Processing device, processing method, and program

Abstract

Time series data of a vital sign index is calculated for each person. A processing device is provided with: a signal acquisition unit that acquires a vital sign signal from a signal reflected by at least one person within a measurement range; an index calculation unit that calculates a vital sign index indicating a vital sign state of at least one person on the basis of the vital sign signal; a body movement determination unit that determines the presence or absence of a body movement of the person within the measurement range; a number-of-people estimation unit that estimates the number of people within the measurement range; a number-of-people change determination unit that determines whether or not there is a possibility of a change in the estimated number of people when it is determined that there is a physical activity of the person within the measurement range; and a calculation unit that calculates time-series data of a vital sign index for each person, and calculates the vital sign index for each person if it is determined that there is a possibility of a change in the estimated number of persons. The calculation unit separately calculates the time-series data of the vital signs before it is determined that there is a likelihood of a change in the number of people estimated, and the time-series data of the vital signs after it is determined that there is a likelihood of a change in the number of people estimated.

Description

TECHNICAL FIELD

[0001] The present application relates to a processing device, a processing method, and a program. BACKGROUND

[0002] For example, in Patent Literature 1, a technique is proposed in which a signal element is separated from a phase signal obtained from a radar signal, a vital sign signal set as an object is recognized from a time-dependent feature such as repetitiveness, frequency characteristics, or the like of the separated signal element, and a vital sign index is calculated.

[0003] PRIOR ART DOCUMENTS

[0004] PATENT LITERATURE

[0005] Patent Literature 1: International Publication No. 2021 / 171091 SUMMARY

[0006] PROBLEMS TO BE SOLVED BY THE INVENTION

[0007] The time series data of the vital sign index is operated by acquiring the vital sign index along the time series. In a case where the number of persons of the subject of measurement is unknown or indefinite, it is possible to detect a vital sign signal, a vital sign index in a quantity of a plurality of persons. In a case where the vital sign index is acquired along the time series, the number of acquisitions of the vital sign index can vary depending on the time. For example, sometimes the number of acquisitions of the vital sign index at a first time is different from the number of acquisitions of the vital sign index at a second time. It is considered that the reason why the number of acquisitions of the vital sign index varies is a case where the number of persons of the subject actually varies. In the existing method, since the vital sign index is operated without considering that the number of persons of the subject can vary, it is difficult to operate the time series data of the vital sign index for each person. The present application is completed in view of the above actual situation, and an object thereof is to provide a technique capable of operating the time series data of the vital sign index for each person.

[0008] TECHNICAL SOLUTION FOR SOLVING THE PROBLEM

[0009] A processing device according to one aspect of the present invention comprises: a signal acquisition unit for acquiring a vital sign signal from a signal reflected by at least one person within a measurement range; an index calculation unit for calculating a vital sign index representing the vital sign status of the at least one person based on the vital sign signal; a body activity determination unit for determining whether there is body activity of the person within the measurement range; a number of people estimation unit for estimating the number of people within the measurement range; a number of people change determination unit for determining whether there is a possibility of a change in the estimated number of people when it is determined that there is body activity of the person within the measurement range; and a calculation unit for calculating time series data of the vital sign index for each person, and when it is determined that there is a possibility of a change in the estimated number of people, the calculation unit separately calculates the time series data of the vital sign index before the determination that there is a possibility of a change in the estimated number of people and the time series data of the vital sign index after the determination that there is a possibility of a change in the estimated number of people.

[0010] The processing device calculates time series data of vital sign indicators for each person. If there is a possibility of a change in the number of people within the measurement range, the time series data of the vital sign indicators before the determination of the possibility of a change in the number of people is calculated separately from the time series data of the vital sign indicators after the determination of the possibility of a change in the number of people is calculated. Thus, for each person, the time series data of the vital sign indicators for the number of people before the change in the number of people is calculated separately from the time series data of the vital sign indicators for the number of people after the change in the number of people is calculated separately.

[0011] In the processing device according to one aspect of the present invention, the physical activity determination unit may calculate the physical activity time of the person within the measurement range, and the number of people change determination unit may determine whether there is a possibility of a change in the estimated number of people based on the physical activity time of the person. For example, if the physical activity time of the person is short, there is no possibility of a change in the estimated number of people, and if the physical activity time of the person is long, there is a possibility of a change in the estimated number of people. According to the processing device, by determining whether there is a possibility of a change in the estimated number of people based on the physical activity time of the person, it is possible to simply determine whether there is a possibility of a change in the estimated number of people.

[0012] In the processing device according to one aspect of the present application, the index calculation section can calculate the vital sign index for each of a plurality of periods, the number estimation section can estimate the number of the person in the measurement range in each of the plurality of periods, the physical activity determination section can determine whether or not the physical activity of the person in the measurement range is present in each of the plurality of periods, and the operation section can operate the time series data of the vital sign index for each of the persons, except for a period in which the vital sign index for which the estimated number of the person is not calculated is present in a period in which the physical activity of the person in the measurement range is determined not to be present in the plurality of periods. The time series data of the vital sign index for the period in which the vital sign index for which the estimated number of the person is not calculated is present can be data of which reliability is low. According to the processing device, the time series data of the vital sign index for each of the persons is operated, except for the period in which the vital sign index for which the estimated number of the person is not calculated is present, and thus it is possible to improve the reliability of the time series data of the vital sign index.

[0013] The processing device according to one aspect of the present application can include a position information calculation section that determines the position of the person in the measurement range and calculates position information of the person associated with the vital sign index for each of the persons, the index calculation section can calculate the vital sign index for each of a plurality of periods, the position information calculation section can calculate the position information for each of the plurality of periods, and the operation section can correlate the vital sign index with each of the persons based on the position information for each of the plurality of periods, thereby determining a combination of the vital sign index for each of the persons, and operate the time series data of the vital sign index for each of the persons based on the combination of the vital sign index. Thus, it is possible to operate the time series data of the vital sign index for each of the persons.

[0014] In the processing device according to one aspect of the present application, the index calculation section can calculate the vital sign index for each of a plurality of periods, and the operation section can correlate the vital sign index with each of the persons based on the value of the vital sign index for each of the plurality of periods, thereby determining a combination of the vital sign index for each of the persons, and operate the time series data of the vital sign index for each of the persons based on the combination of the vital sign index. Thus, it is possible to operate the time series data of the vital sign index for each of the persons.

[0015] The processing device according to one aspect of the present application can also be a processing device including an index output section that outputs the time series data of the vital sign index for each of the persons, and in a case where it is determined that there is a possibility of a change in the estimated number of persons, the index output section separately outputs the time series data of the vital sign index before it is determined that there is a possibility of a change in the estimated number of persons and the time series data of the vital sign index after it is determined that there is a possibility of a change in the estimated number of persons. Thus, it is possible to separately output the time series data of the vital sign index for the amount of persons before a change in the number of persons and the time series data of the vital sign index for the amount of persons after a change in the number of persons for each of the persons.

[0016] In the processing device according to one aspect of the present application, the signal acquisition section can perform processing of clustering groups of vital sign waveforms acquired on the basis of the vital sign signals into a plurality of clusters on the basis of a feature quantity calculated from the vital sign signals, and the number of persons estimation section can estimate the number of persons of the persons in the measurement range on the basis of the number of clusters of the groups of vital sign waveforms after clustering. In the processing device according to one aspect of the present application, the physical activity determination section can determine the presence or absence of the physical activity of the persons in the measurement range in each of the plurality of periods, the number of persons estimation section can estimate the number of persons of the persons in the measurement range in each of the plurality of periods, and for a period in which it is determined that there is no physical activity of the persons in the measurement range in consecutive periods of the plurality of periods, the maximum value of the number of clusters can be estimated as the number of persons of the persons in the measurement range. A period in which it is determined that there is no physical activity of the persons in the measurement range in consecutive periods of the plurality of periods can be estimated as a period in which there is no change in the number of persons, and thus the maximum value of the number of clusters can be estimated as the number of persons of the persons in the measurement range.

[0017] The processing device according to one aspect of the present application can also include an abnormality detection unit that detects a vital sign abnormality of the at least one person in the measurement range based on the estimated number of persons and the number of clusters. In the processing device according to one aspect of the present application, the physical activity determination unit determines whether the physical activity of the person in the measurement range is present or absent in each of the plurality of periods, the number of persons estimation unit estimates the number of persons in the measurement range in each of the plurality of periods, and for a period in which the physical activity of the person in the measurement range is determined to be absent in consecutive periods of the plurality of periods, the maximum value of the number of clusters is estimated as the number of persons in the measurement range, and the abnormality detection unit determines a period in which the number of clusters is smaller than the maximum value as a period in which the vital sign abnormality of the person occurs. Thus, the user can grasp the vital sign abnormality of the person in the measurement range and the period in which the vital sign abnormality occurs.

[0018] The processing device according to one aspect of the present application can also include an abnormality detection unit that detects a vital sign abnormality of the at least one person in the measurement range, a physical activity determination unit that determines whether the physical activity of the person in the measurement range is present or absent in each of the plurality of periods, and a number of persons estimation unit that estimates the number of persons in the measurement range in each of the plurality of periods, and for a period in which the physical activity of the person in the measurement range is determined to be absent in consecutive periods of the plurality of periods, the maximum value of the number of clusters is estimated as the number of persons in the measurement range, and the abnormality detection unit determines whether the vital sign abnormality of the at least one person in the measurement range occurs based on the vital sign signal in the immediately preceding period of the period in which the physical activity of the person in the measurement range is determined to be absent and the period in which the number of clusters is smaller than the maximum value. Thus, the user can grasp the vital sign abnormality of the person in the measurement range.

[0019] Further, the present application can also be understood as a processing method including at least a part of the above processing, a program for causing a computer to execute at least a part of the above processing, or a computer-readable recording medium in which such a program is non-transitorily recorded. The above structures and processing can be combined with each other as long as no technical contradiction arises.

[0020] Effects of Invention

[0021] According to the present application, the time series data of the vital sign index can be calculated for each person.BRIEF DESCRIPTION OF DRAWINGS BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 is a diagram schematically showing a configuration example of the processing device.

[0023] Figure 2 is a diagram showing a schematic configuration of the processing device.

[0024] Figure 3 is a block diagram showing an example of the processing device.

[0025] Figure 4 is a block diagram showing a configuration of a function of the signal acquisition section.

[0026] Figure 5 is a flowchart showing one example of a processing flow of the processing device.

[0027] Figure 6 (A) of FIG. 8 is an explanatory diagram of coordinates of representative waveforms of the clustered respiratory waveform groups, Figure 6 (B) of FIG. 8 is a diagram showing one example of the representative waveforms of the clustered respiratory waveform groups.

[0028] Figure 7 is an explanatory diagram of a processing of estimating the number of persons in the measurement range.

[0029] Figure 8 is an explanatory diagram of one example of excluding data of low reliability from time series data of vital sign indexes.

[0030] Figure 9 is an explanatory diagram of one example of a processing of outputting time series data of respiratory indexes for each person in the measurement range.

[0031] Figure 10 is an explanatory diagram of one example of a processing of outputting time series data of respiratory indexes for each person in the measurement range.

[0032] Figure 11 is a flowchart showing one example of a processing flow of determining whether or not there is a physical activity of a person in the measurement range.

[0033] Figure 12 (A) of FIG. 10 is a diagram showing an amplitude intensity of a received signal from which a stationary component is removed when a person is in a state of rest. Figure 12 (B) of FIG. 10 is a diagram showing an amplitude intensity of a received signal from which a stationary component is removed when a physical activity of a person occurs.

[0034] Figure 13 is a flowchart showing one example of a processing flow of determining a possibility of a change in the estimated number of persons.

[0035] Figure 14 (A)~ Figure 14 (C) is an explanatory diagram of the process of determining the change in the number of people.

[0036] Figure 15 (A)~ Figure 15 (C) is a graph showing the signal strength of the received signal from which the stationary object component has been removed.

[0037] Figure 16 (A)~ Figure 16 (D) is a graph showing the clustering result. DETAILED DESCRIPTION

[0038] The following description will provide examples and embodiments of the present invention with reference to the accompanying drawings. The following application examples and embodiments are one aspect of the present invention and do not limit the scope of the present invention.

[0039] Application Examples

[0040] Figure 1 Schematically shows an example of use of the processing device 100 to which the present invention is applied. Figure 1 In the illustrated example, three people 31, 32, and 33, serving as measurement targets, are arranged on a bed 20 in a room 10. A processing device 100 is also located in the room 10. Processing device 100 transmits signals to the measurement targets 31, 32, and 33 on the bed 20, performing so-called contactless sensing. The frequencies of the signals transmitted to the measurement targets 31, 32, and 33 include those in the 30 GHz to 300 GHz band used by millimeter-wave radars, but frequencies in other frequency bands, such as those of light, radio waves, sound waves, and ultrasonic waves, may also be used.

[0041] Figure 2 1 is a diagram showing an example of the structure of the processing device 100. The processing device 100 includes a transceiver 111, a control device 112, a storage device 113, and an output device 114. The transceiver 111 functions as a signal receiving unit that receives a signal reflected by at least one person within the measurement range. For example, the transceiver 111 performs a Figure 1 The measurement range of the processing device 100 is, for example, Figure 1The measurement range is not limited to the illustrated prescribed range. The control device 112 acquires a vital sign signal from a signal reflected by at least one person in the measurement range. In addition, the control device 112 calculates a vital sign index indicating a vital sign state of at least one person in the measurement range on the basis of the vital sign signal. The storage device 113 stores various data such as signal data received by the transceiving device 111, data used in processing performed by the control device 112, generated data, and the like. The output device 114 notifies a user or outputs data related to a processing result to an external device in accordance with a result of processing performed by the control device 112. Furthermore, the output device 114 can be configured to be able to output data related to a processing result to an external device by various communication methods such as wireless communication, wired communication, and the like.

[0042] The processing device 100 performs non-contact sensing of at least one person in the measurement range using a signal transceiving unit such as a radio wave radar, an ultrasonic sensor, or a sound wave sensor, and performs calculation of a vital sign index indicating a vital sign state of the person and estimation of the number of persons in the measurement range. The processing device 100 operates time series data of the vital sign index for each person, and in a case where there is a possibility of a change in the estimated number of persons, separately operates time series data of the vital sign index before a point in time at which it is determined that there is a possibility of a change in the estimated number of persons and time series data of the vital sign index after the point in time at which it is determined that there is a possibility of a change in the estimated number of persons. Thus, according to the processing device 100, it is possible to separately operate time series data of the vital sign index for the amount of the number of persons before a change in the number of persons and time series data of the vital sign index for the amount of the number of persons after the change in the number of persons for each person.

[0043] <Explanation of Embodiments>

[0044] One embodiment of the technology of the present disclosure will be described. In the present embodiment, as one example, as Figure 1 illustrated, a case is assumed in which the processing device 100 and the bed 20 are arranged in the room 10, and a plurality of persons 31, 32, 33 are lying on the bed 20, and the processing device 100 acquires a vital sign index of each person who is a measurement target. For example, the processing device 100 can also acquire a vital sign index at the time of sleep of each person. Furthermore, in this case, it is assumed that the acquired vital sign index is an index related to respiration of the person who is the measurement target (respiration index), but the acquired vital sign index can also be an index related to heartbeat (heartbeat index).

[0045] Figure 3 is a block diagram illustrating a configuration example of the processing device 100 according to one embodiment. As Figure 3As shown in the figure, in the processing device 100, the transceiving device 111 has a transmission section 121 that transmits a signal to a person in the measurement range, and a reception section 122 that receives a signal reflected by a person in the measurement range. The control device 112 has a signal acquisition section 131, an index calculation section 132, a physical activity determination section 133, a number of persons estimation section 134, a number of persons change determination section 135, a calculation section 136, an index output section 137, an abnormality detection section 138, and a position information calculation section 139.

[0046] The control device 112 includes a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), and the like, and performs control of each section in the processing device 100, various processing, and the like. The storage device 113 stores a program executed by the control device 112, various data used in processing performed by the control device 112, and the like. For example, the storage device 113 is a secondary storage device such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or the like. The storage device 113 can also be realized by a removable storage medium. The output device 114 outputs data generated by the control device 112 to the display device 300. Furthermore, data generated by the control device 112 can also be stored in the storage device 113 and output from the output device 114 to the display device 300 at an arbitrary timing. The output device 114 can be, for example, a communication interface realized by a communication device such as a network card.

[0047] In the present embodiment, the processing device 100 and the display device 300 are assumed to be separate devices, but the processing device 100 can also be integrally configured with the display device 300. Figure 3 The constituent elements of the processing device 100 shown in the figure are not all necessary, and addition or removal of the constituent elements of the processing device 100 can be appropriately performed. Furthermore, at least a part of the functions of the processing device 100 can be realized by a computer on a cloud, or can be a microcomputer such as a PLC (Programmable Logic Controller), a single-board computer, or the like.

[0048] The signal acquisition section 131 acquires a vital sign signal from a signal reflected by at least one person in the measurement range. The index calculation section 132 calculates a vital sign index indicating a vital sign state of at least one person in the measurement range on the basis of the vital sign signal. The physical activity determination section 133 determines whether or not there is physical activity of a person in the measurement range. The number estimation section 134 estimates the number of persons (the number of people) in the measurement range. The number change determination section 135 determines whether or not there is a possibility of a change in the estimated number of persons. That is, the number change determination section 135 determines whether or not there is a possibility of an increase or decrease in the number of persons in the measurement range. The operation section 136 operates time series data of the vital sign index for each person in the measurement range. In a case where it is determined that there is a possibility of a change in the estimated number of persons, the operation section 136 separately operates time series data of the vital sign index before the determination that there is a possibility of a change in the estimated number of persons and time series data of the vital sign index after the determination that there is a possibility of a change in the estimated number of persons. The index output section 137 outputs the time series data of the vital sign index for each person in the measurement range. The abnormality detection section 138 detects a vital sign abnormality of at least one person in the measurement range. The position information calculation section 139 determines the position of a person in the measurement range and calculates position information of the person associated with the vital sign index for each person.

[0049] The processing device 100 performs various processes in a prescribed time slot. Therefore, the signal acquisition section 131 acquires a vital sign signal in each of a plurality of periods. The index calculation section 132 calculates a vital sign index for each of the plurality of periods. The physical activity determination section 133 determines whether or not there is physical activity of a person in the measurement range in each of the plurality of periods. The number estimation section 134 estimates the number of persons in the measurement range in each of the plurality of periods. The number change determination section 135 determines whether or not there is a possibility of a change in the estimated number of persons in each of the plurality of periods. The abnormality detection section 138 detects a vital sign abnormality of at least one person in the measurement range in each of the plurality of periods. The position information calculation section 139 determines the position of a person in the measurement range and calculates position information of the person associated with the vital sign index for each person in each of the plurality of periods.

[0050] Figure 4is a block diagram showing the configuration of the function of the signal acquisition section 131. The function of the signal acquisition section 131 is constituted by the signal processing section 151 and the clustering section 152. The signal processing section 151 performs signal processing on the signal received by the reception section 122, and acquires a vital sign waveform group on the basis of a vital sign signal extracted from the signal received by the reception section 122. Here, the vital sign signal is, for example, a respiration signal, but can also be a heartbeat signal. In addition, the vital sign waveform group is, for example, a respiration waveform group, but can also be a heartbeat waveform group. The clustering section 152 performs processing of clustering the vital sign waveform group, and acquires the number of clusters of the vital sign waveform group after clustering, the representative waveform of each of the vital sign waveform groups, and the coordinates (position information) of the representative waveforms.

[0051] Figure 5 is a flowchart showing one example of the processing flow of the processing device 100. As one example, the processing flow of Figure 5 is instructed to the processing device 100, and thus the processing of Figure 5 is performed. In step S101, the transmission section 121 transmits a signal into the measurement range. For example, the transmission section 121 can also transmit a chirp signal. The frequency band, the up-chirp, the down-chirp, and the like of the chirp signal transmitted by the transmission section 121 can be appropriately set. Here, as one example, it is assumed that, in the FMCW (Frequency Modulated Continuous Wave) method, an array having a sampling period of the transceiver of about 100 μs and an antenna number of 8 ch is used. The reception section 122 receives a signal reflected by at least one person, a stationary object, or the like in the measurement range.

[0052] In step S102, the signal processing section 151 performs signal processing on an IF signal obtained by the difference between the chirp signal transmitted by the transmission section 121 and the signal received by the reception section 122, and calculates the distance from the transceiver device 111 (the processing device 100) to the position (the measurement position) at which the signal is reflected. Specifically, the signal processing section 151 calculates the distance from the transceiver device 111 to the measurement position on the basis of the different frequency spectra obtained by performing Fourier transform (FFT) after AD conversion of the IF signal.

[0053] In step S103, the signal processing section 151 performs signal processing on the IF signal, and calculates the azimuth (angle) of the measurement position with respect to the transceiver device 111 (the processing device 100). Specifically, the signal processing section 151 calculates the angle (arrival azimuth) on the basis of the phase difference of the received signals between the plurality of antennas of the reception section 122. In step S104, the body movement determination section 133 determines whether or not there is body movement of a person in the measurement range. In a case where it is determined that there is no body movement of a person in the measurement range, the processing proceeds to step S105. In a case where it is determined that there is body movement of a person in the measurement range, the processing proceeds to step S110.

[0054] In step S105, the signal processing section 151 acquires a respiratory waveform group on the basis of a respiratory signal extracted by signal processing of a signal received by the reception section 122. The signal received by the reception section 122 also includes a signal not caused by respiratory motion. As the signal not caused by respiratory motion, for example, there are a stationary object such as a bed, a wall, and the like, a slight motion of a person, a vibration of a fan, a motion of a pet, a robot, and the like, a signal mixed on the basis of a plurality of objects, a noise component, and the like. By removing the signal not caused by respiratory motion from the signal received by the reception section 122, the signal processing section 151 removes only a signal (respiratory signal) caused by respiratory motion from the signal received by the reception section 122. The signal processing section 151 performs exclusion of the signal not caused by respiratory motion and extraction of the respiratory signal, for example, on the basis of characteristics of the signal intensity, the phase variation amount, the amplitude variation amount, the repetitiveness of the phase, the frequency, and the like of the reflected wave.

[0055] In step S106, the clustering section 152 clusters the respiratory waveform group on the basis of the characteristic quantity calculated from the vital sign signal and acquires the number of clusters of the clustered respiratory waveform group, the representative waveform of each of the respiratory waveform groups, and the coordinates of the representative waveforms. The clustering section 152 can also cluster the respiratory waveform group using an algorithm of k-means clustering. The clustering section 152 can also perform clustering with the characteristic quantity calculated from the respiratory waveform group as input. The characteristic quantity is, for example, the frequency, the phase, and the coordinate information (distance, direction) of the vital sign signal. In addition, the clustering section 152 can also cluster the respiratory waveform group using an algorithm of a Gaussian mixture model (GMM), X-means, a variational Bayesian GMM (VBGMM), and the like. Figure 6 (A) of FIG. 10 is an explanatory view of the coordinates of the representative waveforms of the clustered respiratory waveform groups. Figure 6 The horizontal axis of (A) of FIG. 10 is the direction, Figure 6 The vertical axis of (A) of FIG. 10 is the distance. In Figure 6 In (A) of FIG. 10, the coordinates (X1, Y1) of the representative waveform Al, the coordinates (X2, Y2) of the representative waveform B1, and the coordinates (X3, Y3) of the representative waveform C1 are shown. Figure 6 (B) of FIG. 10 is a view showing one example of the representative waveforms of each of the clustered respiratory waveform groups. Figure 6 The vertical axis of (B) of FIG. 10 is the amplitude, Figure 7 The horizontal axis of (B) of FIG. 10 is the time.

[0056] In step S107, the index calculation unit 132 calculates a breathing index representing the breathing state of at least one person within the measurement range based on the breathing signal. The index calculation unit 132 calculates the breathing index for one time slot. One time slot is, for example, 20 seconds (250 frames).

[0057] In step S108, the indicator output unit 137 determines whether there is an instruction to output a breathing indicator. If there is an instruction to output a breathing indicator (S108: Yes), the process proceeds to step S109. If there is no instruction to output a breathing indicator (S108: No), the process returns to step S101. The user can operate the processing device 100 and input an instruction to output a breathing indicator to the processing device 100.

[0058] In step S109, the calculation unit 136 calculates the time series data of the breathing index for each person within the measurement range, and the index output unit 137 outputs the time series data of the breathing index for each person within the measurement range. Thereafter, the process returns to step S101. The time series data of the breathing index is data in which the breathing indexes of multiple time slots are arranged in a time series, and is data that represents the time trend of the breathing index. In addition, the calculation unit 136 can calculate the time series data of the breathing index at any time, or calculate the time series data of the breathing index based on pre-set schedule information. The index output unit 137 can output the time series data of the breathing index at any time, or output the time series data of the breathing index based on pre-set schedule information.

[0059] In step S110, the number-of-people estimation unit 134 estimates the number of people within the measurement range, and the number-of-people change determination unit 135 determines whether the estimated number of people is likely to have changed. If it is determined that the estimated number of people is likely to have changed (S110: Yes), the process proceeds to step S111. If it is determined that the estimated number of people is likely to have changed (S110: No), the process returns to step S101.

[0060] In step S111, calculation unit 136 calculates the time series data of the breathing index for each person within the measurement range. In this case, calculation unit 136 separately calculates the time series data of the breathing index before determining the possibility of a change in the number of people, and the time series data of the breathing index after determining the possibility of a change in the number of people. This allows for separate calculations of the time series data of the vital sign index for each person before the change in the number of people, and the time series data of the vital sign index for each person after the change in the number of people. After step S111, the process returns to step S101.

[0061] In step S112, the index output section 137 determines whether there is an instruction of output of the respiratory index. In a case where it is determined that there is an instruction of output of the respiratory index (S112: YES), the process proceeds to step S113. In a case where it is determined that there is no instruction of output of the respiratory index (S112: NO), the process returns to step S101. The user can also operate the processing device 100 and input an instruction of output of the respiratory index to the processing device 100.

[0062] In step S113, the index output section 137 outputs the time series data of the respiratory index for each person in the measurement range. In this case, the index output section 137 outputs the time series data of the respiratory index before the determination that there is a possibility of a change in the number of persons and the time series data of the respiratory index after the determination that there is a possibility of a change in the number of persons separately. Thereby, it is possible to output the time series data of the vital sign index of the amount of the number of persons before the change in the number of persons and the time series data of the vital sign index of the amount of the number of persons after the change in the number of persons for each person separately.

[0063] Figure 7 is an explanatory diagram of the estimation process of the number of persons in the measurement range. Figure 5 Each time slot of is 20 sec. In the first time slot (time slot number 1), the twelfth time slot (time slot number 12), in Figure 5 In step S104 of the processing flow of, it is determined that there is a body movement of a person in the measurement range (body movement determination = 1). Therefore, in each of the first time slot, the twelfth time slot, at least one person in the measurement range is in a dynamic state. In the second to eleventh, thirteenth time slots (time slot numbers 2 to 11, 13), in Figure 7 In step S104 of the processing flow of, it is determined that there is no body movement of a person in the measurement range (body movement determination = 0). Therefore, in each of the second to eleventh, thirteenth time slots, all persons in the measurement range are in a static state. In Figure 7 In, the maximum value of the number of clusters of the second to eleventh, thirteenth time slots is "3".

[0064] During the period when it is determined that the person within the measurement range is not in a physical activity state and there is no movement of the person within the measurement range, it can be estimated that the number of people within the measurement range has not changed, and therefore the maximum value of the result of the clustering processing of the respiratory waveform group can be determined as the correct number of people within the measurement range. During a static state (a state in which there is no change in the number of people), when the number of vital sign indicators (respiratory indicators) is the largest, vital sign indicators corresponding to the actual number of people can be measured. Otherwise, it can be estimated that the vital sign signals for the number of people cannot be obtained due to reasons such as the deterioration of the SN ratio that does not meet the extraction benchmark. The number of people estimation unit 134 estimates the number of people within the measurement range based on the maximum value of the number of clusters during the static state (a state in which there is no change in the number of people). That is, for a period in which it is determined that there is no physical activity of the person within the measurement range among multiple periods, the number of people estimation unit 134 estimates the maximum value of the number of clusters as the number of people within the measurement range. Figure 7 In the illustrated example, the number of people estimating unit 134 estimates the number of people within the measurement range during the static state to be “3”.

[0065] exist Figure 8 In the fourth and tenth time slots, the number of clusters is "2," which is inconsistent with the maximum number of clusters during the static state. In this case, there is a possibility that a person in the measurement range is in a state different from the normal breathing state, such as apnea. Therefore, during a period in the static state when the number of clusters is less than the maximum number of clusters, there is a high possibility that the person in the measurement range is in an abnormal state, such as apnea or coughing. It is preferable to detect a period in which there is a possibility that the person in the measurement range is in an abnormal state, such as apnea or coughing. Therefore, in this embodiment, the abnormality detection unit 138 detects an abnormality in the vital signs of at least one person in the measurement range based on the estimated number of people and the number of clusters. If the estimated number of people (the maximum number of clusters) does not match the number of clusters, the abnormality detection unit 138 determines that at least one person in the measurement range has an abnormal vital sign. Then, the abnormality detection unit 138 determines that a period in which the person in the measurement range has an abnormal vital sign has occurred, during which the person in the measurement range has not moved physically and the number of clusters is less than the maximum number of clusters, among the consecutive periods of the multiple periods. This allows the user to understand whether the vital signs of the person within the measurement range are abnormal or the period during which the vital signs are abnormal.

[0066] The abnormality detection section 138 can also detect a vital sign abnormality of at least one person in the measurement range based on the variation in the vital sign signal in the immediately preceding time slot of the time slot in which the number of persons estimated is inconsistent with the number of clusters. For example, the abnormality detection section 138 can also determine whether a vital sign abnormality has occurred in at least one person in the measurement range by detecting, based on the variation in the vital sign signal, a gradual decrease in the number of breaths, a gradual decrease in the amplitude value of the vital sign signal, or the like. The abnormality detection section 138 can also determine, based on the time slot in which the number of persons estimated is inconsistent with the number of clusters and the immediately preceding time slot, whether a feature consistent with the movement of the body surface when a vital sign abnormality has occurred is detected from the reception signal of the spatial region in which the respiration signal is acquired. The abnormality detection section 138 can also determine, based on the result of whether a feature consistent with the movement of the body surface when a vital sign abnormality has occurred is detected from the reception signal of the spatial region in which the respiration signal is acquired, whether a vital sign abnormality has occurred in at least one person in the measurement range. In this way, the abnormality detection section 138 can also determine, based on the vital sign signal in the immediately preceding period of the period in which physical activity of a person in the measurement range is determined to be absent and the number of clusters is smaller than the maximum value of the number of clusters among the consecutive periods among the plurality of periods, whether a vital sign abnormality has occurred in at least one person in the measurement range. Thus, the user can grasp a vital sign abnormality of a person in the measurement range.

[0067] Figure 8 is a diagram for explaining one example of excluding data of low reliability from time series data of vital sign indexes. Figure 7 The time slot number, time slot, physical activity determination, number of clusters, and respiration index in Figure 9 The number of clusters in the fourth time slot (time slot number 4) and the tenth time slot (time slot number 10) is "2", and the maximum value of the number of clusters in the static state period is "3". Since the number of persons estimation section 134 estimates the number of persons in the measurement range based on the maximum value of the number of clusters in the static state period, the number of persons estimation result in the periods of the first to eleventh time slots is three persons. In the period of the fourth time slot and the period of the tenth time slot, the respiration index of the amount of the number of persons estimated by the number of persons estimation section 134 is not calculated, and thus the data of the respiration index in the period of the fourth time slot and the period of the tenth time slot is data of low reliability. It is preferable to exclude data of low reliability from the time series data of vital sign indexes. Therefore, in the present embodiment, the operation section 136 excludes the period in which the vital sign index (for example, the respiration index) of the amount of the estimated number of persons is not calculated among the periods in which physical activity of a person in the measurement range is determined to be absent (the static state period) among the plurality of periods, and operates the time series data of the vital sign index for each person. Thus, data of low reliability is excluded from the time series data of the vital sign index, and the reliability of the time series data of the vital sign index is improved.

[0068] Figure 9 This is an explanatory diagram of an example of a process of outputting time-series data of a breathing index for each person within a measurement range. Figure 9 Each time slot is 20 seconds. Figure 9 The respiratory index shown includes the number of breaths. The number of clusters during the first, second and fourth time slots (time slot numbers 1, 2 and 4) is "3", and the number of clusters during the third time slot (time slot number 3) is "2". Since the number of people estimating unit 134 estimates the number of people within the measurement range based on the maximum value of the number of clusters during the static state, the number of people estimated during the first to fourth time slots is 3. During the first, second and fourth time slots, the number of breaths for the estimated number of people was calculated. During the third time slot, the number of breaths for the estimated number of people was not calculated. In this case, it is determined that the target person exists, but the breathing signal of the target person does not meet the extraction conditions, and the number of breaths for one person is not calculated. Therefore, during the third time slot, the number of breaths for two people is calculated, and the calculation result of the number of breaths for one person is null.

[0069] The calculation unit 136 compares the breathing rate during each time slot and determines the corresponding relationship between the breathing rates during each time slot for each character. The breathing rates of adjacent time slots of the same character are less likely to change rapidly. Therefore, the calculation unit 136 determines the combination with the smallest difference in the breathing rates between adjacent time slots. Figure 10 In the example shown, calculation unit 136 determines a combination of respiratory rates associated with arrows D1 to D3, a combination of respiratory rates associated with arrows E1 to E2, and a combination of respiratory rates associated with arrows F1 to F3. Thus, calculation unit 136 determines a combination of respiratory indicators for each person by associating respiratory indicators with each person based on the values ​​of the respiratory indicators in each of multiple time periods. Based on the combination of respiratory indicators, calculation unit 136 calculates time-series data of respiratory indicators for each person. Conventional methods cannot calculate time-series data of vital sign indicators for each person, but in this embodiment, time-series data of vital sign indicators can be calculated for each person. When analyzing the time-series data of vital sign indicators, the vital sign indicators of each person can be easily understood. Furthermore, the calculation processing of time-series data of respiratory indicators can also be applied to the calculation processing of time-series data of pulse indicators and other vital sign indicators.

[0070] Figure 10 This is an explanatory diagram of an example of processing for calculating time-series data of a breathing index for each person within the measurement range. Figure 10Each time slot is 20 seconds. Figure 10 The respiration indexes shown include the number of breaths and the spatial coordinates (distance and direction). The coordinates included in the respiration indexes may, for example, also be the coordinates of the representative waveform of the clustered respiration waveform group. During the first, second, and fourth time slots, the number of breaths and the coordinates of the estimated number of persons are calculated. During the third time slot, the number of breaths and the coordinates of the estimated number of persons are not calculated. During the third time slot, the number of breaths and the coordinates of 2 persons are calculated, and the calculation result of the number of breaths and the coordinates of 1 person is null.

[0071] The operation section 136 compares the coordinates of each time slot period, respectively, and determines the correspondence of the respective coordinates of each time slot period for each person. The operation section 136 determines the combination in which the distance between the coordinates (inter-coordinate distance) in the adjacent two time slots is the smallest. In the example shown, the operation section 136 determines the combination of the respiration indexes associated by the arrows K1 to K3, the combination of the respiration indexes associated by the arrows L1 to L2, and the combination of the respiration indexes associated by the arrows M1 to M3. Figure 11 In the example shown, the operation section 136 determines the combination of the respiration indexes associated by the arrows K1 to K3, the combination of the respiration indexes associated by the arrows L1 to L2, and the combination of the respiration indexes associated by the arrows M1 to M3. In this way, the operation section 136 determines the combination of the respiration indexes for each person by establishing a correspondence between the respiration indexes and each person on the basis of the respective coordinates (position information) of the plurality of periods, and operates the time series data of the respiration indexes for each person on the basis of the combination of the respiration indexes. Thereby, the time series data of the vital sign indexes of each person within the measurement range can be accurately operated. When the time series data of the vital sign indexes is analyzed, the vital sign indexes of each person can be easily grasped. Furthermore, the operation processing of the time series data of the respiration indexes can also be applied to the operation processing of the time series data of the pulse indexes and the operation processing of the time series data of the vital sign indexes.

[0072] Figure 11 is a flowchart showing one example of a processing flow of determining whether there is a person within the measurement range who is moving. Figure 5 The processing flow of Figure 5 is executed in step S104. In step S201, the signal processing section 151 removes the stationary object component from the received signal by performing signal processing on the signal received by the reception section 122. The signal processing section 151 may, for example, perform time difference processing between adjacent frames, or may perform difference processing of time averaging from the signal of each frame to the signal within the time slot. In step S202, the signal processing section 151 calculates the body movement index (amplitude value) on the basis of the signal from which the stationary object component has been removed.

[0073] In step S203, the body activity determination unit 133 determines whether the body activity index is above the threshold value. If the body activity index is above the threshold value (S203: Yes), the process proceeds to step S204. In step S204, the body activity determination unit 133 determines that there is a body activity of the person within the measurement range, and the process proceeds to step S205. Figure 5 If the physical activity index is less than the threshold value (S203: No), the process proceeds to step S205. In step S205, the physical activity determination unit 133 determines that there is no physical activity of the person within the measurement range, and the process proceeds to step S110. Figure 12 Step S105.

[0074] Reference Figure 12 (A) and Figure 12 (B) describes an example of a process for determining whether or not there is physical movement of a person within the measurement range. Figure 12 (A) is a graph showing the amplitude strength of a received signal from which stationary object components are removed when a person is in a quiet state. Figure 12 (B) is a diagram showing the amplitude strength of a received signal from which stationary object components are removed in a state where human body movement occurs. Figure 12 (A) and Figure 12 The horizontal axis of (B) represents the direction, Figure 12 (A) and Figure 13 The vertical axis of (B) represents distance. When a person's physical activity occurs, the amplitude value at the location where the person exists increases compared to when the person is at rest. The physical activity determination unit 133 may also determine whether there is physical activity of a person within the measurement range based on the change in the amplitude value. In addition, when a person's physical activity occurs, the range of strong amplitude values ​​increases compared to when the person is at rest. The physical activity determination unit 133 may also determine whether there is physical activity of a person within the measurement range based on the degree of expansion of the range of strong amplitude values.

[0075] Figure 13 This is a flowchart showing an example of a process flow for determining whether or not there is a possibility of a change in the estimated number of people. Figure 5 The processing flow is Figure 5 In step S301, the person change determination unit 135 calculates the physical activity time (measurement). The physical activity time is, for example, the time (elapsed time) from the time when the physical activity of the person in the measurement range is detected to the time when the physical activity of the person in the measurement range is no longer detected.

[0076] In step S302, the number-of-persons change determination section 135 determines whether or not there is a body movement of a person in the measurement range in a preceding time slot (a time slot preceding the processing target time slot). In a case where there is a body movement of a person in the measurement range in the preceding time slot (S302: YES), the processing proceeds to S303. In a case where there is no body movement of a person in the measurement range in the preceding time slot (S302: NO), the processing proceeds to S305.

[0077] In step S303, the number-of-persons change determination section 135 determines whether or not the body movement of a person in the measurement range is continuous. Specifically, the number-of-persons change determination section 135 determines whether or not the body movement of a person in the measurement range in the preceding time slot is in a continuous relationship with the body movement of a person in the measurement range in the processing target time slot. In a case where the body movement of a person in the measurement range in the preceding time slot is in a continuous relationship with the body movement of a person in the measurement range in the processing target time slot, the number-of-persons change determination section 135 determines that the body movement of a person in the measurement range is continuous. In a case where the body movement of a person in the measurement range is continuous (S303: YES), the processing proceeds to step S304. In a case where the body movement of a person in the measurement range in the preceding time slot is not in a continuous relationship with the body movement of a person in the measurement range in the processing target time slot, the number-of-persons change determination section 135 determines that the body movement of a person in the measurement range is not continuous. In a case where the body movement of a person in the measurement range is not continuous (S303: NO), the processing proceeds to step S305.

[0078] In step S304, the number-of-persons change determination section 135 calculates a total body movement time obtained by adding the body movement time in the preceding time slot to the body movement time in the processing target time slot. In step S305, the number-of-persons change determination section 135 determines whether or not the body movement time is equal to or greater than a threshold time. In a case where the body movement time is equal to or greater than the threshold time (S305: YES), the processing proceeds to step S306. In a case where the body movement time is less than the threshold time (S305: NO), the processing proceeds to step S307. In a case where the total body movement time is calculated in step S304, the number-of-persons change determination section 135 determines whether or not the total body movement time is equal to or greater than the threshold time. In a case where the total body movement time is equal to or greater than the threshold time (S305: YES), the processing proceeds to step S306. In a case where the total body movement time is less than the threshold time (S305: NO), the processing proceeds to step S307.

[0079] In step S306, the number-of-persons change determination section 135 determines that there is a possibility of a change in the estimated number of persons, and the processing proceeds to step S111 of FIG. 11. In step S307, the number-of-persons change determination section 135 determines that there is no possibility of a change in the estimated number of persons, and the processing returns to step S301 of FIG. 10. Figure 5 Figure 14 ​The step S101. By determining the possibility of a change in the estimated number of people based on the time of physical activity of the person, it is possible to simply determine the possibility of a change in the estimated number of people.

[0080] The threshold time can also be determined based on the time in which the person in the measurement range is able to move outside the measurement range, for example, based on the times indicated in (1) and (2) below.

[0081] (1) Time in which the person gets up from the bed (time from when the person gets on the bed to when the person lies down)

[0082] (2) Time in which the person moves from inside the measurement range to outside the measurement range (time from when the person moves from outside the measurement range to when the person gets on the bed inside the measurement range)

[0083] In a case in which the shortest distance from the position of the person in the measurement range to outside the measurement range is set to 0.5 m and the movement time of the person is assumed to be 1 m / sec, the time of (1) is 5 sec and the time of (2) is 0.5 sec, and thus the threshold time can also be set to 5.5 sec.

[0084] Reference Figure 14 (A) to Figure 14 (C) of FIG. 10, one example of the determination processing of the number-of-people change determination section 135 will be described. Figure 14 (A) to Figure 14 (C) of FIG. 10 are explanatory diagrams of the determination processing of the number-of-people change. Figure 14 (A) and Figure 14 (B) of FIG. 10. The vertical axis of (A) and (B) indicates the physical activity index, Figure 14 (A) and Figure 14 (B) of FIG. 10. The horizontal axis of (A) and (B) indicates time (frames). The physical activity index is an index indicating the magnitude of physical activity. The number-of-people change determination section 135 can also calculate the physical activity index based on the amplitude information and the like of the signal received by the reception section 122. Figure 14 The period T1 in which the physical activity index indicated in (A) of FIG. 10 increases and Figure 14 The period T2 in which the physical activity index indicated in (B) of FIG. 10 increases is a period in which physical activity of the person in the measurement range occurs. The period T1 and the period T2 can also be the elapsed time from the timing at which physical activity of the person in the measurement range is detected to the timing at which physical activity of the person in the measurement range is no longer detected. Figure 14 The period T1 indicated in (A) of FIG. 10 corresponds to Figure 14 The dynamic state period A2 indicated in (C) of FIG. 10, Figure 12 The period (T2) indicated in (B) of FIG. 10 corresponds to Figure 12 The dynamic state period (B1) indicated in (C) of FIG. 10.

[0085] If the period (T1) is shorter than the threshold time (predetermined time), the number of people change determination unit 135 determines that there is no possibility of a change in the estimated number of people. Figure 12 As shown in (C), the dynamic state period (A2) corresponding to the period (T1) is the period between the static state period (A1) and the static state period (A3). The number of people change determination unit 135 estimates that the period A, which includes the periods (A1), (A2), and (A3), is a period in which the number of people within the measurement range has not changed.

[0086] If the period (T2) is longer than the threshold time, the number of people change determination unit 135 may also determine that there is a possibility that the estimated number of people has changed. Figure 15 As shown in (B), if the baseline of the physical activity index changes, there is a possibility that a person within the measurement range has moved. The number of people change determination unit 135 may also determine that there is a possibility that the estimated number of people has changed when the baseline of the physical activity index changes.

[0087] Reference Figure 15 (A)~ Figure 15 (C) An example of the process of determining a change in the number of people performed by the number of people change determination unit 135 will be described. Figure 15 (A) is a graph showing the signal strength of a received signal with stationary object components removed when a person is in a quiet state. Figure 15 (B) is a graph showing the signal strength of a received signal from which stationary object components are removed in a state where human body movement occurs. Figure 15 (C) is a graph showing the signal strength of a received signal when a person is moving. Figure 15 (A)~ Figure 15 The horizontal axis of (C) represents the direction, Figure 15 (A)~ Figure 15 The vertical axis of (C) represents distance.

[0088] like Figure 16 As shown in (B), when human body activity occurs, a signal peak is generated, such as Figure 16 As shown in (C), when a person moves, the position of the signal peak generated by the person's physical activity changes. The number of people change determination unit 135 can also determine that there is a possibility of a change in the estimated number of people based on the change in the position of the signal peak. For example, the number of people change determination unit 135 can also detect whether a person moves from within the measurement range to outside the measurement range by tracking the change in the position of the signal peak, and determine whether there is a possibility of a change in the estimated number of people.

[0089] Figure 16 (A)~ Figure 16(D) is a diagram showing the result of clustering, which is an image of cluster indices classified by clustering. Figure 16 (A)~ Figure 16 The horizontal axis of each (D) represents the distance, Figure 16 (A)~ Figure 7 The vertical axis of each (D) represents the direction. Figure 16 (A) shows Figure 7 The results of clustering during the second time slot are shown. Figure 16 (B) shows Figure 7 The results of clustering during the third time slot are shown. Figure 16 (C) shows Figure 7 The results of clustering during the fourth time slot are shown. Figure 16 (D) shows Figure 16 The result of clustering during the 5th time slot is shown in FIG. In addition, since the indexes of the clusters are assigned in different orders, as shown in FIG. Figure 7 (A) and Figure 16 As shown in (C), sometimes different indices are assigned to each time slot even in the same area. ​ The second to fifth time slots shown are static state periods, and it is determined that there is no physical movement of the person within the measurement range. However, the number of clusters in the third time slot is smaller than that in the fourth time slot. ​ As shown in (C), no respiratory signal is detected in the region (bin) surrounded by the dotted line. This means that there is a high possibility that a person with respiratory disorder due to apnea, wheezing, coughing, etc. exists during the fourth time slot.

[0090] The abnormality detection unit 138 notifies the user of the occurrence of an abnormality in the vital signs of the person within the measurement range. The abnormality detection unit 138 or the output device 114 may also output a message that an abnormality in the vital signs of the person within the measurement range has occurred to the display device 300. The abnormality detection unit 138 may also report the occurrence of an abnormality in the vital signs by lighting or flashing a display light provided on the processing device 100, or outputting a sound or a warning sound from the processing device 100. In this way, the user can understand that an abnormality in the vital signs of the person within the measurement range has occurred. The abnormality detection unit 138 notifies the user of the period (abnormal period) during which the abnormality in the vital signs of the person within the measurement range has occurred. The abnormality detection unit 138 or the output device 114 may also output data related to the abnormal period to the display device 300. The abnormality detection unit 138 may also report the abnormal period by outputting a sound from the processing device 100. In this way, the user can understand the abnormal period.

[0091] The present application can also be understood as a processing system or a control system having at least a part of each of the structures, each unit, and each function described above. The present application can also be understood as a processing method or a control method including at least a part of each of the processes described above. The present application can also be understood as a method in which a computer executes each of the processes described above. The present application can also be understood as a program for causing a computer to execute each of the processes described above, and the program can be provided to the computer via a network or from a computer-readable recording medium or the like that does not temporarily hold data.

[0092] <Computer-readable recording medium>

[0093] A program that causes the information processing apparatus and other machines, devices (hereinafter, computers or the like) to implement any of the functions described above can be recorded in a recording medium that is readable by a computer or the like. Furthermore, by causing a computer or the like to read the program from the recording medium and execute it, the function thereof can be provided.

[0094] Here, the recording medium that is readable by a computer or the like refers to a recording medium that accumulates information such as data and programs by electrical, magnetic, optical, mechanical, or chemical actions, and is readable from a computer or the like. As the recording medium that is detachable from a computer or the like in such a recording medium, there are, for example, a floppy disk, an optical magnetic disk, a CD-ROM, a CD-R / W, a DVD, a Blu-ray disk, a memory card, and the like. In addition, as the recording medium that is fixed to a computer or the like, there are a hard disk, a ROM, and the like.

[0095] <Note 1>

[0096] A processing apparatus (100) includes:

[0097] a signal acquisition unit (131) that acquires a vital sign signal from a signal reflected by at least one person in a measurement range;

[0098] an index calculation unit (132) that calculates a vital sign index that represents a vital sign state of the at least one person, on the basis of the vital sign signal;

[0099] a physical activity determination unit (133) that determines whether or not there is physical activity of the person in the measurement range;

[0100] a number estimation unit (134) that estimates the number of persons in the measurement range;

[0101] a number change determination unit (135) that determines whether or not there is a possibility of a change in the estimated number of persons, in a case where it is determined that there is the physical activity of the person in the measurement range; and

[0102] a calculation unit (136) that calculates time-series data of the vital sign index for each of the persons,

[0103] In a case where it is determined that there is a possibility of a change in the estimated number of people, the operation section (136) separately operates the time series data of the vital sign index before it is determined that there is a possibility of a change in the estimated number of people and the time series data of the vital sign index after it is determined that there is a possibility of a change in the estimated number of people.

[0104] <Note 2>

[0105] In the processing device (100) according to Note 1,

[0106] The physical activity determination section (133) calculates a physical activity time of the person in the measurement range,

[0107] The number of people change determination section (135) determines whether there is a possibility of a change in the estimated number of people based on the physical activity time of the person.

[0108] <Note 3>

[0109] In the processing device (100) according to Note 1 or 2,

[0110] The index calculation section (132) calculates the vital sign index for each of a plurality of periods,

[0111] The number of people estimation section (134) estimates the number of people of the person in the measurement range in each of the plurality of periods,

[0112] The physical activity determination section (133) determines whether there is the physical activity of the person in the measurement range in each of the plurality of periods,

[0113] The operation section (136) operates the time series data of the vital sign index for each of the persons, except for a period in which the vital sign index for which the estimated number of people is not calculated in a period in which it is determined that there is no physical activity of the person in the measurement range.

[0114] <Note 4>

[0115] In the processing device (100) according to any one of Notes 1 to 3,

[0116] The position information calculation section (138) determines a position of the person in the measurement range and calculates position information of the person associated with the vital sign index for each of the persons,

[0117] The index calculation section (132) calculates the vital sign index for each of a plurality of periods,

[0118] The position information calculation section (138) calculates the position information for each of the plurality of periods,

[0119] The operation section (136) establishes correspondence between the vital sign index and each of the persons based on the position information for each of the plurality of periods, thereby determining a combination of the vital sign index for each of the persons, and operates the time series data of the vital sign index for each of the persons based on the combination of the vital sign index.

[0120] <Note 5>

[0121] In the processing device (100) according to any one of Notes 1 to 3,

[0122] The index calculation section (132) calculates the vital sign index for each of a plurality of periods,

[0123] The operation section (136) establishes correspondence between the vital sign index and each of the persons based on the values of the vital sign index for each of the plurality of periods, thereby determining a combination of the vital sign index for each of the persons, and operates the time series data of the vital sign index for each of the persons based on the combination of the vital sign index.

[0124] <Note 6>

[0125] In the processing device (100) according to any one of Notes 1 to 5,

[0126] The index output section (137) outputs the time series data of the vital sign index for each of the persons,

[0127] In a case where it is determined that there is a possibility of a change in the estimated number of persons, the index output section (137) separately outputs the time series data of the vital sign index before it is determined that there is a possibility of a change in the estimated number of persons, and the time series data of the vital sign index after it is determined that there is a possibility of a change in the estimated number of persons.

[0128] <Note 7>

[0129] In the processing device (100) according to any one of Notes 1 to 6,

[0130] The signal acquisition section (131) performs processing of clustering vital sign waveform groups acquired based on the vital sign signals into a plurality of clusters based on a feature quantity calculated from the vital sign signals,

[0131] The number-of-persons estimation unit (134) estimates the number of persons of the person within the measurement range based on the number of clusters.

[0132] <Note 8>

[0133] In the processing device (100) according to Note 7,

[0134] The physical activity determination unit (133) determines, in each of the plurality of periods, whether or not the physical activity of the person within the measurement range is present,

[0135] The number-of-persons estimation unit (134) estimates the number of persons of the person within the measurement range in each of the plurality of periods, and estimates, as the number of persons of the person within the measurement range, the maximum value of the number of clusters for a period in which the physical activity of the person within the measurement range is determined not to be present among consecutive periods in the plurality of periods.

[0136] <Note 9>

[0137] In the processing device (100) according to Note 7,

[0138] The processing device (100) according to Note 7 further includes an abnormality detection unit (137) that detects a vital sign abnormality of the at least one person within the measurement range based on the estimated number of persons and the number of clusters.

[0139] <Note 10>

[0140] In the processing device (100) according to Note 9,

[0141] The physical activity determination unit (133) determines, in each of the plurality of periods, whether or not the physical activity of the person within the measurement range is present,

[0142] The number-of-persons estimation unit (134) estimates the number of persons of the person within the measurement range in each of the plurality of periods, and estimates, as the number of persons of the person within the measurement range, the maximum value of the number of clusters for a period in which the physical activity of the person within the measurement range is determined not to be present among consecutive periods in the plurality of periods,

[0143] The abnormality detection unit (137) determines a period in which the number of clusters is smaller than the maximum value as a period in which the vital sign abnormality of the person occurs, for a period in which the physical activity of the person within the measurement range is determined not to be present among the consecutive periods.

[0144] <Note 11>

[0145] The processing device (100) described in the supplementary note 7,

[0146] The abnormality detection section (137) detects a vital sign abnormality of the at least one person in the measurement range,

[0147] The physical activity determination section (133) determines whether or not there is the physical activity of the person in the measurement range in each of the plurality of periods,

[0148] The number estimation section (134) estimates the number of persons in the measurement range in each of the plurality of periods, and estimates the maximum value of the cluster number as the number of persons in the measurement range for a period in which the physical activity of the person in the measurement range is determined to be absent in consecutive periods among the plurality of periods,

[0149] The abnormality detection section (137) determines whether or not the vital sign abnormality occurs in the at least one person in the measurement range, based on the vital sign signal in the immediately preceding period of a period in which the physical activity of the person in the measurement range is determined to be absent and the cluster number is smaller than the maximum value, among the consecutive periods.

[0150] <Supplementary Note 12>

[0151] A processing method is a processing method executed by a processing device (100), the processing method having:

[0152] A signal acquisition step acquires a vital sign signal from a signal reflected by at least one person in a measurement range;

[0153] An index calculation step calculates a vital sign index representing a vital sign state of the at least one person, based on the vital sign signal;

[0154] A physical activity determination step determines whether or not there is physical activity of the person in the measurement range;

[0155] A number estimation step estimates the number of persons in the measurement range;

[0156] A number change determination step determines whether or not there is a possibility of a change in the estimated number of persons, in a case where the physical activity of the person in the measurement range is determined to be present; and

[0157] An operation step operates time series data of the vital sign index for each of the persons,

[0158] The operation step includes, in a case where it is determined that there is a possibility of a change in the estimated number of people, separately operating the time series data of the vital sign index before it is determined that there is a possibility of a change in the estimated number of people and the time series data of the vital sign index after it is determined that there is a possibility of a change in the estimated number of people.

[0159] <NOTE 13>

[0160] A program for causing a computer to execute the steps of:

[0161] A signal acquisition step of acquiring a vital sign signal from a signal reflected by at least one person in a measurement range;

[0162] An index calculation step of calculating a vital sign index indicating a vital sign state of the at least one person on the basis of the vital sign signal;

[0163] A body movement determination step of determining whether or not there is a body movement of the person in the measurement range;

[0164] A number estimation step of estimating a number of the person in the measurement range;

[0165] A number change determination step of determining whether or not there is a possibility of a change in the estimated number of the person in the measurement range in a case where it is determined that there is the body movement of the person in the measurement range; and

[0166] An operation step of operating time series data of the vital sign index for each of the person,

[0167] The operation step includes, in a case where it is determined that there is a possibility of a change in the estimated number of people, separately operating the time series data of the vital sign index before it is determined that there is a possibility of a change in the estimated number of people and the time series data of the vital sign index after it is determined that there is a possibility of a change in the estimated number of people.

[0168] Explanation of Reference Signs

[0169] 100: processing device

[0170] 111: transceiving device

[0171] 112: control device

[0172] 113: storage device

[0173] 114: output device

[0174] 121: transmission section

[0175] 122: reception section

[0176] 131: signal acquisition section

[0177] 132: index calculation section

[0178] 133: physical activity determination section

[0179] 134: number of people estimation section

[0180] 135: number of people change determination section

[0181] 136: arithmetic section

[0182] 137: index output section

[0183] 138: abnormality detection section

[0184] 139: position information calculation section

[0185] 151: signal processing section

[0186] 152: clustering section

Claims

1. A processing device comprising: a signal acquisition unit that acquires a vital sign signal from a signal reflected by at least one person within a measurement range; an index calculation unit, which calculates a vital sign index representing a vital sign state of at least one of the persons based on the vital sign signal; a body movement determination unit for determining whether or not there is a body movement of the person within the measurement range; a number estimating unit for estimating the number of the persons within the measurement range; a number-of-people change determination unit that, when it is determined that the physical movement of the person within the measurement range occurs, determines whether there is a possibility of a change in the estimated number of people; as well as A calculation unit calculates the time series data of the vital sign indicators for each of the persons, and when it is determined that there is a possibility of a change in the estimated number of people, the calculation unit separately calculates the time series data of the vital sign indicators before the determination that there is a possibility of a change in the estimated number of people, and the time series data of the vital sign indicators after the determination that there is a possibility of a change in the estimated number of people.

2. The processing device according to claim 1, wherein The physical activity determination unit calculates the physical activity time of the person within the measurement range. The number-of-people change determination unit determines whether there is a possibility of a change in the estimated number of people based on the physical activity time of the person.

3. The processing device according to claim 1, wherein The index calculation unit calculates the vital sign index for each of a plurality of periods, and the number of people estimation unit estimates the number of people within the measurement range in each of the plurality of periods. The body activity determination unit determines whether or not the body activity of the person within the measurement range occurs in each of the plurality of periods. The calculation unit calculates the time series data of the vital sign indicators for each of the persons, excluding periods during which the vital sign indicators for the estimated number of persons are not calculated among the periods determined to be without the physical activity of the persons within the measurement range.

4. The processing device according to claim 1, wherein The processing device includes a position information calculation unit that determines the position of the person within the measurement range and calculates the position information of the person associated with the vital sign index for each person. The index calculation unit calculates the vital sign index for each of a plurality of periods. The position information calculation unit calculates the position information of each of the multiple periods, and the calculation unit establishes a correspondence between the vital sign indicators and each of the persons based on the position information of each of the multiple periods, thereby determining a combination of the vital sign indicators for each of the persons, and calculating the time series data of the vital sign indicators for each of the persons based on the combination of the vital sign indicators.

5. The processing device according to claim 1, wherein The indicator calculation unit calculates the vital sign indicators for each of the multiple periods, and the calculation unit establishes a correspondence between the vital sign indicators and each of the people based on the values ​​of the vital sign indicators for each of the multiple periods, thereby determining a combination of the vital sign indicators for each of the people, and calculating the time series data of the vital sign indicators for each of the people based on the combination of the vital sign indicators.

6. The processing device according to claim 1, wherein The processing device includes an index output unit configured to output the time series data of the vital sign index for each person. When it is determined that there is a possibility of a change in the estimated number of people, the indicator output unit separately outputs the time series data of the vital sign indicators before it is determined that there is a possibility of a change in the estimated number of people, and the time series data of the vital sign indicators after it is determined that there is a possibility of a change in the estimated number of people.

7. The processing device according to any one of claims 1 to 6, wherein The signal acquisition unit performs the following processing: clustering the vital sign waveform group acquired based on the vital sign signal into a plurality of clusters based on the feature amount calculated based on the vital sign signal; The number-of-people estimating unit estimates the number of the people within the measurement range based on the number of clusters.

8. The processing device according to claim 7, wherein: The body activity determination unit determines whether or not the body activity of the person within the measurement range occurs in each of the plurality of periods. The number of people estimating unit estimates the number of the people within the measurement range in each of the multiple periods, and for the periods in which it is determined that there is no physical activity of the people within the measurement range during the consecutive periods among the multiple periods, estimates the maximum value of the cluster number as the number of the people within the measurement range.

9. The processing device according to claim 7, wherein: The processing device includes an abnormality detection unit configured to detect an abnormality in a vital sign of at least one of the people within the measurement range based on the estimated number of people and the number of clusters.

10. The processing device according to claim 9, wherein The body activity determination unit determines whether or not the body activity of the person within the measurement range occurs in each of the plurality of periods. The number estimation unit estimates the number of the persons within the measurement range in each of the plurality of periods, and estimates the maximum value of the number of clusters as the number of the persons within the measurement range for a period in which it is determined that there is no physical activity of the persons within the measurement range in a continuous period among the plurality of periods. The abnormality detection unit determines, as a period during which the abnormality in the vital sign of the person has occurred, a period during which it is determined that there is no physical activity of the person within the measurement range and during which the number of clusters is smaller than the maximum value, among the continuous periods.

11. The processing device according to claim 7, wherein The processing device includes an abnormality detection unit configured to detect an abnormality in a vital sign of at least one of the persons within the measurement range. The body activity determination unit determines whether or not the body activity of the person within the measurement range occurs in each of the plurality of periods. The number estimation unit estimates the number of the persons within the measurement range in each of the plurality of periods, and estimates the maximum value of the number of clusters as the number of the persons within the measurement range for a period in which it is determined that there is no physical activity of the persons within the measurement range in a continuous period among the plurality of periods. The abnormality detection unit determines whether the vital sign abnormality has occurred in at least one of the persons within the measurement range based on the vital sign signal in the period immediately before the period in the continuous period during which it is determined that there is no physical activity of the person within the measurement range and the cluster number is smaller than the maximum value.

12. A processing method is a processing method performed by a processing device, The processing method has the following features: a signal acquisition step of acquiring a vital sign signal from a signal reflected by at least one person within a measurement range; an index calculation step of calculating a vital sign index representing a vital sign status of at least one of the persons based on the vital sign signal; a body activity determination step of determining whether there is any body activity of the person within the measurement range; a number estimation step of estimating the number of the persons within the measurement range; a number of people change determining step of determining whether there is a possibility of a change in the estimated number of people when it is determined that the physical movement of the person within the measurement range occurs; as well as A calculation step is to calculate the time series data of the vital sign indicators for each person, The calculation step includes: when it is determined that there is a possibility of a change in the estimated number of people, separately calculating the time series data of the vital sign indicators before it is determined that there is a possibility of a change in the estimated number of people, and the time series data of the vital sign indicators after it is determined that there is a possibility of a change in the estimated number of people.

13. A program for causing a computer to execute the following steps: a signal acquisition step of acquiring a vital sign signal from a signal reflected by at least one person within a measurement range; an index calculation step of calculating a vital sign index representing a vital sign status of at least one of the persons based on the vital sign signal; a body activity determination step of determining whether there is any body activity of the person within the measurement range; a number estimation step of estimating the number of the persons within the measurement range; a number of people change determining step of determining whether there is a possibility of a change in the estimated number of people when it is determined that the physical movement of the person within the measurement range occurs; as well as A calculation step is to calculate the time series data of the vital sign indicators for each person, The calculation step includes: when it is determined that there is a possibility of a change in the estimated number of people, separately calculating the time series data of the vital sign indicators before it is determined that there is a possibility of a change in the estimated number of people, and the time series data of the vital sign indicators after it is determined that there is a possibility of a change in the estimated number of people.

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