Health risk estimation system

Abstract

To provide a health risk estimation system with which it is possible to suitably estimate the health risk of a subject.SOLUTION: The health risk estimation system comprises: a subject detection sensor 110 capable of detecting the motion of a subject; an action estimation unit capable of estimating an action of the subject on the basis of the detection result of the subject detection sensor 110; a subject detection sensor 110 capable of detecting information on the blood pressure of the subject before and after the action; a blood pressure change data acquisition unit for acquiring blood pressure change data that indicates a change of the blood pressure of the subject before the action and a change of the blood pressure of the subject after the action, on the basis of the detection result of the subject detection sensor 110; and a health risk estimation unit capable of estimating health risks of the subject on the basis of the result of comparison between first blood pressure change data representing blood pressure change data at a first time and second blood pressure change data that is of a time earlier than the first time and is a blood pressure change data representing an action similar to the action of the first blood pressure change data.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to the technology of a health risk estimation system.

Background Art

[0002] Conventionally, the technology of a system for estimating the health risk (health risk) of a subject has been known. For example, it is as described in Patent Document 1.

[0003] Patent Document 1 discloses a technique for estimating the blood pressure fluctuation value of an analysis subject based on the indoor temperature difference and analyzing the health risk of the analysis subject based on the blood pressure fluctuation value. According to the invention described in Patent Document 1, it is possible to show the health risk associated with the change in the indoor temperature environment.

[0004] However, blood pressure fluctuates under various influences. In the invention described in Patent Document 1, since the factors of blood pressure fluctuation other than the indoor temperature environment are not considered, it is assumed that it is difficult to suitably estimate the health risk of the subject.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] The present invention has been made in view of the above circumstances, and the problem to be solved is to provide a health risk estimation system capable of suitably estimating the health risk of a subject.

Means for Solving the Problems

[0007] The problem to be solved by the present invention is as described above. Next, the means for solving this problem will be described.

[0008] That is, in claim 1, there are provided an action detection unit capable of detecting the actions of the subject, an action estimation unit capable of estimating the behavior of the subject based on the detection result of the action detection unit, a blood pressure detection unit capable of detecting information regarding the blood pressure of the subject before and after the action, a blood pressure variability data acquisition unit that acquires blood pressure variability data indicating the fluctuations between the blood pressure of the subject before the action and the blood pressure of the subject after the action based on the detection result of the blood pressure detection unit, a first blood pressure variability data which is the blood pressure variability data at a first time, and a health risk estimation unit capable of estimating the health risk of the subject based on the comparison result between the first blood pressure variability data and second blood pressure variability data which is the blood pressure variability data of an action similar to the action of the first blood pressure variability data and is from a time earlier than the first time.

[0009] In claim 2, the action includes a plurality of types of specific actions set according to the assumed actions of the subject, and the blood pressure variability data acquisition unit can acquire the blood pressure variability data indicating the fluctuations between the blood pressure of the subject before the specific action and the blood pressure of the subject after the specific action.

[0010] In claim 3, when the action estimation unit detects at least one of the movement of the subject to a preset specific area and the change in the posture of the subject in the specific area based on the detection result of the action detection unit, the action estimation unit can estimate that the subject has performed the specific action.

[0011] In claim 4, the blood pressure detection unit can detect information regarding the blood pressure of the subject in a non-contact manner.

[0012] In claim 5, the blood pressure detection unit and the action detection unit are a common device.

[0013] In claim 6, a time information acquisition unit capable of acquiring time information regarding the movement of the subject detected by the movement detection unit is provided, and the action estimation unit estimates the action of the subject based on the detection result of the movement detection unit and the acquisition result of the time information acquisition unit.

Effect of the Invention

[0014] As an effect of the present invention, the following effects are achieved.

[0015] In the present invention, the health risk of the subject can be suitably estimated.

Brief Description of the Drawings

[0016]

Figure 1

Figure 2

Figure 3

Figure 4

Mode for Carrying Out the Invention

[0017] Hereinafter, a health risk estimation system 100 according to an embodiment of the present invention will be described with reference to FIG. 1.

[0018] The health risk estimation system 100 can estimate the health risk of a subject. The "health risk" in the present embodiment refers to a health risk that can be estimated from the health of blood vessels, such as the onset risk of a disease related to blood vessels. First, an example of the subject assumed in the present embodiment and the room 1 of the subject will be described.

[0019] In this embodiment, the person for whom the health risk is estimated by the health risk estimation system 100 (hereinafter referred to as the "subject") is assumed to be an elderly person. Further, in this embodiment, it is assumed that the health risk estimation system 100 is applied to Room 1 where the subject lives in an elderly care facility.

[0020] FIG. 1 shows an example of the subject's Room 1. In Room 1, a bed 10, a dining table 20, dining chairs 30, a toilet 40, a bathtub 50, a kitchen 60, an entrance / exit 70, etc. are installed. The entrance / exit 70 is the entrance / exit of Room 1. The spaces where the toilet 40 and the bathtub 50 are arranged are partitioned from other spaces by a partition wall 41. Note that a washstand (not shown) is arranged in the space where the bathtub 50 is arranged. The partition wall 41 is provided with an entrance / exit for entering and exiting the toilet 40 and the bathtub 50. Although the wall partitioning the space where the toilet 40 is arranged and the space where the bathtub 50 is arranged is not shown in the illustrated example, a wall may be provided to partition each of the above spaces. The configuration of Room 1 is not limited to that described above, and various spaces such as a study or a sofa area (a space where a sofa etc. is arranged) can be arranged.

[0021] Next, the configuration of the health risk estimation system 100 will be described. The health risk estimation system 100 mainly includes a subject detection sensor 110, a staff terminal 120, and a server 130.

[0022] The subject detection sensor 110 is for detecting the position, posture, and blood pressure of the subject. The subject detection sensor 110 is a non-contact sensor. In this embodiment, a millimeter-wave sensor is used as the subject detection sensor 110. The subject detection sensor 110 irradiates an object with millimeter waves (radio waves having a wavelength of 1 to 10 mm and a frequency of 30 to 300 GHz) and observes the reflected radio waves, thereby measuring the position, speed, angle, movement, etc. of the object.

[0023] In this embodiment, the subject detection sensor 110 is installed at a position (such as the ceiling or wall) in Room 1 where radio waves can be irradiated over the entire area of Room 1. In this embodiment, an example is shown in which the entire area of Room 1 is detected by one subject detection sensor 110, but a plurality of subject detection sensors 110 may be used as necessary.

[0024] The staff terminal 120 is for notifying the estimation results and the like by the health risk estimation system 100. As the staff terminal 120, for example, a personal computer can be used. The staff terminal 120 is installed in a place where a person who assists (assists, cares for, etc.) the subject's life can confirm it. In this embodiment, for example, it can be arranged in the cubicle of the staff of a senior facility. By displaying various information on the monitor of the staff terminal 120, the information can be notified to the staff. Note that various other devices (such as portable terminals, etc.) can also be used as the staff terminal 120.

[0025] The server 130 is for performing processing for estimating the health risk by the health risk estimation system 100. The server 130 is constituted by, for example, a cloud server. The server 130 can exchange information with the subject detection sensor 110 and the staff terminal 120.

[0026] Server 130 can determine the position and posture of the target person based on the data obtained by the target person detection sensor 110. Specifically, Server 130 can determine that among the point cloud data obtained based on the reflected radio waves, the data with movement is a person (in this embodiment, the target person). In particular, in this embodiment, since a millimeter-wave sensor is used, even the minute movements of the target person can be accurately detected. Server 130 extracts only the data with movement and can determine the position of the data in Room 1 as the position of the target person (each area described later). Also, Server 130 extracts only the data with movement and can determine the posture of the target person, such as standing (standing position), sitting (sitting position), lying down (lying position), etc., by checking its distribution.

[0027] In addition, Server 130 can measure the blood pressure of the target person based on the data obtained by the target person detection sensor 110. Specifically, Server 130 acquires data on the human heartbeat waveform based on the data indicating the movement of the target person's body (such as the movement of the heart and pulse, etc.) obtained by the reflected radio waves. Also, Server 130 detects a feature amount correlated with blood pressure from the data of the heartbeat waveform and calculates an estimated value (measured value) of blood pressure based on the detection result. As the above-mentioned estimated value of blood pressure, values such as systolic blood pressure, diastolic blood pressure, and mean blood pressure can be adopted, for example. Hereinafter, the estimated value of blood pressure calculated as described above is referred to as "blood pressure data".

[0028] Server 130 stores in advance the position information of areas obtained by dividing Room 1 into a plurality of parts. In FIG. 1, an example is shown in which a bed area A, a dining area B, a toilet area C, a bathroom area D, a kitchen area E, another area F, and an outdoor area G are set according to the arrangement of furniture and the like.

[0029] The bed area A is the area (bedroom) where the bed 10 is placed. The bed area A is set to be, for example, a range that is slightly larger than the bed 10 in plan view. Similarly, a dining area B is set in the area where the dining table 20 and the dining chairs 30 are placed. Also, a kitchen area E is set in the area where the kitchen 60 is placed. The toilet area C and the bathroom area D (washroom) are within the range surrounded by the partition wall 41 and are set in the range where the toilet 40 and the bathtub 50 are placed. Among the areas of Room 1, the areas other than the bed area A, the dining area B, the toilet area C, the bathroom area D, and the kitchen area E are set as other area F. Also, the area outside the entrance 70 is set as the outdoor area G. Note that the above areas are examples, and in addition to the areas A to G described above, it is possible to arbitrarily set areas (for example, a study or a sofa area, etc.) according to the furniture and the like placed in Room 1.

[0030] The server 130 can estimate the actions of the subject based on information (location information, etc.) of the area where the subject is located. More specifically, the server 130 performs the estimation of actions based on, in addition to the location information of the subject, data on the posture of the subject, time (the time when the subject is located in a predetermined area), information such as the stay time in the area, etc.

[0031] Figure 2 is a table showing the relationship between the area where the subject is located and the actions of the subject. In the server 130, several types of actions (for example, "going to bed", etc.) shown in the above table are set according to the actions (for example, taking a lying posture in the bed area A, etc.) assumed from information such as the location information and posture data of the subject. When the server 130 detects the above actions, it estimates that the actions corresponding to the actions have been performed. Hereinafter, an example of a method for the server 130 to estimate the actions of the subject will be described using the above table.

[0032] When the target person is located in the bed area A (bedroom), the server 130 presumes that the target person's action is either "going to bed" or "in bed". For example, when the server 130 detects the target person in the bed area A at the preset bedtime in the schedule, and the target person's posture is a lying position, the server 130 presumes that the target person is about to go to bed (the target person's action is "going to bed"). Also, for example, after "going to bed", when the server 130 detects that the target person has been in the lying position for a predetermined period or more, the server 130 presumes that the target person is "in bed".

[0033] In addition, when the target person is located in the toilet area C, the server 130 presumes that the target person's action is either "urination" or "defecation". More specifically, when the detection of the target person by the target person detection sensor 110 becomes impossible at the entrance of the toilet area C, the server 130 determines that the target person is located in the toilet area C (is in the toilet). When the detection of the target person resumes thereafter, the server 130 determines that the target person has come out of the toilet area C. For example, when the target person's staying time in the toilet (the period from entering the toilet area C to coming out) is less than a preset period, the server 130 presumes that the target person's action is "urination". When the target person's staying time in the toilet is equal to or more than the above period, the server 130 presumes that the target person's action is "defecation".

[0034] Also, when the target person is located in the study (not shown), the server 130 presumes that the target person's action is either "working" or "hobby". For example, when the target person's staying time in the study (the time in the study) is less than a preset period, the server 130 presumes that the target person's action is "hobby". When the target person's staying time in the study is equal to or more than the above period, the server 130 presumes that the target person's action is "working".

[0035] In addition, when the target person is located in the kitchen area E, the server 130 presumes that the target person's action is either "cooking" or "washing dishes". For example, when the server 130 detects that the target person is located in the kitchen area E before a preset meal time, it presumes that the target person's action is "cooking", and when it detects that the target person is located in the kitchen area E after the meal time, it presumes that the target person's action is "washing dishes".

[0036] In addition, when the target person is located in the bathroom area D, the server 130 presumes that the target person's action is either "taking a bath" or "washing face". More specifically, at the entrance of the bathroom area D, when the detection of the target person by the target person detection sensor 110 becomes impossible, the server 130 determines that the target person is located in the bathroom area D (entering the bathroom (washroom)), and when the detection of the target person resumes thereafter, it determines that the target person has exited the bathroom area D. For example, when the staying time of the target person in the bathroom (washroom) (the period from entering to exiting the bathroom area D) is less than a preset period, the server 130 presumes that the target person's action is "washing face", and when the staying time of the target person in the toilet is equal to or more than the above period, the server 130 presumes that the target person's action is "taking a bath".

[0037] In addition, when the target person is located in the dining area B, the server 130 presumes that the target person's action is either "eating", "resting", or "watching TV". For example, when the server 130 detects that the target person is located in the dining area B at a preset meal time, it presumes that the target person's action is "eating". Also, for example, when the staying time of the target person in the dining area B is less than a preset period, the server 130 presumes that the target person's action is "resting", and when the staying time of the target person in the dining area B is equal to or more than the above period, the server 130 presumes that the target person's action is "watching TV".

[0038] In addition, even when the subject is located in the sofa area (not shown), the server 130 can presume that the subject's action is either "eating", "resting", or "watching TV". For example, when the server 130 detects that the subject is located in the sofa area at a preset meal time, it presumes that the subject's action is "eating". Also, for example, when the subject's staying time in the sofa area is less than a preset period, the server 130 presumes that the subject's action is "resting", and when the subject's staying time in the sofa area is equal to or more than the above period, the server 130 presumes that the subject's action is "watching TV".

[0039] In addition, when the subject is located in the outdoor area G, the server 130 presumes that the subject's action is "going out". More specifically, when the server 130 no longer detects the subject at the entrance / exit 70, it presumes that the subject is located in the outdoor area G (the subject's action is "going out").

[0040] Note that the above-described method for presuming the subject's action is just an example, and the method for presuming the subject's action is not limited to the above-described example. Specifically, the subject's action may be presumed using any of the staying time in the area, the current time, and the information of the calendar (schedule). In addition to the above-described example, the server 130 can presume the subject's action by various methods using the data obtained by the subject detection sensor 110.

[0041] Hereinafter, an outline of the process of presuming the health risk of the subject by the health risk estimation system 100 configured as described above will be described.

[0042] The health risk estimation system 100 observes the fluctuation of the subject's blood pressure by using the data of the subject's blood pressure obtained by the subject detection sensor 110, and estimates the health of the subject's blood vessels. Here, the "fluctuation of blood pressure" is the difference between the subject's blood pressure at a certain time and the subject's blood pressure thereafter. In the present embodiment, the difference between the subject's blood pressure before performing a certain action and the subject's blood pressure after performing the above action is observed as the "fluctuation of blood pressure".

[0043] When the range of fluctuations in the blood pressure of the subject is larger than the range of fluctuations in the previous blood pressure, there may be an increased health risk such as hardening of the blood vessels. Here, blood pressure fluctuates under various influences. For this reason, it has been difficult to estimate the health of blood vessels simply by looking at only the information on fluctuations in blood pressure.

[0044] Therefore, the health risk estimation system 100 according to the present embodiment preferably estimates the health of blood vessels by comparing the range of fluctuations in blood pressure (the range of fluctuations in blood pressure this time) when a certain action is performed with the range of fluctuations in blood pressure (the range of fluctuations in previous blood pressure) when the same action as the above action was performed previously. Hereinafter, a specific description of the processing by the health risk estimation system 100 will be given with reference to FIGS. 3 and 4. The health risk estimation system 100 executes the processing shown in FIGS. 3 and 4 (the "blood pressure monitoring process" and the "pre-action estimation process").

[0045] Hereinafter, first, the "blood pressure monitoring process" shown in the flowchart of FIG. 3 will be described. The blood pressure monitoring process is, for example, executed constantly.

[0046] In the blood pressure monitoring process, the server 130 acquires the blood pressure data of the subject (at the time of execution of step S101) based on the data obtained by the subject detection sensor 110 (step S101). By executing the process of step S101, the server 130 can acquire the blood pressure data before the subject performs an action (a specific action estimated in the "pre-action estimation process" described later).

[0047] Next, the server 130 proceeds to the "pre-action estimation process" shown in FIG. 4 (step S102). Hereinafter, the "pre-action estimation process" will be described with reference to the flowchart of FIG. 4.

[0048] In the pre-action estimation process, the server 130 detects changes in the movement and posture of the target person based on the data obtained by the target person detection sensor 110, and acquires the position information of the target person (step S201). Each of the acquired data is stored by the server 130. Next, the server 130 determines whether the target person has moved to a specific area (specific area) based on the position information (step S202). In the present embodiment, as the specific area, each area shown in FIG. 2 (for example, the bed area A, the dining area B, the toilet area C, the bathroom area D, etc.) is adopted. When the server 130 determines that the target person has not moved to the specific area (step S202: NO), the server 130 determines whether the posture of the target person has changed (step S203). When the server 130 detects based on the data obtained by the target person detection sensor 110 that the target person has changed the posture from a certain posture (for example, sitting position) to another posture (for example, lying position), the server 130 determines that "the posture of the target person has changed".

[0049] When the server 130 determines that the posture of the target person has not changed (step S203: NO), that is, when it is determined that the target person has neither moved to the specific area nor changed the posture, the process proceeds to the process of step S201. On the other hand, when the server 130 determines that the target person has moved to the specific area or the posture has changed (step S202: YES, step S203: YES), the process proceeds to the process of step S204.

[0050] In the processes from step S204 to step S206, the server 130 acquires the stay time of the area where the target person is located, the current time, and the information of the calendar (schedule) (steps S204, S205), and determines whether it is possible to estimate the specific actions of the target person (step S206). Here, the "specific actions" refer to actions that can be specified in a specific area. As the "specific actions", actions that can significantly detect fluctuations in the blood pressure of the target person in the processes described later (blood pressure monitoring processes) can be adopted. In this embodiment, a plurality of types of specific actions are set according to the assumed actions of the target person. More specifically, in this embodiment, as the above specific actions, each action shown in FIG. 2 (for example, "going to bed" or "excretion", etc.) is adopted. If the actions of the target person based on the information detected in step S202 or step S203 correspond to each action shown in the table of FIG. 2, it is estimated that the target person has performed a specific action. The server 130 determines that "it is possible to estimate the specific actions of the target person" when the information necessary for the estimation of the above specific actions (such as the information acquired in steps S204 and S205) is complete.

[0051] If the server 130 determines in step S206 that it is possible to estimate the specific actions of the target person, based on each information acquired in steps S201, S204, and S205 (information such as the position information, posture, time, and stay time of the area of the target person), the server 130 estimates the specific actions of the target person and outputs the action estimation result (step S207), and then proceeds to step S103 of the "blood pressure monitoring process" (step S208).

[0052] Also, if the server 130 determines in step S206 that it is impossible to estimate the specific actions of the target person, since the estimation of the specific actions of the target person is impossible, after processing with no specific actions (steps S209, S210), the server 130 proceeds to step S103 of the "blood pressure monitoring process" (step S208). When the server 130 proceeds to step S103 of the blood pressure monitoring process, the pre-action estimation process ends.

[0053] Next, in step S103 of the blood pressure monitoring process shown in FIG. 3, the server 130 determines whether or not there has been a specific action of the subject. That is, the server 130 determines whether or not there has been the specific action (step S207) estimated in the pre-action estimation process. If the server 130 determines that there has been no specific action (step S103: NO), it proceeds to the process of step S101.

[0054] If the server 130 determines in step S103 that there has been a specific action (step S103: YES), the server 130 acquires the blood pressure data of the subject (at the time of execution of step S104) based on the data obtained by the subject detection sensor 110 (step S104). By executing the process of step S104, the server 130 can acquire the blood pressure data after the subject has performed the specific action (resume the acquisition of blood pressure data).

[0055] Next, the server 130 calculates a value indicating the width of the blood pressure fluctuation of the subject associated with the specific action (hereinafter, the above value is referred to as "blood pressure variability data") by comparing the blood pressure data before the specific action (the blood pressure data acquired in step S101) with the blood pressure data after the specific action (the blood pressure data acquired in step S104) (step S105). Specifically, the server 130 subtracts the blood pressure data before the specific action from the blood pressure data after the specific action.

[0056] Next, the server 130 collates the blood pressure variability data obtained in step S105 with the subject's pre-action (specific action determined in step S103) (step S106). Next, the server 130 compares the blood pressure variability data (current blood pressure variability data) obtained in step S105 with the previous blood pressure variability data (step S107). More specifically, the server 130 extracts from the data stored by the server 130 so far the blood pressure variability data that is the same as the current blood pressure variability data and the specific action, and compares the current blood pressure variability data with the previous blood pressure variability data (extracted) that is the comparison target. As the blood pressure variability data (previous blood pressure variability data) to be compared, blood pressure variability data a predetermined period before (for example, one day before, one week before, one month before, one year before, etc.) can be adopted based on the time when the current blood pressure variability data was obtained. Also, as the blood pressure variability data to be compared, data indicating the average value, median value, etc. of the blood pressure variability data within a predetermined period (for example, in the past one year, etc.) can also be adopted.

[0057] Next, the server 130 evaluates the health of the subject's blood vessels based on the comparison result between the current blood pressure variability data in step S206 and the previous blood pressure variability data (step S108). The server 130 evaluates the health of the subject's blood vessels, for example, using the value obtained by subtracting the previous blood pressure variability data from the current blood pressure variability data. When the value obtained by the above calculation is relatively large, it is shown that the current range of blood pressure fluctuations is larger than in the past. The server 130 can evaluate (estimate) that the health of the subject's blood vessels is low and thus the health risk is high if, for example, the value obtained by the above calculation is equal to or greater than a predetermined reference value. Also, the server 130 can display the above evaluation result on the staff terminal 120. After executing the process of step S206, the server 130 ends the blood pressure monitoring process.

[0058] According to the health risk estimation system according to the present embodiment as described above, by comparing the blood pressure variability data (the current blood pressure variability data) when a certain specific action is performed with the blood pressure variability data (the previous blood pressure variability data) when a specific action similar to the above specific action was performed previously, the health of the blood vessels of the subject can be preferably estimated. That is, when a similar specific action (for example, "defecation (large)") is performed, it is considered that the amount of blood discharged accompanying the above specific action is generally the same. In this case, when the width of the blood pressure fluctuation accompanying the above specific action is larger than in the past, it is estimated that the pressure applied to the blood vessels has increased due to the hardening of the blood vessels, and thus it is estimated that the health of the blood vessels is low (the health risk is high). Thus, in the present embodiment, by comparing the blood pressure variability data when the same specific action is performed, the health risk can be preferably estimated.

[0059] As described above, the health risk estimation system 100 according to the present embodiment An action detection unit (subject detection sensor 110) capable of detecting the actions of the subject, An action estimation unit (server 130) capable of estimating the actions of the subject (steps S201 to S207) based on the detection result of the subject detection sensor 110, A blood pressure detection unit (subject detection sensor 110) capable of detecting information regarding the blood pressure of the subject (for example, information on the heartbeat waveform) (steps S101, S104) before and after the action, A blood pressure variability data acquisition unit (server 130) that acquires blood pressure variability data indicating the fluctuations between the blood pressure of the subject before the action and the blood pressure of the subject after the action based on the detection result of the subject detection sensor 110 (step S105), A health risk estimation unit (server 130) capable of estimating the health risk of the subject (step S108) based on the comparison result between the first blood pressure variability data, which is the blood pressure variability data at the first time, and the second blood pressure variability data, which is the blood pressure variability data of an action similar to the action of the first blood pressure variability data and is from before the first time, It is equipped with.

[0060] By configuring in this way, the health risk can be suitably estimated. That is, by comparing the current and past blood pressure variability data when similar actions are taken by each other, the health of blood vessels can be suitably estimated.

[0061] In addition, the actions include a plurality of types of specific actions set according to the assumed actions of the subject. The blood pressure variability data acquisition unit (server 130) is capable of acquiring the blood pressure variability data indicating the variation between the information on the blood pressure of the subject before the specific action and the blood pressure of the subject after the specific action.

[0062] By configuring in this way, based on the blood pressure variability data associated with the specific action, the health risk of the subject can be more suitably estimated. That is, even if the variation in blood pressure cannot be detected by one specific action, there may be a case where the variation in blood pressure can be detected by other specific actions, so the health risk of the subject can be more suitably estimated.

[0063] In addition, the action estimation unit (server 130) when at least one of the movement of the subject to a preset specific area and the change in the posture of the subject in the specific area is detected based on the detection result of the subject detection sensor 110 (step S202: YES, step S203: YES), it is possible to estimate that the subject has performed the specific action.

[0064] By configuring in this way, it is possible to suitably determine that the subject has performed the specific action.

[0065] In addition, the blood pressure detection unit (subject detection sensor 110) is capable of detecting the blood pressure of the subject non - contact.

[0066] By configuring in this way, the burden on the subject when measuring blood pressure can be reduced.

[0067] In addition, the blood pressure detection unit and the motion detection unit are a common device (subject detection sensor 110).

[0068] By configuring in this way, both the motion and blood pressure of the subject can be detected using the common subject detection sensor 110, so the configuration of the health risk estimation system 100 can be simplified.

[0069] In addition, the health risk estimation system 100 according to this embodiment includes a time information acquisition unit (server 130) capable of acquiring time information regarding the motion of the subject detected by the subject detection sensor 110, The action estimation unit estimates the action of the subject based on the detection result of the subject detection sensor 110 and the acquisition result of the time information acquisition unit (server 130) (steps S204 to S207).

[0070] By configuring in this way, the action of the subject can be estimated in consideration of the time (time of day and stay time) related to the motion of the subject.

[0071] Note that the subject detection sensor 110 according to this embodiment is a form of the motion detection unit and the blood pressure detection unit according to the present invention. In addition, the server 130 according to this embodiment is an implementation form of the action estimation unit, the blood pressure variability data acquisition unit, and the health risk estimation unit according to the present invention.

[0072] As described above, one embodiment of the present invention has been described, but the present invention is not limited to the above configuration, and various modifications are possible within the scope of the invention described in the claims. For example, each process executed by the health risk estimation system 100 is not limited to those described above and can be arbitrarily changed.

[0073] In addition, in this embodiment, an example in which both the actions and blood pressure of the target person are detected using the target person detection sensor 110 has been shown. However, the present invention is not limited to this, and an apparatus for detecting the actions of the target person and an apparatus for detecting the blood pressure of the target person may be provided separately.

[0074] Further, in this embodiment, an example in which the target person detection sensor 110 that non - contact detects information related to the blood pressure of the target person is adopted as the blood pressure detection unit has been shown. However, the present invention is not limited to this. For example, as the blood pressure detection unit, one that detects the blood pressure of the target person in a state of being in contact with the body of the target person, such as a wearable device, may be adopted.

[0075] Also, in this embodiment, an example in which data of a heartbeat waveform is adopted as an example of the "information related to blood pressure" detected using the blood pressure detection unit (target person detection sensor 110) has been shown. However, the present invention is not limited to this. As the information related to blood pressure, various data having a feature amount correlated with blood pressure can be adopted. Further, instead of the mode of indirectly detecting the blood pressure of the target person using the data having the feature amount correlated with blood pressure as described above, a mode of directly detecting the value of the blood pressure of the target person as the "information related to blood pressure" can also be adopted. In this case, as the blood pressure detection unit, an apparatus capable of measuring the value of the blood pressure of the target person can be adopted.

[0076] In addition, in this embodiment, each area (bed area A, dining area B, toilet area C, bathroom area D, etc.) shown in FIG. 2 has been exemplified as the specific area. However, the present invention is not limited to this. For example, among the above - mentioned areas, only the areas (toilet area C and bathroom area D) partitioned by the partition wall 41 may be set as the specific area. According to this, based on whether the target person can be detected by the target person detection sensor 110, it is possible to preferably determine that the target person is located in the above - mentioned area and the staying time in the above - mentioned area.

[0077] In addition, in the present embodiment, each action shown in FIG. 2 (such as "going to bed" and "urination (small)") is exemplified as the specific action, but the present invention is not limited thereto. As the specific action, various actions that can be estimated based on information such as the position information and posture data of the target person can be adopted.

[0078] In addition, in the present embodiment, an example in which the health risk estimation system 100 is applied to Room 1 of the elderly facility is shown, but the present invention is not limited thereto, and it can be applied to various other facilities, houses, etc.

[0079] In addition, in the present embodiment, the target person detection sensor 110 (millimeter wave sensor) is exemplified as the detection unit that detects the position and posture of the target person, but the present invention is not limited thereto, and various sensors that can detect the posture, blood pressure, etc. of the target person can also be used.

[0080] In addition, in the present embodiment, an example in which various processes are executed by the server 130 is shown, but the present invention is not limited thereto, and various processes can also be executed using the staff terminal 120 and various other devices (personal computers, tablet terminals, etc.).

Description of Reference Numerals

[0081] 1 Room 100 Health Risk Estimation System 110 Target Person Detection Sensor 120 Staff Terminal 130 Server

Claims

1. An action detection unit capable of detecting the actions of a subject, An action estimation unit capable of estimating the actions of the subject based on the detection results of the action detection unit, A blood pressure detection unit capable of detecting information regarding the blood pressure of the subject before and after the action, A blood pressure variability data acquisition unit that acquires blood pressure variability data indicating the fluctuations between the blood pressure of the subject before the action and the blood pressure of the subject after the action based on the detection results of the blood pressure detection unit, A health risk estimation unit capable of estimating the health risk of the subject based on the comparison result between first blood pressure variability data, which is the blood pressure variability data at a first time, and second blood pressure variability data, which is the blood pressure variability data of an action similar to the action of the first blood pressure variability data and is from a time earlier than the first time, A health risk estimation system comprising the above.

2. The actions include a plurality of types of specific actions set according to the assumed actions of the subject, The blood pressure variability data acquisition unit Is capable of acquiring the blood pressure variability data indicating the fluctuations between the blood pressure of the subject before the specific action and the blood pressure of the subject after the specific action, The health risk estimation system according to Claim 1.

3. The action estimation unit When at least one of the movement of the subject to a preset specific area and the change in the posture of the subject in the specific area is detected based on the detection results of the action detection unit, it is possible to estimate that the subject has performed the specific action, The health risk estimation system according to Claim 2.

4. The blood pressure detection unit Is capable of detecting information regarding the blood pressure of the subject in a non-contact manner, The health risk estimation system according to Claim 1.

5. The blood pressure detection unit and the action detection unit are a common device, The health risk estimation system according to Claim 1.

6. Comprises a time information acquisition unit capable of acquiring information regarding the time of the action of the subject detected by the action detection unit, The action estimation unit Estimates the action of the subject based on the detection results of the action detection unit and the acquisition results of the time information acquisition unit, The health risk estimation system according to any one of Claims 1 to 5.

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