JP2023139471A - Detection apparatus, detection method, and detection program - Google Patents

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

The present invention relates to a detection device, a detection method, and a detection program.

For example, noise due to body movement, static electricity, etc. may be mixed into a waveform that includes a peak of a biological signal. Therefore, a method is used to improve the peak detection accuracy by detecting the peak of the biosignal that is emphasized while reducing the influence of noise.

Patent Document 1 discloses a first calculation unit that sequentially calculates a first moving average amount using a predetermined first time width for biosignals input in time series, and a first calculation unit that sequentially calculates a first moving average amount using a predetermined first time width for biosignals input in time series; a second calculation unit that sequentially calculates a second moving average amount using a predetermined second time width that is larger than one hour width; and a second calculation unit that calculates the first moving average amount calculated by the first calculation unit and A detection device, a detection method, and a program are disclosed, comprising: a third calculation unit that calculates a peak candidate time period that is a time period including the time when the biosignal reaches its peak based on the second moving average amount; has been done.

Japanese Patent Application Publication No. 2012-139433

When detecting the peak of a biological signal, it is conceivable to perform filtering processing to remove or reduce noise in order to improve detection accuracy. However, with the technology described in Patent Document 1, if the noise included in the second time width (second window) has similar frequency characteristics to the peak to be detected, it cannot be completely removed by filtering. First, there is a problem that the noise may be erroneously detected.

The present invention was made to solve such problems, and aims to provide a detection device, a detection method, and a detection program that can detect waveform peaks with high accuracy. be.

A detection device according to an embodiment is a detection device that detects a peak of a biological signal, and has a first time width and a first time width smaller than the first time width with respect to the biological signal inputted in time series. a first calculation unit that extracts a first maximum value of a biological signal included in the first time width; and a second calculation unit that extracts a first maximum value of a biological signal included in the second time width; a third calculation unit that extracts a second maximum value of the signal; and a third calculation unit that extracts a second maximum value of the signal, and uses the first maximum value or the second maximum value corresponding to the latest peak as a reference value, and includes the second maximum value included in each second time width. a detection unit that sequentially acquires the second maximum value and detects it as a peak when the acquired second maximum value falls within a predetermined range including the reference value; The second time width is repeatedly applied starting from the acquisition time of the reference value.

Further, a detection method according to an embodiment is a detection method for detecting a peak of a biological signal, and is a detection method that detects a peak of a biological signal by detecting a first time width and a first time width for the biological signal input in time series. a step of setting a small second time width; a step of extracting a first maximum value of the biological signal included in the first time width; and a step of extracting a second maximum value of the biological signal included in the second time width. a step of extracting a value; using the first maximum value or a second maximum value corresponding to the latest peak as a reference value, sequentially obtaining a second maximum value included in each second time width; and detecting as a peak when the acquired second maximum value falls within a predetermined range including the reference value, and the first time width has a starting point at an arbitrary acquisition time of the input biological signal. The second time width is applied repeatedly starting from the reference value acquisition time.

Further, the detection program according to one embodiment is a detection program that detects a peak of a biosignal, and is a detection program that detects a peak of a biosignal from a first time width and a peak of a biosignal input in time series. a step of setting a small second time width; a step of extracting a first maximum value of the biological signal included in the first time width; and a step of extracting a second maximum value of the biological signal included in the second time width. a step of extracting a value; using the first maximum value or a second maximum value corresponding to the latest peak as a reference value, sequentially obtaining a second maximum value included in each second time width; and detecting as a peak when the acquired second maximum value falls within a predetermined range including the reference value, and the first time width has a starting point at an arbitrary acquisition time of the input biological signal. The second time period causes the computer to execute a process that is repeatedly applied starting from the acquisition time of the reference value.

According to the present invention, it is possible to provide a detection device, a detection method, and a detection program that can detect waveform peaks with high accuracy.

FIG. 3 is a diagram showing an example of time-series data of biological signals input to the detection device according to the first embodiment. 2 is a diagram showing one period of a waveform included in the time series data shown in FIG. 1. FIG. 1 is a block diagram showing an example of a functional configuration of a detection device according to a first embodiment; FIG. 4 is a diagram illustrating a 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. 4 is a diagram showing an example of a processing flow executed by the detection device shown in FIG. 3. FIG. 6 is a diagram schematically showing a part of the processing flow shown in FIG. 5. FIG. It is a figure explaining the detection conditions of an Example. It is a figure explaining the problem of a comparative example.

Embodiment 1
Embodiments of the present invention will be described below with reference to the drawings. However, the present invention is not limited to the following embodiments. Further, in order to clarify the explanation, the following description and drawings are simplified as appropriate. Furthermore, in the following description, the same or equivalent elements are given the same reference numerals, and redundant description will be omitted.

The detection device, detection method, and detection program according to the present embodiment are suitably used for biological signals related to biological phenomena such as heartbeat, pulse, respiration, or brain waves that exhibit periodic waveforms. In this embodiment, a heartbeat signal generated from a living body will be exemplified and explained as a biological signal.

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

As shown in FIG. 1, the time series data D is data generated from biological signals input to the detection device 100 in 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 biological signal, and the horizontal axis of the time series data D indicates time [seconds]. When the biological signal is a heartbeat signal, the time series data D includes waveforms of multiple cycles. In the example of FIG. 1, the time series data D includes four periods of waveforms.

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

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

That is, in the time series data D shown in FIG. 1, four peaks R (peaks R1 to R4) appear periodically. The time width between adjacent peaks R is the RR interval. Hereinafter, when distinguishing four peaks R appearing in time series data D, peak R1, peak R2, peak R3, and peak R4 are assumed to be input in the order of input to the detection device 100.

Furthermore, the time series data D may include noise in addition to the P to U waves. Factors that cause noise to be mixed into an electrocardiogram include, for example, changes in contact resistance between the living body and electrodes, body movements, biological signals of similar frequencies due to electromyogram mixing, and static electricity. Therefore, in order to improve the detection accuracy of biological signals, a method is required that can eliminate noise and the like and detect only the peak R of the detection target from the waveform.

Next, the 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 the 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 heartbeat. As shown in FIG. 3, the detection device 100 includes a sensor section 10 and a processing section 20.

The sensor unit 10 has a function of acquiring biological signals. As the sensor unit 10, for example, an electrode or the like that can directly detect biological signals from a living body by contacting the living body can be used. As another method, the sensor unit 10 may acquire the biosignal by, for example, receiving the biosignal from an external device connected via a connection means such as a network. The biological signals acquired by the sensor section 10 are output to the processing section 20.

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

The A/D converter 30 has a function of converting a biological signal from an analog signal to a digital signal. In this embodiment, the biological signal converted into a digital signal forms electrocardiogram waveform data. The biological signal is converted from an analog signal to a digital signal by the A/D conversion section 30 and then output to the buffer section 40 .

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

The first calculation unit 41 reads biological signals and the like from the buffer unit 40 and performs calculations. The first calculation unit 41 has a function of setting a first time width T1 and a second time width T2 smaller than the first time width T1 for biological signals input in time series.

The first calculation unit 41 applies the first time width T1 from an arbitrary time in the time-series data D when the biosignal is acquired. In the following description, an arbitrary time to which the first time width T1 is applied will be described as a time when the first biosignal is acquired in the time series data D (biosignal acquisition time). Further, the first calculation unit 41 repeatedly applies the second time width 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.

The reference value IH is a value that is sequentially updated every time the detection unit 50 detects the peak R. The reference value IH is updated to the 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 detected value SH.

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. Thereby, in detecting the 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.

Here, with reference to FIG. 4, the relationship between the first time width T1 and the second time width T2 will be described. FIG. 4 is a diagram illustrating the relationship between the first time width and the second time width set by the first calculation unit included in the detection device shown in FIG. 3. As shown in FIG. 4, the first time width T1 and the second time width T2 are set based on the RR interval.

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

Returning to FIG. 3, the second calculation unit 42 reads the biological signals, setting data, etc. from the buffer unit 40 and performs calculations. The second calculation unit 42 has a function of extracting the first maximum value of the biosignal included in the first time width T1 starting from an arbitrary acquisition time of the biosignal. The first maximum value is the signal value of the highest potential among all the biological signals included in the first time width T1. That is, the first maximum value corresponds to the peak R1 that appears first in the time series data D. Data related to the first maximum value extracted by the second calculation unit 42 is stored in the buffer unit 40.

The third calculation unit 43 reads the biological signals, setting data, etc. from the buffer unit 40 and performs calculations. The third calculation unit 43 has a function of extracting the second maximum value of the biological signal included in each second time width T2 that is repeated starting from the acquisition time of the reference value IH. The second maximum value is the signal value of the highest potential among all the biological signals included in the second time width T2. Data regarding the second maximum value extracted by the third calculation unit 43 is stored in the buffer unit 40.

The detection unit 50 has a function of detecting the peak R of the biological signal based on the biological signal and various data read from the buffer unit 40, using the first maximum value or the detected value SH as the reference value IH. Specifically, the detection unit 50 acquires setting data regarding the first time width T1 and the second time width T2 from the first calculation unit 41 via the buffer unit 40 in addition to the biological signal. The detection unit 50 also acquires data regarding the first maximum value from the second calculation unit 42 via the buffer unit 40. Further, the detection unit 50 sequentially acquires the second maximum value included in each second time width T2 from the third calculation unit 43 via the buffer unit 40. Then, the detection unit 50 detects this as a peak R when the acquired second maximum value falls within a predetermined range that includes the reference value IH.

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

Further, each time the detection unit 50 detects a peak R, the detection unit 50 updates the second maximum value corresponding to the latest peak R as the reference value IH, and then uses the updated reference value IH to Detect the peak R that appears in .

In this way, after detecting the peak R that first appears 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 is reached. . The detection unit 50 then outputs the peak R detection information to the output unit 60.

The detection information is, for example, the peak interval calculated using the acquisition time of each detected peak R. When detecting R waves from electrocardiogram waveform data, since the peak interval is the RR interval, the heart rate can be calculated using the peak interval.

The output unit 60 has a function of outputting detection information and the like to the outside, for example. For example, 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 audio. The output unit 60 may output the detection information to the outside as an electrical signal that can be used by other programs.

The first calculation unit 41, the second calculation unit 42, the third calculation unit 43, and the detection unit 50 are configured by, for example, a CPU such as a microprocessor (Micro Processing Unit), a ROM, a RAM, etc. The functions of each functional block are realized by loading a program stored in the ROM into the RAM and executing it. However, the configuration is not limited to this, and the first calculation unit 41, second calculation unit 42, third calculation unit 43, detection unit 50, etc. may be configured by dedicated hardware. .

Next, the processing flow of the detection device 100 having the above configuration will be described with reference to FIGS. 5 and 6. FIG. 5 is a flowchart showing an example of a process executed by the detection device shown in FIG. 3. FIG. 6 is a diagram schematically showing a part of the processing 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 includes steps S1 to S5.

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

In step S4, the first maximum value or the detected value SH is used as the reference value IH, and the second maximum values included in each second time width T2 are sequentially obtained, and the obtained second maximum value is the reference value. If the value falls within a predetermined range including the 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%. Note that the second maximum value falling within the predetermined range corresponds to the detected value SH. The reference value IH immediately after the acquisition of time series data D is started 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 peak R is Each time it is detected, the reference value IH is updated to the latest detected value SH.

In step S5, it is determined whether or not the time series data D is the last. If it is the end of the time series data D (step S5: YES), the processing flow is ended. 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 the processes of steps S3 to S5 are repeated until the end of the time series data D is reached. For example, the detection unit 50 determines that the time series data D is at the end when the number of acquisitions of the second maximum value becomes (first time width T1/second time width T2)+1 or more. be able to.

Examples will be described below. Note that the examples do not limit the present invention. In this embodiment, a specific example of detecting a person's heartbeat using the detection device 100 will be described. In the embodiment, the detection device 100 detects an R wave from an electrocardiogram waveform.

(Example)
First, the range of human heart rate defined in this example will be explained. First, it is said that a person's maximum heart rate is given by, for example, the following equation (2).
Maximum heart rate [bpm] = 220 - age...Formula (2)
Note that bpm (beat per minute) is a unit of heart rate representing the number of beats per minute.

On the other hand, for example, the heart rate of a sports heart such as an athlete whose heart rate is lower than that of the average person is said to be 40 to 50 [bpm].

In this embodiment, based on these, the range of a person's heart rate is defined as shown in equation (3) below.
40≦heart rate [bpm]≦220...Formula (3)

Furthermore, from equation (3), when the unit of heart rate is converted from bpm to bps (beat per second), the range of a person's heart rate is as shown in equation (4) below. Note that bps is a unit representing the number of beats per second.
0.667≦heart rate [bps]≦3.667...Formula (4)

Next, the detection conditions of the detection device 100 will be explained with reference to FIG. FIG. 7 is a diagram illustrating the detection conditions of the example. In this embodiment, the sampling rate in the A/D converter 30 of the detection device 100 is, for example, 1/Δt[/ms]. In this case, the count number N of heartbeat signals included in one second (1000 ms) in the time series data D is given by the following equation (5).
N=1000/Δt...Formula (5)

Here, the upper limit value of 3.667 [bps] in equation (4) is rounded to 4 [bps]. From equations (4) and (5), when evaluating the time width corresponding to the count number N by dividing it into multiple intervals at arbitrary intervals, physiologically, if the arbitrary interval is smaller than N/4, the R wave It can be considered that the next R wave does not appear during the N/4 section immediately after. For this reason, in this embodiment, the lower limit of the RR interval is referred to as the section lower limit, and the section lower limit is set to N/4. By setting the interval lower limit to N/4, two or more R waves will not be included in the N/4 interval. Note that in this embodiment, the arbitrary interval refers to the second time width T2.

The first time width T1 was set to 2N (2 seconds) so that the time width was sufficiently larger than the lower limit of the interval. Further, the second time width T2 was set to N/4 (0.25 seconds) so that the time width was equal to or less than the lower limit of the interval.

Further, the predetermined range was set as the reference value IH±15%. The predetermined range is an arbitrary range determined through experiments or the like for a human heartbeat signal, and is preferably set to a reference value IH±15% when detecting R waves from electrocardiogram waveform data.

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 heartbeat signal included in the 2N interval starting from the heartbeat signal acquisition start time was acquired, and the acquired maximum value was set as the reference value IH.
<Step 2>
The maximum value of the heartbeat signal was acquired every N/4 in each section from N/4 to N starting from the reference value IH.
<Step 3>
The maximum value (the maximum value obtained in step 2) falling within the range of reference value IH±15% was detected as an R wave.
<Step 4>
After updating the reference value IH to the latest maximum value of R waves, the next appearing R wave was detected by repeating step 2.

Next, with reference to FIG. 8, the technology described in Patent Document 1 will be cited as a comparative example, and its problems will be explained. FIG. 8 is a diagram illustrating problems in the comparative example. Note that FIG. 8 is a diagram corresponding to FIG. 10 of Patent Document 1. The technique described in Patent Document 1 detects the peak of a biological signal using a first moving average amount W _N and a second moving average amount W _n that are calculated for biological signals input in time series. It is something. A bandpass filter is applied to the input biosignal in advance to cut low frequency components.

The first moving average amount _WN is calculated sequentially for each first window width, for example, using a time width narrower than the time corresponding to the Q wave to the S wave as the first window width. Each first moving average amount _WN is a power amount calculated using the potential at each time.

The second moving average amount W _n is, for example, a second window width that is 1.2 times or more and 1.5 times or less the time corresponding to R waves to R waves (RR interval). , are calculated sequentially for each second window width. Each second moving average amount W _n is a power amount calculated using the potential at each time.

FIG. 8 is a graph showing the first moving average amount W _N and the second moving average amount W _n along the time axis. In the technique described in Patent Document 1, the time period in which the first moving average amount W _N exceeds the second moving average amount W _n is defined as a peak candidate time period, and the maximum potential of the biosignal in each of the peak candidate time periods is Detect the value as the peak value.

However, in the technique described in Patent Document 1, when the noise included in the second window width has frequency characteristics similar to the peak of the detection target, the first moving average amount is When W _f exceeds the second moving average amount W _n , there is a problem that noise may be erroneously detected as a normal peak value. In particular, in a time period when the second moving average amount W _n is decreasing (a portion corresponding to the peak of the detection target), there is a relative possibility that the first moving average amount W _f exceeds the second moving average amount W _n . It becomes expensive. Therefore, it is considered that such a technique cannot sufficiently remove noise having a certain size.

In contrast, the detection device 100 according to the present embodiment includes a first calculation section 41, a second calculation section 42, a third calculation section 43, and a detection section 50. The first calculation unit 41 sets a first time width T1 and a second time width T2 smaller than the first time width T1 for the biological signals inputted in time series. The second calculation unit 42 extracts the first maximum value of the biological signal included in the first time width T1. The third calculation unit 43 extracts the second maximum value of the biological signal included in the second time width T2. The detection unit 50 uses the first maximum value or the second maximum value corresponding to the latest peak R as the reference value IH, and sequentially acquires the second maximum value included in each second time width T2. , if the acquired second maximum value falls within a predetermined range including the reference value IH, it is detected as a peak R. Further, the first time width T1 is applied starting from an arbitrary acquisition time of the input biological signal, and the second time width T2 is applied repeatedly starting from the acquisition time of the reference value IH. .

With such a configuration, a typical feature amount of the peak R to be detected can be acquired. Further, by removing frequency components outside a predetermined range that appear between peaks R adjacent on the time axis, only the peak R to be detected can be detected. Therefore, for example, as described in Patent Document 1, it is possible to omit the step of equipping the detection device with a filter function such as a bandpass filter and thereby removing noise.

If the detection device 100 according to the present embodiment is used, a biological signal template is not required when detecting the peak R. For example, even when waveform data such as an electrocardiogram has individual differences, the influence of individual differences can be ignored. Can be suppressed. If the detection device 100 according to this embodiment is used, gradual changes in the peak R can be followed, and sudden changes in the peak R can be removed as noise, so erroneous detection of the peak R can be prevented. Therefore, according to the detection device 100 according to this embodiment, the peak R of the waveform can be detected with high accuracy.

In addition, each time the detection unit 50 detects a peak R, the detection unit 50 updates the second maximum value corresponding to the latest peak R as the reference value IH, and then detects the next peak R, and the second time width T2 is , is repeatedly applied starting from the acquisition time of the updated reference value IH. According to the detection device 100 according to the present embodiment, all peaks R to be detected in the time series data D can be detected without exception. Furthermore, since the reference value IH is updated every time the peak R is detected, the influence of individual differences can be reduced.

Further, 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 larger than the heartbeat interval and the second time width T2 is a time width less than or equal to the heartbeat interval, data reliability is improved and peak R can be detected quickly. can be done. Furthermore, when the predetermined range is the reference value IH±15%, R waves can be reliably detected from waveform data of an electrocardiogram obtained from a person.

Therefore, according to the detection device 100 according to this embodiment, heart rate can be detected with high accuracy.

Furthermore, according to the detection device 100 according to the present embodiment, it is possible to provide a detection method and a detection program that achieve the above-mentioned effects.

Note that the present invention is not limited to the above embodiments, and can be modified as appropriate without departing from the spirit. For example, some of the functional blocks of the detection device 100 according to the embodiment described above may be implemented using an external device. As a specific example of another functional configuration, an external device connected to the detection device 100 through a connection means such as a network includes a first calculation section 41, a second calculation section 42, and a third calculation section 43. It may be a configuration. In this case, the detection device 100 does not need to include the first calculation section 41, the second calculation section 42, and the third calculation section 43.

In the examples described above, the program may be stored and provided to the computer using various types of non-transitory computer readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic recording media (eg, flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (eg, magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R/W, semiconductor memory (for example, mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (Random Access Memory)). The program may also be provided to the computer on various types of transitory computer readable media. Examples of transitory computer-readable media include electrical signals, optical signals, and electromagnetic waves. The temporary computer-readable medium can provide the program to the computer via wired communication channels, such as electrical wires and fiber optics, or wireless communication channels.

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 section 60 Output section 100 Detection device D Time series data IH Reference value N Count number R, R1, R2, R3, R4 Peak SH Detection value T1 First time width T2 Second time width W _f , W _N first moving average amount W _n second moving average value

Claims (7)

A detection device that detects a peak of a biological signal,
a first calculation unit that sets a first time width and a second time width smaller than the first time width for the biological signals input in 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;
Using the first maximum value or the second maximum value corresponding to the latest peak as a reference value, the second maximum values included in each of the second time widths are sequentially acquired, and the acquired a detection unit that detects the second maximum value as a peak when it falls within a predetermined range including the reference value;
has
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 the acquisition time of the reference value. The detection unit updates a second maximum value corresponding to the latest peak as the reference value each time it detects the peak, and then detects the next peak,
The detection device according to claim 1, wherein the second time width is repeatedly applied starting from an acquisition time of the updated reference value. The detection device according to claim 1 or 2, wherein the biological signal is a heartbeat signal. 4. The detection device according to claim 3, wherein the first time width is a time width greater than a heartbeat interval, and the second time width is a time width less than or equal to a heartbeat interval. 5. The detection device according to claim 3, wherein the predetermined range is ±15% of the reference value. A detection method 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 signals input in time series;
extracting a first maximum value of the biological signal included in the first time width;
extracting a second maximum value of the biological signal included in the second time width;
Using the first maximum value or the second maximum value corresponding to the latest peak as a reference value, sequentially acquire the second maximum value included in each of the second time widths, and Detecting the second maximum value as a peak if it falls within a predetermined range including the reference value;
has
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 the acquisition time of the reference value. A detection program that detects 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 signals input in time series;
extracting a first maximum value of the biological signal included in the first time width;
extracting a second maximum value of the biological signal included in the second time width;
Using the first maximum value or the second maximum value corresponding to the latest peak as a reference value, the second maximum values included in each of the second time widths are sequentially acquired, and the acquired Detecting the second maximum value as a peak if it falls within a predetermined range including the reference value;
has
The first time width is applied starting from an arbitrary acquisition time of the input biosignal, and the second time width is applied to the computer to repeatedly apply processing starting from the acquisition time of the reference value. Detection program to run.

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