System and method for providing health promotion program

Abstract

According to the present invention, a system for providing a health promotion program for a user in order to effectively utilize biological data, obtained during the daily life of the user, to maintain and promote the health of the user includes: a first sensor installed in a first facility and continuously collecting biological data of the user; a second sensor installed in a second facility and continuously collecting biological data of the same type as the first sensor from the user; an analysis device that performs an analysis including a comparison of the biological data collected by the first and second sensors, and assesses the health state of the user; and a program generation device that generates a health promotion program customized for the user on the basis of the result of the assessment of the health state.

Description

Systems and methods for providing wellness programs

[0001] The present invention relates to a system and method for providing a health promotion program tailored to the health status of users, including residents of a home.

[0002] Smart houses have been gaining attention in recent years. A smart house generally refers to a home that uses information technology (IT) to control electrical and gas-using appliances such as lighting fixtures, cooking appliances, and heating and cooling equipment, thereby optimizing energy consumption.

[0003] For example, Patent Document 1 (JP 2013-15271 A) discloses an indoor environment control system that includes an environmental information detection unit, an occupant information detection unit, a control unit, and an operation unit, in order to control the indoor environment according to the comfort of each occupant with a simple system without increasing time and energy costs. In this indoor environment control system, the storage means of the control unit is provided with a database that records the relationship between occupant information and the comfort of the occupants. The calculation means of the control unit generates an adjustment signal for fluctuating the operation unit using the occupant information as a fluctuation index so that the comfort of the occupants in the database is optimized based on the occupant information detected by the occupant information detection unit.

[0004] Furthermore, Patent Document 2 (Japanese Patent No. 6539799) discloses a safety confirmation system that accurately determines whether a resident is abnormal and, if an abnormality occurs, responds more safely, more reliably, and quickly. This safety confirmation system is installed in a residence and includes a first sensor that detects at least the resident's heart rate and respiratory rate without contact, an abnormality determination unit that detects significant differences from normal in the heart rate and respiratory rate, a communication unit that communicates safety confirmation between an operator and the resident, an arrival information presentation unit that notifies the operator of the arrival of emergency personnel at the residence in response to a dispatch request from the operator, and a remote unlocking unit that emergency unlocks the residence in response to a command from the operator.

[0005] JP 2013-15271 A Japanese Patent No. 6539799 A

[0006] The indoor environment control system of Patent Document 1 is limited to environmental control. The safety confirmation system of Patent Document 2 is limited to safety confirmation. These technologies only make limited use of collected biometric data. Furthermore, these technologies use wearable sensors to acquire biometric data, but putting on and taking off the wearable sensors is a hassle, and some people find the operation complicated. Therefore, there are still issues with the usability of the above technologies.

[0007] Therefore, an object of the present invention is to provide a system and method that can effectively utilize biometric data obtained in the daily lives of users, including residents, to maintain and improve the health of users.

[0008] To solve the above-mentioned problems, one aspect of the present invention provides a system for providing a health promotion program for a user, the system comprising: a first sensor installed in a first facility and continuously collecting biometric data of the user; a second sensor installed in a second facility and continuously collecting the same type of biometric data from the user as the first sensor; an analysis device configured to perform analysis, including a comparison of the biometric data collected by the first and second sensors, to determine the user's health status; and a program generation device configured to generate a health promotion program tailored to the user based on the health status determination result. Here, the biometric data includes not only biological data but also dynamic data. The health promotion program includes, in addition to an exercise program, various programs and various health information for maintaining and improving the user's physical and mental health.

[0009] In the system of the present invention, it is preferable that the biological data is at least one type of data among data indicating facial expression, heart rate, oxygen saturation, carbon dioxide exhalation, surface body 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, fluctuations in the center of gravity, activity level, electromyography, electrocardiography, electroencephalography, 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 of the oral cavity, and fecal components.

[0010] Furthermore, in the system of the present invention, it is preferable that the analysis device executes the steps of: using a person's biometric data including at least one type of data indicating a person's facial expression, heart rate, oxygen saturation, carbon dioxide exhalation, surface body 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, fluctuation of the center of gravity, activity level, electromyography, electrocardiography, electroencephalography, 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 of the oral cavity, and fecal components, as well as the person's health condition including the person's energy expenditure and exercise effect, as training data, generating by machine learning a prediction model whose input is the person's biometric data and whose output is the person's health condition, and using the prediction model to output the user's health condition from the collected biometric data.

[0011] In addition, in the system of the present invention, it is preferable that the program generation unit executes the following steps: extract the biometric characteristics of the user by comparing the collected biometric data with predetermined evaluation indices; use the predetermined evaluation indices and evaluation values ​​indicating the effectiveness of the health promotion program as training data, generate an evaluation model by machine learning, whose input is the biometric data and whose output is an evaluation of the health promotion program; and use the evaluation model to output a health promotion program to be presented to the user from the collected biometric data, together with the user's biometric characteristics.

[0012] Another aspect of the present invention provides a method for providing a health promotion program for a user, characterized in that a computer having a processor and a memory executes the steps of: continuously collecting biometric data of the user using a first sensor installed in a first facility; continuously collecting the same type of biometric data from the user as used by the first sensor using a second sensor installed in a second facility; performing an analysis including a comparison of the biometric data collected by the first and second sensors, determining the health status of the user; and generating a health promotion program tailored to the user based on the results of the health status determination.

[0013] According to the present invention, biological data obtained in the daily life of a user can be effectively utilized to maintain and improve the user's health.

[0014] It is a schematic diagram showing an overall picture of an exemplary embodiment of the present invention. It is a block diagram showing the overall configuration of a system 1 for providing a health promotion program. It is a flowchart showing a processing procedure for providing a health promotion program.

[0015] Representative embodiments of the system and method according to the present invention will be described in detail below with reference to the drawings. However, the present invention is not limited to these drawings. Furthermore, since the drawings are intended to conceptually explain the present invention, dimensions, ratios, and numbers may be exaggerated or simplified as necessary to facilitate understanding.

[0016] 1. Overview of the Present Embodiment The overview surrounding the system according to the present embodiment will be described with reference to FIG.

[0017] The term "facility" in this embodiment (the present invention) refers to any facility (also referred to as a facility, institution, site, place, activity base, etc.) that can use the system according to the present invention. Examples of facilities include, but are not limited to, homes, workplaces, educational facilities such as schools, medical facilities such as hospitals and health checkup centers, nursing homes, care facilities, nursing homes, elderly care facilities, exercise facilities, entertainment facilities, meeting places, and accommodation facilities. Biometric data of users who spend their daily lives in these facilities is sensed by sensors installed in various locations within the facilities. For example, for a user engaged in transportation services, the workplace may include mobile objects such as vehicles, ships, and aircraft.

[0018] Here, biometric data refers to all data that can be obtained from a user's body. Biometric data includes not only dynamic data such as walking posture, walking speed, changes in joint range of motion, center of gravity fluctuation, and activity level, but also static data such as time-series data on electromyography, electrocardiograms, and electroencephalograms, standing and sitting posture, body temperature, blood pressure and blood flow, heart rate, breathing, sweating, eye movements, sleep time, amount and time of excretion, blood components, urine components such as blood glucose levels, saliva components, images of the oral cavity (tongue, pharynx, etc.), and fecal components. Furthermore, a home refers to a building where a person lives daily, and includes not only detached houses and apartment buildings, but also so-called nursing homes.

[0019] The obtained biometric data is then analyzed by computer to determine the health condition of the user. For example, by comparing the same type of biometric data sensed in different facilities, i.e., the first and second biometric data, the health condition of the user in different environments can be accurately evaluated.

[0020] For example, if the measured values ​​of a user's blood pressure, heart rate, respiratory rate, and sweating rate at the workplace are greater than the corresponding values ​​at the user's home by a preset value or more, the user may be assessed as being in a state of excessive tension at the workplace. Alternatively, if the measured values ​​of a user's blood pressure, heart rate, respiratory rate, blood flow, and sweating rate at a user's exercise facility are greater than the corresponding values ​​at the user's home by a preset tolerance, the user may be assessed as being performing moderate exercise. Alternatively, if the measured or estimated values ​​of a user's travel distance, travel speed, and metabolism at the workplace are smaller than the corresponding values ​​at the user's home by a preset value or more, the user may be assessed as being in a state of insufficient exercise at the workplace. Alternatively, if the measured values ​​of a user's blood pressure, heart rate, and respiratory rate at a user's accommodation and recreational facilities are smaller than the corresponding values ​​at the user's home by a preset value or more, the user may be assessed as being in a state of moderate relaxation at the accommodation and recreational facilities. Alternatively, if the measured values ​​of a user's brain waves at a user's educational facility or workplace are different from the corresponding values ​​at the user's home, the user may be assessed as being in a state of lack of concentration.

[0021] Next, a customized health promotion program is created for each user based on the health status assessment results. The health promotion program created here may include exercise programs as well as various programs and health information for maintaining and improving the user's physical and mental health.

[0022] For example, if a user is assessed as being under excessive tension at work, the system may suggest measures to alleviate the tension, such as improving work practices, taking time off, engaging in moderate exercise, getting enough sleep, and consulting a doctor. In this case, an exercise menu tailored to the user's health condition may be presented. Alternatively, if a user is assessed as being under-exercised at work, the system may suggest, for example, moderate exercise.

[0023] Such health promotion programs are provided to users and are implemented by the users.

[0024] The user's health functions are improved by repeating the above-mentioned sensing, health condition assessment, and creation of a health promotion program and its implementation by the user. The collected biometric data may be aggregated in a data server or the like and, with the user's consent, presented to and used by medical professionals such as doctors. The generated health condition assessment results may also be presented to and used by medical professionals with the user's consent.

[0025] Furthermore, with the user's consent, the collected biometric data and the generated health status assessment results may be used by government and local communities to create more comfortable and livable communities, to manage the health of residents, and to enable people to continue living independently in their own homes in old age.

[0026] The system 1 of this embodiment has a functional unit that realizes a sensing function that collects biometric data from users within the facility, an analysis and judgment function that determines the health status of users by analyzing the collected biometric data, and a program generation function that generates a health promotion program based on the health status judgment results.

[0027] To achieve 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 FIG. 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 or integrated. The storage device 50 may be installed as a component of a data center (not shown), and the data center may store not only collected data but also collected samples (e.g., saliva or fecal samples). In this case, the data center may also be called a biobank. These components will be described in detail below.

[0028] 2. Sensor The sensor 10 is a general term for various sensors that are installed in a facility 70 such as a house and continuously collect biometric data of the user H. The sensor 10 transmits and stores the collected biometric data together with the collection date and time to the storage device 50. The storage device 50 may be, but is not limited to, a data server. The sensor 10 may transmit and store the collected biometric data in storage (not shown) within the facility 70.

[0029] Examples of sensors 10 that may 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).

[0030] More specifically, the infrared thermal camera is installed in rooms such as the living room, study, bedroom, and office of the facility 70, and can measure the user H's facial expression, heart rate, oxygen saturation, carbon dioxide exhalation, surface body temperature, and core body temperature. The hyperspectral imaging camera is installed, for example, at the entrance or nearby and can perform personal authentication of the user H, as well as analyze the user H's skin protein, measure body composition (e.g., composition ratio of fat, bone, lean soft tissue, etc., weight, body fat, basal metabolic rate, visceral fat, muscle mass, and bone mass), and measure autonomic nerves (e.g., autonomic nerve fatigue level and balance between sympathetic and parasympathetic nerves). Alternatively, the hyperspectral imaging camera can be installed at the dining table, kitchen, or nearby to measure glycated hemoglobin (HbA1c). The RFID sensor is installed on a wall in the room and can measure the user H's internal water content. The pressure sensor is installed, for example, in the hallway or on the floor in the room and can measure the foot pressure distribution of the user H. The motion capture device can be installed, for example, in a hallway in a room, and can measure the user H's walking posture, walking speed, changes in joint range of motion, fluctuations in the center of gravity, and activity level.

[0031] The sensing of the biometric data of the user H by the sensor 10 may be performed, for example, by constant measurement. The sensor 10 is preferably installed hidden from view so that the user H cannot immediately discover it. This is to prevent the user H from becoming nervous upon noticing the presence of the sensor 10, and to prevent the sensed biometric data from deviating from the everyday values ​​of the user H. In other words, this is to know the user H in a natural state in everyday life.

[0032] In addition to the sensor 10, sensors for obtaining environmental data may be installed. For example, a thermometer for measuring the room temperature, a hygrometer for measuring the humidity in the room, an illuminance meter for measuring the brightness in the room, a CO ２ A carbon dioxide meter or the like may be installed to measure the concentration. The environmental data collected by these sensors is transmitted to and stored in the storage device 50. Note that the sensor 10 may include these sensing functions.

[0033] Additionally, various sensors built into wearable devices and mobile information terminals such as smartphones may be used to acquire biometric data of the user. This type of biometric data is useful for assisting in determining the user's health condition. The sensor 10 may include these sensing functions.

[0034] The collected biometric data, environmental data, and other data are transmitted to and stored in the storage device 50. The storage device 50 may also store the health status assessment results and the generated health promotion program, which will be described later. The various data stored in the storage device 50 may be made available to an external computer 80 used by the doctor and medical institution in charge of user H, with the permission of user H. Such medical collaboration enables various health records necessary for the diagnosis and treatment of user H to be shared in a timely manner among medical professionals. Of course, data collaboration may also be targeted at doctors, dentists, pharmacists, nutritionists, etc., and is not limited to medical professionals.

[0035] 3. Analysis Device The analysis device 20 analyzes the biological data collected by the sensor 10 to determine the health condition of the user H.

[0036] The analysis device 20 can suitably use AI analysis for data analysis. Specifically, the analysis device 20 uses a person's biometric data, including at least one type of data indicating a person's facial expression, heart rate, oxygen saturation, carbon dioxide exhalation, surface body 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 fluctuation, activity level, electromyography, electrocardiography, electroencephalography, standing and sitting posture, body temperature, blood pressure, blood flow, heart rate, breathing, sweating, eye movements, sleep time, amount and time of excretion, blood components, urine components, saliva components, images of the oral cavity, and fecal components, as training data, and the person's health condition, including the person's energy expenditure and exercise effect, to generate a prediction model by machine learning, which inputs the person's biometric data and outputs the person's health condition. The analysis device 20 then uses the generated prediction model to output the user's health condition from the collected biometric data.

[0037] For example, the analysis device 20 can use at least one type of biological data, such as a person's facial expression, heart rate, oxygen saturation, exhaled carbon dioxide, surface body temperature, deep 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 fluctuation, and activity level, as an existing indicator and use it as a teacher variable (teacher data). In other words, the analysis device 20 can perform machine learning using the same type of biological data as the data group collected by the sensor 10 as explanatory variables to create an analysis program. The analysis device 20 can then use basic information, such as age, gender, height, and weight, as parameters to perform algorithmic analysis of biological information, such as facial expression, heart rate, oxygen saturation, exhaled carbon dioxide, surface body temperature, deep body temperature, skin protein analysis, body composition, autonomic nerves, HbA1c, body water content, and foot pressure distribution, as well as joint angles during walking and their changes over time, lower limb muscle strength, center of gravity, or motor function information, such as three-dimensional movement distance of observation points correlated thereto, walking posture, walking speed, and activity level. The analysis device 20 applies the sensing data to the above model to obtain an objective evaluation including health function and motor function as the health state of the user H. An example of machine learning that can be used in this embodiment is deep learning, but is not limited to this.

[0038] The analysis result 20 transmits and stores the assessment result of user H's health condition to the storage device 50. It goes without saying that such assessment result can be effectively used by related parties, including medical professionals, with user H's permission. Furthermore, by outputting the assessment result of user H's health condition to the output device 40 described below, user H and his / her family can detect user H's illness or poor physical condition early and can also use the result to manage user H's health. In other words, the assessment result can be effectively used to support user H and to cooperate with related parties.

[0039] 4. Program Generation Device The program generation device 30 generates a health promotion program customized for each user H based on the health condition assessment results obtained by the analysis device 20. That is, the program generation device 30 compares the collected biometric data with predetermined evaluation indices to extract the user's biometric characteristics. The program generation device 30 then uses the predetermined evaluation indices and evaluation values ​​indicating the effectiveness of the health promotion program as training data to generate an evaluation model through machine learning, with the biometric data as input and the evaluation of the health promotion program as output. The program generation device 30 then uses the evaluation model to output a health promotion program to be presented to the user, along with the user's biometric characteristics, based on the collected biometric data. Here, health promotion programs are broadly divided into those related to health functions and those related to motor functions.

[0040] For example, with regard to health functions, the program generation device 30 identifies the biometric characteristics of user H by comparing the normal range for each individual with evaluation indices such as epidemiological and medical guidelines for facial expression, heart rate, oxygen saturation, carbon dioxide exhalation, surface body temperature, core body temperature, skin protein analysis, body composition, autonomic nerves, HbA1c, body water content, and foot pressure distribution.The program generation device 30 then uses AI to analyze the measured data, basic information such as age, sex, height, and weight, and data on user H's living environment (for example, biometric data collected by the sensor 10), thereby constructing an algorithm related to each individual's lifestyle habits and presenting behavioral changes and the associated effects.

[0041] Furthermore, with regard to motor function, the program generation device 30 identifies the dynamic analysis characteristics of the user H by comparing the position and velocity of each joint, as well as the joint angle and angular velocity. Then, based on the measured data, the program generation device 30 can estimate the amount of energy consumed during exercise and the exercise effect, as well as construct a movement measurement algorithm and present recommended exercises, the amount of energy consumed during exercise, and the exercise effect. Examples of AI analysis that can be used here include, but are not limited to, deep learning.

[0042] The program generation device 30 transmits and stores the generated health promotion program in the storage device 50. Needless to say, such a program can be shared among medical professionals with the permission of user H. Furthermore, by outputting the program to the output device 40, user H and his / her family can clearly understand what they need to do to maintain, restore, and improve user H's health and motor functions, and can utilize the program in user H's health management.

[0043] The analysis device 20 and the program generation device 30 can be configured as one or more computers including an arithmetic circuit such as a central processing unit (CPU) and memories such as a random access memory (RAM) and a read-only memory (ROM). The functions of the analysis device 20 and the program generation device 30 described above can be realized by loading an execution program stored in the ROM into the RAM and executing it with the CPU. The analysis device 20 and the program generation device 30 use continuously collected biological data to determine health conditions and generate health promotion programs periodically or at times considered necessary for each individual.

[0044] The output device 40 is a device that outputs the health status assessment results and the health promotion program. The output device 40 includes the user H's terminal (including a smartphone or personal computer), a display, a printer, a projector, and a speaker. For example, if the health status assessment results indicate an abnormality in the user H's health status, i.e., a deviation from the normal range (for example, in the case of data expressed as a number, if the value is above or below a predetermined threshold or outside the predetermined range), the output device 40 may output an alert to the terminals of the user H and related parties. The output device 40 may also display other information related to daily life, such as information on energy, housing, and local area.

[0045] 5. Operation of the Health Promotion Program Providing System The processing procedure for providing a health promotion program by the system 1 will be described with reference to FIG.

[0046] First, in step S1, the sensor 10 senses the biometric data of the user H and stores the data in association with the sensing time in the storage device 50. The sensing is performed continuously at predetermined time intervals.

[0047] Then, in step S2, the analysis device 20 analyzes the collected biometric data, determines the health condition of user H, and stores the determination result in the storage device 50. For example, the analysis device 20 generates a trained model in advance by machine learning, and obtains the health condition of user H by applying the biometric data of user H to the trained model. Step S2 is executed periodically or at a timing considered necessary for each individual.

[0048] When the health status assessment results are 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 assessment results and stores the program in the storage device 50.

[0049] The health condition assessment results and the health promotion program are displayed on the output device 40. This allows user H to understand his / her own health condition (e.g., health function and motor function) and clearly understand what he / she should do to maintain, restore, and improve his / her health function and motor function. User H can put the presented health promotion program into practice and utilize it in his / her own health management.

[0050] Then, the process returns to sensing and the above procedure is repeated. This allows user H to effectively utilize biometric data obtained in daily life to improve his / her health functions. User H can also understand the effect of practicing the health promotion program through the health condition assessment results from the next time onwards.

[0051] The sensing data, health condition assessment results, and health promotion program accumulated in this way are stored in the storage device 50 and, with the permission of user H, are shared among medical professionals related to user H. This is expected to enable doctors to make diagnoses and treatments more appropriately and quickly. This effect can be expected not only during face-to-face consultations but also in remote consultations, realizing more comprehensive medical cooperation.

[0052] In addition, by sharing the health information of user H described above among caregivers, it is expected that more appropriate and prompt care support will be provided.

[0053] Of course, the sensing data and the health status assessment results can also be used as a monitoring system or anomaly detection system for user H. In addition, the collected biometric data and health status assessment results can be used by the government and local community with the consent of user H, and can be reflected in policies to create a more comfortable and livable community.

[0054] Because the sensor 10 is installed in the facility 70, there is no need to bother putting it on or taking it off, as there is with a wearable sensor. Furthermore, because the sensor 10 is hidden from the eyes of the user H, the user H is not aware of the presence of the sensor 10. Therefore, it is possible to obtain daily biological data of the user H, and to grasp the health condition with high reliability.

[0055] Representative embodiments of the present invention have been described above, but the present invention is not limited to these, and various design modifications are possible, which are also included in the present invention.

[0056] According to the present invention, biometric data obtained in the user's daily life can be effectively utilized to maintain and improve the user's health. Utilization of biometric data includes supporting the user and sharing information with medical and nursing care professionals.

[0057] 1 Health promotion program providing system 10 Sensor 20 Analysis device 30 Program generating device 40 Output device 50 Storage device H User

Claims

1. A system for providing a health promotion program for a user, comprising: a first sensor installed in a first facility and continuously collecting biometric data of the user; a second sensor installed in a second facility and continuously collecting the same type of biometric data from the user as the first sensor; an analysis device configured to perform analysis including a comparison of the biometric data collected by the first and second sensors and determine the health condition of the user; and a program generation device configured to generate a health promotion program tailored to the user based on the results of the health condition determination.

2. The system of claim 1, wherein the biometric data includes at least one type of data among facial expressions, heart rate, oxygen saturation, carbon dioxide exhalation, surface body temperature, deep 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, fluctuations in center of gravity, activity level, electromyography, electrocardiography, electroencephalography, standing and sitting postures, 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 of the inside of the oral cavity, and fecal components.

3. The system described in claim 2, characterized in that the analysis device executes the steps of: using a person's biometric data including at least one type of data indicating a person's facial expression, heart rate, oxygen saturation, carbon dioxide exhalation, surface body temperature, deep body temperature, skin protein analysis, body composition, autonomic nerves, HbA1c, body water content, foot pressure distribution, walking posture, walking speed, change in range of joint motion, fluctuation of center of gravity, activity level, electromyography, electrocardiography, electroencephalography, 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 of the oral cavity, and fecal components, as well as the person's health condition including the person's energy consumption and exercise effect as teacher data, generating a predictive model by machine learning, which takes the person's biometric data as input and outputs the person's health condition, and using the predictive model to output the user's health condition from the collected biometric data.

4. The system described in claim 3, characterized in that the program generation unit executes the steps of: extracting the biometric characteristics of the user by comparing the collected biometric data with predetermined evaluation indexes; using the predetermined evaluation indexes and an evaluation value indicating the effectiveness of the health promotion program as teacher data, generating an evaluation model by machine learning, the input of which is the biometric data and the output of which is an evaluation of the health promotion program; and using the evaluation model, outputting a health promotion program to be presented to the user from the collected biometric data together with the biometric characteristics of the user.

5. A method for providing a health promotion program for a user, comprising: a computer having a processor and memory executing the steps of: continuously collecting biometric data of the user at a first sensor installed in a first facility; continuously collecting the same type of biometric data from the user as that collected by the first sensor at a second sensor installed in a second facility; performing an analysis including a comparison of the biometric data collected by the first and second sensors, determining a health condition of the user; and generating a health promotion program tailored to the user based on the result of the health condition determination.

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