DETECTION APPARATUS, DETECTION METHOD, AND DETECTION PROGRAM

Abstract

To provide a detection device, a detection method, and a detection program capable of detecting a peak of a waveform with high accuracy.SOLUTION: A detection device includes: a first calculation part that sets a first time width T1 and a second time width T2 smaller than the first time width T1 for biological signals input along a time series; and a second calculation part that extracts a first maximum value of the biological signals included in the first time width T1; a third calculation part that extracts a second maximum value of the biological signals included in the second time width T2; and a detection unit that sequentially acquires the second maximum value included in each second time width T2 using the second maximum value corresponding to the first maximum value or the latest peak R as a reference value IH, and detects the value as the peak R when the acquired second maximum value falls within a predetermined range including the reference value IH. The first time width T1 is applied with an arbitrary acquisition time of the input biological signal as a starting point, and the second time width T2 is repeatedly applied with an acquisition time of the reference value IH as a starting point.SELECTED DRAWING: Figure 5

Description

[Technical field]

[0001] The present invention relates to a detection device, a detection method, and a detection program. [Background technology]

[0002] For example, a waveform including a peak of a biosignal may be contaminated with noise due to body movement, static electricity, etc. Therefore, a method is used to improve the detection accuracy of the peak by detecting the enhanced peak of the biosignal by reducing the influence of the noise.

[0003] Patent Document 1 discloses a detection device, a detection method, and a program including a first calculation unit that sequentially calculates a first moving average amount for a biosignal input in a time series using a predetermined first time width, a second calculation unit that sequentially calculates a second moving average amount for the biosignal using a predetermined second time width that is larger than the first time width, and a third calculation unit that calculates a peak candidate time period, which is a time period including the time when the biosignal reaches a peak, based on the first moving average amount calculated by the first calculation unit and the second moving average amount calculated by the second calculation unit. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2012-139433 A Summary of the Invention [Problem to be solved by the invention]

[0005] When detecting the peak of a biological signal, it is possible to remove or reduce noise by performing filtering processing in order to improve detection accuracy. However, the technology described in Patent Document 1 has a problem that when noise included in the second time width (second window) has frequency characteristics similar to those of the peak to be detected, the noise cannot be completely removed by filtering processing, and the noise may be erroneously detected.

[0006] The present invention has been made to solve such problems, and aims to provide a detection device, a detection method, and a detection program that are capable of detecting waveform peaks with high accuracy. [Means for solving the problem]

[0007] A detection device according to one embodiment detects peaks in a biosignal, and includes a first calculation unit that sets a first time width and a second time width smaller than the first time width for the biosignal input in a time series, a second calculation unit that extracts a first maximum value of the biosignal included in the first time width, a third calculation unit that extracts a second maximum value of the biosignal included in the second time width, and a detection unit that uses the first maximum value or the second maximum value corresponding to the latest peak as a reference value to sequentially acquire second maximum values ​​included in each second time width, and detects the acquired second maximum value as a peak when it falls within a predetermined range including the reference value, wherein the first time width is applied starting from an arbitrary acquisition time of the input biosignal, and the second time width is repeatedly applied starting from an acquisition time of the reference value.

[0008] Moreover, a detection method according to one embodiment is a detection method for detecting a peak of a biosignal, and includes the steps of: setting a first time width and a second time width smaller than the first time width for a biosignal input in a time series; extracting a first maximum value of the biosignal included in the first time width; extracting a second maximum value of the biosignal included in the second time width; and using the second maximum value corresponding to the first maximum value or the latest peak as a reference value, sequentially acquiring second maximum values ​​included in each second time width, and detecting the acquired second maximum value as a peak when it falls within a predetermined range including the reference value, wherein the first time width is applied starting from an arbitrary acquisition time of the input biosignal, and the second time width is repeatedly applied starting from an acquisition time of the reference value.

[0009] Moreover, a detection program according to one embodiment is a detection program for detecting peaks in a biosignal, and includes the steps of: setting a first time width and a second time width smaller than the first time width for a biosignal input in a time series; extracting a first maximum value of the biosignal included in the first time width; extracting a second maximum value of the biosignal included in the second time width; and using the second maximum value corresponding to the first maximum value or the latest peak as a reference value, sequentially acquiring second maximum values ​​included in each second time width, and detecting the acquired second maximum value as a peak when it falls within a predetermined range including the reference value, and causes a computer to execute a process in which the first time width is applied starting from an arbitrary acquisition time of the input biosignal, and the second time width is repeatedly applied starting from an acquisition time of the reference value. Effect of the Invention

[0010] The present invention provides a detection device, a detection method, and a detection program capable of detecting waveform peaks with high accuracy. [Brief description of the drawings]

[0011] [Figure 1] FIG. 4 is a diagram showing an example of time-series data of a biological signal input to the detection device according to the first embodiment. [Diagram 2] 2 is a diagram showing one period of a waveform included in the time series data shown in FIG. 1. [Diagram 3] 2 is a block diagram showing an example of a functional configuration of the detection device according to the first embodiment. FIG. [Figure 4] 4 is a diagram illustrating the relationship between a first time width and a second time width set by a first calculation unit included in the detection device shown in FIG. 3. FIG. [Diagram 5] 4 is a diagram showing an example of a process flow executed by the detection device shown in FIG. 3. [Figure 6] FIG. 6 is a diagram showing a schematic diagram of a part of the processing flow shown in FIG. 5. [Figure 7] FIG. 4 is a diagram for explaining detection conditions in an embodiment. [Figure 8]FIG. 13 is a diagram for explaining a problem in the comparative example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] First embodiment Hereinafter, an embodiment of the present invention will be described with reference to the drawings. However, the present invention is not limited to the following embodiment. In addition, in order to clarify the description, the following description and drawings are appropriately simplified. Furthermore, in the following description, the same or equivalent elements are given the same reference numerals, and duplicate descriptions are omitted.

[0013] The detection device, the detection method, and the detection program according to the present embodiment are preferably used for biosignals related to biological phenomena such as heartbeat, pulse, respiration, and brain waves that exhibit periodic waveforms. In the present embodiment, a heartbeat signal generated from a living body is described as an example of the biosignal.

[0014] First, the waveform of a biological signal input to the detection device 100 according to the present embodiment will be described with specific data with reference to Fig. 1. Fig. 1 is a diagram showing an example of time-series data of a biological signal input to the detection device according to the first embodiment.

[0015] As shown in Fig. 1, the time series data D is data generated from a biosignal input to the detection device 100 in a time series, and specifically, is electrocardiogram waveform data. For example, the vertical axis of the time series data D indicates the potential [mV] of the input biosignal, and the horizontal axis of the time series data D indicates the time [seconds]. When the biosignal is a heartbeat signal, the time series data D includes multiple cycles of waveforms. In the example of Fig. 1, the time series data D includes four cycles of waveforms.

[0016] Therefore, the configuration of an electrocardiogram waveform will be described with reference to Fig. 2. Fig. 2 is a diagram showing one cycle of a waveform included in the time series data shown in Fig. 1. As shown in Fig. 2, one cycle of the waveform is composed of at least waves called P waves, QRS waves (Q waves, R waves, S waves), T waves, and U waves.

[0017] Among the P wave, QRS wave, T wave, and U wave, the QRS wave appears when the entire ventricle contracts, and indicates the excitation of the ventricular muscle. In this embodiment, the R wave with the largest potential difference in the electrocardiogram is the peak R to be detected. The time width between adjacent R waves on the time axis is the heartbeat interval called the RR interval. The heart rate can be calculated using the RR interval, for example, by the following formula (1). Heart rate [bpm] = 60 / (RR interval [sec]) Equation (1)

[0018] 1, four peaks R (peaks R1 to R4) appear periodically. The time width between adjacent peaks R is the RR interval. Hereinafter, when distinguishing between the four peaks R appearing in the time series data D, they will be referred to as peak R1, peak R2, peak R3, and peak R4 in the order in which they are input to the detection device 100.

[0019] Furthermore, in addition to the P-U waves, noise may be mixed into the time series data D. Factors that cause noise to be mixed into an electrocardiogram include, for example, changes in contact resistance between a living body and an electrode, body movement, biosignals of similar frequencies due to electromyogram contamination, and static electricity. Therefore, in order to improve the detection accuracy of a biosignal, a method is required that can eliminate noise and detect only the peak R to be detected from the waveform.

[0020] Next, a functional configuration of the detection device 100 will be described with reference to Fig. 3. Fig. 3 is a block diagram showing an example of a functional configuration of the detection device according to the first embodiment. The detection device 100 shown in Fig. 3 is, for example, a wearable electrocardiograph, and is a device for measuring a heart rate. As shown in Fig. 3, the detection device 100 has a sensor unit 10 and a processing unit 20.

[0021] The sensor unit 10 has a function of acquiring a biosignal. For example, an electrode capable of directly detecting a biosignal from a living body by contacting the living body can be used as the sensor unit 10. As another method, the sensor unit 10 may acquire a biosignal by receiving the biosignal from an external device connected by a connection means such as a network. The biosignal acquired by the sensor unit 10 is output to the processing unit 20.

[0022] A biosignal is input to the processing unit 20 from the sensor unit 10. The processing unit 20 generates detection information from the input biosignal and outputs the detection information to the outside. The processing unit 20 has an A / D conversion unit 30, a buffer unit 40, a first calculation unit 41, a second calculation unit 42, a third calculation unit 43, a detection unit 50, and an output unit 60. The detection device 100 may also include an input device or the like.

[0023] The A / D conversion unit 30 has a function of converting the biosignal from an analog signal to a digital signal. In this embodiment, the biosignal converted into a digital signal forms electrocardiogram waveform data. After being converted from an analog signal to a digital signal by the A / D conversion unit 30, the biosignal is output to the buffer unit 40.

[0024] The buffer unit 40 is composed of memories such as a ROM (Read Only Memory) and a RAM (Random Access Memory). The ROM stores various programs for causing a computer to function as the detection device 100, and various data for executing the various programs. The programs stored in the ROM include a detection program for causing a CPU (Central Processing Unit) to execute the process shown in FIG. 5. The RAM stores various data generated or acquired by executing the programs. The buffer unit 40 can exchange various data with each of the first calculation unit 41, the second calculation unit 42, the third calculation unit 43, and the detection unit 50.

[0025] The first calculation unit 41 reads out the biological signal and the like from the buffer unit 40 and performs calculations. The first calculation unit 41 has a function of setting a first time duration T1 and a second time duration T2 smaller than the first time duration T1 for the biological signal input in time series.

[0026] The first calculation unit 41 applies the first time interval T1 from an arbitrary time when a biosignal is acquired in the time series data D. In the following description, the arbitrary time to which the first time interval T1 is applied is described as the time when the first biosignal is acquired in the time series data D (acquisition time of the biosignal). The first calculation unit 41 also repeatedly applies the second time interval T2 from the time when the first maximum value is acquired. Here, the first maximum value corresponds to the peak R1, and becomes the first reference value IH in the time series data D.

[0027] The reference value IH is a value that is updated sequentially every time the detection unit 50 detects a peak R. The reference value IH is updated to a second maximum value corresponding to the latest peak R detected by the detection unit 50. Hereinafter, the second maximum value corresponding to the latest peak R may be referred to as the detection value SH.

[0028] When the reference value IH is updated, the first calculation unit 41 repeatedly applies the second time width T2 from the acquisition time of the updated reference value IH. Thus, when detecting a peak R that appears after the reference value IH is updated, the second time width T2 is repeated starting from the updated reference value IH. Setting data regarding the first time width T1 and the second time width T2 set by the first calculation unit 41 is stored in the buffer unit 40.

[0029] Here, the relationship between the first time duration T1 and the second time duration T2 will be described with reference to Fig. 4. Fig. 4 is a diagram for explaining the relationship between the first time duration T1 and the second time duration T2 set by the first calculation unit included in the detection device shown in Fig. 3. As shown in Fig. 4, the first time duration T1 and the second time duration T2 are set based on the RR interval.

[0030] The first time span T1 is a time span larger than the R-R interval. Since the reliability of the data improves as the number of peaks R included in the first time span T1 increases, it is preferable that the first time span T1 is a time span sufficiently larger than the R-R interval. On the other hand, the second time span T2 is a time span equal to or smaller than the R-R interval. From the viewpoint of processing speed, it is preferable that the second time span T2 is the same time span as the R-R interval.

[0031] Returning to FIG. 3, the second calculation unit 42 reads out the biosignal, the setting data, etc. from the buffer unit 40 and performs calculations. The second calculation unit 42 has a function of extracting a first maximum value of the biosignal included in a first time span T1 starting from an arbitrary acquisition time of the biosignal. The first maximum value is the highest potential signal value of all the biosignals included in the first time span T1. In other words, the first maximum value corresponds to the peak R1 that appears first in the time series data D. The data relating to the first maximum value extracted by the second calculation unit 42 is stored in the buffer unit 40.

[0032] The third calculation unit 43 reads out the biosignal and the setting data from the buffer unit 40 and performs calculations. The third calculation unit 43 has a function of extracting a second maximum value of the biosignal contained in each second time span T2 that is repeated starting from the acquisition time of the reference value IH. The second maximum value is the highest potential signal value of all the biosignals contained in the second time span T2. ​​Data related to the second maximum value extracted by the third calculation unit 43 is stored in the buffer unit 40.

[0033] The detection unit 50 has a function of detecting a peak R of the biosignal using the first maximum value or the detection value SH as a reference value IH based on the biosignal and various data read from the buffer unit 40. In detail, the detection unit 50 acquires setting data related to the first time span T1 and the second time span T2 from the first calculation unit 41 via the buffer unit 40 in addition to the biosignal. The detection unit 50 also acquires data related to the first maximum value from the second calculation unit 42 via the buffer unit 40. The detection unit 50 also acquires second maximum values ​​included in each second time span T2 from the third calculation unit 43 via the buffer unit 40 in sequence. Then, when the acquired second maximum value falls within a predetermined range including the reference value IH, the detection unit 50 detects it as a peak R.

[0034] For example, when the reference value IH is the maximum value of peak R1, the detection unit 50 detects peak R2 that appears second in the time series data D. When the reference value IH is the maximum value of peak R2, the detection unit 50 detects peak R3 that appears third in the time series data D. When the reference value IH is the maximum value of peak R3, the detection unit 50 detects peak R4 that appears fourth in the time series data D.

[0035] Furthermore, each time the detection unit 50 detects a peak R, it updates the second maximum value corresponding to the latest peak R as the reference value IH, and then detects the peak R that appears next after the latest peak R using the updated reference value IH.

[0036] In this way, after detecting the first peak R in the time series data D, the detection unit 50 repeatedly updates the reference value IH and detects the peak R until the end of the time series data D. Then, the detection unit 50 outputs the detection information of the peak R to the output unit 60.

[0037] The detection information is, for example, a peak interval calculated using the acquisition time of each detected peak R. When R waves are detected from electrocardiogram waveform data, the peak interval is an R-R interval, so the heart rate can be calculated using the peak interval.

[0038] The output unit 60 has a function of outputting, for example, the detection information to the outside. When the output unit 60 is configured with an output device such as a display or a speaker, the output unit 60 displays the detection information on the screen of the display or notifies the detection information by voice. The output unit 60 may output the detection information to the outside as an electrical signal that can be used by another program.

[0039] The first calculation unit 41, the second calculation unit 42, the third calculation unit 43, and the detection unit 50 are configured, for example, by a CPU such as a microprocessor (Micro Processing Unit), a ROM, a RAM, etc., and the CPU deploys a program stored in the ROM into the RAM and executes it to realize the function of each functional block. However, without being limited to such a configuration, the first calculation unit 41, the second calculation unit 42, the third calculation unit 43, the detection unit 50, etc. may be configured by dedicated hardware.

[0040] Next, a process flow of the detection device 100 having the above configuration will be described with reference to Fig. 5 and Fig. 6. Fig. 5 is a flow chart showing an example of a process executed by the detection device shown in Fig. 3. Fig. 6 is a schematic diagram showing a part of the process flow shown in Fig. 5. Note that Fig. 6 is a schematic diagram corresponding to step S4. As shown in Figs. 5 and 6, the detection method according to this embodiment has steps S1 to S5.

[0041] In step S1, a first time span T1 and a second time span T2 smaller than the first time span T1 are set for the biosignal input in time series via the sensor unit 10. In step S2, a first maximum value of the biosignal included in the first time span T1 is extracted. Here, the first time span T1 is a time span applied starting from an arbitrary acquisition time of the input biosignal in the time series data D. In step S3, a second maximum value of the biosignal included in the second time span T2 is extracted. Here, the second time span T2 is a time span applied repeatedly starting from an acquisition time of the reference value IH.

[0042] In step S4, the first maximum value or the detection value SH is used as the reference value IH to sequentially obtain the second maximum value included in each second time span T2, and if the obtained second maximum value falls within a predetermined range including the reference value IH, it is detected as a peak R. In the example shown in FIG. 5, the predetermined range is the reference value IH±15 percent. The second maximum value falling within the predetermined range corresponds to the detection value SH. The reference value IH immediately after the acquisition of the time series data D starts is the first maximum value, and after the time when the next peak R is detected using the first maximum value as the reference value IH, the reference value IH is updated to the latest detection value SH every time a peak R is detected.

[0043] In step S5, it is determined whether or not it is the end of the time series data D. If it is the end of the time series data D (step S5: YES), the process flow ends. On the other hand, if it is not the end of the time series data D (step S5: NO), the process returns to step S3, and steps S3 to S5 are repeated until the end of the time series data D is reached. For example, the detection unit 50 can determine that it is the end of the time series data D when the number of times the second maximum value has been acquired becomes (first time duration T1 / second time duration T2)+1 or more.

[0044] An embodiment will be described below. Note that the embodiment does not limit the present invention. In this embodiment, a specific example of detecting a human heartbeat using the detection device 100 will be described. In the embodiment, the detection device 100 detects an R wave from an electrocardiogram waveform.

[0045] (Example) First, the range of a person's heart rate defined in this embodiment will be described. First, the maximum heart rate of a person is considered to be given by, for example, the following formula (2). Maximum heart rate [bpm] = 220 – age ··· Equation (2) Note that bpm (beats per minute) is a unit of heart rate that represents the number of beats per minute.

[0046] On the other hand, the heart rate of an athlete or other sports person, whose heart rate is slower than that of an average person, is said to be 40 to 50 bpm.

[0047] Based on these, in this embodiment, the range of a person's heart rate is defined as shown in the following formula (3). 40≦heart rate [bpm]≦220...Equation (3)

[0048] Furthermore, when the unit of heart rate is converted from bpm to bps (beats per second) using formula (3), the range of a person's heart rate is as shown in the following formula (4). Note that bps is a unit that indicates the number of beats per second. 0.667≦Heart rate [bps]≦3.667···Equation (4)

[0049] Next, the detection conditions of the detection device 100 will be described with reference to Fig. 7. Fig. 7 is a diagram for explaining the detection conditions of an embodiment. In this embodiment, the sampling rate in the A / D conversion unit 30 of the detection device 100 is set to, for example, 1 / Δt [ / ms]. In this case, the count number N of the heartbeat signal included in one second (1000 ms) in the time series data D is given by the following formula (5). N=1000 / Δt...Equation (5)

[0050] Here, the upper limit value 3.667 [bps] of formula (4) is rounded to 4 [bps]. From formulas (4) and (5), when the time width corresponding to the count number N is divided into a plurality of sections at arbitrary intervals for evaluation, it can be considered that, physiologically, if the arbitrary interval is smaller than N / 4, the next R wave does not appear in the N / 4 section immediately following the R wave. For this reason, in this embodiment, the lower limit of the RR interval is called the section lower limit, and the section lower limit is set to N / 4. By setting the section lower limit to N / 4, two or more R waves are not included in the N / 4 section. In this embodiment, the arbitrary interval refers to the second time width T2.

[0051] The first time duration T1 was set to 2N (2 seconds) so that the time duration was sufficiently larger than the lower limit of the section, and the second time duration T2 was set to N / 4 (0.25 seconds) so that the time duration was equal to or smaller than the lower limit of the section.

[0052] Furthermore, the predetermined range is set to the reference value IH±15 percent. The predetermined range is an arbitrary range determined by experiments or the like for a human heartbeat signal, and is preferably set to the reference value IH±15 percent when detecting R waves from electrocardiogram waveform data.

[0053] Based on the above detection conditions, R waves were detected according to the following steps 1 to 4. <Step 1> The maximum value of the heart rate signal included in the 2N section starting from the start time of acquiring the heart rate signal was acquired, and the acquired maximum value was set as the reference value IH. <Step 2> Starting from the reference value IH, the maximum value of the heart rate signal was obtained every N / 4 in each section from N / 4 to N. <Step 3> The maximum value within the range of the reference value IH ±15 percent (the maximum value obtained in step 2) was detected as the R wave. <Step 4> After updating the reference value IH to the maximum value of the most recent R wave, the procedure was repeated from step 2 to detect the next R wave.

[0054] Next, referring to FIG. 8, the technology described in Patent Document 1 will be cited as a comparative example and problems thereof will be described. FIG. 8 is a diagram for explaining the problems of the comparative example. Note that FIG. 8 corresponds to FIG. 10 of Patent Document 1. The technology described in Patent Document 1 uses a first moving average amount W N and the second moving average amount W n The peak of the biological signal is detected by using the above method. A band-pass filter is applied to the input biological signal in advance to cut low frequency components.

[0055] First moving average amount W NFor example, the first window width is a time width narrower than the time corresponding to the Q wave to the S wave, and each first window width is calculated sequentially. N is the amount of power calculated using the potential at each time.

[0056] 2nd moving average amount W n For example, the second window width is set to a time width that is 1.2 times or more and 1.5 times or less of the time corresponding to the R wave to R wave (RR interval), and is calculated sequentially for each second window width. n is the amount of power calculated using the potential at each time.

[0057] Figure 8 shows the first moving average amount W N and the second moving average amount W n In the technique described in Patent Document 1, the first moving average amount W N is the second moving average amount W n The time periods exceeding this value are determined as potential peak time periods, and the maximum value of the potential of the biological signal in each of the potential peak time periods is detected as the peak value.

[0058] However, in the technology described in Patent Document 1, when the noise included in the second window width has frequency characteristics similar to those of the peak to be detected, the first moving average amount W indicated by the dashed line in the part corresponding to the noise is f is the second moving average amount W n In particular, there is a problem that the noise may be erroneously detected as a normal peak value when the second moving average amount W n During the period when the first moving average amount W f is the second moving average amount W n Therefore, it is considered that such a technique cannot sufficiently remove noise having a certain magnitude.

[0059] In contrast, the detection device 100 according to the present embodiment includes a first calculation unit 41, a second calculation unit 42, a third calculation unit 43, and a detection unit 50. The first calculation unit 41 sets a first time span T1 and a second time span T2 smaller than the first time span T1 for a biosignal input in a time series. The second calculation unit 42 extracts a first maximum value of the biosignal included in the first time span T1. The third calculation unit 43 extracts a second maximum value of the biosignal included in the second time span T2. ​​The detection unit 50 uses the first maximum value or the second maximum value corresponding to the latest peak R as a reference value IH to sequentially acquire second maximum values ​​included in each second time span T2, and detects the acquired second maximum value as a peak R when it falls within a predetermined range including the reference value IH. Furthermore, the first time span T1 is applied starting from an arbitrary acquisition time of the inputted biological signal, and the second time span T2 is applied repeatedly starting from an acquisition time of the reference value IH.

[0060] With this configuration, it is possible to obtain a typical feature amount of the peak R to be detected. In addition, it is possible to remove frequency components outside a predetermined range that appear between adjacent peaks R on the time axis and detect only the peak R to be detected. Therefore, for example, as described in Patent Document 1, it is possible to omit a process of removing noise by providing a filter function such as a band-pass filter in the detection device.

[0061] By using the detection device 100 according to this embodiment, a template of a biological signal is not required to detect the peak R, and even if the waveform data has individual differences, such as an electrocardiogram, the influence of individual differences can be suppressed. Furthermore, by using the detection device 100 according to this embodiment, the gradual change of the peak R can be followed and the sudden change of the peak R can be removed as noise, so that erroneous detection of the peak R can be prevented. Therefore, the detection device 100 according to this embodiment can detect the peak R of the waveform with high accuracy.

[0062] Moreover, the detection unit 50 updates the reference value IH to the second maximum value corresponding to the latest peak R every time a peak R is detected, and then detects the next peak R, and the second time width T2 is repeatedly applied starting from the acquisition time of the updated reference value IH. The detection device 100 according to this embodiment can detect all peaks R to be detected in the time series data D without omission. Furthermore, since the reference value IH is updated every time a peak R is detected, the influence of individual differences can be reduced.

[0063] Furthermore, when the biological signal is a heartbeat signal, the heart rate of the biological body can be detected. Furthermore, when the first time width T1 is a time width greater than the heartbeat interval and the second time width T2 is a time width equal to or less than the heartbeat interval, the reliability of the data is improved and the peak R can be detected quickly. Furthermore, when the predetermined range is the reference value IH±15 percent, the R wave can be reliably detected from the electrocardiogram waveform data obtained from the person.

[0064] Therefore, the detection device 100 according to the present embodiment can detect the heart rate with high accuracy.

[0065] Furthermore, the detection device 100 according to the present embodiment can provide a detection method and a detection program that achieve the above-mentioned advantageous effects.

[0066] The present invention is not limited to the above embodiment, and can be appropriately modified without departing from the spirit of the present invention. For example, some of the functional blocks of the detection device 100 according to the above embodiment may be realized using an external device. As a specific example of another functional configuration, the first calculation unit 41, the second calculation unit 42, and the third calculation unit 43 may be provided in an external device connected to the detection device 100 by a connection means such as a network. In this case, it is not necessary for the detection device 100 to have the first calculation unit 41, the second calculation unit 42, and the third calculation unit 43.

[0067] In the above example, the program can be stored and provided to the computer using various types of non-transitory computer readable media. The non-transitory computer readable medium includes various types of tangible storage media. Examples of the non-transitory computer readable medium include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROM (Read Only Memory), CD-R, CD-R / W, and semiconductor memory (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (Random Access Memory)). The program may also be provided to the computer by various types of transitory computer readable media. Examples of the transitory computer readable medium include electric signals, optical signals, and electromagnetic waves. The transitory computer readable medium can provide the program to the computer via a wired communication path such as an electric wire and an optical fiber, or a wireless communication path. [Explanation of symbols]

[0068] 10 Sensor section 20 Processing section 30 A / D conversion section 40 Buffer section 41 First calculation section 42 Second Calculation Section 43 Third Calculation Section 50 Detection unit 60 Output section 100 Detection device D. Time series data IH Standard Value N Count number R, R1, R2, R3, R4 peaks SH detection value T1 First time span T2 Second time span W f , W N 1st moving average amount W n Second moving average value

Claims

1. A detection device for detecting a peak of a biological signal, comprising: a first calculation unit that sets a first time width and a second time width that is smaller than the first time width for the biological signal input in a time series; A second calculation unit that extracts a first maximum value of the biological signal included in the first time width; a third calculation unit that extracts a second maximum value of the biological signal included in the second time width; a detection unit that uses the first maximum value or the second maximum value corresponding to the latest peak as a reference value, sequentially acquires the second maximum value included in each of the second time widths, and detects the acquired second maximum value as a peak when it falls within a predetermined range including the reference value; having the biological signal is a heart rate signal, the first time width is a time width greater than a heartbeat interval, and the second time width is a time width equal to or less than the heartbeat interval, A detection device in which the first time width is applied starting from an arbitrary acquisition time of the input biological signal, and the second time width is repeatedly applied starting from an acquisition time of the reference value.

2. the detection unit updates the second maximum value corresponding to the latest peak as the reference value every time the peak is detected, and then detects the next peak; The detection device according to claim 1 , wherein the second time duration is repeatedly applied from a time when the updated reference value was acquired as a starting point.

3. 2. The detection device of claim 1, wherein the predetermined range is the reference value plus or minus 15 percent.

4. A method for detecting a peak of a biological signal, comprising: setting a first time width and a second time width smaller than the first time width for the biological signal input in time series; extracting a first maximum value of the biological signal included in the first time duration; extracting a second maximum value of the biological signal included in the second time duration; a step of sequentially acquiring the second maximum value included in each of the second time widths by using the first maximum value or the second maximum value corresponding to the latest peak as a reference value, and detecting the acquired second maximum value as a peak when it falls within a predetermined range including the reference value; having the biological signal is a heart rate signal, the first time width is a time width greater than a heartbeat interval, and the second time width is a time width equal to or less than the heartbeat interval, A detection method in which the first time width is applied starting from an arbitrary acquisition time of the input biological signal, and the second time width is repeatedly applied starting from an acquisition time of the reference value.

5. A detection program for detecting a peak of a biological signal, setting a first time width and a second time width smaller than the first time width for the biological signal input in time series; extracting a first maximum value of the biological signal included in the first time duration; extracting a second maximum value of the biological signal included in the second time duration; a step of sequentially acquiring the second maximum value included in each of the second time widths by using the first maximum value or the second maximum value corresponding to the latest peak as a reference value, and detecting the acquired second maximum value as a peak when it falls within a predetermined range including the reference value; having the biological signal is a heart rate signal, the first time width is a time width greater than a heartbeat interval, and the second time width is a time width equal to or less than the heartbeat interval, A detection program that causes a computer to execute a process in which the first time width is applied starting from an arbitrary acquisition time of the input biological signal, and the second time width is repeatedly applied starting from an acquisition time of the reference value.

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