponding to the Q wave peak and the S wave peak, respectively, and the cutting means is based on the zero cross points extracted by the extracting means, It is preferable to extract the Q point and the S point of the electrocardiogram and cut out a high-frequency electrocardiogram between the Q point and the S point.

  In this way, the waveform region (cutout range) of the high-frequency electrocardiogram used when obtaining the similarity can be limited to the QRS wave portion having a strong signal strength. Further, it is possible to remove a portion outside the QRS wave where noise is likely to travel. Therefore, it is possible to further improve resistance to noise.

  The personal identification device according to the present invention has at least a pair of electrocardiogram electrodes, an electrocardiogram acquisition unit that acquires an electrocardiogram, and a high frequency that removes a low-frequency component from the electrocardiogram acquired by the electrocardiogram acquisition unit and acquires a high-frequency electrocardiogram An electrocardiogram acquisition means, an extraction means for extracting the peak centroid of the R wave from the electrocardiogram as a reference point on the R wave, and a cutout for cutting out a high-frequency electrocardiogram for a predetermined range including the reference point on the R wave extracted by the extraction means A storage means for storing in advance a registered high-frequency electrocardiogram as a registered high-frequency electrocardiogram; a high-frequency electrocardiogram of a person to be identified cut out by the cutting-out means; And an identification means for comparing the registered high-frequency electrocardiogram and identifying the person to be identified based on the similarity between the two.

  According to the personal identification device of the present invention, the peak centroid of the R wave is extracted from the electrocardiogram as a reference point on the R wave, and a high frequency electrocardiogram is cut out for a predetermined range including the reference point on the R wave. Therefore, the peak position of the R wave can be specified accurately, and the deviation on the time axis of the cut out high frequency electrocardiogram can be reduced. Therefore, it is possible to accurately match the peaks of the extracted identification target person's high-frequency electrocardiogram and the pre-stored registered high-frequency electrocardiogram, and to accurately determine the degree of similarity (matching degree) between the two. . As a result, personal identification accuracy can be further improved.

  The personal identification device according to the present invention has at least a pair of electrocardiogram electrodes, an electrocardiogram acquisition unit that acquires an electrocardiogram, and a high frequency that removes a low-frequency component from the electrocardiogram acquired by the electrocardiogram acquisition unit and acquires a high-frequency electrocardiogram An electrocardiogram acquisition means, an extraction means for extracting a midpoint at the half value of the peak amplitude of the R wave from the electrocardiogram as a reference point on the R wave, and a predetermined range including the reference point on the R wave extracted by the extraction means Cutting means for cutting out a high-frequency electrocardiogram, storage means for storing high-frequency electrocardiograms of a plurality of registrants cut out by the cutting-out means in advance as registered high-frequency electrocardiograms, and high-frequency of the person to be identified cut out by the cutting-out means An electrocardiogram is compared with a registered high-frequency electrocardiogram stored in advance, and an identification means for identifying a person to be identified based on the similarity between both is provided.

  According to the personal identification device of the present invention, the midpoint at the half value of the peak amplitude of the R wave is extracted from the electrocardiogram as a reference point on the R wave, and a high frequency electrocardiogram is obtained for a predetermined range including the reference point on the R wave. Is cut out. Therefore, the peak position of the R wave can be specified accurately, and the deviation on the time axis of the cut out high frequency electrocardiogram can be reduced. Therefore, it is possible to accurately match the peaks of the extracted identification target person's high-frequency electrocardiogram and the pre-stored registered high-frequency electrocardiogram, and to accurately determine the degree of similarity (matching degree) between the two. . As a result, personal identification accuracy can be further improved.

  In the personal identification device according to the present invention, the identification means obtains the similarity between the high-frequency electrocardiogram of the person to be identified and each of the plurality of registered high-frequency electrocardiograms, and the registrant of the registered high-frequency electrocardiogram having the highest similarity is the identification person. It is preferable to determine that there is.

  In this case, the identification target person's high-frequency electrocardiogram and each of the plurality of registered high-frequency electrocardiograms are compared, and the registrant of the registered high-frequency electrocardiogram having the maximum similarity is determined as the identification target person. Therefore, it is possible to identify a relatively most likely registrant as an identification target person from registrants of registered high-frequency electrocardiograms registered in advance.

  In the personal identification device according to the present invention, when the identification means has a similarity between the identification target person's high-frequency electrocardiogram and the registered high-frequency electrocardiogram greater than or equal to a predetermined threshold value, the registration person of the registered high-frequency electrocardiogram is the identification object person. It is preferable to determine that there is.

  In this way, absolute identification accuracy can be improved. Further, it is possible to arbitrarily adjust the identification accuracy by adjusting the threshold value.

  The personal identification device according to the present invention includes normalizing means for normalizing the amplitude of the high-frequency electrocardiogram cut out by the cutting-out means, and the storage means is a high-frequency electrocardiogram of a plurality of registrants normalized by the normalizing means. Is stored in advance as a registered high-frequency electrocardiogram, and the identification means compares the normalized high-frequency electrocardiogram of the person to be identified with the registered high-frequency electrocardiogram stored in advance and obtains the similarity between the two. Is preferred.

  By the way, the amplitude of the electrocardiogram may change depending on the measurement conditions. For example, when the area in contact with the electrocardiographic electrode is small or when it is dry in winter, the amplitude of the electrocardiographic signal may be small. However, in this case, both the registered high-frequency electrocardiogram stored in advance and the high-frequency electrocardiogram of the person to be identified are normalized, and the degree of similarity is obtained in a form in which the amplitude scales are aligned. Therefore, it is possible to determine the degree of similarity between both more accurately.

  The personal identification device according to the present invention includes a resolution converting means for converting the resolution of the high-frequency electrocardiogram cut out by the cutting-out means, and the storage means converts the resolution of the high-frequency electrocardiogram by the resolution converting means into a plurality of registrant high-frequency electrocardiograms. Is stored in advance as a registered high-frequency electrocardiogram, and the identification means compares the high-frequency electrocardiogram to be identified whose resolution has been converted with the registered high-frequency electrocardiogram that has been previously stored with the resolution converted, and determines the similarity between the two. It is preferable.

  In this way, by appropriately setting (converting) the resolution (definition when discretizing the amplitude axis and time axis of the waveform), while maintaining the shape of the characteristic high-frequency ECG waveform, noise and the like The fluctuation component can be removed. Therefore, the tolerance to noise can be improved, and the individual identification accuracy can be further increased.

  In the personal identification device according to the present invention, the resolution conversion means converts the resolution of the high-frequency electrocardiogram into a plurality of different resolutions, and the identification means converts the similarity for each of the identification target person's high-frequency electrocardiograms converted into the plurality of different resolutions. Is preferably obtained.

  In this way, by setting (converting) optimum resolutions for noise having various frequency components, various noises can be removed while maintaining the characteristic high-frequency ECG waveform shape. . Therefore, it is possible to more effectively prevent the determination accuracy of the similarity between the identification target person's high-frequency electrocardiogram and the registered high-frequency electrocardiogram from being reduced by noise.

  The personal identification device according to the present invention comprises a high-frequency electrocardiogram cut out by the cutting-out means and a resolution conversion means for converting the resolution of a plurality of registered high-frequency electrocardiograms stored in the storage means, and the identification means converts the resolution. It is preferable to compare the identified high-frequency electrocardiogram and the registered high-frequency electrocardiogram whose resolution has been converted to determine the similarity between the two.

  Even in this case, by appropriately setting (converting) the resolution, it is possible to remove fluctuation components such as noise while maintaining the shape of the characteristic high-frequency electrocardiogram waveform. Therefore, the tolerance to noise can be improved, and the individual identification accuracy can be further increased.

  In the personal identification device according to the present invention, the resolution conversion means converts the resolution of each of the high-frequency electrocardiogram and the registered high-frequency electrocardiogram into a plurality of different resolutions, and the identification means converts the high-frequency electrocardiogram of the identification target person into a plurality of different resolutions. It is preferable to obtain the similarity for each of the registered high-frequency electrocardiograms.

  In this way, by setting (converting) optimum resolutions for noise having various frequency components, various noises can be removed while maintaining the characteristic high-frequency ECG waveform shape. . Therefore, it is possible to more effectively prevent the determination accuracy of the similarity between the identification target person's high-frequency electrocardiogram and the registered high-frequency electrocardiogram from being reduced by noise.

  In the personal identification device according to the present invention, the identification unit calculates the absolute value of the difference in amplitude between the identification target person's high-frequency electrocardiogram and the registered high-frequency electrocardiogram for each predetermined period on the time axis, and calculates the absolute value of the difference. It is preferable to obtain the similarity between the two based on the sum.

  In this way, the degree of similarity between the identification target person's high-frequency electrocardiogram and the registered high-frequency electrocardiogram can be quantitatively determined by a relatively simple calculation. Therefore, even if the number of registrants (registered high-frequency electrocardiogram) increases, the amount of calculation does not increase rapidly, and it is possible to prevent a delay in processing due to a rapid increase in calculation load (processing load).

  In the personal identification device according to the present invention, it is preferable that the pair of electrocardiographic electrodes constituting the electrocardiogram acquisition means are attached in contact with both sides of the identification subject's neck.

  In this way, for example, compared with the case of acquiring an electrocardiogram / high-frequency electrocardiogram by holding the device in hand, there is less force applied to the body when acquiring the electrocardiogram / high-frequency electrocardiogram, so that the electromyogram noise is reduced. Can do.

  In the personal identification device according to the present invention, it is preferable that the pair of electrocardiographic electrodes constituting the electrocardiogram acquisition means are attached in contact with both shoulders or both upper arms of the person to be identified.

  In this way, an electrocardiogram / high-frequency electrocardiogram can be acquired without being conscious, and since there is little force applied to the body when the electrocardiogram / high-frequency electrocardiogram is acquired, electromyogram noise can be reduced.

  In the personal identification device according to the present invention, the electrocardiogram acquisition means is formed in a wristwatch shape, and when attached to the wrist of one hand of the person to be identified, the heart provided on the back side that comes into contact with the wrist It is preferable to include an electric electrode and an electrocardiographic electrode provided on the surface side so that the finger of the other hand can come into contact therewith.

  In this way, when the person to be identified wears the device on the wrist of one hand, for example, by touching the surface (electrocardiogram electrode) of the device with the finger of the other hand, the electrocardiogram / high-frequency electrocardiogram can be easily obtained. Acquisition can be done.

  ADVANTAGE OF THE INVENTION According to this invention, in the personal identification device and personal identification method using a high frequency electrocardiogram, it becomes possible to improve an individual identification precision more.

It is a block diagram which shows the structure of the personal identification device which concerns on embodiment. It is a figure for demonstrating the detection method of the peak position of R wave. It is a figure for demonstrating the extraction method of HFECG. It is a figure for demonstrating how to obtain | require the similarity of HFECG of an identification subject person and registration HFECG. It is a flowchart which shows the process sequence of the personal identification process by the personal identification device which concerns on embodiment. It is a flowchart which shows the other process sequence of the personal identification process by the personal identification device which concerns on embodiment. It is a figure which shows the external appearance of a neckband type electrocardiogram / high-frequency electrocardiogram acquisition part. It is a figure which shows the external appearance of a wearable type electrocardiogram / high-frequency electrocardiogram acquisition part. It is a figure which shows the external appearance of a wristwatch-shaped electrocardiogram / high-frequency electrocardiogram acquisition part.

  DESCRIPTION OF EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the drawings. In the drawings, the same reference numerals are used for the same or corresponding parts. Moreover, in each figure, the same code | symbol is attached | subjected to the same element and the overlapping description is abbreviate | omitted.

  First, the configuration of the personal identification device 1 according to the embodiment will be described with reference to FIG. FIG. 1 is a block diagram showing the configuration of the personal identification device 1.

  The personal identification device 1 uses a high frequency electrocardiogram (HFECG) to identify an individual with high accuracy. Therefore, the personal identification device 1 includes an electrocardiogram (ECG) and an electrocardiogram / high-frequency electrocardiogram acquisition unit 10 that acquires the HFECG, and the acquired identification target person's HFECG and a pre-stored registered high-frequency electrocardiogram (registered HFECG). A signal processing unit 20 for identifying a person to be identified based on a comparison result (similarity) is provided. Hereinafter, each component will be described in detail.

  The electrocardiogram / high-frequency electrocardiogram acquisition unit 10 acquires ECG and removes a low-frequency component from the acquired ECG to acquire HFECG. Therefore, the electrocardiogram / high-frequency electrocardiogram acquisition unit 10 includes a pair of electrocardiogram electrodes (first electrocardiogram electrode 11 and second electrocardiogram electrode 12), a signal amplification unit 13, an analog signal processing unit 14, an A / D conversion unit 15, A digital signal processing unit 16, a low-pass filter (LPF) 17, and a high-pass filter (HPF) 18 are included. The electrocardiogram / high-frequency electrocardiogram acquisition unit 10 functions as an electrocardiogram acquisition unit and a high-frequency electrocardiogram acquisition unit described in the claims.

  The first electrocardiogram electrode 11 and the second electrocardiogram electrode 12 detect an electrocardiogram signal, and an electrocardiogram signal corresponding to a potential difference between the first electrocardiogram electrode 11 and the second electrocardiogram electrode 12 is generated. Output. The signal amplifying unit 13 is configured by an amplifier using an operational amplifier, for example, and amplifies the electrocardiogram signals detected by the first electrocardiogram electrode 11 and the second electrocardiogram electrode 12. The amplified electrocardiogram signal is output to the analog signal processing unit 14 and the digital signal processing unit 16 provided in the subsequent stage.

  The analog signal processing unit 14 and the digital signal processing unit 16 remove components (noise) other than normal ECG and HFECG, and perform filtering processing for improving S / N. The analog signal processing unit 14 and / or the digital signal processing unit 16 include a high-pass filter (HPF) having characteristics matched to ECG and a characteristic matching HFECG as a filter for passing both ECG and HFECG frequency bands. Low pass filter (LPF). Note that the analog signal processing unit 14 and / or the digital signal processing unit 16 are also provided with a band reject filter (BRF) or the like for removing hum noise of the commercial power supply as necessary.

  The electrocardiogram signal output from the digital signal processing unit 16 is separated into ECG and HFECG by a low-pass filter (LPF) 17 and a high-pass filter (HPF) 18. That is, the low-pass filter (LPF) 17 generates an ECG (see the lower part of FIG. 3) by removing unnecessary high-frequency components from the electrocardiogram signal output from the digital signal processing unit 16 and outputs it. On the other hand, the high-pass filter (HPF) 18 removes unnecessary low-frequency components from the electrocardiogram signal output from the digital signal processing unit 16 to generate and output HFECG (see the upper part of FIG. 3). Here, the frequency band of normal ECG is about 0.05 to 100 Hz, and the frequency band of HFECG is about 40 to 300 Hz. In FIG. 1, ECG and HFECG are divided after the digital signal processing unit 16. However, since the signal component of HFECG is very small, the analog circuit scale becomes large. A configuration may be adopted in which ECG and EFECG are separated before the amplification unit 13.

  The electrocardiogram / high-frequency electrocardiogram acquisition unit 10 is connected to the signal processing unit 20, and the acquired ECG and HFECG are input to the signal processing unit 20.

  As described above, the signal processing unit 20 identifies the identification target person based on the comparison result (similarity) between the acquired HFECG of the identification target person and the registered HFECG stored in advance. Therefore, the signal processing unit 20 includes a peak extraction unit 21, a HFECG extraction unit 22, a normalization unit 23, a resolution conversion unit 24, a HFECG storage unit 25, and a personal identification unit 26.

  Here, the signal processing unit 20 includes a CPU that performs arithmetic processing, a ROM that stores programs and data for causing the CPU to execute each processing, a RAM that temporarily stores various data such as arithmetic results, a battery, and the like. It is composed of a backup RAM for storing the stored contents, an input / output I / F, and the like. In the signal processing unit 20, the functions of the above-described units are realized by executing a program stored in the ROM by the CPU. Note that an FPGA without programming may be used instead of the CPU.

  As shown in FIG. 2, the peak extraction unit 21 first differentiates the ECG (see the thick solid line in FIG. 2) input from the electrocardiogram / high-frequency electrocardiogram acquisition unit 10 to obtain a differentiated waveform (a fine waveform in FIG. 2). (See broken line). Then, a zero cross point corresponding to the peak of the R wave is extracted from the differential waveform. That is, the peak extraction unit 21 functions as an extraction unit described in the claims. In addition, it is good also as a structure which performs waveform shaping processes, such as smoothing, after a differentiation process. On the other hand, when a QRS wave is cut out by the HFECG cutout unit 22 to be described later, the peak extraction unit 21 applies each of the peak of the Q wave and the peak of the S wave in addition to the zero cross point corresponding to the peak of the R wave. The corresponding zero cross point is also extracted. The zero cross point (information for specifying a peak such as an R wave) extracted by the peak extraction unit 21 is output to the HFECG extraction unit 22.

  The HFECG cutout unit 22 cuts out the HFECG for a predetermined time range including the zero cross point (R wave peak) extracted by the peak extraction unit 21. The HFECG cutting part 22 functions as a cutting means described in the claims. More specifically, as shown in FIG. 3, the HFECG cutout unit 22 is based on the R wave peak extracted by the peak extraction unit 21 and has a predetermined time zone before and after the R wave peak as a reference ( Waveforms belonging to Tpre and Tpost in FIG. 3 are cut out. Here, it is desirable that Tpre and Tpost have a QRS range in which there are many high-frequency signal components. The HFECG cutout unit 22 extracts the Q point and the S point of the ECG based on the zero cross point extracted by the peak extraction unit 21, and the HFECG (QRS wave) between the Q point and the S point. May be cut out. The HFECG extracted by the HFECG extraction unit 22 is output to the normalization unit 23. Instead of the above-described method of cutting out HFECG using the zero cross point (R wave peak) of the ECG differential waveform as a reference point, for example, the R wave peak centroid is calculated and the centroid is extracted as a reference point (R A method of setting a reference point on the wave), a method of cutting out the midpoint at the half value of the amplitude of the peak of the R wave, and using it as a reference point (reference point on the R wave) can also be used.

  The normalizing unit 23 normalizes the amplitude of the HFECG cut out by the HFECG cutout unit 22. That is, the normalization unit 23 functions as normalization means described in the claims. The HFECG normalized by the normalization unit 23 is output to the resolution conversion unit 24.

  The resolution conversion unit 24 converts the resolution of the HFECG cut out by the HFECG cutout unit 22 and normalized by the normalization unit 23. That is, the resolution conversion unit 24 performs requantization and re-sampling of the HFECG waveform, and converts the degree of discretization in the amplitude direction and the time direction (corresponding to the mesh roughness in FIG. 4) to a direction in which the data amount decreases. To do. That is, the resolution conversion unit 24 functions as the resolution conversion unit described in the claims. Here, by appropriately setting the number of re-quantization bits and the frequency (resolution) of re-sampling, it is possible to remove fluctuation components such as noise while maintaining a characteristic waveform shape. Note that when multi-resolution analysis is executed, the resolution conversion unit 24 converts the resolution of HFECG into a plurality of different resolutions (for example, about four patterns). The HFECG whose resolution has been converted by the resolution conversion unit 24 is output to the HFECG storage unit 25 (during registration) or the personal identification unit 26 (during identification).

  The HFECG storage unit 25 includes, for example, the above-described backup RAM and the like. The HFECGs of a plurality of registrants that have been cut out by the HFECG cutout unit 22 and subjected to normalization and resolution conversion are registered in advance (in advance) as registered HFECGs. Remember. That is, the HFECG storage unit 25 functions as a storage unit described in the claims. In addition, the HFECG waveform of 1 beat or more is used for the registration of HFECG. Since the registered waveform may be disturbed depending on measurement conditions and the like, the registered waveform is usually generated by measuring HFECG of a plurality of beats, selecting a waveform having a high correlation coefficient, or calculating an average waveform. Also, since the HFECG waveform may change due to body growth, heart disease, etc., it is desirable to correct the registered waveform in a timely manner. The registered waveform correction may be performed by the registrant or may be performed automatically and periodically.

  The personal identification unit 26 compares the HFECG of the person to be identified that has been subjected to normalization and resolution conversion after being cut out, and the registered HFECG that has been normalized and stored after conversion of the resolution. The person to be identified is identified based on the similarity between the two. That is, the personal identification unit 26 functions as identification means described in the claims. In the case of performing so-called multi-resolution analysis, the personal identification unit 26 applies a plurality of (for example, about 4 patterns) HFECG of the identification target person converted to different resolutions to the similarly converted registration HFECG. Find the similarity with.

  More specifically, the personal identification unit 26 calculates the absolute value of the difference in amplitude between the identification target person's HFECG and the registered HFECG at every predetermined period (every sampling) on the time axis, and calculates the absolute value of the difference. Based on the sum of the two, the similarity between the two is obtained.

  That is, as shown in FIG. 4, the personal identification unit 26 converts the HFECG waveform into a discrete waveform by applying a mesh with a predetermined roughness to the clipped HFECG waveform (resolution conversion) (solid line in FIG. 4). Reference) and the registered HFECG waveform (see the broken line in FIG. 4). Then, the personal identification unit 26 obtains the sum of absolute values of differences in the amplitude direction (error integrated value). If the waveforms are similar, the integrated error value becomes small. Therefore, these values are calculated for the data of all registrants (registered HFECG). In addition to the error integration value described above, the number passing through the same mesh may be counted, and the count integration value may be used as the coincidence number for similarity determination.

  The personal identification unit 26 obtains the similarity between the identification target person HFECG and each of the plurality of registered HFECGs, and the similarity is the highest (the error integrated value is the smallest), and the similarity (the error integrated value) is the same. If the value is equal to or greater than a predetermined threshold value, the registered person of the registered HFECG is determined to be an identification target person. On the other hand, when the similarity is lower than a predetermined threshold value for all registrants, the personal identification unit 26 sets the identification result to “no applicable person” or “non-registrant”. This threshold value is preferably determined in consideration of the balance between the principal rejection rate and the stranger acceptance rate depending on the application. Note that the determination result by the personal identification unit 26 is output and displayed on a display unit (not shown) such as an LCD.

  Next, the operation of the personal identification device 1 will be described with reference to FIG. FIG. 5 is a flowchart showing a processing procedure of personal identification processing by the personal identification device 1.

  First, in step S100, an ECG waveform is acquired. In step S102, a HFECG waveform is acquired. Next, in step S104, the ECG waveform acquired in step S100 is differentiated to generate an ECG differential waveform. Subsequently, in step S106, the zero cross point of the ECG differential waveform acquired in step S104 is extracted, and the R wave peak of the ECG waveform is detected.

  In subsequent step S108, the zero cross point (R wave peak) extracted in step S106 is used as a reference, and a predetermined time zone before and after the zero cross point is set as a cut-out range. In step S110, the HFECG waveform is cut out according to the set cutting range.

  Next, in step S112, normalization and resolution conversion are performed on the extracted HFECG waveform in order to obtain high discrimination performance while suppressing the amount of calculation processing. Subsequently, in step S114, a plurality of registered HFECGs stored in advance (in advance) are read out.

  In step S116, the similarity between the HFECG waveform of the person to be identified and each of the plurality of registered HFECGs is calculated. Since the method of calculating the similarity is as described above, detailed description thereof is omitted here.

  Next, in step S118, the one with the highest similarity is extracted from the similarities obtained in step S116. Then, in step S120, a determination is made as to whether or not the maximum similarity value is greater than a predetermined threshold value. Here, when the maximum value of the similarity is equal to or smaller than the predetermined threshold value, the process proceeds to step S122. On the other hand, when the maximum value of the similarity is larger than the predetermined threshold value, the process proceeds to step S124.

  In step S122, it is determined that there is no identification target person among the registrants, and a determination result (identification result) of “no corresponding person” is output. On the other hand, in step S124, the person to be identified is determined to be a registered person of the registered HFECG having the maximum similarity, and the determination result (identification result) is output.

  Next, another processing procedure (multi-resolution analysis) by the personal identification device 1 will be described with reference to FIG. Here, FIG. 6 is a flowchart showing another processing procedure (multi-resolution analysis) of the personal identification processing by the personal identification device 1. In the flowchart shown in FIG. 6, the same or similar processes as those in FIG.

  In this other processing procedure, after the degree of similarity with the registered HFECG is obtained in step S116 described above, whether or not the degree of similarity is obtained in all of a plurality of resolutions (for example, about 4 patterns) in step S200. Judgment is made. If the similarity is obtained by changing the resolution for all patterns, the process proceeds to step S202. On the other hand, when the resolution is not yet obtained for all the patterns by changing the resolution, the process proceeds to step S112, the HFECG of the identification target person is converted to a different resolution, and the similarity with the registered HFECG is obtained. (Step S116). Thereafter, the process proceeds to step S200 described above.

  In step S202, a comprehensive determination of the similarity calculated by changing the resolution is performed. Here, for example, processing is performed such as obtaining an average value of similarities calculated by changing the resolution or selecting an optimal similarity by removing specific low similarity data. Thereafter, the process proceeds to step S120. In addition, since the process after step S120 is as above-mentioned, detailed description is abbreviate | omitted here.

  As described above, according to the present embodiment, the ECG is differentiated, the zero cross point corresponding to the peak of the R wave is extracted, and the HFECG is cut out for a predetermined range including the zero cross point. Therefore, the peak position of the R wave can be specified more accurately, and the shift on the time axis of the extracted HFECG can be reduced. Therefore, it is possible to accurately match the peaks of the extracted identification target person HFECG and the pre-stored registered HFECG waveforms, and to determine the similarity (matching degree) of both accurately. As a result, personal identification accuracy can be further improved.

  According to the present embodiment, the HFECG of the identification target person is compared with each of the plurality of registered HFECGs, and the registration person of the registered HFECG having the maximum similarity is determined as the identification target person. Therefore, it is possible to identify a relatively most likely registrant as an identification target person from among registered registrants of registered HFECG.

  Further, according to the present embodiment, when the similarity between the identification target person's HFECG and the registered HFECG is greater than or equal to a predetermined threshold value, it is determined that the registered person of the registered HFECG is the identification target person. Therefore, absolute identification accuracy can be improved. Further, it is possible to arbitrarily adjust the identification accuracy by adjusting the threshold value.

  By the way, the amplitude of the ECG may change depending on the measurement conditions. For example, when the area in contact with the electrocardiographic electrode is small or when it is dry in winter, the amplitude of the electrocardiographic signal may be small. However, according to the present embodiment, both the registered HFECG stored in advance and the HFECG of the person to be identified are normalized, and the degree of similarity is obtained in a form in which the amplitude scales are aligned. Therefore, it is possible to determine the degree of similarity between both more accurately.

  According to the present embodiment, the HFECG to be identified whose resolution has been converted is compared with the registered HFECG stored with the resolution converted in advance, and the similarity between the two is obtained. Therefore, by appropriately setting (converting) the resolution, it is possible to remove fluctuation components such as noise while maintaining the characteristic HFECG waveform shape. Therefore, the tolerance to noise can be improved, and the individual identification accuracy can be further increased.

  According to this embodiment, multiresolution analysis is used to set (convert) optimal resolutions for noises having various frequency components, thereby maintaining various shapes of characteristic HFECG waveforms. Noise can be removed. Therefore, it is possible to more effectively prevent the determination accuracy of the similarity between the identification target person's HFECG and the registered HFECG from being reduced by noise.

  According to the present embodiment, the absolute value of the difference in amplitude between the identification target person's HFECG and the registered HFECG is calculated for each predetermined period on the time axis, and based on the sum of the absolute values of the differences, both similarities are calculated. A degree is required. Therefore, the degree of similarity between the identification target person's HFECG and the registered HFECG can be quantitatively determined by a relatively simple calculation. Therefore, even if the number of registrants (registered HFECG) increases, the amount of calculation does not increase rapidly, and it is possible to prevent a delay in processing due to a sudden increase in calculation load (processing load).

  According to this embodiment, based on the extracted zero cross point, the Q point and the S point of the ECG can be extracted, and the HFECG can be cut out between the Q point and the S point. In this way, the waveform area (cutout range) of HFECG used when obtaining the similarity can be limited to a QRS wave portion having a high signal strength. Further, it is possible to remove a portion outside the QRS wave where noise is likely to travel. Therefore, it is possible to further improve resistance to noise.

  Next, a specific embodiment of the electrocardiogram / high-frequency electrocardiogram acquisition unit 10 shown in the block diagram of FIG. 1 will be described with reference to FIGS. FIG. 7 shows a neckband type electrocardiogram / high-frequency electrocardiogram acquisition unit 10A. This neckband ECG / high-frequency electrocardiogram acquisition unit 10A is arranged on a substantially U-shaped neckband 31 that is elastically mounted so as to sandwich the neck from behind the neck of the person to be identified, and on both ends of the neckband 31. It is provided with a first electrocardiogram electrode 11A and a second electrocardiogram electrode 12A that are in contact with both sides of the neck of the identification subject.

  This neckband type electrocardiogram / high-frequency electrocardiogram acquisition unit 10A can perform electrocardiogram detection in a hands-free state. Therefore, for example, compared with the case of acquiring ECG / HFECG by holding the device in hand, the force of entering the identification subject's body is less when ECG / HFECG is acquired, so that myoelectric noise can be reduced. .

  FIG. 8 shows a wearable electrocardiogram / high-frequency electrocardiogram acquisition unit 10B. The wearable electrocardiogram / high-frequency electrocardiogram acquisition unit 10 </ b> B includes a holder garment 41 that is worn covering at least both shoulders of the identification target person and covering both upper arms, and is fixed to the holder garment 41 in advance to thereby identify the identification target person. A first electrocardiogram electrode 11B and a second electrocardiogram electrode 12B are in contact with both shoulders or both upper arms.

  This wearable electrocardiogram / high-frequency electrocardiogram acquisition unit 10B can perform electrocardiogram detection in a hands-free state without a sense of incongruity, and reduces the myoelectric noise because less force is applied to the body when acquiring ECG / HFECG. be able to.

  FIG. 9 shows a wristwatch-type electrocardiogram / high-frequency electrocardiogram acquisition unit 10C. The wristwatch-type electrocardiogram / high-frequency electrocardiogram acquisition unit 10C has a first electrocardiogram electrode (illustrated) disposed on the back surface (back surface) side so as to contact the wrist while being worn on the wrist of one hand of the person to be identified. And a second electrocardiographic electrode 12C disposed on the surface side so as to be operated with the finger of the other hand of the person to be identified. The surface-side second electrocardiographic electrode 12C is disposed, for example, on a switch button provided on the surface side.

  In this wristwatch-type electrocardiogram / high-frequency electrocardiogram acquisition unit 10C, an ECG / HFECG can be easily acquired by touching the switch button with the finger of the other hand while the person to be identified is wearing on the wrist of one hand. Can do. The surface-side second electrocardiographic electrode 12C may be, for example, a light transmissive capacitive coupling electrode provided on a touch panel.

  Although the embodiment of the present invention has been described above, the present invention is not limited to the above embodiment, and various modifications can be made. For example, in the above embodiment, ECG and HFECG are divided after the digital signal processing unit 16, but the signal component of HFECG is very small, so that the analog circuit scale becomes large. Or it is good also as a structure isolate | separated into ECG and EFECG in the front | former stage of the signal amplification part 13. FIG.

  Further, the HFECG waveform cutout unit 22 registers again in accordance with a narrower range (time) when the cutout range (time) of the registered HFECG and the HFECG cutout range (time) of the identification target person are different. It is good also as a structure which cuts out a HFECG waveform (or HFECG of an identification subject person).

  Further, the form of the electrocardiogram / high-frequency electrocardiogram acquisition unit is not limited to the above-described embodiment, and may be configured to be incorporated in a mobile terminal such as a smartphone. In this case, the first electrocardiogram electrode can be disposed on the side surface of the mobile terminal held by the left hand, for example, and the second electrocardiogram electrode can be disposed on the switch button of the mobile terminal operated by the right hand. In that case, the second electrocardiographic electrode may be a light transmissive capacitive coupling electrode on the touch panel of the mobile terminal.

  Furthermore, the registered HFECG data may be stored only in the apparatus (HFECG storage unit 25), or may be stored in the server via, for example, wireless communication.

  In the above embodiment, a pair of the first electrocardiogram electrode 11 and the second electrocardiogram electrode 12 is used to detect an electrocardiogram signal. For example, a three-electrode configuration including a reference electrode (the reference electrode is also on a living body). Arrangement) may also be used.

  In the above embodiment, a waveform having one or a plurality of resolutions is created and stored in advance and compared with the high-frequency electrocardiogram of the person to be identified. For example, when the electrocardiogram waveform is registered at the highest resolution and identification is performed. Alternatively, the resolution conversion unit 24 may select and convert an appropriate resolution to perform comparison (identification).

  In the above embodiment, the HFECG is cut out using the zero cross point (R wave peak) of the ECG differential waveform as a reference point. Instead of this method, for example, the R wave peak centroid is calculated and the centroid is calculated. May be used as a reference point for cutout (reference point on the R wave). Similarly, the midpoint at the half value of the amplitude of the peak of the R wave may be cut out and used as a reference point (reference point on the R wave). In these cases, the midpoint of the R wave peak center of gravity or the half value of the R wave peak amplitude is extracted as a reference point on the R wave, and a high frequency electrocardiogram is obtained for a predetermined range including the reference point on the R wave. Cut out. Therefore, the peak position of the R wave can be specified accurately, and the deviation on the time axis of the cut out high frequency electrocardiogram can be reduced. Therefore, it is possible to accurately match the peaks of the extracted identification target person's high-frequency electrocardiogram and the pre-stored registered high-frequency electrocardiogram, and to accurately determine the degree of similarity (matching degree) between the two. . As a result, personal identification accuracy can be further improved.

DESCRIPTION OF SYMBOLS 1 Personal identification apparatus 10 ECG / high-frequency electrocardiogram acquisition part 10A Neckband type electrocardiogram / high-frequency electrocardiogram acquisition part 10B Wearable electrocardiogram / high-frequency electrocardiogram acquisition part 10C Wristwatch type electrocardiogram / high-frequency electrocardiogram acquisition part 11, 11A, 11B , 12A, 12B, 12C Second electrocardiogram electrode 13 Signal amplification unit 14 Analog signal processing unit 15 A / D conversion unit 16 Digital signal processing unit 17 Low-pass filter (LPF)
18 High-pass filter (HPF)
20 Signal processing unit 21 Peak extraction unit 22 HFECG extraction unit 23 Normalization unit 24 Resolution conversion unit 25 HFECG storage unit 26 Personal identification unit

Claims (17)

An electrocardiogram acquisition means having at least a pair of electrocardiogram electrodes for acquiring an electrocardiogram;
High frequency electrocardiogram acquisition means for removing a low frequency component from the electrocardiogram acquired by the electrocardiogram acquisition means and acquiring a high frequency electrocardiogram;
Extraction means for extracting a reference point on the R wave from the electrocardiogram;
Cutting out means for cutting out a high-frequency electrocardiogram for a predetermined range including a reference point on the R wave extracted by the extracting means;
Storage means for storing a plurality of registrant high-frequency electrocardiograms cut out by the cutting-out means in advance as registered high-frequency electrocardiograms;
An identification means for comparing the high-frequency electrocardiogram of the identification target person cut out by the extraction means with a registered high-frequency electrocardiogram stored in advance, and identifying the identification target person based on the similarity between the two,
Resolution conversion means for converting the resolution of the high-frequency electrocardiogram cut out by the cutting means into a plurality of different resolutions,
The storage means stores a high-frequency electrocardiogram of a plurality of registrants whose resolution has been converted by the resolution conversion means in advance as a registered high-frequency electrocardiogram,
The identification means compares, for each of the identification target high-frequency electrocardiograms converted to different resolutions, the resolution-converted high-frequency electrocardiogram and the registered high-frequency electrocardiogram stored in advance with the resolution converted And a personal identification device characterized by obtaining the similarity between the two . An electrocardiogram acquisition means having at least a pair of electrocardiogram electrodes for acquiring an electrocardiogram;
High frequency electrocardiogram acquisition means for removing a low frequency component from the electrocardiogram acquired by the electrocardiogram acquisition means and acquiring a high frequency electrocardiogram;
Extraction means for extracting a reference point on the R wave from the electrocardiogram;
Cutting out means for cutting out a high-frequency electrocardiogram for a predetermined range including a reference point on the R wave extracted by the extracting means;
Storage means for storing a plurality of registrant high-frequency electrocardiograms cut out by the cutting-out means in advance as registered high-frequency electrocardiograms;
An identification means for comparing the high-frequency electrocardiogram of the identification target person cut out by the extraction means with a registered high-frequency electrocardiogram stored in advance, and identifying the identification target person based on the similarity between the two,
A high-frequency electrocardiogram cut out by the cut-out means, and a resolution conversion means for converting the resolution of each of a plurality of registered high-frequency electrocardiograms stored in the storage means into a plurality of different resolutions,
For each of the identification target person's high-frequency electrocardiogram and registered high-frequency electrocardiogram converted to a plurality of different resolutions, the identification means compares the resolution-converted high-frequency electrocardiogram with the resolution-converted registered high-frequency electrocardiogram. A personal identification device characterized by obtaining the similarity between the two. The extraction means differentiates the electrocardiogram to extract a zero cross point corresponding to an R wave peak,
The personal identification device according to claim 1 or 2, wherein the cutout means cuts out a high-frequency electrocardiogram for a predetermined range including a zero cross point extracted by the extraction means . The extraction means extracts a zero-cross point corresponding to each of the peak of the Q wave and the peak of the S wave,
The cutting means extracts a Q point and an S point of an electrocardiogram based on the zero cross point extracted by the extracting means, and cuts out a high-frequency electrocardiogram between the Q point and the S point. The personal identification device according to claim 3 . An electrocardiogram acquisition means having at least a pair of electrocardiogram electrodes for acquiring an electrocardiogram;
High frequency electrocardiogram acquisition means for removing a low frequency component from the electrocardiogram acquired by the electrocardiogram acquisition means and acquiring a high frequency electrocardiogram;
Extraction means for extracting the peak centroid of the R wave as a reference point on the R wave from the electrocardiogram;
Cutting out means for cutting out a high-frequency electrocardiogram for a predetermined range including a reference point on the R wave extracted by the extracting means;
Storage means for storing a plurality of registrant high-frequency electrocardiograms cut out by the cutting-out means in advance as registered high-frequency electrocardiograms;
A high-frequency electrocardiogram of the identification target person cut out by the cutting-out means and a registered high-frequency electrocardiogram stored in advance, and an identification means for identifying the identification target person based on the similarity between the two. A personal identification device characterized by. An electrocardiogram acquisition means having at least a pair of electrocardiogram electrodes for acquiring an electrocardiogram;
High frequency electrocardiogram acquisition means for removing a low frequency component from the electrocardiogram acquired by the electrocardiogram acquisition means and acquiring a high frequency electrocardiogram;
Extraction means for extracting from the electrocardiogram a midpoint at half the peak amplitude of the R wave as a reference point on the R wave;
Cutting out means for cutting out a high-frequency electrocardiogram for a predetermined range including a reference point on the R wave extracted by the extracting means;
Storage means for storing a plurality of registrant high-frequency electrocardiograms cut out by the cutting-out means in advance as registered high-frequency electrocardiograms;
A high-frequency electrocardiogram of the identification target person cut out by the cutting-out means and a registered high-frequency electrocardiogram stored in advance, and an identification means for identifying the identification target person based on the similarity between the two. A personal identification device characterized by. Comprising resolution conversion means for converting the resolution of the high-frequency electrocardiogram cut out by the cutting means;
The storage means stores a high-frequency electrocardiogram of a plurality of registrants whose resolution has been converted by the resolution conversion means in advance as a registered high-frequency electrocardiogram,
It said identification means includes a high frequency electrocardiogram identification object whose resolution has been converted in advance resolution compares the registration frequency electrocardiogram stored is converted, according to claim 5 or and obtains both similarity 6. The personal identification device according to 6 . The resolution converting means converts the resolution of the high-frequency electrocardiogram into a plurality of different resolutions,
The personal identification device according to claim 7 , wherein the identification unit obtains the similarity for each of a high-frequency electrocardiogram of a person to be identified converted into a plurality of different resolutions. A high-frequency electrocardiogram cut out by the cut-out means, and a resolution conversion means for converting the resolution of a plurality of registered high-frequency electrocardiograms stored in the storage means,
Said identification means includes a high frequency electrocardiogram identification object whose resolution has been converted is compared with the registered frequency electrocardiogram whose resolution has been converted, claim 5 or 6, characterized in that for obtaining both the similarity 1 The personal identification device according to item. The resolution conversion means converts the resolution of each of the high-frequency electrocardiogram and the registered high-frequency electrocardiogram into a plurality of different resolutions,
The personal identification device according to claim 9 , wherein the identification unit obtains the similarity for each of a high-frequency electrocardiogram and a registered high-frequency electrocardiogram of a person to be identified converted into a plurality of different resolutions. The identification means obtains the similarity between the high-frequency electrocardiogram of the person to be identified and each of the plurality of registered high-frequency electrocardiograms, and determines that the registrant of the registered high-frequency electrocardiogram having the highest similarity is the person to be identified. The personal identification device according to any one of claims 1 to 10 . The identifying means determines that the registrant of the registered high-frequency electrocardiogram is the identification target person when the similarity between the high-frequency electrocardiogram of the identification target person and the registered high-frequency electrocardiogram is equal to or greater than a predetermined threshold value. The personal identification device according to any one of claims 1 to 11 . A normalizing means for normalizing the amplitude of the high-frequency electrocardiogram cut out by the cutting means;
It said storage means has been normalized by the normalization means, individuals according to the high frequency electrocardiogram of a plurality of registrants, in any one of claims 1 to 12, characterized in that stored as a pre-registered high-frequency electrocardiogram Identification device. The identification means calculates the absolute value of the difference in amplitude between the identification target person's high-frequency electrocardiogram and the registered high-frequency electrocardiogram for each predetermined period on the time axis, and based on the sum of the absolute values of the differences, personal identification device according to any one of claims 1 to 1 3, characterized in that to determine the degree. The pair of electrocardiographic electrodes constituting the electrocardiogram acquisition means, the personal identification device according to any one of claims 1 to 1 4, characterized in that mounted in contact with both sides of the neck of the identification subject . The pair of electrocardiographic electrodes constituting the electrocardiogram acquisition means individuals according to any one of claims 1 to 1 4, characterized in that mounted in contact with both shoulders or both upper arms of the identification subject Identification device. The electrocardiogram acquisition means is formed in a wristwatch shape, and when attached to the wrist of one hand of the person to be identified, the electrocardiogram electrode provided on the back side that comes into contact with the wrist and the other hand personal identification device according to any one of claims 1 to 1 4, characterized in that it comprises an electrocardiographic electrode fingers are provided capable to surface contact.

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