Biological information detecting device and program

Abstract

To highly accurately detect biological information on a human riding on a moving body even when the moving body is vibrating.SOLUTION: A biological information detecting device is configured to: transmit a transmission wave inside a moving body where a human is present; receive a reflection wave of the transmission wave; calculate, based on the reflection wave, predefined first measurement data at a first measurement point for measuring the data related to a movement of a human body and a vibration of the moving body and predefined second measurement data that is the same in kind as the first measurement data at a second measurement point for measuring the data related to the vibration of the moving body; obtain a first frequency component by a Fourier transformation of the first measurement data; obtain a second frequency component by a Fourier transformation of the second measurement data; obtain a third frequency component by subtracting the second frequency component from the first frequency component; and detect the predefined biological information on the human based on the third frequency component.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] An embodiment of the present invention relates to a biological information detection device and a program. [Background technology]

[0002] In recent years, in driver monitoring systems and the like, technologies have been researched and developed to detect biometric information (e.g., information related to heart rate, pulse rate, and breathing) of occupants (people) of a vehicle (mobile object) based on information such as TOF (Time of Flight) and Doppler shift obtained by sensors that transmit and receive FMCW (Frequency Modulated Continuous Wave) electromagnetic waves. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-104063 [Patent Document 2] Japanese Patent Publication No. 2023-023756 [Patent Document 3] Japanese Patent Publication No. 2022-189451 Summary of the Invention [Problem to be solved by the invention]

[0004] In the above-mentioned technology, in order to detect biological information with high accuracy, it is necessary to remove components caused by vehicle vibration from the data acquired by the sensor, but the conventional technology does not provide a sufficient means for this.

[0005] Therefore, one of the problems that the present invention aims to solve is to provide a biometric information detection device and program that can detect the biometric information of a person riding on a moving body with high accuracy even when the moving body is vibrating. [Means for solving the problem]

[0006] The biometric information detection device of the present invention comprises a transmitting unit that transmits a transmission wave into a room in a moving body where a person is present; a receiving unit that receives a reflected wave of the transmission wave; a calculating unit that calculates, based on the reflected wave, predetermined first measurement data for a first measurement point for measuring data related to the body movement of the person and the vibration of the moving body, and predetermined second measurement data of the same type as the first measurement data for a second measurement point for measuring data related to the vibration of the moving body; a Fourier transform unit that Fourier transforms the first measurement data to obtain a first frequency component, and Fourier transforms the second measurement data to obtain a second frequency component; an arithmetic unit that obtains a third frequency component by subtracting the second frequency component from the first frequency component; and a detecting unit that detects predetermined biometric information of the person based on the third frequency component.

[0007] According to this configuration, as described above, by detecting predetermined biometric information of a person based on the third frequency component obtained by subtracting the second frequency component from the first frequency component, it is possible to detect biometric information of a person riding on a moving object with high accuracy even if the moving object vibrates.

[0008] The program of the present invention is a program for causing a mobile body to function as a transmitting unit that transmits a transmission wave into a room where a person is present, a receiving unit that receives a reflected wave of the transmission wave, and a connected computer, based on the reflected wave, a calculation unit that calculates predetermined first measurement data for a first measurement point for measuring data related to the person's body movement and the vibration of the mobile body, and predetermined second measurement data of the same type as the first measurement data for a second measurement point for measuring data related to the vibration of the mobile body, a Fourier transform unit that Fourier transforms the first measurement data to obtain a first frequency component and Fourier transforms the second measurement data to obtain a second frequency component, an arithmetic unit that subtracts the second frequency component from the first frequency component to obtain a third frequency component, and a detection unit that detects predetermined biometric information of the person based on the third frequency component.

[0009] According to this configuration, as described above, by detecting predetermined biometric information of a person based on the third frequency component obtained by subtracting the second frequency component from the first frequency component, it is possible to detect biometric information of a person riding on a moving object with high accuracy even if the moving object vibrates. [Effects of the Invention]

[0010] According to the biological information detection device and program of the present invention, it is possible to detect biological information of a person riding on a moving object with high accuracy even when the moving object vibrates. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of a vehicle according to an embodiment. [Figure 2] FIG. 2 is a block diagram illustrating an example of a functional configuration of the sensor and the control device according to the embodiment. [Figure 3] FIG. 3 is a diagram showing an outline of signal processing by the FMCW method according to the embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of a transmitted wave, a reflected wave, and a beat frequency according to the embodiment. [Figure 5] FIG. 5 is a diagram illustrating an example of the interior of the vehicle according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of a subtraction process of frequency components according to the embodiment. [Figure 7] FIG. 7 is a flowchart illustrating an example of processing performed by the biological information detecting device according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] The following describes exemplary embodiments of a bioinformation detection device and a program according to the present invention. The configurations of the following embodiments, as well as the actions, results, and advantages achieved by the configurations, are merely examples. The present invention can be realized using configurations other than those disclosed in the following embodiments, and it is possible to obtain at least one of the various advantages and derivative advantages based on the basic configurations.

[0013] FIG. 1 is a diagram showing an example of the configuration of a vehicle C according to an embodiment. A LiDAR (Light Detection and Ranging) sensor 2 and a control device 3 constituting a biological information detection device 1 are arranged inside the vehicle C (an example of a moving body). The LiDAR sensor 2 according to this embodiment is installed on the ceiling of the vehicle. The control device 3 according to this embodiment is installed inside a dashboard provided at the front end of the vehicle. Note that the installation positions and number of the LiDAR sensor 2 and the control device 3 are not limited to these. For example, the LiDAR sensor 2 may be installed (built-in) in an overhead console, a rearview mirror, or the like.

[0014] FIG. 1 illustrates an example of a state in which an occupant M (person) is sitting in a seat S. The following describes how the biometric information detection device 1 detects the presence of the occupant M and detects the biometric information of the occupant M. Note that FIG. 1 illustrates an example of a state in which the occupant M is sitting in the rear seat, but the position of the occupant M to be detected is not limited to this. For example, the occupant sitting in the driver's seat or the passenger seat may be the detection target.

[0015] 2 is a block diagram showing an example of the functional configuration of the LiDAR sensor 2 and the control device 3 according to the embodiment. The LiDAR sensor 2 includes a transmitter 21 and a receiver 22.

[0016] The transmitter 21 transmits, over a wide range within the interior of the vehicle C, laser light (electromagnetic waves) that has been frequency-modulated so as to repeat a gradual increase period in which the frequency gradually increases and a gradual decrease period in which the frequency gradually decreases, as a transmission wave.

[0017] The receiving unit 22 receives a reflected wave generated when the transmitted wave is reflected by an object present in the room.

[0018] The control device 3 is configured by, for example, an MCU (Micro Controller Unit) having an integrated circuit equipped with a hardware processor, a memory, etc. The control device 3 includes an ADC (Analog-to-Digital Converter) 31, a processing unit 32, and a storage unit 33.

[0019] The ADC 31 converts the analog signal acquired by the receiving unit 22 of the LiDAR sensor 2 into a digital signal and outputs the digital signal to the processing unit 32.

[0020] The storage unit 33 is, for example, a storage device such as a RAM (Random Access Memory), a ROM (Read Only Memory), an SSD (Solid State Drive), or an HDD (Hard Disk Drive). The storage unit 33 stores various information such as programs executed by the processing unit 32, data required for executing the programs, and data generated by executing the programs.

[0021] Here, an overview of signal processing using the FMCW method will be described with reference to Fig. 3. Fig. 3 is a diagram showing an overview of signal processing using the FMCW method according to an embodiment. First, as shown in state (A), FMCW-modulated laser light is transmitted from the transmitter 21 of the LiDAR sensor 2 so as to scan the entire interior of the vehicle C. Then, the receiver 22 of the LiDAR sensor 2 receives the reflected wave.

[0022] Next, as shown in state (B), a voxel diagram showing the arrangement (including position, size, shape, etc.) of objects in three-dimensional space (indoor vehicle) is created based on the intensity distribution of the reflected waves in the vehicle. The voxel diagram includes a labeling area D showing the arrangement of objects present in the vehicle (occupant M, seat S, luggage, other vehicle body structures, etc.). The voxel diagram is updated as the reflected wave information acquired by the LiDAR sensor 2 is updated. Information regarding the position and speed of objects can be obtained by analyzing such changes in the voxel diagram. For example, the Doppler shift of the reflected waves can be calculated by performing FFT (Fast Fourier Transform) analysis on the difference between adjacent frames of the voxel diagram.

[0023] Next, as shown in state (C), an occupant M present in the vehicle cabin is detected based on the analysis results of the voxel values of the voxels that make up the labeling area D. For example, among multiple objects present in the vehicle cabin, an object that satisfies predetermined conditions (size, shape, speed, etc.) can be determined to be the occupant M. Furthermore, the biometric information of the occupant M can be detected based on the movement of a part of the object determined to be the occupant M (for example, the face, neck, chest, back, etc.). The biometric information is information about the body of the occupant M present in the vehicle cabin, such as information about at least one of the heart rate, pulse, and breathing of the occupant M.

[0024] Next, the premise of the following description will be described with reference to Fig. 5. Fig. 5 is a diagram showing an example of the interior of a vehicle C according to an embodiment. In the following, a driver DR will be taken as an example of an occupant M.

[0025] Measurement point P1 is an example of a first measurement point for measuring data related to the body movement (here, heartbeat) of the driver DR and vibrations of the vehicle C. Note that the laser light emitted from the transmitter 21 of the LiDAR sensor 2 is not transparent, and if the laser light is irradiated onto clothing, the body movement of the driver DR cannot be detected accurately. Therefore, the position of measurement point P1 is set to the position of the heart of the driver DR and the position of the seat belt 42. At the position of measurement point P1, the body movement caused by the heartbeat of the driver DR is transmitted to the seat belt 42 due to the fastening of the seat belt 42, and therefore, the movement can be detected accurately.

[0026] Measurement points P2 to P5 are examples of second measurement points for measuring data related to vibrations of vehicle C. The position of measurement point P2 is the position of the shoulder of the driver DR. The position of measurement point P3 is the position of the backrest of seat 4. The position of measurement point P4 is the position of the headrest 41 of seat 4. The position of measurement point P5 is the position of the side wall (pillar) of the vehicle body. At these positions of measurement points P2 to P5, it is possible to accurately detect only the vibrations of vehicle C.

[0027] Next, the transmitted wave, the reflected wave, and the beat frequency will be described with reference to Fig. 4. Fig. 4 is a diagram showing an example of the transmitted wave, the reflected wave, and the beat frequency according to an embodiment. In Fig. 4, the upper graph illustrates a line Lt showing the relationship between the elapsed time and the frequency of the transmitted wave transmitted from the transmitter 21 of the LiDAR sensor 2, and a line Lr showing the relationship between the elapsed time and the frequency of the reflected wave received by the receiver 22 of the LiDAR sensor 2. In Fig. 4, the lower graph illustrates a line Lb showing the relationship between the elapsed time and the beat frequency.

[0028] As shown by line Lt, the transmission wave in this embodiment is a chirp signal in which up periods T1 (gradual increase periods), in which the frequency increases over time, and down periods T2 (gradual decrease periods), in which the frequency decreases over time, are repeated alternately. One up period T1 and one down period T2 make up one chirp period T. As shown by line Lr, the frequency of the reflected wave changes with a delay corresponding to the distance from the LiDAR sensor 2 to the object, relative to the change in the frequency of the transmission wave over time. In other words, a difference occurs between the frequency of the transmission wave and the frequency of the reflected wave at the same time.

[0029] The beat frequency is a value determined according to this difference, is proportional to the distance from the LiDAR sensor 2 to the object, and changes according to the movement of the target object. When the object is stationary, the beat frequency in the up period T1 and the beat frequency in the down period T2 will be the same. On the other hand, when the object is moving, the beat frequency in the up period T1 and the beat frequency in the down period T2 will be different, and the speed of the object's movement can be determined from the magnitude of the difference.

[0030] 2, the processing of the processing unit 32 will be described. The processing unit 32 is configured by a hardware processor such as a CPU (Central Processing Unit), for example. The processing unit 32 reads a program stored in the storage unit 33 and executes arithmetic processing. The processing unit 32 includes, as functional units, an acquisition unit 321, a calculation unit 322, a Fourier transform unit 323, an arithmetic unit 324, a detection unit 325, and a control unit 326. Note that some or all of the units 321 to 326 may be configured by hardware such as circuits including an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array).

[0031] The acquisition unit 321 acquires various types of information. The acquisition unit 321 acquires a digital signal from the ADC 31, for example.

[0032] The calculation unit 322 calculates various pieces of information. For example, the calculation unit 322 calculates "predetermined first measurement data for the first measurement point (P1)" and "predetermined second measurement data of the same type as the first measurement data for the second measurement points (P2 to P5)" based on the frequency of the transmitted wave and the frequency of the reflected wave. The first measurement data and the second measurement data are values calculated using one or more of the following (1), (2), and (3):

[0033] (1) Upbeat frequency (beat frequency of up period T1) (2) Downbeat frequency (beat frequency of down period T2) (3) Velocity calculated from upbeat and downbeat frequencies

[0034] Specifically, the combination of the first measurement data and the second measurement data can be, for example, one of the following patterns 1 to 6. However, the combination of the first measurement data and the second measurement data is not limited to patterns 1 to 6.

[0035] [Table 1]

[0036] The Fourier transform unit 323 performs FFT processing (Fourier transform) on the first measurement data to acquire a first frequency component, and performs FFT processing on the second measurement data to acquire a second frequency component. When performing FFT processing on the second measurement data to acquire a second frequency component, the Fourier transform unit 323 acquires the second frequency component by, for example, calculating the average value of the frequency components acquired by FFT processing for each of the multiple second measurement points.

[0037] The calculation unit 324 obtains the third frequency component by subtracting the second frequency component from the first frequency component. These processes will be described with reference to Fig. 6. Fig. 6 is a diagram showing an example of the process of subtracting frequency components in the embodiment.

[0038] In (a), graph G11 is the upbeat frequency (first measurement data) for measurement point P1. By performing FFT processing on this, the first frequency component shown in graph G12 is obtained.

[0039] Next, in (b), graph G21 is the upbeat frequency (second measurement data) for measurement point P2. By performing FFT processing on this, the second frequency component shown in graph G22 is obtained.

[0040] Then, by subtracting the second frequency component (graph G22) from the first frequency component (graph G12), the third frequency component (graph G3) shown in (c) is obtained.

[0041] Returning to FIG. 2, the detection unit 325 detects predetermined biological information of the person (for example, information related to heart rate, pulse rate, and breathing) based on the third frequency component (graph G3 in FIG. 6(c)).

[0042] The control unit 326 executes various controls. For example, the control unit 326 controls the transmitter 21 of the LiDAR sensor 2.

[0043] Next, an example of processing by the biological information detecting device 1 will be described with reference to Fig. 7. Fig. 7 is a flowchart showing an example of processing by the biological information detecting device of the embodiment. For simplicity of explanation, first, a case will be described in which only measurement points P1 and P2 are used out of measurement points P1 to P5 shown in Fig. 5.

[0044] In step S1, the detection unit 325 detects an occupant in the interior of the vehicle C. A specific detection method may be, for example, a detection method using 3D mapping using sensing data from the LiDAR sensor 2, as described above with reference to Fig. 3. However, the detection method is not limited to this, and may also be a detection method using image recognition of an image captured by a camera (not shown), or other detection methods.

[0045] Next, in step S2, the detection unit 325 detects the position of the measurement point P1 (FIG. 5) using data from various sensors (LiDAR sensor 2, camera, etc.).

[0046] In parallel with step S2, in step S3, the detection unit 325 detects the position of the measurement point P2 (FIG. 5) using data from various sensors (LiDAR sensor 2, camera, etc.).

[0047] Next, in step S4, the transmitter 21 of the LiDAR sensor 2 transmits a transmission wave into the interior of the vehicle C.

[0048] Next, in step S5, the receiver 22 of the LiDAR sensor 2 receives the reflected wave of the transmitted wave.

[0049] Next, the processes of steps S6 to S8 and the processes of steps S9 to S11 are performed in parallel.

[0050] In step S6, the acquisition unit 321 acquires data of the measurement point P1 based on the sensing data obtained using the LiDAR sensor 2.

[0051] Next, in step S7, the calculation unit 322 calculates first measurement data (for example, upbeat frequency) for the measurement point P1 based on the data acquired in step S6.

[0052] Next, in step S8, the Fourier transform unit 323 performs FFT processing on the first measurement data (graph G11 in FIG. 6(a)) to acquire a first frequency component (graph G12 in FIG. 6(a)).

[0053] In step S9, the acquisition unit 321 acquires data of the measurement point P2 based on the sensing data obtained using the LiDAR sensor 2.

[0054] Next, in step S10, the calculation unit 322 calculates second measurement data (for example, upbeat frequency) for the measurement point P2 based on the data acquired in step S9.

[0055] Next, in step S11, the Fourier transform unit 323 performs FFT processing on the second measurement data (graph G21 in FIG. 6(b)) to acquire a second frequency component (graph G22 in FIG. 6(b)).

[0056] Next, in step S12, the calculation unit 324 obtains the third frequency component (graph G3 in FIG. 6(c)) by subtracting the second frequency component (graph G22 in FIG. 6(b)) from the first frequency component (graph G12 in FIG. 6(a)).

[0057] Next, in step S13, the detection unit 325 detects information related to the heartbeat of the driver DR based on the third frequency component (graph G3 in FIG. 6(c)).

[0058] Next, in step S14, the calculation unit 324 estimates an RRI (RR Interval) based on the information related to the heart rate detected in step S13.

[0059] Next, in step S15, the calculation unit 324 executes various processes using the RRI estimation result. For example, the calculation unit 324 uses the RRI estimation result to estimate the state of the driver DR, predict state hazards, estimate emotions, etc. Then, the calculation unit 324 notifies the driver DR (by sound or display) as necessary.

[0060] The processes in steps S13 to S15 can be realized by, for example, publicly known techniques.

[0061] As described above, according to the biometric information detection device 1 of this embodiment, by detecting a person's predetermined biometric information based on the third frequency component (graph G3 in Figure 6(c)) obtained by subtracting the second frequency component (graph G22 in Figure 6(b)) from the first frequency component (graph G12 in Figure 6(a)), it is possible to detect the biometric information of a person riding in vehicle C with high accuracy even if vehicle C vibrates.

[0062] In addition, as the first measurement data and the second measurement data, specifically, one of the upbeat frequency, the downbeat frequency, and the velocity calculated therefrom, or values calculated using two or more of them, can be used.

[0063] Furthermore, if a plurality of second measurement points are set, the accuracy of detecting a person's biometric information can be further improved.

[0064] Furthermore, as biometric information, specifically, information relating to at least one of a person's heart rate, pulse rate, and breathing can be detected with high accuracy.

[0065] The effects and advantages will be described in detail below. First, the first frequency component (graph G12) in Fig. 6(a) reflects both the vibration of the vehicle C and the movement due to the heartbeat of the driver DR. Also, the second frequency component (graph G22) in Fig. 6(b) reflects only the vibration of the vehicle C. Therefore, by subtracting the latter from the former, it is possible to obtain the third frequency component (graph G3 in Fig. 6(c)) that reflects only the movement due to the heartbeat of the driver DR.

[0066] Because the vibrations of the vehicle C are highly random in both frequency and intensity, conventional technology has had the problem of making it difficult to detect heartbeats due to noise caused by the vibrations of the vehicle C. Furthermore, as mentioned above, the laser light emitted from the transmitter 21 of the LiDAR sensor 2 is not transparent, and there is also the problem that when the laser light is irradiated onto clothing, the movement of a person's body cannot be detected accurately. Therefore, by positioning the measurement point P1 at the position of the driver DR's heart and the position of the seat belt 42 and performing the above-mentioned processes, both problems can be solved. In other words, as described in FIG. 6 , the influence of noise caused by the vibrations of the vehicle C is eliminated, and the movement caused by the driver DR's heartbeat is transmitted to the seat belt 42 due to the fastening of the seat belt 42, making it possible to accurately detect the heartbeat.

[0067] The program executed by the control device 3 may be provided as a computer program product stored in an installable or executable file format on a computer-readable storage medium such as a CD-ROM, CD-R, memory card, DVD (Digital Versatile Disk), or flexible disk (FD). Alternatively, the program may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Alternatively, the program may be provided or distributed via a network such as the Internet.

[0068] Although the embodiments of the present invention have been described above, the above embodiments are presented as examples and are not intended to limit the scope of the invention. This novel embodiment can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. This embodiment and its modifications are included within the scope and spirit of the invention, and are also included in the inventions and their equivalents as set forth in the claims.

[0069] For example, while Fig. 7 illustrates a case where data from only measurement points P1 and P2 is used, this is not limiting. Alternatively, data from all measurement points P1 to P5 may be used. In this case, the second measurement data for measurement points P2 to P5 may be averaged and used, as in the above-mentioned patterns 5 and 6.

[0070] Moreover, instead of the data at the measurement point P2, data at any one of the measurement points P3 to P5 may be used.

[0071] Furthermore, the position of measurement point P1 (first measurement point for measuring data related to the body movement of the driver DR and the vibration of the vehicle C) is not limited to a position on the seat belt 42. Alternatively, for example, if the biological information to be detected is information related to pulse or breathing, measurement point P1 may be a position on an exposed part of the body of the driver DR where body movement occurs due to pulse or breathing (for example, the neck, face, etc.).

[0072] Furthermore, the positions of measurement points P2 to P5 (second measurement points for measuring data related to vibrations of vehicle C) are not limited to the positions in FIG. 5, and may be any positions as long as only vibrations caused by vehicle C can be detected.

[0073] In the above-described embodiment, FFT is given as a specific example of the Fourier transform performed on the first measurement data and the second measurement data, but this is not limiting and other methods such as STFT (Short-time Fourier transform) may also be used. In other words, the term "Fourier transform" includes various Fourier transforms such as FFT and STFT.

[0074] In the above-described embodiment, the transmitter transmits an FMCW electromagnetic wave, i.e., an electromagnetic wave whose frequency is modulated so as to alternate between a gradual increase period in which the frequency gradually increases and a gradual decrease period in which the frequency gradually decreases. However, the present invention is not limited to this. For example, the transmitter may transmit an electromagnetic wave of a constant frequency. [Explanation of symbols]

[0075] 1... Biological information detection device, 21... Transmitting unit, 22... Receiving unit, 322... Calculating unit, 323... Fourier transform unit, 324... Computing unit, 325... Detecting unit

Claims

1. a transmitting unit in the moving object that transmits a transmission wave into a room where a person is present; a receiving unit that receives a reflected wave of the transmitted wave; Based on the reflected wave, Predetermined first measurement data for a first measurement point for measuring data related to the body movement of the person and the vibration of the moving object; and a calculation unit that calculates predetermined second measurement data of the same type as the first measurement data for a second measurement point for measuring data related to vibration of the moving body; a Fourier transform unit that performs a Fourier transform on the first measurement data to obtain a first frequency component, and that performs a Fourier transform on the second measurement data to obtain a second frequency component; a calculation unit that obtains a third frequency component by subtracting the second frequency component from the first frequency component; a detection unit that detects predetermined biometric information of the person based on the third frequency component; A biological information detection device comprising:

2. the transmitting unit transmits a frequency-modulated transmission wave into a room in which a person is present in the moving body so as to repeat a gradual increase period in which the frequency gradually increases and a gradual decrease period in which the frequency gradually decreases; the calculation unit calculates the first measurement data and the second measurement data based on a frequency of the transmitted wave and a frequency of the reflected wave; 2. The biological information detection device according to claim 1, wherein the first measurement data and the second measurement data are values calculated using one or more of an upbeat frequency corresponding to the gradual increase period, a downbeat frequency corresponding to the gradual decrease period, and a velocity calculated from the upbeat frequency and the downbeat frequency, the beat frequency being a difference between the frequency of the transmitted wave and the frequency of the reflected wave.

3. a plurality of second measurement points are set, 3. The biological information detection device of claim 1, wherein when the Fourier transform unit performs a Fourier transform on the second measurement data to obtain a second frequency component, the Fourier transform unit obtains the second frequency component by calculating an average value of the frequency components obtained by the Fourier transform for each of the plurality of second measurement points.

4. 3. The biological information detection device according to claim 1, wherein the biological information is information relating to at least one of the person's heart rate, pulse rate, and respiration.

5. A transmitting unit that transmits a transmission wave into a room in which a person is present in a moving body, a receiving unit that receives a reflected wave of the transmission wave, and a connected computer Based on the reflected wave, Predetermined first measurement data for a first measurement point for measuring data related to the body movement of the person and the vibration of the moving object; and a calculation unit that calculates predetermined second measurement data of the same type as the first measurement data for a second measurement point for measuring data related to vibration of the moving body; a Fourier transform unit that performs a Fourier transform on the first measurement data to obtain a first frequency component, and that performs a Fourier transform on the second measurement data to obtain a second frequency component; a calculation unit that obtains a third frequency component by subtracting the second frequency component from the first frequency component; a detection unit that detects predetermined biometric information of the person based on the third frequency component; A program to make it function as such.

Images