System and method for providing health promotion program

Abstract

In order to effectively use biological data acquired in daily life of a user for maintenance and promotion of health of the user, the present invention provides a system for providing a health promotion program for a user, characterized by comprising: a first sensor which is provided in a first facility and continuously collects biological data of the user; a second sensor which is provided in a second facility and which continuously collects biological data of the same type as the first sensor from the user; an analysis device configured to perform analysis including comparison of the biological data collected by the first and second sensors, and determine a health state of the user; and a program generation device configured to generate a health promotion program corresponding to the user on the basis of the determination result of the health state.

Description

Technical Field

[0001] The present invention relates to a system and method for providing a health promotion program corresponding to the health status of users including residents of a residence. Background Art

[0002] In recent years, smart houses have attracted much attention. A smart house generally refers to a house that uses information technology (IT) to control lighting, cooking, cooling and heating equipment and other electrical or gas-using devices in the home, thereby optimally controlling energy consumption.

[0003] For example, Patent Document 1 (Japanese Patent Publication No. 2013-15271) discloses an indoor environment control system, which includes: an environment information detection unit, an indoor person information detection unit, a control unit, and an operation unit in order to control the indoor environment according to the comfort of each indoor person with a simple system without increasing the time and energy costs. In the indoor environment control system, the storage mechanism of the control unit is provided with a database that records the relationship between the indoor person information and the comfort of the indoor person in advance. The operation mechanism of the control unit generates an adjustment signal for performing fluctuation control on the operation unit using the indoor person information as a fluctuation index in a manner that optimizes the comfort of the indoor person in the database based on the indoor person information detected by the indoor person information detection unit.

[0004] In addition, Patent Document 2 (Japanese Patent Gazette No. 6539799) discloses a safety confirmation system for accurately determining abnormalities of residents and responding more safely, more reliably and quickly when abnormalities occur. The safety confirmation system comprises: a first sensor, which is installed in the residence and detects at least the heart rate and breathing rate of the resident in a non-contact manner; an abnormality determination unit, which detects significant differences in the heart rate and breathing rate from the usual; a communication unit, which communicates safety confirmation between the operator and the resident; an arrival information prompting unit, which prompts the operator that the rescue personnel have arrived at the residence due to the operator's dispatch request; and a remote unlocking unit, which urgently unlocks the lock of the residence according to the operator's instructions.

[0005] Prior art literature

[0006] Patent Literature

[0007] Patent Document 1: Japanese Patent Application Publication No. 2013-15271

[0008] Patent Document 2: Japanese Patent No. 6539799 Summary of the invention

[0009] Problems to be solved by the invention

[0010] The indoor environment control system of Patent Document 1 is limited to environment control. The safety confirmation system of Patent Document 2 is limited to safety confirmation. These technologies are just limited use of the collected biological data. Moreover, these technologies use wearable sensors to obtain biological data, and wearing and removing wearable sensors takes time and some people feel that the operation is complicated. Therefore, the convenience of the above technologies is problematic.

[0011] Therefore, an object of the present invention is to provide a system and method capable of effectively utilizing biological data obtained in the daily lives of users including residents for maintaining and promoting the health of the users.

[0012] Technical solutions to solve problems

[0013] In order to solve the above-mentioned problems, one embodiment of the present invention provides a system.

[0014] A system for providing a health promotion program for a user, characterized by comprising:

[0015] A first sensor, which is disposed in a first facility and continuously collects biological data of the user;

[0016] a second sensor disposed in a second facility and continuously collecting the same type of biological data from the user as the first sensor;

[0017] an analysis device configured to perform analysis including comparison of the biological data collected by the first and second sensors and determine the health status of the user;

[0018] A program generating device is configured to generate a health promoting program suitable for the user based on the determination result of the health status.

[0019] Here, the biological data includes not only the biological data but also the dynamic data. In addition, the health promotion program includes various programs for maintaining and promoting the physical and mental health of the user and various health information in addition to the exercise program.

[0020] In the system of the present invention, preferably, the biological data is at least one of data representing facial expression, heart rate, oxygen saturation, exhaled carbon dioxide, body surface temperature, core body temperature, skin protein analysis, body composition, autonomic nerves, HbA1c, body water content, foot pressure distribution, walking posture, walking speed, changes in joint range of motion, center of gravity changes, activity level, myoelectricity, electrocardiogram, brain waves, standing and sitting posture, body temperature, blood pressure, blood flow, heart rate, breathing, sweating, eyeballs, sleep time, amount and time of excretion, blood components, urine components, saliva components, images inside the oral cavity, and feces components.

[0021] In addition, in the system of the present invention, it is preferred that

[0022] The analysis device performs the following steps:

[0023] Using biological data of a person including at least one of data representing facial expression, heart rate, oxygen saturation, exhaled carbon dioxide, body surface temperature, core body temperature, skin protein analysis, body composition, autonomic nerves, HbA1c, body water content, foot pressure distribution, walking posture, walking speed, changes in joint range of motion, changes in center of gravity, activity, myoelectricity, electrocardiogram, brain waves, standing and sitting posture, body temperature, blood pressure, blood flow, heart rate, breathing, sweating, eyeballs, sleep time, amount and time of excretion, blood components, urine components, saliva components, images in the oral cavity, and feces components as teaching data, and the health status of the person including the energy consumption and exercise effect of the person, and generating, through machine learning: a prediction model whose input is the biological data of the person and whose output is the health status of the person; and

[0024] The prediction model is used to output the health status of the user based on the collected biological data.

[0025] In addition, in the system of the present invention, it is preferred that

[0026] The program generation unit performs the following steps:

[0027] Extracting the user's biological characteristics by comparing the collected biological data with a predetermined evaluation index;

[0028] Using the evaluation values ​​representing the effects of the predetermined evaluation index and the health promotion program as teaching data, and generating, by machine learning, an evaluation model whose input is the biological data and whose output is the evaluation of the health promotion program; and

[0029] Using the evaluation model, a health promotion program suggested to the user is output together with the user's biometric characteristics based on the collected biometric data.

[0030] Another aspect of the present invention provides a method, characterized in that it is a method for providing a health promotion program for a user, and causes a computer having a processor and a memory to execute the following steps:

[0031] continuously collecting biological data of the user at a first sensor disposed in a first facility;

[0032] At a second sensor installed in a second facility, continuously collecting the same type of biological data from the user as that of the first sensor;

[0033] Performing analysis including comparison of the biological data collected by the first and second sensors to determine the health status of the user;

[0034] Based on the determination result of the health status, a health promotion program corresponding to the user is generated.

[0035] Effects of the Invention

[0036] According to the present invention, biological data acquired in the daily life of the user can be effectively used to maintain and promote the health of the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 is a schematic diagram showing an overall image of an exemplary embodiment of the present invention.

[0038] Figure 2 is a block diagram showing the overall structure of a system 1 for providing a health promotion program.

[0039] Figure 3 is a flow chart representing the processing steps for providing a health promotion program.

[0040] Description of Reference Numerals

[0041] 1 Health Promotion Program Delivery System

[0042] 10 Sensors

[0043] 20 Analysis device

[0044] 30 Program generation device

[0045] 40 Output device

[0046] 50 Storage device

[0047] H User DETAILED DESCRIPTION

[0048] Hereinafter, representative embodiments of the system and method of the present invention will be described in detail with reference to the accompanying drawings. However, the present invention is not limited to these drawings. In addition, the accompanying drawings are used to conceptually illustrate the present invention, and therefore, in order to facilitate understanding, the dimensions, proportions, or quantities are sometimes exaggerated or simplified as needed.

[0049] 1. Overall Image of the Embodiment

[0050] Reference Figure 1 , an overall image of the system surrounding the present embodiment is described.

[0051] The facilities in this embodiment (the present invention) are concepts that include all facilities (also referred to as facilities, institutions, sites, places, or activity bases, etc.) that can utilize the system of the present invention. As an example of a facility, there can be cited residences, workplaces, educational facilities such as schools, medical facilities such as hospitals and physical examination centers, sanatoriums, nursing facilities, childcare facilities, facilities for the elderly, sports facilities, entertainment facilities, clubs, and accommodation facilities, but are not limited to these. The biometric data of users who spend their daily lives in these facilities is sensed by sensors arranged in various places of these facilities. For example, for users engaged in transportation services, the workplace may also include mobile objects such as vehicles, ships, and aircraft.

[0052] Here, biometric data refers to the entirety of data that can be obtained from the user's body. Biometric data includes not only dynamic data such as walking posture, walking speed, changes in the range of joint motion, changes in the center of gravity, and activity, but also time series data such as electromyography, electrocardiography, and brain waves, standing and sitting postures, body temperature, blood pressure and blood flow, heart rate, breathing, sweating, eyeballs, sleep time, amount and time of excretion, blood components, urine components such as blood sugar levels, saliva components, images of the oral cavity (tongue, pharynx, etc.), and static data of fecal components. In addition, a residence refers to a building where the person lives in daily life, including not only single-family houses and apartment-style houses, but also so-called nursing homes.

[0053] Furthermore, the health status of the user is determined by computer analysis of the obtained biometric data. For example, by comparing the same biometric data, i.e., first and second biometric data, sensed in different facilities, i.e., first and second facilities, the health status of the user in different environments can be accurately evaluated.

[0054] To give a specific example, if the measured values ​​of the user's blood pressure, heart rate, respiratory rate, and perspiration at the workplace are greater than the corresponding values ​​at home by a set value or more, it can be evaluated that the user is in an overly stressed state at the workplace.

[0055] Alternatively, if the measured values ​​of the user's blood pressure, heart rate, respiratory rate, blood flow and sweat at a sports facility are greater than the corresponding values ​​at home by a preset allowable range, it can be evaluated that the user is performing moderate exercise.

[0056] Alternatively, when the measured or estimated values ​​of the user's moving distance, moving speed, and metabolism at the workplace are smaller than the corresponding values ​​at home by a set value or more, it can be evaluated that the user is in a state of lack of exercise at the workplace.

[0057] Alternatively, when the measured values ​​of the user's blood pressure, heart rate, and respiratory rate in an accommodation facility or an entertainment facility are smaller than the corresponding values ​​in the user's home by a set value or more, it can be evaluated that the user is in a moderately relaxed state in the accommodation facility or the entertainment facility.

[0058] Alternatively, when the measured values ​​of the user's electroencephalograms in an educational facility or a workplace are different from the corresponding values ​​in the user's home, it may be possible to evaluate that the user is in a state of lack of concentration.

[0059] Next, based on the determination result of the health status, a customized health promotion program is created for each user. Here, as the created health promotion program, in addition to the exercise program, various programs and various health information for maintaining and promoting the user's physical and mental health can be listed.

[0060] For example, for a user who is evaluated as being overly stressed at work, measures to relieve stress are suggested, such as improving work, taking a vacation, exercising moderately, getting enough sleep, and consulting a doctor. In this case, an exercise menu based on the user's health status can also be prompted.

[0061] Alternatively, for a user who is evaluated as being inactive at work, moderate exercise may be suggested.

[0062] The health promotion program is provided to the user, and the user implements the program.

[0063] Furthermore, by repeating the above-mentioned sensing, determination of health status, creation of a health promotion program, and implementation thereof by the user, the user's health function is promoted.

[0064] In addition, the collected biological data can also be collected in a data server, etc., and can be presented to medical personnel such as doctors with the approval of the user, and used by medical personnel. In addition, the generated health status determination results can also be presented to medical personnel with the approval of the user, and used by medical personnel.

[0065] Moreover, the collected biometric data and generated health status determination results can also be used in administration and communities, with the user's approval, to create a more comfortable and livable community, to manage the health of residents, and to enable residents to continue to live independently in their own homes in their later years.

[0066] The system 1 of this embodiment has: a functional unit that realizes: a sensing function for collecting biological data from users in a facility, an analysis and determination function for determining the health status of users by analyzing the collected biological data, and a program generation function for generating a health promotion program based on the determination result of the health status.

[0067] In order to realize this function, the system 1 includes: a sensor 10, an analysis device 20, a program generation device 30, an output device 40, and a storage device 50 (see Figure 2 ). These components are communicatively connected via a wired or wireless communication network. The sensor 10, the analysis device 20, the program generation device 30, the output device 40 and the storage device 50 may be separate bodies or may be integrally constructed. In addition, the storage device 50 may also be configured as a component of a data center (not shown), which not only stores the collected data but also stores the collected samples (for example, saliva or feces samples). The data center in this case is also referred to as a biobank.

[0068] These components are described in detail below.

[0069] 2. Sensors

[0070] The sensor 10 is a general term for various sensors installed in a facility 70 such as a residence, and continuously collects the biological data of the user H. The sensor 10 sends and stores the collected biological data together with the collection date to the storage device 50. The storage device 50 may be a data server, but is not limited thereto. In addition, the sensor 10 may also send and store the collected biological data to a storage device (not shown) in the facility 70.

[0071] Examples of the sensor 10 that can be used include, but are not limited to, infrared temperature cameras, hyperspectral imaging cameras, RFID sensors, pressure sensors, motion capture devices, temperature sensors, component analyzers, weight sensors, flow sensors, and position sensors (none of which are shown in the figure).

[0072] More specifically, the infrared temperature camera is set in the living room, study, bedroom and office of the facility 70, and can measure the expression, heart rate, oxygen saturation, carbon dioxide exhalation, body surface temperature and core body temperature of the user H. The hyperspectral imaging camera is set in the entrance hall and its vicinity, and in addition to the identity authentication function of the user H, it can also perform skin protein analysis, body composition (for example, the composition ratio of fat, bone, soft tissue outside fat, etc., weight, body fat, basal metabolism, visceral fat, muscle mass, bone mass) and autonomic nerve (for example, including the fatigue of the autonomic nerve, the balance of the sympathetic nerve and the parasympathetic nerve) of the user H. Alternatively, the hyperspectral imaging camera is set in the dining table, kitchen and its vicinity, and can measure glycated hemoglobin (HbA1c). The RFID sensor is set on the wall of the room, and can measure the water content in the body of the user H. The pressure sensor is set on the floor of the corridor and the room, and can measure the foot pressure distribution of the user H. The motion capture device is installed in, for example, an indoor corridor, and can measure the user H's walking posture, walking speed, changes in the range of joint motion, changes in the center of gravity, and the amount of activity.

[0073] The sensing of the biological data of the user H by the sensor 10 may be performed, for example, by continuous measurement.

[0074] The sensor 10 is preferably installed in a manner that is not immediately visible to the user H and is hidden from the human eye. This is to prevent the user H from becoming nervous due to noticing the presence of the sensor 10 and the sensed biological data from deviating from the daily value of the user H. In other words, this is to grasp the user H in a natural state in daily life.

[0075] A sensor for acquiring environmental data may be provided separately from the sensor 10. That is, a thermometer for measuring the room temperature, a hygrometer for measuring the humidity of the room, an illuminometer for measuring the brightness of the room, and a carbon dioxide meter for measuring the CO2 concentration of the room may be provided. The environmental data collected by these sensors are sent to and stored in the storage device 50. In addition, the sensor 10 may also include these sensing functions.

[0076] It is also possible to additionally utilize various sensors built into portable information terminals such as wearable devices and smartphones to obtain the user's biological data. Such biological data is useful as an aid in determining the user's health status. The sensor 10 may also include these sensing functions.

[0077] The collected biological data, environmental data and other data are sent to and stored in the storage device 50. The storage device 50 may also store the determination results of the health status described later and the generated health promotion program. The various data stored in the storage device 50 may also be used in the external computer 80 used by the doctor and medical institutions serving the user H with the permission of the user H. Through this medical collaboration, various health records required for the diagnosis and treatment of the user H can be shared among medical personnel in a timely manner. Of course, data collaboration can also be targeted at doctors, dentists, pharmacists or nutritionists, etc., and is not limited to medical-related.

[0078] 3.Analysis device

[0079] The analysis device 20 determines the health status of the user H by analyzing the biological data collected by the sensor 10 .

[0080] The analyzing device 20 can preferably utilize AI analysis to analyze data.

[0081] That is, the analysis device 20 uses the biological data of a person including at least one of data representing the person's facial expression, heart rate, oxygen saturation, carbon dioxide exhalation, body surface temperature, core body temperature, skin protein analysis, body composition, autonomic nerves, HbA1c, body water content, foot pressure distribution, walking posture, walking speed, change in joint range of motion, center of gravity change, activity, myoelectricity, electrocardiogram, brain wave, standing and sitting posture, body temperature, blood pressure, blood flow, heart rate, breathing, sweating, eyeballs, sleep time, amount and time of excretion, blood components, urine components, saliva components, oral images, and feces components, and the health status of the person including the energy consumption and exercise effect of the person as teaching data, and generates a prediction model with input of the biological data of the person and output of the health status of the person through machine learning. And, the analysis device 20 uses the generated prediction model to output the health status of the user based on the collected biological data.

[0082] For example, the analysis device 20 can create a teaching variable (teaching data) using at least one of biological data such as a person's facial expression, heart rate, oxygen saturation, carbon dioxide exhalation, body surface temperature, core body temperature, skin protein analysis, body composition, autonomic nerves, HbA1c, body water content, foot pressure distribution, walking posture, walking speed, joint range of motion change, center of gravity change, activity level, etc. as an existing indicator. That is, the analysis device 20 can implement machine learning using biological data of the same type as the data group collected by the sensor 10 as an explanatory variable and create an analysis program. Furthermore, the analysis device 20 can use basic information such as age, gender, height, and weight as parameters used, and perform algorithmic analysis on biological information such as facial expression, heart rate, oxygen saturation, carbon dioxide exhalation volume, body surface temperature, core body temperature, skin protein analysis, body composition, autonomic nerves, HbA1c, body water content, foot pressure distribution, joint angles during walking, and their changes over time, lower limb muscle strength, three-dimensional movement distance of the center of gravity or related observation points, walking posture, walking speed, activity level, and other motor function information.

[0083] The analysis device 20 applies the sensing data to the above-mentioned model to obtain an objective evaluation including health functions and motor functions as the health status of the user H. In the present embodiment, deep learning is cited as an example of machine learning that can be used, but the present invention is not limited thereto.

[0084] The analysis result 20 sends and stores the determination result of the health status of the user H to the storage device 50. Of course, the determination result can be effectively used among relevant personnel including medical personnel with the permission of the user H. In addition, by outputting the determination result of the health status of the user H to the output device 40 described later, the user H and his family can find the illness or physical discomfort of the user H in advance, and can also be used for the health management of the user H. That is, the determination result can be effectively used to support the user H and cooperate with relevant personnel.

[0085] 4. Program generation device

[0086] The program generating device 30 generates a health-promoting program customized for each user H based on the determination result of the health status acquired by the analyzing device 20 .

[0087] That is, the program generation device 30 extracts the user's biological characteristics by comparing the collected biological data with the specified evaluation index. Furthermore, the program generation device 30 uses the evaluation value representing the specified evaluation index and the effect of the health promotion program as teaching data, and generates an evaluation model through machine learning, which inputs the biological data and outputs the evaluation of the health promotion program. Furthermore, the program generation device 30 uses the evaluation model to output the health promotion program suggested to the user together with the user's biological characteristics based on the collected biological data.

[0088] Here, health promotion programs are roughly divided into programs related to health functions and programs related to sports functions.

[0089] For example, in relation to health functions, the program generation device 30 compares facial expressions, heart rate, oxygen saturation, carbon dioxide exhalation, body surface temperature, core body temperature, skin protein analysis, body composition, autonomic nerves, HbA1c, body water content, and foot pressure distribution with normal ranges for each individual and evaluation indicators such as epidemiological or medical guidelines, thereby clarifying the biological characteristics of the user H. In addition, the program generation device 30 can analyze the measured data, basic information such as age, gender, height, and weight, and the living environment data of the user H (for example, biological data collected by the sensor 10) through AI, and construct an algorithm related to the living habits of each individual, suggesting behavior modification and the subsequent effects.

[0090] In addition, in relation to motor function, the program generation device 30 compares the position and velocity of each joint, as well as the joint angle and angular velocity, to clarify the characteristics of the user H in terms of dynamic analysis. Furthermore, based on the measured data, the program generation device 30 can construct a motion measurement algorithm in addition to estimating the energy consumption or exercise effect during exercise, and can also suggest recommended exercises and the energy consumption or exercise effect during exercise.

[0091] Here, deep learning is cited as an example of usable AI analysis, but it is not limited to this.

[0092] The program generation device 30 sends and stores the generated health promotion program to the storage device 50. Of course, the program can be shared among medical personnel with the permission of the user H. In addition, by outputting the program to the output device 40, the user H and his family can clearly understand what should be done to maintain, restore and improve the health function and motor function of the user H, and can also be used for the health management of the user H.

[0093] In addition, the analysis device 20 and the program generation device 30 can be configured as one or more computers including a computing circuit such as a central processing unit (CPU) and a memory such as a random access memory (RAM) and a read-only memory (ROM). The functions of the above-mentioned analysis device 20 and program generation device 30 can be realized by reading the execution program stored in the ROM into the RAM and executing it by the CPU. The analysis device 20 and the program generation device 30 use the biological data collected continuously and uninterruptedly to determine the health status and generate a health promotion program regularly or at a timing (timing) required for each individual.

[0094] The output device 40 is a device for outputting the determination result of the health status and the health promotion program. The output device 40 includes a terminal of the user H (including a smartphone and a personal computer), a display, a printer, a projector, and a speaker.

[0095] For example, when the health status determination result indicates that the health status of the user H is abnormal, that is, out of the normal range (for example, when the data represented by the numerical value is above or below a predetermined threshold, or deviates from a predetermined range), the output device 40 may also output an alarm to the terminal of the user H and related persons. In addition, the output device 40 may also display other information related to life, such as energy, information related to residence, and regional information.

[0096] 5. Actions of the health promotion program delivery system

[0097] Reference Figure 3 , describing the processing steps used to provide health promotion programs by system 1.

[0098] First, in step S1, the sensor 10 senses the biological data of the user H and stores the sensed data in the storage device 50 in association with the sensed time. The sensing is continuously performed at predetermined time intervals.

[0099] Then, in step S2, the analysis device 20 analyzes the collected biological data, determines the health status of the user H, and stores the determination result in the storage device 50. For example, the analysis device 20 generates a learned model in advance through machine learning, and obtains the health status of the user H by applying the biological data of the user H to the learned model. Step S2 is performed regularly or at a timing considered necessary for each individual.

[0100] When the health status determination result is generated in the analysis device 20 , in step S3 , the program generation device 30 generates a health promotion program for each user H based on the health status determination result, and stores the program in the storage device 50 .

[0101] The determination result of the health status and the health promotion program are displayed on the output device 40. Thus, the user H can understand his / her own health status (e.g., health function and motor function) and clearly understand what to do to maintain, restore and improve his / her health function and motor function. The user H can practice the suggested health promotion program and use it for his / her own health management.

[0102] Then, the process returns to the sensing step and the above steps are repeated. Thus, the user H can effectively utilize the biological data acquired in daily life to promote the health function of the user H. In addition, the user H can understand the practical effect of the health promotion program through the determination result of the health status after the next time.

[0103] The sensor data, health status determination results, and health promotion programs thus accumulated are stored in the storage device 50, and are shared among medical personnel related to the user H with the permission of the user H. As a result, it is expected that the doctor's diagnosis and treatment will be more appropriate and rapid. This effect can be expected not only in face-to-face diagnosis and treatment, but also in remote diagnosis and treatment, achieving more substantial medical collaboration.

[0104] In addition, by sharing the health information of the user H described above among care-related personnel, it is expected that care support will be provided more appropriately and quickly.

[0105] Of course, the sensing data and the determination results of the health status can also be used as a protection system or an abnormality detection system for the user H.

[0106] In addition, the collected biological data and health status determination results can be used in the administration and the community with the approval of the user H, and can be reflected in policies for forming a more comfortable and livable community.

[0107] Since the sensor 10 is installed in the facility 70, there is no trouble of putting on and taking off like a wearable sensor. Moreover, since the sensor 10 is hidden from the eyes of the user H, the user H is not aware of the existence of the sensor 10. Therefore, the daily biological data of the user H can be obtained, and the health status with high reliability can be grasped.

[0108] As mentioned above, although the representative embodiment of the present invention was described, the present invention is not limited to this, and various design changes can be made, and these are also included in the present invention.

[0109] Industrial Applicability

[0110] According to the present invention, biological data obtained in the daily life of a user can be effectively utilized for maintaining and promoting the health of the user. The utilization of biological data includes supporting the user and information cooperation with medical and nursing personnel.

Claims

1. A system, characterized in that: is a system for providing health promotion programs to users, Include: A first sensor, which is disposed in a first facility and continuously collects biological data of the user; a second sensor disposed in a second facility and continuously collecting the same type of biological data from the user as the first sensor; an analysis device configured to perform analysis including comparison of the biological data collected by the first and second sensors and determine the health status of the user; A program generating device is configured to generate a health promoting program suitable for the user based on the determination result of the health status.

2. The system according to claim 1, characterized in that The biological data includes: at least one of data representing facial expression, heart rate, oxygen saturation, exhaled carbon dioxide, body surface temperature, core body temperature, skin protein analysis, body composition, autonomic nerves, HbA1c, body water content, foot pressure distribution, walking posture, walking speed, changes in joint range of motion, center of gravity changes, activity level, myoelectricity, electrocardiogram, brain waves, standing and sitting posture, body temperature, blood pressure, blood flow, heart rate, breathing, sweating, eyeballs, sleep time, excretion amount and time, blood components, urine components, saliva components, images inside the oral cavity, and feces components.

3. The system according to claim 2, characterized in that The analysis device performs the following steps: Using biological data of a person including at least one of data representing facial expression, heart rate, oxygen saturation, exhaled carbon dioxide, body surface temperature, core body temperature, skin protein analysis, body composition, autonomic nerves, HbA1c, body water content, foot pressure distribution, walking posture, walking speed, changes in joint range of motion, changes in center of gravity, activity, myoelectricity, electrocardiogram, brain waves, standing and sitting posture, body temperature, blood pressure, blood flow, heart rate, breathing, sweating, eyeballs, sleep time, amount and time of excretion, blood components, urine components, saliva components, images in the oral cavity, and feces components as teaching data, and the health status of the person including the energy consumption and exercise effect of the person, and generating, through machine learning: a prediction model whose input is the biological data of the person and whose output is the health status of the person; and The prediction model is used to output the health status of the user based on the collected biological data.

4. The system according to claim 3, characterized in that The program generation unit performs the following steps: Extracting the user's biological characteristics by comparing the collected biological data with a predetermined evaluation index; Using the evaluation values ​​representing the effects of the predetermined evaluation index and the health promotion program as teaching data, and generating, by machine learning, an evaluation model whose input is the biological data and whose output is the evaluation of the health promotion program; and Using the evaluation model, a health promotion program suggested to the user is output together with the biological characteristics of the user based on the collected biological data.

5. A method, characterized in that The invention is a method for providing a health promotion program to a user, which causes a computer having a processor and a memory to execute the following steps: continuously collecting biological data of the user at a first sensor disposed in a first facility; At a second sensor installed in a second facility, continuously collecting the same type of biological data from the user as that of the first sensor; performing analysis including comparison of the biological data collected by the first and second sensors to determine the health status of the user; Based on the determination result of the health status, a health promotion program corresponding to the user is generated.

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