system

Abstract

We provide the system. [Solution] A means of providing a database for recording and managing personal health information, A means equipped with artificial intelligence that references past health data and performs generation processing to analyze an individual's health status, A means that provides an interface for outputting generated information and providing medical advice to an individual, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern times, people are increasingly required to effectively manage their own health conditions. On the other hand, it is difficult to integrate health information and records dispersed among medical facilities, and there is a lack of an efficient system for individuals to conduct unified self-health management. This situation poses an obstacle to the selection of appropriate medical institutions and the improvement of lifestyle habits, and as a result, it hinders the prevention of diseases and the promotion of health. Therefore, the present invention aims to solve these problems by centrally managing personal health information and providing appropriate medical advice by utilizing artificial intelligence.

Means for Solving the Problems

[0005] This invention provides a system that centrally manages individual health information by incorporating a database for recording and managing personal health information. Furthermore, it includes artificial intelligence that references past health data and performs generation processing to analyze an individual's health status and generate appropriate medical advice. In addition, it provides rapid medical advice to individuals through an interface that delivers the generated information to them. This system enables individuals to understand their own health status and efficiently take preventative medical actions and improve their lifestyle habits.

[0006] "Personal health information" refers to a collection of data that includes medical records, diagnoses, prescription drug information, and daily health status related to a specific individual.

[0007] A "database" is a system for systematically collecting, managing, and storing information and data, and for making it accessible and manipulated as needed.

[0008] "Generation processing" refers to the process of creating results or information according to a specific purpose based on the input data.

[0009] Artificial intelligence is a technology that uses computer systems to mimic human perception and judgment, and to perform data analysis and problem-solving.

[0010] An "interface" refers to the point of contact or means by which a system or program interacts with a user to exchange information. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4]This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, let's explain the terminology used in the following explanation.

[0014] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0015] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0017] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like.

[0018] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] As shown in Figure 1, the 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.

[0022] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0023] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0024] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0025] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0026] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0029] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0030] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0031] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0032] As an embodiment of this invention, a system is provided that centrally manages individual health data and provides personalized health support using generating AI. This system includes a database for recording the user's health information, artificial intelligence that generates symptom analysis and medical advice based on that information, and an interface for providing this information to the user.

[0033] When the system is launched, individual health data is centrally managed using a health ID issued by the user. Users input their health data, including past prescription information and diagnostic results. This information is transmitted from the terminal to the server and stored in a database based on the health ID.

[0034] When a user experiences a change in their health during their daily life, they input details of their symptoms and physical condition into the application. This information is sent to a server, where artificial intelligence analyzes the data and compares it with past health data to analyze trends in symptoms. After the analysis, the AI ​​generates necessary medical information and advice for improving daily life, and presents this information to the user through the interface.

[0035] For example, if a user frequently experiences health problems, they can input their symptoms into the application. Based on this input, the server suggests potential stress levels or nutrient deficiencies and generates advice, including dietary plans and exercise optimizations as solutions. This advice is notified to the user in real time, enabling quick action.

[0036] Furthermore, as an optional feature, users can provide their genetic information to the system. By utilizing this genetic information, the artificial intelligence can analyze long-term health risks and suggest preventative measures and medical areas requiring attention.

[0037] In this way, the present invention can provide efficient management of health data and advanced medical support using artificial intelligence, thereby supporting the improvement of individual health.

[0038] The following describes the processing flow.

[0039] Step 1:

[0040] The user downloads the application and registers an account by entering personal information. The information entered by the user is sent from the device to the server, which generates a health ID for each user and stores it in a database.

[0041] Step 2:

[0042] The user enters past medical information, such as prescription medications and diagnostic results, into the application. The device sends this information to a server, which updates the individual's health database based on their health ID.

[0043] Step 3:

[0044] The user enters their current health status and symptoms into the application. The device sends this symptom data to a server, and artificial intelligence begins to analyze the entered information.

[0045] Step 4:

[0046] Artificial intelligence on the server references past health information stored in a database and analyzes current symptoms. This identifies potential health problems and areas that need improvement.

[0047] Step 5:

[0048] Artificial intelligence generates appropriate medical advice and suggestions for improving daily life based on the analysis results. This information is sent from the server to the terminal and notified to the user.

[0049] Step 6:

[0050] Based on the advice and recommendations provided, users implement improvements to their lifestyle. They then input their improved health status and feedback into the application, which is then transmitted to the server via their device.

[0051] Step 7:

[0052] The server incorporates the received feedback into the AI's training data, improving the algorithm's accuracy and future disease prediction capabilities. This continuous accumulation and analysis of data provides users with more accurate health support.

[0053] (Example 1)

[0054] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0055] In modern society, there is a need to efficiently manage individual health information and provide appropriate health advice based on diverse health data. However, conventional systems present challenges such as cumbersome data management and difficulty in providing personalized health support.

[0056] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0057] In this invention, the server includes means for providing an information storage device for storing and managing an individual's health information, means for providing an automated intelligence that references past health data to analyze an individual's health status and performs generation processing, and means for providing an input / output device that outputs the generated information and provides health advice to the individual. This makes it possible to efficiently manage each individual's health information and provide appropriate health support.

[0058] "Health information" refers to data about an individual's health status, including past diagnostic results, prescription drug information, and changes in physical condition.

[0059] An "information storage device" is a device or system for storing data in digital format, and is a device that enables centralized management of personal health information using database and cloud storage technologies.

[0060] "Management" refers to the effective storage and handling of information, encompassing the process of managing data according to specific standards and rules, and updating or deleting information as needed.

[0061] "Automated intelligence" refers to a computer program or system that uses technologies such as machine learning and deep learning to analyze data and make decisions or generate advice on behalf of humans.

[0062] An "input / output device" is an interface device used by a user to input information and receive generated results or advice, and includes computer screens, keyboards, smartphone applications, etc.

[0063] An "identification code" is a unique string of characters or code used to identify each individual, and is used to associate individual health data within an information system.

[0064] "Health advice" refers to suggestions that include specific action plans and medical advice for maintaining or improving health, based on an individual's health condition and lifestyle.

[0065] "Long-term health risks" refer to potential health-related risks that may occur in the future, based on the analysis of genetic information and health data.

[0066] This invention is a system that efficiently manages personal health information and provides personalized health advice using AI generation. The system includes a terminal for data input, a server for storing and processing the information, and a user interface for displaying the advice.

[0067] The terminal consists of an information processing device such as a smartphone or computer, and has an application installed for the user to input their own health data. The health data collected here includes past medical examination results, prescription information, and daily health records.

[0068] The server is equipped with a database and a generative AI model. The database utilizes a relational database system to systematically store health information using individual identification codes as keys. The generative AI model is an automated intelligence built on various machine learning algorithms that analyzes current symptoms based on past health data and creates personalized health advice.

[0069] As a concrete example, when a user frequently experiences health problems, they input their symptoms into the application. This information is sent from the device to the server, where the generated AI model analyzes it. After analysis, the server generates advice such as meal plan suggestions and exercise optimization, and can notify the user in real time.

[0070] An example of a prompt would be, "Based on the user's health data, please suggest ways to improve their current symptoms." This prompt prompts the generative AI model to generate and send appropriate advice.

[0071] This will enable a system that allows users to manage their health appropriately and receive personalized medical support.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] Users input health data using their devices. Specifically, they open a dedicated application, fill in past diagnostic results, prescription information, and current health status in an input form, and press the submit button. This operation pre-processes the input data and prepares it for submission.

[0075] Step 2:

[0076] The device sends the entered health data to the server. During transmission, the data is encrypted and reaches the server via the internet using a secure communication protocol. This ensures that the input data is safely transferred to the server.

[0077] Step 3:

[0078] The server stores the received data in a database. The data is classified based on its individual identification code and stored in the information storage device. Specifically, the server executes an SQL query and adds the newly received data to the correct record in the database.

[0079] Step 4:

[0080] When a user experiences a change in their health, they use their device to input the new symptoms. Here, they fill in details of the symptoms and changes in their physical condition in an input form. This information is used to determine whether further analysis is necessary.

[0081] Step 5:

[0082] The server inputs the newly received symptom data into the generating AI model. The model is instructed using the prompt message, "Based on this new symptom data, compare it with past health history and analyze the trend of the symptoms." The generating AI model analyzes the input data based on this prompt and generates health advice as output.

[0083] Step 6:

[0084] The server generates specific health advice based on the analysis results obtained from the generated AI model. This includes dietary guidance and exercise recommendations, and is structured to provide information that directly helps improve the user's health.

[0085] Step 7:

[0086] The user receives advice generated from the server via their device. The server sends the generated advice to the device, which then communicates it to the user in real time through its notification function. This allows the user to receive actionable improvement suggestions immediately.

[0087] Step 8:

[0088] Optionally, users can provide additional genetic information. This allows the server to perform deeper health analyses, assess long-term health risks, and generate new advice.

[0089] (Application Example 1)

[0090] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0091] In modern life, the amount of information available to maintain and improve an individual's health is vast, and it is not easy for individuals to utilize this information effectively. In particular, there is a need for effective means to link health information with dietary choices and incorporate them into daily life. However, conventional systems have the problem of not easily integrating individual health data with meal plans. Therefore, a system is needed to efficiently provide meal suggestions and delivery that take into account an individual's health condition.

[0092] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0093] In this invention, the server includes means for information management for recording and managing an individual's health information, means for information processing for referencing past health data and performing generation processing to analyze an individual's health status, and means for proposing an optimal nutritional intake plan based on the individual's health data and mediating the delivery of prepared foods. This makes it possible to quickly propose a meal plan tailored to an individual's health status and to facilitate meal delivery.

[0094] "Information management means" refers to technologies and devices used to record, organize, and manage an individual's health information.

[0095] "Information processing means" refers to technologies and devices for analyzing an individual's health status based on past data and generating results.

[0096] A "dialogue device" is an interface or device that uses generated information to provide medical suggestions and guidance to an individual.

[0097] A "nutritional intake plan" is a plan that proposes a suitable diet and nutritional supplementation method for an individual based on their health data.

[0098] "Means of mediating the delivery of prepared foods" refers to technologies and systems that facilitate the process of selecting specific foods based on a proposed nutritional plan and delivering them to users.

[0099] The system designed to realize this application embodies a series of processes, from collecting and analyzing individual health data, proposing an optimal meal plan based on the results, to delivering suitable food. Specifically, it is implemented through a combination of servers, terminals, artificial intelligence, and a delivery service.

[0100] The server provides an information management system for centrally managing individual health information. This information is stored and accessible in a database located in a cloud environment (e.g., AWS® RDS). The terminal functions as an interface for users to input their health status and preferences, and the entered data is sent to the server. The transmitted data is processed using an AI analysis engine (e.g., Google® AI Platform), which is an information processing tool. The AI ​​generates an optimal nutrition plan for each individual's health condition by comparing it with past health data.

[0101] Based on the generated plan, the server facilitates food delivery by presenting the menu to the user through a delivery service API (e.g., a common food delivery service API) and making ordering easier. This process is carried out quickly and efficiently through an automated series of operations.

[0102] For example, if a user enters into the device that they "recently feel tired," the AI ​​analyzes this and generates a meal plan that selects iron-rich ingredients. Based on this, appropriate dishes are chosen, and the user is presented with the most suitable menu. Once the user reviews the menu and confirms their order, the food is delivered to the specified location.

[0103] Examples of prompts to input into a generative AI model:

[0104] I've been feeling tired lately. Please suggest a meal plan that takes my health into consideration.

[0105] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0106] Step 1:

[0107] The terminal accepts user health information, current physical condition, and preference information. The entered information is sent to a server in a cloud environment. The input in this step is direct information from the user, and the output is data transmission to the server.

[0108] Step 2:

[0109] The server saves the received data to a cloud database. During this process, information management tools are used to organize and manage the data. The input here is the user information sent in step 1, and the output is the storage of the data in an organized format into the database.

[0110] Step 3:

[0111] The AI ​​analysis engine runs on a server and compares stored health data with historical data. This allows for an analysis of the subject's health status. The input is health information and historical health records stored in the database, and the output is the analysis results.

[0112] Step 4:

[0113] The server creates an optimal nutrition plan for each individual based on the analysis results generated by the AI. Specifically, it generates a detailed meal plan that takes into account the necessary nutrients. The input is the analysis results from the AI, and the output is the proposed meal plan.

[0114] Step 5:

[0115] The server delivers the generated meal plan to the terminal and presents it to the user. The user reviews the plan and selects their order. The input is the meal plan, and the output is the presentation of the plan to the user and the order confirmation.

[0116] Step 6:

[0117] Once the user confirms their order, the server arranges for the delivery of the selected food items via the delivery service API. The input is the order information confirmed by the user, and the output is the delivery instruction to the delivery service.

[0118] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0119] This invention provides a system that achieves more comprehensive health support by managing an individual's health information in detail while also recognizing the user's emotional state. This system incorporates a database, artificial intelligence, an interface, and an emotion engine, enabling the provision of advice based on the user's emotions.

[0120] The application allows users to not only input their personal health data but also record their emotional state. This emotional information is collected, for example, by evaluating the user's mental state through periodic questionnaires. The device sends this information to a server, which centrally records the health information and emotional data in a database.

[0121] The system receives emotional information from the user, and an emotion engine analyzes this information to identify the user's current emotional state. This analyzed information is processed by artificial intelligence, and a health status assessment is performed by combining emotional data and health data. Based on this, medical advice and lifestyle improvement suggestions are generated.

[0122] For example, if a user is experiencing a lot of stress, the system analyzes their emotional information and provides specific suggestions for stress reduction activities and diet. Furthermore, it can predict the impact of stress on the body based on past health data and recommend seeking medical attention if necessary.

[0123] This system allows users to receive a more comprehensive approach to their health management, addressing both physical and psychological aspects. The organic integration of artificial intelligence and an emotion engine enables the provision of real-time, personalized health support, contributing to extending users' healthy lifespans.

[0124] The following describes the processing flow.

[0125] Step 1:

[0126] The user launches the application and inputs health information, daily physical condition, and emotional state. Emotional state is entered through self-assessment and multiple-choice questionnaires.

[0127] Step 2:

[0128] The terminal sends the entered health and emotional information to the server. The server stores the information in a database and updates the records based on each user's health ID.

[0129] Step 3:

[0130] On the server, the emotion engine analyzes emotional information. For example, it evaluates stress levels and positive / negative emotional tendencies from emotional data.

[0131] Step 4:

[0132] Artificial intelligence combines analysis results from an emotion engine with historical health information from a database to assess the user's overall health status. This includes analyzing the potential impact of emotions on physical condition.

[0133] Step 5:

[0134] Artificial intelligence generates medical advice and lifestyle improvement suggestions based on the evaluation results. The generated information includes exercise suggestions for stress management and meal plans to support emotional well-being.

[0135] Step 6:

[0136] The server sends the generated advice to the terminal, which then notifies the user. The user receives the notified information and can take specific actions.

[0137] Step 7:

[0138] The user inputs feedback through the application, based on the results obtained from improving their lifestyle habits according to the advice given. The device then sends this feedback information to the server.

[0139] Step 8:

[0140] The server receives feedback and updates its artificial intelligence algorithms to improve the accuracy of future advice. This enables continuous and effective health support for users.

[0141] (Example 2)

[0142] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0143] The problem that this invention aims to solve is to enable the comprehensive analysis of physical and psychological elements in individual health management and to provide personalized information in real time. Conventional health management systems have not adequately analyzed emotional states, making it difficult to manage an individual's mind and body as a whole and provide appropriate health support.

[0144] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0145] In this invention, the server includes means for data storage for recording and managing an individual's health information and emotional state; means for an analysis engine for analyzing emotional information and identifying an individual's emotional state; and means for artificial intelligence for evaluating the overall health state and generating advice based on the analyzed emotional and health information. This enables the integrated management of physical and emotional elements in an individual's health and allows for the provision of appropriate advice to the user tailored to their individual condition.

[0146] "Personal health information" refers to data that indicates the physical health status of individual users, and mainly includes information such as physical measurements and lifestyle records.

[0147] "Emotional state" refers to data that indicates the user's psychological or emotional state, including information that evaluates stress levels, mood swings, and other factors.

[0148] "Data storage" refers to a digital storage device or system for securely and effectively recording and storing health and emotional information.

[0149] An "analysis engine" is a computer program or script used to analyze input data and identify the user's emotional state.

[0150] "Artificial intelligence" is a program or algorithm that performs data analysis and prediction to help assess health conditions and generate advice.

[0151] An "interface" is a user interface or system design that presents generated information to the user and enables the exchange of input information.

[0152] An "online server" is a remote computing resource used for storing, managing, and processing data in a cloud environment.

[0153] "Identification information" refers to data or codes used to uniquely identify an individual user.

[0154] "Genetic information" refers to data that shows an individual's genetic structure and is information that may affect health risks and physical characteristics.

[0155] A "health hazard" is a factor that indicates a potential risk or expected impairment to an individual's health.

[0156] This invention is a system that integrates and manages an individual's health information and emotional state, and provides personalized health advice to the user. This system comprises data storage, an analysis engine, artificial intelligence, and a user interface. Each component is described below.

[0157] Firstly, users input their health and emotional data through their devices. This process involves using a dedicated application on a digital device such as a smartphone or tablet to record physical information such as weight and blood pressure, as well as providing emotional information such as stress levels and mood in the form of questionnaires.

[0158] The terminal sends the entered information to the server. The server uses data storage to highly encrypt this information and manage it securely in a centralized manner. The data storage is associated with consistent user identification information, ensuring secure data management.

[0159] Next, the server inputs emotional information into the analysis engine to identify the detailed emotional state. The analysis engine uses natural language processing technology to calculate an emotional score from the text data and classify the user's emotional state.

[0160] This emotional and health data is further processed by artificial intelligence. Using a generative AI model, past data and current state are analyzed to assess the user's overall health status. The AI ​​predicts future health risks and provides lifestyle improvement measures as needed.

[0161] Finally, the server returns the generated information to the terminal and displays it on the user interface. Users can receive this information in real time and use it as a guide in their daily lives.

[0162] For example, if a user inputs information such as "I've been feeling stressed lately," the system can suggest specific activities and dietary changes to reduce stress. It also provides comprehensive support, including recommending a visit to a medical institution if necessary. This prompting allows users to gain insights into leading a healthier life.

[0163] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0164] Step 1:

[0165] Users input health and emotional data using their devices. Specifically, they log in to a dedicated application and record health indicators such as weight and blood pressure, as well as emotional states such as mood and stress levels by answering questions presented in a questionnaire format. The entered data is stored in a temporary database on the device and prepared for the next processing step.

[0166] Step 2:

[0167] The device transmits entered health and emotional data to the server. The transmitted data is securely protected using encryption protocols and safely stored in the server's data storage. The input data is linked to identification information and centrally managed in a way that corresponds to individual user accounts.

[0168] Step 3:

[0169] The server inputs stored emotional data into an analysis engine and performs emotional analysis. Specifically, it uses natural language processing technology to calculate an emotional score from text-based data and classifies the user's emotional state. The resulting emotional score is reported as high stress, moderate stress, low stress, etc.

[0170] Step 4:

[0171] The server combines the emotion score obtained from the analysis engine with stored health data to perform a comprehensive health status assessment using artificial intelligence. A generative AI model is used in this assessment process, taking into account past health information and current emotional state to assess the user's current and future health risks. The output generated in this step consists of specific advice for lifestyle improvement and the results of the risk assessment.

[0172] Step 5:

[0173] The server sends the generated advice and evaluation results to the terminal. The terminal displays this information in the user interface. Specifically, the user can launch the application and view the customized feedback and suggestions. This makes it easier for the user to monitor their health status in real time and take necessary actions.

[0174] (Application Example 2)

[0175] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0176] Many modern health management systems focus heavily on physical health information and fail to adequately consider psychological factors. Furthermore, few systems provide rapid responses or warnings regarding real-time changes in health status and emotions. Additionally, the lack of mechanisms for integrating emotional and health data when providing personalized health support limits the effectiveness of improving individual safety and quality of life.

[0177] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0178] In this invention, the server includes means for an information storage device for recording and managing an individual's health information and psychological state; means for a machine learning device that references past data and performs analytical processing to analyze an individual's health and emotional information; means for an output device that outputs the analyzed information and provides health and psychological advice to the individual; and means for a device that monitors an individual's health and emotional state in real time and notifies an external party if an abnormality is detected. This enables comprehensive management of health and psychological information and real-time response.

[0179] An "information storage device" is a digital recording device for centrally recording and managing an individual's health information and psychological state.

[0180] A "machine learning device" is a device that uses algorithms to analyze an individual's past health status and emotional information, and to evaluate future health trends and risks through data analysis.

[0181] An "output device" is a digital display means for providing users with analyzed health and psychological advice, and is a device that plays a role in presenting information visually or audibly.

[0182] A "real-time monitoring device" is a digital sensor network that continuously monitors an individual's health and emotional state, enabling rapid detection and notification of abnormalities.

[0183] An "identifier" is a unique code or pattern used to identify and manage an individual on a network.

[0184] "Genetic information" refers to biological genetic data that forms the basis for evaluating an individual's long-term health risks and the impact of emotional fluctuations.

[0185] The system for implementing this invention consists of a wearable device, including smart glasses, and a server located in the cloud. The user receives data input and feedback through the smart glasses. The glasses are equipped with a heart rate sensor and voice input function, and collect heart rate and emotional data in real time. This allows for an understanding of the user's health and emotional state.

[0186] The server functions as an information storage device, accumulating vital data such as heart rate and blood pressure using the GOOGLE FI™ API. Furthermore, machine learning models such as Hugging Face's Transformer are used for emotion analysis. This data is analyzed by machine learning equipment to reveal the interrelationships between health status and emotion data.

[0187] The analyzed data is fed back to the user through an output device, and health and psychological advice is provided. For example, if the heart rate exceeds the normal range, the system will notify the user to "pay attention to your health" and, if necessary, notify emergency contacts of the abnormality.

[0188] For example, if a user has consumed a sweet food and is experiencing heightened emotions, the system might advise them to "be mindful of the risk of diabetes and try to have a balanced meal next time."

[0189] Examples of prompt messages include, "Recommend the next action based on the current heart rate and stress level," and "Suggest relaxation techniques to display when the user is detected to be anxious." This allows users to receive personalized feedback in real time.

[0190] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0191] Step 1:

[0192] The device collects biometric information such as the user's heart rate and blood pressure through sensors. The input is direct data from biosensors, and the output is vital data in digital format. The data obtained from the sensors is collected at regular intervals and temporarily stored on the local device.

[0193] Step 2:

[0194] The device collects emotional data from the user through voice input or questionnaires. In this step, the input includes voice data and text input provided by the user, and the output is a category representing emotion. The input emotional content is converted into text using speech recognition technology and analyzed by an emotion analysis engine.

[0195] Step 3:

[0196] The device transmits collected vital and emotional data to a server via the network. Here, data stored within the device serves as input, and data is stored in a database on the server as output. Data transmission is performed using a secure protocol.

[0197] Step 4:

[0198] The server analyzes the accumulated data using a machine learning model. It receives past health information and current emotional data as input and generates analysis results corresponding to the health and emotional state as output. The analysis utilizes the Hugging Face Transformer model and employs deep learning with a generative AI model.

[0199] Step 5:

[0200] The server generates health advice for the user based on the analysis results. In this step, the analysis results are the input, and specific health advice sentences are generated as the output. Prompt sentences are input into the AI ​​model to create interactive advice.

[0201] Step 6:

[0202] The device displays or audibly notifies the user of the generated advice. The input is advice data from the server, and the output is visual or auditory feedback on the user's display or speaker. This allows the user to receive real-time information to help manage their health.

[0203] Step 7:

[0204] The device sends a notification to emergency contacts when it detects an anomaly. Inputs include vital data exceeding a certain threshold and analyzed risk categories, while output is the sending of an SMS or email to emergency contacts. An anomaly detection algorithm, utilizing sensors and models, activates and automatically issues an alert.

[0205] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0206] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0207] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0208] [Second Embodiment]

[0209] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0210] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0211] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0212] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0213] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0214] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0215] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0216] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0217] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0218] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0219] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0220] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0221] As an embodiment of this invention, a system is provided that centrally manages individual health data and provides personalized health support using generating AI. This system includes a database for recording the user's health information, artificial intelligence that generates symptom analysis and medical advice based on that information, and an interface for providing this information to the user.

[0222] When the system is launched, individual health data is centrally managed using a health ID issued by the user. Users input their health data, including past prescription information and diagnostic results. This information is transmitted from the terminal to the server and stored in a database based on the health ID.

[0223] When a user experiences a change in their health during their daily life, they input details of their symptoms and physical condition into the application. This information is sent to a server, where artificial intelligence analyzes the data and compares it with past health data to analyze trends in symptoms. After the analysis, the AI ​​generates necessary medical information and advice for improving daily life, and presents this information to the user through the interface.

[0224] For example, if a user frequently experiences health problems, they can input their symptoms into the application. Based on this input, the server suggests potential stress levels or nutrient deficiencies and generates advice, including dietary plans and exercise optimizations as solutions. This advice is notified to the user in real time, enabling quick action.

[0225] Furthermore, as an optional feature, users can provide their genetic information to the system. By utilizing this genetic information, the artificial intelligence can analyze long-term health risks and suggest preventative measures and medical areas requiring attention.

[0226] In this way, the present invention can provide efficient management of health data and advanced medical support using artificial intelligence, thereby supporting the improvement of individual health.

[0227] The following describes the processing flow.

[0228] Step 1:

[0229] The user downloads the application and registers an account by entering personal information. The information entered by the user is sent from the device to the server, which generates a health ID for each user and stores it in a database.

[0230] Step 2:

[0231] The user enters past medical information, such as prescription medications and diagnostic results, into the application. The device sends this information to a server, which updates the individual's health database based on their health ID.

[0232] Step 3:

[0233] The user enters their current health status and symptoms into the application. The device sends this symptom data to a server, and artificial intelligence begins to analyze the entered information.

[0234] Step 4:

[0235] Artificial intelligence on the server references past health information stored in a database and analyzes current symptoms. This identifies potential health problems and areas that need improvement.

[0236] Step 5:

[0237] Artificial intelligence generates appropriate medical advice and suggestions for improving daily life based on the analysis results. This information is sent from the server to the terminal and notified to the user.

[0238] Step 6:

[0239] Based on the advice and recommendations provided, users implement improvements to their lifestyle. They then input their improved health status and feedback into the application, which is then transmitted to the server via their device.

[0240] Step 7:

[0241] The server incorporates the received feedback into the AI's training data, improving the algorithm's accuracy and future disease prediction capabilities. This continuous accumulation and analysis of data provides users with more accurate health support.

[0242] (Example 1)

[0243] Next, we will describe Example 1. 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."

[0244] In modern society, there is a need to efficiently manage individual health information and provide appropriate health advice based on diverse health data. However, conventional systems present challenges such as cumbersome data management and difficulty in providing personalized health support.

[0245] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0246] In this invention, the server includes means for providing an information storage device for storing and managing an individual's health information, means for providing an automated intelligence that references past health data to analyze an individual's health status and performs generation processing, and means for providing an input / output device that outputs the generated information and provides health advice to the individual. This makes it possible to efficiently manage each individual's health information and provide appropriate health support.

[0247] "Health information" refers to data about an individual's health status, including past diagnostic results, prescription drug information, and changes in physical condition.

[0248] An "information storage device" is a device or system for storing data in digital format, and is a device that enables centralized management of personal health information using database and cloud storage technologies.

[0249] "Management" refers to the effective storage and handling of information, encompassing the process of managing data according to specific standards and rules, and updating or deleting information as needed.

[0250] "Automated intelligence" refers to a computer program or system that uses technologies such as machine learning and deep learning to analyze data and make decisions or generate advice on behalf of humans.

[0251] An "input / output device" is an interface device used by a user to input information and receive generated results or advice, and includes computer screens, keyboards, smartphone applications, etc.

[0252] An "identification code" is a unique string of characters or code used to identify each individual, and is used to associate individual health data within an information system.

[0253] "Health advice" refers to suggestions that include specific action plans and medical advice for maintaining or improving health, based on an individual's health condition and lifestyle.

[0254] "Long-term health risks" refer to potential health-related risks that may occur in the future, based on the analysis of genetic information and health data.

[0255] This invention is a system that efficiently manages personal health information and provides personalized health advice using AI generation. The system includes a terminal for data input, a server for storing and processing the information, and a user interface for displaying the advice.

[0256] The terminal consists of an information processing device such as a smartphone or computer, and has an application installed for the user to input their own health data. The health data collected here includes past medical examination results, prescription information, and daily health records.

[0257] The server is equipped with a database and a generative AI model. The database utilizes a relational database system to systematically store health information using individual identification codes as keys. The generative AI model is an automated intelligence built on various machine learning algorithms that analyzes current symptoms based on past health data and creates personalized health advice.

[0258] As a concrete example, when a user frequently experiences health problems, they input their symptoms into the application. This information is sent from the device to the server, where the generated AI model analyzes it. After analysis, the server generates advice such as meal plan suggestions and exercise optimization, and can notify the user in real time.

[0259] An example of a prompt would be, "Based on the user's health data, please suggest ways to improve their current symptoms." This prompt prompts the generative AI model to generate and send appropriate advice.

[0260] This will enable a system that allows users to manage their health appropriately and receive personalized medical support.

[0261] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0262] Step 1:

[0263] Users input health data using their devices. Specifically, they open a dedicated application, fill in past diagnostic results, prescription information, and current health status in an input form, and press the submit button. This operation pre-processes the input data and prepares it for submission.

[0264] Step 2:

[0265] The device sends the entered health data to the server. During transmission, the data is encrypted and reaches the server via the internet using a secure communication protocol. This ensures that the input data is safely transferred to the server.

[0266] Step 3:

[0267] The server stores the received data in a database. The data is classified based on its individual identification code and stored in the information storage device. Specifically, the server executes an SQL query and adds the newly received data to the correct record in the database.

[0268] Step 4:

[0269] When a user experiences a change in their health, they use their device to input the new symptoms. Here, they fill in details of the symptoms and changes in their physical condition in an input form. This information is used to determine whether further analysis is necessary.

[0270] Step 5:

[0271] The server inputs the newly received symptom data into the generating AI model. The model is instructed using the prompt message, "Based on this new symptom data, compare it with past health history and analyze the trend of the symptoms." The generating AI model analyzes the input data based on this prompt and generates health advice as output.

[0272] Step 6:

[0273] The server generates specific health advice based on the analysis results obtained from the generated AI model. This includes dietary guidance and exercise recommendations, and is structured to provide information that directly helps improve the user's health.

[0274] Step 7:

[0275] The user receives advice generated from the server via their device. The server sends the generated advice to the device, which then communicates it to the user in real time through its notification function. This allows the user to receive actionable improvement suggestions immediately.

[0276] Step 8:

[0277] Optionally, users can provide additional genetic information. This allows the server to perform deeper health analyses, assess long-term health risks, and generate new advice.

[0278] (Application Example 1)

[0279] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0280] In modern life, the amount of information available to maintain and improve an individual's health is vast, and it is not easy for individuals to utilize this information effectively. In particular, there is a need for effective means to link health information with dietary choices and incorporate them into daily life. However, conventional systems have the problem of not easily integrating individual health data with meal plans. Therefore, a system is needed to efficiently provide meal suggestions and delivery that take into account an individual's health condition.

[0281] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0282] In this invention, the server includes means for information management for recording and managing an individual's health information, means for information processing for referencing past health data and performing generation processing to analyze an individual's health status, and means for proposing an optimal nutritional intake plan based on the individual's health data and mediating the delivery of prepared foods. This makes it possible to quickly propose a meal plan tailored to an individual's health status and to facilitate meal delivery.

[0283] The "information management means" is a technology or device used to record, organize, and manage personal health information.

[0284] The "information processing means" is a technology or device for analyzing an individual's health status based on past data and generating results.

[0285] The "dialogue device" is an interface or device for providing medical proposals and guidelines to an individual using the generated information.

[0286] The "nutritional intake plan" is a plan that proposes dietary content and nutritional supplementation methods suitable for a person based on their personal health data.

[0287] The "means for mediating the delivery of cooked food" is a technology or system that facilitates the process of selecting specific foods based on the proposed nutritional plan and delivering them to the user.

[0288] The system for realizing this application example embodies a series of processes from collecting and analyzing an individual's health data, proposing an optimal diet plan based on the results, to delivering suitable foods. Specifically, it is realized by a combination of a server, a terminal, artificial intelligence, and a delivery service.

[0289] The server provides information management means to centrally manage an individual's health information. This information is stored in a database (e.g., AWS RDS) installed in a cloud environment and can be accessed. The terminal functions as an interface for the user to input their health status and preferences, and the input data is sent to the server. The sent data is processed using an AI analysis engine (e.g., Google AI Platform) which is the information processing means. The AI generates a nutritional intake plan optimal for each individual's health status by comparing it with past health data.

[0290] Based on the generated plan, the server facilitates food delivery by presenting the menu to the user through a delivery service API (e.g., a common food delivery service API) and making ordering easier. This process is carried out quickly and efficiently through an automated series of operations.

[0291] For example, if a user enters into the device that they "recently feel tired," the AI ​​analyzes this and generates a meal plan that selects iron-rich ingredients. Based on this, appropriate dishes are chosen, and the user is presented with the most suitable menu. Once the user reviews the menu and confirms their order, the food is delivered to the specified location.

[0292] Examples of prompts to input into a generative AI model:

[0293] I've been feeling tired lately. Please suggest a meal plan that takes my health into consideration.

[0294] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0295] Step 1:

[0296] The terminal accepts user health information, current physical condition, and preference information. The entered information is sent to a server in a cloud environment. The input in this step is direct information from the user, and the output is data transmission to the server.

[0297] Step 2:

[0298] The server saves the received data to a cloud database. During this process, information management tools are used to organize and manage the data. The input here is the user information sent in step 1, and the output is the storage of the data in an organized format into the database.

[0299] Step 3:

[0300] The AI analysis engine is run on the server to compare the stored health data with past data, thereby analyzing the health status of the subject. The input is the health information and past health records stored in the database, and the output is the analysis result.

[0301] Step 4:

[0302] Based on the analysis results generated by the AI, the server creates an optimal nutrition intake plan for the individual. Specifically, a specific diet plan considering the required nutrients is generated. The input is the analysis result by the AI, and the output is the proposed diet plan.

[0303] Step 5:

[0304] The server distributes the generated diet plan to the terminal and presents it to the user. The user checks the plan and makes an order selection. The input is the diet plan, and the output is the presentation of the plan to the user and the order confirmation.

[0305] Step 6:

[0306] When the user confirms the order, the server arranges for the delivery of the selected food through the delivery service API. The input is the order information confirmed by the user, and the output is the delivery instruction to the delivery service.

[0307] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion recognition model 59 and perform specific processing using the user's emotions.

[0308] The present invention is a system that realizes more comprehensive health support by managing an individual's health information in detail and also recognizing the user's emotional state. In addition to a database, artificial intelligence, and an interface, this system incorporates an emotion engine to realize the provision of advice based on the user's emotions.

[0309] The application allows users to not only input their personal health data but also record their emotional state. This emotional information is collected, for example, by evaluating the user's mental state through periodic questionnaires. The device sends this information to a server, which centrally records the health information and emotional data in a database.

[0310] The system receives emotional information from the user, and an emotion engine analyzes this information to identify the user's current emotional state. This analyzed information is processed by artificial intelligence, and a health status assessment is performed by combining emotional data and health data. Based on this, medical advice and lifestyle improvement suggestions are generated.

[0311] For example, if a user is experiencing a lot of stress, the system analyzes their emotional information and provides specific suggestions for stress reduction activities and diet. Furthermore, it can predict the impact of stress on the body based on past health data and recommend seeking medical attention if necessary.

[0312] This system allows users to receive a more comprehensive approach to their health management, addressing both physical and psychological aspects. The organic integration of artificial intelligence and an emotion engine enables the provision of real-time, personalized health support, contributing to extending users' healthy lifespans.

[0313] The following describes the processing flow.

[0314] Step 1:

[0315] The user launches the application and inputs health information, daily physical condition, and emotional state. Emotional state is entered through self-assessment and multiple-choice questionnaires.

[0316] Step 2:

[0317] The terminal sends the entered health and emotional information to the server. The server stores the information in a database and updates the records based on each user's health ID.

[0318] Step 3:

[0319] On the server, the emotion engine analyzes emotional information. For example, it evaluates stress levels and positive / negative emotional tendencies from emotional data.

[0320] Step 4:

[0321] Artificial intelligence combines analysis results from an emotion engine with historical health information from a database to assess the user's overall health status. This includes analyzing the potential impact of emotions on physical condition.

[0322] Step 5:

[0323] Artificial intelligence generates medical advice and lifestyle improvement suggestions based on the evaluation results. The generated information includes exercise suggestions for stress management and meal plans to support emotional well-being.

[0324] Step 6:

[0325] The server sends the generated advice to the terminal, which then notifies the user. The user receives the notified information and can take specific actions.

[0326] Step 7:

[0327] The user inputs feedback through the application, based on the results obtained from improving their lifestyle habits according to the advice given. The device then sends this feedback information to the server.

[0328] Step 8:

[0329] The server receives feedback and updates its artificial intelligence algorithms to improve the accuracy of future advice. This enables continuous and effective health support for users.

[0330] (Example 2)

[0331] Next, we will describe Example 2. 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".

[0332] The problem that this invention aims to solve is to enable the comprehensive analysis of physical and psychological elements in individual health management and to provide personalized information in real time. Conventional health management systems have not adequately analyzed emotional states, making it difficult to manage an individual's mind and body as a whole and provide appropriate health support.

[0333] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0334] In this invention, the server includes means for data storage for recording and managing an individual's health information and emotional state; means for an analysis engine for analyzing emotional information and identifying an individual's emotional state; and means for artificial intelligence for evaluating the overall health state and generating advice based on the analyzed emotional and health information. This enables the integrated management of physical and emotional elements in an individual's health and allows for the provision of appropriate advice to the user tailored to their individual condition.

[0335] "Personal health information" refers to data that indicates the physical health status of individual users, and mainly includes information such as physical measurements and lifestyle records.

[0336] "Emotional state" refers to data that indicates the user's psychological or emotional state, including information that evaluates stress levels, mood swings, and other factors.

[0337] "Data storage" refers to a digital storage device or system for securely and effectively recording and storing health and emotional information.

[0338] An "analysis engine" is a computer program or script used to analyze input data and identify the user's emotional state.

[0339] "Artificial intelligence" is a program or algorithm that performs data analysis and prediction to help assess health conditions and generate advice.

[0340] An "interface" is a user interface or system design that presents generated information to the user and enables the exchange of input information.

[0341] An "online server" is a remote computing resource used for storing, managing, and processing data in a cloud environment.

[0342] "Identification information" refers to data or codes used to uniquely identify an individual user.

[0343] "Genetic information" refers to data that shows an individual's genetic structure and is information that may affect health risks and physical characteristics.

[0344] A "health hazard" is a factor that indicates a potential risk or expected impairment to an individual's health.

[0345] This invention is a system that integrates and manages an individual's health information and emotional state, and provides personalized health advice to the user. This system comprises data storage, an analysis engine, artificial intelligence, and a user interface. Each component is described below.

[0346] Firstly, users input their health and emotional data through their devices. This process involves using a dedicated application on a digital device such as a smartphone or tablet to record physical information such as weight and blood pressure, as well as providing emotional information such as stress levels and mood in the form of questionnaires.

[0347] The terminal sends the entered information to the server. The server uses data storage to highly encrypt this information and manage it securely in a centralized manner. The data storage is associated with consistent user identification information, ensuring secure data management.

[0348] Next, the server inputs emotional information into the analysis engine to identify the detailed emotional state. The analysis engine uses natural language processing technology to calculate an emotional score from the text data and classify the user's emotional state.

[0349] This emotional and health data is further processed by artificial intelligence. Using a generative AI model, past data and current state are analyzed to assess the user's overall health status. The AI ​​predicts future health risks and provides lifestyle improvement measures as needed.

[0350] Finally, the server returns the generated information to the terminal and displays it on the user interface. Users can receive this information in real time and use it as a guide in their daily lives.

[0351] For example, if a user inputs information such as "I've been feeling stressed lately," the system can suggest specific activities and dietary changes to reduce stress. It also provides comprehensive support, including recommending a visit to a medical institution if necessary. This prompting allows users to gain insights into leading a healthier life.

[0352] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0353] Step 1:

[0354] Users input health and emotional data using their devices. Specifically, they log in to a dedicated application and record health indicators such as weight and blood pressure, as well as emotional states such as mood and stress levels by answering questions presented in a questionnaire format. The entered data is stored in a temporary database on the device and prepared for the next processing step.

[0355] Step 2:

[0356] The device transmits entered health and emotional data to the server. The transmitted data is securely protected using encryption protocols and safely stored in the server's data storage. The input data is linked to identification information and centrally managed in a way that corresponds to individual user accounts.

[0357] Step 3:

[0358] The server inputs stored emotional data into an analysis engine and performs emotional analysis. Specifically, it uses natural language processing technology to calculate an emotional score from text-based data and classifies the user's emotional state. The resulting emotional score is reported as high stress, moderate stress, low stress, etc.

[0359] Step 4:

[0360] The server combines the emotion score obtained from the analysis engine with stored health data to perform a comprehensive health status assessment using artificial intelligence. A generative AI model is used in this assessment process, taking into account past health information and current emotional state to assess the user's current and future health risks. The output generated in this step consists of specific advice for lifestyle improvement and the results of the risk assessment.

[0361] Step 5:

[0362] The server sends the generated advice and evaluation results to the terminal. The terminal displays this information in the user interface. Specifically, the user can launch the application and view the customized feedback and suggestions. This makes it easier for the user to monitor their health status in real time and take necessary actions.

[0363] (Application Example 2)

[0364] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0365] Many modern health management systems focus heavily on physical health information and fail to adequately consider psychological factors. Furthermore, few systems provide rapid responses or warnings regarding real-time changes in health status and emotions. Additionally, the lack of mechanisms for integrating emotional and health data when providing personalized health support limits the effectiveness of improving individual safety and quality of life.

[0366] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0367] In this invention, the server includes means for an information storage device for recording and managing an individual's health information and psychological state; means for a machine learning device that references past data and performs analytical processing to analyze an individual's health and emotional information; means for an output device that outputs the analyzed information and provides health and psychological advice to the individual; and means for a device that monitors an individual's health and emotional state in real time and notifies an external party if an abnormality is detected. This enables comprehensive management of health and psychological information and real-time response.

[0368] An "information storage device" is a digital recording device for centrally recording and managing an individual's health information and psychological state.

[0369] A "machine learning device" is a device that uses algorithms to analyze an individual's past health status and emotional information, and to evaluate future health trends and risks through data analysis.

[0370] An "output device" is a digital display means for providing users with analyzed health and psychological advice, and is a device that plays a role in presenting information visually or audibly.

[0371] A "real-time monitoring device" is a digital sensor network that continuously monitors an individual's health and emotional state, enabling rapid detection and notification of abnormalities.

[0372] An "identifier" is a unique code or pattern used to identify and manage an individual on a network.

[0373] "Genetic information" refers to biological genetic data that forms the basis for evaluating an individual's long-term health risks and the impact of emotional fluctuations.

[0374] The system for implementing this invention consists of a wearable device, including smart glasses, and a server located in the cloud. The user receives data input and feedback through the smart glasses. The glasses are equipped with a heart rate sensor and voice input function, and collect heart rate and emotional data in real time. This allows for an understanding of the user's health and emotional state.

[0375] The server functions as an information storage device, accumulating vital data such as heart rate and blood pressure using the GOOGLE FIT® API. Furthermore, machine learning models such as Hugging Face's Transformer are used for emotion analysis. This data is analyzed by machine learning equipment to reveal the interrelationships between health status and emotion data.

[0376] The analyzed data is fed back to the user through an output device, and health and psychological advice is provided. For example, if the heart rate exceeds the normal range, the system will notify the user to "pay attention to your health" and, if necessary, notify emergency contacts of the abnormality.

[0377] For example, if a user has consumed a sweet food and is experiencing heightened emotions, the system might advise them to "be mindful of the risk of diabetes and try to have a balanced meal next time."

[0378] Examples of prompt messages include, "Recommend the next action based on the current heart rate and stress level," and "Suggest relaxation techniques to display when the user is detected to be anxious." This allows users to receive personalized feedback in real time.

[0379] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0380] Step 1:

[0381] The device collects biometric information such as the user's heart rate and blood pressure through sensors. The input is direct data from biosensors, and the output is vital data in digital format. The data obtained from the sensors is collected at regular intervals and temporarily stored on the local device.

[0382] Step 2:

[0383] The device collects emotional data from the user through voice input or questionnaires. In this step, the input includes voice data and text input provided by the user, and the output is a category representing emotion. The input emotional content is converted into text using speech recognition technology and analyzed by an emotion analysis engine.

[0384] Step 3:

[0385] The device transmits collected vital and emotional data to a server via the network. Here, data stored within the device serves as input, and data is stored in a database on the server as output. Data transmission is performed using a secure protocol.

[0386] Step 4:

[0387] The server analyzes the accumulated data using a machine learning model. It receives past health information and current emotional data as input and generates analysis results corresponding to the health and emotional state as output. The analysis utilizes the Hugging Face Transformer model and employs deep learning with a generative AI model.

[0388] Step 5:

[0389] The server generates health advice for the user based on the analysis results. In this step, the analysis results are the input, and specific health advice sentences are generated as the output. Prompt sentences are input into the AI ​​model to create interactive advice.

[0390] Step 6:

[0391] The device displays or audibly notifies the user of the generated advice. The input is advice data from the server, and the output is visual or auditory feedback on the user's display or speaker. This allows the user to receive real-time information to help manage their health.

[0392] Step 7:

[0393] The device sends a notification to emergency contacts when it detects an anomaly. Inputs include vital data exceeding a certain threshold and analyzed risk categories, while output is the sending of an SMS or email to emergency contacts. An anomaly detection algorithm, utilizing sensors and models, activates and automatically issues an alert.

[0394] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0395] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0396] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0397] [Third Embodiment]

[0398] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0399] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0400] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0401] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0402] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0403] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0404] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0405] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0406] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0407] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0408] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0409] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0410] As an embodiment of this invention, a system is provided that centrally manages individual health data and provides personalized health support using generating AI. This system includes a database for recording the user's health information, artificial intelligence that generates symptom analysis and medical advice based on that information, and an interface for providing this information to the user.

[0411] When the system is launched, individual health data is centrally managed using a health ID issued by the user. Users input their health data, including past prescription information and diagnostic results. This information is transmitted from the terminal to the server and stored in a database based on the health ID.

[0412] When a user experiences a change in their health during their daily life, they input details of their symptoms and physical condition into the application. This information is sent to a server, where artificial intelligence analyzes the data and compares it with past health data to analyze trends in symptoms. After the analysis, the AI ​​generates necessary medical information and advice for improving daily life, and presents this information to the user through the interface.

[0413] For example, if a user frequently experiences health problems, they can input their symptoms into the application. Based on this input, the server suggests potential stress levels or nutrient deficiencies and generates advice, including dietary plans and exercise optimizations as solutions. This advice is notified to the user in real time, enabling quick action.

[0414] Furthermore, as an optional feature, users can provide their genetic information to the system. By utilizing this genetic information, the artificial intelligence can analyze long-term health risks and suggest preventative measures and medical areas requiring attention.

[0415] In this way, the present invention can provide efficient management of health data and advanced medical support using artificial intelligence, thereby supporting the improvement of individual health.

[0416] The following describes the processing flow.

[0417] Step 1:

[0418] The user downloads the application and registers an account by entering personal information. The information entered by the user is sent from the device to the server, which generates a health ID for each user and stores it in a database.

[0419] Step 2:

[0420] The user enters past medical information, such as prescription medications and diagnostic results, into the application. The device sends this information to a server, which updates the individual's health database based on their health ID.

[0421] Step 3:

[0422] The user enters their current health status and symptoms into the application. The device sends this symptom data to a server, and artificial intelligence begins to analyze the entered information.

[0423] Step 4:

[0424] Artificial intelligence on the server references past health information stored in a database and analyzes current symptoms. This identifies potential health problems and areas that need improvement.

[0425] Step 5:

[0426] Artificial intelligence generates appropriate medical advice and suggestions for improving daily life based on the analysis results. This information is sent from the server to the terminal and notified to the user.

[0427] Step 6:

[0428] Based on the advice and recommendations provided, users implement improvements to their lifestyle. They then input their improved health status and feedback into the application, which is then transmitted to the server via their device.

[0429] Step 7:

[0430] The server incorporates the received feedback into the AI's training data, improving the algorithm's accuracy and future disease prediction capabilities. This continuous accumulation and analysis of data provides users with more accurate health support.

[0431] (Example 1)

[0432] Next, we will describe Example 1. 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."

[0433] In modern society, there is a need to efficiently manage individual health information and provide appropriate health advice based on diverse health data. However, conventional systems present challenges such as cumbersome data management and difficulty in providing personalized health support.

[0434] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0435] In this invention, the server includes means for providing an information storage device for storing and managing an individual's health information, means for providing an automated intelligence that references past health data to analyze an individual's health status and performs generation processing, and means for providing an input / output device that outputs the generated information and provides health advice to the individual. This makes it possible to efficiently manage each individual's health information and provide appropriate health support.

[0436] "Health information" refers to data about an individual's health status, including past diagnostic results, prescription drug information, and changes in physical condition.

[0437] An "information storage device" is a device or system for storing data in digital format, and is a device that enables centralized management of personal health information using database and cloud storage technologies.

[0438] "Management" refers to the effective storage and handling of information, encompassing the process of managing data according to specific standards and rules, and updating or deleting information as needed.

[0439] "Automated intelligence" refers to a computer program or system that uses technologies such as machine learning and deep learning to analyze data and make decisions or generate advice on behalf of humans.

[0440] An "input / output device" is an interface device used by a user to input information and receive generated results or advice, and includes computer screens, keyboards, smartphone applications, etc.

[0441] An "identification code" is a unique string of characters or code used to identify each individual, and is used to associate individual health data within an information system.

[0442] "Health advice" refers to suggestions that include specific action plans and medical advice for maintaining or improving health, based on an individual's health condition and lifestyle.

[0443] "Long-term health risks" refer to potential health-related risks that may occur in the future, based on the analysis of genetic information and health data.

[0444] This invention is a system that efficiently manages personal health information and provides personalized health advice using AI generation. The system includes a terminal for data input, a server for storing and processing the information, and a user interface for displaying the advice.

[0445] The terminal consists of an information processing device such as a smartphone or computer, and has an application installed for the user to input their own health data. The health data collected here includes past medical examination results, prescription information, and daily health records.

[0446] The server is equipped with a database and a generative AI model. The database utilizes a relational database system to systematically store health information using individual identification codes as keys. The generative AI model is an automated intelligence built on various machine learning algorithms that analyzes current symptoms based on past health data and creates personalized health advice.

[0447] As a concrete example, when a user frequently experiences health problems, they input their symptoms into the application. This information is sent from the device to the server, where the generated AI model analyzes it. After analysis, the server generates advice such as meal plan suggestions and exercise optimization, and can notify the user in real time.

[0448] An example of a prompt would be, "Based on the user's health data, please suggest ways to improve their current symptoms." This prompt prompts the generative AI model to generate and send appropriate advice.

[0449] This will enable a system that allows users to manage their health appropriately and receive personalized medical support.

[0450] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0451] Step 1:

[0452] Users input health data using their devices. Specifically, they open a dedicated application, fill in past diagnostic results, prescription information, and current health status in an input form, and press the submit button. This operation pre-processes the input data and prepares it for submission.

[0453] Step 2:

[0454] The device sends the entered health data to the server. During transmission, the data is encrypted and reaches the server via the internet using a secure communication protocol. This ensures that the input data is safely transferred to the server.

[0455] Step 3:

[0456] The server stores the received data in a database. The data is classified based on its individual identification code and stored in the information storage device. Specifically, the server executes an SQL query and adds the newly received data to the correct record in the database.

[0457] Step 4:

[0458] When a user experiences a change in their health, they use their device to input the new symptoms. Here, they fill in details of the symptoms and changes in their physical condition in an input form. This information is used to determine whether further analysis is necessary.

[0459] Step 5:

[0460] The server inputs the newly received symptom data into the generating AI model. The model is instructed using the prompt message, "Based on this new symptom data, compare it with past health history and analyze the trend of the symptoms." The generating AI model analyzes the input data based on this prompt and generates health advice as output.

[0461] Step 6:

[0462] The server generates specific health advice based on the analysis results obtained from the generated AI model. This includes dietary guidance and exercise recommendations, and is structured to provide information that directly helps improve the user's health.

[0463] Step 7:

[0464] The user receives advice generated from the server via their device. The server sends the generated advice to the device, which then communicates it to the user in real time through its notification function. This allows the user to receive actionable improvement suggestions immediately.

[0465] Step 8:

[0466] Optionally, users can provide additional genetic information. This allows the server to perform deeper health analyses, assess long-term health risks, and generate new advice.

[0467] (Application Example 1)

[0468] Next, we will explain Application Example 1. In the following explanation, 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."

[0469] In modern life, the amount of information available to maintain and improve an individual's health is vast, and it is not easy for individuals to utilize this information effectively. In particular, there is a need for effective means to link health information with dietary choices and incorporate them into daily life. However, conventional systems have the problem of not easily integrating individual health data with meal plans. Therefore, a system is needed to efficiently provide meal suggestions and delivery that take into account an individual's health condition.

[0470] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0471] In this invention, the server includes means for information management for recording and managing an individual's health information, means for information processing for referencing past health data and performing generation processing to analyze an individual's health status, and means for proposing an optimal nutritional intake plan based on the individual's health data and mediating the delivery of prepared foods. This makes it possible to quickly propose a meal plan tailored to an individual's health status and to facilitate meal delivery.

[0472] "Information management means" refers to technologies and devices used to record, organize, and manage an individual's health information.

[0473] "Information processing means" refers to technologies and devices for analyzing an individual's health status based on past data and generating results.

[0474] A "dialogue device" is an interface or device that uses generated information to provide medical suggestions and guidance to an individual.

[0475] A "nutritional intake plan" is a plan that proposes a suitable diet and nutritional supplementation method for an individual based on their health data.

[0476] "Means of mediating the delivery of prepared foods" refers to technologies and systems that facilitate the process of selecting specific foods based on a proposed nutritional plan and delivering them to users.

[0477] The system designed to realize this application embodies a series of processes, from collecting and analyzing individual health data, proposing an optimal meal plan based on the results, to delivering suitable food. Specifically, it is implemented through a combination of servers, terminals, artificial intelligence, and a delivery service.

[0478] The server provides an information management system for centrally managing individual health information. This information is stored and accessible in a database located in a cloud environment (e.g., AWS RDS). The terminal functions as an interface where users input their health status and preferences, and the entered data is sent to the server. The transmitted data is processed using an AI analysis engine (e.g., Google AI Platform), which is an information processing tool. The AI ​​generates an optimal nutrition plan for each individual's health condition by comparing it with past health data.

[0479] Based on the generated plan, the server facilitates food delivery by presenting the menu to the user through a delivery service API (e.g., a common food delivery service API) and making ordering easier. This process is carried out quickly and efficiently through an automated series of operations.

[0480] For example, if a user enters into the device that they "recently feel tired," the AI ​​analyzes this and generates a meal plan that selects iron-rich ingredients. Based on this, appropriate dishes are chosen, and the user is presented with the most suitable menu. Once the user reviews the menu and confirms their order, the food is delivered to the specified location.

[0481] Examples of prompts to input into a generative AI model:

[0482] I've been feeling tired lately. Please suggest a meal plan that takes my health into consideration.

[0483] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0484] Step 1:

[0485] The terminal accepts user health information, current physical condition, and preference information. The entered information is sent to a server in a cloud environment. The input in this step is direct information from the user, and the output is data transmission to the server.

[0486] Step 2:

[0487] The server saves the received data to a cloud database. During this process, information management tools are used to organize and manage the data. The input here is the user information sent in step 1, and the output is the storage of the data in an organized format into the database.

[0488] Step 3:

[0489] The AI ​​analysis engine runs on a server and compares stored health data with historical data. This allows for an analysis of the subject's health status. The input is health information and historical health records stored in the database, and the output is the analysis results.

[0490] Step 4:

[0491] The server creates an optimal nutrition plan for each individual based on the analysis results generated by the AI. Specifically, it generates a detailed meal plan that takes into account the necessary nutrients. The input is the analysis results from the AI, and the output is the proposed meal plan.

[0492] Step 5:

[0493] The server delivers the generated meal plan to the terminal and presents it to the user. The user reviews the plan and selects their order. The input is the meal plan, and the output is the presentation of the plan to the user and the order confirmation.

[0494] Step 6:

[0495] Once the user confirms their order, the server arranges for the delivery of the selected food items via the delivery service API. The input is the order information confirmed by the user, and the output is the delivery instruction to the delivery service.

[0496] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0497] This invention provides a system that achieves more comprehensive health support by managing an individual's health information in detail while also recognizing the user's emotional state. This system incorporates a database, artificial intelligence, an interface, and an emotion engine, enabling the provision of advice based on the user's emotions.

[0498] The application allows users to not only input their personal health data but also record their emotional state. This emotional information is collected, for example, by evaluating the user's mental state through periodic questionnaires. The device sends this information to a server, which centrally records the health information and emotional data in a database.

[0499] The system receives emotional information from the user, and an emotion engine analyzes this information to identify the user's current emotional state. This analyzed information is processed by artificial intelligence, and a health status assessment is performed by combining emotional data and health data. Based on this, medical advice and lifestyle improvement suggestions are generated.

[0500] For example, if a user is experiencing a lot of stress, the system analyzes their emotional information and provides specific suggestions for stress reduction activities and diet. Furthermore, it can predict the impact of stress on the body based on past health data and recommend seeking medical attention if necessary.

[0501] This system allows users to receive a more comprehensive approach to their health management, addressing both physical and psychological aspects. The organic integration of artificial intelligence and an emotion engine enables the provision of real-time, personalized health support, contributing to extending users' healthy lifespans.

[0502] The following describes the processing flow.

[0503] Step 1:

[0504] The user launches the application and inputs health information, daily physical condition, and emotional state. Emotional state is entered through self-assessment and multiple-choice questionnaires.

[0505] Step 2:

[0506] The terminal sends the entered health and emotional information to the server. The server stores the information in a database and updates the records based on each user's health ID.

[0507] Step 3:

[0508] On the server, the emotion engine analyzes emotional information. For example, it evaluates stress levels and positive / negative emotional tendencies from emotional data.

[0509] Step 4:

[0510] Artificial intelligence combines analysis results from an emotion engine with historical health information from a database to assess the user's overall health status. This includes analyzing the potential impact of emotions on physical condition.

[0511] Step 5:

[0512] Artificial intelligence generates medical advice and lifestyle improvement suggestions based on the evaluation results. The generated information includes exercise suggestions for stress management and meal plans to support emotional well-being.

[0513] Step 6:

[0514] The server sends the generated advice to the terminal, which then notifies the user. The user receives the notified information and can take specific actions.

[0515] Step 7:

[0516] The user inputs feedback through the application, based on the results obtained from improving their lifestyle habits according to the advice given. The device then sends this feedback information to the server.

[0517] Step 8:

[0518] The server receives feedback and updates its artificial intelligence algorithms to improve the accuracy of future advice. This enables continuous and effective health support for users.

[0519] (Example 2)

[0520] Next, we will describe Example 2. 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."

[0521] The problem that this invention aims to solve is to enable the comprehensive analysis of physical and psychological elements in individual health management and to provide personalized information in real time. Conventional health management systems have not adequately analyzed emotional states, making it difficult to manage an individual's mind and body as a whole and provide appropriate health support.

[0522] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0523] In this invention, the server includes means for data storage for recording and managing an individual's health information and emotional state; means for an analysis engine for analyzing emotional information and identifying an individual's emotional state; and means for artificial intelligence for evaluating the overall health state and generating advice based on the analyzed emotional and health information. This enables the integrated management of physical and emotional elements in an individual's health and allows for the provision of appropriate advice to the user tailored to their individual condition.

[0524] "Personal health information" refers to data that indicates the physical health status of individual users, and mainly includes information such as physical measurements and lifestyle records.

[0525] "Emotional state" refers to data that indicates the user's psychological or emotional state, including information that evaluates stress levels, mood swings, and other factors.

[0526] "Data storage" refers to a digital storage device or system for securely and effectively recording and storing health and emotional information.

[0527] An "analysis engine" is a computer program or script used to analyze input data and identify the user's emotional state.

[0528] "Artificial intelligence" is a program or algorithm that performs data analysis and prediction to help assess health conditions and generate advice.

[0529] An "interface" is a user interface or system design that presents generated information to the user and enables the exchange of input information.

[0530] An "online server" is a remote computing resource used for storing, managing, and processing data in a cloud environment.

[0531] "Identification information" refers to data or codes used to uniquely identify an individual user.

[0532] "Genetic information" refers to data that shows an individual's genetic structure and is information that may affect health risks and physical characteristics.

[0533] A "health hazard" is a factor that indicates a potential risk or expected impairment to an individual's health.

[0534] This invention is a system that integrates and manages an individual's health information and emotional state, and provides personalized health advice to the user. This system comprises data storage, an analysis engine, artificial intelligence, and a user interface. Each component is described below.

[0535] Firstly, users input their health and emotional data through their devices. This process involves using a dedicated application on a digital device such as a smartphone or tablet to record physical information such as weight and blood pressure, as well as providing emotional information such as stress levels and mood in the form of questionnaires.

[0536] The terminal sends the entered information to the server. The server uses data storage to highly encrypt this information and manage it securely in a centralized manner. The data storage is associated with consistent user identification information, ensuring secure data management.

[0537] Next, the server inputs emotional information into the analysis engine to identify the detailed emotional state. The analysis engine uses natural language processing technology to calculate an emotional score from the text data and classify the user's emotional state.

[0538] This emotional and health data is further processed by artificial intelligence. Using a generative AI model, past data and current state are analyzed to assess the user's overall health status. The AI ​​predicts future health risks and provides lifestyle improvement measures as needed.

[0539] Finally, the server returns the generated information to the terminal and displays it on the user interface. Users can receive this information in real time and use it as a guide in their daily lives.

[0540] For example, if a user inputs information such as "I've been feeling stressed lately," the system can suggest specific activities and dietary changes to reduce stress. It also provides comprehensive support, including recommending a visit to a medical institution if necessary. This prompting allows users to gain insights into leading a healthier life.

[0541] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0542] Step 1:

[0543] Users input health and emotional data using their devices. Specifically, they log in to a dedicated application and record health indicators such as weight and blood pressure, as well as emotional states such as mood and stress levels by answering questions presented in a questionnaire format. The entered data is stored in a temporary database on the device and prepared for the next processing step.

[0544] Step 2:

[0545] The device transmits entered health and emotional data to the server. The transmitted data is securely protected using encryption protocols and safely stored in the server's data storage. The input data is linked to identification information and centrally managed in a way that corresponds to individual user accounts.

[0546] Step 3:

[0547] The server inputs stored emotional data into an analysis engine and performs emotional analysis. Specifically, it uses natural language processing technology to calculate an emotional score from text-based data and classifies the user's emotional state. The resulting emotional score is reported as high stress, moderate stress, low stress, etc.

[0548] Step 4:

[0549] The server combines the emotion score obtained from the analysis engine with stored health data to perform a comprehensive health status assessment using artificial intelligence. A generative AI model is used in this assessment process, taking into account past health information and current emotional state to assess the user's current and future health risks. The output generated in this step consists of specific advice for lifestyle improvement and the results of the risk assessment.

[0550] Step 5:

[0551] The server sends the generated advice and evaluation results to the terminal. The terminal displays this information in the user interface. Specifically, the user can launch the application and view the customized feedback and suggestions. This makes it easier for the user to monitor their health status in real time and take necessary actions.

[0552] (Application Example 2)

[0553] Next, we will explain application example 2. In the following explanation, 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."

[0554] Many modern health management systems focus heavily on physical health information and fail to adequately consider psychological factors. Furthermore, few systems provide rapid responses or warnings regarding real-time changes in health status and emotions. Additionally, the lack of mechanisms for integrating emotional and health data when providing personalized health support limits the effectiveness of improving individual safety and quality of life.

[0555] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0556] In this invention, the server includes means for an information storage device for recording and managing an individual's health information and psychological state; means for a machine learning device that references past data and performs analytical processing to analyze an individual's health and emotional information; means for an output device that outputs the analyzed information and provides health and psychological advice to the individual; and means for a device that monitors an individual's health and emotional state in real time and notifies an external party if an abnormality is detected. This enables comprehensive management of health and psychological information and real-time response.

[0557] An "information storage device" is a digital recording device for centrally recording and managing an individual's health information and psychological state.

[0558] A "machine learning device" is a device that uses algorithms to analyze an individual's past health status and emotional information, and to evaluate future health trends and risks through data analysis.

[0559] An "output device" is a digital display means for providing users with analyzed health and psychological advice, and is a device that plays a role in presenting information visually or audibly.

[0560] A "real-time monitoring device" is a digital sensor network that continuously monitors an individual's health and emotional state, enabling rapid detection and notification of abnormalities.

[0561] An "identifier" is a unique code or pattern used to identify and manage an individual on a network.

[0562] "Genetic information" refers to biological genetic data that forms the basis for evaluating an individual's long-term health risks and the impact of emotional fluctuations.

[0563] The system for implementing this invention consists of a wearable device, including smart glasses, and a server located in the cloud. The user receives data input and feedback through the smart glasses. The glasses are equipped with a heart rate sensor and voice input function, and collect heart rate and emotional data in real time. This allows for an understanding of the user's health and emotional state.

[0564] The server functions as an information storage device, accumulating vital data such as heart rate and blood pressure using the Google Fit API. Machine learning models such as Hugging Face's Transformer are used for emotion analysis. This data is analyzed by machine learning equipment to reveal the interrelationships between health status and emotional data.

[0565] The analyzed data is fed back to the user through an output device, and health and psychological advice is provided. For example, if the heart rate exceeds the normal range, the system will notify the user to "pay attention to your health" and, if necessary, notify emergency contacts of the abnormality.

[0566] For example, if a user has consumed a sweet food and is experiencing heightened emotions, the system might advise them to "be mindful of the risk of diabetes and try to have a balanced meal next time."

[0567] Examples of prompt messages include, "Recommend the next action based on the current heart rate and stress level," and "Suggest relaxation techniques to display when the user is detected to be anxious." This allows users to receive personalized feedback in real time.

[0568] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0569] Step 1:

[0570] The device collects biometric information such as the user's heart rate and blood pressure through sensors. The input is direct data from biosensors, and the output is vital data in digital format. The data obtained from the sensors is collected at regular intervals and temporarily stored on the local device.

[0571] Step 2:

[0572] The device collects emotional data from the user through voice input or questionnaires. In this step, the input includes voice data and text input provided by the user, and the output is a category representing emotion. The input emotional content is converted into text using speech recognition technology and analyzed by an emotion analysis engine.

[0573] Step 3:

[0574] The device transmits collected vital and emotional data to a server via the network. Here, data stored within the device serves as input, and data is stored in a database on the server as output. Data transmission is performed using a secure protocol.

[0575] Step 4:

[0576] The server analyzes the accumulated data using a machine learning model. It receives past health information and current emotional data as input and generates analysis results corresponding to the health and emotional state as output. The analysis utilizes the Hugging Face Transformer model and employs deep learning with a generative AI model.

[0577] Step 5:

[0578] The server generates health advice for the user based on the analysis results. In this step, the analysis results are the input, and specific health advice sentences are generated as the output. Prompt sentences are input into the AI ​​model to create interactive advice.

[0579] Step 6:

[0580] The device displays or audibly notifies the user of the generated advice. The input is advice data from the server, and the output is visual or auditory feedback on the user's display or speaker. This allows the user to receive real-time information to help manage their health.

[0581] Step 7:

[0582] The device sends a notification to emergency contacts when it detects an anomaly. Inputs include vital data exceeding a certain threshold and analyzed risk categories, while output is the sending of an SMS or email to emergency contacts. An anomaly detection algorithm, utilizing sensors and models, activates and automatically issues an alert.

[0583] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0584] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0585] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0586] [Fourth Embodiment]

[0587] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0588] As shown in Figure 7, the 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.

[0589] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0590] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0591] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0592] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0593] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0594] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0595] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0596] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0597] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0598] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0599] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0600] As an embodiment of this invention, a system is provided that centrally manages individual health data and provides personalized health support using generating AI. This system includes a database for recording the user's health information, artificial intelligence that generates symptom analysis and medical advice based on that information, and an interface for providing this information to the user.

[0601] When the system is launched, individual health data is centrally managed using a health ID issued by the user. Users input their health data, including past prescription information and diagnostic results. This information is transmitted from the terminal to the server and stored in a database based on the health ID.

[0602] When a user experiences a change in their health during their daily life, they input details of their symptoms and physical condition into the application. This information is sent to a server, where artificial intelligence analyzes the data and compares it with past health data to analyze trends in symptoms. After the analysis, the AI ​​generates necessary medical information and advice for improving daily life, and presents this information to the user through the interface.

[0603] For example, if a user frequently experiences health problems, they can input their symptoms into the application. Based on this input, the server suggests potential stress levels or nutrient deficiencies and generates advice, including dietary plans and exercise optimizations as solutions. This advice is notified to the user in real time, enabling quick action.

[0604] Furthermore, as an optional feature, users can provide their genetic information to the system. By utilizing this genetic information, the artificial intelligence can analyze long-term health risks and suggest preventative measures and medical areas requiring attention.

[0605] In this way, the present invention can provide efficient management of health data and advanced medical support using artificial intelligence, thereby supporting the improvement of individual health.

[0606] The following describes the processing flow.

[0607] Step 1:

[0608] The user downloads the application and registers an account by entering personal information. The information entered by the user is sent from the device to the server, which generates a health ID for each user and stores it in a database.

[0609] Step 2:

[0610] The user enters past medical information, such as prescription medications and diagnostic results, into the application. The device sends this information to a server, which updates the individual's health database based on their health ID.

[0611] Step 3:

[0612] The user enters their current health status and symptoms into the application. The device sends this symptom data to a server, and artificial intelligence begins to analyze the entered information.

[0613] Step 4:

[0614] Artificial intelligence on the server references past health information stored in a database and analyzes current symptoms. This identifies potential health problems and areas that need improvement.

[0615] Step 5:

[0616] Artificial intelligence generates appropriate medical advice and suggestions for improving daily life based on the analysis results. This information is sent from the server to the terminal and notified to the user.

[0617] Step 6:

[0618] Based on the advice and recommendations provided, users implement improvements to their lifestyle. They then input their improved health status and feedback into the application, which is then transmitted to the server via their device.

[0619] Step 7:

[0620] The server incorporates the received feedback into the AI's training data, improving the algorithm's accuracy and future disease prediction capabilities. This continuous accumulation and analysis of data provides users with more accurate health support.

[0621] (Example 1)

[0622] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0623] In modern society, there is a need to efficiently manage individual health information and provide appropriate health advice based on diverse health data. However, conventional systems present challenges such as cumbersome data management and difficulty in providing personalized health support.

[0624] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0625] In this invention, the server includes means for providing an information storage device for storing and managing an individual's health information, means for providing an automated intelligence that references past health data to analyze an individual's health status and performs generation processing, and means for providing an input / output device that outputs the generated information and provides health advice to the individual. This makes it possible to efficiently manage each individual's health information and provide appropriate health support.

[0626] "Health information" refers to data about an individual's health status, including past diagnostic results, prescription drug information, and changes in physical condition.

[0627] An "information storage device" is a device or system for storing data in digital format, and is a device that enables centralized management of personal health information using database and cloud storage technologies.

[0628] "Management" refers to the effective storage and handling of information, encompassing the process of managing data according to specific standards and rules, and updating or deleting information as needed.

[0629] "Automated intelligence" refers to a computer program or system that uses technologies such as machine learning and deep learning to analyze data and make decisions or generate advice on behalf of humans.

[0630] An "input / output device" is an interface device used by a user to input information and receive generated results or advice, and includes computer screens, keyboards, smartphone applications, etc.

[0631] An "identification code" is a unique string of characters or code used to identify each individual, and is used to associate individual health data within an information system.

[0632] "Health advice" refers to suggestions that include specific action plans and medical advice for maintaining or improving health, based on an individual's health condition and lifestyle.

[0633] "Long-term health risks" refer to potential health-related risks that may occur in the future, based on the analysis of genetic information and health data.

[0634] This invention is a system that efficiently manages personal health information and provides personalized health advice using AI generation. The system includes a terminal for data input, a server for storing and processing the information, and a user interface for displaying the advice.

[0635] The terminal consists of an information processing device such as a smartphone or computer, and has an application installed for the user to input their own health data. The health data collected here includes past medical examination results, prescription information, and daily health records.

[0636] The server is equipped with a database and a generative AI model. The database utilizes a relational database system to systematically store health information using individual identification codes as keys. The generative AI model is an automated intelligence built on various machine learning algorithms that analyzes current symptoms based on past health data and creates personalized health advice.

[0637] As a concrete example, when a user frequently experiences health problems, they input their symptoms into the application. This information is sent from the device to the server, where the generated AI model analyzes it. After analysis, the server generates advice such as meal plan suggestions and exercise optimization, and can notify the user in real time.

[0638] An example of a prompt would be, "Based on the user's health data, please suggest ways to improve their current symptoms." This prompt prompts the generative AI model to generate and send appropriate advice.

[0639] This will enable a system that allows users to manage their health appropriately and receive personalized medical support.

[0640] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0641] Step 1:

[0642] Users input health data using their devices. Specifically, they open a dedicated application, fill in past diagnostic results, prescription information, and current health status in an input form, and press the submit button. This operation pre-processes the input data and prepares it for submission.

[0643] Step 2:

[0644] The device sends the entered health data to the server. During transmission, the data is encrypted and reaches the server via the internet using a secure communication protocol. This ensures that the input data is safely transferred to the server.

[0645] Step 3:

[0646] The server stores the received data in a database. The data is classified based on its individual identification code and stored in the information storage device. Specifically, the server executes an SQL query and adds the newly received data to the correct record in the database.

[0647] Step 4:

[0648] When a user experiences a change in their health, they use their device to input the new symptoms. Here, they fill in details of the symptoms and changes in their physical condition in an input form. This information is used to determine whether further analysis is necessary.

[0649] Step 5:

[0650] The server inputs the newly received symptom data into the generating AI model. The model is instructed using the prompt message, "Based on this new symptom data, compare it with past health history and analyze the trend of the symptoms." The generating AI model analyzes the input data based on this prompt and generates health advice as output.

[0651] Step 6:

[0652] The server generates specific health advice based on the analysis results obtained from the generated AI model. This includes dietary guidance and exercise recommendations, and is structured to provide information that directly helps improve the user's health.

[0653] Step 7:

[0654] The user receives advice generated from the server via their device. The server sends the generated advice to the device, which then communicates it to the user in real time through its notification function. This allows the user to receive actionable improvement suggestions immediately.

[0655] Step 8:

[0656] Optionally, users can provide additional genetic information. This allows the server to perform deeper health analyses, assess long-term health risks, and generate new advice.

[0657] (Application Example 1)

[0658] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0659] In modern life, the amount of information available to maintain and improve an individual's health is vast, and it is not easy for individuals to utilize this information effectively. In particular, there is a need for effective means to link health information with dietary choices and incorporate them into daily life. However, conventional systems have the problem of not easily integrating individual health data with meal plans. Therefore, a system is needed to efficiently provide meal suggestions and delivery that take into account an individual's health condition.

[0660] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0661] In this invention, the server includes means for information management for recording and managing an individual's health information, means for information processing for referencing past health data and performing generation processing to analyze an individual's health status, and means for proposing an optimal nutritional intake plan based on the individual's health data and mediating the delivery of prepared foods. This makes it possible to quickly propose a meal plan tailored to an individual's health status and to facilitate meal delivery.

[0662] "Information management means" refers to technologies and devices used to record, organize, and manage an individual's health information.

[0663] "Information processing means" refers to technologies and devices for analyzing an individual's health status based on past data and generating results.

[0664] A "dialogue device" is an interface or device that uses generated information to provide medical suggestions and guidance to an individual.

[0665] A "nutritional intake plan" is a plan that proposes a suitable diet and nutritional supplementation method for an individual based on their health data.

[0666] "Means of mediating the delivery of prepared foods" refers to technologies and systems that facilitate the process of selecting specific foods based on a proposed nutritional plan and delivering them to users.

[0667] The system designed to realize this application embodies a series of processes, from collecting and analyzing individual health data, proposing an optimal meal plan based on the results, to delivering suitable food. Specifically, it is implemented through a combination of servers, terminals, artificial intelligence, and a delivery service.

[0668] The server provides an information management system for centrally managing individual health information. This information is stored and accessible in a database located in a cloud environment (e.g., AWS RDS). The terminal functions as an interface where users input their health status and preferences, and the entered data is sent to the server. The transmitted data is processed using an AI analysis engine (e.g., Google AI Platform), which is an information processing tool. The AI ​​generates an optimal nutrition plan for each individual's health condition by comparing it with past health data.

[0669] Based on the generated plan, the server facilitates food delivery by presenting the menu to the user through a delivery service API (e.g., a common food delivery service API) and making ordering easier. This process is carried out quickly and efficiently through an automated series of operations.

[0670] For example, if a user enters into the device that they "recently feel tired," the AI ​​analyzes this and generates a meal plan that selects iron-rich ingredients. Based on this, appropriate dishes are chosen, and the user is presented with the most suitable menu. Once the user reviews the menu and confirms their order, the food is delivered to the specified location.

[0671] Examples of prompts to input into a generative AI model:

[0672] I've been feeling tired lately. Please suggest a meal plan that takes my health into consideration.

[0673] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0674] Step 1:

[0675] The terminal accepts user health information, current physical condition, and preference information. The entered information is sent to a server in a cloud environment. The input in this step is direct information from the user, and the output is data transmission to the server.

[0676] Step 2:

[0677] The server saves the received data to a cloud database. During this process, information management tools are used to organize and manage the data. The input here is the user information sent in step 1, and the output is the storage of the data in an organized format into the database.

[0678] Step 3:

[0679] The AI ​​analysis engine runs on a server and compares stored health data with historical data. This allows for an analysis of the subject's health status. The input is health information and historical health records stored in the database, and the output is the analysis results.

[0680] Step 4:

[0681] The server creates an optimal nutrition plan for each individual based on the analysis results generated by the AI. Specifically, it generates a detailed meal plan that takes into account the necessary nutrients. The input is the analysis results from the AI, and the output is the proposed meal plan.

[0682] Step 5:

[0683] The server delivers the generated meal plan to the terminal and presents it to the user. The user reviews the plan and selects their order. The input is the meal plan, and the output is the presentation of the plan to the user and the order confirmation.

[0684] Step 6:

[0685] Once the user confirms their order, the server arranges for the delivery of the selected food items via the delivery service API. The input is the order information confirmed by the user, and the output is the delivery instruction to the delivery service.

[0686] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0687] This invention provides a system that achieves more comprehensive health support by managing an individual's health information in detail while also recognizing the user's emotional state. This system incorporates a database, artificial intelligence, an interface, and an emotion engine, enabling the provision of advice based on the user's emotions.

[0688] The application allows users to not only input their personal health data but also record their emotional state. This emotional information is collected, for example, by evaluating the user's mental state through periodic questionnaires. The device sends this information to a server, which centrally records the health information and emotional data in a database.

[0689] The system receives emotional information from the user, and an emotion engine analyzes this information to identify the user's current emotional state. This analyzed information is processed by artificial intelligence, and a health status assessment is performed by combining emotional data and health data. Based on this, medical advice and lifestyle improvement suggestions are generated.

[0690] For example, if a user is experiencing a lot of stress, the system analyzes their emotional information and provides specific suggestions for stress reduction activities and diet. Furthermore, it can predict the impact of stress on the body based on past health data and recommend seeking medical attention if necessary.

[0691] This system allows users to receive a more comprehensive approach to their health management, addressing both physical and psychological aspects. The organic integration of artificial intelligence and an emotion engine enables the provision of real-time, personalized health support, contributing to extending users' healthy lifespans.

[0692] The following describes the processing flow.

[0693] Step 1:

[0694] The user launches the application and inputs health information, daily physical condition, and emotional state. Emotional state is entered through self-assessment and multiple-choice questionnaires.

[0695] Step 2:

[0696] The terminal sends the entered health and emotional information to the server. The server stores the information in a database and updates the records based on each user's health ID.

[0697] Step 3:

[0698] On the server, the emotion engine analyzes emotional information. For example, it evaluates stress levels and positive / negative emotional tendencies from emotional data.

[0699] Step 4:

[0700] Artificial intelligence combines analysis results from an emotion engine with historical health information from a database to assess the user's overall health status. This includes analyzing the potential impact of emotions on physical condition.

[0701] Step 5:

[0702] Artificial intelligence generates medical advice and lifestyle improvement suggestions based on the evaluation results. The generated information includes exercise suggestions for stress management and meal plans to support emotional well-being.

[0703] Step 6:

[0704] The server sends the generated advice to the terminal, which then notifies the user. The user receives the notified information and can take specific actions.

[0705] Step 7:

[0706] The user inputs feedback through the application, based on the results obtained from improving their lifestyle habits according to the advice given. The device then sends this feedback information to the server.

[0707] Step 8:

[0708] The server receives feedback and updates its artificial intelligence algorithms to improve the accuracy of future advice. This enables continuous and effective health support for users.

[0709] (Example 2)

[0710] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0711] The problem that this invention aims to solve is to enable the comprehensive analysis of physical and psychological elements in individual health management and to provide personalized information in real time. Conventional health management systems have not adequately analyzed emotional states, making it difficult to manage an individual's mind and body as a whole and provide appropriate health support.

[0712] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0713] In this invention, the server includes means for data storage for recording and managing an individual's health information and emotional state; means for an analysis engine for analyzing emotional information and identifying an individual's emotional state; and means for artificial intelligence for evaluating the overall health state and generating advice based on the analyzed emotional and health information. This enables the integrated management of physical and emotional elements in an individual's health and allows for the provision of appropriate advice to the user tailored to their individual condition.

[0714] "Personal health information" refers to data that indicates the physical health status of individual users, and mainly includes information such as physical measurements and lifestyle records.

[0715] "Emotional state" refers to data that indicates the user's psychological or emotional state, including information that evaluates stress levels, mood swings, and other factors.

[0716] "Data storage" refers to a digital storage device or system for securely and effectively recording and storing health and emotional information.

[0717] An "analysis engine" is a computer program or script used to analyze input data and identify the user's emotional state.

[0718] "Artificial intelligence" is a program or algorithm that performs data analysis and prediction to help assess health conditions and generate advice.

[0719] An "interface" is a user interface or system design that presents generated information to the user and enables the exchange of input information.

[0720] An "online server" is a remote computing resource used for storing, managing, and processing data in a cloud environment.

[0721] "Identification information" refers to data or codes used to uniquely identify an individual user.

[0722] "Genetic information" refers to data that shows an individual's genetic structure and is information that may affect health risks and physical characteristics.

[0723] A "health hazard" is a factor that indicates a potential risk or expected impairment to an individual's health.

[0724] This invention is a system that integrates and manages an individual's health information and emotional state, and provides personalized health advice to the user. This system comprises data storage, an analysis engine, artificial intelligence, and a user interface. Each component is described below.

[0725] Firstly, users input their health and emotional data through their devices. This process involves using a dedicated application on a digital device such as a smartphone or tablet to record physical information such as weight and blood pressure, as well as providing emotional information such as stress levels and mood in the form of questionnaires.

[0726] The terminal sends the entered information to the server. The server uses data storage to highly encrypt this information and manage it securely in a centralized manner. The data storage is associated with consistent user identification information, ensuring secure data management.

[0727] Next, the server inputs emotional information into the analysis engine to identify the detailed emotional state. The analysis engine uses natural language processing technology to calculate an emotional score from the text data and classify the user's emotional state.

[0728] This emotional and health data is further processed by artificial intelligence. Using a generative AI model, past data and current state are analyzed to assess the user's overall health status. The AI ​​predicts future health risks and provides lifestyle improvement measures as needed.

[0729] Finally, the server returns the generated information to the terminal and displays it on the user interface. Users can receive this information in real time and use it as a guide in their daily lives.

[0730] For example, if a user inputs information such as "I've been feeling stressed lately," the system can suggest specific activities and dietary changes to reduce stress. It also provides comprehensive support, including recommending a visit to a medical institution if necessary. This prompting allows users to gain insights into leading a healthier life.

[0731] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0732] Step 1:

[0733] Users input health and emotional data using their devices. Specifically, they log in to a dedicated application and record health indicators such as weight and blood pressure, as well as emotional states such as mood and stress levels by answering questions presented in a questionnaire format. The entered data is stored in a temporary database on the device and prepared for the next processing step.

[0734] Step 2:

[0735] The device transmits entered health and emotional data to the server. The transmitted data is securely protected using encryption protocols and safely stored in the server's data storage. The input data is linked to identification information and centrally managed in a way that corresponds to individual user accounts.

[0736] Step 3:

[0737] The server inputs stored emotional data into an analysis engine and performs emotional analysis. Specifically, it uses natural language processing technology to calculate an emotional score from text-based data and classifies the user's emotional state. The resulting emotional score is reported as high stress, moderate stress, low stress, etc.

[0738] Step 4:

[0739] The server combines the emotion score obtained from the analysis engine with stored health data to perform a comprehensive health status assessment using artificial intelligence. A generative AI model is used in this assessment process, taking into account past health information and current emotional state to assess the user's current and future health risks. The output generated in this step consists of specific advice for lifestyle improvement and the results of the risk assessment.

[0740] Step 5:

[0741] The server sends the generated advice and evaluation results to the terminal. The terminal displays this information in the user interface. Specifically, the user can launch the application and view the customized feedback and suggestions. This makes it easier for the user to monitor their health status in real time and take necessary actions.

[0742] (Application Example 2)

[0743] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0744] Many modern health management systems focus heavily on physical health information and fail to adequately consider psychological factors. Furthermore, few systems provide rapid responses or warnings regarding real-time changes in health status and emotions. Additionally, the lack of mechanisms for integrating emotional and health data when providing personalized health support limits the effectiveness of improving individual safety and quality of life.

[0745] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0746] In this invention, the server includes means for an information storage device for recording and managing an individual's health information and psychological state; means for a machine learning device that references past data and performs analytical processing to analyze an individual's health and emotional information; means for an output device that outputs the analyzed information and provides health and psychological advice to the individual; and means for a device that monitors an individual's health and emotional state in real time and notifies an external party if an abnormality is detected. This enables comprehensive management of health and psychological information and real-time response.

[0747] An "information storage device" is a digital recording device for centrally recording and managing an individual's health information and psychological state.

[0748] A "machine learning device" is a device that uses algorithms to analyze an individual's past health status and emotional information, and to evaluate future health trends and risks through data analysis.

[0749] An "output device" is a digital display means for providing users with analyzed health and psychological advice, and is a device that plays a role in presenting information visually or audibly.

[0750] A "real-time monitoring device" is a digital sensor network that continuously monitors an individual's health and emotional state, enabling rapid detection and notification of abnormalities.

[0751] An "identifier" is a unique code or pattern used to identify and manage an individual on a network.

[0752] "Genetic information" refers to biological genetic data that forms the basis for evaluating an individual's long-term health risks and the impact of emotional fluctuations.

[0753] The system for implementing this invention consists of a wearable device, including smart glasses, and a server located in the cloud. The user receives data input and feedback through the smart glasses. The glasses are equipped with a heart rate sensor and voice input function, and collect heart rate and emotional data in real time. This allows for an understanding of the user's health and emotional state.

[0754] The server functions as an information storage device, accumulating vital data such as heart rate and blood pressure using the Google Fit API. Machine learning models such as Hugging Face's Transformer are used for emotion analysis. This data is analyzed by machine learning equipment to reveal the interrelationships between health status and emotional data.

[0755] The analyzed data is fed back to the user through an output device, and health and psychological advice is provided. For example, if the heart rate exceeds the normal range, the system will notify the user to "pay attention to your health" and, if necessary, notify emergency contacts of the abnormality.

[0756] For example, if a user has consumed a sweet food and is experiencing heightened emotions, the system might advise them to "be mindful of the risk of diabetes and try to have a balanced meal next time."

[0757] Examples of prompt messages include, "Recommend the next action based on the current heart rate and stress level," and "Suggest relaxation techniques to display when the user is detected to be anxious." This allows users to receive personalized feedback in real time.

[0758] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0759] Step 1:

[0760] The device collects biometric information such as the user's heart rate and blood pressure through sensors. The input is direct data from biosensors, and the output is vital data in digital format. The data obtained from the sensors is collected at regular intervals and temporarily stored on the local device.

[0761] Step 2:

[0762] The device collects emotional data from the user through voice input or questionnaires. In this step, the input includes voice data and text input provided by the user, and the output is a category representing emotion. The input emotional content is converted into text using speech recognition technology and analyzed by an emotion analysis engine.

[0763] Step 3:

[0764] The device transmits collected vital and emotional data to a server via the network. Here, data stored within the device serves as input, and data is stored in a database on the server as output. Data transmission is performed using a secure protocol.

[0765] Step 4:

[0766] The server analyzes the accumulated data using a machine learning model. It receives past health information and current emotional data as input and generates analysis results corresponding to the health and emotional state as output. The analysis utilizes the Hugging Face Transformer model and employs deep learning with a generative AI model.

[0767] Step 5:

[0768] The server generates health advice for the user based on the analysis results. In this step, the analysis results are the input, and specific health advice sentences are generated as the output. Prompt sentences are input into the AI ​​model to create interactive advice.

[0769] Step 6:

[0770] The device displays or audibly notifies the user of the generated advice. The input is advice data from the server, and the output is visual or auditory feedback on the user's display or speaker. This allows the user to receive real-time information to help manage their health.

[0771] Step 7:

[0772] The device sends a notification to emergency contacts when it detects an anomaly. Inputs include vital data exceeding a certain threshold and analyzed risk categories, while output is the sending of an SMS or email to emergency contacts. An anomaly detection algorithm, utilizing sensors and models, activates and automatically issues an alert.

[0773] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0774] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0775] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0776] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0777] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0778] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0779] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0780] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0781] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0782] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0783] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0784] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0785] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0786] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0787] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0788] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0789] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0790] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0791] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0792] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0793] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0794] The following is further disclosed regarding the embodiments described above.

[0795] (Claim 1)

[0796] A means of providing a database for recording and managing personal health information,

[0797] A means equipped with artificial intelligence that references past health data and performs generation processing to analyze an individual's health status,

[0798] A means that provides an interface for outputting generated information and providing medical advice to an individual,

[0799] A system that includes this.

[0800] (Claim 2)

[0801] The system according to claim 1, which has a function to generate a health ID for each individual on a cloud server and to centrally manage health information.

[0802] (Claim 3)

[0803] The system according to claim 1, comprising a function to evaluate long-term health risks and generate advice based on genetic information provided by the user.

[0804] "Example 1"

[0805] (Claim 1)

[0806] A means of providing an information storage device for storing and managing personal health information,

[0807] A means equipped with automated intelligence that references past health data and performs generation processing to analyze an individual's health status,

[0808] A means comprising an input / output device that outputs generated information and provides health advice to an individual,

[0809] A system that includes this.

[0810] (Claim 2)

[0811] The system according to claim 1, comprising a function for generating an identification code for each individual and comprehensively managing health information on a distributed information processing device.

[0812] (Claim 3)

[0813] The system according to claim 1, comprising a function to evaluate long-term health risks and generate advice based on genetic information provided by the user.

[0814] "Application Example 1"

[0815] (Claim 1)

[0816] A means of providing information management tools for recording and managing personal health information,

[0817] A means comprising information processing means that references past health data and performs generation processing in order to analyze an individual's health status,

[0818] A means comprising a dialogue device that outputs generated information and provides medical suggestions to an individual,

[0819] A means of proposing an optimal nutritional intake plan based on individual health data and mediating the delivery of prepared foods,

[0820] A system that includes this.

[0821] (Claim 2)

[0822] The system according to claim 1, comprising an information processing means that generates an identification ID for each individual in a cloud environment and has a function for centrally managing health information.

[0823] (Claim 3)

[0824] The system according to claim 1, which has a function to estimate long-term health risks and propose improvement measures based on genetic information provided by the user.

[0825] "Example 2 of combining an emotion engine"

[0826] (Claim 1)

[0827] A means for recording and managing personal health information and emotional states, and a data storage system for this purpose.

[0828] A means equipped with an analysis engine for analyzing emotional information and identifying an individual's emotional state,

[0829] A means equipped with artificial intelligence to evaluate overall health status and generate advice based on analyzed emotional and health information,

[0830] A means that provides an interface for outputting generated information and providing lifestyle improvement guidance to individuals,

[0831] A system that includes this.

[0832] (Claim 2)

[0833] The system according to claim 1, comprising a function for generating individual identification information on an online server and centrally managing health information.

[0834] (Claim 3)

[0835] The system according to claim 1, comprising a function to evaluate long-term health hazards and generate advice based on genetic information provided by the user.

[0836] "Application example 2 of combining emotional engines"

[0837] (Claim 1)

[0838] A means of providing an information storage device for recording and managing an individual's health information and psychological state,

[0839] A means comprising a machine learning device that references past data and performs analytical processing to analyze an individual's health status and emotional information,

[0840] A means comprising an output device that outputs analyzed information and provides health and psychological advice to an individual,

[0841] A means comprising a device that monitors an individual's health and emotional state in real time and notifies an external party if an abnormality is detected,

[0842] A system that includes this.

[0843] (Claim 2)

[0844] The system according to claim 1, which has the function of generating an identifier for each individual on a network and managing health information and emotional information in an integrated manner.

[0845] (Claim 3)

[0846] The system according to claim 1, comprising a function to evaluate long-term health risks and the impact of emotional fluctuations based on genetic information provided by the user, and to generate advice. [Explanation of Symbols]

[0847] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of providing a database for recording and managing personal health information, A means equipped with artificial intelligence that references past health data and performs generation processing to analyze an individual's health status, A means that provides an interface for outputting generated information and providing medical advice to an individual, A system that includes this.

2. The system according to claim 1, which has a function to generate a health ID for each individual on a cloud server and to centrally manage health information.

3. The system according to claim 1, comprising a function to evaluate long-term health risks and generate advice based on genetic information provided by the user.

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