system

Abstract

Provide a system. A means for recording meal information input by a user; means for recording exercise information input by a user; means for recording health check information entered by a user; A means for making diet, exercise, and fasting recommendations based on the recorded diet information, exercise information, and health check information; means for generating a user's health status based on the recorded health check information; A system including:

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In modern society, people lead busy lives, yet need to maintain their health through proper diet and exercise. However, many people find it difficult to accurately grasp their own health status and lack efficient methods for managing their health. As a result, they may incur unnecessarily high medical expenses for disease prevention and treatment. The present invention aims to solve the above problems by providing a system that records and manages a user's dietary information, exercise information, and health check information, and makes recommendations for appropriate health maintenance. [Means for solving the problem]

[0005] The present invention provides a system including a means for recording dietary information entered by a user, a means for recording exercise information entered by a user, and a means for recording health check information entered by a user. The system also includes a means for recommending appropriate diets, exercise, and fasting to the user based on the recorded dietary information, exercise information, and health check information. The system further includes a means for generating a health status report for the user based on the recorded health check information and notifying the user of the need for a health check, as necessary. This allows the user to efficiently manage their health, prevent illness, and reduce medical costs.

[0006] "User" means an individual who uses an information system or application.

[0007] "Dietary Information" refers to data regarding the foods and dietary content consumed by a user.

[0008] "Exercise information" refers to data regarding the type, duration, intensity, etc. of exercise performed by the user.

[0009] "Health check information" refers to data related to the user's health checkups and daily health status.

[0010] "Means of recording" refers to the function for saving information entered by the user in a database, cloud, etc.

[0011] "Means for making recommendations" refers to a function that suggests appropriate actions to the user based on the recorded data.

[0012] "Means for generating" refers to the function of analyzing and evaluating the user's health condition based on the recorded data.

[0013] "Means of notification" refers to the system's ability to communicate necessary information to the user.

[0014] "System" refers to a computer network configuration in which multiple pieces of software and hardware work together.

[0015] A "server" is a computer that provides data to other computers or devices over a network.

[0016] "Terminal" refers to a device with input and output that can be operated by a user. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] The system of the present invention aims to help users manage their own health and reduce medical costs. This system records dietary information, exercise information, and health check information entered by users, and based on this, makes recommendations for diet, exercise, and fasting, and generates the user's health status.

[0039] 1. Recording your dietary information

[0040] The user inputs the details of the meal they had into the device. For example, if they had "oatmeal and fruit for breakfast," they input that information. The device then sends this data to the server. The server stores the received meal information in a database. This information will be used to analyze the user's eating patterns in the future.

[0041] 2. Recording exercise information

[0042] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information. The device then sends this data to the server. The server stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[0043] 3. Recording health check information

[0044] The user inputs the results of the health check into the terminal. For example, the user may input the result "my health condition is good." The terminal then sends this data to the server. The server stores the received health check information in a database. This information is used to evaluate the user's health condition.

[0045] 4. Diet, exercise, and fasting recommendations

[0046] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary, exercise, and health check information. For example, based on the user's data, it may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." The device then displays these recommendations to the user.

[0047] 5. Health Status Generation

[0048] The server generates the user's latest health status based on the recorded health check information. For example, if the result of the most recent health check is "good health," the server presents that result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays the notification to the user.

[0049] Specific examples

[0050] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, the user underwent a health check and recorded as being in "good health." The server records this information, and when the user accesses the system on January 2nd, it recommends "a balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month." It also presents the information that "the user is in good health" based on the results of the most recent health check.

[0051] In this way, users can maintain their health and reduce medical expenses by inputting information into the system on a daily basis and receiving appropriate health care recommendations from the server via their terminal.

[0052] The processing flow will be explained below.

[0053] Program processing steps

[0054] 1. Recording your dietary information

[0055] Step 1:

[0056] User: Eats "oatmeal and fruit" for breakfast, then enters the meal details into the device.

[0057] Step 2:

[0058] User: Enters "oatmeal and fruit" into the device's input form and presses the submit button.

[0059] Step 3:

[0060] Terminal: Sends the meal details entered by the user to the server.

[0061] Step 4:

[0062] Server: Save the received meal information in the "meals" list. This list is stored in the form of a dictionary of dates and meal information.

[0063] Step 5:

[0064] Server: Confirms that the meal record was saved successfully and sends a confirmation message to the user.

[0065] 2. Recording exercise information

[0066] Step 1:

[0067] User: Goes for a 30-minute jog, then enters the details of the exercise into the device.

[0068] Step 2:

[0069] User: Enter "30 minutes of jogging" into the device's input form and press the send button.

[0070] Step 3:

[0071] Terminal: Sends the exercise information entered by the user to the server.

[0072] Step 4:

[0073] Server: Saves the received exercise details in the "exercises" list. This list is stored in the form of a dictionary of dates and exercise details.

[0074] Step 5:

[0075] Server: Confirms that the exercise record was saved successfully and sends a confirmation message to the user.

[0076] 3. Recording health check information

[0077] Step 1:

[0078] User: Takes a health check and enters the result "I am in good health" into the terminal.

[0079] Step 2:

[0080] User: Enters "My health is good" into the input form on the device and presses the send button.

[0081] Step 3:

[0082] Terminal: Sends the health check information entered by the user to the server.

[0083] Step 4:

[0084] Server: Save the received health check information in the "health_checks" list. This list is stored in the form of a dictionary of dates and health information.

[0085] Step 5:

[0086] Server: Confirm that the health check record was saved successfully and send a confirmation message to the user.

[0087] 4. Dietary Recommendations

[0088] Step 1:

[0089] User: Requests food recommendations from the server via the device.

[0090] Step 2:

[0091] Server: Receives the request and executes the meal recommendation logic based on the stored meal information.

[0092] Step 3:

[0093] Server: Generate the recommendation "balanced vegetable-based meal."

[0094] Step 4:

[0095] Server: Sends recommendations to the user.

[0096] Step 5:

[0097] Device: Displays meal recommendations to the user.

[0098] 5. Exercise Recommendations

[0099] Step 1:

[0100] User: Requests exercise recommendations from the server via the device.

[0101] Step 2:

[0102] Server: Receives the request and executes the exercise recommendation logic based on the stored exercise information.

[0103] Step 3:

[0104] Server: Generate the recommendation "Take a 30-minute walk three times a week."

[0105] Step 4:

[0106] Server: Sends recommendations to the user.

[0107] Step 5:

[0108] Device: Display exercise recommendations to the user.

[0109] 6. Fasting recommendations

[0110] Step 1:

[0111] User: Requests fasting recommendations from the server via the device.

[0112] Step 2:

[0113] Server: Receives the request and executes the fasting recommendation logic.

[0114] Step 3:

[0115] Server: Generate the recommendation "24-hour fast once a month."

[0116] Step 4:

[0117] Server: Sends recommendations to the user.

[0118] Step 5:

[0119] Device: Display fasting recommendations to the user.

[0120] 7. Health Status Generation

[0121] Step 1:

[0122] User: Requests the server to generate a health status via the terminal.

[0123] Step 2:

[0124] Server: Receives the request and executes the logic to generate the user's health status based on the stored health check information.

[0125] Step 3:

[0126] Server: Generates a health status of "good health" based on the latest health check results.

[0127] Step 4:

[0128] Server: Sends the generated health status to the user.

[0129] Step 5:

[0130] Terminal: Display health status to the user.

[0131] Example 1

[0132] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0133] In modern society, individual health management and rising medical costs are becoming serious issues. Current health management systems allow users to input and track their own health data, but they lack effective utilization and optimal health management recommendations. The data entered by users is stored fragmentedly, preventing unified health management advice, making it difficult to improve users' health. Furthermore, users may not receive notifications even if appropriate health checks are not performed, which increases the risk of users neglecting to check their health.

[0134] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0135] In this invention, the server includes a means for recording dietary information entered by the user, a means for recording exercise information entered by the user, a means for recording health check information entered by the user, a means for storing the recorded dietary information, exercise information, and health check information in a database, a means for making diet, exercise, and fasting recommendations using a machine learning algorithm based on the recorded dietary information, exercise information, and health check information, a means for notifying the terminal of the recommendations, and a means for generating the user's health status based on the recorded health check information. This makes it possible to centrally manage health-related data entered by the user and provide optimal health management recommendations using a machine learning algorithm. Furthermore, by providing a notification even if a health check has not been performed, the server can encourage the user to perform a health check.

[0136] "User" refers to an individual who uses the system and is the entity that inputs data such as dietary information, exercise information, and health check information.

[0137] "Terminal" refers to an electronic device used to send data entered by a user to a server, including smartphones and tablets.

[0138] "Dietary information" refers to data relating to the types and amounts of food consumed by the user, and is information for recording the user's nutritional intake status.

[0139] "Exercise information" refers to data relating to the type and duration of exercise performed by the user, and is information for recording the user's exercise status.

[0140] "Health check information" refers to data such as diagnostic results and self-assessment regarding the user's health condition, and is information for evaluating the user's health condition.

[0141] "Server" refers to a centralized computer system that receives, processes, and stores data submitted by users, including databases and analytical algorithms.

[0142] A "database" refers to a digital archive for storing a user's dietary information, exercise information, health check information, etc. in a structured manner, making it easy to search and manage information.

[0143] A "machine learning algorithm" refers to a computational method for discovering patterns based on accumulated data and making predictions and recommendations, and is used in data analysis and building predictive models.

[0144] "Recommendations" refers to health management advice and suggestions for users generated by machine learning algorithms, including diet, exercise, fasting, etc.

[0145] "Notification means" refers to methods for informing users of information such as recommendations and the need for health checks, and includes push notifications and dashboard displays.

[0146] The system of the present invention aims to enable users to manage their own health and reduce medical costs. This system records dietary information, exercise information, and health check information entered by the user, and based on this information, makes recommendations for diet, exercise, and fasting, thereby generating a health status report for the user. Specific embodiments of this system are described below.

[0147] System Configuration

[0148] User

[0149] Users access the system using devices such as smartphones and tablets, which have a dedicated health management app installed.

[0150] Terminal

[0151] The device accepts information about meals, exercise, and health checks entered by the user. This information is converted into JSON format and sent to the server using the HTTPS protocol.

[0152] The device is responsible for displaying recommendations and health check notifications to the user. It uses a push notification service (e.g., Firebase Cloud Messaging) to notify the user.

[0153] server

[0154] The server is built using a cloud service (e.g., a general cloud computing platform). The server has the following roles:

[0155] 1. Data reception: Receives meal information, exercise information, and health check information sent by users. This is done using an API using the Flask framework.

[0156] 2. Data storage: The received data is stored in a MySQL (registered trademark) database. The database is divided into a "meal information table," a "exercise information table," and a "health check information table."

[0157] 3. Data analysis: Periodically, a scheduler (e.g., cron job) is used to analyze the recorded data using machine learning algorithms (e.g., Scikit-learn), which then generates appropriate diet, exercise, and fasting recommendations for the user.

[0158] 4. Health Status Generation: Generates the latest health status based on the recorded health check information. If necessary, notifies the user that a health check is required.

[0159] Specific examples

[0160] For example, if a user eats "oatmeal and fruit" for breakfast on January 1st, goes "30 minutes jogging" on the same day, and records a health check as "good health," the server records this information, and when the user accesses the system on January 2nd, it provides the following recommendations:

[0161] A balanced diet centered around vegetables

[0162] 30-minute walks three times a week

[0163] 24-hour fasting once a month

[0164] It also displays "good health" based on the results of the most recent health check. In this way, users can input information into the system on a daily basis and receive appropriate health management recommendations from the server via their terminal, thereby maintaining their health and reducing medical costs.

[0165] Example of input prompt for generative AI model

[0166] "I would like to design a user interface for a health management system. Please suggest a design for a form that allows users to easily enter information about their diet, exercise, and health checks."

[0167] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0168] Step 1:

[0169] A user opens a smartphone app and inputs the details of the meal they had. For example, they input "oatmeal and fruit for breakfast." The device converts this input information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed data about the meal, and the device converts it into JSON format and sends it.

[0170] Step 2:

[0171] The server receives the meal information using an API built with the Flask framework. It parses the received data and stores it in a MySQL "meal information" table. The input is JSON-formatted meal information data, which is parsed and stored in the database.

[0172] Step 3:

[0173] The user uses the same app to input the details of the exercise they performed. For example, they input "30 minutes of jogging." The device converts this exercise information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed exercise data, which is then converted into JSON format and sent.

[0174] Step 4:

[0175] The server processes the received exercise information using the Flask API, parses the data, and saves it in the MySQL "exercise information" table. The input is exercise information data in JSON format, which is parsed and stored in the database.

[0176] Step 5:

[0177] The user enters the results of their health check into the app. For example, they might enter "My health is good." The device converts this health check information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed health check data, which is then converted into JSON format and sent.

[0178] Step 6:

[0179] The server processes the received health check information through the Flask API, parses the data, and saves it in the MySQL "health check information" table. The input is health check information data in JSON format, which is parsed and stored in the database.

[0180] Step 7:

[0181] The server periodically uses a scheduler (e.g., cron job) to perform data analysis based on the recorded dietary information, exercise information, and health check information. This process uses Python and Scikit-learn. As a result of the analysis, it generates optimal diet, exercise, and fasting recommendations for the user. The input is multiple pieces of information obtained from the database, which are then analyzed and the recommendations are output.

[0182] Step 8:

[0183] The server sends the generated recommendation to the user's device. The device uses the Firebase Cloud Messaging service to send a push notification to the user to notify them of the new recommendation. When the user taps the notification, they can view the detailed recommendation within the app. The input is the generated recommendation, and the operation to send it to the user via a push notification is performed.

[0184] Step 9:

[0185] The server generates the user's latest health status based on the periodically saved health check information. For example, if the most recent health check result is "good health," the server presents that result to the user. The input is health check information retrieved from the database, and the server evaluates it and outputs the latest health status.

[0186] Step 10:

[0187] If there is no health check record, the server uses Firebase Cloud Messaging to notify the user that a "health check is required." The device receives this notification and displays it on the app's dashboard. The input is whether or not there is a health check record, and the notification action is performed based on that.

[0188] (Application example 1)

[0189] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0190] Conventional health management systems require users to manually input information about their diet and exercise, and suffer from issues such as a lack of data accuracy and real-time performance. Furthermore, there are only limited systems that utilize accumulated data to provide effective health management recommendations. This has resulted in a lack of an optimal approach for efficiently managing users' health status and reducing medical costs.

[0191] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0192] In this invention, the server includes a means for transmitting dietary information, exercise information, and health check information manually input by the user to the server, a means for automatically recording the user's exercise data and dietary data using hardware functions such as an exercise sensor and a barcode scanner and transmitting the data to the server, a means for analyzing the data accumulated by the server using a machine learning algorithm to generate appropriate diet, exercise, and fasting recommendations for the user, and a means for notifying the user of the recommendations. This allows users to efficiently accumulate health management information by utilizing both manual input and automatic recording, and to receive optimal health management recommendations for each individual user through the machine learning algorithm.

[0193] "Dietary information" refers to data about the contents of the foods and drinks consumed by the user.

[0194] "Exercise information" refers to data regarding the type, duration, and intensity of exercise performed by the user.

[0195] "Health check information" refers to data related to the user's health condition, such as weight, blood pressure, and heart rate.

[0196] A "server" is a computer system that stores and analyzes data sent by users and provides necessary information.

[0197] "Recommendation" refers to providing optimal diet, exercise, and fasting advice based on the user's health data.

[0198] An "exercise sensor" is a device for detecting a user's exercise status, and is a device for measuring the number of steps, distance, calorie consumption, etc.

[0199] "Barcode scanning" is the act of reading the barcode of food or products and recording that information as data.

[0200] A "machine learning algorithm" is a program that analyzes the data received by the server, finds patterns, and generates optimal recommendations for users.

[0201] "Notification" refers to the act of informing the user of the generated recommendations and necessary health check information.

[0202] A "smartphone" is a multi-function mobile phone that can connect to the Internet and use applications.

[0203] "Smart glasses" are wearable devices that can provide information visually.

[0204] A "smartwatch" is a wearable device that has a built-in motion sensor and measures the user's biometric information and motion data.

[0205] The system for implementing this invention aims to record dietary information, exercise information, and health check information entered by users and provide appropriate health management recommendations. The main components of the system include devices such as smartphones, smart glasses, and smart watches, and a server that performs data analysis.

[0206] System Structure

[0207] 1. Recording your dietary information:

[0208] Users can use their smartphones or smart glasses to input meal information by scanning barcodes or by voice input. For example, they can use their smartphone's camera to scan food barcodes and input "I had oatmeal and fruit for breakfast."

[0209] The device sends the entered meal information to the server, and the server stores the received data in a database (e.g., Firebase, Google (registered trademark) Cloud Firestore).

[0210] 2. Recording exercise information:

[0211] The smartwatch's motion sensor automatically records the user's motion data. For example, if you go for a 30-minute jog, the smartwatch will record that motion data.

[0212] The device transfers this data to a smartphone via Bluetooth, which then sends it to a server, which stores the data in a database.

[0213] 3. Recording Health Check Information:

[0214] Users enter their health check information (weight, blood pressure, heart rate, etc.) through the app. For example, if their weight is 65 kg, their blood pressure is 120 / 80 mmHg, and their heart rate is 70 bpm, they enter that information into their smartphone.

[0215] The terminal sends the input information to the server, which stores it in a database.

[0216] 4. Health Care Recommendations:

[0217] The server analyzes the collected data using machine learning algorithms (e.g., TENSORFLOW®) to generate recommendations for diet, exercise, and fasting. For example, based on the analysis of the user's dietary and exercise information, the server may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month."

[0218] The device will notify the user of the recommendations, for example, by displaying them on the HUD (heads-up display) of smart glasses or via a pop-up notification on a smartphone.

[0219] 5. Health generation:

[0220] The server analyzes the user's latest health status based on the recorded health check information. For example, if the result of the most recent health check is "good health," the server presents that information to the user.

[0221] If the health status is not recorded, the server will notify the user that a health check is required.

[0222] Specific examples

[0223] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went on a "30-minute jog" on the same day. If this user also records "weight 65 kg, blood pressure 120 / 80 mmHg, heart rate 70 bpm" during a health check, the server will record this information, and when the user accesses the system on January 2nd, it will recommend "a balanced diet centered on vegetables," "30-minute walks three times a week," and "24-hour fasting once a month." It will also present the latest health check result as "good health."

[0224] Prompt Sentence Examples

[0225] Q: What was the last thing you ate?

[0226] How to register your meal information:

[0227] Scan the barcode with your camera or say, "I had oatmeal and fruit."

[0228] In this way, the system aims to enable users to efficiently manage their health and reduce medical costs by inputting their health information on a daily basis and receiving recommendations for appropriate health care.

[0229] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0230] Step 1:

[0231] Users can input meal information using their smartphones or smart glasses. For example, they can scan the barcode of a food item with their smartphone camera and input that they had "oatmeal and fruit for breakfast." This information is then sent to the device.

[0232] Input: Meal information (e.g., "oatmeal and fruit")

[0233] Output: Meal data (e.g., {"meal": "oatmeal and fruit"})

[0234] Step 2:

[0235] The device sends the entered meal information to the server. The device sends the meal data to the server's API endpoint, and the server receives the data and stores it in a database (e.g., Firebase, Google Cloud Firestore).

[0236] Input: Sending food data from device to server

[0237] Output: Meal data stored in the server database (e.g. {"meal": "oatmeal and fruit"})

[0238] Step 3:

[0239] The smartwatch automatically detects and records the exercise the user performs. For example, if you jog for 30 minutes, the smartwatch records that data. The smartwatch then transfers this data to your smartphone via Bluetooth.

[0240] Input: User's exercise data (e.g., {"activity": "jogging", "duration": 30})

[0241] Output: Exercise data transferred to a smartphone

[0242] Step 4:

[0243] The smartphone sends the received exercise data to a server, which receives the data and stores it in a database.

[0244] Input: Exercise data sent from smartphone to server

[0245] Output: Exercise data stored in the server database (e.g. {"activity": "jogging", "duration": 30})

[0246] Step 5:

[0247] The user enters health check information through the app. For example, "weight 65 kg, blood pressure 120 / 80 mmHg, heart rate 70 bpm." The device (smartphone) then sends this information to the server.

[0248] Input: Health check information (e.g., {"weight": 65, "blood_pressure": "120 / 80", "heart_rate": 70})

[0249] Output: Health data sent to the server

[0250] Step 6:

[0251] After receiving the health check information, the server stores it in a database, which is used for analysis.

[0252] Input: Request to save health check information

[0253] Output: Health data stored in a database

[0254] Step 7:

[0255] The server analyzes the collected dietary, exercise, and health check information using machine learning algorithms (e.g., TensorFlow). The server finds correlations between each piece of data and generates optimal diet, exercise, and fasting recommendations for the user. For example, it may generate recommendations such as "a balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month."

[0256] Input: Various health data stored in the database

[0257] Output: Recommendation (e.g., {"diet_recommendation": "Balanced, plant-based diet", "exercise_recommendation": "30-minute walks three times a week", "fasting_recommendation": "24-hour fast once a month"})

[0258] Step 8:

[0259] The device (smartphone, smart glasses, etc.) notifies the user of the generated recommendation content, for example, by displaying it on the smart glasses' HUD (heads-up display) or via a pop-up notification on the smartphone.

[0260] Input: Recommendation

[0261] Output: Notification to the user (e.g. smartphone notification, smart glasses display)

[0262] Step 9:

[0263] The server evaluates the user's latest health status based on the recorded health check information and presents the results to the user. For example, it may notify the user that their health status is good. Furthermore, if a health check has not been recorded, it may notify the user that they need to take a health check again.

[0264] Input: Health check data

[0265] Output: Health status notification to user (e.g. "Your health is good"), reminders when a health check is needed

[0266] Through the above steps, the system can comprehensively collect and analyze the user's health care information and provide recommendations for optimal health care.

[0267] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0268] The system of the present invention aims to help users manage their own health and reduce medical costs. In addition to dietary information, exercise information, and health check information, the system records the user's emotional information and can adapt the recommendations based on that information.

[0269] 1. Recording your dietary information

[0270] The user inputs the details of the meal they had into the device. For example, if they had "oatmeal and fruit for breakfast," they input that information. The device then sends this data to the server. The server stores the received meal information in a database. This information will be used to analyze the user's eating patterns in the future.

[0271] 2. Recording exercise information

[0272] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information. The device then sends this data to the server. The server stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[0273] 3. Recording health check information

[0274] The user inputs the results of the health check into the terminal. For example, the user may input the result "my health condition is good." The terminal then sends this data to the server. The server stores the received health check information in a database. This information is used to evaluate the user's health condition.

[0275] 4. Recording emotional information

[0276] The user automatically recognizes their current emotional state through the emotion engine. For example, if the user is feeling stressed, the emotion engine recognizes and records that information. The device then sends this data to a server, which stores the received emotional information in a database. This information is used to analyze the user's emotional tendencies.

[0277] 5. Diet, exercise, and fasting recommendations

[0278] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary information, exercise information, health check information, and emotional information. For example, based on the user's data, it may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." If the user is feeling stressed, it may recommend "foods that have a relaxing effect." The device then displays these recommendations to the user.

[0279] 6. Health Status Generation

[0280] The server generates the user's latest health status based on the recorded health check information and emotional information. For example, if the result of the most recent health check is "good health," the server presents that result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays the notification to the user.

[0281] Specific examples

[0282] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records that their health is "good," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that the user is "in good health" based on the results of the most recent health check.

[0283] In this way, users can input information into the system on a daily basis, collect emotional information through the emotion engine, and receive appropriate health care recommendations from the server based on this information, thereby maintaining their health and reducing medical costs. This system allows users to effectively manage both their health and emotional states.

[0284] The processing flow will be explained below.

[0285] Program processing steps

[0286] 1. Recording your dietary information

[0287] Step 1:

[0288] User: Eats "oatmeal and fruit" for breakfast, then enters the meal details into the device.

[0289] Step 2:

[0290] User: Enters "oatmeal and fruit" into the device's input form and presses the submit button.

[0291] Step 3:

[0292] Terminal: Sends the meal details entered by the user to the server.

[0293] Step 4:

[0294] Server: Save the received meal information in the "meals" list. This list is stored in the form of a dictionary of dates and meal information.

[0295] Step 5:

[0296] Server: Confirms that the meal record was saved successfully and sends a confirmation message to the user.

[0297] 2. Recording exercise information

[0298] Step 1:

[0299] User: Goes for a 30-minute jog, then enters the details of the exercise into the device.

[0300] Step 2:

[0301] User: Enter "30 minutes of jogging" into the device's input form and press the send button.

[0302] Step 3:

[0303] Terminal: Sends the exercise information entered by the user to the server.

[0304] Step 4:

[0305] Server: Saves the received exercise details in the "exercises" list. This list is stored in the form of a dictionary of dates and exercise details.

[0306] Step 5:

[0307] Server: Confirms that the exercise record was saved successfully and sends a confirmation message to the user.

[0308] 3. Recording health check information

[0309] Step 1:

[0310] User: Takes a health check and enters the result "I am in good health" into the terminal.

[0311] Step 2:

[0312] User: Enters "My health is good" into the input form on the device and presses the send button.

[0313] Step 3:

[0314] Terminal: Sends the health check information entered by the user to the server.

[0315] Step 4:

[0316] Server: Save the received health check information in the "health_checks" list. This list is stored in the form of a dictionary of dates and health information.

[0317] Step 5:

[0318] Server: Confirm that the health check record was saved successfully and send a confirmation message to the user.

[0319] 4. Recording emotional information

[0320] Step 1:

[0321] Emotion engine: The system automatically recognizes emotions without the user having to input their current emotional state. For example, the emotion engine recognizes that the user is feeling stressed.

[0322] Step 2:

[0323] Terminal: The emotion engine sends the recognized emotion information to the server.

[0324] Step 3:

[0325] Server: Save the received emotion information in the "emotions" list. This list is stored in the form of a dictionary of dates and emotion information.

[0326] Step 4:

[0327] Server: Checks that the emotion recording was saved successfully and sends a confirmation message to the user.

[0328] 5. Dietary Recommendations

[0329] Step 1:

[0330] User: Requests food recommendations from the server via the device.

[0331] Step 2:

[0332] Server: Receives the request and executes the meal recommendation logic based on the stored meal information.

[0333] Step 3:

[0334] Server: Generate the recommendation "balanced vegetable-based meal."

[0335] Step 4:

[0336] Server: We also consider "foods that have a relaxing effect" (e.g., chamomile tea) based on emotional information.

[0337] Step 5:

[0338] Server: Sends recommendations to the user.

[0339] Step 6:

[0340] Device: Displays meal recommendations to the user.

[0341] 6. Exercise Recommendations

[0342] Step 1:

[0343] User: Requests exercise recommendations from the server via the device.

[0344] Step 2:

[0345] Server: Receives the request and executes the exercise recommendation logic based on the stored exercise information.

[0346] Step 3:

[0347] Server: Generate the recommendation "Take a 30-minute walk three times a week."

[0348] Step 4:

[0349] Server: We also consider "stress reduction exercise" (e.g., yoga) based on emotional information.

[0350] Step 5:

[0351] Server: Sends recommendations to the user.

[0352] Step 6:

[0353] Device: Display exercise recommendations to the user.

[0354] 7. Fasting Recommendations

[0355] Step 1:

[0356] User: Requests fasting recommendations from the server via the device.

[0357] Step 2:

[0358] Server: Receives the request and executes the fasting recommendation logic.

[0359] Step 3:

[0360] Server: Generate the recommendation "24-hour fast once a month."

[0361] Step 4:

[0362] Server: Sends recommendations to the user.

[0363] Step 5:

[0364] Device: Display fasting recommendations to the user.

[0365] 8. Health Status Generation

[0366] Step 1:

[0367] User: Requests the server to generate a health status via the terminal.

[0368] Step 2:

[0369] Server: Receives the request and executes the logic for generating the user's health status based on the stored health check information and emotion information.

[0370] Step 3:

[0371] Server: Generates a health status of "good health" based on the latest health check results.

[0372] Step 4:

[0373] Server: Sends the generated health status to the user.

[0374] Step 5:

[0375] Terminal: Display health status to the user.

[0376] Example 2

[0377] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0378] Conventional health management systems have had problems in that it is difficult for users to comprehensively manage their own health status, and they are unable to quickly obtain appropriate advice based on new health status or emotional information. Furthermore, they lack an approach that takes into account the impact of stress and emotional changes on health, making it impossible to provide optimal health management for individual users.

[0379] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0380] In this invention, the server includes means for recording dietary information input by the user, means for recording exercise information input by the user, means for recording health check information input by the user, means for automatically recognizing and recording emotional information, means for recommending diet, exercise, and fasting based on the recorded dietary information, exercise information, health check information, and emotional information, and means for generating the user's health status based on the recorded health check information and emotional information. This allows the user to comprehensively manage both their health status and emotional state, and to receive appropriate health management advice in a timely manner.

[0381] A "user" is an individual who uses the health management system to record their own dietary information, exercise information, health check information, and emotional information.

[0382] A "server" is a processing device for receiving, storing, analyzing, and providing recommendations and notifications for data sent by users.

[0383] "Terminal" refers to a device that allows a user to input information about their diet, exercise, health checks, and emotions. Specifically, this refers to a smartphone or PC.

[0384] "Dietary information" is data related to meals consumed by a user, including the contents of meals at a specific point in time.

[0385] "Exercise information" is data related to the exercise performed by the user, including the specific exercise content and exercise time.

[0386] "Health check information" is data relating to the results of a health status evaluation that a user periodically performs.

[0387] "Emotion information" is data that indicates the user's emotional state, and is automatically recognized and recorded using an emotion engine or the like.

[0388] An "emotion engine" is software or hardware that analyzes the user's emotional state and outputs the results as data.

[0389] "Recommendations" are health care advice or instructions generated by the server based on the user's recorded data.

[0390] A "generative AI model" is an artificial intelligence algorithm used by the server to analyze collected data and make optimal recommendations to users.

[0391] A "prompt sentence" is a sentence indicating an instruction or question that the system asks the user.

[0392] The system of the present invention aims to enable users to manage their own health and reduce medical costs. This system records the user's dietary information, exercise information, health check information, and emotional information, and makes appropriate recommendations based on this information. Specific embodiments of the system are described below.

[0393] Recording food information

[0394] The user inputs the details of the meal they have eaten into the device. For example, they input "oatmeal and fruit for breakfast." The device sends this data to the server as an HTTP request. The server analyzes the received meal information and saves the "date, meal details, and user ID" in a database using SQL statements. This information is used to analyze the user's eating patterns.

[0395] Recording exercise information

[0396] The user enters the details of the exercise they performed into the device. For example, they enter "30 minutes of jogging." The device then sends the exercise information to the server as an HTTP request. The server analyzes the received exercise information and uses SQL statements to store the "date, exercise details, and user ID" in a database. This information is used to analyze the user's exercise habits.

[0397] Recording health check information

[0398] The user enters the results of their health check into the terminal. For example, they enter "My health condition is good." The terminal sends the health check information to the server as an HTTP request. The server analyzes the received health check information and uses SQL statements to store the "date, health check details, and user ID" in a database. This information is used to evaluate the user's health condition.

[0399] Recording emotional information

[0400] The user uses the emotion engine to automatically recognize their current emotional state. For example, if the user is feeling stressed, the emotion engine will recognize and record that information. The device then sends the emotional information to the server as an HTTP request. The server then analyzes the received emotional information and uses SQL statements to store the date, emotional state, and user ID in a database. This information is then used to analyze the user's emotional tendencies.

[0401] Diet, exercise, and fasting recommendations

[0402] The server references the dietary information, exercise information, health check information, and emotional information in the database, and integrates and analyzes them. The server uses the generative AI model to recommend optimal diet, exercise, and fasting for the user. For example, it might recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." If the user is feeling stressed, it might also recommend "foods with a relaxing effect (e.g., chamomile tea)." The generated recommendations are sent to the device, which displays them to the user.

[0403] Health state generation

[0404] The server generates the user's current health status based on the recorded health check information and emotional information. For example, if the result of a recent health check is "good health," the server notifies the user of that result. If no record exists, the server notifies the user that a health check is necessary. The terminal displays these notifications to the user.

[0405] Specific example explanation

[0406] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records that their health is "good," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that the user is "in good health" based on the results of the most recent health check.

[0407] In this way, users can input information into the system on a daily basis, and by collecting emotional information through the emotion engine, the server can recommend appropriate health care. This system allows users to effectively manage both their health and emotional states.

[0408] Prompt Sentence Examples

[0409] 1. "What did you eat today? Example: Oatmeal and fruit for breakfast."

[0410] 2. "Please enter the exercise you did today. Example: 30 minutes of jogging."

[0411] 3. "Please enter the results of your most recent health check. Example: I am in good health."

[0412] 4. Check the emotion engine results. Example: Stress state.

[0413] 5. "Would you like to see today's food and exercise recommendations?"

[0414] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0415] Step 1: Enter your meal information

[0416] The user inputs the details of the meal they have eaten into the terminal, for example, "oatmeal and fruit for breakfast."

[0417] Input: Meal details (e.g., "Oatmeal and fruit for breakfast")

[0418] Output: HTTP request sent to the terminal

[0419] Step 2: Submit your meal information

[0420] The device generates an HTTP request to send the input meal information to the server. The HTTP request includes the meal details, date and time, and the user ID.

[0421] Input: Meal information (e.g., "Oatmeal and fruit for breakfast"), date and time, user ID

[0422] Output: HTTP request sent to the server

[0423] Step 3: Save your meal information

[0424] The server stores the received meal information in a database. The server first analyzes the HTTP request and extracts the data. Then it generates an SQL statement and inserts the "date, meal content, and user ID" into the database.

[0425] Input: HTTP request (meal information, date and time, user ID)

[0426] Output: Save results to database

[0427] Step 4: Enter your exercise information

[0428] The user inputs the details of the exercise he or she has done into the terminal. For example, the user inputs "30 minutes of jogging."

[0429] Input: Exercise content (e.g., "30 minutes of jogging")

[0430] Output: HTTP request sent to the terminal

[0431] Step 5: Sending exercise information

[0432] The device generates an HTTP request to send the input exercise information to the server. The HTTP request includes the exercise details, date and time, and the user ID.

[0433] Input: Exercise information (e.g., "30 minutes of jogging"), date and time, user ID

[0434] Output: HTTP request sent to the server

[0435] Step 6: Save your exercise information

[0436] The server stores the received exercise information in a database. It analyzes the HTTP request, extracts the necessary data, and then generates an SQL statement to insert the "date, exercise content, and user ID" into the database.

[0437] Input: HTTP request (exercise information, date and time, user ID)

[0438] Output: Save results to database

[0439] Step 7: Enter your health check information

[0440] The user inputs the results of the health check into the terminal. For example, the user inputs "my health is good."

[0441] Input: Health check details (e.g. "I am in good health")

[0442] Output: HTTP request sent to the terminal

[0443] Step 8: Submit your health check information

[0444] The terminal generates an HTTP request to send the entered health check information to the server. The HTTP request includes the health check details, date and time, and user ID.

[0445] Input: Health check information (e.g., "My health is good"), date and time, user ID

[0446] Output: HTTP request sent to the server

[0447] Step 9: Save your health check information

[0448] The server saves the received health check information in a database. It analyzes the HTTP request, extracts the necessary data, and then generates an SQL statement to insert the date, health check details, and user ID into the database.

[0449] Input: HTTP request (health check information, date and time, user ID)

[0450] Output: Save results to database

[0451] Step 10: Recognizing Emotional Information

[0452] The user automatically recognizes their current emotional state using the emotion engine, which uses biometric sensors and other input devices to analyze the user's emotional state.

[0453] Input: Data from biometric sensors (e.g., heart rate, facial expression)

[0454] Output: Perceived emotional state (e.g., "stressed")

[0455] Step 11: Sending Emotional Information

[0456] The device generates an HTTP request to send the recognized emotion information to the server, which includes the emotional state, the date and time, and the user ID.

[0457] Input: Emotion information (e.g., "stress state"), date and time, user ID

[0458] Output: HTTP request sent to the server

[0459] Step 12: Storing Emotional Information

[0460] The server stores the received emotional information in a database by parsing the HTTP request, extracting the emotional state, and then inserting the date, emotional state, and user ID into the database using an SQL statement.

[0461] Input: HTTP request (emotion information, date and time, user ID)

[0462] Output: Save results to database

[0463] Step 13: Generate recommendations

[0464] The server integrates and analyzes the dietary, exercise, health check, and emotional information stored in the database, and uses a generative AI model to generate optimal diet, exercise, and fasting recommendations for the user.

[0465] Input: Various information in the database (diet, exercise, health check, emotions)

[0466] Output: Recommendation (e.g., "Eat a balanced diet centered on vegetables," "Take a 30-minute walk three times a week," "Fast for 24 hours once a month")

[0467] Step 14: Submit and view your recommendation

[0468] The server sends the generated recommendations to the terminal, which then displays them to the user.

[0469] Input: Generated recommendation

[0470] Output: Recommendation to be displayed to the user (e.g., "Eat a balanced diet centered around vegetables")

[0471] Step 15: Generate Health States

[0472] The server generates the current health status of the user based on the recorded health check information and emotional information.

[0473] Input: Health check information and emotion information in the database

[0474] Output: The generated health status (e.g. "Your health is good")

[0475] Step 16: Health Status Notification

[0476] The server sends the generated health status to the terminal, which displays it to the user. If the user's health check information is not recorded, the terminal notifies the user that a health check is required.

[0477] Input: Current health status or notification of missing check

[0478] Output: Health status information or notification displayed to the user (e.g., "Your health is good," "Please take a health check")

[0479] (Application example 2)

[0480] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0481] Conventional health management systems provide simple recommendations based only on dietary information, exercise information, and health check information. However, because they do not take the user's emotional state into account, they are insufficient for maintaining a consistent health status or managing stress. Furthermore, health management content is not personalized, failing to meet the needs of individual users. The present invention aims to solve these problems and provide personalized health management and wellness content tailored to the user's emotional state.

[0482] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0483] In this invention, the server includes means for recording dietary information input by a user, means for recording exercise information input by a user, means for recording health check information and emotional information input by a user, means for recommending diet, exercise, and fasting based on the recorded dietary information, exercise information, health check information, and emotional information, means for generating a user's health status based on the recorded health check information and emotional information, means for notifying the user that a health check is necessary if a health status has not been recorded, means for providing health management content to the user based on the recorded emotional information, and means for transmitting the dietary information, exercise information, health check information, and emotional information input by the user to the server. This enables personalized health management and stress management while taking the user's emotional state into consideration.

[0484] Creating definition statements

[0485] "User" means an individual who utilizes the system to record dietary information, exercise information, health check information, and emotional information, and who interacts with the system to receive health management and wellness content.

[0486] "Input" refers to the act of a user providing dietary information, exercise information, health check information, and emotional information to the system via an interface such as a keyboard or voice input.

[0487] "Dietary information" refers to data relating to the content and quantity of food consumed by the user.

[0488] "Exercise information" refers to data regarding the type, duration, and intensity of exercise performed by the user.

[0489] "Health check information" refers to data on the user's blood pressure, weight, body temperature, and other measurement and diagnosis results related to their health condition.

[0490] "Emotion information" refers to data relating to the user's emotional state, such as stress or relaxation.

[0491] "Recording" refers to the act of saving information entered by a user within a system or on a server.

[0492] "Recommendations" means suggestions and advice regarding diet, exercise, and fasting that the system provides to the user based on the recorded information.

[0493] "Generation" refers to the act of the system analyzing the recorded information and creating the user's latest health status and appropriate health management content.

[0494] "Notification" refers to the act of a system sending a message or alert to a user under certain conditions.

[0495] "Health Management Content" refers to personalized advice and information provided based on a user's health and emotional state.

[0496] A "server" is a computing device that receives and stores user-entered data and makes recommendations and analyses based on the recorded information.

[0497] MODE FOR CARRYING OUT THE INVENTION

[0498] A system for implementing the present invention aims to enable a user to manage their health status and provide personalized health management content. This system is implemented using a device such as a smartphone, smart glasses, or a head-mounted display. The configuration and operation of the system are described below.

[0499] 1. Recording your dietary information

[0500] The user inputs the details of the meal they ate into the device. For example, if they had "oatmeal and fruit" for breakfast, they input that information into the device. The device then sends this meal information to the server, which stores the received data in a database. This information is used to analyze future eating patterns.

[0501] 2. Recording exercise information

[0502] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information into the device. The device then sends this exercise information to the server. The server then stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[0503] 3. Recording health check information

[0504] The user inputs the results of the health check into the terminal. For example, if the user's health condition is evaluated as "good," the user inputs the result into the terminal. The terminal then sends this health check information to the server. The server stores the received information in a database and uses it to evaluate the user's health condition.

[0505] 4. Recording emotional information

[0506] The user uses the emotion engine to automatically recognize and record their current emotional state. For example, if the user is feeling stressed, the emotion engine will recognize and record that state. The device then sends the emotional information to the server, which stores the received emotional information in a database. This information is used to analyze the user's emotional tendencies.

[0507] 5. Diet, exercise, and fasting recommendations

[0508] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary information, exercise information, health check information, and emotional information. For example, based on the user's data, recommendations such as "a balanced diet centered on vegetables" and "a 30-minute walk three times a week" may be made. Also, if the user is feeling stressed, recommendations such as "eating foods with a relaxing effect (chamomile tea)" may be made. This allows the user to consistently maintain their health.

[0509] 6. Health Status Generation

[0510] The server generates the user's latest health status based on the recorded health check information and emotional information. For example, if the result of the most recent health check is "good health," the server presents this result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays this notification to the user.

[0511] Hardware and software used

[0512] Hardware: Devices such as smartphones, smart glasses, and head-mounted displays

[0513] Software: Python program, emotion engine, cloud server, database

[0514] Specific examples

[0515] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records "good health," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that "good health" based on the results of the most recent health check.

[0516] Prompt Sentence Examples

[0517] User profile: "Diet information: oatmeal and fruit", "Exercise information: 30 minutes of jogging", "Health check information: good health", "Emotion information: stressed"

[0518] Based on this information, generate recommendations for appropriate diet, exercise, and relaxation methods and display them in your "Wellness Concierge."

[0519] In this way, users can input information using the system on a daily basis, collect emotional information through the emotion engine, and receive appropriate health care recommendations from the server based on this information, thereby maintaining their health and reducing medical costs.

[0520] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0521] Program processing steps

[0522] Step 1:

[0523] Enter and submit meal information

[0524] The user uses the device to input the details of the meal they have eaten. Specifically, if the user had "oatmeal and fruit" for breakfast, they enter that information into the application. The device converts the input meal information into a data format and sends it to the cloud server. The server stores the received data in a database.

[0525] Input: Meal information entered by the user

[0526] Data processing: The device converts the meal information into data format and sends it to the server.

[0527] Output: Meal information stored on the cloud server

[0528] Step 2:

[0529] Enter and submit exercise information

[0530] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information. The device converts the exercise information into a data format and sends it to the cloud server. The server stores the received exercise information in a database.

[0531] Input: Exercise information entered by the user

[0532] Data processing and calculation: The device converts the motion information into data format and sends it to the server.

[0533] Output: Exercise information stored on a cloud server

[0534] Step 3:

[0535] Enter and submit health check information

[0536] The user inputs the results of the health check into the device. For example, if the user's health condition is evaluated as "good," the user inputs the result. The device converts the health check information into a data format and sends it to the cloud server. The server stores the received health check information in a database.

[0537] Input: Health check information entered by the user

[0538] Data processing: The terminal converts the health check information into data format and sends it to the server.

[0539] Output: Health check information stored on the cloud server

[0540] Step 4:

[0541] Recording and transmitting emotional information

[0542] The user uses the emotion engine to automatically recognize their current emotional state. For example, if the user is feeling stressed, the emotion engine will recognize and record that state. The device then converts this emotional information into a data format and sends it to a cloud server. The server then stores the received emotional information in a database.

[0543] Input: Emotion information generated by the emotion engine

[0544] Data processing operation: The device converts the emotional information into data format and sends it to the server.

[0545] Output: Emotion information stored on the cloud server

[0546] Step 5:

[0547] Recommendation generation

[0548] The server makes recommendations for appropriate diet, exercise, and fasting to the user based on the recorded dietary information, exercise information, health check information, and emotional information. For example, recommendations such as "a balanced diet centered on vegetables" and "a 30-minute walk three times a week" may be made based on the user's data. Furthermore, if the user is feeling stressed, recommendations may include information such as "foods with a relaxing effect (e.g., chamomile tea)."

[0549] Input: Diet, exercise, health check, and emotional information stored in the database

[0550] Data processing: The server analyzes this information and generates appropriate recommendations for the user.

[0551] Output: Generated recommendations

[0552] Step 6:

[0553] Health status generation and notification

[0554] The server generates the user's latest health status based on the recorded health check information and emotional information. For example, if the result of the most recent health check is "good health," the server presents this result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays this notification to the user.

[0555] Input: Health check information and emotional information stored in the database

[0556] Data processing and calculation: The server analyzes this information and generates and notifies the user of their health status.

[0557] Output: Notifications and reminders of the user's health status

[0558] In this way, the system can provide appropriate health management and wellness content based on the user's input information.

[0559] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0560] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0561] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0562] [Second embodiment]

[0563] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0564] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0565] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0566] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0567] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0568] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0569] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0570] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0571] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0572] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0573] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0574] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0575] The system of the present invention aims to help users manage their own health and reduce medical costs. This system records dietary information, exercise information, and health check information entered by users, and based on this, makes recommendations for diet, exercise, and fasting, and generates the user's health status.

[0576] 1. Recording your dietary information

[0577] The user inputs the details of the meal they had into the device. For example, if they had "oatmeal and fruit for breakfast," they input that information. The device then sends this data to the server. The server stores the received meal information in a database. This information will be used to analyze the user's eating patterns in the future.

[0578] 2. Recording exercise information

[0579] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information. The device then sends this data to the server. The server stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[0580] 3. Recording health check information

[0581] The user inputs the results of the health check into the terminal. For example, the user may input the result "my health condition is good." The terminal then sends this data to the server. The server stores the received health check information in a database. This information is used to evaluate the user's health condition.

[0582] 4. Diet, exercise, and fasting recommendations

[0583] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary, exercise, and health check information. For example, based on the user's data, it may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." The device then displays these recommendations to the user.

[0584] 5. Health Status Generation

[0585] The server generates the user's latest health status based on the recorded health check information. For example, if the result of the most recent health check is "good health," the server presents that result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays the notification to the user.

[0586] Specific examples

[0587] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, the user underwent a health check and recorded as being in "good health." The server records this information, and when the user accesses the system on January 2nd, it recommends "a balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month." It also presents the information that "the user is in good health" based on the results of the most recent health check.

[0588] In this way, users can maintain their health and reduce medical expenses by inputting information into the system on a daily basis and receiving appropriate health care recommendations from the server via their terminal.

[0589] The processing flow will be explained below.

[0590] Program processing steps

[0591] 1. Recording your dietary information

[0592] Step 1:

[0593] User: Eats "oatmeal and fruit" for breakfast, then enters the meal details into the device.

[0594] Step 2:

[0595] User: Enters "oatmeal and fruit" into the device's input form and presses the submit button.

[0596] Step 3:

[0597] Terminal: Sends the meal details entered by the user to the server.

[0598] Step 4:

[0599] Server: Save the received meal information in the "meals" list. This list is stored in the form of a dictionary of dates and meal information.

[0600] Step 5:

[0601] Server: Confirms that the meal record was saved successfully and sends a confirmation message to the user.

[0602] 2. Recording exercise information

[0603] Step 1:

[0604] User: Goes for a 30-minute jog, then enters the details of the exercise into the device.

[0605] Step 2:

[0606] User: Enter "30 minutes of jogging" into the device's input form and press the send button.

[0607] Step 3:

[0608] Terminal: Sends the exercise information entered by the user to the server.

[0609] Step 4:

[0610] Server: Saves the received exercise details in the "exercises" list. This list is stored in the form of a dictionary of dates and exercise details.

[0611] Step 5:

[0612] Server: Confirms that the exercise record was saved successfully and sends a confirmation message to the user.

[0613] 3. Recording health check information

[0614] Step 1:

[0615] User: Takes a health check and enters the result "I am in good health" into the terminal.

[0616] Step 2:

[0617] User: Enters "My health is good" into the input form on the device and presses the send button.

[0618] Step 3:

[0619] Terminal: Sends the health check information entered by the user to the server.

[0620] Step 4:

[0621] Server: Save the received health check information in the "health_checks" list. This list is stored in the form of a dictionary of dates and health information.

[0622] Step 5:

[0623] Server: Confirm that the health check record was saved successfully and send a confirmation message to the user.

[0624] 4. Dietary Recommendations

[0625] Step 1:

[0626] User: Requests food recommendations from the server via the device.

[0627] Step 2:

[0628] Server: Receives the request and executes the meal recommendation logic based on the stored meal information.

[0629] Step 3:

[0630] Server: Generate the recommendation "balanced vegetable-based meal."

[0631] Step 4:

[0632] Server: Sends recommendations to the user.

[0633] Step 5:

[0634] Device: Displays meal recommendations to the user.

[0635] 5. Exercise Recommendations

[0636] Step 1:

[0637] User: Requests exercise recommendations from the server via the device.

[0638] Step 2:

[0639] Server: Receives the request and executes the exercise recommendation logic based on the stored exercise information.

[0640] Step 3:

[0641] Server: Generate the recommendation "Take a 30-minute walk three times a week."

[0642] Step 4:

[0643] Server: Sends recommendations to the user.

[0644] Step 5:

[0645] Device: Display exercise recommendations to the user.

[0646] 6. Fasting recommendations

[0647] Step 1:

[0648] User: Requests fasting recommendations from the server via the device.

[0649] Step 2:

[0650] Server: Receives the request and executes the fasting recommendation logic.

[0651] Step 3:

[0652] Server: Generate the recommendation "24-hour fast once a month."

[0653] Step 4:

[0654] Server: Sends recommendations to the user.

[0655] Step 5:

[0656] Device: Display fasting recommendations to the user.

[0657] 7. Health Status Generation

[0658] Step 1:

[0659] User: Requests the server to generate a health status via the terminal.

[0660] Step 2:

[0661] Server: Receives the request and executes the logic to generate the user's health status based on the stored health check information.

[0662] Step 3:

[0663] Server: Generates a health status of "good health" based on the latest health check results.

[0664] Step 4:

[0665] Server: Sends the generated health status to the user.

[0666] Step 5:

[0667] Terminal: Display health status to the user.

[0668] Example 1

[0669] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0670] In modern society, individual health management and rising medical costs are becoming serious issues. Current health management systems allow users to input and track their own health data, but they lack effective utilization and optimal health management recommendations. The data entered by users is stored fragmentedly, preventing unified health management advice, making it difficult to improve users' health. Furthermore, users may not receive notifications even if appropriate health checks are not performed, which increases the risk of users neglecting to check their health.

[0671] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0672] In this invention, the server includes a means for recording dietary information entered by the user, a means for recording exercise information entered by the user, a means for recording health check information entered by the user, a means for storing the recorded dietary information, exercise information, and health check information in a database, a means for making diet, exercise, and fasting recommendations using a machine learning algorithm based on the recorded dietary information, exercise information, and health check information, a means for notifying the terminal of the recommendations, and a means for generating the user's health status based on the recorded health check information. This makes it possible to centrally manage health-related data entered by the user and provide optimal health management recommendations using a machine learning algorithm. Furthermore, by providing a notification even if a health check has not been performed, the server can encourage the user to perform a health check.

[0673] "User" refers to an individual who uses the system and is the entity that inputs data such as dietary information, exercise information, and health check information.

[0674] "Terminal" refers to an electronic device used to send data entered by a user to a server, including smartphones and tablets.

[0675] "Dietary information" refers to data relating to the types and amounts of food consumed by the user, and is information for recording the user's nutritional intake status.

[0676] "Exercise information" refers to data relating to the type and duration of exercise performed by the user, and is information for recording the user's exercise status.

[0677] "Health check information" refers to data such as diagnostic results and self-assessment regarding the user's health condition, and is information for evaluating the user's health condition.

[0678] "Server" refers to a centralized computer system that receives, processes, and stores data submitted by users, including databases and analytical algorithms.

[0679] A "database" refers to a digital archive for storing a user's dietary information, exercise information, health check information, etc. in a structured manner, making it easy to search and manage information.

[0680] A "machine learning algorithm" refers to a computational method for discovering patterns based on accumulated data and making predictions and recommendations, and is used in data analysis and building predictive models.

[0681] "Recommendations" refers to health management advice and suggestions for users generated by machine learning algorithms, including diet, exercise, fasting, etc.

[0682] "Notification means" refers to methods for informing users of information such as recommendations and the need for health checks, and includes push notifications and dashboard displays.

[0683] The system of the present invention aims to enable users to manage their own health and reduce medical costs. This system records dietary information, exercise information, and health check information entered by the user, and based on this information, makes recommendations for diet, exercise, and fasting, thereby generating a health status report for the user. Specific embodiments of this system are described below.

[0684] System Configuration

[0685] User

[0686] Users access the system using devices such as smartphones and tablets, which have a dedicated health management app installed.

[0687] Terminal

[0688] The device accepts information about meals, exercise, and health checks entered by the user. This information is converted into JSON format and sent to the server using the HTTPS protocol.

[0689] The device is responsible for displaying recommendations and health check notifications to the user. It uses a push notification service (e.g., Firebase Cloud Messaging) to notify the user.

[0690] server

[0691] The server is built using a cloud service (e.g., a general cloud computing platform). The server has the following roles:

[0692] 1. Data reception: Receives meal information, exercise information, and health check information sent by users. This is done using an API using the Flask framework.

[0693] 2. Data storage: The received data is stored in a MySQL database. The database is divided into a "meal information table," a "exercise information table," and a "health check information table."

[0694] 3. Data analysis: Periodically, a scheduler (e.g., cron job) is used to analyze the recorded data using machine learning algorithms (e.g., Scikit-learn), which then generates appropriate diet, exercise, and fasting recommendations for the user.

[0695] 4. Health Status Generation: Generates the latest health status based on the recorded health check information. If necessary, notifies the user that a health check is required.

[0696] Specific examples

[0697] For example, if a user eats "oatmeal and fruit" for breakfast on January 1st, goes "30 minutes jogging" on the same day, and records a health check as "good health," the server records this information, and when the user accesses the system on January 2nd, it provides the following recommendations:

[0698] A balanced diet centered around vegetables

[0699] 30-minute walks three times a week

[0700] 24-hour fasting once a month

[0701] It also displays "good health" based on the results of the most recent health check. In this way, users can input information into the system on a daily basis and receive appropriate health management recommendations from the server via their terminal, thereby maintaining their health and reducing medical costs.

[0702] Example of input prompt for generative AI model

[0703] "I would like to design a user interface for a health management system. Please suggest a design for a form that allows users to easily enter information about their diet, exercise, and health checks."

[0704] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0705] Step 1:

[0706] A user opens a smartphone app and inputs the details of the meal they had. For example, they input "oatmeal and fruit for breakfast." The device converts this input information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed data about the meal, and the device converts it into JSON format and sends it.

[0707] Step 2:

[0708] The server receives the meal information using an API built with the Flask framework. It parses the received data and stores it in a MySQL "meal information" table. The input is JSON-formatted meal information data, which is parsed and stored in the database.

[0709] Step 3:

[0710] The user uses the same app to input the details of the exercise they performed. For example, they input "30 minutes of jogging." The device converts this exercise information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed exercise data, which is then converted into JSON format and sent.

[0711] Step 4:

[0712] The server processes the received exercise information using the Flask API, parses the data, and saves it in the MySQL "exercise information" table. The input is exercise information data in JSON format, which is parsed and stored in the database.

[0713] Step 5:

[0714] The user enters the results of their health check into the app. For example, they might enter "My health is good." The device converts this health check information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed health check data, which is then converted into JSON format and sent.

[0715] Step 6:

[0716] The server processes the received health check information through the Flask API, parses the data, and saves it in the MySQL "health check information" table. The input is health check information data in JSON format, which is parsed and stored in the database.

[0717] Step 7:

[0718] The server periodically uses a scheduler (e.g., cron job) to perform data analysis based on the recorded dietary information, exercise information, and health check information. This process uses Python and Scikit-learn. As a result of the analysis, it generates optimal diet, exercise, and fasting recommendations for the user. The input is multiple pieces of information obtained from the database, which are then analyzed and the recommendations are output.

[0719] Step 8:

[0720] The server sends the generated recommendation to the user's device. The device uses the Firebase Cloud Messaging service to send a push notification to the user to notify them of the new recommendation. When the user taps the notification, they can view the detailed recommendation within the app. The input is the generated recommendation, and the operation to send it to the user via a push notification is performed.

[0721] Step 9:

[0722] The server generates the user's latest health status based on the periodically saved health check information. For example, if the most recent health check result is "good health," the server presents that result to the user. The input is health check information retrieved from the database, and the server evaluates it and outputs the latest health status.

[0723] Step 10:

[0724] If there is no health check record, the server uses Firebase Cloud Messaging to notify the user that a "health check is required." The device receives this notification and displays it on the app's dashboard. The input is whether or not there is a health check record, and the notification action is performed based on that.

[0725] (Application example 1)

[0726] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0727] Conventional health management systems require users to manually input information about their diet and exercise, and suffer from issues such as a lack of data accuracy and real-time performance. Furthermore, there are only limited systems that utilize accumulated data to provide effective health management recommendations. This has resulted in a lack of an optimal approach for efficiently managing users' health status and reducing medical costs.

[0728] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0729] In this invention, the server includes a means for transmitting dietary information, exercise information, and health check information manually input by the user to the server, a means for automatically recording the user's exercise data and dietary data using hardware functions such as an exercise sensor and a barcode scanner and transmitting the data to the server, a means for analyzing the data accumulated by the server using a machine learning algorithm to generate appropriate diet, exercise, and fasting recommendations for the user, and a means for notifying the user of the recommendations. This allows users to efficiently accumulate health management information by utilizing both manual input and automatic recording, and to receive optimal health management recommendations for each individual user through the machine learning algorithm.

[0730] "Dietary information" refers to data about the contents of the foods and drinks consumed by the user.

[0731] "Exercise information" refers to data regarding the type, duration, and intensity of exercise performed by the user.

[0732] "Health check information" refers to data related to the user's health condition, such as weight, blood pressure, and heart rate.

[0733] A "server" is a computer system that stores and analyzes data sent by users and provides necessary information.

[0734] "Recommendation" refers to providing optimal diet, exercise, and fasting advice based on the user's health data.

[0735] An "exercise sensor" is a device for detecting a user's exercise status, and is a device for measuring the number of steps, distance, calorie consumption, etc.

[0736] "Barcode scanning" is the act of reading the barcode of food or products and recording that information as data.

[0737] A "machine learning algorithm" is a program that analyzes the data received by the server, finds patterns, and generates optimal recommendations for users.

[0738] "Notification" refers to the act of informing the user of the generated recommendations and necessary health check information.

[0739] A "smartphone" is a multi-function mobile phone that can connect to the Internet and use applications.

[0740] "Smart glasses" are wearable devices that can provide information visually.

[0741] A "smartwatch" is a wearable device that has a built-in motion sensor and measures the user's biometric information and motion data.

[0742] The system for implementing this invention aims to record dietary information, exercise information, and health check information entered by users and provide appropriate health management recommendations. The main components of the system include devices such as smartphones, smart glasses, and smart watches, and a server that performs data analysis.

[0743] System Structure

[0744] 1. Recording your dietary information:

[0745] Users can use their smartphones or smart glasses to input meal information by scanning barcodes or by voice input. For example, they can use their smartphone's camera to scan food barcodes and input "I had oatmeal and fruit for breakfast."

[0746] The device sends the entered meal information to the server, and the server stores the received data in a database (e.g., Firebase, Google Cloud Firestore).

[0747] 2. Recording exercise information:

[0748] The smartwatch's motion sensor automatically records the user's motion data. For example, if you go for a 30-minute jog, the smartwatch will record that motion data.

[0749] The device transfers this data to a smartphone via Bluetooth, which then sends it to a server, which stores the data in a database.

[0750] 3. Recording Health Check Information:

[0751] Users enter their health check information (weight, blood pressure, heart rate, etc.) through the app. For example, if their weight is 65 kg, their blood pressure is 120 / 80 mmHg, and their heart rate is 70 bpm, they enter that information into their smartphone.

[0752] The terminal sends the input information to the server, which stores it in a database.

[0753] 4. Health Care Recommendations:

[0754] The server analyzes the collected data using machine learning algorithms (e.g., TensorFlow) to generate recommendations for diet, exercise, and fasting. For example, based on the analysis of the user's diet and exercise information, it may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month."

[0755] The device will notify the user of the recommendations, for example, by displaying them on the HUD (heads-up display) of smart glasses or via a pop-up notification on a smartphone.

[0756] 5. Health generation:

[0757] The server analyzes the user's latest health status based on the recorded health check information. For example, if the result of the most recent health check is "good health," the server presents that information to the user.

[0758] If the health status is not recorded, the server will notify the user that a health check is required.

[0759] Specific examples

[0760] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went on a "30-minute jog" on the same day. If this user also records "weight 65 kg, blood pressure 120 / 80 mmHg, heart rate 70 bpm" during a health check, the server will record this information, and when the user accesses the system on January 2nd, it will recommend "a balanced diet centered on vegetables," "30-minute walks three times a week," and "24-hour fasting once a month." It will also present the latest health check result as "good health."

[0761] Prompt Sentence Examples

[0762] Q: What was the last thing you ate?

[0763] How to register your meal information:

[0764] Scan the barcode with your camera or say, "I had oatmeal and fruit."

[0765] In this way, the system aims to enable users to efficiently manage their health and reduce medical costs by inputting their health information on a daily basis and receiving recommendations for appropriate health care.

[0766] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0767] Step 1:

[0768] Users can input meal information using their smartphones or smart glasses. For example, they can scan the barcode of a food item with their smartphone camera and input that they had "oatmeal and fruit for breakfast." This information is then sent to the device.

[0769] Input: Meal information (e.g., "oatmeal and fruit")

[0770] Output: Meal data (e.g., {"meal": "oatmeal and fruit"})

[0771] Step 2:

[0772] The device sends the entered meal information to the server. The device sends the meal data to the server's API endpoint, and the server receives the data and stores it in a database (e.g., Firebase, Google Cloud Firestore).

[0773] Input: Sending food data from device to server

[0774] Output: Meal data stored in the server database (e.g. {"meal": "oatmeal and fruit"})

[0775] Step 3:

[0776] The smartwatch automatically detects and records the exercise the user performs. For example, if you jog for 30 minutes, the smartwatch records that data. The smartwatch then transfers this data to your smartphone via Bluetooth.

[0777] Input: User's exercise data (e.g., {"activity": "jogging", "duration": 30})

[0778] Output: Exercise data transferred to a smartphone

[0779] Step 4:

[0780] The smartphone sends the received exercise data to a server, which receives the data and stores it in a database.

[0781] Input: Exercise data sent from smartphone to server

[0782] Output: Exercise data stored in the server database (e.g. {"activity": "jogging", "duration": 30})

[0783] Step 5:

[0784] The user enters health check information through the app. For example, "weight 65 kg, blood pressure 120 / 80 mmHg, heart rate 70 bpm." The device (smartphone) then sends this information to the server.

[0785] Input: Health check information (e.g., {"weight": 65, "blood_pressure": "120 / 80", "heart_rate": 70})

[0786] Output: Health data sent to the server

[0787] Step 6:

[0788] After receiving the health check information, the server stores it in a database, which is used for analysis.

[0789] Input: Request to save health check information

[0790] Output: Health data stored in a database

[0791] Step 7:

[0792] The server analyzes the collected dietary, exercise, and health check information using machine learning algorithms (e.g., TensorFlow). The server finds correlations between each piece of data and generates optimal diet, exercise, and fasting recommendations for the user. For example, it may generate recommendations such as "a balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month."

[0793] Input: Various health data stored in the database

[0794] Output: Recommendation (e.g., {"diet_recommendation": "Balanced, plant-based diet", "exercise_recommendation": "30-minute walks three times a week", "fasting_recommendation": "24-hour fast once a month"})

[0795] Step 8:

[0796] The device (smartphone, smart glasses, etc.) notifies the user of the generated recommendation content, for example, by displaying it on the smart glasses' HUD (heads-up display) or via a pop-up notification on the smartphone.

[0797] Input: Recommendation

[0798] Output: Notification to the user (e.g. smartphone notification, smart glasses display)

[0799] Step 9:

[0800] The server evaluates the user's latest health status based on the recorded health check information and presents the results to the user. For example, it may notify the user that their health status is good. Furthermore, if a health check has not been recorded, it may notify the user that they need to take a health check again.

[0801] Input: Health check data

[0802] Output: Health status notification to user (e.g. "Your health is good"), reminders when a health check is needed

[0803] Through the above steps, the system can comprehensively collect and analyze the user's health care information and provide recommendations for optimal health care.

[0804] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0805] The system of the present invention aims to help users manage their own health and reduce medical costs. In addition to dietary information, exercise information, and health check information, the system records the user's emotional information and can adapt the recommendations based on that information.

[0806] 1. Recording your dietary information

[0807] The user inputs the details of the meal they had into the device. For example, if they had "oatmeal and fruit for breakfast," they input that information. The device then sends this data to the server. The server stores the received meal information in a database. This information will be used to analyze the user's eating patterns in the future.

[0808] 2. Recording exercise information

[0809] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information. The device then sends this data to the server. The server stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[0810] 3. Recording health check information

[0811] The user inputs the results of the health check into the terminal. For example, the user may input the result "my health condition is good." The terminal then sends this data to the server. The server stores the received health check information in a database. This information is used to evaluate the user's health condition.

[0812] 4. Recording emotional information

[0813] The user automatically recognizes their current emotional state through the emotion engine. For example, if the user is feeling stressed, the emotion engine recognizes and records that information. The device then sends this data to a server, which stores the received emotional information in a database. This information is used to analyze the user's emotional tendencies.

[0814] 5. Diet, exercise, and fasting recommendations

[0815] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary information, exercise information, health check information, and emotional information. For example, based on the user's data, it may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." If the user is feeling stressed, it may recommend "foods that have a relaxing effect." The device then displays these recommendations to the user.

[0816] 6. Health Status Generation

[0817] The server generates the user's latest health status based on the recorded health check information and emotional information. For example, if the result of the most recent health check is "good health," the server presents that result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays the notification to the user.

[0818] Specific examples

[0819] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records that their health is "good," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that the user is "in good health" based on the results of the most recent health check.

[0820] In this way, users can input information into the system on a daily basis, collect emotional information through the emotion engine, and receive appropriate health care recommendations from the server based on this information, thereby maintaining their health and reducing medical costs. This system allows users to effectively manage both their health and emotional states.

[0821] The processing flow will be explained below.

[0822] Program processing steps

[0823] 1. Recording your dietary information

[0824] Step 1:

[0825] User: Eats "oatmeal and fruit" for breakfast, then enters the meal details into the device.

[0826] Step 2:

[0827] User: Enters "oatmeal and fruit" into the device's input form and presses the submit button.

[0828] Step 3:

[0829] Terminal: Sends the meal details entered by the user to the server.

[0830] Step 4:

[0831] Server: Save the received meal information in the "meals" list. This list is stored in the form of a dictionary of dates and meal information.

[0832] Step 5:

[0833] Server: Confirms that the meal record was saved successfully and sends a confirmation message to the user.

[0834] 2. Recording exercise information

[0835] Step 1:

[0836] User: Goes for a 30-minute jog, then enters the details of the exercise into the device.

[0837] Step 2:

[0838] User: Enter "30 minutes of jogging" into the device's input form and press the send button.

[0839] Step 3:

[0840] Terminal: Sends the exercise information entered by the user to the server.

[0841] Step 4:

[0842] Server: Saves the received exercise details in the "exercises" list. This list is stored in the form of a dictionary of dates and exercise details.

[0843] Step 5:

[0844] Server: Confirms that the exercise record was saved successfully and sends a confirmation message to the user.

[0845] 3. Recording health check information

[0846] Step 1:

[0847] User: Takes a health check and enters the result "I am in good health" into the terminal.

[0848] Step 2:

[0849] User: Enters "My health is good" into the input form on the device and presses the send button.

[0850] Step 3:

[0851] Terminal: Sends the health check information entered by the user to the server.

[0852] Step 4:

[0853] Server: Save the received health check information in the "health_checks" list. This list is stored in the form of a dictionary of dates and health information.

[0854] Step 5:

[0855] Server: Confirm that the health check record was saved successfully and send a confirmation message to the user.

[0856] 4. Recording emotional information

[0857] Step 1:

[0858] Emotion engine: The system automatically recognizes emotions without the user having to input their current emotional state. For example, the emotion engine recognizes that the user is feeling stressed.

[0859] Step 2:

[0860] Terminal: The emotion engine sends the recognized emotion information to the server.

[0861] Step 3:

[0862] Server: Save the received emotion information in the "emotions" list. This list is stored in the form of a dictionary of dates and emotion information.

[0863] Step 4:

[0864] Server: Checks that the emotion recording was saved successfully and sends a confirmation message to the user.

[0865] 5. Dietary Recommendations

[0866] Step 1:

[0867] User: Requests food recommendations from the server via the device.

[0868] Step 2:

[0869] Server: Receives the request and executes the meal recommendation logic based on the stored meal information.

[0870] Step 3:

[0871] Server: Generate the recommendation "balanced vegetable-based meal."

[0872] Step 4:

[0873] Server: We also consider "foods that have a relaxing effect" (e.g., chamomile tea) based on emotional information.

[0874] Step 5:

[0875] Server: Sends recommendations to the user.

[0876] Step 6:

[0877] Device: Displays meal recommendations to the user.

[0878] 6. Exercise Recommendations

[0879] Step 1:

[0880] User: Requests exercise recommendations from the server via the device.

[0881] Step 2:

[0882] Server: Receives the request and executes the exercise recommendation logic based on the stored exercise information.

[0883] Step 3:

[0884] Server: Generate the recommendation "Take a 30-minute walk three times a week."

[0885] Step 4:

[0886] Server: We also consider "stress reduction exercise" (e.g., yoga) based on emotional information.

[0887] Step 5:

[0888] Server: Sends recommendations to the user.

[0889] Step 6:

[0890] Device: Display exercise recommendations to the user.

[0891] 7. Fasting Recommendations

[0892] Step 1:

[0893] User: Requests fasting recommendations from the server via the device.

[0894] Step 2:

[0895] Server: Receives the request and executes the fasting recommendation logic.

[0896] Step 3:

[0897] Server: Generate the recommendation "24-hour fast once a month."

[0898] Step 4:

[0899] Server: Sends recommendations to the user.

[0900] Step 5:

[0901] Device: Display fasting recommendations to the user.

[0902] 8. Health Status Generation

[0903] Step 1:

[0904] User: Requests the server to generate a health status via the terminal.

[0905] Step 2:

[0906] Server: Receives the request and executes the logic for generating the user's health status based on the stored health check information and emotion information.

[0907] Step 3:

[0908] Server: Generates a health status of "good health" based on the latest health check results.

[0909] Step 4:

[0910] Server: Sends the generated health status to the user.

[0911] Step 5:

[0912] Terminal: Display health status to the user.

[0913] Example 2

[0914] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0915] Conventional health management systems have had problems in that it is difficult for users to comprehensively manage their own health status, and they are unable to quickly obtain appropriate advice based on new health status or emotional information. Furthermore, they lack an approach that takes into account the impact of stress and emotional changes on health, making it impossible to provide optimal health management for individual users.

[0916] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0917] In this invention, the server includes means for recording dietary information input by the user, means for recording exercise information input by the user, means for recording health check information input by the user, means for automatically recognizing and recording emotional information, means for recommending diet, exercise, and fasting based on the recorded dietary information, exercise information, health check information, and emotional information, and means for generating the user's health status based on the recorded health check information and emotional information. This allows the user to comprehensively manage both their health status and emotional state, and to receive appropriate health management advice in a timely manner.

[0918] A "user" is an individual who uses the health management system to record their own dietary information, exercise information, health check information, and emotional information.

[0919] A "server" is a processing device for receiving, storing, analyzing, and providing recommendations and notifications for data sent by users.

[0920] "Terminal" refers to a device that allows a user to input information about their diet, exercise, health checks, and emotions. Specifically, this refers to a smartphone or PC.

[0921] "Dietary information" is data related to meals consumed by a user, including the contents of meals at a specific point in time.

[0922] "Exercise information" is data related to the exercise performed by the user, including the specific exercise content and exercise time.

[0923] "Health check information" is data relating to the results of a health status evaluation that a user periodically performs.

[0924] "Emotion information" is data that indicates the user's emotional state, and is automatically recognized and recorded using an emotion engine or the like.

[0925] An "emotion engine" is software or hardware that analyzes the user's emotional state and outputs the results as data.

[0926] "Recommendations" are health care advice or instructions generated by the server based on the user's recorded data.

[0927] A "generative AI model" is an artificial intelligence algorithm used by the server to analyze collected data and make optimal recommendations to users.

[0928] A "prompt sentence" is a sentence indicating an instruction or question that the system asks the user.

[0929] The system of the present invention aims to enable users to manage their own health and reduce medical costs. This system records the user's dietary information, exercise information, health check information, and emotional information, and makes appropriate recommendations based on this information. Specific embodiments of the system are described below.

[0930] Recording food information

[0931] The user inputs the details of the meal they have eaten into the device. For example, they input "oatmeal and fruit for breakfast." The device sends this data to the server as an HTTP request. The server analyzes the received meal information and saves the "date, meal details, and user ID" in a database using SQL statements. This information is used to analyze the user's eating patterns.

[0932] Recording exercise information

[0933] The user enters the details of the exercise they performed into the device. For example, they enter "30 minutes of jogging." The device then sends the exercise information to the server as an HTTP request. The server analyzes the received exercise information and uses SQL statements to store the "date, exercise details, and user ID" in a database. This information is used to analyze the user's exercise habits.

[0934] Recording health check information

[0935] The user enters the results of their health check into the terminal. For example, they enter "My health condition is good." The terminal sends the health check information to the server as an HTTP request. The server analyzes the received health check information and uses SQL statements to store the "date, health check details, and user ID" in a database. This information is used to evaluate the user's health condition.

[0936] Recording emotional information

[0937] The user uses the emotion engine to automatically recognize their current emotional state. For example, if the user is feeling stressed, the emotion engine will recognize and record that information. The device then sends the emotional information to the server as an HTTP request. The server then analyzes the received emotional information and uses SQL statements to store the date, emotional state, and user ID in a database. This information is then used to analyze the user's emotional tendencies.

[0938] Diet, exercise, and fasting recommendations

[0939] The server references the dietary information, exercise information, health check information, and emotional information in the database, and integrates and analyzes them. The server uses the generative AI model to recommend optimal diet, exercise, and fasting for the user. For example, it might recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." If the user is feeling stressed, it might also recommend "foods with a relaxing effect (e.g., chamomile tea)." The generated recommendations are sent to the device, which displays them to the user.

[0940] Health state generation

[0941] The server generates the user's current health status based on the recorded health check information and emotional information. For example, if the result of a recent health check is "good health," the server notifies the user of that result. If no record exists, the server notifies the user that a health check is necessary. The terminal displays these notifications to the user.

[0942] Specific example explanation

[0943] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records that their health is "good," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that the user is "in good health" based on the results of the most recent health check.

[0944] In this way, users can input information into the system on a daily basis, and by collecting emotional information through the emotion engine, the server can recommend appropriate health care. This system allows users to effectively manage both their health and emotional states.

[0945] Prompt Sentence Examples

[0946] 1. "What did you eat today? Example: Oatmeal and fruit for breakfast."

[0947] 2. "Please enter the exercise you did today. Example: 30 minutes of jogging."

[0948] 3. "Please enter the results of your most recent health check. Example: I am in good health."

[0949] 4. Check the emotion engine results. Example: Stress state.

[0950] 5. "Would you like to see today's food and exercise recommendations?"

[0951] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0952] Step 1: Enter your meal information

[0953] The user inputs the details of the meal they have eaten into the terminal, for example, "oatmeal and fruit for breakfast."

[0954] Input: Meal details (e.g., "Oatmeal and fruit for breakfast")

[0955] Output: HTTP request sent to the terminal

[0956] Step 2: Submit your meal information

[0957] The device generates an HTTP request to send the input meal information to the server. The HTTP request includes the meal details, date and time, and the user ID.

[0958] Input: Meal information (e.g., "Oatmeal and fruit for breakfast"), date and time, user ID

[0959] Output: HTTP request sent to the server

[0960] Step 3: Save your meal information

[0961] The server stores the received meal information in a database. The server first analyzes the HTTP request and extracts the data. Then it generates an SQL statement and inserts the "date, meal content, and user ID" into the database.

[0962] Input: HTTP request (meal information, date and time, user ID)

[0963] Output: Save results to database

[0964] Step 4: Enter your exercise information

[0965] The user inputs the details of the exercise he or she has done into the terminal. For example, the user inputs "30 minutes of jogging."

[0966] Input: Exercise content (e.g., "30 minutes of jogging")

[0967] Output: HTTP request sent to the terminal

[0968] Step 5: Sending exercise information

[0969] The device generates an HTTP request to send the input exercise information to the server. The HTTP request includes the exercise details, date and time, and the user ID.

[0970] Input: Exercise information (e.g., "30 minutes of jogging"), date and time, user ID

[0971] Output: HTTP request sent to the server

[0972] Step 6: Save your exercise information

[0973] The server stores the received exercise information in a database. It analyzes the HTTP request, extracts the necessary data, and then generates an SQL statement to insert the "date, exercise content, and user ID" into the database.

[0974] Input: HTTP request (exercise information, date and time, user ID)

[0975] Output: Save results to database

[0976] Step 7: Enter your health check information

[0977] The user inputs the results of the health check into the terminal. For example, the user inputs "my health is good."

[0978] Input: Health check details (e.g. "I am in good health")

[0979] Output: HTTP request sent to the terminal

[0980] Step 8: Submit your health check information

[0981] The terminal generates an HTTP request to send the entered health check information to the server. The HTTP request includes the health check details, date and time, and user ID.

[0982] Input: Health check information (e.g., "My health is good"), date and time, user ID

[0983] Output: HTTP request sent to the server

[0984] Step 9: Save your health check information

[0985] The server saves the received health check information in a database. It analyzes the HTTP request, extracts the necessary data, and then generates an SQL statement to insert the date, health check details, and user ID into the database.

[0986] Input: HTTP request (health check information, date and time, user ID)

[0987] Output: Save results to database

[0988] Step 10: Recognizing Emotional Information

[0989] The user automatically recognizes their current emotional state using the emotion engine, which uses biometric sensors and other input devices to analyze the user's emotional state.

[0990] Input: Data from biometric sensors (e.g., heart rate, facial expression)

[0991] Output: Perceived emotional state (e.g., "stressed")

[0992] Step 11: Sending Emotional Information

[0993] The device generates an HTTP request to send the recognized emotion information to the server, which includes the emotional state, the date and time, and the user ID.

[0994] Input: Emotion information (e.g., "stress state"), date and time, user ID

[0995] Output: HTTP request sent to the server

[0996] Step 12: Storing Emotional Information

[0997] The server stores the received emotional information in a database by parsing the HTTP request, extracting the emotional state, and then inserting the date, emotional state, and user ID into the database using an SQL statement.

[0998] Input: HTTP request (emotion information, date and time, user ID)

[0999] Output: Save results to database

[1000] Step 13: Generate recommendations

[1001] The server integrates and analyzes the dietary, exercise, health check, and emotional information stored in the database, and uses a generative AI model to generate optimal diet, exercise, and fasting recommendations for the user.

[1002] Input: Various information in the database (diet, exercise, health check, emotions)

[1003] Output: Recommendation (e.g., "Eat a balanced diet centered on vegetables," "Take a 30-minute walk three times a week," "Fast for 24 hours once a month")

[1004] Step 14: Submit and view your recommendation

[1005] The server sends the generated recommendations to the terminal, which then displays them to the user.

[1006] Input: Generated recommendation

[1007] Output: Recommendation to be displayed to the user (e.g., "Eat a balanced diet centered around vegetables")

[1008] Step 15: Generate Health States

[1009] The server generates the current health status of the user based on the recorded health check information and emotional information.

[1010] Input: Health check information and emotion information in the database

[1011] Output: The generated health status (e.g. "Your health is good")

[1012] Step 16: Health Status Notification

[1013] The server sends the generated health status to the terminal, which displays it to the user. If the user's health check information is not recorded, the terminal notifies the user that a health check is required.

[1014] Input: Current health status or notification of missing check

[1015] Output: Health status information or notification displayed to the user (e.g., "Your health is good," "Please take a health check")

[1016] (Application example 2)

[1017] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1018] Conventional health management systems provide simple recommendations based only on dietary information, exercise information, and health check information. However, because they do not take the user's emotional state into account, they are insufficient for maintaining a consistent health status or managing stress. Furthermore, health management content is not personalized, failing to meet the needs of individual users. The present invention aims to solve these problems and provide personalized health management and wellness content tailored to the user's emotional state.

[1019] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1020] In this invention, the server includes means for recording dietary information input by a user, means for recording exercise information input by a user, means for recording health check information and emotional information input by a user, means for recommending diet, exercise, and fasting based on the recorded dietary information, exercise information, health check information, and emotional information, means for generating a user's health status based on the recorded health check information and emotional information, means for notifying the user that a health check is necessary if a health status has not been recorded, means for providing health management content to the user based on the recorded emotional information, and means for transmitting the dietary information, exercise information, health check information, and emotional information input by the user to the server. This enables personalized health management and stress management while taking the user's emotional state into consideration.

[1021] Creating definition statements

[1022] "User" means an individual who utilizes the system to record dietary information, exercise information, health check information, and emotional information, and who interacts with the system to receive health management and wellness content.

[1023] "Input" refers to the act of a user providing dietary information, exercise information, health check information, and emotional information to the system via an interface such as a keyboard or voice input.

[1024] "Dietary information" refers to data relating to the content and quantity of food consumed by the user.

[1025] "Exercise information" refers to data regarding the type, duration, and intensity of exercise performed by the user.

[1026] "Health check information" refers to data on the user's blood pressure, weight, body temperature, and other measurement and diagnosis results related to their health condition.

[1027] "Emotion information" refers to data relating to the user's emotional state, such as stress or relaxation.

[1028] "Recording" refers to the act of saving information entered by a user within a system or on a server.

[1029] "Recommendations" means suggestions and advice regarding diet, exercise, and fasting that the system provides to the user based on the recorded information.

[1030] "Generation" refers to the act of the system analyzing the recorded information and creating the user's latest health status and appropriate health management content.

[1031] "Notification" refers to the act of a system sending a message or alert to a user under certain conditions.

[1032] "Health Management Content" refers to personalized advice and information provided based on a user's health and emotional state.

[1033] A "server" is a computing device that receives and stores user-entered data and makes recommendations and analyses based on the recorded information.

[1034] MODE FOR CARRYING OUT THE INVENTION

[1035] A system for implementing the present invention aims to enable a user to manage their health status and provide personalized health management content. This system is implemented using a device such as a smartphone, smart glasses, or a head-mounted display. The configuration and operation of the system are described below.

[1036] 1. Recording your dietary information

[1037] The user inputs the details of the meal they ate into the device. For example, if they had "oatmeal and fruit" for breakfast, they input that information into the device. The device then sends this meal information to the server, which stores the received data in a database. This information is used to analyze future eating patterns.

[1038] 2. Recording exercise information

[1039] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information into the device. The device then sends this exercise information to the server. The server then stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[1040] 3. Recording health check information

[1041] The user inputs the results of the health check into the terminal. For example, if the user's health condition is evaluated as "good," the user inputs the result into the terminal. The terminal then sends this health check information to the server. The server stores the received information in a database and uses it to evaluate the user's health condition.

[1042] 4. Recording emotional information

[1043] The user uses the emotion engine to automatically recognize and record their current emotional state. For example, if the user is feeling stressed, the emotion engine will recognize and record that state. The device then sends the emotional information to the server, which stores the received emotional information in a database. This information is used to analyze the user's emotional tendencies.

[1044] 5. Diet, exercise, and fasting recommendations

[1045] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary information, exercise information, health check information, and emotional information. For example, based on the user's data, recommendations such as "a balanced diet centered on vegetables" and "a 30-minute walk three times a week" may be made. Also, if the user is feeling stressed, recommendations such as "eating foods with a relaxing effect (chamomile tea)" may be made. This allows the user to consistently maintain their health.

[1046] 6. Health Status Generation

[1047] The server generates the user's latest health status based on the recorded health check information and emotional information. For example, if the result of the most recent health check is "good health," the server presents this result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays this notification to the user.

[1048] Hardware and software used

[1049] Hardware: Devices such as smartphones, smart glasses, and head-mounted displays

[1050] Software: Python program, emotion engine, cloud server, database

[1051] Specific examples

[1052] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records "good health," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that "good health" based on the results of the most recent health check.

[1053] Prompt Sentence Examples

[1054] User profile: "Diet information: oatmeal and fruit", "Exercise information: 30 minutes of jogging", "Health check information: good health", "Emotion information: stressed"

[1055] Based on this information, generate recommendations for appropriate diet, exercise, and relaxation methods and display them in your "Wellness Concierge."

[1056] In this way, users can input information using the system on a daily basis, collect emotional information through the emotion engine, and receive appropriate health care recommendations from the server based on this information, thereby maintaining their health and reducing medical costs.

[1057] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1058] Program processing steps

[1059] Step 1:

[1060] Enter and submit meal information

[1061] The user uses the device to input the details of the meal they have eaten. Specifically, if the user had "oatmeal and fruit" for breakfast, they enter that information into the application. The device converts the input meal information into a data format and sends it to the cloud server. The server stores the received data in a database.

[1062] Input: Meal information entered by the user

[1063] Data processing: The device converts the meal information into data format and sends it to the server.

[1064] Output: Meal information stored on the cloud server

[1065] Step 2:

[1066] Enter and submit exercise information

[1067] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information. The device converts the exercise information into a data format and sends it to the cloud server. The server stores the received exercise information in a database.

[1068] Input: Exercise information entered by the user

[1069] Data processing and calculation: The device converts the motion information into data format and sends it to the server.

[1070] Output: Exercise information stored on a cloud server

[1071] Step 3:

[1072] Enter and submit health check information

[1073] The user inputs the results of the health check into the device. For example, if the user's health condition is evaluated as "good," the user inputs the result. The device converts the health check information into a data format and sends it to the cloud server. The server stores the received health check information in a database.

[1074] Input: Health check information entered by the user

[1075] Data processing: The terminal converts the health check information into data format and sends it to the server.

[1076] Output: Health check information stored on the cloud server

[1077] Step 4:

[1078] Recording and transmitting emotional information

[1079] The user uses the emotion engine to automatically recognize their current emotional state. For example, if the user is feeling stressed, the emotion engine will recognize and record that state. The device then converts this emotional information into a data format and sends it to a cloud server. The server then stores the received emotional information in a database.

[1080] Input: Emotion information generated by the emotion engine

[1081] Data processing operation: The device converts the emotional information into data format and sends it to the server.

[1082] Output: Emotion information stored on the cloud server

[1083] Step 5:

[1084] Recommendation generation

[1085] The server makes recommendations for appropriate diet, exercise, and fasting to the user based on the recorded dietary information, exercise information, health check information, and emotional information. For example, recommendations such as "a balanced diet centered on vegetables" and "a 30-minute walk three times a week" may be made based on the user's data. Furthermore, if the user is feeling stressed, recommendations may include information such as "foods with a relaxing effect (e.g., chamomile tea)."

[1086] Input: Diet, exercise, health check, and emotional information stored in the database

[1087] Data processing: The server analyzes this information and generates appropriate recommendations for the user.

[1088] Output: Generated recommendations

[1089] Step 6:

[1090] Health status generation and notification

[1091] The server generates the user's latest health status based on the recorded health check information and emotional information. For example, if the result of the most recent health check is "good health," the server presents this result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays this notification to the user.

[1092] Input: Health check information and emotional information stored in the database

[1093] Data processing and calculation: The server analyzes this information and generates and notifies the user of their health status.

[1094] Output: Notifications and reminders of the user's health status

[1095] In this way, the system can provide appropriate health management and wellness content based on the user's input information.

[1096] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1097] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1098] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1099] [Third embodiment]

[1100] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1101] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1102] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1103] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1104] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1105] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1106] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1107] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1108] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1109] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1110] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1111] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1112] The system of the present invention aims to help users manage their own health and reduce medical costs. This system records dietary information, exercise information, and health check information entered by users, and based on this, makes recommendations for diet, exercise, and fasting, and generates the user's health status.

[1113] 1. Recording your dietary information

[1114] The user inputs the details of the meal they had into the device. For example, if they had "oatmeal and fruit for breakfast," they input that information. The device then sends this data to the server. The server stores the received meal information in a database. This information will be used to analyze the user's eating patterns in the future.

[1115] 2. Recording exercise information

[1116] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information. The device then sends this data to the server. The server stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[1117] 3. Recording health check information

[1118] The user inputs the results of the health check into the terminal. For example, the user may input the result "my health condition is good." The terminal then sends this data to the server. The server stores the received health check information in a database. This information is used to evaluate the user's health condition.

[1119] 4. Diet, exercise, and fasting recommendations

[1120] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary, exercise, and health check information. For example, based on the user's data, it may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." The device then displays these recommendations to the user.

[1121] 5. Health Status Generation

[1122] The server generates the user's latest health status based on the recorded health check information. For example, if the result of the most recent health check is "good health," the server presents that result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays the notification to the user.

[1123] Specific examples

[1124] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, the user underwent a health check and recorded as being in "good health." The server records this information, and when the user accesses the system on January 2nd, it recommends "a balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month." It also presents the information that "the user is in good health" based on the results of the most recent health check.

[1125] In this way, users can maintain their health and reduce medical expenses by inputting information into the system on a daily basis and receiving appropriate health care recommendations from the server via their terminal.

[1126] The processing flow will be explained below.

[1127] Program processing steps

[1128] 1. Recording your dietary information

[1129] Step 1:

[1130] User: Eats "oatmeal and fruit" for breakfast, then enters the meal details into the device.

[1131] Step 2:

[1132] User: Enters "oatmeal and fruit" into the device's input form and presses the submit button.

[1133] Step 3:

[1134] Terminal: Sends the meal details entered by the user to the server.

[1135] Step 4:

[1136] Server: Save the received meal information in the "meals" list. This list is stored in the form of a dictionary of dates and meal information.

[1137] Step 5:

[1138] Server: Confirms that the meal record was saved successfully and sends a confirmation message to the user.

[1139] 2. Recording exercise information

[1140] Step 1:

[1141] User: Goes for a 30-minute jog, then enters the details of the exercise into the device.

[1142] Step 2:

[1143] User: Enter "30 minutes of jogging" into the device's input form and press the send button.

[1144] Step 3:

[1145] Terminal: Sends the exercise information entered by the user to the server.

[1146] Step 4:

[1147] Server: Saves the received exercise details in the "exercises" list. This list is stored in the form of a dictionary of dates and exercise details.

[1148] Step 5:

[1149] Server: Confirms that the exercise record was saved successfully and sends a confirmation message to the user.

[1150] 3. Recording health check information

[1151] Step 1:

[1152] User: Takes a health check and enters the result "I am in good health" into the terminal.

[1153] Step 2:

[1154] User: Enters "My health is good" into the input form on the device and presses the send button.

[1155] Step 3:

[1156] Terminal: Sends the health check information entered by the user to the server.

[1157] Step 4:

[1158] Server: Save the received health check information in the "health_checks" list. This list is stored in the form of a dictionary of dates and health information.

[1159] Step 5:

[1160] Server: Confirm that the health check record was saved successfully and send a confirmation message to the user.

[1161] 4. Dietary Recommendations

[1162] Step 1:

[1163] User: Requests food recommendations from the server via the device.

[1164] Step 2:

[1165] Server: Receives the request and executes the meal recommendation logic based on the stored meal information.

[1166] Step 3:

[1167] Server: Generate the recommendation "balanced vegetable-based meal."

[1168] Step 4:

[1169] Server: Sends recommendations to the user.

[1170] Step 5:

[1171] Device: Displays meal recommendations to the user.

[1172] 5. Exercise Recommendations

[1173] Step 1:

[1174] User: Requests exercise recommendations from the server via the device.

[1175] Step 2:

[1176] Server: Receives the request and executes the exercise recommendation logic based on the stored exercise information.

[1177] Step 3:

[1178] Server: Generate the recommendation "Take a 30-minute walk three times a week."

[1179] Step 4:

[1180] Server: Sends recommendations to the user.

[1181] Step 5:

[1182] Device: Display exercise recommendations to the user.

[1183] 6. Fasting recommendations

[1184] Step 1:

[1185] User: Requests fasting recommendations from the server via the device.

[1186] Step 2:

[1187] Server: Receives the request and executes the fasting recommendation logic.

[1188] Step 3:

[1189] Server: Generate the recommendation "24-hour fast once a month."

[1190] Step 4:

[1191] Server: Sends recommendations to the user.

[1192] Step 5:

[1193] Device: Display fasting recommendations to the user.

[1194] 7. Health Status Generation

[1195] Step 1:

[1196] User: Requests the server to generate a health status via the terminal.

[1197] Step 2:

[1198] Server: Receives the request and executes the logic to generate the user's health status based on the stored health check information.

[1199] Step 3:

[1200] Server: Generates a health status of "good health" based on the latest health check results.

[1201] Step 4:

[1202] Server: Sends the generated health status to the user.

[1203] Step 5:

[1204] Terminal: Display health status to the user.

[1205] Example 1

[1206] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1207] In modern society, individual health management and rising medical costs are becoming serious issues. Current health management systems allow users to input and track their own health data, but they lack effective utilization and optimal health management recommendations. The data entered by users is stored fragmentedly, preventing unified health management advice, making it difficult to improve users' health. Furthermore, users may not receive notifications even if appropriate health checks are not performed, which increases the risk of users neglecting to check their health.

[1208] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1209] In this invention, the server includes a means for recording dietary information entered by the user, a means for recording exercise information entered by the user, a means for recording health check information entered by the user, a means for storing the recorded dietary information, exercise information, and health check information in a database, a means for making diet, exercise, and fasting recommendations using a machine learning algorithm based on the recorded dietary information, exercise information, and health check information, a means for notifying the terminal of the recommendations, and a means for generating the user's health status based on the recorded health check information. This makes it possible to centrally manage health-related data entered by the user and provide optimal health management recommendations using a machine learning algorithm. Furthermore, by providing a notification even if a health check has not been performed, the server can encourage the user to perform a health check.

[1210] "User" refers to an individual who uses the system and is the entity that inputs data such as dietary information, exercise information, and health check information.

[1211] "Terminal" refers to an electronic device used to send data entered by a user to a server, including smartphones and tablets.

[1212] "Dietary information" refers to data relating to the types and amounts of food consumed by the user, and is information for recording the user's nutritional intake status.

[1213] "Exercise information" refers to data relating to the type and duration of exercise performed by the user, and is information for recording the user's exercise status.

[1214] "Health check information" refers to data such as diagnostic results and self-assessment regarding the user's health condition, and is information for evaluating the user's health condition.

[1215] "Server" refers to a centralized computer system that receives, processes, and stores data submitted by users, including databases and analytical algorithms.

[1216] A "database" refers to a digital archive for storing a user's dietary information, exercise information, health check information, etc. in a structured manner, making it easy to search and manage information.

[1217] A "machine learning algorithm" refers to a computational method for discovering patterns based on accumulated data and making predictions and recommendations, and is used in data analysis and building predictive models.

[1218] "Recommendations" refers to health management advice and suggestions for users generated by machine learning algorithms, including diet, exercise, fasting, etc.

[1219] "Notification means" refers to methods for informing users of information such as recommendations and the need for health checks, and includes push notifications and dashboard displays.

[1220] The system of the present invention aims to enable users to manage their own health and reduce medical costs. This system records dietary information, exercise information, and health check information entered by the user, and based on this information, makes recommendations for diet, exercise, and fasting, thereby generating a health status report for the user. Specific embodiments of this system are described below.

[1221] System Configuration

[1222] User

[1223] Users access the system using devices such as smartphones and tablets, which have a dedicated health management app installed.

[1224] Terminal

[1225] The device accepts information about meals, exercise, and health checks entered by the user. This information is converted into JSON format and sent to the server using the HTTPS protocol.

[1226] The device is responsible for displaying recommendations and health check notifications to the user. It uses a push notification service (e.g., Firebase Cloud Messaging) to notify the user.

[1227] server

[1228] The server is built using a cloud service (e.g., a general cloud computing platform). The server has the following roles:

[1229] 1. Data reception: Receives meal information, exercise information, and health check information sent by users. This is done using an API using the Flask framework.

[1230] 2. Data storage: The received data is stored in a MySQL database. The database is divided into a "meal information table," a "exercise information table," and a "health check information table."

[1231] 3. Data analysis: Periodically, a scheduler (e.g., cron job) is used to analyze the recorded data using machine learning algorithms (e.g., Scikit-learn), which then generates appropriate diet, exercise, and fasting recommendations for the user.

[1232] 4. Health Status Generation: Generates the latest health status based on the recorded health check information. If necessary, notifies the user that a health check is required.

[1233] Specific examples

[1234] For example, if a user eats "oatmeal and fruit" for breakfast on January 1st, goes "30 minutes jogging" on the same day, and records a health check as "good health," the server records this information, and when the user accesses the system on January 2nd, it provides the following recommendations:

[1235] A balanced diet centered around vegetables

[1236] 30-minute walks three times a week

[1237] 24-hour fasting once a month

[1238] It also displays "good health" based on the results of the most recent health check. In this way, users can input information into the system on a daily basis and receive appropriate health management recommendations from the server via their terminal, thereby maintaining their health and reducing medical costs.

[1239] Example of input prompt for generative AI model

[1240] "I would like to design a user interface for a health management system. Please suggest a design for a form that allows users to easily enter information about their diet, exercise, and health checks."

[1241] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1242] Step 1:

[1243] A user opens a smartphone app and inputs the details of the meal they had. For example, they input "oatmeal and fruit for breakfast." The device converts this input information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed data about the meal, and the device converts it into JSON format and sends it.

[1244] Step 2:

[1245] The server receives the meal information using an API built with the Flask framework. It parses the received data and stores it in a MySQL "meal information" table. The input is JSON-formatted meal information data, which is parsed and stored in the database.

[1246] Step 3:

[1247] The user uses the same app to input the details of the exercise they performed. For example, they input "30 minutes of jogging." The device converts this exercise information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed exercise data, which is then converted into JSON format and sent.

[1248] Step 4:

[1249] The server processes the received exercise information using the Flask API, parses the data, and saves it in the MySQL "exercise information" table. The input is exercise information data in JSON format, which is parsed and stored in the database.

[1250] Step 5:

[1251] The user enters the results of their health check into the app. For example, they might enter "My health is good." The device converts this health check information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed health check data, which is then converted into JSON format and sent.

[1252] Step 6:

[1253] The server processes the received health check information through the Flask API, parses the data, and saves it in the MySQL "health check information" table. The input is health check information data in JSON format, which is parsed and stored in the database.

[1254] Step 7:

[1255] The server periodically uses a scheduler (e.g., cron job) to perform data analysis based on the recorded dietary information, exercise information, and health check information. This process uses Python and Scikit-learn. As a result of the analysis, it generates optimal diet, exercise, and fasting recommendations for the user. The input is multiple pieces of information obtained from the database, which are then analyzed and the recommendations are output.

[1256] Step 8:

[1257] The server sends the generated recommendation to the user's device. The device uses the Firebase Cloud Messaging service to send a push notification to the user to notify them of the new recommendation. When the user taps the notification, they can view the detailed recommendation within the app. The input is the generated recommendation, and the operation to send it to the user via a push notification is performed.

[1258] Step 9:

[1259] The server generates the user's latest health status based on the periodically saved health check information. For example, if the most recent health check result is "good health," the server presents that result to the user. The input is health check information retrieved from the database, and the server evaluates it and outputs the latest health status.

[1260] Step 10:

[1261] If there is no health check record, the server uses Firebase Cloud Messaging to notify the user that a "health check is required." The device receives this notification and displays it on the app's dashboard. The input is whether or not there is a health check record, and the notification action is performed based on that.

[1262] (Application example 1)

[1263] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1264] Conventional health management systems require users to manually input information about their diet and exercise, and suffer from issues such as a lack of data accuracy and real-time performance. Furthermore, there are only limited systems that utilize accumulated data to provide effective health management recommendations. This has resulted in a lack of an optimal approach for efficiently managing users' health status and reducing medical costs.

[1265] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1266] In this invention, the server includes a means for transmitting dietary information, exercise information, and health check information manually input by the user to the server, a means for automatically recording the user's exercise data and dietary data using hardware functions such as an exercise sensor and a barcode scanner and transmitting the data to the server, a means for analyzing the data accumulated by the server using a machine learning algorithm to generate appropriate diet, exercise, and fasting recommendations for the user, and a means for notifying the user of the recommendations. This allows users to efficiently accumulate health management information by utilizing both manual input and automatic recording, and to receive optimal health management recommendations for each individual user through the machine learning algorithm.

[1267] "Dietary information" refers to data about the contents of the foods and drinks consumed by the user.

[1268] "Exercise information" refers to data regarding the type, duration, and intensity of exercise performed by the user.

[1269] "Health check information" refers to data related to the user's health condition, such as weight, blood pressure, and heart rate.

[1270] A "server" is a computer system that stores and analyzes data sent by users and provides necessary information.

[1271] "Recommendation" refers to providing optimal diet, exercise, and fasting advice based on the user's health data.

[1272] An "exercise sensor" is a device for detecting a user's exercise status, and is a device for measuring the number of steps, distance, calorie consumption, etc.

[1273] "Barcode scanning" is the act of reading the barcode of food or products and recording that information as data.

[1274] A "machine learning algorithm" is a program that analyzes the data received by the server, finds patterns, and generates optimal recommendations for users.

[1275] "Notification" refers to the act of informing the user of the generated recommendations and necessary health check information.

[1276] A "smartphone" is a multi-function mobile phone that can connect to the Internet and use applications.

[1277] "Smart glasses" are wearable devices that can provide information visually.

[1278] A "smartwatch" is a wearable device that has a built-in motion sensor and measures the user's biometric information and motion data.

[1279] The system for implementing this invention aims to record dietary information, exercise information, and health check information entered by users and provide appropriate health management recommendations. The main components of the system include devices such as smartphones, smart glasses, and smart watches, and a server that performs data analysis.

[1280] System Structure

[1281] 1. Recording your dietary information:

[1282] Users can use their smartphones or smart glasses to input meal information by scanning barcodes or by voice input. For example, they can use their smartphone's camera to scan food barcodes and input "I had oatmeal and fruit for breakfast."

[1283] The device sends the entered meal information to the server, and the server stores the received data in a database (e.g., Firebase, Google Cloud Firestore).

[1284] 2. Recording exercise information:

[1285] The smartwatch's motion sensor automatically records the user's motion data. For example, if you go for a 30-minute jog, the smartwatch will record that motion data.

[1286] The device transfers this data to a smartphone via Bluetooth, which then sends it to a server, which stores the data in a database.

[1287] 3. Recording Health Check Information:

[1288] Users enter their health check information (weight, blood pressure, heart rate, etc.) through the app. For example, if their weight is 65 kg, their blood pressure is 120 / 80 mmHg, and their heart rate is 70 bpm, they enter that information into their smartphone.

[1289] The terminal sends the input information to the server, which stores it in a database.

[1290] 4. Health Care Recommendations:

[1291] The server analyzes the collected data using machine learning algorithms (e.g., TensorFlow) to generate recommendations for diet, exercise, and fasting. For example, based on the analysis of the user's diet and exercise information, it may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month."

[1292] The device will notify the user of the recommendations, for example, by displaying them on the HUD (heads-up display) of smart glasses or via a pop-up notification on a smartphone.

[1293] 5. Health generation:

[1294] The server analyzes the user's latest health status based on the recorded health check information. For example, if the result of the most recent health check is "good health," the server presents that information to the user.

[1295] If the health status is not recorded, the server will notify the user that a health check is required.

[1296] Specific examples

[1297] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went on a "30-minute jog" on the same day. If this user also records "weight 65 kg, blood pressure 120 / 80 mmHg, heart rate 70 bpm" during a health check, the server will record this information, and when the user accesses the system on January 2nd, it will recommend "a balanced diet centered on vegetables," "30-minute walks three times a week," and "24-hour fasting once a month." It will also present the latest health check result as "good health."

[1298] Prompt Sentence Examples

[1299] Q: What was the last thing you ate?

[1300] How to register your meal information:

[1301] Scan the barcode with your camera or say, "I had oatmeal and fruit."

[1302] In this way, the system aims to enable users to efficiently manage their health and reduce medical costs by inputting their health information on a daily basis and receiving recommendations for appropriate health care.

[1303] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1304] Step 1:

[1305] Users can input meal information using their smartphones or smart glasses. For example, they can scan the barcode of a food item with their smartphone camera and input that they had "oatmeal and fruit for breakfast." This information is then sent to the device.

[1306] Input: Meal information (e.g., "oatmeal and fruit")

[1307] Output: Meal data (e.g., {"meal": "oatmeal and fruit"})

[1308] Step 2:

[1309] The device sends the entered meal information to the server. The device sends the meal data to the server's API endpoint, and the server receives the data and stores it in a database (e.g., Firebase, Google Cloud Firestore).

[1310] Input: Sending food data from device to server

[1311] Output: Meal data stored in the server database (e.g. {"meal": "oatmeal and fruit"})

[1312] Step 3:

[1313] The smartwatch automatically detects and records the exercise the user performs. For example, if you jog for 30 minutes, the smartwatch records that data. The smartwatch then transfers this data to your smartphone via Bluetooth.

[1314] Input: User's exercise data (e.g., {"activity": "jogging", "duration": 30})

[1315] Output: Exercise data transferred to a smartphone

[1316] Step 4:

[1317] The smartphone sends the received exercise data to a server, which receives the data and stores it in a database.

[1318] Input: Exercise data sent from smartphone to server

[1319] Output: Exercise data stored in the server database (e.g. {"activity": "jogging", "duration": 30})

[1320] Step 5:

[1321] The user enters health check information through the app. For example, "weight 65 kg, blood pressure 120 / 80 mmHg, heart rate 70 bpm." The device (smartphone) then sends this information to the server.

[1322] Input: Health check information (e.g., {"weight": 65, "blood_pressure": "120 / 80", "heart_rate": 70})

[1323] Output: Health data sent to the server

[1324] Step 6:

[1325] After receiving the health check information, the server stores it in a database, which is used for analysis.

[1326] Input: Request to save health check information

[1327] Output: Health data stored in a database

[1328] Step 7:

[1329] The server analyzes the collected dietary, exercise, and health check information using machine learning algorithms (e.g., TensorFlow). The server finds correlations between each piece of data and generates optimal diet, exercise, and fasting recommendations for the user. For example, it may generate recommendations such as "a balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month."

[1330] Input: Various health data stored in the database

[1331] Output: Recommendation (e.g., {"diet_recommendation": "Balanced, plant-based diet", "exercise_recommendation": "30-minute walks three times a week", "fasting_recommendation": "24-hour fast once a month"})

[1332] Step 8:

[1333] The device (smartphone, smart glasses, etc.) notifies the user of the generated recommendation content, for example, by displaying it on the smart glasses' HUD (heads-up display) or via a pop-up notification on the smartphone.

[1334] Input: Recommendation

[1335] Output: Notification to the user (e.g. smartphone notification, smart glasses display)

[1336] Step 9:

[1337] The server evaluates the user's latest health status based on the recorded health check information and presents the results to the user. For example, it may notify the user that their health status is good. Furthermore, if a health check has not been recorded, it may notify the user that they need to take a health check again.

[1338] Input: Health check data

[1339] Output: Health status notification to user (e.g. "Your health is good"), reminders when a health check is needed

[1340] Through the above steps, the system can comprehensively collect and analyze the user's health care information and provide recommendations for optimal health care.

[1341] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1342] The system of the present invention aims to help users manage their own health and reduce medical costs. In addition to dietary information, exercise information, and health check information, the system records the user's emotional information and can adapt the recommendations based on that information.

[1343] 1. Recording your dietary information

[1344] The user inputs the details of the meal they had into the device. For example, if they had "oatmeal and fruit for breakfast," they input that information. The device then sends this data to the server. The server stores the received meal information in a database. This information will be used to analyze the user's eating patterns in the future.

[1345] 2. Recording exercise information

[1346] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information. The device then sends this data to the server. The server stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[1347] 3. Recording health check information

[1348] The user inputs the results of the health check into the terminal. For example, the user may input the result "my health condition is good." The terminal then sends this data to the server. The server stores the received health check information in a database. This information is used to evaluate the user's health condition.

[1349] 4. Recording emotional information

[1350] The user automatically recognizes their current emotional state through the emotion engine. For example, if the user is feeling stressed, the emotion engine recognizes and records that information. The device then sends this data to a server, which stores the received emotional information in a database. This information is used to analyze the user's emotional tendencies.

[1351] 5. Diet, exercise, and fasting recommendations

[1352] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary information, exercise information, health check information, and emotional information. For example, based on the user's data, it may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." If the user is feeling stressed, it may recommend "foods that have a relaxing effect." The device then displays these recommendations to the user.

[1353] 6. Health Status Generation

[1354] The server generates the user's latest health status based on the recorded health check information and emotional information. For example, if the result of the most recent health check is "good health," the server presents that result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays the notification to the user.

[1355] Specific examples

[1356] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records that their health is "good," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that the user is "in good health" based on the results of the most recent health check.

[1357] In this way, users can input information into the system on a daily basis, collect emotional information through the emotion engine, and receive appropriate health care recommendations from the server based on this information, thereby maintaining their health and reducing medical costs. This system allows users to effectively manage both their health and emotional states.

[1358] The processing flow will be explained below.

[1359] Program processing steps

[1360] 1. Recording your dietary information

[1361] Step 1:

[1362] User: Eats "oatmeal and fruit" for breakfast, then enters the meal details into the device.

[1363] Step 2:

[1364] User: Enters "oatmeal and fruit" into the device's input form and presses the submit button.

[1365] Step 3:

[1366] Terminal: Sends the meal details entered by the user to the server.

[1367] Step 4:

[1368] Server: Save the received meal information in the "meals" list. This list is stored in the form of a dictionary of dates and meal information.

[1369] Step 5:

[1370] Server: Confirms that the meal record was saved successfully and sends a confirmation message to the user.

[1371] 2. Recording exercise information

[1372] Step 1:

[1373] User: Goes for a 30-minute jog, then enters the details of the exercise into the device.

[1374] Step 2:

[1375] User: Enter "30 minutes of jogging" into the device's input form and press the send button.

[1376] Step 3:

[1377] Terminal: Sends the exercise information entered by the user to the server.

[1378] Step 4:

[1379] Server: Saves the received exercise details in the "exercises" list. This list is stored in the form of a dictionary of dates and exercise details.

[1380] Step 5:

[1381] Server: Confirms that the exercise record was saved successfully and sends a confirmation message to the user.

[1382] 3. Recording health check information

[1383] Step 1:

[1384] User: Takes a health check and enters the result "I am in good health" into the terminal.

[1385] Step 2:

[1386] User: Enters "My health is good" into the input form on the device and presses the send button.

[1387] Step 3:

[1388] Terminal: Sends the health check information entered by the user to the server.

[1389] Step 4:

[1390] Server: Save the received health check information in the "health_checks" list. This list is stored in the form of a dictionary of dates and health information.

[1391] Step 5:

[1392] Server: Confirm that the health check record was saved successfully and send a confirmation message to the user.

[1393] 4. Recording emotional information

[1394] Step 1:

[1395] Emotion engine: The system automatically recognizes emotions without the user having to input their current emotional state. For example, the emotion engine recognizes that the user is feeling stressed.

[1396] Step 2:

[1397] Terminal: The emotion engine sends the recognized emotion information to the server.

[1398] Step 3:

[1399] Server: Save the received emotion information in the "emotions" list. This list is stored in the form of a dictionary of dates and emotion information.

[1400] Step 4:

[1401] Server: Checks that the emotion recording was saved successfully and sends a confirmation message to the user.

[1402] 5. Dietary Recommendations

[1403] Step 1:

[1404] User: Requests food recommendations from the server via the device.

[1405] Step 2:

[1406] Server: Receives the request and executes the meal recommendation logic based on the stored meal information.

[1407] Step 3:

[1408] Server: Generate the recommendation "balanced vegetable-based meal."

[1409] Step 4:

[1410] Server: We also consider "foods that have a relaxing effect" (e.g., chamomile tea) based on emotional information.

[1411] Step 5:

[1412] Server: Sends recommendations to the user.

[1413] Step 6:

[1414] Device: Displays meal recommendations to the user.

[1415] 6. Exercise Recommendations

[1416] Step 1:

[1417] User: Requests exercise recommendations from the server via the device.

[1418] Step 2:

[1419] Server: Receives the request and executes the exercise recommendation logic based on the stored exercise information.

[1420] Step 3:

[1421] Server: Generate the recommendation "Take a 30-minute walk three times a week."

[1422] Step 4:

[1423] Server: We also consider "stress reduction exercise" (e.g., yoga) based on emotional information.

[1424] Step 5:

[1425] Server: Sends recommendations to the user.

[1426] Step 6:

[1427] Device: Display exercise recommendations to the user.

[1428] 7. Fasting Recommendations

[1429] Step 1:

[1430] User: Requests fasting recommendations from the server via the device.

[1431] Step 2:

[1432] Server: Receives the request and executes the fasting recommendation logic.

[1433] Step 3:

[1434] Server: Generate the recommendation "24-hour fast once a month."

[1435] Step 4:

[1436] Server: Sends recommendations to the user.

[1437] Step 5:

[1438] Device: Display fasting recommendations to the user.

[1439] 8. Health Status Generation

[1440] Step 1:

[1441] User: Requests the server to generate a health status via the terminal.

[1442] Step 2:

[1443] Server: Receives the request and executes the logic for generating the user's health status based on the stored health check information and emotion information.

[1444] Step 3:

[1445] Server: Generates a health status of "good health" based on the latest health check results.

[1446] Step 4:

[1447] Server: Sends the generated health status to the user.

[1448] Step 5:

[1449] Terminal: Display health status to the user.

[1450] Example 2

[1451] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1452] Conventional health management systems have had problems in that it is difficult for users to comprehensively manage their own health status, and they are unable to quickly obtain appropriate advice based on new health status or emotional information. Furthermore, they lack an approach that takes into account the impact of stress and emotional changes on health, making it impossible to provide optimal health management for individual users.

[1453] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1454] In this invention, the server includes means for recording dietary information input by the user, means for recording exercise information input by the user, means for recording health check information input by the user, means for automatically recognizing and recording emotional information, means for recommending diet, exercise, and fasting based on the recorded dietary information, exercise information, health check information, and emotional information, and means for generating the user's health status based on the recorded health check information and emotional information. This allows the user to comprehensively manage both their health status and emotional state, and to receive appropriate health management advice in a timely manner.

[1455] A "user" is an individual who uses the health management system to record their own dietary information, exercise information, health check information, and emotional information.

[1456] A "server" is a processing device for receiving, storing, analyzing, and providing recommendations and notifications for data sent by users.

[1457] "Terminal" refers to a device that allows a user to input information about their diet, exercise, health checks, and emotions. Specifically, this refers to a smartphone or PC.

[1458] "Dietary information" is data related to meals consumed by a user, including the contents of meals at a specific point in time.

[1459] "Exercise information" is data related to the exercise performed by the user, including the specific exercise content and exercise time.

[1460] "Health check information" is data relating to the results of a health status evaluation that a user periodically performs.

[1461] "Emotion information" is data that indicates the user's emotional state, and is automatically recognized and recorded using an emotion engine or the like.

[1462] An "emotion engine" is software or hardware that analyzes the user's emotional state and outputs the results as data.

[1463] "Recommendations" are health care advice or instructions generated by the server based on the user's recorded data.

[1464] A "generative AI model" is an artificial intelligence algorithm used by the server to analyze collected data and make optimal recommendations to users.

[1465] A "prompt sentence" is a sentence indicating an instruction or question that the system asks the user.

[1466] The system of the present invention aims to enable users to manage their own health and reduce medical costs. This system records the user's dietary information, exercise information, health check information, and emotional information, and makes appropriate recommendations based on this information. Specific embodiments of the system are described below.

[1467] Recording food information

[1468] The user inputs the details of the meal they have eaten into the device. For example, they input "oatmeal and fruit for breakfast." The device sends this data to the server as an HTTP request. The server analyzes the received meal information and saves the "date, meal details, and user ID" in a database using SQL statements. This information is used to analyze the user's eating patterns.

[1469] Recording exercise information

[1470] The user enters the details of the exercise they performed into the device. For example, they enter "30 minutes of jogging." The device then sends the exercise information to the server as an HTTP request. The server analyzes the received exercise information and uses SQL statements to store the "date, exercise details, and user ID" in a database. This information is used to analyze the user's exercise habits.

[1471] Recording health check information

[1472] The user enters the results of their health check into the terminal. For example, they enter "My health condition is good." The terminal sends the health check information to the server as an HTTP request. The server analyzes the received health check information and uses SQL statements to store the "date, health check details, and user ID" in a database. This information is used to evaluate the user's health condition.

[1473] Recording emotional information

[1474] The user uses the emotion engine to automatically recognize their current emotional state. For example, if the user is feeling stressed, the emotion engine will recognize and record that information. The device then sends the emotional information to the server as an HTTP request. The server then analyzes the received emotional information and uses SQL statements to store the date, emotional state, and user ID in a database. This information is then used to analyze the user's emotional tendencies.

[1475] Diet, exercise, and fasting recommendations

[1476] The server references the dietary information, exercise information, health check information, and emotional information in the database, and integrates and analyzes them. The server uses the generative AI model to recommend optimal diet, exercise, and fasting for the user. For example, it might recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." If the user is feeling stressed, it might also recommend "foods with a relaxing effect (e.g., chamomile tea)." The generated recommendations are sent to the device, which displays them to the user.

[1477] Health state generation

[1478] The server generates the user's current health status based on the recorded health check information and emotional information. For example, if the result of a recent health check is "good health," the server notifies the user of that result. If no record exists, the server notifies the user that a health check is necessary. The terminal displays these notifications to the user.

[1479] Specific example explanation

[1480] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records that their health is "good," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that the user is "in good health" based on the results of the most recent health check.

[1481] In this way, users can input information into the system on a daily basis, and by collecting emotional information through the emotion engine, the server can recommend appropriate health care. This system allows users to effectively manage both their health and emotional states.

[1482] Prompt Sentence Examples

[1483] 1. "What did you eat today? Example: Oatmeal and fruit for breakfast."

[1484] 2. "Please enter the exercise you did today. Example: 30 minutes of jogging."

[1485] 3. "Please enter the results of your most recent health check. Example: I am in good health."

[1486] 4. Check the emotion engine results. Example: Stress state.

[1487] 5. "Would you like to see today's food and exercise recommendations?"

[1488] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1489] Step 1: Enter your meal information

[1490] The user inputs the details of the meal they have eaten into the terminal, for example, "oatmeal and fruit for breakfast."

[1491] Input: Meal details (e.g., "Oatmeal and fruit for breakfast")

[1492] Output: HTTP request sent to the terminal

[1493] Step 2: Submit your meal information

[1494] The device generates an HTTP request to send the input meal information to the server. The HTTP request includes the meal details, date and time, and the user ID.

[1495] Input: Meal information (e.g., "Oatmeal and fruit for breakfast"), date and time, user ID

[1496] Output: HTTP request sent to the server

[1497] Step 3: Save your meal information

[1498] The server stores the received meal information in a database. The server first analyzes the HTTP request and extracts the data. Then it generates an SQL statement and inserts the "date, meal content, and user ID" into the database.

[1499] Input: HTTP request (meal information, date and time, user ID)

[1500] Output: Save results to database

[1501] Step 4: Enter your exercise information

[1502] The user inputs the details of the exercise he or she has done into the terminal. For example, the user inputs "30 minutes of jogging."

[1503] Input: Exercise content (e.g., "30 minutes of jogging")

[1504] Output: HTTP request sent to the terminal

[1505] Step 5: Sending exercise information

[1506] The device generates an HTTP request to send the input exercise information to the server. The HTTP request includes the exercise details, date and time, and the user ID.

[1507] Input: Exercise information (e.g., "30 minutes of jogging"), date and time, user ID

[1508] Output: HTTP request sent to the server

[1509] Step 6: Save your exercise information

[1510] The server stores the received exercise information in a database. It analyzes the HTTP request, extracts the necessary data, and then generates an SQL statement to insert the "date, exercise content, and user ID" into the database.

[1511] Input: HTTP request (exercise information, date and time, user ID)

[1512] Output: Save results to database

[1513] Step 7: Enter your health check information

[1514] The user inputs the results of the health check into the terminal. For example, the user inputs "my health is good."

[1515] Input: Health check details (e.g. "I am in good health")

[1516] Output: HTTP request sent to the terminal

[1517] Step 8: Submit your health check information

[1518] The terminal generates an HTTP request to send the entered health check information to the server. The HTTP request includes the health check details, date and time, and user ID.

[1519] Input: Health check information (e.g., "My health is good"), date and time, user ID

[1520] Output: HTTP request sent to the server

[1521] Step 9: Save your health check information

[1522] The server saves the received health check information in a database. It analyzes the HTTP request, extracts the necessary data, and then generates an SQL statement to insert the date, health check details, and user ID into the database.

[1523] Input: HTTP request (health check information, date and time, user ID)

[1524] Output: Save results to database

[1525] Step 10: Recognizing Emotional Information

[1526] The user automatically recognizes their current emotional state using the emotion engine, which uses biometric sensors and other input devices to analyze the user's emotional state.

[1527] Input: Data from biometric sensors (e.g., heart rate, facial expression)

[1528] Output: Perceived emotional state (e.g., "stressed")

[1529] Step 11: Sending Emotional Information

[1530] The device generates an HTTP request to send the recognized emotion information to the server, which includes the emotional state, the date and time, and the user ID.

[1531] Input: Emotion information (e.g., "stress state"), date and time, user ID

[1532] Output: HTTP request sent to the server

[1533] Step 12: Storing Emotional Information

[1534] The server stores the received emotional information in a database by parsing the HTTP request, extracting the emotional state, and then inserting the date, emotional state, and user ID into the database using an SQL statement.

[1535] Input: HTTP request (emotion information, date and time, user ID)

[1536] Output: Save results to database

[1537] Step 13: Generate recommendations

[1538] The server integrates and analyzes the dietary, exercise, health check, and emotional information stored in the database, and uses a generative AI model to generate optimal diet, exercise, and fasting recommendations for the user.

[1539] Input: Various information in the database (diet, exercise, health check, emotions)

[1540] Output: Recommendation (e.g., "Eat a balanced diet centered on vegetables," "Take a 30-minute walk three times a week," "Fast for 24 hours once a month")

[1541] Step 14: Submit and view your recommendation

[1542] The server sends the generated recommendations to the terminal, which then displays them to the user.

[1543] Input: Generated recommendation

[1544] Output: Recommendation to be displayed to the user (e.g., "Eat a balanced diet centered around vegetables")

[1545] Step 15: Generate Health States

[1546] The server generates the current health status of the user based on the recorded health check information and emotional information.

[1547] Input: Health check information and emotion information in the database

[1548] Output: The generated health status (e.g. "Your health is good")

[1549] Step 16: Health Status Notification

[1550] The server sends the generated health status to the terminal, which displays it to the user. If the user's health check information is not recorded, the terminal notifies the user that a health check is required.

[1551] Input: Current health status or notification of missing check

[1552] Output: Health status information or notification displayed to the user (e.g., "Your health is good," "Please take a health check")

[1553] (Application example 2)

[1554] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1555] Conventional health management systems provide simple recommendations based only on dietary information, exercise information, and health check information. However, because they do not take the user's emotional state into account, they are insufficient for maintaining a consistent health status or managing stress. Furthermore, health management content is not personalized, failing to meet the needs of individual users. The present invention aims to solve these problems and provide personalized health management and wellness content tailored to the user's emotional state.

[1556] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1557] In this invention, the server includes means for recording dietary information input by a user, means for recording exercise information input by a user, means for recording health check information and emotional information input by a user, means for recommending diet, exercise, and fasting based on the recorded dietary information, exercise information, health check information, and emotional information, means for generating a user's health status based on the recorded health check information and emotional information, means for notifying the user that a health check is necessary if a health status has not been recorded, means for providing health management content to the user based on the recorded emotional information, and means for transmitting the dietary information, exercise information, health check information, and emotional information input by the user to the server. This enables personalized health management and stress management while taking the user's emotional state into consideration.

[1558] Creating definition statements

[1559] "User" means an individual who utilizes the system to record dietary information, exercise information, health check information, and emotional information, and who interacts with the system to receive health management and wellness content.

[1560] "Input" refers to the act of a user providing dietary information, exercise information, health check information, and emotional information to the system via an interface such as a keyboard or voice input.

[1561] "Dietary information" refers to data relating to the content and quantity of food consumed by the user.

[1562] "Exercise information" refers to data regarding the type, duration, and intensity of exercise performed by the user.

[1563] "Health check information" refers to data on the user's blood pressure, weight, body temperature, and other measurement and diagnosis results related to their health condition.

[1564] "Emotion information" refers to data relating to the user's emotional state, such as stress or relaxation.

[1565] "Recording" refers to the act of saving information entered by a user within a system or on a server.

[1566] "Recommendations" means suggestions and advice regarding diet, exercise, and fasting that the system provides to the user based on the recorded information.

[1567] "Generation" refers to the act of the system analyzing the recorded information and creating the user's latest health status and appropriate health management content.

[1568] "Notification" refers to the act of a system sending a message or alert to a user under certain conditions.

[1569] "Health Management Content" refers to personalized advice and information provided based on a user's health and emotional state.

[1570] A "server" is a computing device that receives and stores user-entered data and makes recommendations and analyses based on the recorded information.

[1571] MODE FOR CARRYING OUT THE INVENTION

[1572] A system for implementing the present invention aims to enable a user to manage their health status and provide personalized health management content. This system is implemented using a device such as a smartphone, smart glasses, or a head-mounted display. The configuration and operation of the system are described below.

[1573] 1. Recording your dietary information

[1574] The user inputs the details of the meal they ate into the device. For example, if they had "oatmeal and fruit" for breakfast, they input that information into the device. The device then sends this meal information to the server, which stores the received data in a database. This information is used to analyze future eating patterns.

[1575] 2. Recording exercise information

[1576] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information into the device. The device then sends this exercise information to the server. The server then stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[1577] 3. Recording health check information

[1578] The user inputs the results of the health check into the terminal. For example, if the user's health condition is evaluated as "good," the user inputs the result into the terminal. The terminal then sends this health check information to the server. The server stores the received information in a database and uses it to evaluate the user's health condition.

[1579] 4. Recording emotional information

[1580] The user uses the emotion engine to automatically recognize and record their current emotional state. For example, if the user is feeling stressed, the emotion engine will recognize and record that state. The device then sends the emotional information to the server, which stores the received emotional information in a database. This information is used to analyze the user's emotional tendencies.

[1581] 5. Diet, exercise, and fasting recommendations

[1582] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary information, exercise information, health check information, and emotional information. For example, based on the user's data, recommendations such as "a balanced diet centered on vegetables" and "a 30-minute walk three times a week" may be made. Also, if the user is feeling stressed, recommendations such as "eating foods with a relaxing effect (chamomile tea)" may be made. This allows the user to consistently maintain their health.

[1583] 6. Health Status Generation

[1584] The server generates the user's latest health status based on the recorded health check information and emotional information. For example, if the result of the most recent health check is "good health," the server presents this result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays this notification to the user.

[1585] Hardware and software used

[1586] Hardware: Devices such as smartphones, smart glasses, and head-mounted displays

[1587] Software: Python program, emotion engine, cloud server, database

[1588] Specific examples

[1589] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records "good health," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that "good health" based on the results of the most recent health check.

[1590] Prompt Sentence Examples

[1591] User profile: "Diet information: oatmeal and fruit", "Exercise information: 30 minutes of jogging", "Health check information: good health", "Emotion information: stressed"

[1592] Based on this information, generate recommendations for appropriate diet, exercise, and relaxation methods and display them in your "Wellness Concierge."

[1593] In this way, users can input information using the system on a daily basis, collect emotional information through the emotion engine, and receive appropriate health care recommendations from the server based on this information, thereby maintaining their health and reducing medical costs.

[1594] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1595] Program processing steps

[1596] Step 1:

[1597] Enter and submit meal information

[1598] The user uses the device to input the details of the meal they have eaten. Specifically, if the user had "oatmeal and fruit" for breakfast, they enter that information into the application. The device converts the input meal information into a data format and sends it to the cloud server. The server stores the received data in a database.

[1599] Input: Meal information entered by the user

[1600] Data processing: The device converts the meal information into data format and sends it to the server.

[1601] Output: Meal information stored on the cloud server

[1602] Step 2:

[1603] Enter and submit exercise information

[1604] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information. The device converts the exercise information into a data format and sends it to the cloud server. The server stores the received exercise information in a database.

[1605] Input: Exercise information entered by the user

[1606] Data processing and calculation: The device converts the motion information into data format and sends it to the server.

[1607] Output: Exercise information stored on a cloud server

[1608] Step 3:

[1609] Enter and submit health check information

[1610] The user inputs the results of the health check into the device. For example, if the user's health condition is evaluated as "good," the user inputs the result. The device converts the health check information into a data format and sends it to the cloud server. The server stores the received health check information in a database.

[1611] Input: Health check information entered by the user

[1612] Data processing: The terminal converts the health check information into data format and sends it to the server.

[1613] Output: Health check information stored on the cloud server

[1614] Step 4:

[1615] Recording and transmitting emotional information

[1616] The user uses the emotion engine to automatically recognize their current emotional state. For example, if the user is feeling stressed, the emotion engine will recognize and record that state. The device then converts this emotional information into a data format and sends it to a cloud server. The server then stores the received emotional information in a database.

[1617] Input: Emotion information generated by the emotion engine

[1618] Data processing operation: The device converts the emotional information into data format and sends it to the server.

[1619] Output: Emotion information stored on the cloud server

[1620] Step 5:

[1621] Recommendation generation

[1622] The server makes recommendations for appropriate diet, exercise, and fasting to the user based on the recorded dietary information, exercise information, health check information, and emotional information. For example, recommendations such as "a balanced diet centered on vegetables" and "a 30-minute walk three times a week" may be made based on the user's data. Furthermore, if the user is feeling stressed, recommendations may include information such as "foods with a relaxing effect (e.g., chamomile tea)."

[1623] Input: Diet, exercise, health check, and emotional information stored in the database

[1624] Data processing: The server analyzes this information and generates appropriate recommendations for the user.

[1625] Output: Generated recommendations

[1626] Step 6:

[1627] Health status generation and notification

[1628] The server generates the user's latest health status based on the recorded health check information and emotional information. For example, if the result of the most recent health check is "good health," the server presents this result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays this notification to the user.

[1629] Input: Health check information and emotional information stored in the database

[1630] Data processing and calculation: The server analyzes this information and generates and notifies the user of their health status.

[1631] Output: Notifications and reminders of the user's health status

[1632] In this way, the system can provide appropriate health management and wellness content based on the user's input information.

[1633] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1634] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1635] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1636] [Fourth embodiment]

[1637] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1638] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1639] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1640] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1641] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1642] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1643] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1644] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1645] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1646] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1647] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1648] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1649] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1650] The system of the present invention aims to help users manage their own health and reduce medical costs. This system records dietary information, exercise information, and health check information entered by users, and based on this, makes recommendations for diet, exercise, and fasting, and generates the user's health status.

[1651] 1. Recording your dietary information

[1652] The user inputs the details of the meal they had into the device. For example, if they had "oatmeal and fruit for breakfast," they input that information. The device then sends this data to the server. The server stores the received meal information in a database. This information will be used to analyze the user's eating patterns in the future.

[1653] 2. Recording exercise information

[1654] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information. The device then sends this data to the server. The server stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[1655] 3. Recording health check information

[1656] The user inputs the results of the health check into the terminal. For example, the user may input the result "my health condition is good." The terminal then sends this data to the server. The server stores the received health check information in a database. This information is used to evaluate the user's health condition.

[1657] 4. Diet, exercise, and fasting recommendations

[1658] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary, exercise, and health check information. For example, based on the user's data, it may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." The device then displays these recommendations to the user.

[1659] 5. Health Status Generation

[1660] The server generates the user's latest health status based on the recorded health check information. For example, if the result of the most recent health check is "good health," the server presents that result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays the notification to the user.

[1661] Specific examples

[1662] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, the user underwent a health check and recorded as being in "good health." The server records this information, and when the user accesses the system on January 2nd, it recommends "a balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month." It also presents the information that "the user is in good health" based on the results of the most recent health check.

[1663] In this way, users can maintain their health and reduce medical expenses by inputting information into the system on a daily basis and receiving appropriate health care recommendations from the server via their terminal.

[1664] The processing flow will be explained below.

[1665] Program processing steps

[1666] 1. Recording your dietary information

[1667] Step 1:

[1668] User: Eats "oatmeal and fruit" for breakfast, then enters the meal details into the device.

[1669] Step 2:

[1670] User: Enters "oatmeal and fruit" into the device's input form and presses the submit button.

[1671] Step 3:

[1672] Terminal: Sends the meal details entered by the user to the server.

[1673] Step 4:

[1674] Server: Save the received meal information in the "meals" list. This list is stored in the form of a dictionary of dates and meal information.

[1675] Step 5:

[1676] Server: Confirms that the meal record was saved successfully and sends a confirmation message to the user.

[1677] 2. Recording exercise information

[1678] Step 1:

[1679] User: Goes for a 30-minute jog, then enters the details of the exercise into the device.

[1680] Step 2:

[1681] User: Enter "30 minutes of jogging" into the device's input form and press the send button.

[1682] Step 3:

[1683] Terminal: Sends the exercise information entered by the user to the server.

[1684] Step 4:

[1685] Server: Saves the received exercise details in the "exercises" list. This list is stored in the form of a dictionary of dates and exercise details.

[1686] Step 5:

[1687] Server: Confirms that the exercise record was saved successfully and sends a confirmation message to the user.

[1688] 3. Recording health check information

[1689] Step 1:

[1690] User: Takes a health check and enters the result "I am in good health" into the terminal.

[1691] Step 2:

[1692] User: Enters "My health is good" into the input form on the device and presses the send button.

[1693] Step 3:

[1694] Terminal: Sends the health check information entered by the user to the server.

[1695] Step 4:

[1696] Server: Save the received health check information in the "health_checks" list. This list is stored in the form of a dictionary of dates and health information.

[1697] Step 5:

[1698] Server: Confirm that the health check record was saved successfully and send a confirmation message to the user.

[1699] 4. Dietary Recommendations

[1700] Step 1:

[1701] User: Requests food recommendations from the server via the device.

[1702] Step 2:

[1703] Server: Receives the request and executes the meal recommendation logic based on the stored meal information.

[1704] Step 3:

[1705] Server: Generate the recommendation "balanced vegetable-based meal."

[1706] Step 4:

[1707] Server: Sends recommendations to the user.

[1708] Step 5:

[1709] Device: Displays meal recommendations to the user.

[1710] 5. Exercise Recommendations

[1711] Step 1:

[1712] User: Requests exercise recommendations from the server via the device.

[1713] Step 2:

[1714] Server: Receives the request and executes the exercise recommendation logic based on the stored exercise information.

[1715] Step 3:

[1716] Server: Generate the recommendation "Take a 30-minute walk three times a week."

[1717] Step 4:

[1718] Server: Sends recommendations to the user.

[1719] Step 5:

[1720] Device: Display exercise recommendations to the user.

[1721] 6. Fasting recommendations

[1722] Step 1:

[1723] User: Requests fasting recommendations from the server via the device.

[1724] Step 2:

[1725] Server: Receives the request and executes the fasting recommendation logic.

[1726] Step 3:

[1727] Server: Generate the recommendation "24-hour fast once a month."

[1728] Step 4:

[1729] Server: Sends recommendations to the user.

[1730] Step 5:

[1731] Device: Display fasting recommendations to the user.

[1732] 7. Health Status Generation

[1733] Step 1:

[1734] User: Requests the server to generate a health status via the terminal.

[1735] Step 2:

[1736] Server: Receives the request and executes the logic to generate the user's health status based on the stored health check information.

[1737] Step 3:

[1738] Server: Generates a health status of "good health" based on the latest health check results.

[1739] Step 4:

[1740] Server: Sends the generated health status to the user.

[1741] Step 5:

[1742] Terminal: Display health status to the user.

[1743] Example 1

[1744] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1745] In modern society, individual health management and rising medical costs are becoming serious issues. Current health management systems allow users to input and track their own health data, but they lack effective utilization and optimal health management recommendations. The data entered by users is stored fragmentedly, preventing unified health management advice, making it difficult to improve users' health. Furthermore, users may not receive notifications even if appropriate health checks are not performed, which increases the risk of users neglecting to check their health.

[1746] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1747] In this invention, the server includes a means for recording dietary information entered by the user, a means for recording exercise information entered by the user, a means for recording health check information entered by the user, a means for storing the recorded dietary information, exercise information, and health check information in a database, a means for making diet, exercise, and fasting recommendations using a machine learning algorithm based on the recorded dietary information, exercise information, and health check information, a means for notifying the terminal of the recommendations, and a means for generating the user's health status based on the recorded health check information. This makes it possible to centrally manage health-related data entered by the user and provide optimal health management recommendations using a machine learning algorithm. Furthermore, by providing a notification even if a health check has not been performed, the server can encourage the user to perform a health check.

[1748] "User" refers to an individual who uses the system and is the entity that inputs data such as dietary information, exercise information, and health check information.

[1749] "Terminal" refers to an electronic device used to send data entered by a user to a server, including smartphones and tablets.

[1750] "Dietary information" refers to data relating to the types and amounts of food consumed by the user, and is information for recording the user's nutritional intake status.

[1751] "Exercise information" refers to data relating to the type and duration of exercise performed by the user, and is information for recording the user's exercise status.

[1752] "Health check information" refers to data such as diagnostic results and self-assessment regarding the user's health condition, and is information for evaluating the user's health condition.

[1753] "Server" refers to a centralized computer system that receives, processes, and stores data submitted by users, including databases and analytical algorithms.

[1754] A "database" refers to a digital archive for storing a user's dietary information, exercise information, health check information, etc. in a structured manner, making it easy to search and manage information.

[1755] A "machine learning algorithm" refers to a computational method for discovering patterns based on accumulated data and making predictions and recommendations, and is used in data analysis and building predictive models.

[1756] "Recommendations" refers to health management advice and suggestions for users generated by machine learning algorithms, including diet, exercise, fasting, etc.

[1757] "Notification means" refers to methods for informing users of information such as recommendations and the need for health checks, and includes push notifications and dashboard displays.

[1758] The system of the present invention aims to enable users to manage their own health and reduce medical costs. This system records dietary information, exercise information, and health check information entered by the user, and based on this information, makes recommendations for diet, exercise, and fasting, thereby generating a health status report for the user. Specific embodiments of this system are described below.

[1759] System Configuration

[1760] User

[1761] Users access the system using devices such as smartphones and tablets, which have a dedicated health management app installed.

[1762] Terminal

[1763] The device accepts information about meals, exercise, and health checks entered by the user. This information is converted into JSON format and sent to the server using the HTTPS protocol.

[1764] The device is responsible for displaying recommendations and health check notifications to the user. It uses a push notification service (e.g., Firebase Cloud Messaging) to notify the user.

[1765] server

[1766] The server is built using a cloud service (e.g., a general cloud computing platform). The server has the following roles:

[1767] 1. Data reception: Receives meal information, exercise information, and health check information sent by users. This is done using an API using the Flask framework.

[1768] 2. Data storage: The received data is stored in a MySQL database. The database is divided into a "meal information table," a "exercise information table," and a "health check information table."

[1769] 3. Data analysis: Periodically, a scheduler (e.g., cron job) is used to analyze the recorded data using machine learning algorithms (e.g., Scikit-learn), which then generates appropriate diet, exercise, and fasting recommendations for the user.

[1770] 4. Health Status Generation: Generates the latest health status based on the recorded health check information. If necessary, notifies the user that a health check is required.

[1771] Specific examples

[1772] For example, if a user eats "oatmeal and fruit" for breakfast on January 1st, goes "30 minutes jogging" on the same day, and records a health check as "good health," the server records this information, and when the user accesses the system on January 2nd, it provides the following recommendations:

[1773] A balanced diet centered around vegetables

[1774] 30-minute walks three times a week

[1775] 24-hour fasting once a month

[1776] It also displays "good health" based on the results of the most recent health check. In this way, users can input information into the system on a daily basis and receive appropriate health management recommendations from the server via their terminal, thereby maintaining their health and reducing medical costs.

[1777] Example of input prompt for generative AI model

[1778] "I would like to design a user interface for a health management system. Please suggest a design for a form that allows users to easily enter information about their diet, exercise, and health checks."

[1779] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1780] Step 1:

[1781] A user opens a smartphone app and inputs the details of the meal they had. For example, they input "oatmeal and fruit for breakfast." The device converts this input information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed data about the meal, and the device converts it into JSON format and sends it.

[1782] Step 2:

[1783] The server receives the meal information using an API built with the Flask framework. It parses the received data and stores it in a MySQL "meal information" table. The input is JSON-formatted meal information data, which is parsed and stored in the database.

[1784] Step 3:

[1785] The user uses the same app to input the details of the exercise they performed. For example, they input "30 minutes of jogging." The device converts this exercise information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed exercise data, which is then converted into JSON format and sent.

[1786] Step 4:

[1787] The server processes the received exercise information using the Flask API, parses the data, and saves it in the MySQL "exercise information" table. The input is exercise information data in JSON format, which is parsed and stored in the database.

[1788] Step 5:

[1789] The user enters the results of their health check into the app. For example, they might enter "My health is good." The device converts this health check information into JSON format and sends it to the server using the HTTPS protocol. The input is detailed health check data, which is then converted into JSON format and sent.

[1790] Step 6:

[1791] The server processes the received health check information through the Flask API, parses the data, and saves it in the MySQL "health check information" table. The input is health check information data in JSON format, which is parsed and stored in the database.

[1792] Step 7:

[1793] The server periodically uses a scheduler (e.g., cron job) to perform data analysis based on the recorded dietary information, exercise information, and health check information. This process uses Python and Scikit-learn. As a result of the analysis, it generates optimal diet, exercise, and fasting recommendations for the user. The input is multiple pieces of information obtained from the database, which are then analyzed and the recommendations are output.

[1794] Step 8:

[1795] The server sends the generated recommendation to the user's device. The device uses the Firebase Cloud Messaging service to send a push notification to the user to notify them of the new recommendation. When the user taps the notification, they can view the detailed recommendation within the app. The input is the generated recommendation, and the operation to send it to the user via a push notification is performed.

[1796] Step 9:

[1797] The server generates the user's latest health status based on the periodically saved health check information. For example, if the most recent health check result is "good health," the server presents that result to the user. The input is health check information retrieved from the database, and the server evaluates it and outputs the latest health status.

[1798] Step 10:

[1799] If there is no health check record, the server uses Firebase Cloud Messaging to notify the user that a "health check is required." The device receives this notification and displays it on the app's dashboard. The input is whether or not there is a health check record, and the notification action is performed based on that.

[1800] (Application example 1)

[1801] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1802] Conventional health management systems require users to manually input information about their diet and exercise, and suffer from issues such as a lack of data accuracy and real-time performance. Furthermore, there are only limited systems that utilize accumulated data to provide effective health management recommendations. This has resulted in a lack of an optimal approach for efficiently managing users' health status and reducing medical costs.

[1803] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1804] In this invention, the server includes a means for transmitting dietary information, exercise information, and health check information manually input by the user to the server, a means for automatically recording the user's exercise data and dietary data using hardware functions such as an exercise sensor and a barcode scanner and transmitting the data to the server, a means for analyzing the data accumulated by the server using a machine learning algorithm to generate appropriate diet, exercise, and fasting recommendations for the user, and a means for notifying the user of the recommendations. This allows users to efficiently accumulate health management information by utilizing both manual input and automatic recording, and to receive optimal health management recommendations for each individual user through the machine learning algorithm.

[1805] "Dietary information" refers to data about the contents of the foods and drinks consumed by the user.

[1806] "Exercise information" refers to data regarding the type, duration, and intensity of exercise performed by the user.

[1807] "Health check information" refers to data related to the user's health condition, such as weight, blood pressure, and heart rate.

[1808] A "server" is a computer system that stores and analyzes data sent by users and provides necessary information.

[1809] "Recommendation" refers to providing optimal diet, exercise, and fasting advice based on the user's health data.

[1810] An "exercise sensor" is a device for detecting a user's exercise status, and is a device for measuring the number of steps, distance, calorie consumption, etc.

[1811] "Barcode scanning" is the act of reading the barcode of food or products and recording that information as data.

[1812] A "machine learning algorithm" is a program that analyzes the data received by the server, finds patterns, and generates optimal recommendations for users.

[1813] "Notification" refers to the act of informing the user of the generated recommendations and necessary health check information.

[1814] A "smartphone" is a multi-function mobile phone that can connect to the Internet and use applications.

[1815] "Smart glasses" are wearable devices that can provide information visually.

[1816] A "smartwatch" is a wearable device that has a built-in motion sensor and measures the user's biometric information and motion data.

[1817] The system for implementing this invention aims to record dietary information, exercise information, and health check information entered by users and provide appropriate health management recommendations. The main components of the system include devices such as smartphones, smart glasses, and smart watches, and a server that performs data analysis.

[1818] System Structure

[1819] 1. Recording your dietary information:

[1820] Users can use their smartphones or smart glasses to input meal information by scanning barcodes or by voice input. For example, they can use their smartphone's camera to scan food barcodes and input "I had oatmeal and fruit for breakfast."

[1821] The device sends the entered meal information to the server, and the server stores the received data in a database (e.g., Firebase, Google Cloud Firestore).

[1822] 2. Recording exercise information:

[1823] The smartwatch's motion sensor automatically records the user's motion data. For example, if you go for a 30-minute jog, the smartwatch will record that motion data.

[1824] The device transfers this data to a smartphone via Bluetooth, which then sends it to a server, which stores the data in a database.

[1825] 3. Recording Health Check Information:

[1826] Users enter their health check information (weight, blood pressure, heart rate, etc.) through the app. For example, if their weight is 65 kg, their blood pressure is 120 / 80 mmHg, and their heart rate is 70 bpm, they enter that information into their smartphone.

[1827] The terminal sends the input information to the server, which stores it in a database.

[1828] 4. Health Care Recommendations:

[1829] The server analyzes the collected data using machine learning algorithms (e.g., TensorFlow) to generate recommendations for diet, exercise, and fasting. For example, based on the analysis of the user's diet and exercise information, it may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month."

[1830] The device will notify the user of the recommendations, for example, by displaying them on the HUD (heads-up display) of smart glasses or via a pop-up notification on a smartphone.

[1831] 5. Health generation:

[1832] The server analyzes the user's latest health status based on the recorded health check information. For example, if the result of the most recent health check is "good health," the server presents that information to the user.

[1833] If the health status is not recorded, the server will notify the user that a health check is required.

[1834] Specific examples

[1835] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went on a "30-minute jog" on the same day. If this user also records "weight 65 kg, blood pressure 120 / 80 mmHg, heart rate 70 bpm" during a health check, the server will record this information, and when the user accesses the system on January 2nd, it will recommend "a balanced diet centered on vegetables," "30-minute walks three times a week," and "24-hour fasting once a month." It will also present the latest health check result as "good health."

[1836] Prompt Sentence Examples

[1837] Q: What was the last thing you ate?

[1838] How to register your meal information:

[1839] Scan the barcode with your camera or say, "I had oatmeal and fruit."

[1840] In this way, the system aims to enable users to efficiently manage their health and reduce medical costs by inputting their health information on a daily basis and receiving recommendations for appropriate health care.

[1841] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1842] Step 1:

[1843] Users can input meal information using their smartphones or smart glasses. For example, they can scan the barcode of a food item with their smartphone camera and input that they had "oatmeal and fruit for breakfast." This information is then sent to the device.

[1844] Input: Meal information (e.g., "oatmeal and fruit")

[1845] Output: Meal data (e.g., {"meal": "oatmeal and fruit"})

[1846] Step 2:

[1847] The device sends the entered meal information to the server. The device sends the meal data to the server's API endpoint, and the server receives the data and stores it in a database (e.g., Firebase, Google Cloud Firestore).

[1848] Input: Sending food data from device to server

[1849] Output: Meal data stored in the server database (e.g. {"meal": "oatmeal and fruit"})

[1850] Step 3:

[1851] The smartwatch automatically detects and records the exercise the user performs. For example, if you jog for 30 minutes, the smartwatch records that data. The smartwatch then transfers this data to your smartphone via Bluetooth.

[1852] Input: User's exercise data (e.g., {"activity": "jogging", "duration": 30})

[1853] Output: Exercise data transferred to a smartphone

[1854] Step 4:

[1855] The smartphone sends the received exercise data to a server, which receives the data and stores it in a database.

[1856] Input: Exercise data sent from smartphone to server

[1857] Output: Exercise data stored in the server database (e.g. {"activity": "jogging", "duration": 30})

[1858] Step 5:

[1859] The user enters health check information through the app. For example, "weight 65 kg, blood pressure 120 / 80 mmHg, heart rate 70 bpm." The device (smartphone) then sends this information to the server.

[1860] Input: Health check information (e.g., {"weight": 65, "blood_pressure": "120 / 80", "heart_rate": 70})

[1861] Output: Health data sent to the server

[1862] Step 6:

[1863] After receiving the health check information, the server stores it in a database, which is used for analysis.

[1864] Input: Request to save health check information

[1865] Output: Health data stored in a database

[1866] Step 7:

[1867] The server analyzes the collected dietary, exercise, and health check information using machine learning algorithms (e.g., TensorFlow). The server finds correlations between each piece of data and generates optimal diet, exercise, and fasting recommendations for the user. For example, it may generate recommendations such as "a balanced diet centered on vegetables," "a 30-minute walk three times a week," and "a 24-hour fast once a month."

[1868] Input: Various health data stored in the database

[1869] Output: Recommendation (e.g., {"diet_recommendation": "Balanced, plant-based diet", "exercise_recommendation": "30-minute walks three times a week", "fasting_recommendation": "24-hour fast once a month"})

[1870] Step 8:

[1871] The device (smartphone, smart glasses, etc.) notifies the user of the generated recommendation content, for example, by displaying it on the smart glasses' HUD (heads-up display) or via a pop-up notification on the smartphone.

[1872] Input: Recommendation

[1873] Output: Notification to the user (e.g. smartphone notification, smart glasses display)

[1874] Step 9:

[1875] The server evaluates the user's latest health status based on the recorded health check information and presents the results to the user. For example, it may notify the user that their health status is good. Furthermore, if a health check has not been recorded, it may notify the user that they need to take a health check again.

[1876] Input: Health check data

[1877] Output: Health status notification to user (e.g. "Your health is good"), reminders when a health check is needed

[1878] Through the above steps, the system can comprehensively collect and analyze the user's health care information and provide recommendations for optimal health care.

[1879] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1880] The system of the present invention aims to help users manage their own health and reduce medical costs. In addition to dietary information, exercise information, and health check information, the system records the user's emotional information and can adapt the recommendations based on that information.

[1881] 1. Recording your dietary information

[1882] The user inputs the details of the meal they had into the device. For example, if they had "oatmeal and fruit for breakfast," they input that information. The device then sends this data to the server. The server stores the received meal information in a database. This information will be used to analyze the user's eating patterns in the future.

[1883] 2. Recording exercise information

[1884] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information. The device then sends this data to the server. The server stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[1885] 3. Recording health check information

[1886] The user inputs the results of the health check into the terminal. For example, the user may input the result "my health condition is good." The terminal then sends this data to the server. The server stores the received health check information in a database. This information is used to evaluate the user's health condition.

[1887] 4. Recording emotional information

[1888] The user automatically recognizes their current emotional state through the emotion engine. For example, if the user is feeling stressed, the emotion engine recognizes and records that information. The device then sends this data to a server, which stores the received emotional information in a database. This information is used to analyze the user's emotional tendencies.

[1889] 5. Diet, exercise, and fasting recommendations

[1890] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary information, exercise information, health check information, and emotional information. For example, based on the user's data, it may recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." If the user is feeling stressed, it may recommend "foods that have a relaxing effect." The device then displays these recommendations to the user.

[1891] 6. Health Status Generation

[1892] The server generates the user's latest health status based on the recorded health check information and emotional information. For example, if the result of the most recent health check is "good health," the server presents that result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays the notification to the user.

[1893] Specific examples

[1894] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records that their health is "good," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that the user is "in good health" based on the results of the most recent health check.

[1895] In this way, users can input information into the system on a daily basis, collect emotional information through the emotion engine, and receive appropriate health care recommendations from the server based on this information, thereby maintaining their health and reducing medical costs. This system allows users to effectively manage both their health and emotional states.

[1896] The processing flow will be explained below.

[1897] Program processing steps

[1898] 1. Recording your dietary information

[1899] Step 1:

[1900] User: Eats "oatmeal and fruit" for breakfast, then enters the meal details into the device.

[1901] Step 2:

[1902] User: Enters "oatmeal and fruit" into the device's input form and presses the submit button.

[1903] Step 3:

[1904] Terminal: Sends the meal details entered by the user to the server.

[1905] Step 4:

[1906] Server: Save the received meal information in the "meals" list. This list is stored in the form of a dictionary of dates and meal information.

[1907] Step 5:

[1908] Server: Confirms that the meal record was saved successfully and sends a confirmation message to the user.

[1909] 2. Recording exercise information

[1910] Step 1:

[1911] User: Goes for a 30-minute jog, then enters the details of the exercise into the device.

[1912] Step 2:

[1913] User: Enter "30 minutes of jogging" into the device's input form and press the send button.

[1914] Step 3:

[1915] Terminal: Sends the exercise information entered by the user to the server.

[1916] Step 4:

[1917] Server: Saves the received exercise details in the "exercises" list. This list is stored in the form of a dictionary of dates and exercise details.

[1918] Step 5:

[1919] Server: Confirms that the exercise record was saved successfully and sends a confirmation message to the user.

[1920] 3. Recording health check information

[1921] Step 1:

[1922] User: Takes a health check and enters the result "I am in good health" into the terminal.

[1923] Step 2:

[1924] User: Enters "My health is good" into the input form on the device and presses the send button.

[1925] Step 3:

[1926] Terminal: Sends the health check information entered by the user to the server.

[1927] Step 4:

[1928] Server: Save the received health check information in the "health_checks" list. This list is stored in the form of a dictionary of dates and health information.

[1929] Step 5:

[1930] Server: Confirm that the health check record was saved successfully and send a confirmation message to the user.

[1931] 4. Recording emotional information

[1932] Step 1:

[1933] Emotion engine: The system automatically recognizes emotions without the user having to input their current emotional state. For example, the emotion engine recognizes that the user is feeling stressed.

[1934] Step 2:

[1935] Terminal: The emotion engine sends the recognized emotion information to the server.

[1936] Step 3:

[1937] Server: Save the received emotion information in the "emotions" list. This list is stored in the form of a dictionary of dates and emotion information.

[1938] Step 4:

[1939] Server: Checks that the emotion recording was saved successfully and sends a confirmation message to the user.

[1940] 5. Dietary Recommendations

[1941] Step 1:

[1942] User: Requests food recommendations from the server via the device.

[1943] Step 2:

[1944] Server: Receives the request and executes the meal recommendation logic based on the stored meal information.

[1945] Step 3:

[1946] Server: Generate the recommendation "balanced vegetable-based meal."

[1947] Step 4:

[1948] Server: We also consider "foods that have a relaxing effect" (e.g., chamomile tea) based on emotional information.

[1949] Step 5:

[1950] Server: Sends recommendations to the user.

[1951] Step 6:

[1952] Device: Displays meal recommendations to the user.

[1953] 6. Exercise Recommendations

[1954] Step 1:

[1955] User: Requests exercise recommendations from the server via the device.

[1956] Step 2:

[1957] Server: Receives the request and executes the exercise recommendation logic based on the stored exercise information.

[1958] Step 3:

[1959] Server: Generate the recommendation "Take a 30-minute walk three times a week."

[1960] Step 4:

[1961] Server: We also consider "stress reduction exercise" (e.g., yoga) based on emotional information.

[1962] Step 5:

[1963] Server: Sends recommendations to the user.

[1964] Step 6:

[1965] Device: Display exercise recommendations to the user.

[1966] 7. Fasting Recommendations

[1967] Step 1:

[1968] User: Requests fasting recommendations from the server via the device.

[1969] Step 2:

[1970] Server: Receives the request and executes the fasting recommendation logic.

[1971] Step 3:

[1972] Server: Generate the recommendation "24-hour fast once a month."

[1973] Step 4:

[1974] Server: Sends recommendations to the user.

[1975] Step 5:

[1976] Device: Display fasting recommendations to the user.

[1977] 8. Health Status Generation

[1978] Step 1:

[1979] User: Requests the server to generate a health status via the terminal.

[1980] Step 2:

[1981] Server: Receives the request and executes the logic for generating the user's health status based on the stored health check information and emotion information.

[1982] Step 3:

[1983] Server: Generates a health status of "good health" based on the latest health check results.

[1984] Step 4:

[1985] Server: Sends the generated health status to the user.

[1986] Step 5:

[1987] Terminal: Display health status to the user.

[1988] Example 2

[1989] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1990] Conventional health management systems have had problems in that it is difficult for users to comprehensively manage their own health status, and they are unable to quickly obtain appropriate advice based on new health status or emotional information. Furthermore, they lack an approach that takes into account the impact of stress and emotional changes on health, making it impossible to provide optimal health management for individual users.

[1991] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1992] In this invention, the server includes means for recording dietary information input by the user, means for recording exercise information input by the user, means for recording health check information input by the user, means for automatically recognizing and recording emotional information, means for recommending diet, exercise, and fasting based on the recorded dietary information, exercise information, health check information, and emotional information, and means for generating the user's health status based on the recorded health check information and emotional information. This allows the user to comprehensively manage both their health status and emotional state, and to receive appropriate health management advice in a timely manner.

[1993] A "user" is an individual who uses the health management system to record their own dietary information, exercise information, health check information, and emotional information.

[1994] A "server" is a processing device for receiving, storing, analyzing, and providing recommendations and notifications for data sent by users.

[1995] "Terminal" refers to a device that allows a user to input information about their diet, exercise, health checks, and emotions. Specifically, this refers to a smartphone or PC.

[1996] "Dietary information" is data related to meals consumed by a user, including the contents of meals at a specific point in time.

[1997] "Exercise information" is data related to the exercise performed by the user, including the specific exercise content and exercise time.

[1998] "Health check information" is data relating to the results of a health status evaluation that a user periodically performs.

[1999] "Emotion information" is data that indicates the user's emotional state, and is automatically recognized and recorded using an emotion engine or the like.

[2000] An "emotion engine" is software or hardware that analyzes the user's emotional state and outputs the results as data.

[2001] "Recommendations" are health care advice or instructions generated by the server based on the user's recorded data.

[2002] A "generative AI model" is an artificial intelligence algorithm used by the server to analyze collected data and make optimal recommendations to users.

[2003] A "prompt sentence" is a sentence indicating an instruction or question that the system asks the user.

[2004] The system of the present invention aims to enable users to manage their own health and reduce medical costs. This system records the user's dietary information, exercise information, health check information, and emotional information, and makes appropriate recommendations based on this information. Specific embodiments of the system are described below.

[2005] Recording food information

[2006] The user inputs the details of the meal they have eaten into the device. For example, they input "oatmeal and fruit for breakfast." The device sends this data to the server as an HTTP request. The server analyzes the received meal information and saves the "date, meal details, and user ID" in a database using SQL statements. This information is used to analyze the user's eating patterns.

[2007] Recording exercise information

[2008] The user enters the details of the exercise they performed into the device. For example, they enter "30 minutes of jogging." The device then sends the exercise information to the server as an HTTP request. The server analyzes the received exercise information and uses SQL statements to store the "date, exercise details, and user ID" in a database. This information is used to analyze the user's exercise habits.

[2009] Recording health check information

[2010] The user enters the results of their health check into the terminal. For example, they enter "My health condition is good." The terminal sends the health check information to the server as an HTTP request. The server analyzes the received health check information and uses SQL statements to store the "date, health check details, and user ID" in a database. This information is used to evaluate the user's health condition.

[2011] Recording emotional information

[2012] The user uses the emotion engine to automatically recognize their current emotional state. For example, if the user is feeling stressed, the emotion engine will recognize and record that information. The device then sends the emotional information to the server as an HTTP request. The server then analyzes the received emotional information and uses SQL statements to store the date, emotional state, and user ID in a database. This information is then used to analyze the user's emotional tendencies.

[2013] Diet, exercise, and fasting recommendations

[2014] The server references the dietary information, exercise information, health check information, and emotional information in the database, and integrates and analyzes them. The server uses the generative AI model to recommend optimal diet, exercise, and fasting for the user. For example, it might recommend a "balanced diet centered on vegetables," "a 30-minute walk three times a week," or "a 24-hour fast once a month." If the user is feeling stressed, it might also recommend "foods with a relaxing effect (e.g., chamomile tea)." The generated recommendations are sent to the device, which displays them to the user.

[2015] Health state generation

[2016] The server generates the user's current health status based on the recorded health check information and emotional information. For example, if the result of a recent health check is "good health," the server notifies the user of that result. If no record exists, the server notifies the user that a health check is necessary. The terminal displays these notifications to the user.

[2017] Specific example explanation

[2018] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records that their health is "good," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that the user is "in good health" based on the results of the most recent health check.

[2019] In this way, users can input information into the system on a daily basis, and by collecting emotional information through the emotion engine, the server can recommend appropriate health care. This system allows users to effectively manage both their health and emotional states.

[2020] Prompt Sentence Examples

[2021] 1. "What did you eat today? Example: Oatmeal and fruit for breakfast."

[2022] 2. "Please enter the exercise you did today. Example: 30 minutes of jogging."

[2023] 3. "Please enter the results of your most recent health check. Example: I am in good health."

[2024] 4. Check the emotion engine results. Example: Stress state.

[2025] 5. "Would you like to see today's food and exercise recommendations?"

[2026] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2027] Step 1: Enter your meal information

[2028] The user inputs the details of the meal they have eaten into the terminal, for example, "oatmeal and fruit for breakfast."

[2029] Input: Meal details (e.g., "Oatmeal and fruit for breakfast")

[2030] Output: HTTP request sent to the terminal

[2031] Step 2: Submit your meal information

[2032] The device generates an HTTP request to send the input meal information to the server. The HTTP request includes the meal details, date and time, and the user ID.

[2033] Input: Meal information (e.g., "Oatmeal and fruit for breakfast"), date and time, user ID

[2034] Output: HTTP request sent to the server

[2035] Step 3: Save your meal information

[2036] The server stores the received meal information in a database. The server first analyzes the HTTP request and extracts the data. Then it generates an SQL statement and inserts the "date, meal content, and user ID" into the database.

[2037] Input: HTTP request (meal information, date and time, user ID)

[2038] Output: Save results to database

[2039] Step 4: Enter your exercise information

[2040] The user inputs the details of the exercise he or she has done into the terminal. For example, the user inputs "30 minutes of jogging."

[2041] Input: Exercise content (e.g., "30 minutes of jogging")

[2042] Output: HTTP request sent to the terminal

[2043] Step 5: Sending exercise information

[2044] The device generates an HTTP request to send the input exercise information to the server. The HTTP request includes the exercise details, date and time, and the user ID.

[2045] Input: Exercise information (e.g., "30 minutes of jogging"), date and time, user ID

[2046] Output: HTTP request sent to the server

[2047] Step 6: Save your exercise information

[2048] The server stores the received exercise information in a database. It analyzes the HTTP request, extracts the necessary data, and then generates an SQL statement to insert the "date, exercise content, and user ID" into the database.

[2049] Input: HTTP request (exercise information, date and time, user ID)

[2050] Output: Save results to database

[2051] Step 7: Enter your health check information

[2052] The user inputs the results of the health check into the terminal. For example, the user inputs "my health is good."

[2053] Input: Health check details (e.g. "I am in good health")

[2054] Output: HTTP request sent to the terminal

[2055] Step 8: Submit your health check information

[2056] The terminal generates an HTTP request to send the entered health check information to the server. The HTTP request includes the health check details, date and time, and user ID.

[2057] Input: Health check information (e.g., "My health is good"), date and time, user ID

[2058] Output: HTTP request sent to the server

[2059] Step 9: Save your health check information

[2060] The server saves the received health check information in a database. It analyzes the HTTP request, extracts the necessary data, and then generates an SQL statement to insert the date, health check details, and user ID into the database.

[2061] Input: HTTP request (health check information, date and time, user ID)

[2062] Output: Save results to database

[2063] Step 10: Recognizing Emotional Information

[2064] The user automatically recognizes their current emotional state using the emotion engine, which uses biometric sensors and other input devices to analyze the user's emotional state.

[2065] Input: Data from biometric sensors (e.g., heart rate, facial expression)

[2066] Output: Perceived emotional state (e.g., "stressed")

[2067] Step 11: Sending Emotional Information

[2068] The device generates an HTTP request to send the recognized emotion information to the server, which includes the emotional state, the date and time, and the user ID.

[2069] Input: Emotion information (e.g., "stress state"), date and time, user ID

[2070] Output: HTTP request sent to the server

[2071] Step 12: Storing Emotional Information

[2072] The server stores the received emotional information in a database by parsing the HTTP request, extracting the emotional state, and then inserting the date, emotional state, and user ID into the database using an SQL statement.

[2073] Input: HTTP request (emotion information, date and time, user ID)

[2074] Output: Save results to database

[2075] Step 13: Generate recommendations

[2076] The server integrates and analyzes the dietary, exercise, health check, and emotional information stored in the database, and uses a generative AI model to generate optimal diet, exercise, and fasting recommendations for the user.

[2077] Input: Various information in the database (diet, exercise, health check, emotions)

[2078] Output: Recommendation (e.g., "Eat a balanced diet centered on vegetables," "Take a 30-minute walk three times a week," "Fast for 24 hours once a month")

[2079] Step 14: Submit and view your recommendation

[2080] The server sends the generated recommendations to the terminal, which then displays them to the user.

[2081] Input: Generated recommendation

[2082] Output: Recommendation to be displayed to the user (e.g., "Eat a balanced diet centered around vegetables")

[2083] Step 15: Generate Health States

[2084] The server generates the current health status of the user based on the recorded health check information and emotional information.

[2085] Input: Health check information and emotion information in the database

[2086] Output: The generated health status (e.g. "Your health is good")

[2087] Step 16: Health Status Notification

[2088] The server sends the generated health status to the terminal, which displays it to the user. If the user's health check information is not recorded, the terminal notifies the user that a health check is required.

[2089] Input: Current health status or notification of missing check

[2090] Output: Health status information or notification displayed to the user (e.g., "Your health is good," "Please take a health check")

[2091] (Application example 2)

[2092] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2093] Conventional health management systems provide simple recommendations based only on dietary information, exercise information, and health check information. However, because they do not take the user's emotional state into account, they are insufficient for maintaining a consistent health status or managing stress. Furthermore, health management content is not personalized, failing to meet the needs of individual users. The present invention aims to solve these problems and provide personalized health management and wellness content tailored to the user's emotional state.

[2094] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2095] In this invention, the server includes means for recording dietary information input by a user, means for recording exercise information input by a user, means for recording health check information and emotional information input by a user, means for recommending diet, exercise, and fasting based on the recorded dietary information, exercise information, health check information, and emotional information, means for generating a user's health status based on the recorded health check information and emotional information, means for notifying the user that a health check is necessary if a health status has not been recorded, means for providing health management content to the user based on the recorded emotional information, and means for transmitting the dietary information, exercise information, health check information, and emotional information input by the user to the server. This enables personalized health management and stress management while taking the user's emotional state into consideration.

[2096] Creating definition statements

[2097] "User" means an individual who utilizes the system to record dietary information, exercise information, health check information, and emotional information, and who interacts with the system to receive health management and wellness content.

[2098] "Input" refers to the act of a user providing dietary information, exercise information, health check information, and emotional information to the system via an interface such as a keyboard or voice input.

[2099] "Dietary information" refers to data relating to the content and quantity of food consumed by the user.

[2100] "Exercise information" refers to data regarding the type, duration, and intensity of exercise performed by the user.

[2101] "Health check information" refers to data on the user's blood pressure, weight, body temperature, and other measurement and diagnosis results related to their health condition.

[2102] "Emotion information" refers to data relating to the user's emotional state, such as stress or relaxation.

[2103] "Recording" refers to the act of saving information entered by a user within a system or on a server.

[2104] "Recommendations" means suggestions and advice regarding diet, exercise, and fasting that the system provides to the user based on the recorded information.

[2105] "Generation" refers to the act of the system analyzing the recorded information and creating the user's latest health status and appropriate health management content.

[2106] "Notification" refers to the act of a system sending a message or alert to a user under certain conditions.

[2107] "Health Management Content" refers to personalized advice and information provided based on a user's health and emotional state.

[2108] A "server" is a computing device that receives and stores user-entered data and makes recommendations and analyses based on the recorded information.

[2109] MODE FOR CARRYING OUT THE INVENTION

[2110] A system for implementing the present invention aims to enable a user to manage their health status and provide personalized health management content. This system is implemented using a device such as a smartphone, smart glasses, or a head-mounted display. The configuration and operation of the system are described below.

[2111] 1. Recording your dietary information

[2112] The user inputs the details of the meal they ate into the device. For example, if they had "oatmeal and fruit" for breakfast, they input that information into the device. The device then sends this meal information to the server, which stores the received data in a database. This information is used to analyze future eating patterns.

[2113] 2. Recording exercise information

[2114] The user inputs the details of the exercise they performed into the device. For example, if they performed a 30-minute jog, they input that information into the device. The device then sends this exercise information to the server. The server then stores the received exercise information in a database. This information is used to analyze the user's exercise habits.

[2115] 3. Recording health check information

[2116] The user inputs the results of the health check into the terminal. For example, if the user's health condition is evaluated as "good," the user inputs the result into the terminal. The terminal then sends this health check information to the server. The server stores the received information in a database and uses it to evaluate the user's health condition.

[2117] 4. Recording emotional information

[2118] The user uses the emotion engine to automatically recognize and record their current emotional state. For example, if the user is feeling stressed, the emotion engine will recognize and record that state. The device then sends the emotional information to the server, which stores the received emotional information in a database. This information is used to analyze the user's emotional tendencies.

[2119] 5. Diet, exercise, and fasting recommendations

[2120] The server recommends appropriate diet, exercise, and fasting to the user based on the recorded dietary information, exercise information, health check information, and emotional information. For example, based on the user's data, recommendations such as "a balanced diet centered on vegetables" and "a 30-minute walk three times a week" may be made. Also, if the user is feeling stressed, recommendations such as "eating foods with a relaxing effect (chamomile tea)" may be made. This allows the user to consistently maintain their health.

[2121] 6. Health Status Generation

[2122] The server generates the user's latest health status based on the recorded health check information and emotional information. For example, if the result of the most recent health check is "good health," the server presents this result to the user. If there is no record, the server notifies the user that a health check is necessary. The terminal displays this notification to the user.

[2123] Hardware and software used

[2124] Hardware: Devices such as smartphones, smart glasses, and head-mounted displays

[2125] Software: Python program, emotion engine, cloud server, database

[2126] Specific examples

[2127] For example, suppose a user had "oatmeal and fruit" for breakfast on January 1st and went for a "30-minute jog" on the same day. Furthermore, if this user undergoes a health check and records "good health," and the emotion engine recognizes the user's emotion as "stressed," the server will use this information to make recommendations such as "foods with a relaxing effect (e.g., chamomile tea)" and "exercise three times a week to reduce stress." It will also present information that "good health" based on the results of the most recent health check.

[2128] Prompt Sentence Examples

[2129] User profile: "Diet information: oatmeal and fruit", "Exercise information: 30 minutes of jogging", "Health check information: good health", "Emotion information: stressed"

[2130] Based on this information, generate recommendations for appropriate diet, exercise, and relaxation methods and display them in your "Wellness Concierge."

[2131] In this way, users can input information using the system on a daily basis, collect emotional information through the emotion engine, and r...

Claims

1. means for recording meal information input by a user; means for recording exercise information input by a user; means for recording health check information entered by a user; A means for making diet, exercise, and fasting recommendations based on the recorded diet information, exercise information, and health check information; means for generating a user's health status based on the recorded health check information; A system including:

2. 10. The system of claim 1, further comprising means for notifying the user that a health check is required if the user's health condition has not been recorded.

3. 2. The system according to claim 1, further comprising means for transmitting the diet information, exercise information, and health check information input by the user to a server.

4. 2. The system according to claim 1, further comprising means for saving the diet information, exercise information, and health check information input by the user in a list structure.

5. 2. The system of claim 1, wherein the server includes means for notifying the user of diet, exercise, and fasting recommendations.

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