Biological information detection device

Abstract

The invention provides a biological information detection device which can detect biological information with high precision. This biological information detection device is provided with: a sensor that detects information relating to body movement of a person; a frequency analysis unit that performs frequency analysis on a detection signal based on information relating to the body movement from the sensor; a filter processing unit that generates a filter based on the result of the frequency analysis and applies the generated filter to the detection signal; and a detection unit that detects biological information, which is a heartbeat interval, on the basis of a detection signal before the application of the filter corresponding to a peak value of the detection signal after the application of the filter.

Description

Technical Field

[0001] The present invention relates to a biological information detection device. Background Art

[0002] Conventional technologies are known for detecting biological information by acquiring human body movements. For example, Patent Document 1 discloses a technique that uses a filter with a passband that uses the largest peak in the 0.5-2 Hz range as the fundamental frequency and a harmonic frequency band up to four times the fundamental frequency (i.e., the quadruple frequency) as the passband through frequency conversion. The technique then extracts the heartbeat waveform by inversely converting the heartbeat signal within this passband.

[0003] Patent Document 1: Japanese Patent Application Laid-Open No. 2009-22638

[0004] However, this prior art degrades the signal-to-noise ratio of the signal waveform after filter application if noise overlaps with the harmonic frequency band, or if the signal strength of a specific harmonic component is insufficient due to physical condition or sensor contact. Furthermore, this prior art cannot accurately infer the fundamental frequency if noise overlaps near it. Consequently, this prior art sometimes makes it difficult to accurately detect biological information such as heartbeats. Summary of the Invention

[0005] The present invention has been made in view of the above, and one object of the present invention is to provide a living body information detection device and a living body information detection method capable of detecting living body information with high accuracy.

[0006] The biological information detection device of the present invention comprises: a sensor for detecting information related to human body movement; a frequency analysis unit for performing frequency analysis on a detection signal of the information related to the body movement based on the above-mentioned sensor; a filtering processing unit for generating a filter based on the result of the frequency analysis and applying the generated filter to the above-mentioned detection signal; and a detection unit for detecting the interval between heartbeats, i.e., biological information, based on the detection signal before application of the above-mentioned filter corresponding to the peak value of the detection signal after application of the above-mentioned filter.

[0007] According to the living body information detection device of the present invention, living body information can be detected with high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 This is a diagram showing an example of the configuration of a vehicle according to the first embodiment.

[0009] Figure 2 It is a diagram showing an example of the configuration of the air pressure sensor according to the first embodiment.

[0010] Figure 3This is a block diagram showing an example of the system configuration and hardware configuration of the living body information detection system according to the first embodiment.

[0011] Figure 4 This is a diagram showing an example of the functional configuration of the living body information detection device according to the first embodiment.

[0012] Figure 5 This is a flowchart showing an example of the procedure of the biological information detection process according to the first embodiment.

[0013] Figure 6 This is a diagram showing an example of a waveform of a frequency analysis result according to the first embodiment.

[0014] Figure 7 This is a flowchart showing an example of the procedure of the fundamental frequency estimation process according to the first embodiment.

[0015] Figure 8 This is a flowchart showing an example of the procedure of the filtering process according to the first embodiment.

[0016] Figure 9 This is a flowchart showing an example of the procedure of the peak detection process according to the first embodiment.

[0017] Figure 10 This is a diagram showing a comparison between the detection signal before application of the filter and the detection signal after application of the filter according to the first embodiment.

[0018] Figure 11 This is a flowchart showing an example of the procedure of the peak correction process according to the first embodiment.

[0019] Figure 12 This is a flowchart showing an example of the procedure of the biological information detection process according to the second embodiment.

[0020] Figure 13 This is a flowchart showing an example of the procedure of the fundamental frequency estimation process according to the second embodiment.

[0021] Description of Reference Signs

[0022] 1…vehicle; 12…air pressure sensor; 100…biological information detection system; 111…biological information detection device; 112…vehicle control system; 201…acquisition unit; 202…frequency analysis unit; 203…noise level inference unit; 204…basic frequency inference unit (inference unit); 205…filter processing unit; 206…peak detection unit (detection unit); 207…peak correction unit (correction unit); 208…output unit. DETAILED DESCRIPTION

[0023] The following discloses exemplary embodiments of the present invention. The structures of the embodiments described below, as well as the functions, results, and effects resulting from these structures, are merely examples. The present invention can also be implemented using structures other than those disclosed in the following embodiments, and can provide at least one of the various effects and derivative effects based on the basic structures.

[0024] (First embodiment)

[0025] Figure 1 1 is a diagram showing an example of the structure of a vehicle 1 according to the first embodiment. The vehicle 1 is an example of a mobile object equipped with a biological information detection device. The biological information detection device of this embodiment estimates the status of a driver 2 driving the vehicle 1 and passengers other than the driver 2. Figure 1 In the example of , an example of detecting the state of the driver 2 is shown.

[0026] The vehicle 1 of this embodiment includes an air pressure sensor 12 and a camera 14. In addition, the vehicle 1 includes a biological information detection system 100 (see Figure 3 ).

[0027] The air pressure sensor 12 is a sensor for detecting body surface movement, i.e., body motion, of a passenger, such as the driver 2. The air pressure sensor 12 outputs a signal indicating the detected body motion. In this embodiment, the air pressure sensor 12 detects a signal related to the passenger's heartbeat (pulsation) as body motion. The signal detected by the air pressure sensor 12 is referred to as a detection signal.

[0028] The air pressure sensor 12 is provided inside the backrest 22. In this embodiment, the air pressure sensor 12 is provided as an example of a sensor for detecting the heartbeat, which is a body movement. However, the sensor for detecting the heartbeat is not limited to this. For example, a Doppler sensor or the like may also be used as a sensor for detecting the heartbeat.

[0029] The camera 14 is a device that captures image data of the driver 2 seated in the seat 21. The camera 14 illustrated here is located near the boundary between the roof 31 and the front windshield 32, capturing image data including the driver 2's face from above and in front of the driver 2. By analyzing this image data, information related to changes in the driver's appearance, such as their gaze movements, eye movements, and body movements, can be obtained.

[0030] Next, the air pressure sensor 12 will be described in detail.

[0031] Figure 2 It is a diagram showing an example of the configuration of the air pressure sensor 12 according to the first embodiment.

[0032] The air pressure sensor 12 includes an air pressure source 1201 such as a pump, a variable airbag 1202 , a pressure introduction portion 1203 , and a pressure sensor 1204 provided at a distal end of the pressure introduction portion 1203 .

[0033] The air pressure source 1201 and the pressure sensor 1204 are connected to the biological information detection device 111 (see Figure 3 ) is connected to the processor 121 of the pressure sensor 1204. The processor 121 detects body motion as biological information based on the detection signal of the pressure sensor 1204, and controls the variable airbag 1202 individually via the air pressure source 1201.

[0034] The variable airbag 1202 is an air bag that can be deformed according to changes in pressure caused by supply pressure and body movements of an occupant such as the driver 2 .

[0035] The pressure introduction section 1203 is connected to one end of the variable airbag 1202, and the other end is sealed with a pressure sensor 1204. The pressure introduction section 1203 is a tubular component capable of transmitting pressure fluctuations caused by the supply pressure and the body movements of passengers such as the driver 2. To accurately and quickly transmit pressure changes, the internal volume of the pressure introduction section 1203 is sufficiently smaller than that of the variable airbag 1202.

[0036] Furthermore, even when the variable airbag 1202 deforms due to changes in the pressure of the air supplied from the air pressure source 1201, the pressure introduction portion 1203 is made of a material that does not absorb the pressure fluctuations, maintains its shape, and is capable of transmitting the pressure to the pressure sensor 1204. Furthermore, the pressure introduction portion 1203 is disposed within a predetermined space within the seat of the vehicle 1, is appropriately supported by a supporting member, and does not hinder deformation due to changes in the supply pressure.

[0037] The pressure sensor 1204 is provided at the other end of the pressure introduction portion 1203 , detects the pressure caused by the supply pressure and the body movement of the occupant, and outputs a pressure detection signal.

[0038] In this embodiment, the air pressure source 1201 , the variable airbag 1202 , the pressure introduction portion 1203 , and the pressure sensor 1204 are housed in a seat of the vehicle 1 as the air pressure sensor 12 .

[0039] In the above structure, in order to prevent the pressure introduction part 1203 from being affected by the pulsation when the supply pressure fluctuates, the air introduction tube 1206 of the air pressure source 1201 is set at a position separated from the position where the variable airbag 1202 is set (ideally at an opposite position).

[0040] Next, the living body information detection system 100 according to this embodiment will be described.

[0041] Figure 3 1 is a diagram showing an example of the system configuration and hardware configuration of the living body information detection system 100 according to the first embodiment. Figure 3 As shown, the living body information detection system 100 includes a living body information detection device 111 and a vehicle control system 112. Here, the living body information detection device 111 and the vehicle control system 112 are connected to each other by wire or wirelessly.

[0042] The biological information detection device 111 is a device that detects biological information of passengers such as the driver 2 of the vehicle 1. Figure 3 As shown, the biological information detection device 111 includes an air pressure sensor 12, a processor 121, and the like.

[0043] Processor 121 is an information processing device that performs various computations based on programs. It is composed of, for example, a CPU (Central Processing Unit), RAM (Random Access Memory), ROM (Read Only Memory), SSD (Solid State Drive), and an interface (Interface). Processor 121 loads programs stored in ROM and SSD into RAM to execute computations and control processes for estimating the state of driver 2. Processor 121 also transmits and receives various information to and from other devices via the interface.

[0044] The processor 121 of this embodiment performs processing for detecting biological information of a passenger, such as the driver 2, based on a detection signal related to body movement, i.e., a detection signal related to heartbeat, acquired by the air pressure sensor 12. At this time, the biological information of the passenger, such as the driver 2, detected by the processor 121 is output to the vehicle control system 112.

[0045] like Figure 3As shown, the vehicle control system 112 includes an ECU (Electronic Control Unit) 131, a drive mechanism 132, a brake mechanism 133, a steering mechanism 134, a user I / F 135, etc. The drive mechanism 132 is a mechanism that includes the drive source of the vehicle 1 (for example, an engine, a motor, etc.). The brake mechanism 133 is a mechanism that slows down and stops the vehicle 1. The steering mechanism 134 is a mechanism that changes the direction of travel of the vehicle 1. The user I / F 135 is a display, speaker, operation unit, etc. equipped in the vehicle. The ECU 131 is an information processing device for controlling the drive mechanism 132, the brake mechanism 133, the steering mechanism 134, the user I / F 135, etc. and performing various processes. The ECU 131 of this embodiment uses the biological information output from the biological information detection device 111, etc. to perform predetermined control. The ECU 131 controls the driving mechanism 132 , braking mechanism 133 , steering mechanism 134 , user I / F 135 , etc. based on biological information, etc., to implement danger avoidance actions. The danger avoidance actions may include warning the driver 2 or slowing down or stopping the vehicle 1 .

[0046] Figure 4 1 is a diagram showing an example of the functional configuration of the living body information detection device 111 according to the first embodiment. Figure 4 As shown, the living body information detection device 111 of this embodiment mainly includes an acquisition unit 201, a frequency analysis unit 202, a noise level estimation unit 203, a fundamental frequency estimation unit 204, a filtering unit 205, a peak detection unit 206, a peak correction unit 207, and an output unit 208. These functional units are implemented through the cooperation of hardware elements and software elements (programs, etc.) of the living body information detection device 111. Alternatively, at least one of these functional units may be implemented as dedicated hardware (circuitry, etc.).

[0047] The acquisition unit 201 acquires a detection signal of body movement output from the air pressure sensor 12 , that is, a detection signal related to the heartbeat.

[0048] The frequency analysis unit 202 performs frequency analysis processing such as fast Fourier transform on the detection signal acquired by the acquisition unit 201 and outputs a frequency domain signal of the detection signal as a result of the frequency analysis.

[0049] The noise level estimation unit 203 estimates the noise level of the detection signal using the result of the frequency analysis.

[0050] The fundamental frequency estimation unit 204 estimates the fundamental frequency of the heartbeat. The fundamental frequency of the heartbeat is the reciprocal of the roughly average heartbeat interval and is a frequency with a peak that appears around 1 Hz.

[0051] The fundamental frequency estimation unit 204 determines whether the signal-to-noise ratio (hereinafter referred to as “SN ratio”) of the detection signal in the assumed heartbeat fundamental frequency band is smaller than a second threshold value.

[0052] Here, the heartbeat basic frequency band is assumed to be a frequency band in which a basic frequency is assumed to exist.

[0053] If the SN ratio of the detection signal in the assumed fundamental frequency band is greater than or equal to the second threshold, the fundamental frequency estimation unit 204 determines that the noise in the assumed fundamental frequency band is low or that the detection signal strength is high. Therefore, the fundamental frequency estimation unit 204 detects the peak value of the detection signal in the assumed fundamental frequency band and estimates the frequency of the peak value detected in the assumed fundamental frequency band as the fundamental frequency.

[0054] If the SN ratio of the detection signal in the assumed heartbeat fundamental frequency band is less than the second threshold, fundamental frequency estimation unit 204 determines that the noise in the assumed fundamental frequency band is high or the detection signal strength is low. Therefore, fundamental frequency estimation unit 204 detects a peak in the frequency region of the detection signal in the assumed heartbeat higher harmonic frequency band and estimates the fundamental frequency based on the frequency of the peak detected in the assumed heartbeat higher harmonic frequency band.

[0055] Here, the assumed heartbeat higher harmonic frequency band refers to a frequency band in which frequencies higher than the fundamental frequency are assumed to exist. In this embodiment, the fundamental frequency estimation unit 204 detects peak values ​​of the frequency region signal of the detection signal in a frequency band that is an integer multiple of the assumed heartbeat fundamental frequency band, which is the assumed heartbeat higher harmonic frequency band. The fundamental frequency of the heartbeat is estimated by performing an inverse calculation based on the difference in frequencies of the peak values ​​detected in the assumed heartbeat higher harmonic frequency band.

[0056] The filter processing unit 205 generates a filter based on the result of the frequency analysis performed by the frequency analysis unit 202 and applies the generated filter to the detection signal. Here, the filter processing unit 205 generates a bandpass filter having a predetermined frequency range as a passband in the fundamental frequency band and the harmonic frequency band.

[0057] Here, the fundamental frequency band refers to a frequency band of a predetermined width based on the fundamental frequency estimated by the fundamental frequency estimation unit 204. The higher harmonic frequency band refers to a frequency band having a higher frequency than the fundamental frequency band.

[0058] Specifically, the filter processing unit 205 obtains the SN ratio of the detection signal for each fundamental frequency band and harmonic frequency band, and generates a bandpass filter that passes only frequency bands where the SN ratio is equal to or greater than a predetermined first threshold value.

[0059] The peak detection unit 206 detects heartbeat intervals, or biometric information, based on the detection signal before the bandpass filter is applied (hereinafter referred to as "before the filter is applied"), corresponding to the peak value of the detection signal after the bandpass filter is applied (hereinafter referred to as "after the filter is applied"). Specifically, for each peak value in the detection signal after the filter is applied, the peak value of the detection signal before the filter is applied is determined. Furthermore, the peak detection unit 206 detects the arrangement of the peak values ​​of the detection signal based on the peak values ​​of the detection signal after the filter is applied and the peak values ​​of the detection signal before the filter is applied.

[0060] Specifically, the peak detection unit 206 detects the arrangement of the peaks of the detection signal as biological information based on the respective positions of the peak (second peak) immediately before the moment of the first peak among the peaks of the detection signal before the application of the filter and the peak (third peak) immediately after the moment of the first peak among the peaks of the detection signal before the application of the filter.

[0061] The peak correction unit 207 corrects the position of the peak of the detection signal when the peak of the detection signal exists within a predetermined outlier range.

[0062] The output unit 208 outputs the heartbeat interval based on the corrected peak value of the detection signal to the vehicle control system 112 as biological information.

[0063] Next, the biological information detection process of the biological information detection device 111 according to this embodiment will be described.

[0064] Figure 5 This is a flowchart showing an example of the procedure of the biological information detection process according to the first embodiment.

[0065] First, the acquisition unit 201 acquires the detection signal from the air pressure sensor 12 (S101). Next, the frequency analysis unit 202 performs frequency analysis on the acquired detection signal (S102). This results in a frequency domain signal of the detection signal. Next, the noise level estimation unit 203 estimates the noise level of the detection signal (S103). Specifically, to calculate the SN ratio, the noise level estimation unit 203 estimates a noise approximation line by curve-fitting the noise to the frequency domain signal of the detection signal.

[0066] Figure 6 : is a diagram showing an example of the waveform of the frequency domain signal which is the result of the frequency analysis of the first embodiment. Figure 6 In the graph, the horizontal axis represents the frequency and the vertical axis represents the strength of the detection signal.

[0067] The waveforms shown by the solid line and the dashed line are the frequency domain signals of the detection signal. Here, the waveform shown by the dashed line is the noise waveform. The waveform shown by the solid line is the waveform of the detection signal. Figure 6 In FIG, the dotted line is a noise approximation line indicating the noise level estimated by the noise level estimation unit 203 .

[0068] return Figure 5 Next, the fundamental frequency estimation unit 204 performs a fundamental frequency estimation process for estimating the fundamental frequency of the heartbeat (S104).

[0069] Figure 7 This is a flowchart showing an example of the procedure of the fundamental frequency estimation process according to the first embodiment.

[0070] First, the fundamental frequency estimation unit 204 obtains the SN ratio of the detection signal in the above-mentioned assumed heartbeat fundamental frequency band and determines whether the SN ratio is greater than or equal to a second threshold value (S201). Figure 6 The portion of the noise approximation line indicated by symbol 702 is used as the noise level, and the SN ratio is calculated based on the signal strength (ie, amplitude) in the assumed heartbeat fundamental frequency band.

[0071] Moreover, when the SN ratio of the detection signal in the assumed heartbeat basic frequency band is greater than the second threshold value (S201: Yes), the signal strength relative to the noise is sufficient, and the basic frequency inference unit 204 determines that the basic frequency can be directly inferred from the assumed heartbeat basic frequency band. Therefore, the basic frequency inference unit 204 detects the peak value of the frequency region signal of the detection signal in the assumed heartbeat basic frequency band (S202). Moreover, the basic frequency inference unit 204 sets the frequency of the largest peak value among the peak values ​​detected in the assumed heartbeat basic frequency band as the basic frequency (S203). Figure 6 In the example of , the fundamental frequency estimation unit 204 sets the peak value indicated by the asterisk mark to the maximum and sets it as the fundamental frequency.

[0072] On the other hand, if the SN ratio of the detection signal in the assumed heartbeat fundamental frequency band is less than the second threshold value in S201 (S201: No), the signal strength relative to noise is insufficient, making it difficult for the fundamental frequency estimation unit 204 to directly estimate the fundamental frequency based on the assumed heartbeat fundamental frequency band. For example, this may be due to a high noise level. Therefore, rather than directly detecting the fundamental frequency from the assumed heartbeat fundamental frequency band, the fundamental frequency estimation unit 204 estimates the fundamental frequency based on the peak value of the frequency region signal of the detection signal in the assumed heartbeat fundamental frequency band.

[0073] In this embodiment, the fundamental frequency estimation unit 204 detects peaks in the frequency region of the detection signal in a frequency band that is an integer multiple of the assumed heartbeat fundamental frequency band, which is the assumed heartbeat higher harmonic frequency band. Specifically, the fundamental frequency estimation unit 204 multiplies the signal strength by a window function that amplifies higher frequencies to calculate the autocorrelation coefficient (S204).

[0074] The fundamental frequency estimation unit 204 then detects peaks in a frequency band outside the assumed fundamental frequency band based on the autocorrelation coefficient (S205). Specifically, the fundamental frequency estimation unit 204 shifts the frequency domain signal of the detection signal toward the higher frequency side along the frequency axis while calculating the autocorrelation coefficient with the signal before the shift. The unit determines that the state where the autocorrelation coefficient reaches its maximum value indicates that the peaks of the signals before and after the shift overlap. The fundamental frequency estimation unit 204 then sets the amount of shift along the frequency axis, determined based on the autocorrelation coefficient, as the fundamental frequency (S206).

[0075] For example, the fundamental frequency inference unit 204 calculates the autocorrelation coefficient for the signal in the assumed heartbeat harmonic frequency band, which is twice the assumed heartbeat fundamental frequency band, while shifting it toward the assumed heartbeat harmonic frequency band, which is three times the assumed heartbeat fundamental frequency band. Furthermore, the fundamental frequency inference unit 204 determines that the location with the largest autocorrelation coefficient is the location that coincides with the peak value in the assumed heartbeat harmonic frequency band, which is three times the assumed heartbeat fundamental frequency band. The sliding width (e.g., a bandwidth of 1.2 Hz) in this case is the width between the peak value of the assumed heartbeat harmonic frequency band, which is twice, and the peak value of the assumed heartbeat harmonic frequency band, which is three times. Therefore, the fundamental frequency inference unit 204 infers the frequency of this width as the fundamental frequency of the heartbeat based on the peak value of the assumed heartbeat harmonic frequency band, which is twice.

[0076] As described above, after estimating the fundamental frequency of the heartbeat, the fundamental frequency estimation unit 204 sets a frequency band of a predetermined width based on the fundamental frequency as the fundamental frequency band, and also sets a frequency band of a predetermined width on the higher harmonic side of an integer multiple of the fundamental frequency band 601 as the higher harmonic frequency band. Figure 6 In the example of FIG. 1 , a fundamental frequency band 601 , a harmonic frequency band 602 twice the fundamental frequency band 601 , and a harmonic frequency band 603 three times the fundamental frequency band 601 are set.

[0077] Furthermore, processing is restored to the callout source.

[0078] return Figure 5 After the fundamental frequency estimation process (S104) is completed, the filter processing unit 205 performs a filtering process (S105) of generating a bandpass filter and applying it to the detection signal.

[0079] Figure 8 This is a flowchart showing an example of the procedure of the filtering process according to the first embodiment.

[0080] First, the filter processing unit 205 extracts a higher harmonic frequency band below the frequency f corresponding to the frequency response characteristics of the air pressure sensor 12 based on the fundamental frequency (S301). The responsivity of higher harmonics varies depending on the frequency response characteristics of the sensor. Therefore, in the case of a highly responsive air pressure sensor 12, the filter processing unit 205 extracts a higher harmonic frequency band below the frequency band of five times the fundamental frequency, for example. In the case of a less responsive air pressure sensor 12, the filter processing unit 205 extracts a higher harmonic frequency band below the frequency band of three times the fundamental frequency, for example.

[0081] Next, the filter processing unit 205 calculates the SN ratio of the detection signal according to the fundamental frequency band and the harmonic frequency band (S302). Figure 6 In the example, the filtering processing unit 205 calculates the SN ratio using the noise level of the noise approximation line symbol 702 in the fundamental frequency band, the noise level of the noise approximation line symbol 703 in the higher harmonic frequency band 602 twice the fundamental frequency band, and the noise level of the noise approximation line symbol 704 in the higher harmonic frequency band 603 three times the fundamental frequency band.

[0082] Next, the filter processing unit 205 generates a bandpass filter that passes only the frequency band with an SN ratio of not less than the first threshold value from among the fundamental frequency band and the higher harmonic frequency band (S303). Figure 6 In the example of , the filter processing unit 205 extracts a frequency band 602 twice and a frequency band 603 three times the fundamental frequency band 601 as harmonic frequency bands, but does not extract a frequency band four times (near 5 Hz).

[0083] Then, the filter processing unit 205 applies the generated bandpass filter to the detection signal, thereby extracting only the passband detection signal. Then, the processing returns to the call source.

[0084] return Figure 5 After the filtering process (S105) is completed, the peak detection unit 206 performs a peak detection process (S106) for detecting the peak value of the detection signal.

[0085] Figure 9 This is a flowchart showing an example of the procedure of the peak detection process according to the first embodiment.

[0086] Figure 10 This is a diagram showing a comparison between the detection signal before and after the filter is applied in the first embodiment. Figure 10 In the example, the horizontal axis is time and the vertical axis is intensity. Figure 10In the graph, the upper solid line shows the detection signal and peak position before the filter is applied. The lower dashed line shows the detection signal and peak position after the filter is applied. In each waveform, the peak position is indicated by an inverted triangle.

[0087] First, the peak detection unit 206 detects the peak moment of the detection signal after the filter is applied (S401). Figure 10 As shown in FIG. 1 , the arrangement of the peak values ​​(first peak values) of the detection signal detected after the filter is applied is referred to as arrangement A.

[0088] Next, the peak detection unit 206 detects the peak moment of the detection signal before the filter is applied (S402). Figure 10 As shown in FIG. 1 , the arrangement of the peak values ​​of the detection signal before the filter is applied is referred to as arrangement B.

[0089] Next, the peak detection unit 206 extracts the peak (second peak) of the element of the array B immediately before the time of each element of the array A of the peak of the detection signal after the filter is applied (S403). Figure 10 As shown, the extracted element of the array B is set to C.

[0090] Next, the peak detection unit 206 extracts the peak value (third peak value) of the element of the array B immediately after the time of each element of the array A of the peak value of the detection signal after the filter is applied (S404). Figure 10 As shown, the extracted element of the array B is set to D.

[0091] Next, the peak detection unit 206 obtains a value X using the following formula (1) for each element of the array A, C, and D, and further calculates an average value d of X calculated for each element ( S405 ).

[0092] X=abs((AC) / (DC)-0.5)···(1)

[0093] Here, X is a value indicating the difference between the peak time after the filter is applied and the center of the peak time immediately before and after the peak time (in the detection signal before the filter is applied).

[0094] That is, at each peak (first peak) in the detection signal after the filter is applied, when the position of the first peak is separated from the center position of the interval between the second peak and the third peak by more than a specified distance, the peak closest to the first peak between the second peak and the third peak is set as the peak of the detection signal, and the arrangement of the peaks of the detection signal is detected as the biological information.

[0095] Furthermore, when the position of the first peak is within a predetermined distance from the center position of the interval between the second peak and the third peak, the peak detection unit 206 determines the second peak as the peak of the detection signal and detects the arrangement of the peaks of the detection signal.

[0096] Specifically, the following processing is performed.

[0097] Peak detection unit 206 determines whether the average value d of X is greater than a first threshold value, which serves as a predetermined distance, that is, whether the second and third peaks are far from the center (S406). If the average value d is greater than the first threshold value (S406: Yes), this means that the second and third peaks are far from the center. Therefore, peak detection unit 206 extracts the closest element of array B (i.e., the peak of the detection signal after filtering) to each element of array A (i.e., the peak time of the detection signal after filtering) and detects the extracted element as the peak array of the detection signal (S407).

[0098] On the other hand, if average value d is less than the first threshold value in S406 (S406: No), this means that the second peak and the third peak are not that far from the center. Therefore, peak detection unit 206 detects array C (i.e., the element of array B immediately preceding the position of the detection signal after filter application corresponding to each element of array A) as the peak array of the detection signal (S408).

[0099] In this way, the peak detection unit 206 detects the peak sequence of the detection signal, and then returns to the call source.

[0100] return Figure 5 After the peak detection process (S106) is completed, the peak correction unit 207 performs a peak correction process (S107) for correcting the peak value of the detection signal detected in S106.

[0101] Figure 11 This is a flowchart showing an example of the procedure of the peak correction process according to the first embodiment.

[0102] First, the peak correction unit 207 calculates the difference (ie, the interval) between each element of the peak array of the detection signal and the immediately preceding element (S501). The interval between each element is called a heartbeat interval array.

[0103] Next, the peak correction unit 207 detects whether the heartbeat interval array obtained in S501 is an outlier, and stores the index of the element determined to be an outlier and whether the element with the index determined to be an outlier deviates to the upper side or the lower side in the array (S502).

[0104] Here, an upper outlier corresponds to, for example, a value exceeding the mean + standard deviation * n (n is an integer). A lower outlier corresponds to, for example, a value falling below the mean - standard deviation * n (n is an integer). However, these are merely examples and are not limiting.

[0105] Next, the peak correction unit 207 initializes the counter i to 1 ( S503 ).

[0106] Next, it is determined whether the value of the counter i is smaller than the number of outliers detected in S502 ( S504 ).

[0107] If the value of counter i is less than the number of outliers (S504: Yes), the peak correction unit 207 determines whether the difference between the i-th and i+1-th indices of the outlier elements is less than a predetermined threshold (S505). If the difference between the i-th and i+1-th indices of the outlier elements is greater than the predetermined threshold (S505: No), the peak correction unit 207 increments the counter i by 1 (S511), and the process returns to S504, where the process is repeated from S504.

[0108] On the other hand, in S505, when the difference between the i-th and i+1-th indexes of the outlier, i.e., the element, is less than the specified threshold value (S505: yes), the peak correction unit 207 determines whether the i-th element of the index is an outlier on the upper side, and determines whether the i+1-th element of the index is an outlier on the lower side (S506).

[0109] If the i-th element of the index is an outlier on the upper side and the i+1-th element of the index is an outlier on the lower side (S506: Yes), this means that the interval between the i-th element of the index and the i+1-th element of the index has narrowed. Therefore, the peak correction unit 207 changes the elements of the peak array of the detection signal from the element with the i-th index to the element with the i+1-th index -1 to the peak value of the previous moment in array B (the peak array before the filter is applied) (S507). Furthermore, the peak correction unit 207 increments the counter i by 1 (S508). Next, the peak correction unit 207 further increments the counter i by 1 (S511), and the process returns to S504, where the process is repeated from S504.

[0110] In S506, when the i-th element of the index is not an outlier on the upper side, or the i+1-th element of the index is not an outlier on the lower side (S506: No), the peak correction unit 207 determines whether the i-th outlier is on the lower side, and determines whether the i+1-th outlier is on the upper side (S509).

[0111] When the i-th outlier is not on the lower side or the i+1-th outlier is not on the upper side ( S509 : No), the peak correction unit 207 increments the counter i by 1 ( S511 ), and the process returns to S504 , and the process from S504 is repeated.

[0112] In S509, if the i-th outlier is on the lower side and the i+1-th outlier is on the upper side (S509: Yes), this means that the gap between the i-th element of the index and the i+1-th element of the index has widened. Therefore, the peak correction unit 207 changes the elements of the peak array of the detection signal from the element with the i-th index to the element with the i+1-th index -1 to the peak value at the next moment in array B (the peak array before the filter is applied) (S510). Furthermore, the peak correction unit 207 increments the counter i by 1 (S508). Next, the peak correction unit 207 further increments the counter i by 1 (S511), and the process returns to S504, where the process is repeated.

[0113] In S504 , when the value of the counter i is equal to or greater than the number of outliers ( S504 : No), the process returns to the call source.

[0114] return Figure 5 After the peak correction process (S107) is completed, the output unit 208 outputs the heartbeat interval based on the peak value of the detection signal as biological information to the vehicle control system 112 (S108).

[0115] Thus, the living body information detection device 111 of this embodiment includes: an air pressure sensor 12, which detects information related to human body movement; a frequency analysis unit 202, which performs frequency analysis on the detection signal of the information related to body movement based on the air pressure sensor 12; a filtering processing unit 205, which generates a filter based on the result of the frequency analysis and applies the generated filter to the detection signal; and a peak detection unit 206, which detects the heartbeat interval, that is, the living body information, based on the detection signal before the application of the filter corresponding to the peak value of the detection signal after the application of the filter.

[0116] Therefore, according to this embodiment, instead of using the filtered detection signal of body motion-related information, the raw data of the pre-filtered detection signal corresponding to the peak of the filtered signal is used to detect heartbeat intervals, i.e., biological information. This allows for highly accurate detection of biological information. Furthermore, according to this embodiment, only the air pressure sensor 12 is used to detect the detection signal, simplifying the device structure and reducing manufacturing costs compared to using multiple sensors.

[0117] In addition, the biological information detection device 111 of this embodiment also has a basic frequency inference unit 204 for inferring the basic frequency of body movement, and a filtering processing unit 205 generates a filter that uses a frequency band based on the inferred basic frequency, i.e., the basic frequency band, and a frequency band with a frequency higher than the basic frequency band, i.e., the higher harmonic frequency band, as a passband, and applies the generated filter to the detection signal.

[0118] Therefore, according to this embodiment, by applying the filter, the frequency related to the detection signal can be easily extracted, and the frequency adjusted by the filter can be extracted, so that the biological information can be detected with higher accuracy.

[0119] In the living body information detection apparatus 111 of this embodiment, the filter processing unit 205 calculates the SN ratio of the detection signal for each fundamental frequency band and harmonic frequency band, and generates a filter that passes only frequency bands where the SN ratio is equal to or greater than a first threshold value.

[0120] Therefore, according to this embodiment, a filter that passes only the frequency band with a high SN ratio in the fundamental frequency band and the higher harmonic frequency band is applied to the detection signal, thereby suppressing waveform degradation of the detection signal and enabling more accurate detection of biological information.

[0121] In the living body information detection apparatus 111 of this embodiment, the filter processing unit 205 generates the filter having a passband corresponding to the frequency response characteristics of the air pressure sensor 12 in the fundamental frequency band and the harmonic frequency band.

[0122] Therefore, according to the present embodiment, the accuracy of the detection signal after the filter is applied is improved, thereby enabling detection of biological information with higher accuracy.

[0123] In addition, the biological information detection device 111 of this embodiment has a fundamental frequency inference unit 204. When the SN ratio of the detection signal in the frequency band in which the fundamental frequency is assumed to exist, that is, the assumed heartbeat fundamental frequency band, is less than the second threshold value, the fundamental frequency inference unit 204 detects the peak value of the frequency region signal of the detection signal in the frequency band in which the fundamental frequency is assumed to exist, that is, the assumed heartbeat higher harmonic frequency band, and infers the fundamental frequency based on the frequency of the peak value detected in the assumed heartbeat higher harmonic frequency band.

[0124] Therefore, according to this embodiment, even when the fundamental frequency is difficult to estimate due to noise in the assumed heartbeat fundamental frequency band, the SN ratio of the detection signal is low and the peak is unclear, the fundamental frequency can be estimated based on the peak detected in the assumed heartbeat higher harmonic frequency band. Therefore, according to this embodiment, even when the SN ratio of the detection signal in the assumed heartbeat fundamental frequency band is low, the fundamental frequency can be accurately estimated, resulting in higher-precision detection of biological information.

[0125] In addition, in the biological information detection device 111 of the present embodiment, the fundamental frequency inference unit 204 detects the peak value of the frequency region signal of the detection signal in a frequency band that is an integer multiple of the assumed heartbeat fundamental frequency band, which is an assumed heartbeat higher harmonic frequency band, and infers the fundamental frequency by performing an inverse operation based on the difference in frequency of the peak value detected in the assumed heartbeat higher harmonic frequency band.

[0126] Therefore, according to this embodiment, even when the fundamental frequency is difficult to estimate due to noise in the assumed heartbeat fundamental frequency band, the detection signal has a low SN ratio and unclear peaks, the fundamental frequency is estimated by performing an inverse calculation based on the difference in the frequencies of peaks detected in assumed heartbeat higher harmonic frequency bands that are integer multiples of the assumed heartbeat fundamental frequency band. This improves robustness and allows accurate and easy estimation of the fundamental frequency. Therefore, according to this embodiment, even when the detection signal has a low SN ratio in the assumed heartbeat fundamental frequency band, the fundamental frequency can be accurately and easily estimated, resulting in higher-precision detection of biological information.

[0127] In addition, in the biological information detection device 111 of the present embodiment, the peak detection unit 206 detects the arrangement of the peaks of the detection signal as biological information based on the respective positions of the second peak, which is the peak immediately before the moment of the first peak in the detection signal before the application of the filter, and the third peak, which is the peak immediately after the moment of the first peak in the detection signal before the application of the filter.

[0128] Therefore, according to this embodiment, for the first peak in the detection signal after the filter is applied, the second peak immediately before the moment of the first peak and the third peak immediately after the moment of the first peak are used to detect the arrangement of the peaks of the detection signal as biological information, thereby enabling the heartbeat interval, i.e., biological information, to be detected with higher accuracy.

[0129] In addition, in the biological information detection device 111 of the present embodiment, the peak detection unit 206 sets the peak closest to the first peak between the second peak and the third peak as the peak of the detection signal at each first peak when the position of the first peak exceeds a prescribed distance relative to the center position of the interval between the second peak and the third peak, and detects the arrangement of the peaks of the detection signal as the above-mentioned biological information.

[0130] Therefore, according to this embodiment, when the position of the first peak is more than a specified distance away from the center position of the interval between the second peak and the third peak, by setting the peak closest to the first peak among the second peak and the third peak as the peak of the detection signal, the heartbeat interval, that is, the biological information, can be detected with higher accuracy.

[0131] Furthermore, in the living body information detection device 111 of this embodiment, when the position of the first peak is within a predetermined distance from the center of the interval between the second and third peaks, the peak detection unit 206 detects the second peak as the peak of the detection signal and detects the arrangement of the peaks of the detection signal as the living body information. Therefore, according to this embodiment, by using the second peak as the peak of the detection signal when the position of the first peak is within a predetermined distance from the center of the interval between the second and third peaks, it is possible to detect heartbeat intervals, i.e., living body information, with higher accuracy.

[0132] Furthermore, the living body information detection device 111 of this embodiment further includes a peak correction unit 207 that corrects the position of the detection signal's peak value when the peak value of the detection signal falls within a predetermined outlier range. Therefore, according to this embodiment, even if the peak value of the detection signal detected by the peak detection unit 206 is erroneous, the correction allows for more accurate detection of heartbeat intervals, i.e., living body information.

[0133] Furthermore, in the living body information detection device 111 of this embodiment, the air pressure sensor 12 detects information related to a person's heartbeat as information related to human body motion. Therefore, according to this embodiment, by detecting a signal related to the heartbeat, which represents body motion, and performing various processing, it is possible to detect heartbeat intervals, i.e., living body information, with higher accuracy.

[0134] Furthermore, in the living body information detection device 111 of this embodiment, the air pressure sensor 12 detects heartbeat-related information based on changes in air pressure within the air bladder that compresses the person while the person is seated. Therefore, according to this embodiment, heartbeat-related information is detected using existing components, simplifying the device structure and reducing manufacturing costs.

[0135] (Variation)

[0136] In the above embodiment, the peak detection unit 206 detects the arrangement of the peaks of the detection signal using all peaks of the detection signal after the filter is applied, but the present invention is not limited to this. For example, the peak detection unit 206 can be configured to detect the arrangement of the peaks of the detection signal while ignoring peaks that deviate from the fundamental frequency among the peaks of the detection signal after the filter is applied.

[0137] In this case, by ignoring peaks that deviate from the fundamental frequency, it is possible to detect heartbeat intervals, that is, biological information, with higher accuracy.

[0138] (Second embodiment)

[0139] In the first embodiment and its variant, human body movement is detected and the heartbeat interval based on the peak value of the detection signal is detected as biological information, without considering the person's respiration. In this second embodiment, the heartbeat interval based on the peak value of the detection signal is detected as biological information after considering the person's respiration.

[0140] The configuration of the vehicle 1 , the configuration of the living body information detection system 100 , and the configuration of the living body information detection device 111 of the second embodiment are the same as those of the first embodiment.

[0141] In addition to having the same functions as the first embodiment, the fundamental frequency inference unit 204 of the biological information detection device 111 of this embodiment detects body movements based on breathing as respiratory body movement information based on the frequency area signal of the detection signal, and infers the fundamental frequency of the heartbeat based on the detected respiratory body movement information and the frequency of the peak detected in the above-mentioned assumed heartbeat fundamental frequency band or the above-mentioned assumed heartbeat higher harmonic frequency band.

[0142] Next, the biological information detection process of this embodiment will be described.

[0143] Figure 12 This is a flowchart showing an example of the steps of the biological information detection process according to the second embodiment. The processes (S101 to S103) from the input of the detection signal from the air pressure sensor 12 to the estimation of the noise level are performed in the same manner as in the first embodiment.

[0144] In this embodiment, the following processing is executed in parallel with or in advance.

[0145] Specifically, when the occupant is in a resting state, the acquisition unit 201 inputs the detection signal from the air pressure sensor 12 ( S601 ). Next, the fundamental frequency estimation unit 204 acquires the fundamental frequency of breathing from the HF band (0.04 to 0.15 Hz) in the frequency domain ( S602 ).

[0146] Next, the fundamental frequency estimation unit 204 performs a fundamental frequency estimation process ( S603 ).

[0147] Figure 13 This is a flowchart showing an example of the procedure of the fundamental frequency estimation process according to the second embodiment.

[0148] As in the first embodiment, the fundamental frequency estimation unit 204 determines whether the SN ratio of the detection signal within the assumed heartbeat fundamental frequency band is greater than or equal to a second threshold (S201). If the SN ratio is less than the second threshold (S201: No), the fundamental frequency estimation unit 204 calculates the autocorrelation coefficient (S204) and detects peaks based on the autocorrelation coefficient outside the assumed heartbeat fundamental frequency band (S205), as in the first embodiment. Furthermore, as in the first embodiment, the fundamental frequency estimation unit 204 sets the shift amount along the frequency axis determined based on the autocorrelation coefficient as a candidate for the heartbeat fundamental frequency (S706). The process then proceeds to S702.

[0149] In S201, if the SN ratio of the detection signal in the assumed heartbeat fundamental frequency band is greater than or equal to the second threshold (S201: No), the fundamental frequency estimation unit 204 detects a peak in the assumed heartbeat fundamental frequency band (S202), similar to the first embodiment. Next, the fundamental frequency estimation unit 204 extracts the frequency with the maximum peak as a candidate for the heartbeat fundamental frequency (S701).

[0150] Next, in S702, the fundamental frequency estimation unit 204 compares the candidate heartbeat fundamental frequency with the fundamental frequency of respiration and the respiratory harmonics relative to the fundamental frequency of respiration set in S205 (S702). Specifically, where the fundamental frequency and the respiratory harmonics relative to the fundamental frequency of respiration are represented by Xn (n is an integer), the fundamental frequency estimation unit 204 determines whether the fundamental frequency of respiration and the respiratory harmonics overlap with the candidate heartbeat fundamental frequency (S703). Specifically, the fundamental frequency estimation unit 204 compares each of the fundamental frequency of respiration and the respiratory harmonics with the candidate heartbeat fundamental frequency while increasing n, to determine whether the two overlap.

[0151] If the fundamental frequency of respiration and its harmonics do not overlap with the candidate fundamental frequency of the heartbeat ( S703 : No), the fundamental frequency estimation unit 204 sets the detected candidate fundamental frequency as the fundamental frequency of the heartbeat ( S704 ).

[0152] On the other hand, if the fundamental frequency of respiration and its harmonics overlap with the candidate fundamental frequency of the heartbeat in S703 (S703: Yes), the fundamental frequency estimation unit 204 estimates the frequency of the next largest peak after the largest peak among the detected fundamental frequency candidates as the fundamental frequency of the heartbeat (S705). The process then returns to S703, and the process from S703 onward is repeated while incrementing n. Thus, the frequency of a peak that does not overlap with the fundamental frequency of respiration and its harmonics is detected within the assumed fundamental frequency band of the heartbeat and estimated as the fundamental frequency of the heartbeat.

[0153] return Figure 12 After the fundamental frequency estimation process (S604) is completed, similarly to the first embodiment, the filtering process to the biological information output process (S105 to S108) are executed.

[0154] Thus, in the living body information detection device 11 of this embodiment, the fundamental frequency estimation unit 204 detects body motion based on respiration as respiratory motion information based on the frequency domain signal of the detection signal, and estimates the fundamental heartbeat frequency based on the detected respiratory motion information and the frequency of the peak detected in the assumed heartbeat fundamental frequency band or the assumed heartbeat higher harmonic frequency band. Therefore, in this embodiment, the fundamental heartbeat frequency is estimated by taking the frequency of respiration into account, making it possible to more accurately estimate the fundamental frequency, thereby enabling more precise detection of heartbeat intervals, i.e., living body information.

[0155] Furthermore, in the living body information detection device 11 of this embodiment, the fundamental frequency estimation unit 204 detects the fundamental frequency of respiration as respiratory body motion information and determines whether the detected fundamental frequency of respiration and respiratory harmonics relative to the fundamental frequency overlap with the frequency of a peak detected in the assumed heartbeat fundamental frequency band. If there is no overlap, the fundamental frequency of the detection signal is estimated from the frequency of the peak detected in the assumed heartbeat fundamental frequency band or the assumed heartbeat harmonic frequency band. If there is overlap, the fundamental frequency of the detected signal is estimated from the peak that does not overlap with the fundamental frequency of respiration and respiratory harmonics in the assumed heartbeat fundamental frequency band and estimated as the fundamental frequency of the body motion. Therefore, according to this embodiment, the fundamental frequency of the heartbeat is estimated after removing the respiratory frequency, making it possible to more accurately estimate the fundamental frequency of the heartbeat, thereby enabling more precise detection of heartbeat intervals, i.e., living body information.

[0156] In the above embodiment, the biological information detection device 111 detects biological information of passengers such as the driver 2 of the vehicle 1 . However, the detection target is not limited to passengers of the vehicle 1 , and any device that detects biological information of a person may be used.

[0157] The program for enabling a computer (processor 121, etc.) to implement the functions of the biological information detection device 111 of the above-mentioned embodiment and modified example can also be configured as a file recorded in an installable or executable form on a computer-readable recording medium such as a CD-ROM, floppy disk (FD), CD-R, DVD (Digital Versatile Disk), etc.

[0158] Alternatively, the program may be stored on a computer connected to a network such as the Internet and provided by downloading the program via the network. Alternatively, the program may be provided or distributed via a network such as the Internet.

[0159] While several embodiments of the present invention have been described, these embodiments are provided as examples and are not intended to limit the scope of the invention. These novel embodiments may be implemented in various other ways, and various omissions, substitutions, and modifications may be made without departing from the spirit of the invention. These embodiments and their variations are included within the scope and spirit of the invention, and are included in the invention recited in the claims and their equivalents.

Claims

1. A biological information detection device, wherein: have: Sensors that detect information related to human body movements; a frequency analysis unit for performing frequency analysis on a detection signal of the sensor based on the information related to the body movement; a filter processing unit that generates a filter based on a result of the frequency analysis and applies the generated filter to the detection signal; as well as The detection unit detects the interval between heartbeats, ie, biological information, based on the detection signal before application of the filter corresponding to the peak of the detection signal after application of the filter.

2. The living body information detection device according to claim 1, wherein further comprising an estimating unit for estimating the fundamental frequency of the body movement, The filter processing unit generates the filter having a passband within a predetermined frequency range of a fundamental frequency band based on the estimated fundamental frequency and a harmonic frequency band having frequencies higher than the fundamental frequency band, and applies the generated filter to the detection signal.

3. The biological information detection device according to claim 2, wherein: The filter processing unit calculates a signal-to-noise ratio of the detection signal for each of the fundamental frequency band and the harmonic frequency band, and generates the filter such that only a frequency band in which the signal-to-noise ratio is equal to or greater than a first threshold value is used as the passband.

4. The living body information detection device according to claim 2, wherein: The filter processing unit generates the filter having a frequency band corresponding to the frequency response characteristics of the sensor, of the fundamental frequency band and the harmonic frequency band, as the passband.

5. The living body information detection device according to claim 2, wherein: The inference unit detects the peak value of the frequency region signal of the detection signal in a frequency band in which a frequency higher than the fundamental frequency is assumed to exist, i.e., an assumed heartbeat higher harmonic frequency band, when the signal-to-noise ratio of the detection signal in the frequency band in which the fundamental frequency is assumed to exist, i.e., an assumed heartbeat fundamental frequency band, is less than a second threshold value, and infers the fundamental frequency based on the frequency of the peak value detected in the assumed heartbeat higher harmonic frequency band.

6. The living body information detection device according to claim 5, wherein: The inference unit detects the peak value of the frequency region signal of the detection signal in a frequency band that is an integer multiple of the assumed heartbeat basic frequency band, which is the assumed heartbeat higher harmonic frequency band, and infers the basic frequency by performing an inverse operation based on the difference in frequency of the peak value detected in the assumed heartbeat higher harmonic frequency band.

7. The living body information detection device according to claim 5, wherein: The inference unit detects body movements based on breathing as respiratory body movement information based on the frequency region signal of the detection signal, and infers the basic frequency of the body movement based on the detected respiratory body movement information and the frequency of the peak detected in the assumed heartbeat basic frequency band or the assumed heartbeat higher harmonic frequency band.

8. The living body information detection device according to claim 7, wherein: As the respiratory body movement information, the inference unit detects the basic frequency of breathing, determines whether the detected basic frequency of breathing and the respiratory higher harmonics relative to the basic frequency of breathing overlap with the frequency of the peak detected in the assumed heartbeat basic frequency band. If there is no overlap, the frequency of the peak detected in the assumed heartbeat basic frequency band is inferred as the basic frequency of the detection signal. If there is overlap, the frequency of the peak that does not overlap with the basic frequency of breathing and the respiratory higher harmonics is detected from the assumed heartbeat basic frequency band and inferred as the basic frequency of the body movement.

9. The living body information detection device according to claim 2, wherein: The detection unit detects the arrangement of the peaks of the detection signal as the biological information based on the respective positions of the second peak, which is the peak immediately before the moment of the first peak in the detection signal before the application of the filter, and the third peak, which is the peak immediately after the moment of the first peak in the detection signal before the application of the filter, for each peak in the detection signal after the application of the filter, i.e., the first peak.

10. The living body information detection device according to claim 9, wherein: At each of the first peaks, when the position of the first peak is separated from the center position of the interval between the second peak and the third peak by more than a specified distance, the detection unit sets the peak closest to the first peak between the second peak and the third peak as the peak of the detection signal, and detects the arrangement of the peaks of the detection signal as the biological information.

11. The living body information detection device according to claim 10, wherein: Furthermore, when the position of the first peak is within the specified distance relative to the center position of the interval between the second peak and the third peak, the detection unit detects the second peak as the peak of the detection signal and detects the arrangement of the peaks of the detection signal as the biological information.

12. The living body information detection device according to claim 9, wherein: The detection unit ignores peaks deviating from the fundamental frequency among peaks in the detection signal after application of the filter.

13. The living body information detection device according to claim 1, wherein The method further includes a correction unit configured to correct a position of the peak of the detection signal when the peak of the detection signal is within a predetermined outlier range.

14. The living body information detection device according to claim 1, wherein The sensor detects information related to the person's heartbeat as information related to the person's body movement.

15. The living body information detection device according to claim 14, wherein: The sensor detects information related to the heartbeat based on changes in air pressure of an air bag that can press the person while the person is seated.

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