Biological information detection device and biological information detection method

Abstract

The present invention reduces noise contained in a signal relating to biological information obtained via a radio-wave sensor. This biological information detection device comprises: a reflected signal acquisition unit (110) which acquires reflected signals obtained from a biological body when radio waves are emitted toward the biological body; an image acquisition unit (120) which acquires an image of the biological body; an image processing unit (130) which performs image processing on the acquired image; a signal intensity estimation unit (141) which, on the basis of a result of the image processing, estimates the potential range of signal intensities of the reflected signals; and a noise reduction processing unit (142) which reduces signals having intensities falling outside the estimated range of signal intensities.

Description

[Technical field]

[0001] The present disclosure relates to a biological information detection device and a biological information detection method. [Background technology]

[0002] In order to observe the health condition of a living body, research and development is being conducted on obtaining biological information such as respiration rate or heart rate using a radio wave sensor. For example, Patent Document 1 discloses a method for obtaining the movement of a monitored subject as a movement signal using a radio wave sensor, converting the obtained movement signal into a frequency domain signal by fast Fourier transform, passing the frequency domain signal through a bandpass filter corresponding to the respiration rate or heart rate, and obtaining the peak frequency as the respiration rate or heart rate. Like A technique for obtaining biometric information has been disclosed. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 3057438 Summary of the Invention [Problem to be solved by the invention]

[0004] According to the technology disclosed in Patent Document 1, when noise such as body movement of a living body is input into the passband of a bandpass filter, the respiration rate or heart rate is detected using a signal on which the noise is superimposed, resulting in a problem of erroneous detection.

[0005] The present disclosure has been made to solve the above-mentioned problems, and one aspect of an embodiment aims to provide a biological information detection device that can reduce noise contained in a signal related to biological information. [Means for solving the problem]

[0006] The biometric information detection device of the present disclosure includes a reflected signal acquisition unit that acquires a reflected signal from the living body of radio waves irradiated toward the living body, an image acquisition unit that acquires an image of the living body, an image processing unit that performs image processing on the acquired image, a signal strength estimation unit that estimates a range of signal strengths that the reflected signal can have based on the results of the image processing, and a noise reduction processing unit that reduces signals from the reflected signal that have strengths outside the estimated signal strength range. Effect of the Invention

[0007] According to the present disclosure, it is possible to reduce noise contained in signals related to biological information. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a monitoring system including a biological information detection device. [Diagram 2] FIG. 13 is a schematic diagram showing a noise reduction process. [Figure 3A] FIG. 2 is a diagram illustrating an example of a hardware configuration of a biological information detection device. [Figure 3B] FIG. 2 is a diagram illustrating an example of a hardware configuration of a biological information detection device. [Figure 4] 1 is a flowchart of a biological information detection method. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Embodiment 1 <Configuration> Various embodiments according to the present disclosure will be described in detail below with reference to the drawings. Fig. 1 is a diagram showing a configuration example of a monitoring system 10 including a biological information detection device 100 according to a first embodiment. The monitoring system 10 is a system for monitoring biological information such as respiratory rate and heart rate. As shown in Fig. 1, the monitoring system 10 includes a radio wave sensor 20, a camera 30, a frequency input device 40, the biological information detection device 100, and a control device 50.

[0010] (Radio wave sensor) The radio wave sensor 20 is a sensor for obtaining biometric information from a monitoring target. The radio wave sensor 20 emits radio waves toward the target, receives the reflected waves reflected by the target, amplifies the received reflected signal, and performs A / D conversion on the amplified reflected signal. Examples of the radio wave sensor 20 include a Doppler sensor and a millimeter wave sensor. The radio wave sensor 20 may be positioned anywhere as long as it can emit radio waves to the target and receive a reflected signal from the target. The radio wave sensor 20 outputs the A / D converted reflected signal to the biometric information detection device 100.

[0011] (camera) The camera 30 is a camera for acquiring an image of an object to be monitored. Examples of the camera 30 include a visible light camera and an infrared camera using a near-infrared light source and an infrared transmission filter. The camera 30 may be a monocular camera or a stereo camera. The camera 30 outputs captured image data to the biological information detection device 100.

[0012] (Frequency input device) The frequency input device 40 is an input device for designating a frequency domain for performing frequency analysis. The frequency input device 40 outputs the designated frequency domain to the biological information detection device 100.

[0013] (Biometric information detection device) The biological information detection device 100 is a device that receives signals from the radio wave sensor 20 and the camera 30, performs predetermined signal processing, and outputs a biological information signal. As shown in Fig. 1, the biological information detection device 100 includes a reflected signal acquisition unit 110, an image acquisition unit 120, a frequency acquisition unit 160, an image processing unit 130, a noise processing unit 140, and a biological information calculation unit 150.

[0014] The image processing unit 130 includes a distance estimation unit 131 , a bone structure estimation unit 132 , a material estimation unit 133 , a gender estimation unit 134 , and an age estimation unit 135 .

[0015] The noise processing unit 140 includes a signal intensity estimation unit 141 and a noise reduction processing unit 142 .

[0016] (Reflected signal acquisition section) The reflected signal acquisition unit 110 acquires an A / D converted reflected signal from the radio wave sensor 20. This allows a value for measuring biological information to be detected. Specifically, for example, a value obtained by a Doppler radar is detected. That is, a value corresponding to each frame is detected. Each frame corresponds to a predetermined time period.

[0017] (Image acquisition section) The image acquisition section 120 acquires digital image data captured by the camera 30. The image acquisition section 120 outputs the acquired digital image data to the image processing section .

[0018] (Frequency acquisition section) The frequency acquisition unit 160 acquires the designated frequency range output by the frequency input device 40 , and outputs the acquired designated frequency range to the noise processing unit 140 .

[0019] (Distance estimation section) Distance estimation unit 131 estimates the distance from camera 30 to an object and the position of the object based on the image acquired by image acquisition unit 120. A general algorithm such as trigonometry using parallax due to stereo vision can be used to estimate the distance and position.

[0020] When a monocular camera is used, the size of an object (e.g., the number of pixels) according to the distance from the monocular camera to the object existing in the imaging space is specified in advance as table data. Then, the distance associated with the size of the object in the image capturing the object is acquired by referring to the table. This makes it possible to estimate the distance from the monocular camera to the object. Also, by specifying the pixel position of the object according to the distance from the monocular camera to the object, the position of the object can be estimated from the image capturing the object. An example of an object existing in the imaging space is a seat belt in the vehicle interior space in which the camera 30 is disposed.

[0021] The distance estimation unit 131 estimates the distance from the radio wave sensor 20 to the target based on the estimated target position and the positional relationship between the camera 30 and the radio wave sensor 20 .

[0022] (Bone structure estimation department) The skeleton estimation unit 132 captures the posture or skeleton of the target and acquires the angle and area of ​​the radio wave irradiation surface based on the image acquired by the image acquisition unit 120. A general algorithm such as OpenPose can be used as a method for estimating the posture or skeleton.

[0023] (Material estimation department) The material estimation unit 133 acquires the material of the surface irradiated with radio waves of the wearable object such as clothes or accessories worn by the subject based on the image acquired by the image acquisition unit 120. The material can be estimated by creating a learning model that links the image and the material using a general algorithm such as CNN (Convolutional Neural Network). By estimating the material, it becomes possible to take into account the transmittance of the material that exists before the radio waves reach the subject's body surface.

[0024] (Gender Estimation Department) The gender estimation unit 134 estimates the gender of the subject based on the image acquired by the image acquisition unit 120. Gender estimation can be performed by creating a learning model that links the image and gender using a general algorithm such as CNN (Convolutional Neural Network). By estimating gender, it becomes possible to take into account the reflectivity of radio waves on the subject's body surface due to differences in gender.

[0025] (Age Estimation Department) The age estimation unit 135 estimates the age of the target based on the image acquired by the image acquisition unit 120. The age can be estimated by creating a learning model that links the image and the age using a general algorithm such as CNN (Convolutional Neural Network). By estimating the age, it becomes possible to take into account the reflectivity of radio waves on the target's body surface due to differences in age.

[0026] (Signal strength estimation unit) The signal strength estimation unit 141 estimates the range of the signal strength of the radio wave reflected by the target based on the estimation results output from each functional unit of the image processing unit 130. As an example, the signal strength estimation unit 141 estimates the range of the signal strength of the radio wave reflected by the target under normal circumstances based on the distance from the radio wave sensor 20 to the target estimated by the distance estimation unit 131. In general, the shorter the distance, the stronger the signal strength. The terms "normal" or "normal" refer to a state in which the target is not intentionally moving its body. Therefore, when there is a natural movement of the body such as a pulse or heartbeat, the target is not intentionally moving its body, and so this state is included in that case.

[0027] As another example, based on the estimated posture or skeleton of the target estimated by the skeleton estimation unit 132, the signal strength estimation unit 141 estimates the range of signal strength of radio waves reflected from the target under normal conditions. More specifically, based on the angle and area of ​​the radio wave irradiation surface estimated by the skeleton estimation unit 132, the signal strength estimation unit 141 estimates the range of signal strength. In general, the greater the degree to which the radio wave irradiation surface intersects perpendicularly with the boresight direction of the antenna of the radio wave sensor, the stronger the signal strength will be. Also, the greater the area of ​​the irradiation surface desired by the radio wave sensor, the stronger the signal strength will be.

[0028] As another example, the signal strength estimation unit 141 estimates the range of signal strength under normal circumstances of radio waves reflected by an object, based on the material estimated by the material estimation unit 133. Since the transmittance of radio waves differs depending on the material, it is considered that the signal strength will be stronger if the material of the object worn by the object has a higher transmittance.

[0029] As another example, based on the gender estimated by the gender estimation unit 134, the signal strength estimation unit 141 estimates the range of signal strength of radio waves reflected by a target under normal circumstances. On average, men have a higher water content than women. Also, the more moisture there is, the higher the reflectivity of radio waves becomes. Therefore, since the reflectivity of radio waves is higher on average for men than for women, it is considered that the signal strength will be stronger for men than for women.

[0030] As another example, the signal strength estimation unit 141 estimates the range of signal strength of radio waves reflected by a target under normal circumstances, based on the age estimated by the age estimation unit 135. In general, the younger the age, the higher the water content, so it is considered that the younger the age, the stronger the signal strength.

[0031] These examples may be combined in any way. For example, the signal strength estimation unit 141 may estimate the range of signal strength of radio waves reflected by an object under normal circumstances based on the estimated distance estimated by the distance estimation unit 131 and the angle and area of ​​the irradiation surface estimated by the skeleton estimation unit 132. Alternatively, the signal strength estimation unit 141 may estimate the range of signal strength of radio waves reflected by an object under normal circumstances based on the estimated distance estimated by the distance estimation unit 131, the material estimated by the material estimation unit 133, the gender estimated by the gender estimation unit 134, or the age estimated by the age estimation unit 135.

[0032] As a method for estimating the range of signal strength in normal times, a learning model is created in advance that links the estimation results of each functional unit of the image processing unit 130 with the signal strength of the reflected wave from the target using a general algorithm such as CNN (Convolutional Neural Network) under a transmission wave of a predetermined strength, and the estimation results of each functional unit of the image processing unit 130 are input to the created learning model to estimate the range of signal strength in normal times. A learning model that inputs transmission waves with different strengths may be created. In addition, the estimation results of each functional unit of the image processing unit 130 may be used to estimate the range of signal strength in normal times of the reflected wave from the target on a rule-based basis using a general algorithm such as the 3σ method.

[0033] (Noise reduction processing section) The noise reduction processing unit 142 reduces noise contained in the reflected signal acquired by the reflected signal acquisition unit 110, using the range of the target signal strength estimated by the signal strength estimation unit 141. As a noise reduction method, the reflected signal is subjected to a fast Fourier transform, and signals with strengths exceeding the range of the target signal strength estimated by the signal strength estimation unit 141 or signals with strengths below that range are reduced or removed.

[0034] Here, the signal strength estimation process and noise reduction process will be described with reference to Fig. 2. In Fig. 2, a waveform indicates the frequency spectrum of a signal obtained from an object. Based on the estimation results of each functional part of the image processing part 130, the signal strength estimation part 141 estimates a predetermined range from the estimated signal strength ESS of the object as an estimated strength range ESR. The noise reduction processing part 142 estimates the signal strength within a specified frequency range f B In the method, a signal having an intensity exceeding the upper limit of the estimated intensity range ESR or a signal having an intensity below the lower limit of the estimated intensity range ESR is regarded as an unintended signal and is reduced or eliminated.

[0035] frequency domain f B The frequency range f is specified by the user via the frequency input device 40. B The frequency acquisition unit 160 acquires from the frequency input device 40 and supplies to the noise processing unit 140. In a normal state, the range of frequencies that can be taken varies depending on parameters related to biological information, such as the heart rate being 0.8 to 1.2 [Hz] and the respiratory rate being 0.2 to 0.3 [Hz]. Therefore, the frequency domain f B is specified.

[0036] 2, the second peak P2 from the left exceeds the estimated intensity range ESR, so it is considered that noise due to, for example, body movement is superimposed on the peak P2. Therefore, the noise reduction processing unit 142 replaces the signal intensity value from valley V1 to V2 with, for example, 0. Alternatively, the signal intensity value from valley V1 to V2 is multiplied by an appropriate coefficient. In this way, noise is removed or reduced.

[0037] After performing the noise reduction process as described above, the noise reduction processing unit 142 outputs the reflected signal from which noise has been reduced or removed to the biological information calculation unit 150.

[0038] (Biometric information calculation section) The biometric information calculation unit 150 calculates the biometric information from the reflected signal that has been subjected to noise reduction processing by the noise reduction processing unit 142. The calculation method can be performed by identifying a peak frequency in a frequency band in which any biometric information can be taken from the reflected signal that has been subjected to noise reduction processing. As a specific example, the biometric information calculation unit 150 calculates the biometric information from a specified frequency range f B In the frequency domain f B When 0.8 to 1.2 [Hz] corresponding to the heart rate is specified as the frequency, for example, 1 [Hz] is specified as the frequency corresponding to the peak P3. In this case, 1 is multiplied by 60 to calculate the heart rate of 60 [beats / min] as the bioinformation. Examples of the calculated bioinformation include the heart rate, pulse rate, respiratory rate, and heart rate variability. The bioinformation calculation unit 150 outputs the calculated bioinformation to the control device 50.

[0039] In addition, the frequency domain f B Data that is not within this range is not taken into consideration. That is, in the waveform of Figure 2, the frequencies corresponding to the first peak from the left, P1, and the fourth peak from the left, P4, are not taken into consideration. Also, since noise has been reduced or removed from the signal of peak P2, the frequency corresponding to peak P2 is not used.

[0040] The control device 50 performs various controls using the biological information received from the biological information calculation unit 150. For example, it performs display control to display the biological information on a display device (not shown).

[0041] Next, a hardware configuration example of the bioinformation detection device 100 will be described with reference to Fig. 3A and Fig. 3B. As an example, as shown in Fig. 3A, the bioinformation detection device 100 includes a processor 101, a memory 102, and an input / output interface 103. The processor 101, the memory 102, and the input / output interface 103 are connected to each other via a bus 104. In this configuration example, the input / output interface 103 realizes the reflected signal acquisition unit 110, the image acquisition unit 120, and the frequency acquisition unit 160. Furthermore, the program stored in the memory 102 is read out and executed by the processor 101, thereby realizing each functional unit of the image processing unit 130, each functional unit of the noise processing unit 140, and the bioinformation calculation unit 150. The program is realized as software, firmware, or a combination of software and firmware. Examples of memory 102 include, for example, non-volatile or volatile semiconductor memory such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically-EPROM), magnetic disks, flexible disks, optical disks, compact disks, mini disks, and DVDs.

[0042] As another example, as shown in FIG. 3B, the bioinformation detection device 100 includes a processing circuit 105 and an input / output interface 103. The processing circuit 105 and the input / output interface 103 are connected to each other via a bus 106. In this configuration example, the input / output interface 103 realizes the reflected signal acquisition unit 110, the image acquisition unit 120, and the frequency acquisition unit 160. The processing circuit 105 realizes each functional unit of the image processing unit 130, each functional unit of the noise processing unit 140, and the bioinformation calculation unit 150. The processing circuit 105 is, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a combination thereof. The functions of each functional unit of the image processing unit 130, each functional unit of the noise processing unit 140, and the bioinformation calculation unit 150 may be realized by separate processing circuits, or these functions may be realized together by one processing circuit.

[0043] <Operation> Next, a flow of a biological information detection method performed as an operation of the biological information detection device 100 will be described with reference to Fig. 4. In step S101, the reflected signal acquisition unit 110 acquires, from the radio wave sensor 20, a reflected signal from a living body that is a target acquired by the radio wave sensor 20. In step S102, the image acquisition unit 120 acquires, from the camera 30, image data of the target acquired by the camera 30. Note that the processing in step S101 and the processing in step S102 are in no particular order.

[0044] In step S103, the distance estimation unit 131 of the image processing unit 130 estimates the position of the target based on the image data acquired by the image acquisition unit 120. The distance estimation unit 131 also estimates the distance from the radio wave sensor 20 to the target based on the estimated target position and the positional relationship between the camera 30 and the radio wave sensor 20. In step S104, the skeleton estimation unit 132 of the image processing unit 130 captures the posture or skeleton of the target based on the image acquired by the image acquisition unit 120, and acquires the angle and area of ​​the radio wave irradiation surface. In step S105, the material estimation unit 133 of the image processing unit 130 acquires the material of the radio wave irradiation surface of the wearable item such as clothes and accessories worn by the target based on the image acquired by the image acquisition unit 120. In step S106, the gender estimation unit 134 of the image processing unit 130 estimates the gender of the target based on the image acquired by the image acquisition unit 120. In step S107, the age estimation section 135 of the image processing section 130 estimates the age of the target based on the image acquired by the image acquisition section 120. Note that the processes from step S103 to step S107 may be performed in any order.

[0045] In step S108, the signal strength estimation unit 141 estimates a possible range of the signal strength of the radio wave reflected by the target, based on the estimation results obtained by each functional unit of the image processing unit 130. In step S109, the noise reduction processing unit 142 uses the signal strength of the target obtained by the signal strength estimation unit 141 to process the signal strength from outside the target, which is included in the reflected signal obtained by the reflected signal acquisition unit 110, as noise.

[0046] In step S110, the biological information calculation section 150 calculates biological information from the reflected signal on which the noise reduction processing has been performed by the noise reduction processing section 142.

[0047] According to the bioinformation detection device 100 of the present disclosure, when multiple peaks are found in a specified frequency band including the bioinformation to be extracted when a reflected signal is subjected to a fast Fourier transform, signals having intensities outside the estimated signal intensity range of the target are removed or reduced, thereby reducing false positives of the bioinformation, thereby improving the detection accuracy of the bioinformation.

[0048] <Additional Notes> Some of the various aspects of the embodiments described above are summarized below.

[0049] (Appendix 1) The biometric information detection device 100 of Appendix 1 comprises a reflected signal acquisition unit 110 that acquires a reflected signal from the living body of radio waves irradiated toward the living body, an image acquisition unit 120 that acquires an image of the living body, an image processing unit 130 that performs image processing on the acquired image, a signal strength estimation unit 141 that estimates a range of signal strengths that the reflected signal can have based on the results of the image processing, and a noise reduction processing unit 142 that reduces signals from the reflected signal having strengths outside the estimated signal strength range.

[0050] (Appendix 2) The biometric information detection device 100 of Appendix 2 is the biometric information detection device 100 of Appendix 1, wherein the image processing unit includes a skeleton estimation unit 132 that estimates the skeleton of the living body, and the signal intensity estimation unit estimates a range of signal intensity that the reflected signal can have based on the estimated skeleton.

[0051] (Appendix 3) The biometric information detection device 100 of Supplementary Note 3 is the biometric information detection device 100 of Supplementary Note 1 or 2, wherein the image processing unit includes a material estimation unit 133 that estimates a material of an article worn by the living body, and the signal intensity estimation unit estimates a range of signal intensity that the reflected signal can have based on the estimated material.

[0052] (Appendix 4) The biometric information detection device 100 of Appendix 4 is any one of the biometric information detection devices 100 of Appendix 1 to 3, wherein the image processing unit includes a gender estimation unit 134 that estimates the gender of the living body, and the signal intensity estimation unit estimates a range of signal intensity that the reflected signal can have based on the estimated gender.

[0053] (Appendix 5) The biometric information detection device 100 of Appendix 5 is the biometric information detection device 100 of any one of Appendixes 1 to 4, wherein the image processing unit includes an age estimation unit 135 that estimates the age of the living body, and the signal intensity estimation unit estimates a range of signal intensity that the reflected signal can have based on the estimated age.

[0054] (Appendix 6) The biometric information detection device 100 of Appendix 6 is any one of the biometric information detection devices 100 of Appendix 1 to 5, wherein the image processing unit includes a distance estimation unit 131 that estimates a distance to the living body, and the signal intensity estimation unit estimates a range of signal intensity that the reflected signal can have based on the estimated distance.

[0055] (Appendix 7) The biometric information detection method of Appendix 7 is a biometric information detection method performed by a biometric information detection device including a reflected signal acquisition unit, an image acquisition unit, an image processing unit, a signal intensity estimation unit, and a noise reduction processing unit, and includes the following steps: step S101 in which the reflected signal acquisition unit acquires a reflected signal from the biometric information detection device of radio waves irradiated toward the biometric information; step S102 in which the image acquisition unit acquires an image of the biometric information; steps (S103 to S107) in which the image processing unit performs image processing on the acquired image; step S108 in which the signal intensity estimation unit estimates a range of signal intensity that the reflected signal can have based on a result of the image processing; and step S109 in which the noise reduction processing unit reduces signals having intensity outside the estimated signal intensity range from the reflected signal.

[0056] It is possible to combine the embodiments, and to modify or omit each embodiment as appropriate. [Industrial Applicability]

[0057] INDUSTRIAL APPLICABILITY The biological information detection device according to the present disclosure can reduce noise superimposed on biological information signals, and therefore can be used in systems for monitoring biological information. [Explanation of symbols]

[0058] 10 monitoring system, 20 radio wave sensor, 30 camera, 40 frequency input device, 50 control device, 100 biometric information detection device, 101 processor, 102 memory, 103 input / output interface, 104 bus, 105 processing circuit, 106 bus, 110 reflected signal acquisition unit, 120 image acquisition unit, 130 image processing unit, 131 distance estimation unit, 132 skeleton estimation unit, 133 material estimation unit, 134 gender estimation unit, 135 age estimation unit, 140 noise processing unit, 141 signal strength estimation unit, 142 noise reduction processing unit, 150 biometric information calculation unit, 160 frequency acquisition unit.

Claims

1. a reflected signal acquisition unit that acquires a reflected signal from a living body of radio waves irradiated toward the living body; an image acquisition unit for acquiring an image of the living body; an image processing unit that performs image processing on the acquired image; a signal intensity estimation unit that estimates a range of possible signal intensities of the reflected signal based on a result of the image processing; a noise reduction processing unit that reduces, from the reflected signal, signals having intensities outside a range of possible signal intensities of the estimated reflected signal; Equipped with The image processing unit includes a skeleton estimation unit that estimates a skeleton of the living body, The signal strength estimation unit estimates the strength of the reflected signal from the living body based on the estimated skeleton so that the greater the degree to which the irradiation surface of the radio waves irradiated toward the living body intersects perpendicularly with the boresight direction, the stronger the signal strength of the reflected signal will be, and estimates a predetermined range from the estimated reflected signal strength as the range of signal strength that the reflected signal can take.This is a biological information detection device.

2. a reflected signal acquisition unit that acquires a reflected signal from a living body of radio waves irradiated toward the living body; an image acquisition unit for acquiring an image of the living body; an image processing unit that performs image processing on the acquired image; a signal intensity estimation unit that estimates a range of possible signal intensities of the reflected signal based on a result of the image processing; a noise reduction processing unit that reduces, from the reflected signal, signals having intensities outside a range of possible signal intensities of the estimated reflected signal; Equipped with The image processing unit includes a material estimation unit that estimates a material of an article worn by the living body, The signal strength estimation unit estimates the strength of the reflected signal from the living body based on the estimated material so that the signal strength of the reflected signal is stronger if the material has a higher transmittance, and estimates a predetermined range from the estimated reflected signal strength as the range of signal strength that the reflected signal can have.This is a biological information detection device.

3. a reflected signal acquisition unit that acquires a reflected signal from a living body of radio waves irradiated toward the living body; an image acquisition unit for acquiring an image of the living body; an image processing unit that performs image processing on the acquired image; a signal intensity estimation unit that estimates a range of possible signal intensities of the reflected signal based on a result of the image processing; a noise reduction processing unit that reduces, from the reflected signal, signals having intensities outside a range of possible signal intensities of the estimated reflected signal; Equipped with The image processing unit includes a gender estimation unit that estimates the gender of the living body, The signal strength estimation unit estimates the strength of the reflected signal from the living body based on the estimated gender so that the signal strength of the reflected signal is stronger for men than for women, and estimates a predetermined range from the estimated reflected signal strength as the range of signal strength that the reflected signal can take.

4. a reflected signal acquisition unit that acquires a reflected signal from a living body of radio waves irradiated toward the living body; an image acquisition unit for acquiring an image of the living body; an image processing unit that performs image processing on the acquired image; a signal intensity estimation unit that estimates a range of possible signal intensities of the reflected signal based on a result of the image processing; a noise reduction processing unit that reduces, from the reflected signal, signals having intensities outside a range of possible signal intensities of the estimated reflected signal; Equipped with The image processing unit includes an age estimation unit that estimates an age of the living body, The signal strength estimation unit estimates the strength of the reflected signal from the living body based on the estimated age, so that the signal strength of the reflected signal is stronger when the age is younger, and estimates a predetermined range from the estimated reflected signal strength as the range of signal strength that the reflected signal can take.

5. a reflected signal acquisition unit that acquires a reflected signal from a living body of radio waves irradiated toward the living body; an image acquisition unit for acquiring an image of the living body; an image processing unit that performs image processing on the acquired image; a signal intensity estimation unit that estimates a range of possible signal intensities of the reflected signal based on a result of the image processing; a noise reduction processing unit that reduces, from the reflected signal, signals having intensities outside a range of possible signal intensities of the estimated reflected signal; Equipped with The image processing unit includes a distance estimation unit that estimates a distance to the living body, The signal strength estimation unit estimates the strength of the reflected signal from the living body based on the estimated distance so that the signal strength of the reflected signal is stronger when the distance is shorter, and estimates a predetermined range from the estimated reflected signal strength as the range of signal strength that the reflected signal can take.This is a biological information detection device.

6. A biological information detection method performed by a biological information detection device including a reflected signal acquisition unit, an image acquisition unit, an image processing unit, a signal intensity estimation unit, and a noise reduction processing unit, a step of the reflected signal acquiring unit acquiring a reflected signal from the living body of the radio wave irradiated toward the living body; The image acquisition unit acquires an image of the living body; The image processing unit performs image processing on the acquired image to estimate a bone structure, a material of a garment, a sex, or an age of the living body; a step of estimating a range of signal strengths that the reflected signal can have based on a result of the image processing by the signal strength estimating unit, Based on the estimated skeleton, the greater the degree to which the irradiation surface of the radio waves irradiated toward the living body intersects perpendicularly with the boresight direction, the stronger the signal intensity of the reflected signal becomes. Based on the estimated material, the higher the transmittance of the material, the stronger the signal strength of the reflected signal. based on the estimated gender, such that the signal strength of the reflected signal is stronger for males than for females; or Based on the estimated age, the younger the age, the stronger the signal strength of the reflected signal. a step of estimating an intensity of a reflected signal from the living body, and estimating a predetermined range from the estimated reflected signal intensity as a range of signal intensity that the reflected signal can take; a step of reducing, from the reflected signal, a signal having an intensity outside a range of signal intensity that the estimated reflected signal can have, by the noise reduction processing unit; A biological information detection method comprising:

Images