Biological information processing device, biological information processing method, and program

Abstract

To provide a technology to associate a person to be measured with biological information.SOLUTION: A biological information processing device includes: a signal reception unit for receiving a signal on biological information reflected from at least one person to be measured; a candidate region specification unit for calculating an arrival direction of the signal and / or a distance to the person to be measured from the received signal, and specifying a candidate region of the person to be measured using the calculated arrival direction and / or the distance; an information generation unit for generating biological information corresponding to the candidate region of the person to be measured from the received signal; a position information acquisition unit for acquiring position information on the person to be measured; and a biological information association unit for associating the person to be measured with the generated biological information on the basis of the acquired position information.SELECTED DRAWING: Figure 3

Description

Technical Field

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[0001] The present invention relates to a technique for processing biological information.

Background Art

[0002] Techniques for acquiring biological information of a person to be measured using non-contact means such as various sensors and radars and associating the acquired biological information with the person to be measured have been put into practical use. For example, in Patent Document 1, a technique for identifying a person to be measured from an image generated by an imaging device and associating the person to be measured with the biological information of the person to be measured acquired separately has been proposed.

Prior Art Documents

Patent Documents

[0003] [[ID=2​​​​​​​​​​​​​​​​​​​​​​​To achieve the above objective, the present invention employs the following configuration.

[0007] One aspect of the present invention is a biological information processing device comprising: a signal receiving unit that receives a signal relating to biological information reflected from at least one person to be measured; a candidate region identification unit that calculates the direction of arrival of the received signal and / or the distance to the person to be measured, and identifies a candidate region of the person to be measured using the calculated direction of arrival and / or the distance; an information generation unit that generates biological information corresponding to the candidate region of the person to be measured from the received signal; a location information acquisition unit that acquires location information of the person to be measured; and a biological information association unit that associates the person to be measured with the generated biological information based on the acquired location information. Alternatively, one aspect of the present invention is a bio-information processing device comprising: a signal receiving unit that receives signals relating to bio-information reflected from a plurality of persons; a candidate region identification unit that calculates the direction of arrival of the received signal and / or the distance to at least one person to be measured from the plurality of persons, and identifies a candidate region of the person to be measured using the calculated direction of arrival and / or the distance; an information generation unit that generates bio-information corresponding to the candidate region of the person to be measured from the received signal; a location information acquisition unit that acquires the location information of the person to be measured; and a bio-information association unit that associates the person to be measured with the generated bio-information based on the acquired location information. This makes it possible to accurately associate bio-information obtained from a person to be measured by a non-contact bio-information acquisition means with the person to be measured. .

[0008] Furthermore, the positional information of the person being measured may be obtained by optically measuring the contour shape of the person being measured. Alternatively, the positional information of the person being measured may be obtained by measuring the distribution of pressure applied to different locations by the person being measured. Alternatively, the positional information of the person being measured may be obtained by measuring the distribution of the person's body temperature. Alternatively, the positional information of the person being measured may be obtained by measuring the distribution of the space occupied by the person being measured. Alternatively, the positional information of the person being measured may be obtained by measuring the sound emitted by the person being measured and the location where the sound originated. Alternatively, the positional information of the person being measured may be positional information indicating the space occupied by the person being measured at the time of measurement. Alternatively, the positional information of the person being measured may be positional information identified by the detection location of a tag worn by the person being measured that has the identification information of the person being measured. As a result, based on the various positional information described above, the correspondence between the person being measured and their biological information can be accurately identified using the characteristics of the person's biological information.

[0009] Furthermore, the biometric information association unit may associate the person being measured with the generated biometric information based on information that identifies the person being measured, which has been acquired in advance. This is expected to improve the accuracy of the association between the person being measured and the biometric information. The biometric information processing device may also further include an output unit that outputs a notification that the association between the person being measured and the biometric information cannot be performed properly when the spatial distribution of the reflection points of the received signal is abnormal. This allows for accurate association between the biometric information and the person being measured while suppressing the possibility of an anomaly that could hinder the acquisition of the biometric information of the person being measured.

[0010] Furthermore, one aspect of the present invention is a bio-information processing device characterized by comprising: a signal receiving unit that receives signals indicating pressure applied to different locations by at least one person who is to be measured; a candidate region identification unit that identifies candidate regions of the person to be measured based on the pressure distribution obtained from the received signals; an information generation unit that generates bio-information corresponding to the candidate regions of the person to be measured from the received signals; a location information acquisition unit that acquires location information of the person to be measured; and a bio-information association unit that associates the person to be measured with the generated bio-information based on the acquired location information. This makes it possible to accurately associate bio-information with a person to be measured, for example, when a person to be measured is on a bed in which pressure measuring elements are arranged in a planar manner.

[0011] Furthermore, one aspect of the present invention is a bio-information processing device comprising: a signal receiving unit that receives a signal relating to bio-information reflected from at least one person who is a subject to measurement; an estimation unit that estimates the number of persons to be measured by machine learning for each predetermined unit of arrival direction and / or distance from the received signal to the person who is a subject to measurement; an information generation unit that generates bio-information of the person to be measured from the received signal; a classification unit that classifies the generated bio-information of the person to be measured based on the estimated number of persons to be measured; a location information acquisition unit that acquires location information of the person to be measured; and a bio-information association unit that associates the person to be measured with the classified bio-information based on the acquired location information, wherein the classification unit, when it acquires information regarding the number of persons to be measured, classifies the generated bio-information of the person to be measured based on the acquired information instead of the estimated number of persons to be measured. Furthermore, one aspect of the present invention is a bio-information processing device comprising: a signal receiving unit that receives a signal relating to bio-information reflected from at least one person who is a subject to measurement; The biometric information processing device is characterized by comprising: a signal receiving unit; an information generation unit that generates biometric information of the person to be measured from the received signal; an acquisition unit that acquires information regarding the number of people to be measured; a classification unit that classifies the generated biometric information of the people to be measured based on the acquired information regarding the number of people to be measured; a location information acquisition unit that acquires location information of the people to be measured; and a biometric information association unit that associates the people to be measured with the classified biometric information based on the acquired location information. This makes it possible to classify biometric information using information with higher accuracy than the information regarding the number of people to be measured that can be identified by inference.

[0012] Furthermore, the present invention can also be understood as a method for processing biometric information, which includes at least a part of the above-described process, a program for causing a computer to execute such a method, or a computer-readable recording medium on which such a program is non-temporarily recorded. Each of the above configurations and processes can be combined with each other to constitute the present invention, provided that no technical inconsistencies arise. [Effects of the Invention]

[0013] According to the present invention, biometric information obtained from a person being measured can be accurately associated with that person. [Brief explanation of the drawing]

[0014] [Figure 1] Figure 1 is a schematic diagram showing an example of the configuration of a biological information processing device to which the present invention is applied. [Figure 2] Figure 2 shows a schematic configuration of a biological information processing device according to one embodiment. [Figure 3] Figure 3 is a block diagram showing an example of a bio-information processing device according to one embodiment. [Figure 4] Figure 4 is a flowchart showing an example of the processing flow of a biological information processing device according to one embodiment. [Figure 5]FIG. 5A is a diagram showing an example of a candidate region of a person to be measured in one embodiment, FIG. 5B is a diagram showing an example of position information of a person to be measured in one embodiment, and FIGS. 5C to 5E are diagrams showing examples of biological information of a person to be measured in one embodiment. [Figure 6] FIG. 6A is a diagram schematically showing a configuration example of a biological information processing apparatus according to one embodiment, and FIG. 6B is a diagram showing an example of a candidate region of a person to be measured in one embodiment. [Figure 7] FIG. 7A is a diagram schematically showing a configuration example of a biological information processing apparatus according to one embodiment, and FIG. 7B is a diagram showing an example of a candidate region of a person to be measured in one embodiment. [Figure 8] FIG. 8A is a diagram schematically showing a configuration example of a biological information processing apparatus according to one embodiment, and FIG. 8B is a diagram showing an example of a candidate region of a person to be measured in one embodiment. [Figure 9] FIG. 9A is a diagram schematically showing a configuration example of a biological information processing apparatus according to one embodiment, and FIG. 9B is a diagram showing an example of a candidate region of a person to be measured in one embodiment. [Figure 10] FIG. 10A is a diagram schematically showing a configuration example of a biological information processing apparatus according to one embodiment, and FIG. 10B is a diagram showing an example of a candidate region of a person to be measured in one embodiment. [Figure 11] FIG. 11A is a diagram schematically showing a configuration example of a biological information processing apparatus according to a modification example, and FIG. 11B is a diagram schematically showing a configuration example of a bed in a modification example. [Figure 12] FIG. 12A is a flowchart showing an example of a processing flow of a biological information processing apparatus according to a modification example, and FIG. 12B is a diagram showing an example of a candidate region of a person to be measured in a modification example. [Figure 13] FIG. 13 is a flowchart showing an example of a processing flow of a biological information processing apparatus according to a modification example. [Figure 14] FIG. 14 is a flowchart showing an example of a processing flow of a biological information processing apparatus according to a modification example.

MODE FOR CARRYING OUT THE INVENTION

[0015] <Applicable Example> An applicable example of the present invention will be described. In the prior art, in order to identify a person to be measured based on an image of the person to be measured, when a plurality of persons to be measured use the same bedding, for example, since the difference in the images of the persons to be measured is small, there is a possibility that each person to be measured cannot be accurately identified. Further, in the prior art, depending on the position of the person to be measured, the imaging device may not be able to correctly image the person to be measured, and there is a possibility that face authentication cannot be performed normally.

[0016] FIG. 1 is a diagram schematically showing a usage example of a biological information processing apparatus 100 to which the present invention is applied. In the usage example shown in FIG. 1, three persons 31, 32, and 33 who are measurement targets of biological information are lined up on a bed 20 installed in a room 10. Further, in the room 10, a biological information processing apparatus 100 and a LiDAR (Light Detection and Ranging) scanner 150 are arranged. The biological information processing apparatus 100 transmits signals to the persons 31, 32, and 33 to be measured on the bed 20 and performs so-called non-contact biological information sensing. Examples of the frequency of the signals transmitted to the persons 31, 32, and 33 to be measured include frequencies in the frequency band of 30 GHz to 300 GHz used for a millimeter-wave radar, but frequencies in other frequency bands such as light, radio waves, sound waves, and ultrasonic waves may be adopted. The LiDAR scanner 150 is a device that measures the position of a person to be measured by LiDAR technology.

[0017] Figure 2 shows an example configuration of the biometric information processing device 100. The biometric information processing device 100 includes a transmitting / receiving unit 111, a control unit 112, a storage unit 113, and an output unit 114. The transmitting / receiving unit 111 functions as a signal receiving unit that receives signals related to biometric information reflected from the person being measured, and transmits and receives signals to and from the persons 31, 32, and 33 being measured. The control unit 112 generates biometric information for each person being measured using the signals received by the transmitting / receiving unit 111 from the persons 31, 32, and 33 being measured. Details of the biometric information generation process performed by the control unit 112 will be described later. The storage unit 113 stores various data, such as signal data received by the transmitting / receiving unit 111, and data used or generated in the processing performed by the control unit 112. The output unit 114 notifies the user or outputs data related to the results to an external device according to the results of the processing performed by the control unit 112. The output unit 114 may be configured to output data relating to the biological information of the person being measured to an external device using various communication methods such as wireless communication or wired communication.

[0018] The biometric information processing device 100 uses signal transmission and reception means such as radio wave radar, ultrasonic sensors, and sound wave sensors to perform non-contact biometric information sensing on multiple individuals to be measured, and identifies the acquired biometric information of each individual based on the location information of the individuals to be measured. Therefore, the biometric information processing device 100 can accurately associate the biometric information acquired from individuals to be measured with the individuals to be measured.

[0019] <Description of Embodiments> An embodiment of the technology disclosed herein will now be described. In this embodiment, as an example, a biometric information processing device 100 and a bed 20 are arranged in a room 10 as shown in Figure 1, and several people 31, 32, and 33, who are to be measured for biometric information, lie on the bed 20, and biometric information regarding the breathing of each person during sleep is to be acquired by the biometric information processing device. Here, it is assumed that the people 31, 32, and 33 who are to be measured constitute one family, and are a woman, a child, and a man, respectively. In this example, the biometric information to be acquired is assumed to be biometric information regarding the breathing of the people to be measured, but the biometric information to be acquired may also be biometric information regarding heart rate, body movement, etc.

[0020] Figure 3 is a block diagram showing an example configuration of a biometric information processing device 100 according to one embodiment. As shown in Figure 3, in the biometric information processing device 100, the transmitting / receiving unit 111 transmits information to the person being measured. The system includes a transmitting unit 121 that transmits signals to objects and a receiving unit 122 that receives signals reflected from the person being measured. Furthermore, the transmitting / receiving unit 111 communicates with a LiDAR scanner 150 and acquires the position information of each person being measured as measured by the LiDAR scanner 150. The LiDAR scanner 150 is an example of a device that generates position information of a person being measured by optically measuring the contour shape of the person being measured. As a result, even in cases where conventional image recognition processing of a person being measured cannot correctly identify the person being measured due to reasons such as the person's posture being inappropriate or the person being measured using the same bedding, it is possible to appropriately generate position information for each person being measured.

[0021] Furthermore, the control unit 112 includes a signal addition unit 123 that performs signal addition by summing the signals received by the receiving unit 122, an information generation unit 124 that generates biological information by performing signal processing on the added signals, a candidate area identification unit 125 that identifies candidate areas indicating the location of the person to be measured, and a biological information association unit 126 that associates biological information with each person to be measured. The biological information for each person to be measured, associated by the biological information association unit 126, is output to the display device 300 by the output unit 114. Examples of display devices include displays and information processing terminals (such as smartphones).

[0022] The control unit 112 includes a CPU (Central Processing Unit), RAM (Random Access Memory), ROM (Read Only Memory), etc., and controls various parts of the biometric information processing device 100 and performs various information processing. The storage unit 113 stores programs executed by the control unit 112 and various data used in the processing performed by the control unit 112. For example, the storage unit 113 is an auxiliary storage device such as a hard disk drive or solid-state drive. The output unit 114 outputs the biometric information of the person being measured, processed by the control unit 112, to the display device 300. The biometric information generated by the control unit 112 may be stored in the storage unit 113 and output to the display device 300 from the output unit 114 at any time.

[0023] Furthermore, in this embodiment, the biometric information processing device 100 and the display device 300 are assumed to be separate devices, but the biometric information processing device 100 may be configured as an integral part of the display device 300. Also, at least some of the functions of the biometric information processing device 100 may be implemented by a computer on the cloud, or by a PLC (Programmable Logic Controller) or a single board This could also be a microcomputer, such as a computer.

[0024] Figure 4 is a flowchart showing an example of the processing flow of the biometric information processing device 100. For example, after power-on, the user operates the biometric information processing device 100 to instruct it to start the processing flow of Figure 4, and the processing of Figure 4 is executed. In addition, before the processing of this flowchart is started, information indicating that the target of acquiring biometric information is the measurement target persons 31, 32, and 33, and characteristic information regarding the biometric information characteristics of the measurement target persons 31, 32, and 33 are stored in the storage unit 113 in advance. Alternatively, this information may be specified by the user of the biometric information processing device 100 before the processing of this flowchart is started. The characteristic information of the biometric information of each measurement target person is information used in the biometric information processing device 100 to associate the biometric information generated by the processing described later with each measurement target person, and in this embodiment, as an example, it is information indicating the characteristics of the body contour shape of each measurement target person. Referring to Figure 4, the process of identifying biometric information for each measurement target person executed in the biometric information processing device 100 will be explained.

[0025] In step S301, the transmitter 121 transmits a chirp signal to the people 31, 32, and 33 on the bed 20 whose biological information is to be measured. The frequency bandwidth and transmission method, such as up-chirp or down-chirp, of the chirp signal transmitted by the transmitter 121 may be set as appropriate. Here, as an example, the FMCW (Continuous Frequency Modulation) method is used, and the transmission and reception samples... The ping period is assumed to be around 100 μs, and an 8-channel array antenna is assumed to be used. The receiving unit 122 receives the signals reflected from the people 31, 32, and 33 being measured. Next, in step S302, the signal summing unit 123 performs signal summing by adding the IF signals obtained from the difference between the chirp signal transmitted by the transmitting unit 121 and the signal received by the receiving unit 122.

[0026] In step S303, the control unit 112 determines whether the transmission and reception of chirp signals to the persons 31, 32, and 33 to be measured in step S301 has been performed a predetermined number of times. Here, the accuracy of the biometric information of the persons to be measured, which will be generated by the processing described later, can be ensured by performing the transmission and reception of chirp signals a predetermined number of times. If the transmission and reception of chirp signals has been performed a predetermined number of times (S303: YES), the control unit 112 proceeds to step S304, and if the number of times the transmission and reception of chirp signals has been performed is less than the predetermined number (S303: NO), the processing returns to step S301. The predetermined number of times the transmission and reception of chirp signals may be determined as appropriate depending on the type of biometric information to be generated.

[0027] In step S304, the information generation unit 124 calculates the distance from the transmitting / receiving unit 111 (biological information processing device 100) using the signals added in step S302. Specifically, the information generation unit 124 performs AD conversion on the IF signals added in step S302, then performs a Fourier transform (FFT) to obtain different frequency spectra, from which it calculates the distance to the position where the signal was reflected.

[0028] In step S305, the information generation unit 124 calculates the direction relative to the transmitting / receiving unit 111 (biometric information processing device 100) using the signals added in step S302. Specifically, the information generation unit 124 calculates the direction of arrival (angle) from the phase difference of the received signals between the multiple antennas of the receiving unit 122.

[0029] Next, in step S306, the transmitting / receiving unit 111 acquires the location information of the people 31, 32, and 33 to be measured, as measured by the LiDAR scanner 150. Next, in step S307, the information generation unit 124 generates information regarding the spatial distribution of reflection points received by the receiving unit 122 based on the distance and direction calculated in steps S304 and S305. Then, in step S308, the information generation unit 124 identifies candidate regions of the people to be measured based on the information regarding the spatial distribution of reflection points.

[0030] Figure 5A shows an example of candidate regions identified by the information generation unit 124 based on information regarding the spatial distribution of reflection points in this embodiment. Here, regions 51, 52, and 53 correspond to the people 31, 32, and 33 being measured. Figure 5B shows an example of positional information of the people 31, 32, and 33 being measured, which is received by the transmitting / receiving unit 111 from the LiDAR scanner 150 in this embodiment. As shown in Figure 5B, the LiDAR scanner 150 outputs point clouds 201, 202, and 203, which represent the contour shapes of the people 31, 32, and 33 being measured, as positional information. As shown in the figure, point clouds 201 (size: medium), 202 (size: small), and 203 (size: large) are obtained according to the size of the people 31, 32, and 33 being measured.

[0031] Next, in step S309, the information generation unit 124 generates biological information showing the respiratory waveform from the time-dependent change in amplitude or phase for each candidate region 51, 52, and 53 identified in step S308, using the signals added in step S302. Figures 5C, 5D, and 5E are examples of graphs showing the time-dependent change in amplitude or phase (respiratory waveform) in each candidate region 51, 52, and 53 in this embodiment. As shown in Figures 5C, 5D, and 5E, biological information showing respiratory waveforms with different time-dependent changes in amplitude or phase is obtained for each candidate region 51, 52, and 53.

[0032] Then, in step S310, the biometric information association unit 126 associates the biometric information of the people 31, 32, and 33, based on the similarity between the features of the body contour shape of the people 31, 32, and 33, indicated by the positional information of the people 31, 32, and 33 measured by the LiDAR scanner 150 acquired in step S306, and the features of the body contour shape of the people 31, 32, and 33 stored in the memory unit 113. For example, the biometric information association unit 126 determines that the point cloud 201 is the contour shape of person 31 based on the contour shape features (size: medium) indicated by the point cloud 201, and associates the biometric information obtained from the candidate region 51 corresponding to the position of the point cloud 201 with person 31. Similarly, the biometric information association unit 126 associates the biometric information obtained from the candidate regions 52 and 53 with people 32 and 33, respectively.

[0033] According to this embodiment, based on the positional information of each person to be measured, obtained by optically measuring the contour shape of each person to be measured using a LiDAR scanner, the biometric information obtained for multiple people to be measured using non-contact biometric information acquisition means such as radar can be accurately correlated with each person to be measured.

[0034] (Second Embodiment) Next, a biological information processing device according to the second embodiment will be described. In the following description, the same reference numerals will be used for components and processes similar to those in the first embodiment, and detailed explanations will be omitted.

[0035] In the first embodiment of the biometric information processing device 100, each candidate region 51, 52, 53 is associated with each person 31, 32, 33, which are the subjects of measurement, based on the position information of each person obtained by optically measuring the contour shape of each person being measured using a LiDAR scanner. However, in the second embodiment of the biometric information processing device 100, each candidate region 51, 52, 53 is associated with each person 31, 32, 33, which are the subjects of measurement, based on characteristic information of the pressure distribution obtained from each person being measured for biometric information on the body pressure sensor. Furthermore, in this embodiment, before the processing of the flowchart shown in Figure 4 begins, information indicating that the subjects from which biometric information is to be acquired are the persons 31, 32, 33, which are the subjects of measurement, and information regarding the characteristics of the biometric information of each person being measured for biometric information obtained from the body pressure sensor (for example, pressure distribution) are stored in the storage unit 113 in advance. Alternatively, this information may be specified by the user of the biometric information processing device 100 before the processing of this flowchart begins.

[0036] Figure 6A shows an example of the use of the biomedical information processing device 100 in this embodiment. As shown in Figure 6A, a body pressure sensor 160 is placed on a bed 20, and the people to be measured 31, 32, and 33 are lying on the body pressure sensor 160. The body pressure sensor 160 measures the distribution of pressure applied at different locations by each person being measured. It then outputs characteristic information showing the pressure distribution for each person 31, 32, and 33 on the body pressure sensor 160 to the biomedical information processing device 100. The transmitting and receiving unit 111 acquires the characteristic information of the pressure distribution of each person being measured, as measured by the body pressure sensor 160.

[0037] In this embodiment, in step S306, the transmitting / receiving unit 111 acquires characteristic information indicating the pressure distribution of the persons 31, 32, and 33 being measured, as measured by the body pressure sensor 160. Figure 6B shows an example of characteristic information regarding the pressure distribution of the persons 31, 32, and 33 being measured, which the transmitting / receiving unit 111 receives from the body pressure sensor 160 in this embodiment. As shown in Figure 6B, the body pressure sensor 160 outputs as position information regions 211 (size: medium), 212 (size: small), and 213 (size: large) that indicate the pressure distribution on the body pressure sensor 160 according to the size of the bodies of the persons 31, 32, and 33 being measured.

[0038] Then, in step S310, the biological information association unit 126 in step S306 Based on the similarity between the pressure distribution characteristics of the subjects 31, 32, and 33, which are output from the body pressure sensor 160 and which are stored in the memory unit 113, the system associates the subjects 31, 32, and 33 with their biological information. For example, the biological information association unit 126 determines that region 211 is the pressure distribution of subject 31 based on the characteristics (size: medium) of the region 211 showing the pressure distribution, and associates the biological information obtained from candidate region 51 corresponding to the location of region 211 with subject 31. Similarly, the biological information association unit 126 associates the biological information obtained from candidate regions 52 and 53 with subjects 32 and 33, respectively.

[0039] Therefore, according to this embodiment, based on the positional information of the pressure distribution of each person being measured obtained by the body pressure sensor, the biometric information obtained for multiple people being measured by a non-contact biometric information acquisition means such as radar can be accurately associated with each person being measured. Alternatively, or in addition to the above, the transmitting / receiving unit 111 may acquire information indicating the weight of each person being measured from the body pressure sensor 160, and the biometric information association unit 126 may associate the biometric information with each person being measured based on the characteristic information of the pressure distribution of each person being measured and / or the information indicating the weight of each person being measured.

[0040] (Third embodiment) Next, a biological information processing device according to the third embodiment will be described. In the following description, the same reference numerals will be used for components and processes similar to those in the above embodiments, and detailed explanations will be omitted.

[0041] In the first embodiment of the biometric information processing device 100, each candidate region 51, 52, 53 is associated with each person 31, 32, 33, which are the subjects of measurement, based on the position information of each person obtained by optically measuring the contour shape of each person to be measured using a LiDAR scanner. However, in the third embodiment of the biometric information processing device 100, each candidate region 51, 52, 53 is associated with each person 31, 32, 33, which are the subjects of measurement, based on characteristic information of the body temperature distribution of each person to be measured, which is measured by a thermal image sensor. Furthermore, in this embodiment, before the processing of the flowchart shown in Figure 4 begins, information indicating that the subjects from which biometric information is to be acquired are the persons 31, 32, 33, which are the subjects of measurement, and information regarding the characteristics of the biometric information of each person to be measured obtained from the thermal image sensor (for example, body temperature distribution) are stored in the storage unit 113 in advance. Alternatively, this information may be specified by the user of the biometric information processing device 100 before the processing of this flowchart begins.

[0042] Figure 7A shows an example of the use of the biomedical information processing device 100 in this embodiment. As shown in Figure 7A, a thermal image sensor 170 is placed in room 10. The thermal image sensor 170 measures the body temperature of each person 31, 32, and 33 being measured and outputs characteristic information showing the body temperature distribution for each person 31, 32, and 33 to the biomedical information processing device 100. The transmitting and receiving unit 111 acquires the characteristic information of the body temperature distribution of each person being measured, as measured by the thermal image sensor 170.

[0043] In this embodiment, in step S306, the transmitting / receiving unit 111 acquires characteristic information indicating the body temperature distribution of the persons 31, 32, and 33 being measured, as measured by the thermal image sensor 170. Figure 7B shows an example of characteristic information regarding the body temperature distribution of the persons 31, 32, and 33 being measured, which the transmitting / receiving unit 111 receives from the thermal image sensor 170 in this embodiment. As shown in Figure 7B, the thermal image sensor 170 outputs as location information regions 221 (size: medium), 222 (size: small), and 223 (size: large) that indicate the body temperature distribution according to the size of the bodies of the persons 31, 32, and 33 being measured.

[0044] Then, in step S310, the biometric information association unit 126 uses the data of the people 31, 32, and 33 that were to be measured, which were output from the thermal image sensor 170 in step S306. Based on the similarity between the characteristics of the body temperature distribution and the characteristics of the body temperature distributions of the subjects 31, 32, and 33 stored in the memory unit 113, the system associates the subjects 31, 32, and 33 with their biological information. For example, the biological information association unit 126 determines that region 221, which shows the body temperature distribution, is the body temperature distribution of subject 31 based on its characteristics (size: medium), and associates the biological information obtained from candidate region 51 corresponding to the location of region 221 with subject 31. Similarly, the biological information association unit 126 associates the biological information obtained from candidate regions 52 and 53 with subjects 32 and 33, respectively.

[0045] Therefore, according to this embodiment, based on the positional information of the body temperature distribution of each person being measured obtained by the thermal image sensor, the biometric information obtained for multiple people being measured by a non-contact biometric information acquisition means such as radar can be accurately associated with each person being measured. Alternatively, or in addition to the above, the transmitting / receiving unit 111 may acquire information indicating the body temperature of each person being measured from the thermal image sensor 170, and the biometric information association unit 126 may associate the biometric information with each person being measured based on the characteristic information of the body temperature distribution of each person being measured and / or the information indicating the body temperature of each person being measured.

[0046] (Fourth Embodiment) Next, a biological information processing device according to the fourth embodiment will be described. In the following description, the same reference numerals will be used for components and processes similar to those in the above embodiments, and detailed explanations will be omitted.

[0047] In the first embodiment of the biometric information processing device 100, each candidate region 51, 52, 53 is associated with each individual 31, 32, 33, which are the subjects of measurement, based on the positional information of each individual obtained by optically measuring the contour shape of each individual subject of measurement using a LiDAR scanner. However, in the fourth embodiment of the biometric information processing device 100, each candidate region 51, 52, 53 is associated with each individual 31, 32, 33, which are the subjects of measurement, based on characteristic information of the spatial distribution occupied by each individual subject of measurement, which is measured by a rotating radar for spatial distribution detection, as an example. Furthermore, in this embodiment, before the processing of the flowchart shown in Figure 4 begins, information indicating that the subjects of biometric information acquisition are the individuals 31, 32, 33, and information regarding the characteristics of the biometric information of each individual obtained from the radar for spatial distribution detection (as an example, the size of the spatial distribution occupied by the individuals subject of measurement) is pre-stored in the storage unit 113. Alternatively, this information may be specified by the user of the biometric information processing device 100 before the processing of this flowchart begins.

[0048] Figure 8A shows an example of the use of the biometric information processing device 100 in this embodiment. As shown in Figure 8A, a radar 180 for spatial distribution detection is placed in room 10. The radar 180 measures the spatial distribution occupied by each of the persons 31, 32, and 33 being measured, and outputs characteristic information indicating the spatial distribution for each of the persons 31, 32, and 33 being measured to the biometric information processing device 100. The transmitting and receiving unit 111 acquires the characteristic information of the spatial distribution occupied by each of the persons being measured, as measured by the radar 180.

[0049] In this embodiment, in step S306, the transmitting / receiving unit 111 acquires characteristic information indicating the spatial distribution occupied by the persons 31, 32, and 33 being measured by the radar 180. Figure 8B shows an example of characteristic information of the spatial distribution occupied by the persons 31, 32, and 33 being measured, which the transmitting / receiving unit 111 receives from the radar 180 in this embodiment. As shown in Figure 8B, the radar 180 outputs as location information regions 231 (size: medium), 232 (size: small), and 233 (size: large), which indicate the spatial distribution according to the body size of the persons 31, 32, and 33 being measured.

[0050] Then, in step S310, the biological information association unit 126 in step S306 Based on the similarity between the spatial distribution characteristics of the subjects 31, 32, and 33, which are output from the radar 180 and acquired in the above location, and the spatial distribution characteristics of the subjects 31, 32, and 33 stored in the memory unit 113, the system associates the subjects 31, 32, and 33 with their biological information. For example, the biological information association unit 126 determines from the characteristics (size: medium) of the region 231 that shows the spatial distribution that region 231 is the body temperature distribution of the subject 31, and associates the biological information obtained from the candidate region 51 corresponding to the location of region 231 with the subject 31. Similarly, the biological information association unit 126 associates the biological information obtained from the candidate regions 52 and 53 with the subjects 32 and 33, respectively.

[0051] Therefore, according to this embodiment, based on the spatial distribution position information of each person being measured obtained by a radar for spatial distribution detection, the biometric information obtained for multiple people being measured by a non-contact biometric information acquisition means such as a radar for biosignal detection can be accurately correlated with each person being measured.

[0052] (Fifth embodiment) Next, a biological information processing device according to the fifth embodiment will be described. In the following description, the same reference numerals will be used for components and processes similar to those in the above embodiments, and detailed explanations will be omitted.

[0053] In the first embodiment of the biometric information processing device 100, each candidate region 51, 52, 53 is associated with each individual 31, 32, 33, which are the subjects of measurement, based on the positional information of each individual obtained by optically measuring the contour shape of each individual subject of measurement using a LiDAR scanner. However, in the fifth embodiment of the biometric information processing device 100, for example, the voice and breathing sounds of each individual subject of measurement are measured using an array microphone, and each candidate region 51, 52, 53 is associated with each individual 31, 32, 33, which are the subjects of measurement, based on the waveform of the sound emitted by each individual and characteristic information indicating the sound generation location. Furthermore, in this embodiment, before the processing of the flowchart shown in Figure 4 is started, information indicating that the target for acquiring biometric information is the individuals 31, 32, 33, and information regarding the characteristics of the biometric information of each individual obtained from the array microphone (for example, the waveform of voice and breathing sounds) is stored in the storage unit 113 in advance. Alternatively, this information may be specified by the user of the biometric information processing device 100 before the processing of this flowchart is started.

[0054] Figure 9A shows an example of the use of the biometric information processing device 100 in this embodiment. As shown in Figure 9A, an array microphone 190 is placed in room 10. The array microphone 190 measures the sound emitted by each person 31, 32, and 33 being measured, for each direction, and outputs information indicating the sound waveform and the sound source location to the biometric information processing device 100.

[0055] In this embodiment, in step S306, the transmitting / receiving unit 111 acquires information indicating the location of sound emitted by the persons 31, 32, and 33 being measured, as measured by the array microphone 190. Figure 9B shows an example of location information indicating the location of sound emitted by the persons 31, 32, and 33 being measured, which the transmitting / receiving unit 111 receives from the array microphone 190 in this embodiment. As shown in Figure 9B, the array microphone 190 outputs as location information the directions indicating the locations 241, 242, and 243 where the sound emitted by the persons 31, 32, and 33 being measured was generated.

[0056] Then, in step S310, the bio-information association unit 126 determines that the sound generation locations 241, 242, and 243 are the voices, breathing sounds, etc., of the persons being measured, respectively, based on the similarity between the waveforms of the sounds emitted by the persons being measured 31, 32, and 33, which were output from the array microphone 190 and acquired in step S306, and the waveforms of the voices, breathing sounds, etc., of the persons being measured 31, 32, and 33, which are stored in the memory unit 113, and determines that the sound generation locations 241, 242, and 243 are the voices, breathing sounds, etc., of the persons being measured 31, 32, and 33, respectively. The biometric information obtained from candidate regions 51, 52, and 53 corresponding to locations 241, 242, and 243 is associated with the individuals 31, 32, and 33 being measured, respectively.

[0057] Therefore, according to this embodiment, based on positional information indicating the location of sound emitted by each person being measured, obtained by an array microphone, it is possible to accurately correlate the biometric information obtained from multiple people being measured using non-contact biometric information acquisition means such as radar with each person being measured.

[0058] (Sixth Embodiment) Next, a biological information processing device according to the sixth embodiment will be described. In the following description, the same reference numerals will be used for components and processes similar to those in the above embodiments, and detailed explanations will be omitted.

[0059] In the first embodiment of the biometric information processing device 100, each candidate region 51, 52, 53 is associated with each person 31, 32, 33 based on the location information of each person to be measured, which is obtained by optically measuring the contour shape of each person to be measured using a LiDAR scanner. However, in the sixth embodiment of the biometric information processing device 100, each person to be measured is wearing an RFID (Radio Frequency Identification) tag, and each candidate region 51, 52, 53 is associated with each person 31, 32, 33 based on the location information indicating the detection location of the RFID tag. Furthermore, in this embodiment, before the processing of the flowchart shown in Figure 4 begins, information indicating that the target for acquiring biometric information is the person 31, 32, 33 to be measured, and the ID information of the RFID tag of each person to be measured are stored in the storage unit 113 in advance. Alternatively, this information may be specified by the user of the biometric information processing device 100 before the processing of this flowchart begins.

[0060] Figure 10A shows an example of the use of the biometric information processing device 100 in this embodiment. As shown in Figure 10A, an RFID tag detection device 210 is placed in room 10. The people to be measured 31, 32, and 33 are each wearing RFID tags 251, 252, and 253, which have different ID information (in the figure, "ID:A", "ID:B", and "ID:C"). The detection device 210 detects the RFID tags 251, 252, and 253 and outputs the information of each tag and location information indicating the detection location to the biometric information processing device 100. The transmitting and receiving unit 111 acquires the RFID tag information and location information indicating the detection location of each person to be measured detected by the detection device 210.

[0061] In this embodiment, in step S306, the transmitting / receiving unit 111 acquires information on the RFID tags 251, 252, and 253 of the persons 31, 32, and 33 to be measured, as well as location information indicating the detection location, as detected by the detection device 210. Figure 10B shows an example of the information on the RFID tags 251, 252, and 253 of the persons 31, 32, and 33 to be measured, and location information indicating the detection location, which the transmitting / receiving unit 111 receives from the detection device 210 in this embodiment. As shown in Figure 10B, the detection device 210 outputs the ID information of the RFID tags 251, 252, and 253 of the persons 31, 32, and 33 to be measured, and the detection locations 261, 262, and 263 as location information.

[0062] Then, in step S310, the biometric information association unit 126, based on the comparison of the information of the RFID tags 251, 252, and 253 of the persons to be measured 31, 32, and 33 acquired in step S306 with the ID information of the RFID tags of the persons to be measured 31, 32, and 33 stored in the storage unit 113, determines that the persons to be measured 31, 32, and 33 are located at the detection positions 261, 262, and 263 of the RFID tags 251, 252, and 253, respectively, and associates the biometric information obtained from the candidate regions 51, 52, and 53 corresponding to the detection positions 261, 262, and 263 with the persons to be measured 31, 32, and 33, respectively.

[0063] Therefore, according to this embodiment, based on the ID information of the tag and location information indicating the detection location obtained by detecting the RFID tag worn by the person being measured, it is possible to accurately associate the biometric information obtained from multiple people being measured using a non-contact biometric information acquisition means such as radar with each person being measured.

[0064] <Other> The embodiments described above are merely illustrative examples of the configuration of the present invention. The present invention is not limited to the specific forms described above, and various modifications are possible within the scope of its technical idea. Modifications of the above embodiments will be described below. In the following description, the same reference numerals will be used for components and processes similar to those in the above embodiments, and detailed explanations will be omitted. Furthermore, the above embodiments and the modifications described below can be combined as appropriate.

[0065] (Variation 1) The following describes the biometric information processing device 100 according to Modification 1. In this modification, as shown in Figure 11A, a bed 200 equipped with pressure measuring elements is used instead of the bed 20. As shown in Figure 11B, the bed 200 is constructed by stacking a group of pressure measuring elements 202 and a mattress 201 on a base 203. The group of pressure measuring elements 202 is constructed by arranging the pressure measuring elements in a grid pattern on a plane, thereby transmitting signals indicating the positions of the people 31, 32, and 33 whose biometric information is being measured on the bed 200, as well as the positions of each pressure measuring element and the magnitude of the pressure, to the transmitting / receiving unit 111 of the biometric information processing device 100. Therefore, the receiving unit 122 can receive signals indicating the pressure applied to different positions by multiple people who are being measured. In addition, in this modification, a LiDAR scanner 250 is placed in the room 10. The LiDAR scanner 250 corresponds to the LiDAR scanner 150 of the first embodiment, and a detailed explanation is omitted here.

[0066] Furthermore, in this embodiment, before the processing of the flowchart shown in Figure 4 begins, information indicating that the subjects from which biological information is to be acquired are the measurement subjects 31, 32, and 33, and information regarding the characteristics of the biological information of each measurement subject obtained from the LiDAR scanner 250 (for example, the characteristics of the body contour shape of each measurement subject) are pre-stored in the storage unit 113. Alternatively, this information may be specified by the user of the biological information processing device 100 before the processing of this flowchart begins.

[0067] Figure 12A shows an example of the processing flow executed by the control unit 112 in this modified example. In step S1201, the receiving unit 122 receives the output signals of the position and pressure of each pressure measuring element from the pressure measuring element group 202. Next, in step S1202, the transmitting and receiving unit 111 acquires the position information of the people 31, 32, and 33 being measured by the LiDAR scanner 250.

[0068] Next, in step S1203, the information generation unit 124 generates information regarding the spatial distribution of pressure indicated by the pressure signal received by the receiving unit 122, based on the output signal of the pressure measuring element group 202. Then, in step S1204, the information generation unit 124 identifies candidate regions of the person to be measured based on the output signal of the pressure measuring element group 202. Figure 12B shows an example of candidate regions identified by the information generation unit 124 in this modified example. As shown in Figure 12B, candidate regions 271, 272, and 273 are identified within the XY Cartesian coordinate system that defines the plane on which the pressure measuring element group 202 is arranged. Here, candidate regions 271, 272, and 273 correspond to the people 31, 32, and 33 to be measured.

[0069] Next, in step S1205, the information generation unit 124 in step S1204 For each of the identified candidate regions 271, 272, and 273, biological information indicating a respiratory waveform is generated from the time-dependent changes in amplitude or phase using the output signals of the pressure measurement element group 202.

[0070] Then, in step S310, the biometric information association unit 126 associates the biometric information of the people 31, 32, and 33, based on the similarity between the features of the body contour shape of the people 31, 32, and 33, indicated by the positional information of the people 31, 32, and 33 measured by the LiDAR scanner 250 acquired in step S306, and the features of the body contour shape of the people 31, 32, and 33 stored in the memory unit 113. For example, the biometric information association unit 126 determines that the point cloud 201 is the contour shape of person 31 based on the contour shape features (size: medium) indicated by the point cloud 201, and associates the biometric information obtained from the candidate region 51 corresponding to the position of the point cloud 201 with person 31. Similarly, the biometric information association unit 126 associates the biometric information obtained from the candidate regions 52 and 53 with people 32 and 33, respectively.

[0071] According to this modified version, biological information can be acquired non-contactually from pressure measuring elements, etc., and the biological information obtained for multiple individuals being measured can be accurately correlated with each individual being measured.

[0072] (Modification 2) Next, a biometric information processing device 100 according to Modification 2 will be described. In the above embodiment, for example, if the position or posture of the person being measured is not suitable for acquiring biometric information, such as when the person being measured is bending their waist or back, or if the candidate area cannot be properly identified because the reflector is not properly attached, then inappropriate situations may occur when identifying the correspondence between the person being measured and the biometric information. In this modification, however, the user can be notified of an error when such an inappropriate situation occurs.

[0073] Figure 13 shows an example of the processing flow executed by the control unit 112 in this modified example. In this processing flow, the processing in steps S301 to S310 is the same as described above, so a detailed explanation is omitted. In step S1301, the control unit 112 determines whether or not there is a possibility that the process of identifying candidate regions of the person to be measured and the process of generating biometric information cannot be executed normally, based on the spatial distribution information generated in step S307, and determines whether or not an error has occurred.

[0074] For example, in the first embodiment, if the shape of any of the point clouds 201 to 203 acquired from the LiDAR scanner 150 is abnormal, the control unit 112 determines that an error has occurred, on the grounds that the posture of the person being measured may be inappropriate and therefore the above process may not be executed correctly. Also, for example, in the second embodiment, if the shape of any of the pressure distribution regions 211 to 213 acquired from the body pressure sensor 160 is abnormal, the control unit 112 determines that an error has occurred, on the grounds that the posture of the person being measured may be inappropriate and therefore the above process may not be executed correctly. Also, for example, in the fifth embodiment, if the array microphone 190 cannot recognize the sound emitted by the person being measured, the control unit 112 determines that an error has occurred, on the grounds that the above process may not be executed correctly. The criteria for determining whether the shape of the point clouds or regions, or speech recognition, is abnormal may be appropriately determined depending on the type of biometric information generated.

[0075] If the control unit 112 determines that an error has occurred (S1301: YES), it proceeds to step S1302; if it determines that no error has occurred (S1302: NO), it proceeds to step S308. In step S1302, the control unit 112 functions as a notification unit and generates information indicating the determination result of S1301 and information indicating a solution to resolve the error, and outputs it to the user, for example, the display device 300, from the output unit 114. Information indicating a solution to resolve the error may include adjusting the position of the LiDAR scanner 150. Examples include information that encourages the subject to take action, information that prompts the subject to return to the correct posture, and information that prompts the subject to attempt voice recognition with the array microphone 190.

[0076] According to this modified version, by notifying of any abnormalities that may hinder the acquisition of biometric information from the person being measured, such possibilities can be suppressed, while the biometric information obtained from multiple people being measured using non-contact biometric information acquisition means such as radar can be accurately correlated with each person being measured.

[0077] Furthermore, as another modification, in the above embodiment, it is assumed that the transmitting / receiving unit 111 transmits and receives radio waves with the person whose biological information is being measured. Instead, the transmitting / receiving unit 111 may transmit and receive ultrasound, sound waves, light of any wavelength, etc., with the person whose biological information is being measured. In the case where ultrasound or sound waves are transmitted and received with the person whose biological information is being measured, in the above embodiment, the control unit 112 does not perform a process to calculate the distance using the signals transmitted and received by the transmitting / receiving unit 111, but rather performs a process to calculate the direction of arrival of the signals transmitted and received by the transmitting / receiving unit 111, thereby performing the association between the person whose biological information is being measured.

[0078] In another modification, the biometric information processing device 100 may receive input from the user regarding the position (sleeping area, etc.) of the person(s) to be measured on the bed 20 (e.g., sleeping area) as position information indicating the space occupied by the person(s) to be measured at the time of measurement. Based on the received position information, the device may use the correspondence between candidate regions 251, 252, 253 and the generated biometric information, along with the characteristic information of the person(s) to be measured stored in the memory unit 113, to associate the person(s) to be measured with their biometric information. Alternatively, switches for each subject may be installed in the room 10 to notify the biometric information processing device 100 of the person(s) to be measured entering the room, and the transmitting / receiving unit 111 may receive information regarding the on / off status of the switches. Alternatively, the transmitting / receiving unit 111 may communicate with an information terminal carried by the person(s) to be measured and receive information from the information terminal. In the above embodiment, candidate regions corresponding to the person(s) to be measured may be identified based on the received information. Furthermore, the biometric information processing device 100 may accept information identifying the person to be measured in room 10 as pre-measurement information from the user or obtain it from an external source. This is expected to improve the accuracy of associating the person to be measured with their biometric information.

[0079] Furthermore, in the above embodiment, the signal summing unit 123 performs signal summing by adding together the IF signals obtained from the difference between the chirp signal transmitted by the transmitting unit 121 and the signal received by the receiving unit 122, and the information generation unit 123 performs signal processing on the added signals to generate biological information. However, the signal summing by the signal summing unit 123 may be omitted, and the information generation unit 124 may generate biological information by performing signal processing on the IF signals obtained from the difference between the chirp signal transmitted by the transmitting unit 121 and the signal received by the receiving unit 122.

[0080] (Variation 3) The following describes the biometric information processing device 100 according to Modification 3. In this modification, as an example, similar to the first embodiment shown in Figure 1, the biometric information processing device 100, LiDAR scanner 150, and bed 20 are arranged in a room 10, and multiple people 31, 32, and 33, who are the subjects of biometric information measurement, lie on the bed 20, and the biometric information processing device acquires biometric information regarding the breathing of each subject during sleep.

[0081] Figure 14 is a flowchart showing an example of the processing flow of the bio-information processing device 100. The processing in steps S301 to S306 is the same as in the first embodiment. More specifically, in step S304, the information generation unit 124 performs a Fourier transform on the received signal obtained by the FMCW method and decomposes it into complex number signals for each distance bin. Also, in step S305, the information generation unit 124 uses direction estimation by a phased array radar to determine the direction of the received signal. The complex number signal is decomposed into a bin-by-bin complex number signal. Then, through the processing in steps S304 and S305, complex number signal data (referred to as "Bscope") decomposed into two dimensions of distance × direction is generated. Then, in step S306, similar to the first embodiment, the transmitting and receiving unit 111 acquires the position information of the people 31, 32, and 33 being measured by the LiDAR scanner 150.

[0082] In step S1101, the control unit 112 determines whether or not it has acquired information identifying the number of people to be measured in room 10. In this modified example, the control unit 112 acquires this information by receiving input from the user via an input unit (not shown) of the biometric information processing device 100, or by the transmitting / receiving unit 111 receiving it through communication with an external source. Alternatively, this information may be stored in the storage unit 113 before the start of processing in this flowchart, and the control unit 112 may acquire the information stored in the storage unit 113. If the control unit 112 has acquired information identifying the number of people to be measured (S1101: YES), it proceeds to step S1103; otherwise, it proceeds to step S1102.

[0083] In step S1102, the information generation unit 124 uses complex signal data (Bscope) from multiple frames to detect the position of a person in room 10, thereby determining the distance and orientation of the person to be measured for which breathing extraction will be performed. As an estimation unit, the information generation unit 124, in the process of detecting the position of the person to be measured, compares the change in the time difference of the signal for each bin and estimates the number and position of the person to be measured using machine learning. Here, the orientation bin and / or distance bin correspond to an example of an arrival orientation and / or distance of a predetermined unit, but the predetermined unit may be one bin or may span multiple bins.

[0084] Next, in step S1103, the information generation unit 124 uses the signals added in step S302 to generate biological information indicating a respiratory waveform from the time-dependent changes in amplitude or phase.

[0085] Next, in step S1104, the information generation unit 124, acting as a classification unit, classifies the biometric information generated in step 1103 based on the information identifying the number of people to be measured, which was determined to have been acquired in step S1101, or based on the information regarding the number and location of people to be measured, which was estimated in step S1102.

[0086] Here, we will explain an example of the classification of biometric information in this modified example. Suppose the respiratory rates of three individuals 31, 32, and 33 in room 10 are 15 RR / min, 20 RR / min, and 10 RR / min, respectively. If the number of individuals to be measured estimated in step S1101 is estimated to be three, the information generation unit 124 classifies the biometric information generated in step 1102 into three biometric information based on the difference in respiratory rates. However, in the estimation process in step S1101, the estimated number of individuals to be measured may not match the number of individuals to be measured in room 10 due to reasons such as failure to detect individuals or false detections. In this case, for example, biometric information that should be classified as having a respiratory rate of 15 RR / min may be included in biometric information classified as having a respiratory rate of 10 RR / min or 20 RR / min, or biometric information that should be classified as having a respiratory rate of 20 RR / min may be split and classified as biometric information of multiple individuals. As a result, it may not be possible to correctly associate the individuals to be measured with their biometric information.

[0087] Therefore, in this modified example, the control unit 112, acting as an acquisition unit, acquires information that identifies the number of people to be measured in the room 10. Then, when the information generation unit 124 acquires information that identifies the number of people to be measured, it performs the estimation process in step S1102. Instead of using estimated information about the number and location of the measured individuals, biometric data is classified using the number indicated by that information. This allows for the classification of biometric data using more accurate information than the number of measured individuals identified by inference.

[0088] Then, in step S1105, the biometric information association unit 126 associates the biometric information generated by the information generation unit 124 with each person being measured. Specifically, the biometric information association unit 126 associates the biometric information classified in step S1104 with the biometric information classified in step S1104, based on the similarity between the characteristics of the body contour shape of the people being measured, as indicated by the location information of the people being measured, 31, 32, and 33, which was acquired in step S306 by the LiDAR scanner 150, and the characteristics of the body contour shape of the people being measured, 31, 32, and 33, which are stored in the memory unit 113.

[0089] According to the modified biometric information processing device 100, by acquiring information on the number of people being measured who are present in room 10, it is expected that the accuracy of associating biometric information with each person being measured will be improved.

[0090] <Note 1> A biological information processing device, A signal receiving unit (111) that receives signals relating to biometric information reflected from at least one person being measured, A candidate region identification unit (125) calculates the direction of arrival of the received signal and / or the distance to the person to be measured, and identifies a candidate region of the person to be measured using the calculated direction of arrival and / or the distance, An information generation unit (124) generates biological information corresponding to the candidate region of the person to be measured from the received signal, A location information acquisition unit (111) acquires the location information of the person to be measured, Based on the acquired location information, a biometric information association unit (126) associates the person being measured with the generated biometric information, A biological information processing device characterized by having the following features.

[0091] <Note 2> A biological information processing device, A signal receiving unit (111) that receives signals related to biometric information reflected from multiple individuals, A candidate region identification unit (125) calculates the direction of arrival of the received signal and / or the distance to at least one of the multiple persons to be measured from the received signal, and identifies a candidate region of the person to be measured using the calculated direction of arrival and / or the distance, An information generation unit (124) generates biological information corresponding to the candidate region of the person to be measured from the received signal, A location information acquisition unit (111) acquires the location information of the person to be measured, Based on the acquired location information, a biometric information association unit (126) associates the person being measured with the generated biometric information, A biological information processing device characterized by having the following features.

[0092] <Note 3> A biological information processing device, A signal receiving unit (111) that receives signals indicating pressure applied at different locations by at least one person being measured, A candidate region identification unit (125) identifies a candidate region of the person to be measured based on the pressure distribution obtained from the received signal, From the received signal, biometric information corresponding to the candidate region of the person being measured is generated. The information generation unit (124) and A location information acquisition unit (111) acquires the location information of the person to be measured, Based on the acquired location information, a biometric information association unit (126) associates the person being measured with the generated biometric information, A biological information processing device characterized by having the following features.

[0093] <Note 4> A method for processing biological information performed by a biological information processing device, A signal reception step (S301) is performed, which involves receiving a signal relating to biometric information reflected from at least one person who is the subject of measurement. A candidate region identification step (S308) involves calculating the direction of arrival of the received signal and / or the distance to the person to be measured, and using the calculated direction of arrival and / or the distance to identify a candidate region of the person to be measured, An information generation step (S309) is performed to generate biological information corresponding to the candidate region of the person to be measured from the received signal, A location information acquisition step (S306) is performed to acquire the location information of the person to be measured, Based on the acquired location information, a biometric information association step (S310) is performed to associate the person to be measured with the generated biometric information, A method for processing biological information, characterized by including the following:

[0094] <Note 5> A method for processing biological information performed by a biological information processing device, A signal reception step (S301) in which signals relating to biometric information reflected from multiple individuals, A candidate region identification step (S308) involves calculating the direction of arrival of the received signal and / or the distance to at least one of the multiple persons to be measured, and using the calculated direction of arrival and / or distance to identify a candidate region of the person to be measured, An information generation step (S309) is performed to generate biological information corresponding to the candidate region of the person to be measured from the received signal, A location information acquisition step (S306) is performed to acquire the location information of the person to be measured, Based on the acquired location information, a biometric information association step (S310) is performed to associate the person to be measured with the generated biometric information, A method for processing biological information, characterized by having the following features.

[0095] <Note 6> A method for processing biological information performed by a biological information processing device, A signal reception step (S301) is performed, which involves receiving a signal relating to biometric information reflected from at least one person who is the subject of measurement. Estimation step (S1101): Based on the received signal, estimation is performed by machine learning to estimate the number of people to be measured for each predetermined unit of the direction of arrival of the signal and / or the distance to the person to be measured. An information generation step (S1102) is performed to generate biometric information of the person to be measured from the received signal, A classification step (S1103) is performed to classify the generated biometric information of the individuals to be measured based on the estimated number of individuals to be measured, A location information acquisition step (S306) is performed to acquire the location information of the person to be measured, Based on the acquired location information, a biometric information association step (S1104) is performed to associate the person to be measured with the classified biometric information, Includes, The classification step, when information regarding the number of individuals to be measured is obtained, classifies the generated biometric information of the individuals to be measured based on the obtained information, instead of the estimated number of individuals to be measured. A method for processing biological information characterized by the following features.

[0096] <Note 7> A method for processing biological information performed by a biological information processing device, A signal reception step (S301) is performed, which involves receiving a signal relating to biometric information reflected from at least one person who is the subject of measurement. An information generation step (S1102) is performed to generate biometric information of the person to be measured from the received signal, The acquisition step (S1103) involves obtaining information regarding the number of persons being measured, A classification step (S1103) is performed to classify the generated biometric information of the individuals to be measured based on the acquired information regarding the number of individuals to be measured, A location information acquisition step (S306) is performed to acquire the location information of the person to be measured, Based on the acquired location information, a biometric information association step (S1104) is performed to associate the person to be measured with the classified biometric information, including A method for processing biological information characterized by the following features.

[0097] <Note 8> A biological information processing device, A signal receiving unit (111) that receives signals relating to biometric information reflected from at least one person being measured, An estimation unit (124) estimates the number of people to be measured by machine learning for each predetermined unit of arrival direction and / or distance from the received signal, based on the direction of arrival of the signal and / or the distance to the person to be measured. An information generation unit (124) generates biological information of the person being measured from the received signal, A classification unit (124) that classifies the generated biometric information of the individuals to be measured based on the estimated number of individuals to be measured, A location information acquisition unit (111) acquires the location information of the person to be measured, Based on the acquired location information, a biometric information association unit (126) associates the person being measured with the classified biometric information, It has, When the classification unit obtains information regarding the number of individuals to be measured, it classifies the generated biometric information of the individuals to be measured based on the obtained information, instead of using the estimated number of individuals to be measured. A biological information processing device characterized by the following:

[0098] <Note 9> A biological information processing device, A signal receiving unit (111) that receives signals relating to biometric information reflected from at least one person being measured, An information generation unit (124) generates biological information of the person being measured from the received signal, An acquisition unit (112) that acquires information regarding the number of people being measured, A classification unit (124) classifies the generated biometric information of the individuals to be measured based on the acquired information regarding the number of individuals to be measured, A location information acquisition unit (111) acquires the location information of the person to be measured, Based on the acquired location information, a biometric information association unit (126) associates the person being measured with the classified biometric information, has A biological information processing device characterized by the following: [Explanation of symbols]

[0099] 100 Biological information processing device, 111 Transmit / receive unit, 112 Control unit, 124 Information generation unit, 125 Candidate region identification unit, 126 Biological information association unit

Claims

1. A biological information processing device, A signal receiving unit that receives signals relating to biological information reflected from at least one person being measured, A candidate region identification unit calculates the direction of arrival of the received signal and / or the distance to the person to be measured from the received signal, and identifies a candidate region of the person to be measured using the calculated direction of arrival and / or the distance, An information generation unit generates biological information corresponding to the candidate region of the person to be measured from the received signal, A location information acquisition unit that acquires the location information of the person to be measured, A biometric information association unit that associates the person being measured with the generated biometric information based on the acquired location information, It has, The positional information of the person being measured is obtained by optically measuring the contour shape of the person being measured. The biometric information association unit identifies and associates a person being measured based on the degree of similarity between the characteristic information relating to the contour shape indicated by the acquired location information and the characteristic information relating to the contour shape of each person being measured that has been stored in advance. A biological information processing device characterized by the following:

2. The biological information processing device according to claim 1, characterized in that the characteristic information is the size of the object to be measured indicated by the position information.

3. The biological information processing device according to Claim 1, characterized in that the position information is a point cloud measured by a LiDAR scanner.

4. The bio-information processing device according to claim 1, characterized in that the contour shape is the contour shape of the body of the person being measured.

5. A method for processing biological information performed by a biological information processing device, Receive signals related to biometric information reflected from at least one person being measured. Signal reception step, A candidate region identification step involves calculating the direction of arrival of the received signal and / or the distance to the person to be measured, and using the calculated direction of arrival and distance to identify a candidate region of the person to be measured. An information generation step of generating biometric information corresponding to the candidate region of the person to be measured from the received signal, A location information acquisition step to acquire the location information of the person to be measured, The process includes a biometric information association step of associating the person to be measured with the generated biometric information based on the acquired location information, The positional information of the person being measured is obtained by optically measuring the contour shape of the person being measured. In the biometric information association step, the person to be measured is identified and associated based on the degree of similarity between the contour shape characteristics indicated by the acquired location information and the contour shape characteristics of each person to be measured that have been stored in advance. A method for processing biological information characterized by the following features.

6. A program for causing a computer to perform each step of the biological information processing method described in claim 5.

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