Health condition notification system, health condition notification program, and health condition notification method

Abstract

To provide a health condition notification system and a health condition notification program for efficiently acquiring information, and for improving the quality of information. And a health condition notification method.SOLUTION: The health-condition notification system 1 according to an embodiment notifies the health condition of a participant who is a person involved in a device. A health condition notification system 1 includes a sensor 10 that is provided at a position away from an apparatus and acquires physical information that is information on a body of a participant, an analysis unit 24 that receives the physical information from the sensor 10, analyzes the physical information, and determines whether or not it is preferable for the participant to be involved in the apparatus, and a notification unit 25 that notifies a result analyzed by the analysis unit 24. When the participant is not involved in the apparatus, the sensor 10 acquires the physical information, the analysis unit 24 performs the determination, and the notification unit 25 notifies the result.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a health condition notification system, a health condition notification program, and a health condition notification method for notifying a participant involved in a device of the health condition of the participant. [Background technology]

[0002] Patent Document 1 describes a drowsiness prevention information presentation device that presents a self-improvable sleep schedule and biological rhythm adjustment method tailored to the individual characteristics of railway drivers. The drowsiness prevention information presentation device accepts input of sleeping hours from the driver and accepts input of answers to questions from the driver regarding drowsiness, physical fatigue, and mental fatigue.

[0003] After receiving the above responses, the drowsiness prevention information presentation device reads the driver's lifestyle history information for the past 10 days and calculates the driver's sleep characteristics, biological rhythms, and sleep debt for only work days or only rest days.The drowsiness prevention information presentation device determines whether there is a problem with the driver's sleep situation based on the sleep characteristics, biological rhythms, and sleep debt, and if it determines that there is a problem, it displays details of the determination result and improvement methods on the display unit. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2007-164366 Summary of the Invention [Problem to be solved by the invention]

[0005] In the above-mentioned drowsiness prevention information providing device, the driver must input answers to questions about sleep time, drowsiness, and physical and mental fatigue. Therefore, there is a problem that the information cannot be acquired efficiently. Furthermore, when the driver is asked to input answers, it is possible that the input information is different from the actual information, so there is room for improvement in terms of the quality of the information.

[0006] The present disclosure aims to provide a health condition notification system, a health condition notification program, and a health condition notification method that can efficiently acquire information and improve the quality of the information. [Means for solving the problem]

[0007] (1) A health status notification system according to the present disclosure notifies the health status of a participant who is involved with a device. The health status notification system includes a sensor located away from the device and acquiring physical information about the participant's body, an analysis unit that receives the physical information from the sensor, analyzes the physical information, and determines whether it is desirable for the participant to be involved with the device, and a notification unit that notifies the results of the analysis by the analysis unit. When the participant is not involved with the device, the sensor acquires the physical information, the analysis unit makes a determination, and the notification unit notifies the result.

[0008] This health status notification system includes a sensor located away from the device, an analysis unit that determines whether it is desirable for a participant to be involved with the device based on physical information from the sensor, and a notification unit that notifies the results of the analysis by the analysis unit. The sensor acquires physical information of the participant involved with the device, and the physical information is analyzed by the analysis unit. Therefore, inputting answers to questions is unnecessary, thereby efficiently acquiring physical information and improving the quality of the acquired physical information. The acquisition of physical information by the sensor, the determination by the analysis unit, and the notification of the results by the notification unit are performed when the participant is away from the device and not involved with the device. Therefore, by notifying the results by the notification unit before the participant is involved with the device, accidents caused by participants who are not desirable to be involved with the device being involved with the device can be prevented. Furthermore, by acquiring physical information by the sensor when the participant is not involved with the device, it is easier to determine whether it is better for the participant not to be involved with the device compared to when physical information is acquired when the participant is involved with the device.

[0009] (2) In the above (1), the sensor may acquire physical information while the participant is sleeping, the analysis unit may make a determination, and the notification unit may notify the result. In this case, the sensor acquires physical information while the participant is sleeping, and this physical information is analyzed by the analysis unit. Therefore, when determining whether or not it is desirable for the participant to be involved with the equipment, various physical information obtained during sleep can be used, thereby improving the accuracy of the above determination.

[0010] (3) In the above (1) or (2), when the participant is not using the equipment and is sitting, the sensor may acquire physical information, the analysis unit may make a determination, and the notification unit may notify the result. In this case, the sensor acquires physical information when the participant is sitting, and this physical information is analyzed by the analysis unit. Therefore, when determining whether it is desirable for the participant to use the equipment, physical information such as posture while sitting can be used, thereby improving the accuracy of the above determination.

[0011] (4) In any of the above (1) to (3), the physical information may include sleep state information that indicates the sleep state of the participant. In this case, when determining whether or not it is desirable for the participant to participate in the device, the sleep state information that indicates how the participant has slept up to now can be used, so that a participant who is not in a good sleep state can be prevented from continuing to participate in the device for a long time.

[0012] (5) In any of the above (1) to (4), the physical information may include autonomic nerve information, which is information indicating the state of the autonomic nerves of the participant. In this case, the autonomic nerve information indicating the state of the autonomic nerves of the participant can be used when determining whether or not it is desirable for the participant to be involved with the equipment. Therefore, it is possible to prevent a participant with an undesirable balance between the sympathetic and parasympathetic nerves from continuing to be involved with the equipment for a long period of time.

[0013] (6) In any of the above (1) to (5), the physical information may include apnea information indicating the apnea state of the participant during sleep. In this case, the apnea information indicating whether or not the participant is experiencing apnea can be used when determining whether or not it is desirable for the participant to participate in the device. Therefore, it is possible to prevent a participant who frequently suffers from sleep apnea from continuing to participate in the device for a long period of time.

[0014] (7) A health status notification program according to the present disclosure notifies the health status of a participant who is involved with a device. The health status notification program causes a computer to execute, when the participant is not involved with the device, the steps of receiving physical information of the participant from a sensor located away from the device, analyzing the physical information, and determining whether it is desirable for the participant to be involved with the device, and notifying the result of the analysis in the determining step.

[0015] This health status notification program includes a step of determining whether it is desirable for a participant to be involved with a device based on physical information from a sensor installed away from the device, and a step of notifying the participant of the determination result. Therefore, since inputting answers to questions is not required, similar to the health status notification system described above, physical information can be acquired efficiently and the quality of the obtained physical information can be improved. The determination of whether it is desirable for a participant to be involved with a device and the notification of the determination result are made when the participant is away from the device and not involved with the device. Therefore, by notifying the result before the participant is involved with the device, similar to the health status notification system described above, accidents caused by a participant who is not desirable to be involved with the device being involved with the device can be prevented.

[0016] (8) A health status notification method according to the present disclosure notifies the health status of a participant who is involved with a device. The health status notification method includes a step of acquiring physical information of the participant using a sensor located away from the device, a step of an analysis unit receiving the physical information from the sensor analyzing the physical information to determine whether it is desirable for the participant to be involved with the device, and a step of a notification unit notifying the result of the analysis in the determination step. The steps of acquiring physical information, determining, and notifying are performed when the participant is not involved with the device.

[0017] In this health status notification method, an analysis unit determines whether it is desirable for a participant to be involved with the equipment based on physical information from a sensor installed at a location remote from the equipment, and the notification unit notifies the result of the analysis by the analysis unit. Because the sensor acquires physical information about the participant involved with the equipment and this physical information is analyzed by the analysis unit, inputting answers to questions is unnecessary. Therefore, similar to the health status notification system described above, physical information can be acquired efficiently and the quality of the acquired physical information can be improved. Therefore, this health status notification method achieves the same effects as the health status notification system described above. [Effects of the Invention]

[0018] According to the present disclosure, it is possible to efficiently acquire information and improve the quality of the information. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 is a block diagram showing the functions of a health condition notification system and a health condition notification program according to the first embodiment. [Figure 2] FIG. 2 is a diagram showing an example of a sensor sheet having sensors according to the first embodiment. [Figure 3] FIG. 3 is a diagram showing a sensor-equipped cushion as an example having a sensor according to the first embodiment. [Figure 4] FIG. 4 is a diagram showing an example of a screen for inputting a sleep state. [Figure 5] FIG. 5 is a diagram showing an example of a notification screen showing the determination result of the health condition of a participant involved in a device. [Figure 6] FIG. 6 is a sequence diagram showing an example of steps of the health condition notification method according to the first embodiment. [Figure 7] FIG. 7 is a diagram showing another example of a notification screen showing the determination result of the health condition of a participant involved in a device. [Figure 8] FIG. 8 is a sequence diagram showing an example of steps of a health condition notification method according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0020] Below, embodiments of the health status notification system, health status notification program, and health status notification method according to the present disclosure will be described with reference to the drawings. In the description of the drawings, identical or corresponding elements are designated by the same reference numerals, and duplicate explanations will be omitted as appropriate. The drawings may be partially simplified or exaggerated for ease of understanding, and the dimensional proportions and the like are not limited to those shown in the drawings.

[0021] In this specification, "health condition" refers to mental and physical state. "Mental and physical" refers to at least one of the mind and body. "Mental and physical state" refers to the mental and physical state of a person involved in a device, and refers to at least one of the mental state, psychological state, mood state, stress level, fatigue level, and autonomic nervous system state, for example. "Notification" refers to informing. "Notification" refers to displaying on the display of a terminal owned by the person to be notified, for example. "Notification" may refer to changing the rate of automatic control of the device, for example.

[0022] "Equipment" refers to at least one of machinery, instruments, and tools. "Equipment" is, for example, a vehicle, heavy machinery, or precision machinery. "Equipment" is, for example, a machine that requires a relatively high level of skill to operate. "Machine" is, for example, a machine that can cause an accident if operated incorrectly. "Vehicle" is a car, train, ship, or aircraft. "Vehicle" is an automobile, bicycle, railroad car, industrial vehicle, or construction vehicle.

[0023] "Involved in equipment" refers to being involved with equipment. "Involved in equipment" refers to, for example, operating equipment or monitoring equipment. "Operating equipment" refers to, for example, driving a vehicle or operating a machine. "Participant" refers to a person involved in equipment. "Participant" refers to, for example, a person who drives a vehicle, operates a machine, or monitors equipment.

[0024] (First embodiment) FIG. 1 is a block diagram showing the configuration of a health condition notification system 1 according to the first embodiment. The health condition notification system 1 is used by operating a terminal T used by a user of the health condition notification system 1. A "user" refers to a person who uses the health condition notification system 1. A "user" may be a participant or a person other than a participant. A "user" may also be an employer of a participant.

[0025] The health condition notification system 1 notifies the health condition of a participant who is a person involved with a device. For example, the health condition notification system 1 includes a terminal T, a sensor 10, and a health condition notification program 20. The terminal T includes, for example, a computer. The health condition notification program 20 is, for example, an application (hereinafter also referred to as an "app") that is installed on the terminal T and can be operated on the terminal T. The type of app is not particularly limited, and may be, for example, a download app downloaded from a server, an SNS (social network service) app, or a communication app.

[0026] Terminal T is, for example, a device capable of executing health condition notification system 1 and health condition notification program 20. Terminal T is, for example, a mobile terminal. A mobile terminal refers to a portable terminal such as a mobile phone including a smartphone, a tablet, a camera, or a laptop. Terminal T may also be a terminal other than a mobile terminal, for example, a personal computer.

[0027] Terminal T includes a processor (e.g., a CPU) that executes an operating system and software (applications), a main memory unit configured with ROM and RAM, an auxiliary memory unit configured with flash memory or the like, a communication control unit configured with a wireless communication module or the like, an input device such as buttons, and an output device such as a display. However, the configuration of terminal T is not limited to the above and can be changed as appropriate. Hereinafter, the main memory unit and the auxiliary memory unit may be collectively referred to as a memory unit.

[0028] In terminal T, for example, a health condition notification program 20 is executed as an application. The health condition notification program 20 is, for example, an application executed in terminal T. However, at least some of the functions of the health condition notification program 20 may be executed by a server external to terminal T.

[0029] The health condition notification program 20 may be downloaded from the server. In the following, an example will be described in which the health condition notification program 20 is an application downloaded to the terminal T and the functions of the health condition notification program 20 are executed on the terminal T.

[0030] Each function of the health condition notification system 1 is realized by loading a health condition notification program 20 into a processor or main memory and executing the health condition notification program 20. The processor operates the communication control unit, input device, or output device described above in accordance with the health condition notification program 20, and reads and writes data from and to the memory. Data used for processing by terminal T is stored in the memory.

[0031] Health condition notification system 1 may be a distributed processing system consisting of multiple computers, or may be a client-server system or a cloud system. Health condition notification program 20 includes, for example, a main module, a data acquisition module, a determination module, and an output module. Execution of the data acquisition module, determination module, and output module causes each functional element of health condition notification program 20 to function.

[0032] For example, the health condition notification program 20 may be provided by being permanently recorded on a tangible storage medium such as a CD-ROM, a DVD-ROM, or a semiconductor memory. The health condition notification program 20 may also be provided via a communication network as a data signal superimposed on a carrier wave.

[0033] The sensor 10 is provided at a location remote from the equipment. "Location remote from the equipment" refers to a location where the participant is not involved with the equipment. "Location remote from the equipment" is, for example, outside a vehicle or away from a machine. "Location remote from the equipment" is, for example, the participant's home. In this case, the sensor 10 is provided at the participant's home. "Location remote from the equipment" may also be an office where the equipment is not provided and where the participant is staying. In this case, the sensor 10 is provided at the office where the participant is staying when not involved with the equipment.

[0034] "When a participant is not involved with the equipment" refers to a time when the participant is not operating or monitoring the equipment. "When a participant is not involved with the equipment" refers to, for example, a time when the participant is not driving a vehicle, a time when the participant is not operating a machine, or a time when the participant is not monitoring the equipment. "When a participant is not involved with the equipment" may be a time when the participant is at home or when the participant is staying in an office where no equipment is installed. "When a participant is not involved with the equipment" may be a time when the participant is sleeping, or a time when the participant is not involved with the equipment and is sitting down.

[0035] An example of the sensor 10 will be described below. The sensor 10 acquires physical information, which is information about the body of a participant. The sensor 10 acquires the physical information when the participant is not involved with the equipment. The physical information is, for example, vital data. The sensor 10 is, for example, at least one of a sensor sheet 11 and a cushion sensor 12.

[0036] FIG. 2 is a schematic diagram showing the sensor sheet 11. The sensor sheet 11 is mounted on the bedding used by the participant. As an example, the sensor sheet 11 is fixed to the cover of the participant's bedding. The sensor sheet 11 may be disposed between the core material and the cover of the participant's bedding.

[0037] The sensor sheet 11 is capable of communicating with the health condition notification program 20. The sensor sheet 11 is, for example, detachable from bedding. The sensor sheet 11 transmits the acquired physical information (vital data) to the health condition notification program 20. The sensor sheet 11 acquires, for example, vital data of the participant lying on the bedding.

[0038] The sensor sheet 11 acquires vital data of the participant while they are sleeping. The vital data includes, for example, at least one of breathing information, heartbeat information, and body movement information of the participant. The breathing information is information indicating the breathing of the participant, the heartbeat information is information indicating the heartbeat of the participant, and the body movement information is information indicating the body movement of the participant.

[0039] The content of the vital data can be changed as appropriate. The vital data may include at least one of information indicating the body temperature of the participant and information indicating the blood glucose level. The vital data may include, for example, information regarding blood pressure. The vital data may include an electrocardiogram.

[0040] The sensor sheet 11 includes, for example, a sheet-like fabric 11b, a sensor unit 11c, and a power supply unit 11d. The sensor unit 11c includes, for example, a thread-like sensor 11f that is embroidered on the sheet-like fabric 11b and detects vital data from the body of a participant placed on the sensor unit 11c, and a data acquisition unit 11h that acquires the vital data detected by the thread-like sensor 11f.

[0041] The thread-like sensor 11f is, for example, a piezoelectric sensor. However, the type of the thread-like sensor 11f is not particularly limited. The thread-like sensor 11f is fixed, for example, by embroidery on the sheet-like fabric 11b so as to spread two-dimensionally. The thread-like sensor 11f has, for example, a plurality of first wave-like portions 11f1 protruding in a first direction A1, a folded portion, and a plurality of second wave-like portions 11f2 protruding in a second direction A2 opposite to the first direction A1. The power supply unit 11d activates the sensor unit 11c by supplying power to the data acquisition unit 11h.

[0042] The data acquiring unit 11h acquires vital data when the sensor unit 11c is activated and outputs the acquired vital data to the outside of the sensor sheet 11. For example, the thread-like sensor 11f generates an electrical signal corresponding to the applied load on the body of the participant. The sensor sheet 11 acquires the electrical signal as the above-mentioned breathing information, body movement information, and heart rate information.

[0043] When the participant places their body against the bedding with the sensor sheet 11 fixed to it, the thread-like sensor 11f generates an electrical signal. In this way, the thread-like sensor 11f generates an electrical signal, and the sensor sheet 11 acquires vital data. The vital data acquired by the sensor sheet 11 is sent to the health condition notification program 20.

[0044] FIG. 3 is a perspective view showing an example of the core material 14 of the cushion 13 to which the cushion sensor 12 is attached. The cushion 13 is provided, for example, in the participant's home or in an office where the participant is staying. The cushion sensor 12 acquires vital data of the participant, similar to the sensor sheet 11. The cushion 13 may be provided in a chair on which the participant sits when interacting with the equipment. In this case, the cushion sensor 12 acquires vital data of the participant when the participant interacts with the equipment.

[0045] In this embodiment, both the sensor sheet 11 and the cushion sensor 12 acquire vital data of the participants. This allows the acquisition of vital data both when the participants are working in the office and when they are staying at home, thereby enabling the acquisition of vital data of the participants with higher accuracy.

[0046] In the cushion 13, for example, the core material 14 is housed in a bag-shaped fabric (not shown). The core material 14 is made of, for example, urethane foam. As an example, the core material 14 is formed by urethane molding. In this case, the cushion 13 can be made more compliant when the body is placed on it, thereby providing the user with a comfortable sitting experience. However, the material of the core material 14 is not particularly limited.

[0047] The core material 14 has a seating portion 15 extending horizontally and a lumbar support portion 16 extending upward from the seating portion 15. For example, the seating portion 15 extends in a first direction D1 and a second direction D2 intersecting the first direction D1. The first direction D1 is the front-to-back direction when viewed from the perspective of a person seated on the seating portion 15, and the second direction D2 is the left-to-right direction when viewed from the perspective of a person seated on the seating portion 15.

[0048] The seating section 15 has a thickness in a third direction D3 that intersects with the first direction D1 and the second direction D2. For example, the third direction D3 is the vertical direction. The seating section 15 has a buttocks support section 15b and two thigh support sections 15c. The buttocks support section 15b and the thigh support sections 15c are arranged side by side along the first direction D1. Hereinafter, the direction in front of the participant seated on the seating section 15 as seen from the participant may be referred to as the "front," "front side," or "forward." The direction opposite to the forward direction may be referred to as the "rear," "rear side," or "rearward." However, these directions are used for convenience of explanation and do not limit the position or orientation of each section.

[0049] The buttocks support portion 15b is located on the rear side of the seating portion 15. The buttocks of the participant are placed on the buttocks support portion 15b. The buttocks support portion 15b supports the buttocks of the participant. The two thigh support portions 15c are lined up in the second direction D2 on the front side of the seating portion 15. The backs of the thighs of the participant are placed on the thigh support portions 15c. The thigh support portions 15c support the backs of the thighs of the participant.

[0050] Lumbar support section 16 extends upward from the rear end of seat section 15. Lumbar support section 16 has, for example, a general section 16b extending in second direction D2 and third direction D3, and a sacrum support section 16c located in the center of general section 16b in second direction D2. General section 16b refers to the portion of lumbar support section 16 other than sacrum support section 16c.

[0051] The sacrum support portion 16c has a convex shape that protrudes forward. The sacrum support portion 16c protrudes forward from the general portion 16b. As an example, the shape of the sacrum support portion 16c when viewed from the front has a major axis and a minor axis. For example, the shape of the sacrum support portion 16c when viewed from the front is an oval shape (an elliptical shape, for example).

[0052] The cushion sensor 12 acquires vital data of the participant seated on the cushion 13. In this embodiment, the cushion sensor 12 acquires heart rate information of the participant during the day. The cushion sensor 12 is, for example, a piezoelectric sensor fixed to the core material 14. In this case, the cushion sensor 12 measures the pressure from the body of the participant placed on the cushion 13 to each part of the cushion 13. However, the type of cushion sensor 12 is not particularly limited. The cushion sensor 12 includes, for example, a seating portion sensor 12b attached to the seating portion 15, a sacrum support portion sensor 12c attached to the sacrum support portion 16c, and thigh support portion sensors 12d attached to each of the two thigh support portions 15c.

[0053] The seating sensor 12b detects that the participant is seated on the seating 15. The seating sensor 12b detects, for example, that the participant's sitting bones are in contact with the seating sensor 12b. The sacral support sensor 12c measures, for example, the load of the participant's body that is in contact with the sacral support sensor 12c.

[0054] The thigh support sensor 12d measures, for example, the load on the thighs of the participant seated on the seat 15. The seat sensor 12b, the sacrum support sensor 12c, and the thigh support sensor 12d generate electrical signals corresponding to the load of the participant's body and acquire the electrical signals as the heart rate information described above. Note that, hereinafter, the electrical signals may also be simply referred to as signals.

[0055] The above describes an example in which the sensor 10 is at least one of the sensor sheet 11 and the cushion sensor 12. However, the sensor 10 may be something other than the sensor sheet 11 and the cushion sensor 12. For example, the sensor 10 may include an activity meter, which is a device that measures the physical activity of the participant. The activity meter, for example, records the participant's body movements while worn by the participant. When the sensor 10 includes an activity meter, it is possible to obtain the participant's physical information with higher accuracy, including during the day and while sleeping. When the sensor 10 includes an activity meter, it is possible to perform sleep analysis and determine whether the amount of exercise that day is appropriate or excessive by measuring the participant's sleeping posture, amount of exercise, number of steps, etc. Furthermore, the sensor 10 may be a wearable measuring device such as a ring-type smart watch.

[0056] Health condition notification program 20 notifies the participant of their health condition. The functional configuration of health condition notification program 20 will be described. As shown in FIG. 1 , health condition notification program 20 includes, as functional components, a physical information input unit 21, an autonomic nerve acquisition unit 22, a respiratory information acquisition unit 23, an analysis unit 24, a notification unit 25, and a memory unit 26. For example, health condition notification program 20 uses a past sleep accumulation database 31, a pre-device engagement sleep database 32, a pre-device engagement database 33, a during-device engagement database 34, and a post-device engagement database 35.

[0057] For example, when health condition notification program 20 is downloaded to terminal T, past sleep accumulation database 31, pre-device involvement sleep database 32, pre-device involvement database 33, during-device involvement database 34, and post-device involvement database 35 are stored in a memory unit of terminal T. However, past sleep accumulation database 31, pre-device involvement sleep database 32, pre-device involvement database 33, during-device involvement database 34, and post-device involvement database 35 may be stored in a server external to terminal T, and the locations where past sleep accumulation database 31, pre-device involvement sleep database 32, pre-device involvement database 33, during-device involvement database 34, and post-device involvement database 35 are stored are not particularly limited.

[0058] For example, the notification unit 25 displays an operation screen for operating the functions of the health condition notification program 20 on the display of the terminal T. The notification unit 25 displays various screens of the health condition notification program 20 on the display of the terminal T in accordance with, for example, commands from functions other than the notification unit 25 of the health condition notification program 20. For example, the notification unit 25 is a function that controls screen display on the display of the terminal T. The content of the information notified by the notification unit 25 will be described in detail later.

[0059] The memory unit 26 has a function of storing data input and output to the terminal T by the health status notification program 20. The memory unit 26 stores various types of information in a past sleep accumulation database 31, a pre-device engagement sleep database 32, a pre-device engagement database 33, a device engagement database 34, and a post-device engagement database 35.

[0060] The past sleep accumulation database 31 stores past sleep state information of participants. "Sleep state information" is information indicating a sleep state. "Sleep state" indicates the sleep state of a participant. "Sleep state" may include biological information of a participant other than the sleep state, such as sleep state such as sleep time and sleep stage, fatigue level, and stress level. "Sleep state information" may be included in physical information (vital data). In this embodiment, "sleep state information" includes at least one of the participant's bedtime, wake-up time, sleep stage ratio, sleep onset latency (time to fall asleep), sleep efficiency, number of awakenings, and duration of awakenings.

[0061] The bedtime indicates the time when the participant went to bed. The wake-up time indicates the time when the participant woke up. The sleep stage indicates the depth of the participant's sleep. The sleep stages are classified into, for example, wakefulness, REM sleep, and non-REM sleep. The non-REM sleep is classified into, for example, four types of sleep stages.

[0062] Non-REM sleep may be classified into two or three sleep stages. Hereinafter, REM sleep or a stage of non-REM sleep may be referred to as "sleep." The sleep onset time is the time, between going to bed and waking up, at which the participant's sleep stage changes from awake to sleep. The wake-up time is the time, between going to bed and waking up, at which the participant's sleep stage last changed to awake.

[0063] The sleep stage ratio indicates the proportion of time spent in each sleep stage relative to the time from bedtime to wake-up time. Sleep onset latency (time to fall asleep) indicates the length of time from bedtime to sleep onset. Sleep efficiency is an index for evaluating sleep quality. Sleep efficiency is, for example, the value obtained by subtracting the time spent waking up during the night from the time from bedtime to wake-up time, and dividing the result by the time from bedtime to wake-up time. Awakening during the night indicates that the participant wakes up between the time they fall asleep and the time they wake up. "Awake" indicates that the sleep stage changes from REM sleep or non-REM sleep to the wake-up stage.

[0064] The past sleep accumulation database 31 stores sleep state information from, for example, a predetermined period of time to the day before the participant interacts with the device. The "predetermined period" is, for example, one month, three months, six months, or one year, but is not limited thereto. The "predetermined period" may be changeable by operating the health condition notification program 20.

[0065] The pre-equipment involvement sleep database 32 stores, for example, sleep state information for the day before the participant engages with the equipment. For example, the data stored in the pre-equipment involvement sleep database 32 is transferred to the past sleep accumulation database 31 when the day changes. The pre-equipment involvement database 33 stores, for example, vital data for the day the participant engages with the equipment and before the participant engages with the equipment.

[0066] The equipment involvement database 34 stores, for example, vital data when the participant is involved with the equipment. The post-equipment involvement database 35 stores, for example, vital data on the day the participant is involved with the equipment and after the participant has been involved with the equipment. The pre-equipment involvement database 33, the equipment involvement database 34, and the post-equipment involvement database 35 store, for example, vital data for a predetermined period of time.

[0067] The physical information input unit 21 is a function that allows the participant to input their health condition. The physical information input unit 21 acquires the subjective physical information of the participant. The physical information input unit 21 acquires, for example, the subjective sleep state information of the participant. As shown in FIG. 4, for example, the physical information input unit 21 displays an input screen 41 on the terminal T of the participant, on which the subjective sleep state information can be input.

[0068] The input screen 41 is a screen on which, for example, subjective information is input. The subjective information is information indicating the subjective evaluation of the participant. The subjective information includes, for example, a subjective sleep evaluation (subjective sleep state information). The input screen 41 includes an evaluation input section 42, which is a section on which the subjective sleep evaluation is input.

[0069] For example, the evaluation input unit 42 receives a subjective sleep evaluation as a score, with 100 being the perfect score. However, the form of the subjective sleep state information input to the evaluation input unit 42 is not limited to the above. For example, the evaluation input unit 42 may be configured to allow input of sleep state information as a comment. The evaluation input unit 42 may be configured to allow input of subjective physical information. In this case, the physical information input unit 21 acquires the subjective physical information.

[0070] The subjective physical information of the participant acquired by the physical information input unit 21 is stored in the pre-device involvement sleep database 32 by the memory unit 26, for example. When the physical information input unit 21 acquires the subjective physical information before the participant engages with the device, the memory unit 26 stores the physical information in the pre-device involvement database 33. When the physical information input unit 21 acquires the subjective physical information after the participant engages with the device, the memory unit 26 stores the physical information in the post-device involvement database 35. Note that the physical information input unit 21 can be omitted, and the health condition notification program 20 may not have the physical information input unit 21.

[0071] The autonomic nerve acquiring unit 22 acquires autonomic nerve information of the participant. The autonomic nerve information is information indicating the state of the autonomic nerves of the participant. The autonomic nerve acquiring unit 22, for example, analyzes heart rate information acquired by the sensor 10 to acquire the heart rate variability (HRV) of the participant. For example, the autonomic nerve acquiring unit 22 acquires periodic components contained in the heart rate variability from the heart rate variability of the participant. The autonomic nerve acquiring unit 22 performs frequency analysis on the periodic components of the heart rate variability to acquire the power spectrum of each frequency.

[0072] The power spectrum of the autonomic nervous system obtained as a result of the above frequency analysis is divided into an LF (Low Frequency) component, which is the integral of the power spectrum in the low frequency band (for example, 0.04 Hz to 0.15 Hz), and an HF (High Frequency) component, which is the integral of the power spectrum in the high frequency band (for example, 0.15 Hz to 0.4 Hz). The LF component reflects sympathetic and parasympathetic nervous activity, and the HF component reflects parasympathetic nervous activity.

[0073] The autonomic nerve acquiring unit 22 acquires a sympathetic nerve index and a parasympathetic nerve index as autonomic nerve information. The sympathetic nerve index is an index indicating the dominance of the sympathetic nerve. For example, the sympathetic nerve index is a value obtained by dividing the value of the LF component by the value of the HF component. The parasympathetic nerve index is an index indicating the dominance of the parasympathetic nerve. For example, the parasympathetic nerve index is a value obtained by dividing the value of the HF component by the sum of the LF component and the HF component.

[0074] The autonomic nerve acquiring unit 22 acquires, for example, the activity level at the time of awakening from the acquired sympathetic nerve index as autonomic nerve information. The activity level indicates the degree of dominance of the sympathetic nerve over the parasympathetic nerve. The autonomic nerve acquiring unit 22 acquires the relaxation level at the time of falling asleep from the acquired parasympathetic nerve index. The relaxation level indicates the degree of dominance of the parasympathetic nerve over the sympathetic nerve. The autonomic nerve acquiring unit 22 acquires the acquired relaxation level at the time of falling asleep and the activity level at the time of awakening as autonomic nerve information.

[0075] The autonomic nerve acquiring unit 22 may acquire the mental state of the participant as autonomic nerve information from the sympathetic nerve index and the parasympathetic nerve index. The autonomic nerve acquiring unit 22 may classify the mental state of the participant into, for example, a high performance state, a relaxed state, a stressed state, or a depressed state from the sympathetic nerve index and the parasympathetic nerve index.

[0076] For example, the high performance state is a state in which the sympathetic nerve index is equal to or greater than a predetermined first index threshold and the parasympathetic nerve index is equal to or greater than a predetermined second index threshold. The relaxed state is, for example, a state in which the sympathetic nerve index is less than the first index threshold and the parasympathetic nerve index is equal to or greater than a second index threshold. The stress state is, for example, a state in which the sympathetic nerve index is equal to or greater than the first index threshold and the parasympathetic nerve index is less than the second index threshold. The depressed state is, for example, a state in which the sympathetic nerve index is less than the first index threshold and the parasympathetic nerve index is less than the second index threshold.

[0077] The autonomic nerve information of the participant acquired by the autonomic nerve acquisition unit 22 is stored in a pre-equipment involvement database 33 by the storage unit 26, for example, before the participant becomes involved with the equipment. When the autonomic nerve acquisition unit 22 acquires the autonomic nerve information of the participant while the participant is involved with the equipment, the storage unit 26 stores the autonomic nerve information in a during-equipment involvement database 34. When the autonomic nerve acquisition unit 22 acquires the autonomic nerve information of the participant after the participant becomes involved with the equipment, the storage unit 26 stores the autonomic nerve information in a post-equipment involvement database 35.

[0078] The respiratory information acquisition unit 23 acquires respiratory information from the sensor 10. The respiratory information acquisition unit 23 determines, for example, from the acquired respiratory information, whether or not there is an abnormal respiratory state and whether or not there is a health risk due to the abnormal respiratory state. The health risk is, for example, the risk of heart failure or the like associated with sleep apnea syndrome (SAS). The abnormal respiratory state is, for example, a breathing state during sleep that may pose a health risk to the participant. The abnormal respiratory state includes, for example, an apnea state and a hypopnea state.

[0079] The respiratory information acquisition unit 23 acquires apnea information. The apnea information is information indicating the state of apnea of ​​the participant while sleeping. The apnea information is included, for example, in physical information (vital data). The apnea state is, for example, a state in which the participant's breathing stops for 10 seconds or more. The hypopnea state is a state in which the amplitude of the participant's airflow in breathing decreases by 30% or more and the arterial blood oxygen saturation (SpO2) decreases by 3% or more for 10 seconds or more.

[0080] As described above, the respiratory information acquiring unit 23 detects the abnormal respiratory state of the participant. The respiratory information acquiring unit 23 detects the abnormal respiratory state from, for example, respiratory information acquired by the sensor 10. As an example, the respiratory information acquiring unit 23 detects the abnormal respiratory state from the participant's respiratory rate. The respiratory information acquiring unit 23 may acquire the number of detected abnormal respiratory states for each unit time period from the time of falling asleep to the time of awakening.

[0081] A unit time period is a time period having a predetermined duration. The duration of the unit time period is, for example, one hour. The respiratory information acquisition unit 23 acquires, for example, an average detection count from the number of detected abnormal respiratory states. The average detection count is a value obtained by dividing the total number of detections of abnormal respiratory states from the time of falling asleep to the time of waking up by the time from the time of falling asleep to the time of waking up. When the duration of the unit time period is one hour, the average detection count corresponds to the so-called Apnea Hypopnea Index (AHI).

[0082] The respiratory information acquiring unit 23 may acquire a maximum number of detected abnormal breathing states from the number of detected abnormal breathing states. The maximum number of detected abnormal breathing states is, for example, the maximum number of detected abnormal breathing states among the number of detected abnormal breathing states per unit time period. For example, the respiratory information acquiring unit 23 acquires the number of detected abnormal breathing states per unit time period.

[0083] The respiratory information acquiring unit 23 acquires the number of detections of abnormal breathing states in a unit time period with the highest number of detections as the maximum number of detections. The respiratory information acquiring unit 23 determines that there is a health risk, for example, when the average number of detections is equal to or greater than a first number threshold and the maximum number of detections is equal to or greater than a second number threshold. The first number threshold is a predetermined maximum allowable value for the average number of detections, and the second number threshold is a predetermined maximum allowable value for the maximum number of detections.

[0084] The apnea information acquired by the respiratory information acquisition unit 23 is stored in the pre-equipment engagement sleep database 32 by the storage unit 26, for example, before the participant engages with the equipment. The storage unit 26 stores, for example, the respiratory information acquired by the respiratory information acquisition unit 23 and the determination result by the respiratory information acquisition unit 23 in the pre-equipment engagement sleep database 32.

[0085] The analysis unit 24 receives body information (vital data) from the sensor 10. The analysis unit 24 determines the bedtime and wake-up time from, for example, body movement information acquired by the sensor 10 and movement of bedding detected by the sensor 10 (for example, an acceleration sensor), and acquires the bedtime and wake-up time.

[0086] The analysis unit 24 acquires the sleep stages using, for example, a signal indicating body movement associated with breathing, a signal indicating body movement associated with heartbeat, and a signal indicating body movement unassociated with breathing and heartbeat, all output from the sensor 10. The analysis unit 24 acquires the sleep stage ratio from, for example, the sleep stage, bedtime, and wake-up time. The analysis unit 24 acquires, for example, the time from bedtime to sleep onset as the sleep onset latency based on the bedtime and sleep stage.

[0087] The analysis unit 24 obtains, for example, the duration of awakenings and the number of awakenings from the bedtime, wake-up time, and sleep stage. The analysis unit 24 obtains, for example, the time of falling asleep from the bedtime and sleep stage, and obtains the time of awakening from the wake-up time and sleep stage. The analysis unit 24 obtains, for example, the duration of awakenings and the number of awakenings from the time of falling asleep, wake-up time, and sleep stage. The analysis unit 24 obtains, for example, the sleep efficiency from the bedtime, wake-up time, and sleep stage. The analysis unit 24 obtains, for example, the sleep efficiency from the time of going to bed, wake-up time, time of falling asleep, wake-up time, and the duration of awakenings.

[0088] For example, the analysis unit 24 may estimate the exercise performance of the participant from the sleep state information stored in the past sleep accumulation database 31, and the autonomic nerve information, body temperature, blood pressure, and heart rate stored in the pre-device involvement database 33. The exercise performance is an index that indicates the physical condition of the participant.

[0089] The analysis unit 24 may estimate the participant's mental ability from the sleep state information, autonomic nerve information, and respiratory information. For example, the analysis unit 24 may estimate concentration and drowsiness from the autonomic nerve information. The analysis unit 24 may estimate the participant's reaction speed from the autonomic nerve information. The analysis unit 24 may quantify each of the participant's exercise performance, mental ability, concentration, and reaction speed.

[0090] For example, the analysis unit 24 generates prediction information, which is information indicating the predicted state of the participant while awake, from at least one of the sleep state information and the autonomic nerve information. The prediction information is information indicating the predicted mental and physical state of the participant. The prediction information includes, for example, mental information, which is information indicating the mental state of the participant, physical condition information, which is information indicating the physical condition of the participant, and brain information, which is information indicating the mental state of the participant.

[0091] For example, the analysis unit 24 may determine whether the sleep efficiency is equal to or greater than a predetermined value from the sleep state information stored in the past sleep accumulation database 31. For example, the analysis unit 24 may determine whether the participant's concentration is equal to or greater than a predetermined value from information indicating concentration. The analysis unit 24 may generate prediction information from the sleep efficiency determination result and the concentration determination result.

[0092] The analysis unit 24 generates mental information from, for example, autonomic nerve information. The mental information includes, for example, information regarding the mood swings of the participant. As an example, the mental information includes information indicating whether the participant is prone to feeling depressed. For example, when the analysis unit 24 classifies the mental state of the participant as a stressed state or a depressed state, the analysis unit 24 may generate, as mental information, information indicating that the participant is prone to feeling depressed.

[0093] The analysis unit 24 generates physical condition information from, for example, the sleep state information stored in the past sleep accumulation database 31. The physical condition information includes, for example, information indicating whether the participant's physical condition is good or bad while awake. For example, if the analysis unit 24 determines that the sleep efficiency is not equal to or greater than a predetermined value, the analysis unit 24 may generate, as physical condition information, information indicating that the participant's physical condition is tending to worsen.

[0094] For example, the analysis unit 24 generates brain information from the sleep state information and autonomic nerve information stored in the past sleep accumulation database 31. The brain information is information indicating the quality of the participant's brain function. The brain information includes, for example, information indicating the quality of the participant's concentration, memory, and thinking ability.

[0095] For example, when the mental state of the participant is classified as a high performance state, the analysis unit 24 may generate, as the brain information, information indicating that the participant's concentration is predicted to be high. For example, when the sleep efficiency is not equal to or greater than a predetermined value, the analysis unit 24 may generate, as the brain information, information indicating that the participant's thinking ability is predicted to be low.

[0096] As described above, the analysis unit 24 acquires autonomic nervous system information, the presence or absence of an abnormal respiratory state, health risks, mental state, information indicating athletic performance, information indicating thinking ability, information indicating concentration, information indicating drowsiness, information indicating reaction speed, and prediction information (mental information, physical condition information, and brain information). In this embodiment, at least one of the autonomic nervous system information, the presence or absence of an abnormal respiratory state, health risks, mental state, information indicating athletic performance, information indicating thinking ability, information indicating concentration, information indicating drowsiness, information indicating reaction speed, and prediction information represents the mental and physical state of the participant.

[0097] In other words, at least one of the following is estimated as the physical and mental state of the participant: the state of the autonomic nervous system, the presence or absence of abnormal respiratory conditions, health risks, mental state, information indicating athletic performance, information indicating thinking ability, information indicating concentration, information indicating drowsiness, information indicating reaction speed, and predicted information.

[0098] The analysis unit 24 may estimate one or two of the mental information, physical condition information, and brain information as the mental and physical condition of the participant. For example, from any of the above information, the analysis unit 24 may estimate at least one of the mental state, psychological state, mood state, stress level, fatigue level, autonomic nervous state, and health state of the participant as the mental and physical condition.

[0099] The analysis unit 24 may detect whether the participant has arrhythmia from the heartbeat information acquired by the sensor 10. The arrhythmia is, for example, respiratory arrhythmia. In respiratory arrhythmia, the interval between heartbeats shortens when breathing in, and the interval between heartbeats lengthens when breathing out. In this case, it is desirable to increase the oxygen concentration and blood flow when breathing in to take in more oxygen, and to decrease the oxygen concentration and blood flow when breathing out to promote recovery from cardiac fatigue.

[0100] "Arrhythmia" refers to either a slow pulse, a fast pulse, or an irregular pulse. "Arrhythmia" refers to a state in which the speed or rhythm of the heart's beat (contraction and expansion) is disturbed. "Pulse" refers to the rhythm in which the heart pumps blood throughout the body, i.e., the number of times the heart beats in a given period of time. When arrhythmia occurs, symptoms such as palpitations, chest tightness, shortness of breath, fatigue, dizziness, fainting, and skipped beats occur. Arrhythmia is often not dangerous. However, because arrhythmia can also be caused by heart disease, it is desirable to be able to properly detect arrhythmia.

[0101] Arrhythmias include bradyarrhythmia, tachyarrhythmia, and premature contractions. Bradyarrhythmia is characterized by a slow heartbeat (e.g., below 50 BPM), which can make you feel short of breath or fatigued. If the heartbeat is even slower, it can cause dizziness or fainting. Arrhythmias include those caused by sick sinus syndrome and atrioventricular block. In arrhythmias caused by sick sinus syndrome, there is an abnormality in the sinus node, which reduces the frequency of electrical signals and slows the heartbeat. In arrhythmias caused by atrioventricular block, electrical signals are difficult to transmit or are interrupted in the pathways connecting the atria and ventricles.

[0102] Tachyarrhythmia causes rapid heartbeats (e.g., over 100 BPM), leading to palpitations or chest tightness. Arrhythmias include atrial flutter, atrial fibrillation, ventricular tachycardia, and ventricular fibrillation. In atrial flutter arrhythmia, the atria beat rapidly, resulting in a heart rate of approximately 300 BPM. In atrial fibrillation arrhythmia, the atria beat rapidly, resulting in a heart rate of approximately 500 BPM. If atrial fibrillation arrhythmia continues for a long period of time, blood clots may form in the atria, potentially leading to cerebral infarction. In ventricular tachycardia arrhythmia, abnormal electrical impulses occur in the ventricles, resulting in a heart rate of approximately 200 BPM. In ventricular fibrillation arrhythmia, abnormal electrical impulses occur in the ventricles, resulting in a heart rate of approximately 400 BPM.

[0103] For example, the analysis unit 24 detects the various arrhythmias described above. For example, the analysis unit 24 classifies heartbeat waveforms into normal waveforms and abnormal waveforms. The analysis unit 24 detects abnormal waveforms obtained as a result of this classification as arrhythmias. The analysis unit 24 may have learned normal waveforms and abnormal waveforms. In this case, the analysis unit 24 can efficiently determine whether the heartbeat waveform is normal or abnormal.

[0104] The analysis unit 24 may, for example, detect the timing of the occurrence of arrhythmia from the heartbeat information. The analysis unit 24 may calculate the frequency of arrhythmia from the heartbeat information. The analysis unit 24 may calculate the duration of arrhythmia from the heartbeat information. The analysis unit 24 may detect the presence or absence of premature contractions from the heartbeat information. An "extrasystole" indicates that an irregular beat appears between normal beats. An "extrasystole" may also indicate that a beat occurs early due to a timing shift between beats that occur at a constant rhythm. For example, the analysis unit 24 detects the presence of a premature contraction when it detects a heart rate that is X times (X is a positive real number) or more the immediately preceding heart rate, or when it detects a heart rate that is 1 / X times or less the immediately preceding heart rate. As an example, the value of X is 2.

[0105] The analysis unit 24 may include information about the detected arrhythmia in the prediction information. For example, the analysis unit 24 may predict a disease that may occur in the participant in the future from the information about the detected arrhythmia and include the predicted disease in the prediction information. The analysis unit 24 may generate information for eliminating the arrhythmia from the information about the detected arrhythmia as improvement information.

[0106] For example, the analysis unit 24 may include in the improvement information information that recommends getting more sleep, reducing alcohol intake, or visiting a hospital (for example, a cardiology department). The analysis unit 24 may also include in the improvement information advice that it is better to avoid dangerous work and driving a car. The analysis unit 24 may also include in the improvement information advice that it is better to adopt at least one of breathing techniques and relaxation techniques. The improvement information is included in the mental and physical state of the participant output by the analysis unit 24.

[0107] The mental and physical state of the participant obtained by the analysis unit 24 is stored in a pre-equipment involvement database 33 if the participant is before the participant is involved with the equipment, stored in an equipment involvement database 34 if the participant is involved with the equipment, and stored in a post-equipment involvement database 35 if the participant has already involved with the equipment.

[0108] The analysis unit 24 analyzes the physical information received from the sensor 10 and determines whether it is desirable for the participant to be involved with the equipment. "Whether it is desirable for the participant to be involved with the equipment" refers to whether the participant's physical and mental condition is good enough to allow the participant to be involved with the equipment appropriately.

[0109] "Whether it is desirable for the participant to be involved with the equipment" indicates, for example, whether the participant's physical and mental state is suitable for driving a vehicle, whether the participant's physical and mental state is suitable for operating a machine, or whether the participant's physical and mental state is suitable enough to adequately monitor the equipment. "Able to be appropriately involved with the equipment" indicates, for example, being able to safely drive a vehicle, be able to safely operate the equipment, or be able to appropriately monitor the equipment.

[0110] The analysis unit 24 determines whether it is desirable for the participant to be involved with the equipment when the participant is not involved with the equipment. The analysis unit 24 makes the above determination, for example, from at least one of sleep state information and mental and physical state. The analysis unit 24 may output the determination result of whether it is desirable for the participant to be involved with the equipment as a score. The analysis unit 24 may output the upper limit of the time that the participant can appropriately be involved with the equipment. In this case, the analysis unit 24 may output the recommended time, which is the upper limit of the time that the participant can appropriately be involved with the equipment. The analysis unit 24 may output the determination result as a comment, or may output the determination result as a symbol such as "○", "△", or "×".

[0111] The analysis unit 24 may make the above-mentioned determination based on the sleep state information and output the determination result as a drowsiness index. For example, the smaller the drowsiness index, the more preferable it is for the participant to be involved with the equipment, and the larger the drowsiness index, the less preferable it is for the participant to be involved with the equipment. The analysis unit 24 may make the above-mentioned determination based on the mental and physical state and output the determination result as a comment. In this way, the manner in which the result of the determination by the analysis unit 24 is output can be changed as appropriate.

[0112] The analysis unit 24 may determine whether it is appropriate for the participant to be involved with the equipment based on the sleep state information of the previous day stored in the pre-equipment engagement sleep database 32. In this case, it is possible to determine whether it is appropriate for the participant to be involved with the equipment based on the sleep state of the participant of the previous day. The analysis unit 24 may determine whether it is appropriate for the participant to be involved with the equipment based on the sleep state information stored in the past sleep accumulation database 31. In this case, it is possible to determine whether it is appropriate for the participant to be involved with the equipment based on the participant's previous sleep state.

[0113] The analysis unit 24 may determine whether it is desirable for the participant to be involved with the equipment based on the mental and physical conditions stored in the pre-equipment involvement database 33. In this case, it can be determined whether the participant's mental and physical conditions are good before the participant is involved with the equipment. The analysis unit 24 may determine whether it is desirable for the participant to be involved with the equipment based on the mental and physical conditions stored in the during-equipment involvement database 34. The analysis unit 24 may determine whether it is desirable for the participant to be involved with the equipment on the next day based on the mental and physical conditions stored in the post-equipment involvement database 35.

[0114] The notification unit 25 notifies the result of the analysis performed by the analysis unit 24. The notification unit 25 notifies the result when the participant is not involved in the device. The notification unit 25 may notify the result (determination result) determined by the analysis unit 24. The notification unit 25 may notify information generated, estimated, or acquired by the analysis unit 24.

[0115] 5, for example, the notification unit 25 displays an output screen 43 showing the result determined by the analysis unit 24 on the terminal T of the participant. The output screen 43 is a screen on which the determination result by the analysis unit 24 is output. The output screen 43 includes, for example, a drowsiness index output unit 44 that outputs the drowsiness index of the participant, and a comment display unit 45 that displays the comments output by the analysis unit 24. For example, the comment display unit 45 may include a recommended time display unit 46 that displays a recommended time, which is the upper limit of the time that the participant can appropriately interact with the equipment.

[0116] As an example, the drowsiness index output unit 44 displays that the drowsiness index is "30," and the comment display unit 45 displays a comment that the participant is somewhat tired and should refrain from driving for long periods of time. The recommended time display unit 46 displays 7.5 hours of possible driving time, which is an example of a recommended time. In this way, the results of the analysis by the analysis unit 24 and the results of the determination are displayed on the output screen 43, so that the participant can understand to what extent they can operate the equipment.

[0117] The notification unit 25 may notify the participant of a recommendation for their physical and mental state. A "recommendation" is information indicating an action recommended for the participant, for example, information indicating the participant's physical and mental state and the action recommended for that physical and mental state. The recommendation may be improvement information that improves the participant's life. The notification unit 25 may display on the terminal T a recommendation that the participant should stop by a nap room and take a nap.

[0118] The notification unit 25 may notify the participant of advice regarding sleep. The advice may include, for example, at least one of information regarding how well the participant falls asleep and information regarding whether the participant is able to sleep continuously. The advice may include, for example, advice for improving the participant's sleep. The advice for improving sleep may include, for example, behaviors during wakefulness that are effective in reducing the number of times the participant wakes up during the night.

[0119] The notification unit 25 provides, for example, information that encourages a behavioral change according to the participant's physical and mental state. Behavioral change means that the participant changes their own behavior. Information that encourages a behavioral change includes, for example, information that encourages the participant to go to a place where sleep consultations are available (hereinafter, sometimes referred to as a "sleep consultation center") and consult with a sleep specialist.

[0120] The sleep consultation center may include, for example, a hospital specializing in sleep, a hospital or clinic with expertise in sleep, or a counseling room other than a hospital. The sleep specialist may be, for example, a doctor specializing in sleep, or a non-physician. The information encouraging behavioral change may include, for example, information indicating the geographic location of a preset sleep consultation center. In this way, the notification unit 25 may display information encouraging behavioral change on the terminal T.

[0121] For example, when the analysis unit 24 estimates that the participant's thinking ability has declined, the notification unit 25 displays information that it is recommended not to make an important decision as a recommendation. For example, the notification unit 25 displays the recommendation on the display of the terminal T. For example, the memory unit 26 stores a history of recommendations notified by the notification unit 25. The notification unit 25 may change the nature of recommendations to be notified to the participant in the future, taking into account the recommendation history stored in the memory unit 26 and the subjective information input to the physical information input unit 21. In this case, it is possible to notify a recommendation that is more suitable for the participant.

[0122] Next, an example of the steps of the health condition notification method according to this embodiment will be described with reference to FIG. 6. FIG. 6 is a sequence diagram showing an example of the steps of the health condition notification method. Below, an example will be described in which the health condition notification program 20 described above notifies a participant of their health condition. An example will be described in which the device is a car, the participation is driving, and the participant is a user of the health condition notification system 1 and a person who drives the car (driver). The "driver" may be, for example, a private driver, a truck driver, a taxi driver, an aircraft pilot, or a train driver.

[0123] In the following health condition notification method, information management before driving is performed based on physical information to ensure safer driving. By acquiring physical information before driving and physical information after driving, the driver's health condition can be grasped with higher accuracy. Furthermore, by acquiring and notifying physical information before driving, it is possible to prevent drivers in poor health from driving for long periods of time.

[0124] First, the user (driver) installs the health condition notification system 1 (step S1). At this time, the user installs the health condition notification program 20 in the terminal T. For example, the health condition notification program 20 causes the terminal T, which is a computer, to execute the following steps: Then, the sensor sheet 11 is placed on bedding, and the cushion 13 is placed on a chair in the user's home (or office).

[0125] The user sleeps on the bedding on which the sensor sheet 11 is placed (step S2). At this time, the sensor sheet 11 acquires physical information (vital data) of the user while he or she is sleeping (asleep) and transmits the acquired physical information to the health condition notifying program 20. The sensor sheet 11 acquires, for example, breathing information, heart rate information, and body movement information of the user as the physical information.

[0126] For example, the analysis unit 24 receives the physical information from the sensor sheet 11 (step S3). When the analysis unit 24 receives the physical information, the storage unit 26 stores the physical information in the pre-device engagement sleep database 32. The analysis unit 24 analyzes and determines the physical information (determining step, determining process, step S4).

[0127] At this time, the analysis unit 24 may acquire the bedtime and wake-up time by determining the bedtime and wake-up time from the body movement information acquired by the sensor sheet 11 and the movement of the bedding detected by the sensor sheet 11. The analysis unit 24 may acquire the sleep stages, or may acquire the sleep stage ratios from the sleep stages, the bedtime, and the wake-up time. The analysis unit 24 may acquire the time from the bedtime to the sleep onset time as the sleep onset latency based on the bedtime and the sleep stage.

[0128] The analysis unit 24 may acquire the duration of awakenings and the number of awakenings from the bedtime, wake-up time, and sleep stage. The analysis unit 24 may acquire the sleep onset time from the bedtime and sleep stage, or may acquire the awakening time from the wake-up time and sleep stage. The analysis unit 24 may acquire the duration of awakenings and the number of awakenings from the sleep onset time, wake-up time, and sleep stage. The analysis unit 24 may acquire sleep efficiency from the bedtime, wake-up time, and sleep stage. The analysis unit 24 may acquire sleep efficiency from the bedtime, wake-up time, sleep onset time, wake-up time, and duration of awakenings.

[0129] The analysis unit 24 may acquire the user's exercise performance from the sleep state information, autonomic nerve information, body temperature, blood pressure, and heart rate. The analysis unit 24 may acquire the user's thinking ability from the sleep state information, autonomic nerve information, and breathing information. The analysis unit 24 may acquire the user's concentration and drowsiness from the autonomic nerve information. The analysis unit 24 may acquire the user's reaction speed from the autonomic nerve information and body movement information.

[0130] The analysis unit 24 may acquire prediction information for the user while awake from at least one of the sleep state information and the autonomic nerve information. The analysis unit 24 may determine whether or not the sleep efficiency is equal to or greater than a predetermined value from the sleep state information. The analysis unit 24 may determine whether or not the user's concentration is equal to or greater than a predetermined value from information indicating concentration. The analysis unit 24 may acquire prediction information from the sleep efficiency judgment result and the concentration judgment result. The analysis unit 24 may generate mental information from the autonomic nerve information. The analysis unit 24 may acquire physical condition information from the sleep state information. The analysis unit 24 may acquire brain information from the sleep state information and the autonomic nerve information.

[0131] The analysis unit 24 may acquire one or two of mental information, physical condition information, and brain information as the mental and physical condition of the user. From any of the above information, the analysis unit 24 may acquire at least one of the user's mental state, psychological state, mood state, stress level, fatigue level, autonomic nervous state, and health state as the mental and physical condition.

[0132] The analysis unit 24 may determine whether the user has arrhythmia from the heartbeat information acquired by the sensor sheet 11. The analysis unit 24 may classify waveforms indicating the heartbeat information into normal waveforms and abnormal waveforms. The analysis unit 24 may identify the abnormal waveform obtained as a result of this classification as arrhythmia.

[0133] The analysis unit 24 may acquire the timing of occurrence of arrhythmia from the heartbeat information. The analysis unit 24 may calculate the frequency of arrhythmia from the heartbeat information. The analysis unit 24 may calculate the duration of arrhythmia from the heartbeat information. The analysis unit 24 may detect the presence or absence of premature contractions from the heartbeat information.

[0134] The analysis unit 24 may include the acquired arrhythmia information in the prediction information. The analysis unit 24 may predict a disease that the user may develop in the future from the acquired arrhythmia information and include the predicted disease in the prediction information. The analysis unit 24 may acquire, from the acquired arrhythmia information, information for eliminating the arrhythmia as improvement information.

[0135] The analysis unit 24 analyzes the various pieces of information calculated and acquired as described above to determine whether it is desirable for the user to drive a vehicle. The information calculated and acquired by the analysis unit 24 and the results of the analysis and determination by the analysis unit 24 are stored in the pre-device engagement sleep database 32 by the storage unit 26.

[0136] The notification unit 25 notifies the result of the analysis by the analysis unit 24 (notifying step, notifying process, step S5). Then, the user wakes up (step S6), and the notification by the notification unit 25 is received by the terminal T. At this time, for example, the output screen 43 is displayed on the display of the terminal T.

[0137] For example, the user sits on the cushion 13 placed on a chair at home (or in the office) (step S7). At this time, the cushion sensor 12 acquires physical information (vital data) of the user while he or she is seated (step S8), and transmits the acquired physical information to the health condition notifying program 20.

[0138] At this time, cushion sensor 12 may acquire information about the user's heart rate during the day. Seat sensor 12b may detect the user sitting on seat 15, or seat sensor 12b may detect contact of the user's ischial bones with seat sensor 12b. Sacral support sensor 12c may measure the weight of the user's body in contact with sacral support sensor 12c. Thigh support sensor 12d may measure the weight of the user's thighs sitting on seat 15.

[0139] The seat sensor 12b, the sacral support sensor 12c, and the thigh support sensor 12d may generate signals corresponding to the load of the user's body and acquire the signals as the heart rate information. Furthermore, the activity meter may acquire the user's physical information during the day. At least one of the acquired physical information and heart rate information is sent to the health condition notification program 20.

[0140] For example, the analysis unit 24 receives physical information from the cushion sensor 12. When the analysis unit 24 receives the physical information, the storage unit 26 stores the physical information in the pre-device involvement database 33. The analysis unit 24 analyzes and judges the physical information (judging step, judging process, step S9).

[0141] At this time, the analysis unit 24 may determine the user's posture from the body movement information acquired by the cushion sensor 12 and the movement of the cushion 13 detected by the cushion sensor 12. The analysis unit 24 may determine the user's posture from the results of measurement by the sacral support sensor 12c. The analysis unit 24 may determine that the user's posture is hunched (slightly sitting) and inappropriate when the user's body (e.g., sacrum) is not in contact with the sacral support sensor 12c. The analysis unit 24 may acquire the time for which the user maintains a hunched posture.

[0142] The analysis unit 24 may determine that the user is leaning back too much when the load measured by the sacral support sensor 12c is equal to or greater than a certain value. The analysis unit 24 may also acquire the time for which the user is leaning back too much. The sacral support sensor 12c may measure the amount of deformation (degree of crushing) of the sacral support portion 16c, and the analysis unit 24 may determine that the user is leaning back too much when the measured amount of deformation of the sacral support portion 16c is equal to or greater than a certain value.

[0143] The analysis unit 24 may determine that the user's posture is appropriate when the load measured by the sacral support sensor 12c is less than a certain value. The analysis unit 24 may also acquire the time during which the posture is appropriate. The analysis unit 24 may also determine that the posture is appropriate when the measured deformation amount of the sacral support sensor 16c is less than a certain value.

[0144] The analysis unit 24 may acquire the difference in the loads on the thigh support sensor 12d measured by the pair of thigh support sensors 12d. The analysis unit 24 may calculate the absolute value of the difference between the load on one thigh support sensor 12d received from the left thigh and the load on the other thigh support sensor 12d received from the right thigh. The analysis unit 24 may then determine that the left-right balance is not good and the posture is not appropriate when the calculated absolute value is equal to or greater than a certain value, and may determine that the left-right balance is good when the calculated absolute value is not equal to or greater than the certain value. The analysis unit 24 may acquire the time during which the left-right balance is not good.

[0145] The analysis unit 24 may obtain the degree of fatigue from at least one of the time period during which the posture is appropriate, the time period during which the posture is hunched, the time period during which the posture is leaning back too much, and the time period during which the left and right balance is not good. For example, the analysis unit 24 determines that the degree of fatigue is low when the time period during which the posture is appropriate is equal to or longer than a certain period of time.

[0146] For example, the analysis unit 24 determines that the level of fatigue is high when the user has a hunched back, leans back too much, or has poor left-right balance for a certain period of time or more. The level of fatigue determined by the analysis unit 24 is included in the mental and physical state. As in step S4, the analysis unit 24 may acquire at least one of the user's mental state, psychological state, mood state, stress level, fatigue level, autonomic nervous state, and health state as the mental and physical state.

[0147] The analysis unit 24 may acquire the user's exercise performance from the autonomic nervous system information, body temperature, blood pressure, and heart rate. The analysis unit 24 may acquire the user's thinking ability from the autonomic nervous system information and respiratory information. The analysis unit 24 may acquire the user's concentration and drowsiness from the autonomic nervous system information. The analysis unit 24 may acquire the user's reaction speed from the autonomic nervous system information and body movement information.

[0148] The analysis unit 24 may acquire prediction information of the user from the autonomic nerve information. The analysis unit 24 may determine whether the user's concentration is equal to or greater than a predetermined value from information indicating the concentration. The analysis unit 24 may acquire prediction information from the determination result of the concentration.

[0149] As described above, in step S9, the analysis unit 24 performs the same analysis and determination as in step S4. The analysis unit 24 analyzes the various pieces of information acquired as described above and determines again whether it is desirable for the user to drive the car. The information acquired by the analysis unit 24 and the results of the analysis and determination by the analysis unit 24 are stored in the pre-device involvement database 33 by the storage unit 26. Then, the notification unit 25 notifies the results of the analysis by the analysis unit 24 (notifying step, notifying process, step S10). The content of step S10 is the same as the content of step S5 described above.

[0150] The above steps S1 to S10 are executed before the user drives the vehicle (when the involved party is not involved in the equipment). Thereafter, the user starts driving the vehicle (step S11). A cushion 13 may be placed in the driver's seat of the vehicle. In this case, the cushion sensor 12 acquires physical information when the user is sitting on the cushion 13 in the driver's seat (step S12). The content of step S12 is the same as the content of step S8 described above. The analysis unit 24 receives the physical information from the cushion sensor 12 and performs the above-mentioned analysis, determination, and calculation and acquisition of various information (step S13). The physical information received by the analysis unit 24 is stored in the equipment involved database 34 by the memory unit 26.

[0151] The information acquired by the analysis unit 24 and the results of the analysis and determination by the analysis unit 24 are stored in the equipment involvement database 34 by the storage unit 26. Then, the notification unit 25 notifies the results of the analysis by the analysis unit 24 (notifying step, notifying process, step S14). The content of step S14 is the same as the content of steps S5 and S10 described above.

[0152] Through the above steps, a series of steps of the health condition notification method is completed. Note that the above example has been described in which the device is a vehicle, the involvement is driving, and the participant is the driver who drives the vehicle. However, the health condition notification method described above can also be applied to cases in which the device is not a vehicle, the involvement is not driving, or the participant is not the driver who drives the vehicle.

[0153] Next, the effects obtained from the health condition notification system 1, health condition notification program 20, and health condition notification method according to this embodiment will be described. The health condition notification system 1, health condition notification program 20, and health condition notification method according to this embodiment include a sensor 10 installed at a location away from a device such as a vehicle, an analysis unit 24 that determines whether or not it is desirable for a participant such as a driver to be involved in the device based on physical information from the sensor 10, and a notification unit 25 that notifies the results of the analysis by the analysis unit 24. The sensor 10 acquires physical information of the participant involved in the device, and this physical information is analyzed by the analysis unit 24. This eliminates the need to input answers to questions, making it possible to efficiently acquire physical information and improve the quality of the acquired physical information.

[0154] The acquisition of physical information by the sensor 10, the determination by the analysis unit 24, and the notification of the result by the notification unit 25 are performed when the participant is away from the equipment and not involved with the equipment. Therefore, by notifying the result by the notification unit 25 before the participant is involved with the equipment, it is possible to prevent accidents from occurring due to a participant who is not desirable to be involved with the equipment being involved with the equipment. Furthermore, by acquiring physical information by the sensor 10 when the participant is not involved with the equipment, it is easier to determine whether it is better not to be involved with the equipment, compared to when physical information is acquired when the participant is involved with the equipment.

[0155] As described above, the sensor 10 (e.g., the sensor sheet 11) may acquire physical information while the participant is sleeping, the analysis unit 24 may make a determination, and the notification unit 25 may notify the result. In this case, the sensor 10 acquires physical information while the participant is sleeping, and this physical information is analyzed by the analysis unit 24. Therefore, when determining whether or not it is desirable for the participant to participate in the equipment, various pieces of physical information obtained during sleep can be used, thereby improving the accuracy of the above determination.

[0156] As described above, when the participant is not involved with the equipment and is sitting, the sensor 10 (e.g., cushion sensor 12) may acquire physical information, the analysis unit 24 may make a determination, and the notification unit 25 may notify the result. In this case, the sensor 10 acquires physical information when the participant is sitting, and this physical information is analyzed by the analysis unit 24. Therefore, when determining whether it is desirable for the participant to be involved with the equipment, physical information such as posture while sitting can be used, thereby improving the accuracy of the above determination.

[0157] As described above, the physical information may include sleep state information that indicates the sleep state of the participant. For example, the physical information may include sleep state information stored in the past sleep accumulation database 31, and the analysis unit 24 may determine whether or not it is desirable for the participant to participate in the device based on the sleep state information stored in the past sleep accumulation database 31. In this case, when determining whether or not it is desirable for the participant to participate in the device, the sleep state information that indicates how the participant has slept up to now can be used. Therefore, it is possible to prevent a participant with poor sleep state from continuing to participate in the device for a long period of time.

[0158] As described above, the physical information may include autonomic nerve information, which is information indicating the state of the autonomic nerves of the participant. The analysis unit 24 may determine whether or not it is desirable for the participant to be involved with the equipment based on the stored autonomic nerve information. In this case, the autonomic nerve information indicating the state of the autonomic nerves of the participant can be used when determining whether or not it is desirable for the participant to be involved with the equipment. Therefore, it is possible to prevent a participant with an unfavorable balance between the sympathetic and parasympathetic nerves from continuing to be involved with the equipment for a long period of time.

[0159] As described above, the physical information may include apnea information indicating the apnea state of the participant during sleep. The analysis unit 24 may determine whether or not it is desirable for the participant to participate in the device based on the stored apnea information. In this case, the apnea information indicating whether or not the participant is experiencing apnea can be used when determining whether or not it is desirable for the participant to participate in the device. Therefore, it is possible to prevent a participant who frequently suffers from sleep apnea from continuing to participate in the device for a long period of time.

[0160] As mentioned above, the device may be a car, and the participant may be a driver of the car. In this case, the participant can understand whether or not he or she is in a state of health suitable for driving before driving. The participant can determine whether or not it is okay to drive for a certain length of time when the conditions are good, or whether or not it is better to refrain from driving for a long period of time when the conditions are not good. The determination by the analysis unit 24 is based on objective data obtained from the sensor 10, and therefore a highly objective and highly accurate determination result can be provided to the participant. As a result, the participant can more accurately determine whether or not it is okay for him or her to drive for a long period of time.

[0161] As described above, the subjective physical information of the participant acquired by the physical information input unit 21 is stored in the pre-equipment engagement sleep database 32 by the storage unit 26, for example. The analysis unit 24 may determine whether it is desirable for the participant to engage with the equipment, taking into account the subjective physical information stored in the pre-equipment engagement sleep database 32. In this case, it becomes possible to analyze and determine the physical information taking into account not only objective data but also subjective data, thereby making it possible to provide information with even higher accuracy.

[0162] (Second embodiment) Next, a health condition notification system according to the second embodiment will be described. In the first embodiment described above, an example was described in which the notification unit 25 displays an output screen 43 showing the results determined by the analysis unit 24 on the terminal T of the participant. However, the recipient of the notification by the notification unit 25 is not limited to the participant. In the second embodiment, an example will be described in which the recipient of the notification by the notification unit 25 is the employer of the participant. "Employer" refers to the person or organization (e.g., a company) that employs the participant. Below, explanations that overlap with the contents of the first embodiment will be omitted as appropriate.

[0163] 7, the analysis unit 24 performs the above-mentioned analysis and judgment on multiple participants (e.g., drivers), and the notification unit 25 displays an output screen 47 showing the judgment results of the multiple participants on the employer's terminal T. The output screen 47 is a screen on which the judgment results of the multiple people by the analysis unit 24 are output. The output screen 47 displays a table 48 summarizing the judgment results of the multiple people on the display of the terminal T.

[0164] The table 48 has a name display section 48b that displays the names of the participants, a drowsiness index display section 48c that displays the drowsiness index of the participants, a recommended time display section 48d that displays the recommended time, and a comment display section 48f. The name display section 48b displays, for example, the names of the drivers, and the drowsiness index display section 48c displays the drowsiness index for each driver.

[0165] The recommended time display section 48d displays the remaining driving time for each driver, and the comment display section 48f displays comments for each driver. The drowsiness index, recommended time (e.g., remaining driving time), and comments displayed in the table 48 may be updated every time the sensor 10 performs a measurement.

[0166] By looking at table 48, an employer employing multiple participants (e.g., drivers) can easily determine which drivers are capable of driving for long periods of time and which drivers can only drive for short periods of time. The notification unit 25 may display not only sleep state information such as a drowsiness index, but also autonomic nervous system information and apnea information for each participant. In this case, it is possible to determine with greater accuracy which participants are allowed to drive, and to avoid allowing participants with poor autonomic nervous system status or who may suffer from sleep apnea syndrome to drive for long periods of time. As a result, accidents while driving can be prevented.

[0167] Next, an example of the steps of the health condition notification method according to the second embodiment will be described with reference to the sequence diagram of FIG. 8. Steps S21 to S23 are the same as steps S1 to S3 of the first embodiment. In step S24, the analysis unit 24 analyzes and determines physical information for multiple users (drivers) (determining step, determining step). The content of step S24 is the same as the content of step S4 described above, except that it targets multiple users (drivers).

[0168] The notification unit 25 notifies the results of the analysis of the multiple users by the analysis unit 24 (notifying step, notifying process, step S25). At this time, the judgment result of the user by the analysis unit 24 is sent to the terminal T of the user, and the judgment results of the multiple users by the analysis unit 24 are sent to the terminal T of the employer of the multiple users. For example, an output screen 47 is displayed on the display of the terminal T of the employer.

[0169] The process contents from step S26 to step S29 are the same as the process contents from step S6 to step S9 described above. Then, the notification unit 25 notifies the determination results of the multiple people analyzed by the analysis unit 24 (notifying step, notifying step, step S30). The process contents of step S30 are the same as the process contents of step S25 described above. The process contents from step S21 to step S30 described above are executed before the user drives the car (when the involved person is not involved in the device).

[0170] The employer of the multiple users, for example, looks at the output screen 47 displayed on terminal T and decides which driver (user) to have drive for how long. Then, each of the multiple drivers starts driving the car (step S31). The process contents from step S32 to step S34 are the same as the process contents from step S12 to step S14 described above, except that the target is multiple drivers. In step S34, notification unit 25 notifies the judgment results of the multiple users analyzed by analysis unit 24 (notifying step, notifying step), and then the series of steps of the health condition notification method is completed.

[0171] As described above, the second embodiment includes the sensor 10 provided at a position away from the device such as an automobile, the analysis unit 24 that determines whether it is desirable for a participant such as a driver to be involved in the device based on physical information from the sensor 10, and the notification unit 25 that notifies the result of the analysis by the analysis unit 24. Therefore, the second embodiment can achieve the same effects as the first embodiment.

[0172] In the second embodiment, the analysis unit 24 acquires, analyzes, and judges the physical information of multiple participants, and the notification unit 25 notifies the employer of the judgment results of the analysis unit 24 for the multiple participants. Therefore, it is possible to identify participants among the multiple participants who are undesirable for involvement with the equipment, and to prevent accidents caused by such participants' involvement with the equipment. The employer can manage work shifts so that participants do not accumulate fatigue, and can encourage participants to undergo health checkups as necessary. Furthermore, the employer can encourage participants to take naps or rest.

[0173] In the second embodiment, the notification unit 25 notifies the employer of the physical and mental conditions of multiple drivers, thereby preventing drivers who are not in good physical or mental condition from driving for long periods of time. For example, if the driver is a bus driver, the notification unit 25 may notify passengers of the driver's physical and mental condition. In this case, by notifying passengers that the driver is in good physical and mental condition, the passengers can be reassured and safety can be ensured.

[0174] Various embodiments of the health status notification system, health status notification program, and health status notification method according to the present disclosure have been described above. However, the present disclosure is not limited to the above-described embodiments, and may be further modified within the scope of the gist of the claims. In other words, the configuration and function of each part of the health status notification system and health status notification program, as well as the content and order of the steps of the health status notification method, may be modified as appropriate within the scope of the above-described gist. Various modifications are described below.

[0175] The health condition notification system 1, health condition notification program 20, and health condition notification method according to the above-described embodiments can grasp the physical condition of a driver of a vehicle by analyzing, determining, and notifying the driver's physical information. The health condition notification system and health condition notification program may be linked to any of the devices and systems installed in the vehicle.

[0176] The health condition notification system and the health condition notification program may be linked to a safety device of the vehicle. For example, the notification unit 25 may activate a safety device of the vehicle when a driver who is determined by the analysis unit 24 to be unsuitable for driving a vehicle for long periods of time drives the vehicle. For example, the notification unit 25 may cause the vehicle to drive automatically when a driver who is determined by the analysis unit 24 to be unsuitable for driving a vehicle drives the vehicle. Furthermore, the notification unit 25 may output an alert at regular intervals or encourage the driver to take a break when the driver is driving the vehicle. The notification unit 25 may notify the driver of information about service areas where resting is possible when the driver is driving the vehicle.

[0177] For example, analysis unit 24 may analyze the sleep state information stored in past sleep accumulation database 31 and pre-device engagement sleep database 32, and if it determines that the driver's drowsiness index is equal to or greater than a certain value, may activate the automatic brakes of the vehicle earlier than a predetermined time when the driver is driving the vehicle. For example, analysis unit 24 may analyze the sleep state information stored in past sleep accumulation database 31 and pre-device engagement sleep database 32, and if it determines that the driver's drowsiness index is equal to or greater than a certain value, may activate the automatic brakes of the vehicle more strongly than a predetermined strength when the driver is driving the vehicle.

[0178] For example, if the vehicle has a function to output an audio alert when it approaches an obstacle by a certain distance, the analysis unit 24 may analyze the sleep state information stored in the past sleep accumulation database 31 and the pre-device involvement sleep database 32, and if it determines that the driver's sleepiness index is above a certain value, it may increase the certain distance.

[0179] For example, the analysis unit 24 may analyze the sleep state information stored in the past sleep accumulation database 31 and the pre-appliance sleep database 32, and if it determines that the driver's drowsiness index is above a certain value, it may lower the set temperature of the vehicle's air conditioner. In this case, it is possible to avoid inducing drowsiness in the driver by making the interior of the vehicle cooler. For example, the analysis unit 24 may analyze the sleep state information stored in the past sleep accumulation database 31 and the pre-appliance sleep database 32, and if it determines that the driver's drowsiness index is above a certain value, it may increase the air volume of the vehicle's air conditioner. In this case, the same effect as above can be obtained.

[0180] In the above-described embodiment, an example in which the participant is a driver has been described. However, the participant may be a person other than a driver. The participant may be anyone who is involved with the equipment. The participant may be, for example, a medical professional including a doctor, nurse, or paramedic, a construction worker, a control tower worker, an air traffic controller, a road or railway monitoring center worker, a teacher, a police officer, a firefighter, an IT engineer, a food processor, a manufacturing line worker, or a customer service representative.

[0181] In the above-described embodiment, an example in which the device is an automobile has been described. However, the device may be something other than an automobile. For example, the device may be a robotic hand such as a surgical robotic hand, a construction machine, a remotely controlled tool, a computer, a precision machine, a train, a ship, a bicycle, an aircraft, or an industrial vehicle. [Explanation of symbols]

[0182] 1...health condition notification system, 10...sensor, 11...sensor sheet, 11b...sheet-like fabric, 11c...sensor unit, 11d...power supply unit, 11f...thread-like sensor, 11f1...first waveform unit, 11f2...second waveform unit, 11h...data acquisition unit, 12...cushion sensor, 12b...seating unit sensor, 12c...sacrum support unit sensor, 12d...thigh support unit sensor, 13...cushion, 14...core material, 15...seating unit, 15b...buttocks support unit, 15c...thigh support unit, 16...lumbar support unit, 16b...general unit, 16c...sacrum support unit, 20...health condition notification program, 21...body Information input unit, 22...autonomic nervous system acquisition unit, 23...respiratory information acquisition unit, 24...analysis unit, 25...notification unit, 26...memory unit, 31...past sleep accumulation database, 32...sleep database before device involvement, 33...database before device involvement, 34...database during device involvement, 35...database after device involvement, 41...input screen, 42...evaluation input unit, 43...output screen, 44...drowsiness index output unit, 45...comment display unit, 46...recommended time display unit, 47...output screen, 48b...name display unit, 48c...drowsiness index display unit, 48d...recommended time display unit, 48f...comment display unit, T...terminal.

Claims

1. A health status notification system that notifies the health status of a participant who is a person involved in a device, a sensor provided at a position remote from the device for acquiring physical information of the participant; an analysis unit that receives the physical information from the sensor, analyzes the physical information, and determines whether it is desirable for the participant to be involved in the device; a notification unit that notifies the result of the analysis by the analysis unit; Equipped with When the participant is not involved in the device, the sensor acquires the physical information, the analysis unit makes the determination, and the notification unit notifies the result. Health status notification system.

2. When the participant is sleeping, the sensor acquires the physical information, the analysis unit makes the determination, and the notification unit notifies the result. The health condition notification system of claim 1 .

3. When the participant is not using the equipment and is sitting, the sensor acquires the physical information, the analysis unit makes the determination, and the notification unit notifies the result. The health condition notification system of claim 1 .

4. The physical information includes sleep state information that is information indicating the sleep state of the participant. The health condition notification system according to claim 1 or 2.

5. The physical information includes autonomic nerve information that is information indicating the state of the autonomic nerves of the participant. The health condition notification system according to claim 1 or 2.

6. The physical information includes apnea information that indicates an apnea state of the participant during sleep. The health condition notification system according to claim 1 or 2.

7. A health status notification program for notifying a participant of a health status of a person involved in a device, On the computer, receiving physical information of the participant from a sensor located away from the device, and analyzing the physical information to determine whether it is desirable for the participant to participate in the device; a step of notifying the result of the analysis in the determining step; when the participant is not involved with the device; Health Status Notification Program.

8. A health status notification method for notifying a health status of a participant who is a person involved in a device, comprising: a step of acquiring physical information of the participant by a sensor provided at a position remote from the device; an analysis unit that receives the physical information from the sensor and analyzes the physical information to determine whether it is desirable for the participant to be involved in the device; a step of notifying the result of the analysis in the determining step by a notifying unit; Equipped with performing the steps of acquiring the physical information, the step of determining, and the step of notifying when the participant is not involved in the device; Health status notification method.

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