Life improvement system

Abstract

A life improvement system is provided with: a sensor unit that acquires respiration information, body movement information, and heartbeat information; a sleep state acquisition unit that acquires sleep state information on the basis of at least one of breathing information, body movement information, and heartbeat information; a vegetative nerve acquisition unit that acquires vegetative nerve information on the basis of the heartbeat information; a device control unit that controls the operation of the device on the basis of at least one of pre-stored past sleep information and vegetative neural information; a prediction information generation unit that generates prediction information on the basis of the past sleep information and / or the vegetative neural information; and an improvement information generation unit that generates improvement information on the basis of the prediction information.

Description

Technical Field

[0001] The present disclosure relates to a life improvement system.

[0002] This application claims priority based on Japanese application No. 2023-021847, filed on February 15, 2023, and incorporates by reference all the disclosures disclosed in the aforementioned Japanese application. Background Art

[0003] Japanese Patent Application Laid-Open No. 2006-087850 describes a sleep state sensing system for detecting a person's sleep state. This sleep state sensing system comprises: a radio wave transceiver that transmits microwaves toward a sleeping person and receives reflected waves from the microwaves, which are affected by the person's body movements; and a computer that analyzes the reflected wave data to detect the person's sleep state. Based on the detected sleep state, the computer controls the operation and shutdown of air conditioning, lighting, and audio equipment.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Laid-Open No. 2006-087850 Summary of the Invention

[0007] Problems to be solved by the invention

[0008] The aforementioned sleep state sensing system controls the operation and shutdown of air conditioning, lighting, and audio equipment based on the user's sleep state from the time they go to bed until they wake up. However, to improve the user's life, there may be a need to predict the user's wakefulness state after waking up and provide information to improve the user's life.

[0009] An object of the present disclosure is to provide a life-improving system that can predict a user's state of wakefulness and provide information for improving the user's life.

[0010] Means used to solve problems

[0011] (1) The life improvement system disclosed in the present invention is a life improvement system for improving the life of a user. The life improvement system comprises: a sensor unit that acquires at least one of information representing the user's breathing, namely, breathing information, information representing the user's body movement, namely, body movement information, and information representing the user's heartbeat, namely, heartbeat information; a sleep state acquisition unit that acquires information representing the user's sleep state, namely, sleep state information, based on at least one of the breathing information, body movement information, and heartbeat information; an autonomic nerve acquisition unit that acquires information representing the state of the user's autonomic nerves, namely, autonomic nerve information, based on the heartbeat information; a device control unit that controls the operation of devices constituting the user's surrounding environment based on pre-stored past sleep state information, namely, past sleep information, and at least one of autonomic nerve information; a prediction information generation unit that generates information representing the predicted state of the user while awake, namely, prediction information, based on at least one of the past sleep information and autonomic nerve information; and an improvement information generation unit that generates information for improving the user's life, namely, improvement information, based on the prediction information.

[0012] This life-improvement system generates predictive information for the user based on at least one of past sleep information and autonomic nervous system information. For example, the life-improvement system can provide the user with information indicating the user's physical and mental state as predictive information. This life-improvement system generates improvement information based on the predictive information. For example, if the life-improvement system predicts that the user's physical and mental state is trending downward, it can provide the user with information as improvement information that recommends not making important decisions. The life-improvement system not only controls devices while the user is asleep but also predicts the user's waking state based on their sleep and provides information to improve the user's life based on their sleep state. This life-improvement system can generate predictive information and improvement information based on the user's past sleep state. In addition to the user's sleep state for the current day, the system can also consider the user's past sleep state to generate predictive information indicating the user's predicted waking state and improvement information to improve their life. Compared to generating predictive information and improvement information based solely on the user's sleep state from bedtime to waking, this system can generate predictive information and improvement information based on longer-term records. As a result, it can generate more accurate predictive information and improvement information.

[0013] (2) In the above (1), the sensor unit may include a seat cushion sensor attached to a seat cushion on which the user sits. In this case, for example, the user's vital sign data can be obtained not only during sleep but also during the day. Since the prediction information and improvement information can be generated by taking into account the user's vital sign data during the day, the prediction information and improvement information can be generated more accurately by utilizing the user's state both during sleep and when awake.

[0014] (3) In (1) or (2) above, the prediction information may include mental information representing the user's mental state, physical information representing the user's physical condition, and brain information representing the user's mental state. In this case, the user's mental, physical, and mental states can be predicted while awake.

[0015] (4) In the above (3), the physical condition information may include skin information indicating the condition of the user's skin. In this case, the information indicating the condition of the user's skin can be provided as prediction information.

[0016] (5) In any of the above (1) to (4), the improvement information generating unit may generate the improvement information based on subjective information, which is information indicating a user's subjective evaluation. In this case, the improvement information can be generated taking into account the user's subjective evaluation, thereby enabling more accurate generation of the improvement information.

[0017] (6) In any of the above (1) to (5), the improvement information may include information indicating the type of clothing recommended to the user. In this case, the information indicating the type of clothing recommended to the user can be provided as the improvement information.

[0018] (7) In any of the above (1) to (6), the improvement information may include information indicating the type of food recommended to the user. In this case, the information indicating the type of food recommended to the user can be provided as the improvement information.

[0019] (8) In any of the above (1) to (7), the improvement information may include information indicating the type of cosmetic recommended to the user. In this case, the information indicating the type of cosmetic recommended to the user can be provided as the improvement information.

[0020] (9) In any of the above (1) to (8), the device may include a pillow for the user to use when sleeping, and the device control unit may control the angle of the pillow's support surface relative to the horizontal plane that supports the user's head. In this case, since the angle of the pillow's support surface can be adjusted while the user is sleeping, the user's sleeping condition can be further improved.

[0021] (10) In any of the above (1) to (9), the life-improving system may include an arrhythmia detection unit that detects whether the user has arrhythmia based on the heartbeat information obtained by the sensor unit. In this case, by detecting the presence of arrhythmia based on the heartbeat information obtained by the sensor unit, information on the presence of arrhythmia can be obtained during sleep or wakefulness. The user can understand whether they have arrhythmia.

[0022] (11) Another aspect of the present disclosure is a life-improving system for improving a user's life. The life-improving system includes: a sensor unit that acquires heartbeat information, which is information indicating the user's heartbeat; an autonomic nerve acquisition unit that acquires autonomic nerve information, which is information indicating the state of the user's autonomic nerves, based on the heartbeat information; a prediction information generation unit that generates prediction information, which is information indicating the predicted state of the user while awake, based on the autonomic nerve information; and an improvement information generation unit that generates improvement information, which is information indicating improvement of the user's life, based on the prediction information.

[0023] This life-improving system generates prediction information about the user based on autonomic nerve information and generates improvement information based on the prediction information. Thus, similar to the aforementioned life-improving system, it can predict the user's state of wakefulness and provide information to improve the user's life.

[0024] Effects of the Invention

[0025] According to the present disclosure, the user's state of wakefulness can be predicted, and information for improving the user's life can be provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a block diagram showing an example of a life-improving system.

[0027] Figure 2 Yes Figure 1 FIG. 1 is a diagram showing an example of a subjective information input screen displayed on an information terminal.

[0028] Figure 3 (a) is a perspective view showing a buffer body to which a sensor sheet is mounted. Figure 3 (b) indicates the composition Figure 3 A three-dimensional view of the core material of the buffer body shown in (a).

[0029] Figure 4 This is a perspective view showing a core material of a seat cushion to which a seat cushion sensor is mounted.

[0030] Figure 5 Yes Figure 1 FIG. 1 is a diagram showing an example of an output screen of prediction information and improvement information displayed on an information terminal.

[0031] Figure 6 Yes Figure 1 FIG. 1 is a diagram showing an example of an output screen of feedback information displayed on an information terminal shown.

[0032] Figure 7 This is a flowchart showing an example of the operation of the life improvement system.

[0033] Figure 8This is a flowchart showing an example of the arrhythmia detection function of the life-improving system. DETAILED DESCRIPTION

[0034] The following describes an example of the life-improving system disclosed herein with reference to the accompanying drawings. In the accompanying drawings, identical or corresponding elements are designated by the same reference numerals, and duplicate descriptions are omitted as appropriate. For ease of understanding, the drawings may be partially simplified or exaggerated, and dimensional ratios, etc., are not limited to those depicted in the drawings.

[0035] The life-improving system disclosed herein improves the lives of its users. The life-improving system can be used, for example, as a personal or home system, or as a system for experimental research in research institutes, etc. It can also be used as a therapeutic system in hospitals, etc. A "user" refers to someone whose life is improved by the life-improving system. Examples of users include those facing health risks due to disrupted lifestyles, those receiving medical treatment in hospitals, etc., or those who wish to improve their lives.

[0036] Figure 1 1 is a block diagram showing an example of a life-improving system 1. The life-improving system 1 includes a sensor unit 11, an information terminal 101, and a life-improving server 102.

[0037] The information terminal 101 is, for example, a mobile terminal. A "mobile terminal" is a portable information terminal, such as a mobile phone including a smartphone, a tablet computer, a laptop computer, a wearable terminal such as a watch, etc. The information terminal 101 may also be a terminal other than a mobile terminal, for example, a desktop computer. As an example, the information terminal 101 includes a processor (such as a CPU) that executes an operating system and software (applications), a main storage unit composed of ROM and RAM, an auxiliary storage unit composed of a flash memory, a communication control unit composed of a wireless communication module, an input device, and an output device such as a display. However, the structure of the information terminal 101 is not limited to this and can be changed appropriately.

[0038] On the information terminal 101, a life-improving application 40 is executed as an application. The life-improving application 40 may be an application downloaded to the information terminal 101 and executed there, or it may be executed on the life-improving server 102. The life-improving application 40 may also be an application downloaded from the life-improving server 102. The following describes an example in which the life-improving application 40 is an application downloaded to the information terminal 101 and the functions of the life-improving application 40 are executed there.

[0039] The various functions of the life-improving application 40 are implemented by having the processor or main storage read and execute prescribed software. The processor operates the aforementioned communication control unit, input device, and output device according to this software, and reads and writes data from and to the main storage or auxiliary storage. The data and databases required to execute the functions of the life-improving application 40 are stored in the main storage or auxiliary storage.

[0040] Each functional element of the information terminal 101 is implemented by having the processor or storage unit (e.g., the aforementioned main storage unit or auxiliary storage unit) read and execute specified software. The processor operates the aforementioned communication control unit, input device, and output device according to the software, and reads or writes data from or to the storage unit. The data and database used in the processing of the life improvement server 102 are stored in the storage unit.

[0041] The life-improving application 40 can be a distributed processing system composed of multiple computers, or a client-server system or a cloud system. The life-improving application 40 includes, for example, a main module, a data acquisition module, a determination module, and an output module. By executing the data acquisition module, the determination module, and the output module, the various functional elements of the life-improving application 40 function. As an example, the life-improving application 40 can be provided by being fixedly recorded on a physical storage medium such as a CD-ROM, DVD-ROM, or semiconductor memory. The life-improving application 40 can also be provided as a data signal superimposed on a carrier wave via a communication network. The functional structure of the life-improving application 40 will be described later.

[0042] The information terminal 101 is a terminal that can input information by accepting user operations. The information terminal 101 can transmit the input information to the life improvement server 102. For example, the information terminal 101 transmits subjective information, which is information indicating the user's subjective evaluation, to the life improvement server 102.

[0043] Figure 2 This figure shows an example of a subjective information input screen 80 displayed on information terminal 101. Input screen 80 is a screen for inputting subjective information. Subjective information includes, for example, a subjective sleep evaluation. Input screen 80 includes a sleep evaluation input section 81 for inputting a subjective sleep evaluation. In sleep evaluation input section 81, a subjective sleep evaluation, for example, with 100 as the full score, is input as a score.

[0044] The information terminal 101 displays prediction information and improvement information. The prediction information and improvement information will be described in detail later.

[0045] Information terminal 101 can access a specific website 103. For example, website 103 includes at least one of an online shopping website, where goods such as clothing, food, soap, and cosmetics are sold, and a travel website, where travel websites promote travel and accept reservations for accommodation facilities. Website 103 transmits information to information terminal 101 in response to a request from information terminal 101. The information transmitted by website 103 includes, for example, a URL (Uniform Resource Locator). Information transmitted from website 103 to information terminal 101 is displayed on information terminal 101 and provided to the user. Website 103 can also be accessed from life improvement server 102.

[0046] The sensor unit 11 obtains information about the user's body. The sensor unit 11 obtains at least one of respiratory information, body movement information, and heartbeat information. As an example, the sensor unit 11 obtains respiratory information, body movement information, and heartbeat information. Respiratory information is information indicating the user's respiration. Body movement information is information indicating the user's body movement. Heartbeat information is information indicating the user's heartbeat. Heartbeat information includes, for example, a heartbeat waveform. The content of the information obtained by the sensor unit 11 can be appropriately changed. The sensor unit 11 can also further obtain at least one of information indicating the user's body temperature, information indicating blood pressure, and information indicating a blood sugar level. The sensor unit 11 includes a sensor sheet 12 mounted on the mattress 10a and a seat cushion sensor 13 mounted on the seat cushion 10b.

[0047] Figure 3 (a) is a perspective view showing a mattress 10a to which the sensor sheet 12 is mounted. Figure 3 (b) indicates the composition Figure 3 (a) shows a perspective view of the core material 2 of the mattress 10a. The sensor sheet 12 is detachable from the mattress 10a. The sensor sheet 12 acquires vital sign data of the user lying on the mattress 10a. For example, the sensor sheet 12 can acquire an electrocardiogram. The aforementioned vital sign data includes, for example, respiratory information, body movement information, and heart rate information. The sensor sheet 12 acquires the user's respiratory information, body movement information, and heart rate information while sleeping.

[0048] For example, the sensor sheet 12 includes a sheet of fabric into which a thread-shaped sensor is embroidered, and the position of the sheet of fabric relative to the mattress 10a can be changed. The thread-shaped sensor of the sensor sheet 12 is fixed to the sheet of fabric in a two-dimensionally unfolded manner, for example, by embroidery. As an example, the thread-shaped sensor is a piezoelectric sensor. In this case, the piezoelectric sensor of the sensor sheet 12 generates an electrical signal corresponding to the load applied to the user's body. The sensor sheet 12 obtains the electrical signal as the aforementioned respiratory information, body movement information, and heartbeat information. Hereinafter, the electrical signal obtained as respiratory information, body movement information, and heartbeat information may also be referred to as a "signal."

[0049] The sensor sheet 12 includes, for example, the aforementioned filamentary sensor (one example being a piezoelectric sensor) and a communication unit that outputs respiratory information, body movement information, and heartbeat information as electrical signals generated by the filamentary sensor to the outside of the sensor sheet 12. The above description describes an example in which the sensor sheet 12 includes a piezoelectric sensor. However, the type of sensor in the sensor sheet 122 is not particularly limited and is not limited to piezoelectric sensors. For example, the sensor sheet 12 may also include an acceleration sensor.

[0050] Respiration information includes a signal indicating the user's body movements associated with breathing. "Body movements associated with breathing" refers to body movements associated with breathing. Sensor sheet 12 detects the user's body movements associated with breathing. Sensor sheet 12 outputs a signal indicating the body movements associated with breathing to the outside of sensor sheet 12. Heartbeat information includes a signal indicating the user's body movements associated with heartbeat. "Body movements associated with heartbeat" refers to body movements associated with heartbeat. Sensor sheet 12 detects the user's body movements associated with heartbeat. Sensor sheet 12 outputs a signal indicating the body movements associated with heartbeat to the outside of sensor sheet 12. Body movement information includes a signal indicating the user's body movements not associated with breathing or heartbeat. "Body movements not associated with breathing or heartbeat" refers to body movements unrelated to breathing or heartbeat, such as body movements caused by turning over. Sensor sheet 12 detects the user's body movements not associated with breathing or heartbeat. The sensor sheet 12 outputs a signal indicating body movement that is not accompanied by breathing and heartbeat to the outside of the sensor sheet 12 .

[0051] For example, the sensor sheet 12 is attached to a mattress 10a that supports the user's body. The mattress 10a has a rectangular shape when viewed from above. The mattress 10a extends along a longitudinal direction D1 and a transverse direction D2 perpendicular to the longitudinal direction D1. The mattress 10a has a thickness in a thickness direction D3 perpendicular to both the longitudinal direction D1 and the transverse direction D2.

[0052] The length of the mattress 10a in the longitudinal direction D1 is, for example, 120 cm to 210 cm (one example is 195 cm). The length of the mattress 10a in the transverse direction D2 is, for example, 70 cm to 180 cm (one example is 97 cm). The length of the mattress 10a in the thickness direction D3 is, for example, 3 cm to 40 cm (one example is 9 cm).

[0053] For example, the user of the mattress 10a places his or her body on the mattress 10a. In this case, the extending direction of the user's body (ie, the direction connecting the user's head and feet) coincides with, for example, the longitudinal direction D1 of the mattress 10a.

[0054] like Figure 3 As shown in (b), mattress 10a includes a core material 2 housed within a cover material 3, described later. For example, core material 2 has a rectangular shape when viewed from above. Core material 2 includes, for example, a content and a bag that holds the content. The content is, for example, polyurethane foam or polyester. The bag is made of, for example, cotton or polyester.

[0055] The core material 2 is in the shape of a rectangular parallelepiped. The core material 2 has an upper surface 21 that supports the user's body and a lower surface 22 facing the opposite side of the upper surface 21. The upper surface 21 is one side facing the thickness direction D3 ( Figure 3 The lower surface 22 is the surface facing the other side in the thickness direction D3 ( Figure 3 The core material 2 has a plurality of side surfaces 23 connecting the upper surface 21 and the lower surface 22.

[0056] like Figure 3 As shown in (a), the mattress 10a has a cover material 3. For example, the cover material 3 is bag-shaped and has a rectangular shape when viewed from above. The cover material 3 has, for example, a surface layer 31 covering the upper surface 21 of the core material 2, a back layer 32 covering the lower surface 22 of the core material 2, and an opening and closing member 33 connecting the surface layer 31 and the back layer 32 to each other. The opening and closing member 33 is provided at a position in the cover material 3 corresponding to the side surface 23 of the core material 2. When observed from the thickness direction D3, the opening and closing member 33 is located on the outside of the side surface 23 of the core material 2. The cover material 3 is detachable relative to the core material 2. "Disassembly relative to the core material" includes the case where the cover material is lifted relative to the core material and the case where the cover material is rolled up to expose at least a portion of the core material.

[0057] As an example, the opening and closing member 33 is a so-called double slider type and may include two sliders 34 and an opening and closing portion 35 that opens and closes the surface layer 31 and the back layer 32 by sliding the sliders 34 .

[0058] For example, by moving the first slider 34 along the opening and closing portion 35 in the first direction ( Figure 3(a) in the clockwise direction), and the second slider 34 is slid along the opening and closing portion 35 in a second direction ( Figure 3 Sliding in the counterclockwise direction in (a) can open the surface layer 31 and the back layer 32.

[0059] Furthermore, by sliding the first slider 34 along the opening and closing portion 35 in the second direction, and by sliding the second slider 34 along the opening and closing portion 35 in the first direction, the surface layer 31 and the back layer 32 can be closed. The opening and closing member 33 may also be a so-called single slider type. In this case, the opening and closing member 33 includes a slider 34 and an opening and closing portion 35.

[0060] The sensor sheet 12 is, for example, placed inside the bag-shaped cover 3. The sensor sheet 12 is positioned between the core 2 and the cover 3. When the sensor sheet 12 is attached to the mattress 10a, for example, it is positioned so as to extend along the short-side direction D2 of the mattress 10a. In this case, when viewed from the cover 3 of the mattress 10a, the sensor sheet 12 is located on the side opposite the user's body. Therefore, when the user's body rests on the mattress 10a, the sensor sheet 12 does not come into contact with the user. The sensor sheet 12 acquires the user's breathing, body movement, and heart rate information in a contactless manner.

[0061] The sensor sheet 12 is installed at a position corresponding to the user's heart in the longitudinal direction D1. As an example, the sensor sheet 12 is installed at a position separated from the position where the user's head is placed along the longitudinal direction D1 of the mattress 10a ( Figure 3 The position of the sensor sheet 12 in the longitudinal direction D1 can be changed. The distance from the position where the user's head is supported to the position where the sensor sheet 12 is installed can be, for example, 40 cm to 50 cm (50 cm in one example).

[0062] Figure 4 This is a perspective view of the core material 14 of the seat cushion 10b, to which the seat cushion sensor 13 is mounted. The seat cushion 10b includes, for example, the core material 14 and a bag-shaped fabric material (not shown) that houses the core material 14. The core material 14 includes a horizontally extending seat portion 15 and a lumbar support portion 16 that extends upward from the seat portion 15. The core material 14 is made of a flexible material such as polyurethane foam.

[0063] The seat portion 15 extends in a first direction A1 and a second direction A2 intersecting the first direction A1. The first direction A1 is the front-to-back direction when viewed from a user seated on the seat portion 15, and the second direction A2 is the left-to-right direction when viewed from a user seated on the seat portion 15. The seat portion 15 has a thickness in a third direction A3 intersecting both the first direction A1 and the second direction A2. For example, the third direction A3 is a vertical direction. The seat portion 15 includes a buttocks support portion 15a and two thigh supports 15b. The buttocks support portion 15a and the thigh supports 15b are arranged so as to be aligned along the first direction A1.

[0064] Hereinafter, the front direction when viewed from a user sitting on the seat portion 15 may be referred to as "front," "front side," or "front," and the direction opposite to the front direction may be referred to as "rear," "rear side," or "rear." However, these directions are for convenience of explanation and do not limit the positions or orientations of the various components.

[0065] The buttocks support 15a is located on the rear side of the seat 15. The user's buttocks rest on the buttocks support 15a. The buttocks support 15a supports the user's buttocks. Two thigh supports 15b are arranged along the second direction A2 on the front side of the seat 15. The backs of the user's thighs rest on the thigh supports 15b. The thigh supports 15b support the backs of the user's thighs.

[0066] The lumbar support portion 16 extends upward from the end (rear end) of the seating portion 15 in the first direction A1. The lumbar support portion 16 includes, for example, a general portion 16a extending in both the second direction A2 and the third direction A3, and a sacrum support portion 16b located at the center of the general portion 16a in the second direction A2. The general portion 16a represents the portion of the lumbar support portion 16 excluding the sacrum support portion 16b.

[0067] The sacrum support portion 16b has a convex shape that protrudes forward. The sacrum support portion 16b protrudes forward from the general portion 16a. As an example, the shape of the sacrum support portion 16b viewed from the front has a major axis and a minor axis. For example, the shape of the sacrum support portion 16b viewed from the front is an oblong shape (an elliptical shape is an example).

[0068] The seat cushion sensor 13 obtains vital sign data of the user sitting on the seat cushion 10b. For example, the seat cushion sensor 13 obtains the user's heart rate information during the day. The seat cushion sensor 13 is, for example, a piezoelectric sensor fixed to the core material 14. In this case, the seat cushion sensor 13 measures the pressure exerted by the user's body supported on the seat cushion 10b on various parts of the seat cushion 10b. The type of seat cushion sensor 13 is not particularly limited. The seat cushion sensor 13 includes, for example, a seat sensor 13a mounted on the seat portion 15, a sacrum support sensor 13b mounted on the sacrum support portion 16b, and thigh support sensors 13c mounted on each of the two thigh support portions 15b.

[0069] The seat sensor 13a senses when a user sits on the seat 15. For example, the seat sensor 13a senses when the user's ischial bones contact the seat sensor 13a. The sacrum support sensor 13b measures, for example, the load on the user's body in contact with the sacrum support sensor 13b. The thigh support sensor 13c measures, for example, the load on the user's thighs while seated on the seat 15. The seat sensor 13a, sacrum support sensor 13b, and thigh support sensor 13c generate electrical signals corresponding to the load on the user's body, and acquire these electrical signals as, for example, the aforementioned heart rate information.

[0070] The functional structure of the life-improving application 40 is described. Figure 1 As shown, the life-improving application 40 includes, as its functional structure, a sleep state acquisition unit 41, an autonomic nerve acquisition unit 42, a storage unit 43, a device control unit 44, a prediction information generation unit 45, an improvement information generation unit 46, and an arrhythmia detection unit 47.

[0071] The sleep state acquisition unit 41 acquires sleep state information, which indicates the user's sleep state, based on at least one of the respiratory information, body movement information, and heart rate information acquired by the sensor unit 11. The sleep state refers to the user's sleep state. The sleep state information may include, for example, sleep duration, sleep stages, and other aspects of the user's sleep state, as well as other biological information about the user, such as fatigue and tension. For example, the sleep state information includes at least one of the user's bedtime, wake-up time, sleep stage ratio, sleep onset latency (sleep onset time), sleep efficiency, number of awakenings, and duration of awakenings.

[0072] Going to bed time refers to the time when the user goes to bed. Waking up time refers to the time when the user wakes up the next morning. Sleep stage is an indicator of the depth of the user's sleep. Sleep stages are classified into, for example, wakefulness, rapid eye movement (REM) sleep, and non-rapid eye movement (NREM) sleep. Non-REM sleep is classified into, for example, four sleep stages. In addition, non-REM sleep can also be classified into two or three sleep stages. Hereinafter, the stages of REM sleep or non-REM sleep are sometimes referred to as "sleep." The moment when the user's sleep stage changes from wakefulness to sleep during the period from going to bed time to waking up time is called the time of falling asleep. The moment when the user's sleep stage finally changes to the awake stage during the period from going to bed time to waking up time is called the awake time.

[0073] The proportion of sleep stages refers to the proportion of the time spent in each sleep stage relative to the time from going to bed to waking up. The sleep onset latency (sleep onset time) refers to the length of time from going to bed to falling asleep. Sleep efficiency is an indicator used to evaluate the quality of sleep. Sleep efficiency is, for example, the value obtained by subtracting the time spent waking up midway from the time from falling asleep to waking up, divided by the time from going to bed to falling asleep. Waking up midway means that the user is awake (wakes up) during the period from falling asleep to waking up. "Awake" means that the sleep stage changes from the stage of rapid eye movement sleep or non-rapid eye movement sleep to the stage of wakefulness.

[0074] The sleep state acquisition unit 41 determines the bedtime and waking time based on, for example, the body motion information acquired by the sensor unit 11 and the movement of the bedding detected by the sensor unit 11 (e.g., an accelerometer), and acquires the bedtime and waking time. The sleep state acquisition unit 41 acquires the sleep stage using, for example, signals output from the sensor unit 11 indicating body motion associated with breathing, signals indicating body motion associated with heartbeat, and signals indicating body motion not associated with breathing or heartbeat.

[0075] The sleep state acquisition unit 41 acquires the sleep stage ratio based on the sleep stage, bedtime, and wake-up time. The sleep state acquisition unit 41 acquires the time from bedtime to sleep onset as the sleep onset latency based on the bedtime and sleep stage.

[0076] The sleep state acquisition unit 41 acquires the time and number of awakenings during the middle of the night based on, for example, the bedtime, the waking time, and the sleep stage. For example, the sleep state acquisition unit 41 acquires the time of falling asleep based on the bedtime and the sleep stage, and acquires the time of waking up based on the waking time and the sleep stage. The sleep state acquisition unit 41 acquires the time and number of awakenings during the middle of the night based on the bedtime, the waking time, and the sleep stage.

[0077] The sleep state acquisition unit 41 acquires sleep efficiency based on, for example, bedtime, wake-up time, and sleep stage. The sleep state acquisition unit 41 acquires sleep efficiency based on, for example, bedtime, wake-up time, sleep onset time, wake-up time, and sleep awakening time.

[0078] The autonomic nerve acquisition unit 42 acquires autonomic nerve information, which indicates the state of the user's autonomic nerves, based on the heartbeat information acquired by the sensor unit 11. Autonomic nerves refer to nerves that control the functioning of organs such as the heart and stomach, as well as involuntary functions such as blood circulation. "Involuntary" means, for example, that the user's autonomic nerves are not in accordance with their own thoughts or intentions. The autonomic nerves are composed of sympathetic and parasympathetic nerves. The sympathetic and parasympathetic nerves regulate each other in a balanced manner.

[0079] The sympathetic nervous system functions during times of excitement, tension, or stress. This activity causes the body to respond with increased heart rate, shallow and rapid breathing, vasoconstriction, and increased blood pressure. The parasympathetic nervous system functions during times of relaxation, causing the body to respond with slower heart rate, deeper and slower breathing, vasodilation, lower blood pressure, and increased immune function. These autonomic nervous system responses, which cannot be controlled voluntarily, are used as objective indicators of mood, emotion, fatigue, and stress.

[0080] The autonomic nerve acquisition unit 42 acquires the user's heart rate variability (HRV) by, for example, analyzing the heart rate information acquired by the sensor unit 11. For example, the autonomic nerve acquisition unit 42 acquires information indicating the periodic components contained in the heart rate variability based on the user's heart rate variability. The autonomic nerve acquisition unit 42 performs frequency analysis on the periodic components of the heart rate variability to acquire information indicating the power spectrum of each frequency.

[0081] The autonomic nerve energy spectrum obtained as a result of the above-mentioned frequency analysis is divided into an LF (Low Frequency) component and an HF (High Frequency) component. The LF component is the integrated value of the energy spectrum in the low frequency range (0.04 Hz to 0.15 Hz, for example), and the HF component is the integrated value of the energy spectrum in the high frequency range (0.15 Hz to 0.4 Hz, for example). The LF component reflects sympathetic and parasympathetic nerve activity, while the HF component reflects parasympathetic nerve activity. The autonomic nerve acquisition unit 42 acquires information indicating a sympathetic nerve index and information indicating a parasympathetic nerve index as autonomic nerve information. The sympathetic nerve index is an indicator of the dominance of the sympathetic nerves. As an example, the sympathetic nerve index is the value obtained by dividing the LF component value by the HF component value. The parasympathetic nerve index is an indicator of the dominance of the parasympathetic nerves. As an example, the parasympathetic nerve index is the value obtained by dividing the HF component value by the sum of the LF and HF components.

[0082] The autonomic nerve acquisition unit 42 acquires the user's psychological state based on the autonomic nerve information. The autonomic nerve acquisition unit 42 classifies the user's psychological state into, for example, a high-performance state, a relaxed state, a stressed state, or a depression-prone state based on the autonomic nerve information.

[0083] A high-performance state, for example, refers to a state in which the sympathetic nerve index is above a predetermined first threshold and the parasympathetic nerve index is above a predetermined second threshold. A relaxed state, for example, refers to a state in which the sympathetic nerve index is below the first threshold and the parasympathetic nerve index is above the second threshold. A stressed state, for example, refers to a state in which the sympathetic nerve index is above the first threshold and the parasympathetic nerve index is below the second threshold. A depressive tendency state, for example, refers to a state in which the sympathetic nerve index is below the first threshold and the parasympathetic nerve index is below the second threshold.

[0084] For example, the life-improvement application 40 generates information indicating the user's exercise efficiency based on past sleep information stored in the life-improvement server 102, autonomic nerve information acquired by the autonomic nerve acquisition unit 42, and body temperature, blood pressure, and heart rate information acquired by the sensor unit 11. Past sleep information refers to information about the user's past sleep state. "Past" refers to a time point prior to the time when the device control unit 44 controlled the operation of the device 104. Past sleep information is, for example, accumulated data on the user's sleep information from several days ago to the previous day.

[0085] The above-mentioned motor performance is an indicator of the user's physical condition. The life-improving application 40 generates information indicating thinking ability based on past sleep information, autonomic nervous system information, and respiratory information. For example, the life-improving application 40 generates information indicating concentration and sleepiness based on autonomic nervous system information. The life-improving application 40 generates information indicating reaction speed based on autonomic nervous system information and body movement information. The life-improving application 40 can quantify the user's motor performance, thinking ability, concentration, and reaction speed. For example, the life-improving application 40 generates information indicating the number of times the user tossed and turned over based on past sleep information and body movement information.

[0086] The storage unit 43 stores the sleep state information acquired by the sleep state acquisition unit 41. For example, the storage unit 43 stores the sleep state information in the life-improving server 102. The storage unit 43 may store the sleep state information in the memory of the information terminal 101, for example.

[0087] The device control unit 44 controls the operation of the device 104 based on at least one of the past sleep information pre-stored in the life-improving server 102 and the autonomic nerve information obtained by the autonomic nerve obtaining unit 42. For example, the device control unit 44 can determine whether the sleep ratio is above a predetermined value based on the past sleep information. For example, the device control unit 44 can determine whether the sleep efficiency is above a predetermined value based on the past sleep information. For example, the device control unit 44 can determine whether the average value of the time from going to bed to falling asleep (sleep onset latency) in the past sleep information is above a predetermined time.

[0088] The device control unit 44 can, for example, determine whether the number of turning over is above a prescribed value based on information indicating the number of turning over. The device control unit 44 can, for example, determine whether the sympathetic nerve index is above a prescribed value based on autonomic nerve information. The device control unit 44 can, for example, determine whether the number of awakenings obtained by the sleep state acquisition unit 41 is above a prescribed value. The device control unit 44 can, for example, determine whether the user's exercise efficiency is above a prescribed value based on information indicating exercise efficiency. The device control unit 44 can, for example, determine whether the user's thinking ability is above a prescribed value based on information indicating thinking ability. The device control unit 44 can, for example, determine whether the user's reaction speed is above a prescribed value based on information indicating reaction speed. The device control unit 44 can control the action of the device 104 based on the determination results of at least any one of the foregoing.

[0089] The life-improving system 1 further includes a device server 105. The device server 105 is capable of communicating with the device control unit 44. The device server 105 receives information from the device control unit 44 for controlling the operation of the device 104. The device server 105 controls the device 104 based on the received information. However, if the device control unit 44 can communicate directly with the device 104, the device server 105 may not be provided. The device server 105 may also be capable of communicating with the life-improving server 102. In this case, the device server 105 can communicate with the information terminal 101 via the life-improving server 102.

[0090] The device 104 constitutes the user's surrounding environment and includes, for example, at least one of an air conditioner and lighting fixtures installed in the user's bedroom, a pillow and heated mattress used by the user when sleeping, a coffee machine, and a car.

[0091] For example, if device 104 is an air conditioner, device control unit 44 can adjust the temperature of the space the user is in by controlling the operation of the air conditioner. For example, if device control unit 44 determines that the REM sleep rate is greater than a predetermined value, device control unit 44 can control device 104 to increase the temperature of the space to warm the space.

[0092] For example, if device 104 is a lighting fixture, device control unit 44 can adjust at least one of the brightness and color temperature of the user's space by controlling the lighting fixture's operation. For example, if device control unit 44 determines that sleep efficiency is not above a predetermined value, device 104 can be controlled to brighten the user's space during the morning hours, such as the following morning. Device control unit 44 can also perform the same control described above if, for example, autonomic nervous system acquisition unit 42 classifies the user's mental state as either relaxed or depressive. In this case, the space can be brightened, thereby contributing to improvements in the user's mental state.

[0093] For example, if device 104 is a pillow, device control unit 44 can control the angle of the pillow's support surface relative to the horizontal plane by controlling the pillow's movement. For example, if the average time from bedtime to sleep onset in past sleep information is determined to be greater than a predetermined time, device control unit 44 can control device 104 to decrease the angle of the support surface relative to the horizontal plane. For example, if it is determined based on past sleep information and respiratory information that airway protection is necessary, the angle of the user's head and neck relative to the horizontal plane can be adjusted, thereby adjusting the pillow's tilt so that the user's head lies flat. This can suppress snoring.

[0094] For example, if device 104 is a heated mattress, device control unit 44 can adjust the temperature of the user's bed by controlling the operation of the heated mattress. For example, if device control unit 44 determines that the number of tossing and turning is not above a predetermined value and the sleep efficiency is not above a predetermined value, device control unit 44 can control device 104 to increase the temperature of the bed. For example, if device control unit 44 determines that the number of awakenings during sleep is above a predetermined value, device control unit 44 can control device 104 to increase the temperature of the bed in real time.

[0095] For example, if device 104 is a coffee machine, device control unit 44 can adjust the strength of the coffee that the user drinks after waking up by controlling the operation of the coffee machine. For example, if device control unit 44 determines that the sympathetic nerve index is not above a predetermined value, device control unit 44 can control device 104 to increase the strength of the coffee.

[0096] For example, in the case where the device 104 is a car, the car can perform vehicle control in multiple driving modes. The multiple driving modes include, for example, a steering assist mode (autonomous driving mode) that assists the driver in steering and a normal mode that does not assist in steering. The device control unit 44 can, for example, switch the driving mode of the car to a steering assist mode or a normal mode by controlling the car, or recommend the user to switch. For example, the device control unit 44 can switch the action of the car to a steering assist mode, or recommend the user to switch, if it is determined that the sports efficiency is not above a specified value. The device control unit 44 can, for example, perform the same control as above, if it is determined that the user's thinking ability is not above a specified value. The device control unit 44 can, for example, perform the same control as above, if it is determined that the user's reaction speed is not above a specified value. In other cases, the device control unit 44 can, for example, switch the action of the car to a normal mode or recommend the user to switch.

[0097] The prediction information generation unit 45 generates prediction information, which is information indicating the predicted state of the user while awake, based on at least one of the past sleep information obtained by the sleep state acquisition unit 41 and the autonomic nerve information obtained by the autonomic nerve acquisition unit 42. For example, the prediction information includes mental information indicating the user's mental state, physical condition information indicating the user's physical condition, and mental information indicating the user's mental state.

[0098] For example, the prediction information generating unit 45 may determine whether the sleep efficiency is above a predetermined value based on past sleep information. For example, the prediction information generating unit 45 may determine whether the user's concentration is above a predetermined value based on information indicating concentration. The prediction information generating unit 45 may generate prediction information based on the aforementioned sleep efficiency and concentration determination results.

[0099] The prediction information generation unit 45 generates mental information based on, for example, the autonomic nervous system information. Mental information includes, for example, information related to the user's mood swings. For example, the mental information includes information indicating whether the user's mood is prone to depression. For example, if the autonomic nervous system acquisition unit 42 classifies the user's mental state as a stressful state or a state prone to depression, the prediction information generation unit 45 may generate information indicating that the user's mood is prone to depression as mental information.

[0100] Prediction information generation unit 45 generates physical condition information based on past sleep information, for example. Physical condition information includes, for example, information indicating whether the user's physical condition is good while awake. For example, if the prediction information generation unit 45 determines that the user's sleep efficiency is not above a predetermined value, it may generate information indicating that the user's physical condition is likely to deteriorate as physical condition information. For example, the physical condition information includes skin information indicating the condition of the user's skin. This skin information may include information indicating that the user's skin quality is predicted to be poor. "Poor skin quality" refers to, for example, a state where the skin's moisture content has decreased from a predetermined value.

[0101] The prediction information generation unit 45 generates brain information based on, for example, past sleep information and autonomic nerve information. Brain information is information indicating whether the user's brain functions well. Brain information includes, for example, information indicating whether the user's concentration, memory, and thinking abilities are good. For example, when the autonomic nerve acquisition unit 42 classifies the user's mental state as a high-efficiency state, the prediction information generation unit 45 may generate information indicating that the user's concentration is predicted to be high as brain information. For example, when it is determined that the sleep efficiency is not above a specified value, the prediction information generation unit 45 may generate information indicating that the user's thinking ability is predicted to be low as brain information. For example, when the autonomic nerve acquisition unit 42 classifies the user's mental state as a stress state, a relaxed state, or a depressive tendency state, or when it is determined that the user's concentration is not above a specified value, the prediction information generation unit 45 may perform the same processing as described above.

[0102] Improvement information generation unit 46 generates improvement information, which is information for improving the user's life, based on the prediction information generated by prediction information generation unit 45. For example, the improvement information includes at least one of information indicating the type of clothing recommended to the user, information indicating the type of soap, cosmetics, and food, and information indicating a recommended action. Information indicating the type of clothing includes, for example, at least one of information on the color of the clothing, information on the type of fabric used, and the number of pieces of clothing to be worn.

[0103] For example, the improvement information generating unit 46 generates information indicating the type of cosmetics as improvement information based on the skin information generated by the prediction information generating unit 45. For example, if the prediction information generating unit 45 generates information indicating a prediction of poor skin quality, the improvement information generating unit 46 generates information indicating the type of cosmetics that improves the moisturizing ability of the skin.

[0104] For example, based on information indicating that the user is predicted to have a tendency toward depression, the improvement information generation unit 46 generates, as improvement information, information indicating the type of clothing (e.g., color) recommended to the user. For example, if the autonomic nerve acquisition unit 42 classifies the user's mental state as a state prone to depression, the improvement information generation unit 46 may generate improvement information recommending clothing in warm colors (e.g., red). For example, based on information indicating that the user is predicted to have poor skin quality, the improvement information generation unit 46 generates, as improvement information, at least one of information indicating the type of soap, cosmetics, and food recommended to the user and information indicating that the user should avoid sunlight during the day.

[0105] For example, based on information indicating that the user's thinking ability is expected to be low, improvement information generation unit 46 generates information indicating a recommendation not to make important decisions as improvement information. For example, based on information indicating movement efficiency, information indicating thinking ability, and information indicating reaction speed, improvement information generation unit 46 generates information indicating whether the vehicle's driving mode is recommended to be a steering assist mode or a normal mode as improvement information.

[0106] The arrhythmia detection unit 47 detects whether the user has arrhythmia based on the heartbeat information obtained by the sensor unit 11. An example of arrhythmia is respiratory arrhythmia. In respiratory arrhythmia, the heartbeat intervals shorten during inhalation and lengthen during exhalation. In this case, it is ideal to increase the oxygen concentration and blood flow during inhalation to allow more oxygen to enter the body, and to reduce them during exhalation to promote recovery from cardiac fatigue.

[0107] "Arrhythmia" manifests as any of a slower pulse, a faster pulse, and an irregular pulse. "Arrhythmia" refers to a state in which the speed or rhythm of the heartbeat (contraction and relaxation) becomes disordered. "Pulse" represents the rhythm of the heart pumping blood throughout the body, that is, the number of heartbeats within a certain period of time. If an arrhythmia occurs, symptoms such as palpitations, chest tightness, shortness of breath, weakness, dizziness, coma, and irregular pulse will occur. Arrhythmia is not dangerous in many cases. However, because arrhythmia is sometimes caused by heart disease, it is desirable to be able to properly detect arrhythmia.

[0108] Arrhythmias include slow arrhythmias, fast arrhythmias and extrasystoles. If it is a slow arrhythmia, the beat slows down (for example, below 50 BPM), and it is easy to feel breathless or weak. If the beat slows down further, dizziness or coma may occur. Arrhythmias include arrhythmias caused by sick sinus syndrome and arrhythmias caused by atrioventricular block. If the arrhythmia is caused by sick sinus syndrome, the sinus node becomes abnormal, the frequency of electrical signals decreases, and the beat slows down. If the arrhythmia is caused by atrioventricular block, the electrical signal is difficult to transmit or is interrupted in the path connecting the atria and ventricles.

[0109] If it is a rapid arrhythmia, the heartbeat becomes faster (for example, more than 100 BPM), and it is easy to feel palpitations or chest tightness. Arrhythmias include arrhythmias caused by atrial flutter, arrhythmias caused by atrial fibrillation, arrhythmias caused by ventricular tachycardia, and arrhythmias caused by ventricular fibrillation. If the arrhythmia is caused by atrial flutter, the atria beat slightly, and the heart rate reaches about 300 BPM. If the arrhythmia is caused by atrial fibrillation, the atria beat slightly, and the heart rate reaches about 500 BPM. If the arrhythmia caused by atrial fibrillation persists for a long time, it is possible that a blood clot will form in the atria and cause a cerebral infarction. If the arrhythmia is caused by ventricular tachycardia, abnormal electrical stimulation will be generated in the ventricles, and the heart rate will reach about 200 BPM. If the arrhythmia is caused by ventricular fibrillation, abnormal electrical stimulation will be generated in the ventricles, and the heart rate will reach about 400 BPM.

[0110] For example, the arrhythmia detection unit 47 detects the various arrhythmias described above. For example, the arrhythmia detection unit 47 classifies the heartbeat waveform into a normal waveform and an abnormal waveform. The arrhythmia detection unit 47 detects the abnormal waveform obtained through this classification as an arrhythmia. The arrhythmia detection unit 47 may also learn the normal and abnormal waveforms. In this case, the arrhythmia detection unit 47 can efficiently determine whether the heartbeat waveform is normal or abnormal.

[0111] The arrhythmia detection unit 47 detects the timing of occurrence of arrhythmia based on the heartbeat information, for example. The arrhythmia detection unit 47 can also calculate the frequency of arrhythmia based on the heartbeat information. The arrhythmia detection unit 47 can also calculate the duration of arrhythmia based on the heartbeat information. The arrhythmia detection unit 47 can also detect the presence or absence of extrasystoles based on the heartbeat information. "Extrasystoles" refer to irregular pulsations occurring during a normal pulsation period. "Extrasystoles" sometimes also refer to pulsations occurring earlier due to a timing shift between pulsations occurring at a certain rhythm. For example, the arrhythmia detection unit 47 detects the presence of extrasystoles when it detects a heart rate that is X times (X is a positive real number) or more than the previous heart rate, or when it detects a heart rate that is 1 / X times or less than the previous heart rate. As an example, the value of X is 2.

[0112] The prediction information generating unit 45 may also include information about arrhythmias detected by the arrhythmia detecting unit 47 in the prediction information. For example, the prediction information generating unit 45 may also predict a disease that the user may develop in the future based on the information about arrhythmias detected by the arrhythmia detecting unit 47, and include the predicted disease in the prediction information. The improvement information generating unit 46 may also generate information for eliminating the arrhythmia as improvement information based on the information about arrhythmias detected by the arrhythmia detecting unit 47. For example, the improvement information generating unit 46 may include in the improvement information information a recommendation to get sleep, reduce alcohol intake, or visit a hospital (for example, a cardiovascular department). The improvement information generating unit 46 may also include in the improvement information a recommendation to avoid dangerous work and driving a car. The improvement information generating unit 46 may also include in the improvement information a recommendation to adopt at least one of breathing techniques and relaxation techniques.

[0113] For example, the life-improving application 40 displays the prediction information generated by the prediction information generating unit 45 and the improvement information generated by the improvement information generating unit 46 on the information terminal 101 . Figure 5 This figure shows an example of an output screen 82 of prediction information and improvement information displayed on the information terminal 101. The life improvement application 40 displays the prediction information and improvement information on the information terminal 101 as output screen 82. Output screen 82 is, for example, a screen for providing the prediction information and improvement information to the user. Output screen 82 includes a prediction information display portion 83, which displays prediction information, and an improvement information display portion 84, which displays improvement information.

[0114] The prediction information display unit 83 may, for example, display at least one of information indicating that the user's mood is predicted to be low, information indicating that skin quality is predicted to be poor, and information indicating that concentration and thinking ability are predicted to be low. Alternatively, the prediction information display unit 83 may display at least one of information indicating that the user's mood is predicted to be high, information indicating that skin quality is predicted to be good, and information indicating that concentration and thinking ability are predicted to be high.

[0115] For example, the improvement information display unit 84 displays at least one of information indicating a recommended clothing color for the user, information indicating that the user should avoid sunlight during the day, information indicating that the user should not make important decisions, and information indicating that the steering assist mode is recommended as the driving mode for the vehicle. For example, the improvement information display unit 84 displays information indicating soap, cosmetics, and food recommended for the user. For example, the improvement information display unit 84 displays the URL of the website 103 that contains information related to the product recommended to the user.

[0116] For example, the improvement information generation unit 46 generates improvement information based on the aforementioned prediction information and subjective information. The improvement information generation unit 46 may also obtain objective information based on past sleep information and autonomic nervous system information. Objective information refers to objective information about the user obtained from objective data obtained through measurements such as sleep state information or autonomic nervous system information. Objective information includes, for example, an objective sleep evaluation. The improvement information generation unit 46 obtains the subjective sleep evaluation included in the subjective information. Based on the subjective and objective sleep evaluations, the improvement information generation unit 46 generates feedback information as improvement information. The feedback information includes, for example, information indicating the difference between the subjective and objective sleep evaluations.

[0117] For example, the life-improving application 40 displays the feedback information generated by the improvement information generating unit 46 on the information terminal 101 . Figure 6 This figure shows an example of an output screen 85 of feedback information displayed on information terminal 101. The life-improvement application 40 displays feedback information on information terminal 101 as output screen 85. Output screen 85 is, for example, a screen for providing feedback information to the user. Output screen 85 includes a subjective information display section 86 that displays a subjective sleep evaluation, an objective information display section 87 that displays an objective sleep evaluation, and a feedback display section 88 that displays feedback information.

[0118] The subjective information display unit 86 displays the subjective information. For example, the subjective information display unit 86 displays the subjective information input by the user to the sleep evaluation input unit 81 (see Figure 2) subjective sleep evaluation. The objective information display unit 87 displays objective information. For example, the objective information display unit 87 displays the user's objective sleep evaluation obtained based on the sleep state information obtained by the sleep state acquisition unit 41 and the autonomic nerve information obtained by the autonomic nerve acquisition unit 42. The objective information display unit 87 displays the objective sleep evaluation as a score with a maximum score of 100. The feedback display unit 88 displays information indicating the difference between the subjective sleep evaluation and the objective sleep evaluation, for example.

[0119] The life-improving application 40 implements total feedback. This total feedback includes feedback used to improve the accuracy of device 104 control. Total feedback is implemented to improve the accuracy of generated prediction information and improvement information. For example, if the subjective sleep evaluation exceeds the objective sleep evaluation by a predetermined value or more, the device control unit 44 may prioritize subjective control of the device 104 over objective control of the device 104. In this case, the device 104 can be controlled according to the user's subjective judgment.

[0120] Communication between the sensor unit 11 and the life-improving application 40, communication between the life-improving application 40 and the life-improving server 102, communication between the life-improving server 102 and the information terminal 101, communication between the life-improving server 102 and the device server 105, communication between the device control unit 44 and the device server 105, and communication between the device server 105 and the device 104 can be achieved, for example, via a wireless communication interface such as a wireless LAN (Local Area Network) or Bluetooth (registered trademark). Alternatively, these communications can be achieved via wired communication.

[0121] An example of the operation of the life-improving system 1 will be described. Figure 7 This is a flowchart illustrating an example of the operation of the life-improving system 1. Before operating the life-improving system 1, the sensor sheet 12 is first attached to the mattress 10a, and the seat cushion sensor 13 is attached to the seat cushion 10b. Next, the user's body rests on the mattress 10a or seat cushion 10b. For example, when sleeping, the user's body rests on the mattress 10a, contacting the surface layer 31 of the cover 3. For example, during the day, the user's body rests on the seat portion 15 of the seat cushion 10b.

[0122] The sensor unit 11 obtains breathing information, body movement information, and heartbeat information based on the user's body movement associated with breathing, body movement associated with heartbeat, and body movement not associated with breathing and heartbeat (step S1). When the user's vital sign data is obtained through the sensor sheet 12, in step S1, the sensor sheet 12 detects the user's body movement associated with breathing, body movement associated with heartbeat, and body movement not associated with breathing and heartbeat. The sensor sheet 12 outputs a signal indicating body movement associated with breathing, a signal indicating body movement associated with heartbeat, and a signal indicating body movement not associated with breathing and heartbeat to the outside of the sensor sheet 12. When the user's vital sign data is obtained through the seat cushion sensor 13, in step S1, the seat cushion sensor 13 detects the user's body movement associated with heartbeat. The seat cushion sensor 13 outputs a signal indicating body movement associated with heartbeat to the outside of the seat cushion sensor 13. In this manner, the sensor unit 11 outputs a signal indicating body movement associated with breathing, a signal indicating body movement associated with heartbeat, and a signal indicating body movement not associated with breathing and heartbeat to the outside of the sensor unit 11 .

[0123] The sleep state acquisition unit 41 acquires sleep state information based on, for example, the signal output from the sensor unit 11. The sleep state acquisition unit 41 acquires the user's sleep state information based on at least one of the respiratory information, body movement information, and heart rate information acquired by the sensor unit 11 (step S2). In step S2, the sleep state acquisition unit 41 acquires the user's bedtime, waking time, sleep stage ratio, sleep onset latency, sleep efficiency, number of awakenings, and duration of awakenings based on, for example, the respiratory information, body movement information, and heart rate information.

[0124] The autonomic nerve acquisition unit 42 acquires autonomic nerve information based on, for example, the heartbeat information acquired by the sensor unit 11 (step S3). In step S3, for example, the autonomic nerve acquisition unit 42 acquires the user's heartbeat fluctuations by analyzing the heartbeat information acquired by the sensor unit 11. In step S3, the autonomic nerve acquisition unit 42 acquires autonomic nerve information based on the user's heartbeat fluctuations. The autonomic nerve information includes, for example, information indicating the frequency of the R wave of the heartbeat. In step S3, the autonomic nerve acquisition unit 42 acquires the user's psychological state based on the autonomic nerve information.

[0125] For example, the device control unit 44 controls the operation of the device 104 based on at least one of the past sleep information and the autonomic nervous system information (step S4). In step S4, for example, the device control unit 44 controls the operation of the coffee machine. For example, the device control unit 44 can control the operation of the coffee machine based on the past sleep information and the user's mental state to adjust the strength of the coffee to be consumed by the user upon waking.

[0126] The prediction information generation unit 45 generates prediction information based on at least one of the past sleep information pre-stored in the life improvement server 102 and the autonomic nerve information obtained by the autonomic nerve acquisition unit 42 (step S5). In step S5, the prediction information generation unit 45 generates at least one of mental information, physical condition information, and brain information as prediction information based on the past sleep information and the autonomic nerve information. The prediction information generation unit 45 generates skin information as physical condition information. The prediction information generation unit 45 generates information indicating that the user's mood is predicted to be low as prediction information. The prediction information generation unit 45 generates information indicating whether the user's physical condition is good while awake as prediction information. The prediction information generation unit 45 generates information indicating that the user's thinking ability and concentration are predicted to be high as prediction information.

[0127] Next, the improvement information generation unit 46 generates improvement information based on the prediction information generated by the prediction information generation unit 45 (step S6). For example, the improvement information generation unit 46 generates information indicating the type of clothing recommended to the user as improvement information. For example, the improvement information generation unit 46 generates information indicating the types of soap, cosmetics, and food as improvement information. For example, the improvement information generation unit 46 generates information indicating the recommended action as improvement information.

[0128] In step S6, the improvement information generating unit 46 generates improvement information based on the predicted information and the subjective information. For example, the improvement information generating unit 46 obtains an objective sleep evaluation included in objective information obtained from the sleep state information and autonomic nerve information. For example, the improvement information generating unit 46 obtains a subjective sleep evaluation included in subjective information input by the user. For example, the improvement information generating unit 46 generates feedback information based on the subjective and objective sleep evaluations. For example, the improvement information generating unit 46 generates information indicating the difference between the subjective and objective sleep evaluations.

[0129] The life-improving application 40 displays the prediction information generated by the prediction information generating unit 45 and the improvement information generated by the improvement information generating unit 46. The life-improving application 40 displays the prediction information and the improvement information as an output screen 82 (see Figure 5 ) is displayed on the information terminal 101. Next, the life-improving application 40 displays the feedback information generated by the improvement information generating unit 46. The life-improving application 40 displays the feedback information as an output screen 85 (see Figure 6 ) is displayed on the information terminal 101.

[0130] Next, the life-improving application 40 implements overall feedback (step S7). In step S7, for example, if the subjective sleep evaluation exceeds the objective sleep evaluation by a predetermined value or more, the device control unit 44 of the life-improving application 40 prioritizes subjective control of the device 104 over objective control of the device 104.

[0131] Reference Figure 8 An example of the arrhythmia detection step of the arrhythmia detection unit 47 will be described. The arrhythmia detection step is performed, for example, before the generation of the prediction information (step S5) described above. However, the timing of performing the arrhythmia detection step is not particularly limited.

[0132] The arrhythmia detection unit 47 detects the presence or absence of arrhythmia based on the heartbeat information obtained by the sensor unit 11. The arrhythmia detection unit 47 detects the presence or absence of extrasystoles based on the heartbeat information (step S11). When the arrhythmia detection unit 47 detects the presence of extrasystoles, for example, it outputs coping plan 1 (step S12). Coping plan 1 is a suggestion to urge improvement of lifestyle habits such as getting enough sleep or reducing alcohol intake. In the case where the arrhythmia detection unit 47 detects extrasystoles multiple times (for example, when more than 10 extrasystoles are detected in 100 pulses), coping plan 1 may also be a suggestion to urge a visit to the cardiovascular department. Coping plan 1 output by the arrhythmia detection unit 47 is included in the improvement information by the improvement information generation unit 46, for example, and is displayed as improvement information on the information terminal 101 (refer to Figure 5 ). Then, end the series of steps.

[0133] When no extrasystoles are detected ("No" in step S11), the arrhythmia detection unit 47 determines whether the heart rate is less than X1 (X1 is a positive real number) (step S13). As an example, the value of X1 is 50 (BMP). When the arrhythmia detection unit 47 determines that the heart rate is less than X1, it determines that there is a slow arrhythmia. At this time, the arrhythmia detection unit 47 outputs the response plan 2 (step S14). Response plan 2 is, for example, a suggestion to avoid dangerous operations and driving due to the possibility of dizziness or coma. Response plan 2 can also be a suggestion to urge a visit to the cardiovascular department. Response plan 2 output by the arrhythmia detection unit 47 is included in the improvement information by the improvement information generation unit 46, for example, and is displayed as improvement information on the information terminal 101. Then, a series of steps are completed.

[0134] When the arrhythmia detection unit 47 determines that the heart rate is not less than X1 ("No" in step S13), it determines whether the heart rate is greater than X2 (X2 is a positive real number) which is greater than X1 (step S15). As an example, the value of X2 is 100 (BMP). When the arrhythmia detection unit 47 determines that the heart rate is greater than X2, it determines that there is a cardiac tachyarrhythmia. At this time, the arrhythmia detection unit 47 outputs the response plan 3 (step S16). The response plan 3 is, for example, a suggestion that it is best to adopt a relaxation method such as breathing or meditation. When the arrhythmia detection unit 47 determines that the user's heart rate is greater than X2 when at rest, the response plan 3 may also be a suggestion to urge the user to visit the cardiovascular department. The response plan 3 output by the arrhythmia detection unit 47 is included in the improvement information by the improvement information generation unit 46, for example, and is displayed as improvement information on the information terminal 101. Then, a series of steps are completed.

[0135] If the arrhythmia detection unit 47 determines that the heart rate is not greater than X2 ("No" in step S5), it determines that the heart rate is normal and there is no arrhythmia. The arrhythmia detection unit 47 outputs information indicating that the heart rate is normal and there is no arrhythmia (step S17). For example, the improvement information generation unit 46 includes the information indicating that the heart rate is normal and there is no arrhythmia in the improvement information, and the improvement information is displayed on the information terminal 101. Then, a series of steps are completed.

[0136] An example of the steps of the operation of the life improvement system 1 has been described above. However, the content and order of the steps of the operation of the life improvement system 1 are not limited to the above-mentioned examples, but can be changed appropriately. The steps of the arrhythmia detection unit 47 detecting arrhythmias are not limited to the above-mentioned examples. For example, the arrhythmia detection unit 47 can also determine the heart rate and determine the respiratory rate. Respiratory sinus arrhythmia among arrhythmias has a rule that the pulse becomes faster during inspiration (inhalation) and the pulse becomes slower during exhalation (exhalation). For example, the arrhythmia detection unit 47 can determine that there is a danger when the rule is not met. For example, in the case of apnea during sleep, the heart rate becomes bradycardia during the respiratory arrest process and becomes tachycardia when breathing resumes. The arrhythmia detection unit 47 can also detect the above-mentioned abnormalities while determining the heart rate and the respiratory rate.

[0137] The effects of the life improvement system 1 are described. The life improvement system 1 generates prediction information for the user based on at least one of past sleep information and autonomic nervous system information. For example, the life improvement system 1 can provide the user with information indicating the user's physical and mental state as prediction information. This life improvement system 1 generates improvement information based on the prediction information. For example, when the life improvement system 1 predicts that the user's physical and mental state has a tendency to be unfavorable, it can provide the user with information indicating a recommendation not to make a heavy decision as improvement information. The life improvement system 1 not only controls the device 104 during the user's sleep, but can also predict the user's state of wakefulness based on the user's sleep, and can provide information for improving the user's life based on the sleep state.

[0138] This life-improving system 1 can generate prediction information and improvement information based on the user's past sleep state. In addition to the user's current sleep state, past sleep states can also be considered to generate prediction information indicating the user's predicted state while awake, as well as improvement information for improving life. Compared to generating prediction information and improvement information based solely on the user's sleep state from bedtime to waking up, prediction information and improvement information can be generated based on longer-term records. As a result, more accurate prediction information and improvement information can be generated.

[0139] As previously mentioned, the sensor unit 11 may also include a seat cushion sensor 13 attached to the seat cushion 10b on which the user sits. In this case, for example, the user's vital sign data can be continuously acquired not only during sleep but also during the day. Since prediction information and improvement information can be generated based on the user's vital sign data continuously measured during the day, prediction information and improvement information can be more accurately generated by utilizing the user's state both while asleep and while awake.

[0140] The prediction information may also include mental information (information indicating the user's mental state), physical information (information indicating the user's physical condition), and mental information (information indicating the user's mental state). In this case, the mental, physical, and mental states of a user who is awake can be predicted. The physical information may also include skin information indicating the condition of the user's skin. In this case, information indicating the condition of the user's skin can be provided as the prediction information.

[0141] The improvement information generating unit 46 may generate improvement information based on subjective information and prediction information, which are information indicating the user's subjective evaluation. This allows the improvement information to be generated taking the user's subjective evaluation into consideration, thereby enabling more accurate generation of the improvement information.

[0142] The improvement information may also include information indicating the types of clothing, food, and cosmetics recommended to the user. In this case, information indicating the types of clothing, food, and cosmetics recommended to the user can be provided as the improvement information.

[0143] The device 104 may also include a pillow for the user to sleep on, and the device control unit 44 may also control the angle of the pillow's support surface relative to the horizontal plane. In this case, since the angle of the pillow's support surface can be adjusted while the user is sleeping, the user's sleeping condition can be further improved.

[0144] The life improvement system 1 includes: a sensor unit 11, which obtains information indicating the user's heartbeat, namely, heartbeat information; an autonomic nerve acquisition unit 42, which obtains information indicating the state of the user's autonomic nerves, namely, autonomic nerve information, based on the heartbeat information; a prediction information generation unit 45, which generates information indicating the predicted state of the user while awake, namely, prediction information, based on the autonomic nerve information; and an improvement information generation unit 46, which generates information for improving the user's life, namely, improvement information, based on the prediction information.

[0145] As described above, the life-improving system 1 generates prediction information of the user based on autonomic nerve information and generates improvement information based on the prediction information. Therefore, it is possible to predict the user's state of wakefulness and provide information for improving the user's life.

[0146] The life-improving system 1 may also include an arrhythmia detection unit 47 that detects whether the user has arrhythmia based on the heartbeat information obtained by the sensor unit 11. In this case, by detecting the presence of arrhythmia based on the heartbeat information obtained by the sensor unit 11, information on the presence of arrhythmia can be obtained while the user is asleep or awake. This allows the user to understand whether they have arrhythmia.

[0147] While the examples of the life-improving system of the present disclosure have been described above, the present disclosure is not limited to the above examples, and various modifications are possible without departing from the scope of the gist of the claims.

[0148] As mentioned above, the sensor unit 11 can also obtain information indicating the user's body temperature. As an example, the life improvement system can also calculate the body temperature by correcting the temperature measured by the sensor unit 11 with a predetermined coefficient (or formula). The life improvement system can also monitor the changes in the user's body temperature obtained by the sensor unit 11. The life improvement system can also display the changes in the user's body temperature obtained by the sensor unit 11 on the information terminal 101. For example, it can also be that the aforementioned arrhythmia detection unit 47 detects atrial fibrillation, and the sensor unit 11 continuously measures the user's body temperature during sleep. In this case, when the user is a female, for example, certain hints corresponding to female-specific body changes can be given (such as menstruation (ovulation) or signs of pregnancy. The user can grasp the body temperature that is prone to pregnancy).

[0149] When women are trying to conceive, they sometimes measure their basal body temperature to predict ovulation. In such cases, the lifestyle improvement system can detect changes in body temperature based on the measurement results of the sensor unit 11. Furthermore, the lifestyle improvement system can also detect changes in body temperature due to infection using the sensor unit 11. In this case, the user can gain insight into their own physical concerns. Regardless of whether the user is female or male, the above-mentioned effects can be achieved in all situations.

[0150] The life improvement system can also calculate immunity in a numerical form based on body temperature. It is generally known that when body temperature drops, immunity decreases. Therefore, by having the life improvement system calculate immunity based on body temperature, users can understand their own immunity and their own health status. If the basal body temperature rises, blood circulation becomes good, shoulder stiffness is improved, basal metabolism increases, and the body becomes easy to lose weight. Moreover, if the basal body temperature rises, edema is eliminated, and dysmenorrhea and irregular menstruation will be improved. Therefore, by having the life improvement system calculate basal body temperature based on the measurement results of the sensor unit 11, users can understand their own blood circulation, shoulder stiffness, basal metabolism, whether they have a physique that is easy to lose weight, edema, dysmenorrhea and irregular menstruation.

[0151] The sensor unit 11 may also include a blood glucose sensor for acquiring information indicating the user's blood glucose level, i.e., blood glucose information. For example, the blood glucose sensor may be mounted on the armrest of a bed on which the user sleeps, provided with the mattress 10a. In this case, the prediction information generation unit 45 may generate information indicating the likelihood of a hangover as the physical condition information based on at least one of the blood glucose information, blood pressure information, and heart rate information acquired by the sensor unit 11, and the number of awakenings acquired by the sleep state acquisition unit 41.

[0152] For example, the prediction information generating unit 45 may determine whether the user's blood sugar level is above a predetermined value based on information indicating the blood sugar level. For example, the prediction information generating unit 45 may determine whether the user's blood pressure is above a predetermined value based on information indicating the blood pressure. For example, the prediction information generating unit 45 may determine whether the user's heart rate is above a predetermined value based on heartbeat information. For example, the prediction information generating unit 45 may determine whether the number of awakenings during the meal is above a predetermined value.

[0153] For example, the prediction information generating unit 45 may generate information indicating a high probability of a hangover as prediction information if it determines that the user's blood sugar level is above a predetermined value. For example, the prediction information generating unit 45 may also perform the same processing as described above if it determines that the user's blood pressure is above a predetermined value, or if it determines that the user's heart rate is above a predetermined value. For example, the prediction information generating unit 45 may also perform the same processing as described above if it determines that the number of mid-night awakenings is above a predetermined value.

[0154] While the preceding description illustrates an example in which the life-improving system 1 provides improvement information to the user, the life-improving system 1 can also provide improvement information to people other than the user. "People other than the user" can be, for example, the user's family members. In this case, if the prediction information generation unit 45 generates information indicating a predicted poor physical condition for the user as prediction information, the life-improving application 40 can display the prediction information on an information terminal owned by the user's family members. In this case, since the user's prediction information can be provided to the user's family members, the user's prediction information can be shared with the user's family members. For example, if the user is an elderly person living alone, the user's family members can detect any abnormal changes in the user.

[0155] The "person other than the user" may be, for example, a physician stationed at the company where the user works. In this case, the prediction information generating unit 45 may determine whether the user is predicted to develop a disease based on past sleep information and autonomic nervous system information. If the prediction information generating unit 45 determines that the user is predicted to develop a disease, it may provide the physician with information indicating the predicted disease as prediction information.

[0156] For example, a "person other than the user" may be a real estate company managing the item or an insurance company handling insurance. In this case, if the user is not predicted to develop a disease, the prediction information generating unit 45 may provide the real estate company or insurance company with information indicating that no disease is predicted as prediction information. Providing this prediction information to the real estate company allows for a more reliable determination of whether the item can be rented to the user. Providing this prediction information to the insurance company allows for a more reliable determination of whether an insurance contract can be concluded with the user.

[0157] For example, a "person other than the user" may be a staff member in the human resources department of the company where the user works. In this case, the prediction information generation unit 45 may determine the good or bad physical and mental state of the user (each employee of the company) based on past sleep information and autonomic nervous system information. For example, if the prediction information generation unit 45 determines that each employee's physical and mental state is tending to deteriorate, it may generate information indicating that each employee's physical and mental state is tending to deteriorate as prediction information. In this case, the improvement information generation unit 46 may generate information indicating a recommendation to reduce overtime work as improvement information.

[0158] In the above description, air conditioners, lighting fixtures, pillows, heated mattresses, coffee machines, and cars are cited as examples of device 104. However, device 104 may also be, for example, an aromatherapy diffuser or music player that emits fragrance into the user's space. Thus, the type of device 104 is not particularly limited.

[0159] Prediction information and improvement information are not limited to the above description. For example, if the prediction information generation unit 45 determines that the user's thinking ability is not above a specified value, it can generate information indicating that the user is not suitable for engaging in risky activities (such as investment) as prediction information. For example, the prediction information generation unit 45 can also perform the same processing as described above when the autonomic nerve acquisition unit 42 classifies the user's psychological state as a stress state or a depression-prone state. For example, the improvement information generation unit 46 can also generate information indicating a recommendation not to engage in risky activities as improvement information.

[0160] For example, if the user's thinking ability and concentration are determined to be above a predetermined value, the prediction information generating unit 45 may generate information indicating that the user is predicted to be suitable for learning. For example, the improvement information generating unit 46 may generate information indicating that learning is recommended.

[0161] For example, if the autonomic nerve acquisition unit 42 classifies the user's mental state as a stress state, the prediction information generation unit 45 may generate information indicating a tendency to experience stress as prediction information. In this case, the improvement information generation unit 46 may generate information indicating a recommendation for meditation as improvement information.

[0162] In the case where the prediction information generation unit 45 generates information indicating that the user's mood is predicted to be low as prediction information, the improvement information generation unit 46 may also generate, for example, information indicating content that improves low mood (such as movies, music, games, or books, etc.) and at least any one of travel-related information (such as travel destinations, accommodations, and tourist attractions, etc.) as improvement information.

[0163] The life-improvement system 1 can also be used in at least one of a financial institution, a medical institution, a store selling automobiles, home appliances, beauty products, clothing, or food, an e-commerce company, or an educational institution. The life-improvement system 1 can also be used to provide products and services tailored to each user based on at least one of their past sleep information and autonomic nervous system information.

[0164] Description of Reference Numerals

[0165] 1: Life Improvement System

[0166] 2. 14: Core material

[0167] 3: Kit

[0168] 10a: Mattress

[0169] 10b: Cushion

[0170] 11: Sensor unit

[0171] 12: Sensor sheet

[0172] 13: Seat cushion sensor

[0173] 13a: Seat sensor

[0174] 13b: Sacral support sensor

[0175] 13c: Thigh support sensor

[0176] 15: Seating

[0177] 15a: Buttocks support

[0178] 15b: Thigh support

[0179] 16: Lumbar support

[0180] 16a: General

[0181] 16b: Sacral support

[0182] 21: Upper surface

[0183] 22: Lower surface

[0184] 23: Side

[0185] 31: Surface

[0186] 32: Back layer

[0187] 33: Opening and closing parts

[0188] 34: Slider

[0189] 35: Opening and closing part

[0190] 40: Life-Improving Apps

[0191] 41: Sleep state acquisition unit

[0192] 42: Autonomic Nerve Acquisition Department

[0193] 43: Storage

[0194] 44: Equipment Control Department

[0195] 45: Forecast Information Generation Department

[0196] 46: Improvement of information generation department

[0197] 47: Arrhythmia Detection Department

[0198] 80: Input screen

[0199] 81: Sleep evaluation input unit

[0200] 82, 85: Output screen

[0201] 83: Forecast Information Display Department

[0202] 84: Improve information display department

[0203] 86: Subjective information display unit

[0204] 87: Objective information display unit

[0205] 88: Feedback display unit

[0206] 101: Information Terminal

[0207] 102: Life Improvement Server

[0208] 103: Website

[0209] 104: Equipment

[0210] 105: Device Server

[0211] A1: First direction

[0212] A2: Second direction

[0213] A3: Third direction

[0214] D1: Long side direction

[0215] D2: Short side direction

[0216] D3: thickness direction

Claims

1. A life improvement system for improving the life of a user, characterized in that: have: a sensor unit configured to acquire at least one of respiratory information representing the user's respiration, body motion information representing the user's body motion, and heartbeat information representing the user's heartbeat; a sleep state acquisition unit for acquiring sleep state information indicating the sleep state of the user based on at least one of the respiratory information, the body movement information, and the heartbeat information; an autonomic nerve acquisition unit for acquiring autonomic nerve information, which is information indicating a state of the user's autonomic nerves, based on the heartbeat information; a device control unit configured to control the operation of devices constituting an environment surrounding the user based on at least one of the past sleep state information of the user stored in advance, i.e., past sleep information and the autonomic nerve information; a prediction information generating unit that generates prediction information representing a predicted state of the user while awake based on at least one of the past sleep information and the autonomic nerve information; and An improvement information generating unit generates improvement information, which is information for improving the user's life, based on the prediction information.

2. The life improvement system according to claim 1, characterized in that: The sensor unit includes a seat cushion sensor attached to a seat cushion on which the user sits.

3. The life improvement system according to claim 1 or 2, characterized in that: The prediction information includes mental information representing the user's mental state, physical condition information representing the user's physical condition, and brain information representing the user's mental state.

4. The life improvement system according to claim 3, characterized in that: The physical condition information includes skin information indicating the condition of the user's skin.

5. The life improvement system according to claim 1 or 2, characterized in that: The improvement information generating unit generates the improvement information based on subjective information, which is information indicating the user's subjective evaluation.

6. The life improvement system according to claim 1 or 2, characterized in that: The improvement information includes information indicating the type of clothing recommended to the user.

7. The life improvement system according to claim 1 or 2, characterized in that: The improvement information includes information indicating the type of food recommended to the user.

8. The life improvement system according to claim 1 or 2, characterized in that: The improvement information includes information indicating the type of cosmetic recommended to the user.

9. The life improvement system according to claim 1 or 2, characterized in that: The device comprises a pillow used by the user to sleep, The device control unit controls an angle of a support surface of the pillow supporting the user's head relative to a horizontal plane.

10. The life improvement system according to claim 1 or 2, characterized in that: The life-improving system includes an arrhythmia detecting unit configured to detect whether the user has arrhythmia based on the heartbeat information acquired by the sensor unit.

11. A life improvement system for improving the life of a user, characterized in that: have: a sensor unit for acquiring heartbeat information representing a user's heartbeat; an autonomic nerve acquisition unit for acquiring autonomic nerve information, which is information indicating a state of the user's autonomic nerves, based on the heartbeat information; a prediction information generating unit configured to generate prediction information indicating a predicted state of the user while awake based on the autonomic nerve information; and An improvement information generating unit generates improvement information, which is information for improving the user's life, based on the prediction information.

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