System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting genetic information of an individual; means for collecting nutritional intake data, physical activity data, and sleep pattern data; means for integrating and analyzing the genetic information and the daily life data; means for generating a personalized health plan based on the analysis; and means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, personal health management is becoming increasingly important. However, existing health management systems are difficult to individualize, and there are limitations to their approach of comprehensively utilizing users' genetic information and daily life data. Another issue is the lack of interactive health improvement tools to raise users' health awareness and encourage behavioral change. In particular, optimizing health management and disease prevention by taking genetic factors into account is difficult, making it difficult to implement effective interventions. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention provides the following means: A system is provided that includes a means for collecting an individual's genetic information, a means for collecting nutritional intake data, physical activity data, and sleep pattern data, and a means for integrating and analyzing this data. It also includes a means for generating a personalized health plan based on the analysis results, and a means for providing an interactive health improvement experience using virtual reality (VR) or augmented reality (AR). This system optimizes an individual's health status in real time, increasing user engagement while achieving effective disease prevention and health promotion.

[0006] "Personal genetic information" refers to information about genetic characteristics and risks obtained from an individual's DNA.

[0007] "Nutrition intake data" is information about the foods and drinks that a user takes in on a daily basis, and includes data such as calories, nutrients, and dietary details.

[0008] "Physical activity data" is information relating to the exercise and activity level of the user in their daily life, and includes the number of steps, exercise time, calories burned, and the like.

[0009] "Sleep pattern data" is information about the user's sleep, including the amount of sleep, the quality of sleep, and the time of waking up and going to bed.

[0010] An "integrated database" is a database that organizes and centrally manages multiple different types of data within a single system.

[0011] An "artificial intelligence engine" is a computer program that analyzes large amounts of data, recognizes patterns, and makes predictions and decisions.

[0012] A "personalized health plan" is a specific set of action plans and advice customized to a particular user's health status and genetic predispositions.

[0013] "Virtual reality (VR)" is a technology that allows users to interactively experience a virtual space generated by computer graphics.

[0014] Augmented reality (AR) is a technology that overlays computer-generated information onto the real world, allowing users to experience it interactively.

[0015] An "interactive health improvement experience" is a system or content that allows users to actively participate in an experience aimed at improving their health. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data, and is implemented as follows.

[0038] Data collection methods

[0039] First, the user collects a sample using a genetic test kit to obtain genetic information. The device (smartphone app) digitally inputs this genetic information and sends it to a server. The device also continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application. This data is periodically sent from the device to a cloud server.

[0040] Data Integration Methods

[0041] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0042] Data Analysis Methods

[0043] An artificial intelligence engine on the server analyzes the data in the integrated database to assess the user's genetic risk and health trends. For example, if a user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[0044] Health plan generator

[0045] Based on the analysis results, the server's AI engine generates a personalized health plan with specific action items and recommendations tailored to the user's needs, such as "do 30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[0046] Means of providing VR / AR experiences

[0047] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their own VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutritional information.

[0048] Feedback and Adjustments

[0049] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[0050] Specific examples

[0051] As a concrete example, let's consider the case where User A uses this system. User A provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and after analysis by an artificial intelligence engine, it is determined that User A is at risk of diabetes. As a result, a health plan including daily aerobic exercise and calorie restriction is created. This plan is provided as VR content, and User A can receive interactive exercise guidance within the VR environment. As User A implements the plan and provides feedback, the server adjusts the plan based on that data, continuously providing optimal health improvements.

[0052] The above is an embodiment of the present invention.

[0053] The processing flow will be explained below.

[0054] Step 1:

[0055] A user collects a sample using a genetic testing kit and digitally inputs genetic information through an application provided with the kit, which then transmits the input genetic information from the device to a server.

[0056] Step 2:

[0057] The device continuously collects daily life data through the user's smartwatch or mobile application, including nutritional intake data, physical activity data, and sleep pattern data, which is then automatically uploaded to a server.

[0058] Step 3:

[0059] The server checks the consistency of the received genetic information and daily life data. If there is missing or inconsistent data, the server notifies the user and requests that the data be resent.

[0060] Step 4:

[0061] The server stores verified genetic information and daily life data in an integrated database, which is linked based on a personal identification code (user ID).

[0062] Step 5:

[0063] An artificial intelligence engine on the server analyzes the integrated data, assessing genetic risks and health trends and providing a specific diagnosis for each user. For example, it may say, "User A is at high risk for type 2 diabetes."

[0064] Step 6:

[0065] The server's AI engine generates a personalized health plan based on the analysis results, which includes specific guidelines for action, such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[0066] Step 7:

[0067] The server then creates VR / AR content based on the generated health plan, which can be interactively experienced by users, such as exercise guides in VR or meal planners using AR.

[0068] Step 8:

[0069] The device provides the created VR / AR content to the user, who then experiences the content using their smartphone or VR device.

[0070] Step 9:

[0071] As users follow their health plan, they input feedback via the device, including the results of their exercise and diet, and changes in their health status.

[0072] Step 10:

[0073] The device sends the collected feedback data to a server, which analyzes this feedback and adjusts the health plan as needed.

[0074] Step 11:

[0075] The server then generates an adjusted health plan and provides it to the user via the device, thereby optimizing the user's health status in real time.

[0076] The above is the specific processing flow of the program.

[0077] Example 1

[0078] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0079] For health management, there is a need for a system that provides more accurate, personalized health plans by integrating and analyzing not only an individual's genetic information but also their daily life data. However, there are challenges in that the integrated analysis of genetic information and daily life data has not been sufficiently carried out, and there is a lack of a mechanism for providing real-time feedback and adjustments on the effectiveness of the health plans provided.

[0080] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0081] In this invention, the server includes means for collecting an individual's genetic information, means for collecting nutritional intake data, physical activity data, and sleep pattern data, means for integrating and analyzing the genetic information and the daily life data, means for generating a personalized health plan based on the analysis results, means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan, means for recording the implementation status and feedback of the health plan and transmitting it to the server, and means for analyzing the feedback data and reevaluating and adjusting the health plan, thereby enabling the provision of a highly accurate personalized health plan and the ability to provide feedback on its effectiveness and adjust it in real time.

[0082] "Genetic information" is data based on an individual's DNA that indicates genetic characteristics and risks.

[0083] "Nutrition intake data" refers to information about the foods and nutrients that an individual consumes in their daily lives.

[0084] "Physical activity data" refers to information relating to the amount and pattern of exercise in an individual's daily life.

[0085] "Sleep pattern data" is information about an individual's sleep duration, sleep quality, and sleep cycle.

[0086] "Synthesis" is the process of combining different types of data into a single, coherent data set.

[0087] "Analysis" is the process of analyzing collected data and extracting meaningful information and patterns.

[0088] A "health plan" is a written plan that includes specific action guidelines and recommendations for improving an individual's health.

[0089] "Virtual reality" refers to a virtual environment or experience created using computer technology.

[0090] "Augmented reality" is a technology that overlays computer-generated images and information on real-world scenes.

[0091] An "interactive health improvement experience" is a health improvement program designed to allow users to actively participate, often using virtual reality or augmented reality.

[0092] "Feedback" refers to the data and opinions obtained after a user implements a health plan, and is information used to reevaluate and adjust the plan.

[0093] "Reevaluation" is the process of reassessing the effectiveness of current health plans based on collected feedback data and making adjustments as necessary.

[0094] "Adjustment" is the process of modifying and improving existing plans and systems based on evaluation results and feedback.

[0095] This invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data. The system is implemented as follows:

[0096] Data collection

[0097] First, the user collects a sample using a genetic test kit to obtain genetic information. The device (smartphone app) digitally inputs this genetic information and sends it to a server. The device also continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application. This data is periodically sent from the device to a cloud server.

[0098] Data Integration

[0099] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0100] Data analysis

[0101] The server's AI engine analyzes the data in the integrated database to assess the user's genetic risk and health trends. For example, if the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[0102] Health plan generation

[0103] Based on the analysis, the server's AI engine generates a personalized health plan with specific action items and recommendations tailored to the user's needs, such as "do 30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[0104] Providing VR / AR experiences

[0105] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutrition information.

[0106] Feedback and Adjustments

[0107] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[0108] Specific examples

[0109] For example, when User A uses this system, the process goes as follows: User A provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and the AI ​​engine analyzes it to determine whether User A is at risk of diabetes. The generated health plan includes instructions for daily aerobic exercise and calorie restriction and is provided as VR content. When User A implements the plan and provides feedback, the server reevaluates and adjusts the plan based on that data, continuously providing User A with optimal health improvements.

[0110] Prompt Sentence Examples

[0111] Below is an example of a prompt sentence to be input to the generative AI model of this system.

[0112] Describe a system that integrates a user's genetic information and daily life data to generate a personalized health plan. Illustrate how a health plan is created and provided to a user at risk for diabetes.

[0113] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0114] Step 1:

[0115] A user collects a sample (e.g., saliva) using a genetic test kit and mails it to a testing institution. The genetic information obtained from the testing institution is provided in digital format and entered into a terminal (smartphone app). The terminal sends this input data (genetic information) to a server. The input is the user ID and genetic information, and the output is the digital genetic information sent to the server.

[0116] Step 2:

[0117] The device continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) using a smartwatch or mobile application. For example, the smartwatch records heart rate and exercise volume, and the mobile application inputs the user's dietary information. This data (input) is periodically sent to a server (output) and stored on the server.

[0118] Step 3:

[0119] The server checks the integrity of all received data. Specifically, it checks the format of the genetic information and checks for abnormal values ​​in the daily life data. The input is the genetic information and daily life data sent from the device, and the output is the verified integrated data. This data is stored in the server's integrated database.

[0120] Step 4:

[0121] The AI ​​engine on the server analyzes the data in the integrated database. The input data is genetic information and daily life data, and the output is the results of the user's genetic risk assessment and health trend analysis. For example, it determines whether or not a person is at high risk for diabetes. These analyses are performed using machine learning algorithms.

[0122] Step 5:

[0123] Based on the analysis results, the server's AI engine generates a personalized health plan. The input is the analysis results by the AI ​​engine, and the output is a health plan including specific action items (e.g., "30 minutes of aerobic exercise every day" and "eat at least three vegetables per week"). This plan is customized based on the user's lifestyle and genetic risk.

[0124] Step 6:

[0125] The server generates VR / AR content based on the generated health plan and provides it to the user through the device. The input is the generated health plan, and the output is interactive content that can be displayed on a VR device or smartphone. For example, it includes an AR trainer for exercise guidance and a meal planner for nutritional information.

[0126] Step 7:

[0127] The device records the user's progress and feedback. For example, the user enters the results of implementing a health plan and their thoughts about it into the app. The input is the user's feedback data, and the output is a progress record including the feedback. This data is sent from the device to the server.

[0128] Step 8:

[0129] The server analyzes the collected feedback data and evaluates whether the health plan is appropriate. If necessary, it reevaluates the health plan and generates a new, adjusted plan. The input is the feedback data and the current health plan, and the output is the adjusted health plan. The updated plan is again provided to the user via the terminal.

[0130] (Application example 1)

[0131] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0132] In today's world, personal health management is becoming an increasingly important issue, and there is a demand for providing personalized health plans that utilize genetic information and daily life data. However, conventional systems struggle to efficiently integrate and analyze genetic information and daily life data, and lack the means to interactively provide personalized health improvement content in real time. Furthermore, the generation of prompts that provide information tailored to each user's needs when generating individual health plans is not automated, making it difficult to provide personalized services.

[0133] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0134] In this invention, the server includes: means for collecting an individual's genetic information; means for collecting nutritional intake data, physical activity data, and sleep pattern data; means for integrating and analyzing the genetic information and daily life data; means for generating a personalized health plan based on the analysis results; means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan; and means for generating individual prompts using a generative AI model when generating the health plan. This enables efficient integration and analysis of genetic information and daily life data, and personalized health improvement content to be provided interactively in real time. Furthermore, automatic generation of individual prompts tailored to the needs of each user enables the provision of even more advanced personalized services.

[0135] "Personal genetic information" is data that indicates the genetic characteristics and risks of individual users.

[0136] "Nutrition intake data" is information about the foods and nutrients that a user takes in on a daily basis.

[0137] "Physical activity data" is information relating to the amount of exercise and activity level of the user in their daily life.

[0138] "Sleep pattern data" is information relating to the user's sleep duration, quality, and patterns.

[0139] "Analysis means" refers to technologies such as artificial intelligence engines that integrate collected genetic information with daily life data to assess the user's health status and risks.

[0140] A "health plan" is a plan that includes specific advice and recommendations for individualized health improvement based on the results of the analysis.

[0141] "Virtual reality" is a technology that allows users to have interactive experiences in a virtual space.

[0142] "Augmented reality" is a technology that overlays digital information and objects onto the real world.

[0143] An "interactive health improvement experience" is an experience in which users actively participate and interact with the experience through virtual reality or augmented reality to improve their health.

[0144] A "generative AI model" is a model that uses artificial intelligence to analyze data and generate appropriate output.

[0145] A "prompt" is a sentence output by a generative AI model that contains instructions or questions designed to elicit a specific action or response.

[0146] This invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data, with the aim of helping users effectively improve their health.

[0147] Data collection methods

[0148] First, the user collects a genetic sample using a genetic test kit and digitally inputs the information into a device (smartphone app). The device then transmits the genetic information to a server. Furthermore, the device also continuously collects daily life data (nutritional intake, physical activity, and sleep patterns) via a smartwatch or mobile app, and periodically transmits this data to a cloud-based server.

[0149] Data Integration Methods

[0150] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0151] Data Analysis Methods

[0152] An artificial intelligence engine (e.g., TensorFlow) on the server analyzes the data in the integrated database. The analysis is performed to evaluate the user's genetic risk and health trends. For example, if the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[0153] Health plan generator

[0154] Based on the analysis results, the server's AI engine generates a personalized health plan, which includes specific action items and recommendations tailored to the user's needs, such as "30 minutes of aerobic exercise every day" and "eat at least three vegetables per week."

[0155] Means of providing VR / AR experiences

[0156] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their own VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutritional information.

[0157] Feedback and Adjustments

[0158] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[0159] Prompt generation method

[0160] When generating a health plan, the server uses a generative AI model to generate personalized prompts that provide information and instructions tailored to the user's needs and circumstances. For example, prompts such as "Did you achieve your exercise goal today?" or "Are you satisfied with your meal plan this week?"

[0161] Specific examples

[0162] When User A uses this system, he or she provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and after analysis by an artificial intelligence engine, it determines that User A is at risk of diabetes. As a result, a health plan including daily aerobic exercise and calorie restriction is created. This plan is provided as VR content, and User A can receive interactive exercise guidance within the VR environment. As User A implements the plan and provides feedback, the server adjusts the plan based on that data, continuously providing optimal health improvements.

[0163] Prompt Sentence Examples

[0164] "Did you achieve your exercise goal today?"

[0165] "Are you happy with your meal plan this week?"

[0166] "How was your sleep quality?"

[0167] In this way, users can enjoy a continuous, personalized health improvement experience.

[0168] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0169] Step 1:

[0170] Users use a genetic testing kit to collect genetic samples and enter the genetic information into a device (smartphone app).

[0171] Input: Gene sample, user ID

[0172] Output: Genetic information in digital form

[0173] Specific behavior:

[0174] The user collects a sample using a genetic testing kit.

[0175] The genetic information is read within the app and transferred to the screen.

[0176] Step 2:

[0177] The device transmits the genetic information in digital form to a server.

[0178] Input: Digital genetic information, user ID

[0179] Output: Genetic information is stored on the server.

[0180] Specific behavior:

[0181] The app combines the genetic information with the user ID and sends it to the server.

[0182] Step 3:

[0183] The device continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application and periodically transmits it to a server.

[0184] Input: User's daily life data (nutrition, physical activity, sleep), user ID

[0185] Output: Daily life data is saved on the server.

[0186] Specific behavior:

[0187] Smartwatches and apps automatically record daily life data.

[0188] The terminal sends the collected data to the server.

[0189] Step 4:

[0190] The server checks the consistency of the received genetic information and daily life data and integrates them.

[0191] Input: Genetic information, daily life data, user ID

[0192] Output: Integrated data stored in an integrated database

[0193] Specific behavior:

[0194] The server associates genetic information with daily life data in a database.

[0195] Check the integrity of the data format and save it in the integrated database.

[0196] Step 5:

[0197] An artificial intelligence engine within the server analyzes the integrated data to assess the user's genetic risks and health trends.

[0198] Input: Integrated data in the integrated database

[0199] Output: Analysis results (health risks, health trends)

[0200] Specific behavior:

[0201] The AI ​​engine processes and analyzes the integrated data.

[0202] Evaluate health risks and trends and generate analytical results.

[0203] Step 6:

[0204] Based on the analysis results, the server's AI engine generates a personalized health plan.

[0205] Input: Analysis results, user ID

[0206] Output: A health plan with specific action items and recommendations

[0207] Specific behavior:

[0208] The AI ​​engine will create the optimal health plan based on the analysis results.

[0209] Step 7:

[0210] The server uses a generative AI model to generate personalized prompts related to the health plan.

[0211] Input: Health plan, user ID

[0212] Output: prompt statement

[0213] Specific behavior:

[0214] Parse the health plan and generate the appropriate prompt.

[0215] For example: "Did you achieve your exercise goal today?", "Are you happy with your meal plan this week?"

[0216] Step 8:

[0217] The server generates VR / AR content based on the health plan and provides it to the user through the device.

[0218] Input: Health plan, prompt, user ID

[0219] Output: VR / AR content

[0220] Specific behavior:

[0221] Create VR / AR content and distribute it to devices.

[0222] Examples: interactive exercise guides, meal planners, etc.

[0223] Step 9:

[0224] The device records the user's progress and reactions and sends them to the server.

[0225] Input: User progress data, feedback

[0226] Output: Progress data, feedback sent to the server.

[0227] Specific behavior:

[0228] Log user actions and feedback.

[0229] Sends progress data to the server.

[0230] Step 10:

[0231] The server analyzes the progress data and feedback and adjusts the health plan accordingly.

[0232] Inputs: progress data, feedback, existing health plan

[0233] Output: Coordinated Health Plan

[0234] Specific behavior:

[0235] Analyze progress data and generate a plan with appropriate modifications.

[0236] The updated plan will be delivered to your device.

[0237] Through these steps, users can enjoy a continuously personalized health improvement experience.

[0238] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0239] The present invention is an AI-driven health coaching system that integrates and analyzes personal genetic information, daily life data, and user emotional data, and is implemented as follows.

[0240] Data collection methods

[0241] First, the user collects a sample using a genetic testing kit and digitally inputs their genetic information through the app that comes with the kit. The input genetic information is then sent from the device to a server. The device also continuously collects daily life data (nutritional intake, physical activity, and sleep patterns) via a smartwatch or mobile app. This data is automatically uploaded to the server.

[0242] Furthermore, the device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data, including the user's motivation and stress level, which is then sent to the server.

[0243] Data Integration Methods

[0244] The server checks the consistency of the received genetic information, daily life data, and emotional data, and then integrates these data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0245] Data Analysis Methods

[0246] An artificial intelligence engine on the server analyzes the integrated data to assess the user's genetic risk, health trends, and emotional state. For example, if a user is at risk for diabetes, a specific health plan is generated based on the risk assessment results. The system also takes into account the user's stress level and motivation based on emotional data.

[0247] Health plan generator

[0248] Based on the analysis results, the server's AI engine generates a personalized health plan. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, in addition to advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it may also include advice such as "add relaxation exercises on days when you are under high stress."

[0249] Means of providing VR / AR experiences

[0250] The server creates VR / AR content based on the generated health plan and provides it to the user via the device. The user experiences the provided content using their smartphone or VR device. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction based on emotional data.

[0251] Feedback and Adjustments

[0252] The device records the user's progress and reactions and sends them to the server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health and emotional status in real time and increases engagement.

[0253] Specific examples

[0254] As a concrete example, let's consider the case where User B uses this system. User B provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. In addition, emotional data is obtained from User B's voice and facial expressions. The server integrates this data, and an artificial intelligence engine analyzes it, revealing that User B has a high stress level and is at risk of diabetes. The generated health plan includes daily exercise and a balanced diet, as well as relaxation exercises to reduce stress. This plan is provided as VR content, and User B experiences interactive relaxation training within the VR environment. User B provides feedback during and after the plan, and the server uses that data to adjust the health plan and continuously provide optimal improvement guidelines.

[0255] The above is an embodiment of the present invention.

[0256] The processing flow will be explained below.

[0257] Step 1:

[0258] A user collects a sample using a genetic testing kit and digitally inputs genetic information through an application provided with the kit, which then transmits the input genetic information from the device to a server.

[0259] Step 2:

[0260] The device continuously collects daily life data through the user's smartwatch or mobile application, including nutritional intake data, physical activity data, and sleep pattern data, which is then automatically uploaded to a server.

[0261] Step 3:

[0262] The device analyzes the user's voice, facial expressions, and behavioral patterns to acquire emotional data, including the user's motivation and stress level, and transmits the acquired emotional data to a server.

[0263] Step 4:

[0264] The server checks the consistency of genetic information, daily life data, and emotional data, checking for inconsistencies or missing data, and notifying the user if necessary.

[0265] Step 5:

[0266] The server stores the verified data in a consolidated database, where the data is linked based on a personal identification code (user ID).

[0267] Step 6:

[0268] The server's artificial intelligence engine analyzes the integrated data. Specifically, it evaluates genetic risk, health trends, and emotional state, and makes a specific diagnosis for each user. For example, it might say, "User B is in a high stress state and has a high genetic risk of diabetes."

[0269] Step 7:

[0270] The server's AI engine generates a personalized health plan based on the analysis results. The health plan includes specific guidelines for action and takes emotional data into consideration. For example, in addition to basic advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it also includes specific suggestions such as "add relaxation exercises on days when you're under high stress."

[0271] Step 8:

[0272] The server then creates VR / AR content based on the generated health plan, which users can experience interactively, such as an exercise guide in VR or a meal planner using AR.

[0273] Step 9:

[0274] The device provides the created VR / AR content to the user, who then experiences the content using their smartphone or VR device.

[0275] Step 10:

[0276] The device provides feedback on the results of activities and emotional responses as the user follows a health plan, including the type and duration of exercise, dietary content, and changes in emotional state.

[0277] Step 11:

[0278] The device sends the collected feedback data to a server, which analyzes the feedback and evaluates whether the health plan is appropriate.

[0279] Step 12:

[0280] The server adjusts the health plan as needed and generates an updated version, which is then provided to the user via the device again, optimizing the user's health and emotional state in real time.

[0281] The above is the specific processing flow of the program of the present invention combined with the emotion engine.

[0282] Example 2

[0283] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0284] Although there are systems that comprehensively integrate an individual's genetic information, daily life data, and emotional data to provide personalized health plans, many of them lack the ability to integrate and analyze data in a comprehensive manner, making it difficult to provide real-time feedback and adjustments. Another issue is that it is difficult to provide health plans that take into account the user's emotional state.

[0285] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0286] In this invention, the server includes: means for collecting personal genetic information, means for collecting nutritional intake data, physical activity data, and sleep pattern data, means for analyzing the user's voice, facial expressions, and behavioral patterns to obtain emotional data, means for transmitting the genetic information, daily life data, and emotional data to the server and integrating these data, means for analyzing the integrated data using an artificial intelligence engine to evaluate genetic risks, health trends, and emotional states, means for generating a personalized health plan based on the analysis results, means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan, and means for collecting the user's progress and reactions as feedback and adjusting the health plan, thereby enabling the provision of a comprehensive health plan based on the user's genetic risks, daily life data, and emotional states.

[0287] "Individual genetic information" refers to data that indicates an individual's biological characteristics obtained through genetic testing.

[0288] "Nutrient intake data" refers to information about the foods and their nutritional components that a user consumes in their daily lives.

[0289] "Physical activity data" is information about the exercise and daily physical activity of the user.

[0290] "Sleep pattern data" is data that indicates information related to the user's sleep state, sleep duration, and sleep quality.

[0291] "Emotional data" refers to information such as the user's psychological state, motivation, stress level, etc., analyzed from the user's voice, facial expressions, and behavior.

[0292] "Means of integration" refers to methods or technologies for centrally collecting, linking, and organizing various types of data.

[0293] An "artificial intelligence engine" is software or a system that analyzes large amounts of data and replicates human knowledge and pattern recognition.

[0294] "Genetic risk" is a risk assessment that indicates the likelihood of developing a particular disease or health problem based on genetic information.

[0295] "Health trends" is information that indicates trends regarding an individual's health condition and lifestyle habits based on daily life data.

[0296] "Personalized health plan" refers to a course of action or plan proposed for optimal health maintenance or improvement based on a user's individual genetic information, daily life data, and emotional data.

[0297] "Virtual reality" is a technology that uses computer technology to create a virtual 3D environment in which users can interact.

[0298] "Augmented reality" is a technology that overlays digital information and 3D objects onto a real environment, providing users with an experience that blends reality and virtuality.

[0299] "Means for collecting feedback" refers to methods or techniques for collecting progress and reactions from users and using them to evaluate and improve the system.

[0300] A "means for adjusting a health plan" is a method or technology for analyzing collected feedback data and revising the health plan to best suit the user.

[0301] This invention is a system that provides a health plan by integrating and analyzing an individual's genetic information, daily life data, and emotional data, and specific embodiments thereof will be described below.

[0302] Collection of genetic information

[0303] A user collects their own sample using a genetic testing kit. This sample is then digitally entered through an application that comes with the kit. The entered genetic information is then sent from the device to a server. This process involves the use of a genetic analysis kit and application.

[0304] Collection of daily life data

[0305] The device (e.g., smartwatch or mobile app) collects data on the user's daily life, including nutritional intake data, physical activity data, and sleep pattern data, and automatically uploads this data to a server. Specifically, the smartwatch measures exercise volume and sleep patterns, and the food recording app records nutritional intake data.

[0306] Collecting Emotional Data

[0307] The device (e.g., a smartphone or special sensor) analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. This data, including the user's motivation and stress level, is sent to a server. Speech recognition software and facial expression recognition algorithms are used.

[0308] Data integration and transmission

[0309] The device automatically sends all data to the server, which receives and centrally integrates this data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0310] Data analysis

[0311] An artificial intelligence engine on the server analyzes the integrated data. The analysis is carried out to assess the user's genetic risk, health trends, and emotional state. For example, genetic data and lifestyle data are used to analyze diabetes risk. The AI ​​engine analyzes this data and assesses health risks.

[0312] Health plan generation

[0313] The server's AI engine then generates a personalized health plan based on the analysis results. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, instructions include "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," and also includes instructions such as "add relaxation exercises on days when you're under high stress."

[0314] Providing VR / AR content

[0315] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user experiences this content using a smartphone or VR device. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction based on emotional data.

[0316] Gather feedback and adjust your plan

[0317] The device records the user's progress and reactions and sends them to the server. Feedback includes the results of exercise and diet, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates and adjusts the health plan to determine whether it is appropriate. If necessary, the health plan is revised appropriately and the updated plan is provided to the user via the device.

[0318] Prompt Sentence Examples

[0319] Here are some examples of prompts to input to a generative AI model:

[0320] Prompt: Analyze the health risks of users based on their genetic information, daily life data, and emotional data, and generate a personalized health plan. For example, what advice would you give to a user who is at risk of diabetes?

[0321] By feeding this prompt into a generative AI model, we can understand how the system processes the data and provides specific health advice.

[0322] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0323] Step 1: Collecting genetic information

[0324] A user collects a sample using a genetic testing kit, enters genetic information digitally through the kit's application, and transmits it to a server via a terminal.

[0325] Specific behavior:

[0326] The user uses a cotton swab to collect cells from inside the mouth.

[0327] Launch the application and scan or enter your genetic information.

[0328] The device will use Wi-Fi or mobile data to send genetic information to a server.

[0329] Input: Gene sample

[0330] Output: Genetic information in digital form

[0331] Step 2: Collecting daily life data

[0332] The device (smartwatch or mobile app) collects data about the user's daily life and automatically uploads it to a server.

[0333] Specific behavior:

[0334] The smartwatch measures the user's steps and exercise volume.

[0335] The food recording app inputs the user's meal details.

[0336] A sleep tracker analyzes your sleep patterns.

[0337] The device periodically uploads this data to the server.

[0338] Input: User's daily living activities

[0339] Output: Digital daily life data

[0340] Step 3: Collecting emotion data

[0341] The device analyzes the user's voice, facial expressions, and behavioral patterns, acquires emotional data, and sends it to the server.

[0342] Specific behavior:

[0343] The smartphone camera captures and analyzes the user's facial expressions.

[0344] It uses speech recognition technology to analyze the content and tone of what a user is saying.

[0345] The terminal transmits this emotion data to the server.

[0346] Input: User's voice, facial expressions, and actions

[0347] Output: Digital emotional data

[0348] Step 4: Integrate and send data

[0349] The genetic information, daily life data, and emotional data collected by the device are sent to a server, which then stores them in a centralized integrated database.

[0350] Specific behavior:

[0351] The device sends each piece of data to the server using Wi-Fi or mobile data.

[0352] The server receives all the data, organizes it and consolidates it based on the personal identification code (user ID).

[0353] Input: Genetic information, daily life data, emotional data

[0354] Output: Integrated database

[0355] Step 5: Data analysis

[0356] An artificial intelligence engine within the server analyzes the integrated data and assesses the user's genetic risks, health trends and emotional state.

[0357] Specific behavior:

[0358] The AI ​​engine extracts risk factors from genetic data.

[0359] Analyze health trends based on daily life data.

[0360] Evaluate stress levels and motivation from emotional data.

[0361] Input: Integrated database

[0362] Output: Analysis results (genetic risk, health trends, emotional state)

[0363] Step 6: Generate a health plan

[0364] The server's AI engine generates a personalized health plan based on the analysis results.

[0365] Specific behavior:

[0366] The AI ​​engine generates specific guidelines for action, such as "30 minutes of aerobic exercise every day."

[0367] It suggests relaxation exercises based on the user's stress level.

[0368] Input: Analysis results

[0369] Output: personalized health plan

[0370] Step 7: Providing VR / AR content

[0371] The server creates VR / AR content based on the generated health plan and provides it to the user via their device, where the user can experience it.

[0372] Specific behavior:

[0373] Create VR / AR content using dedicated software.

[0374] The device delivers VR / AR content to the user.

[0375] Users experience the content using a smartphone or VR device.

[0376] Enter: personalized health plans.

[0377] Output: VR / AR content experience

[0378] Step 8: Gather feedback and refine your plan

[0379] The device records the user's progress and reactions and sends them to a server, which analyzes the feedback data and adjusts and updates the health plan.

[0380] Specific behavior:

[0381] The device records the user's exercise log, meal log, and emotional changes.

[0382] The server analyzes the feedback data and adjusts the health plan.

[0383] Input: User progress and feedback

[0384] Output: Coordinated Health Plan

[0385] (Application example 2)

[0386] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0387] Conventional health management systems generate health plans based solely on genetic information and daily life data, failing to fully consider the user's emotional state and motivation, making it difficult to effectively improve their health. Furthermore, they lacked personalized product recommendations and interactive experiences, resulting in low user engagement. This led to a decline in users' motivation to continue managing their health, making it difficult to effectively improve their health.

[0388] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0389] In this invention, the server includes: means for collecting personal genetic information; means for collecting nutritional intake data, physical activity data, and sleep pattern data; means for collecting emotional data from voice, facial expressions, and behavioral patterns; means for integrating and analyzing the genetic information, the daily life data, and the emotional data; means for generating a personalized health plan based on the analysis results; means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan; and means for recommending products in a virtual store based on the health plan. This makes it possible to provide a personalized health plan that takes into account the user's genetic risks and health trends, as well as their emotional state and motivation, and further makes it possible to more effectively support the user's health improvement by recommending appropriate products in the virtual store.

[0390] "Genetic information" is data that indicates the genetic characteristics of a user, and is information obtained through DNA analysis.

[0391] "Daily life data" refers to data relating to the user's daily activities and lifestyle habits, including information on nutritional intake, physical activity, sleep patterns, and the like.

[0392] "Emotion data" is data obtained from the user's voice, facial expressions, and behavioral patterns, and is information that indicates the user's emotional state, such as stress level and motivation.

[0393] "Integration" means bringing together multiple different data into a single database and managing them in a correlated manner.

[0394] "Analysis" is an information processing activity that uses collected data to clarify its content and meaning.

[0395] A "health plan" is a plan that includes specific, personalized actions and advice to improve a user's health.

[0396] "Virtual reality" is a technology that uses computer technology to provide users with virtual environments and experiences that do not exist in reality.

[0397] "Augmented reality" is a technology that displays digital information overlaid on visual information from the real world, enhancing the user's experience.

[0398] An "interactive health improvement experience" refers to activities and training for improving health that are provided in a way that allows users to actively participate, and that enhances effectiveness through two-way interaction.

[0399] A "virtual store" is a virtual store accessible via the Internet, an online platform where users can browse, select and purchase products in a digital environment.

[0400] "Product recommendation" refers to selecting and suggesting specific products that match the user's needs and preferences.

[0401] This invention is a system that integrates and analyzes an individual's genetic information, daily life data, and emotional data to provide a personalized health plan to the user. A specific implementation method is described below.

[0402] Data collection methods

[0403] First, the user collects a sample using a genetic test kit and digitally enters their genetic information through a dedicated application. This genetic information is then sent to a server from a device such as a smartphone. Furthermore, the user's daily life data (nutritional intake, physical activity, and sleep pattern data) is continuously collected via a smartwatch or mobile application, and this data is also automatically uploaded to the server. Additionally, the device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. This emotional data includes the user's motivation and stress level and is then sent to the server.

[0404] Data Integration Methods

[0405] The server checks the consistency of the received genetic information, daily life data, and emotional data, and integrates them. All data is linked based on a personal identification code (user ID) and stored in an integrated database. The hardware used is compatible with AWS (Amazon Web Services) databases.

[0406] Data Analysis Methods

[0407] An artificial intelligence engine on the server analyzes the integrated data to assess the user's genetic risk, health trends, and emotional state. For example, this is done using Python and TensorFlow. If the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results. The system also takes into account the user's stress level and motivation based on emotional data.

[0408] Health plan generator

[0409] Based on the analysis results, the server's AI engine generates a personalized health plan. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, in addition to advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it may also include advice such as "add relaxation exercises on days when you are under high stress."

[0410] Means of providing VR / AR experiences

[0411] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user can experience the provided content using their smartphone or VR device. For example, they can use an Oculus Quest to experience an AR trainer that guides exercise, or a relaxation program that reduces stress based on emotional data.

[0412] Feedback and Adjustments

[0413] The device records the user's progress and reactions and sends them to the server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health and emotional status in real time and increases engagement.

[0414] Examples and prompts

[0415] As a concrete example, let's consider the case where User B uses this system. User B provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. In addition, emotional data is obtained from User B's voice and facial expressions. The server integrates this data, and an artificial intelligence engine analyzes it, revealing that User B has a high stress level and is at risk of diabetes. The generated health plan includes daily exercise and a balanced diet, as well as relaxation exercises to reduce stress. This plan is provided as VR content, and User B experiences interactive relaxation training within the VR environment. User B provides feedback during and after the plan, and the server uses that data to adjust the health plan and continuously provide optimal improvement guidelines.

[0416] Example prompt sentence:

[0417] "Generate a personalized health plan and related product recommendations based on the user's genetic information, daily life data (activity, nutrition, sleep patterns), and emotional data (facial expressions, voice). The health plan should include specific exercise instructions, dietary suggestions, and advice on stress reduction. Related products should suggest fitness equipment, supplements, and relaxation tools available for purchase in a virtual store."

[0418] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0419] Step 1:

[0420] Users use a genetic test kit to collect a genetic sample and input the results into the application, which then sends the data from a device such as a smartphone to a server.

[0421] Input: Genetic sample results

[0422] Output: Sending genetic information to the server

[0423] Step 2:

[0424] The device (smartwatch or mobile application) continuously collects data on the user's daily life (nutritional intake data, physical activity data, sleep pattern data) and automatically uploads this data to a server.

[0425] Input: Daily life data (exercise, nutrition, sleep data)

[0426] Output: Sending daily life data to the server

[0427] Step 3:

[0428] The device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. It uses voice recognition and facial expression analysis algorithms to determine the user's emotional state. This data is then sent to the server.

[0429] Input: Voice data, facial expression data, behavior patterns

[0430] Output: Sending emotion data to the server

[0431] Step 4:

[0432] The server integrates the received genetic information, daily life data, and emotion data. Using Python and AWS databases, the data is integrated and stored in a database. This process verifies the integrity of the data and generates a single linked dataset.

[0433] Input: Genetic information, daily life data, emotional data

[0434] Output: A consolidated dataset

[0435] Step 5:

[0436] The AI ​​engine on the server analyzes the integrated data set to assess the user's genetic risk, health trends, and emotional state. It uses AI tools such as TensorFlow to perform the analysis and then predicts health risks and evaluates emotional state based on the results.

[0437] Input: Integrated dataset

[0438] Output: Analysis results (health risk assessment, emotional state assessment)

[0439] Step 6:

[0440] The server's AI engine generates a personalized health plan based on the analysis results. This health plan includes specific guidelines for action and takes into account the user's emotional state. For example, instructions include "30 minutes of aerobic exercise every day," "eat at least three servings of vegetables per week," and "add relaxation exercises on days when you're under high stress."

[0441] Input: Analysis results

[0442] Output: personalized health plan

[0443] Step 7:

[0444] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user experiences the content using a VR device such as Oculus Quest. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction.

[0445] Enter: personalized health plans.

[0446] Output: VR / AR content

[0447] Step 8:

[0448] The device records the user's progress and reactions and sends them to a server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data, evaluates whether the health plan is appropriate, and adjusts the health plan accordingly, if necessary.

[0449] Input: User feedback data

[0450] Output: Coordinated Health Plan

[0451] The above are the processing steps of the system that realizes the application example.

[0452] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0453] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0454] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0455] [Second embodiment]

[0456] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0457] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0458] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0459] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0460] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0461] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0462] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0463] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0464] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0465] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0466] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0467] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0468] The present invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data, and is implemented as follows.

[0469] Data collection methods

[0470] First, the user collects a sample using a genetic test kit to obtain genetic information. The device (smartphone app) digitally inputs this genetic information and sends it to a server. The device also continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application. This data is periodically sent from the device to a cloud server.

[0471] Data Integration Methods

[0472] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0473] Data Analysis Methods

[0474] An artificial intelligence engine on the server analyzes the data in the integrated database to assess the user's genetic risk and health trends. For example, if a user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[0475] Health plan generator

[0476] Based on the analysis results, the server's AI engine generates a personalized health plan with specific action items and recommendations tailored to the user's needs, such as "do 30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[0477] Means of providing VR / AR experiences

[0478] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their own VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutritional information.

[0479] Feedback and Adjustments

[0480] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[0481] Specific examples

[0482] As a concrete example, let's consider the case where User A uses this system. User A provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and after analysis by an artificial intelligence engine, it is determined that User A is at risk of diabetes. As a result, a health plan including daily aerobic exercise and calorie restriction is created. This plan is provided as VR content, and User A can receive interactive exercise guidance within the VR environment. As User A implements the plan and provides feedback, the server adjusts the plan based on that data, continuously providing optimal health improvements.

[0483] The above is an embodiment of the present invention.

[0484] The processing flow will be explained below.

[0485] Step 1:

[0486] A user collects a sample using a genetic testing kit and digitally inputs genetic information through an application provided with the kit, which then transmits the input genetic information from the device to a server.

[0487] Step 2:

[0488] The device continuously collects daily life data through the user's smartwatch or mobile application, including nutritional intake data, physical activity data, and sleep pattern data, which is then automatically uploaded to a server.

[0489] Step 3:

[0490] The server checks the consistency of the received genetic information and daily life data. If there is missing or inconsistent data, the server notifies the user and requests that the data be resent.

[0491] Step 4:

[0492] The server stores verified genetic information and daily life data in an integrated database, which is linked based on a personal identification code (user ID).

[0493] Step 5:

[0494] An artificial intelligence engine on the server analyzes the integrated data, assessing genetic risks and health trends and providing a specific diagnosis for each user. For example, it may say, "User A is at high risk for type 2 diabetes."

[0495] Step 6:

[0496] The server's AI engine generates a personalized health plan based on the analysis results, which includes specific guidelines for action, such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[0497] Step 7:

[0498] The server then creates VR / AR content based on the generated health plan, which can be interactively experienced by users, such as exercise guides in VR or meal planners using AR.

[0499] Step 8:

[0500] The device provides the created VR / AR content to the user, who then experiences the content using their smartphone or VR device.

[0501] Step 9:

[0502] As users follow their health plan, they input feedback via the device, including the results of their exercise and diet, and changes in their health status.

[0503] Step 10:

[0504] The device sends the collected feedback data to a server, which analyzes this feedback and adjusts the health plan as needed.

[0505] Step 11:

[0506] The server then generates an adjusted health plan and provides it to the user via the device, thereby optimizing the user's health status in real time.

[0507] The above is the specific processing flow of the program.

[0508] Example 1

[0509] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0510] For health management, there is a need for a system that provides more accurate, personalized health plans by integrating and analyzing not only an individual's genetic information but also their daily life data. However, there are challenges in that the integrated analysis of genetic information and daily life data has not been sufficiently carried out, and there is a lack of a mechanism for providing real-time feedback and adjustments on the effectiveness of the health plans provided.

[0511] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0512] In this invention, the server includes means for collecting an individual's genetic information, means for collecting nutritional intake data, physical activity data, and sleep pattern data, means for integrating and analyzing the genetic information and the daily life data, means for generating a personalized health plan based on the analysis results, means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan, means for recording the implementation status and feedback of the health plan and transmitting it to the server, and means for analyzing the feedback data and reevaluating and adjusting the health plan, thereby enabling the provision of a highly accurate personalized health plan and the ability to provide feedback on its effectiveness and adjust it in real time.

[0513] "Genetic information" is data based on an individual's DNA that indicates genetic characteristics and risks.

[0514] "Nutrition intake data" refers to information about the foods and nutrients that an individual consumes in their daily lives.

[0515] "Physical activity data" refers to information relating to the amount and pattern of exercise in an individual's daily life.

[0516] "Sleep pattern data" is information about an individual's sleep duration, sleep quality, and sleep cycle.

[0517] "Synthesis" is the process of combining different types of data into a single, coherent data set.

[0518] "Analysis" is the process of analyzing collected data and extracting meaningful information and patterns.

[0519] A "health plan" is a written plan that includes specific action guidelines and recommendations for improving an individual's health.

[0520] "Virtual reality" refers to a virtual environment or experience created using computer technology.

[0521] "Augmented reality" is a technology that overlays computer-generated images and information on real-world scenes.

[0522] An "interactive health improvement experience" is a health improvement program designed to allow users to actively participate, often using virtual reality or augmented reality.

[0523] "Feedback" refers to the data and opinions obtained after a user implements a health plan, and is information used to reevaluate and adjust the plan.

[0524] "Reevaluation" is the process of reassessing the effectiveness of current health plans based on collected feedback data and making adjustments as necessary.

[0525] "Adjustment" is the process of modifying and improving existing plans and systems based on evaluation results and feedback.

[0526] This invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data. The system is implemented as follows:

[0527] Data collection

[0528] First, the user collects a sample using a genetic test kit to obtain genetic information. The device (smartphone app) digitally inputs this genetic information and sends it to a server. The device also continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application. This data is periodically sent from the device to a cloud server.

[0529] Data Integration

[0530] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0531] Data analysis

[0532] The server's AI engine analyzes the data in the integrated database to assess the user's genetic risk and health trends. For example, if the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[0533] Health plan generation

[0534] Based on the analysis, the server's AI engine generates a personalized health plan with specific action items and recommendations tailored to the user's needs, such as "do 30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[0535] Providing VR / AR experiences

[0536] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutrition information.

[0537] Feedback and Adjustments

[0538] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[0539] Specific examples

[0540] For example, when User A uses this system, the process goes as follows: User A provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and the AI ​​engine analyzes it to determine whether User A is at risk of diabetes. The generated health plan includes instructions for daily aerobic exercise and calorie restriction and is provided as VR content. When User A implements the plan and provides feedback, the server reevaluates and adjusts the plan based on that data, continuously providing User A with optimal health improvements.

[0541] Prompt Sentence Examples

[0542] Below is an example of a prompt sentence to be input to the generative AI model of this system.

[0543] Describe a system that integrates a user's genetic information and daily life data to generate a personalized health plan. Illustrate how a health plan is created and provided to a user at risk for diabetes.

[0544] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0545] Step 1:

[0546] A user collects a sample (e.g., saliva) using a genetic test kit and mails it to a testing institution. The genetic information obtained from the testing institution is provided in digital format and entered into a terminal (smartphone app). The terminal sends this input data (genetic information) to a server. The input is the user ID and genetic information, and the output is the digital genetic information sent to the server.

[0547] Step 2:

[0548] The device continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) using a smartwatch or mobile application. For example, the smartwatch records heart rate and exercise volume, and the mobile application inputs the user's dietary information. This data (input) is periodically sent to a server (output) and stored on the server.

[0549] Step 3:

[0550] The server checks the integrity of all received data. Specifically, it checks the format of the genetic information and checks for abnormal values ​​in the daily life data. The input is the genetic information and daily life data sent from the device, and the output is the verified integrated data. This data is stored in the server's integrated database.

[0551] Step 4:

[0552] The AI ​​engine on the server analyzes the data in the integrated database. The input data is genetic information and daily life data, and the output is the results of the user's genetic risk assessment and health trend analysis. For example, it determines whether or not a person is at high risk for diabetes. These analyses are performed using machine learning algorithms.

[0553] Step 5:

[0554] Based on the analysis results, the server's AI engine generates a personalized health plan. The input is the analysis results by the AI ​​engine, and the output is a health plan including specific action items (e.g., "30 minutes of aerobic exercise every day" and "eat at least three vegetables per week"). This plan is customized based on the user's lifestyle and genetic risk.

[0555] Step 6:

[0556] The server generates VR / AR content based on the generated health plan and provides it to the user through the device. The input is the generated health plan, and the output is interactive content that can be displayed on a VR device or smartphone. For example, it includes an AR trainer for exercise guidance and a meal planner for nutritional information.

[0557] Step 7:

[0558] The device records the user's progress and feedback. For example, the user enters the results of implementing a health plan and their thoughts about it into the app. The input is the user's feedback data, and the output is a progress record including the feedback. This data is sent from the device to the server.

[0559] Step 8:

[0560] The server analyzes the collected feedback data and evaluates whether the health plan is appropriate. If necessary, it reevaluates the health plan and generates a new, adjusted plan. The input is the feedback data and the current health plan, and the output is the adjusted health plan. The updated plan is again provided to the user via the terminal.

[0561] (Application example 1)

[0562] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0563] In today's world, personal health management is becoming an increasingly important issue, and there is a demand for providing personalized health plans that utilize genetic information and daily life data. However, conventional systems struggle to efficiently integrate and analyze genetic information and daily life data, and lack the means to interactively provide personalized health improvement content in real time. Furthermore, the generation of prompts that provide information tailored to each user's needs when generating individual health plans is not automated, making it difficult to provide personalized services.

[0564] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0565] In this invention, the server includes: means for collecting an individual's genetic information; means for collecting nutritional intake data, physical activity data, and sleep pattern data; means for integrating and analyzing the genetic information and daily life data; means for generating a personalized health plan based on the analysis results; means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan; and means for generating individual prompts using a generative AI model when generating the health plan. This enables efficient integration and analysis of genetic information and daily life data, and personalized health improvement content to be provided interactively in real time. Furthermore, automatic generation of individual prompts tailored to the needs of each user enables the provision of even more advanced personalized services.

[0566] "Personal genetic information" is data that indicates the genetic characteristics and risks of individual users.

[0567] "Nutrition intake data" is information about the foods and nutrients that a user takes in on a daily basis.

[0568] "Physical activity data" is information relating to the amount of exercise and activity level of the user in their daily life.

[0569] "Sleep pattern data" is information relating to the user's sleep duration, quality, and patterns.

[0570] "Analysis means" refers to technologies such as artificial intelligence engines that integrate collected genetic information with daily life data to assess the user's health status and risks.

[0571] A "health plan" is a plan that includes specific advice and recommendations for individualized health improvement based on the results of the analysis.

[0572] "Virtual reality" is a technology that allows users to have interactive experiences in a virtual space.

[0573] "Augmented reality" is a technology that overlays digital information and objects onto the real world.

[0574] An "interactive health improvement experience" is an experience in which users actively participate and interact with the experience through virtual reality or augmented reality to improve their health.

[0575] A "generative AI model" is a model that uses artificial intelligence to analyze data and generate appropriate output.

[0576] A "prompt" is a sentence output by a generative AI model that contains instructions or questions designed to elicit a specific action or response.

[0577] This invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data, with the aim of helping users effectively improve their health.

[0578] Data collection methods

[0579] First, the user collects a genetic sample using a genetic test kit and digitally inputs the information into a device (smartphone app). The device then transmits the genetic information to a server. Furthermore, the device also continuously collects daily life data (nutritional intake, physical activity, and sleep patterns) via a smartwatch or mobile app, and periodically transmits this data to a cloud-based server.

[0580] Data Integration Methods

[0581] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0582] Data Analysis Methods

[0583] An artificial intelligence engine (e.g., TensorFlow) on the server analyzes the data in the integrated database. The analysis is performed to evaluate the user's genetic risk and health trends. For example, if the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[0584] Health plan generator

[0585] Based on the analysis results, the server's AI engine generates a personalized health plan, which includes specific action items and recommendations tailored to the user's needs, such as "30 minutes of aerobic exercise every day" and "eat at least three vegetables per week."

[0586] Means of providing VR / AR experiences

[0587] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their own VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutritional information.

[0588] Feedback and Adjustments

[0589] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[0590] Prompt generation method

[0591] When generating a health plan, the server uses a generative AI model to generate personalized prompts that provide information and instructions tailored to the user's needs and circumstances. For example, prompts such as "Did you achieve your exercise goal today?" or "Are you satisfied with your meal plan this week?"

[0592] Specific examples

[0593] When User A uses this system, he or she provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and after analysis by an artificial intelligence engine, it determines that User A is at risk of diabetes. As a result, a health plan including daily aerobic exercise and calorie restriction is created. This plan is provided as VR content, and User A can receive interactive exercise guidance within the VR environment. As User A implements the plan and provides feedback, the server adjusts the plan based on that data, continuously providing optimal health improvements.

[0594] Prompt Sentence Examples

[0595] "Did you achieve your exercise goal today?"

[0596] "Are you happy with your meal plan this week?"

[0597] "How was your sleep quality?"

[0598] In this way, users can enjoy a continuous, personalized health improvement experience.

[0599] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0600] Step 1:

[0601] Users use a genetic testing kit to collect genetic samples and enter the genetic information into a device (smartphone app).

[0602] Input: Gene sample, user ID

[0603] Output: Genetic information in digital form

[0604] Specific behavior:

[0605] The user collects a sample using a genetic testing kit.

[0606] The genetic information is read within the app and transferred to the screen.

[0607] Step 2:

[0608] The device transmits the genetic information in digital form to a server.

[0609] Input: Digital genetic information, user ID

[0610] Output: Genetic information is stored on the server.

[0611] Specific behavior:

[0612] The app combines the genetic information with the user ID and sends it to the server.

[0613] Step 3:

[0614] The device continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application and periodically transmits it to a server.

[0615] Input: User's daily life data (nutrition, physical activity, sleep), user ID

[0616] Output: Daily life data is saved on the server.

[0617] Specific behavior:

[0618] Smartwatches and apps automatically record daily life data.

[0619] The terminal sends the collected data to the server.

[0620] Step 4:

[0621] The server checks the consistency of the received genetic information and daily life data and integrates them.

[0622] Input: Genetic information, daily life data, user ID

[0623] Output: Integrated data stored in an integrated database

[0624] Specific behavior:

[0625] The server associates genetic information with daily life data in a database.

[0626] Check the integrity of the data format and save it in the integrated database.

[0627] Step 5:

[0628] An artificial intelligence engine within the server analyzes the integrated data to assess the user's genetic risks and health trends.

[0629] Input: Integrated data in the integrated database

[0630] Output: Analysis results (health risks, health trends)

[0631] Specific behavior:

[0632] The AI ​​engine processes and analyzes the integrated data.

[0633] Evaluate health risks and trends and generate analytical results.

[0634] Step 6:

[0635] Based on the analysis results, the server's AI engine generates a personalized health plan.

[0636] Input: Analysis results, user ID

[0637] Output: A health plan with specific action items and recommendations

[0638] Specific behavior:

[0639] The AI ​​engine will create the optimal health plan based on the analysis results.

[0640] Step 7:

[0641] The server uses a generative AI model to generate personalized prompts related to the health plan.

[0642] Input: Health plan, user ID

[0643] Output: prompt statement

[0644] Specific behavior:

[0645] Parse the health plan and generate the appropriate prompt.

[0646] For example: "Did you achieve your exercise goal today?", "Are you happy with your meal plan this week?"

[0647] Step 8:

[0648] The server generates VR / AR content based on the health plan and provides it to the user through the device.

[0649] Input: Health plan, prompt, user ID

[0650] Output: VR / AR content

[0651] Specific behavior:

[0652] Create VR / AR content and distribute it to devices.

[0653] Examples: interactive exercise guides, meal planners, etc.

[0654] Step 9:

[0655] The device records the user's progress and reactions and sends them to the server.

[0656] Input: User progress data, feedback

[0657] Output: Progress data, feedback sent to the server.

[0658] Specific behavior:

[0659] Log user actions and feedback.

[0660] Sends progress data to the server.

[0661] Step 10:

[0662] The server analyzes the progress data and feedback and adjusts the health plan accordingly.

[0663] Inputs: progress data, feedback, existing health plan

[0664] Output: Coordinated Health Plan

[0665] Specific behavior:

[0666] Analyze progress data and generate a plan with appropriate modifications.

[0667] The updated plan will be delivered to your device.

[0668] Through these steps, users can enjoy a continuously personalized health improvement experience.

[0669] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0670] The present invention is an AI-driven health coaching system that integrates and analyzes personal genetic information, daily life data, and user emotional data, and is implemented as follows.

[0671] Data collection methods

[0672] First, the user collects a sample using a genetic testing kit and digitally inputs their genetic information through the app that comes with the kit. The input genetic information is then sent from the device to a server. The device also continuously collects daily life data (nutritional intake, physical activity, and sleep patterns) via a smartwatch or mobile app. This data is automatically uploaded to the server.

[0673] Furthermore, the device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data, including the user's motivation and stress level, which is then sent to the server.

[0674] Data Integration Methods

[0675] The server checks the consistency of the received genetic information, daily life data, and emotional data, and then integrates these data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0676] Data Analysis Methods

[0677] An artificial intelligence engine on the server analyzes the integrated data to assess the user's genetic risk, health trends, and emotional state. For example, if a user is at risk for diabetes, a specific health plan is generated based on the risk assessment results. The system also takes into account the user's stress level and motivation based on emotional data.

[0678] Health plan generator

[0679] Based on the analysis results, the server's AI engine generates a personalized health plan. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, in addition to advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it may also include advice such as "add relaxation exercises on days when you are under high stress."

[0680] Means of providing VR / AR experiences

[0681] The server creates VR / AR content based on the generated health plan and provides it to the user via the device. The user experiences the provided content using their smartphone or VR device. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction based on emotional data.

[0682] Feedback and Adjustments

[0683] The device records the user's progress and reactions and sends them to the server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health and emotional status in real time and increases engagement.

[0684] Specific examples

[0685] As a concrete example, let's consider the case where User B uses this system. User B provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. In addition, emotional data is obtained from User B's voice and facial expressions. The server integrates this data, and an artificial intelligence engine analyzes it, revealing that User B has a high stress level and is at risk of diabetes. The generated health plan includes daily exercise and a balanced diet, as well as relaxation exercises to reduce stress. This plan is provided as VR content, and User B experiences interactive relaxation training within the VR environment. User B provides feedback during and after the plan, and the server uses that data to adjust the health plan and continuously provide optimal improvement guidelines.

[0686] The above is an embodiment of the present invention.

[0687] The processing flow will be explained below.

[0688] Step 1:

[0689] A user collects a sample using a genetic testing kit and digitally inputs genetic information through an application provided with the kit, which then transmits the input genetic information from the device to a server.

[0690] Step 2:

[0691] The device continuously collects daily life data through the user's smartwatch or mobile application, including nutritional intake data, physical activity data, and sleep pattern data, which is then automatically uploaded to a server.

[0692] Step 3:

[0693] The device analyzes the user's voice, facial expressions, and behavioral patterns to acquire emotional data, including the user's motivation and stress level, and transmits the acquired emotional data to a server.

[0694] Step 4:

[0695] The server checks the consistency of genetic information, daily life data, and emotional data, checking for inconsistencies or missing data, and notifying the user if necessary.

[0696] Step 5:

[0697] The server stores the verified data in a consolidated database, where the data is linked based on a personal identification code (user ID).

[0698] Step 6:

[0699] The server's artificial intelligence engine analyzes the integrated data. Specifically, it evaluates genetic risk, health trends, and emotional state, and makes a specific diagnosis for each user. For example, it might say, "User B is in a high stress state and has a high genetic risk of diabetes."

[0700] Step 7:

[0701] The server's AI engine generates a personalized health plan based on the analysis results. The health plan includes specific guidelines for action and takes emotional data into consideration. For example, in addition to basic advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it also includes specific suggestions such as "add relaxation exercises on days when you're under high stress."

[0702] Step 8:

[0703] The server then creates VR / AR content based on the generated health plan, which users can experience interactively, such as an exercise guide in VR or a meal planner using AR.

[0704] Step 9:

[0705] The device provides the created VR / AR content to the user, who then experiences the content using their smartphone or VR device.

[0706] Step 10:

[0707] The device provides feedback on the results of activities and emotional responses as the user follows a health plan, including the type and duration of exercise, dietary content, and changes in emotional state.

[0708] Step 11:

[0709] The device sends the collected feedback data to a server, which analyzes the feedback and evaluates whether the health plan is appropriate.

[0710] Step 12:

[0711] The server adjusts the health plan as needed and generates an updated version, which is then provided to the user via the device again, optimizing the user's health and emotional state in real time.

[0712] The above is the specific processing flow of the program of the present invention combined with the emotion engine.

[0713] Example 2

[0714] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0715] Although there are systems that comprehensively integrate an individual's genetic information, daily life data, and emotional data to provide personalized health plans, many of them lack the ability to integrate and analyze data in a comprehensive manner, making it difficult to provide real-time feedback and adjustments. Another issue is that it is difficult to provide health plans that take into account the user's emotional state.

[0716] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0717] In this invention, the server includes: means for collecting personal genetic information, means for collecting nutritional intake data, physical activity data, and sleep pattern data, means for analyzing the user's voice, facial expressions, and behavioral patterns to obtain emotional data, means for transmitting the genetic information, daily life data, and emotional data to the server and integrating these data, means for analyzing the integrated data using an artificial intelligence engine to evaluate genetic risks, health trends, and emotional states, means for generating a personalized health plan based on the analysis results, means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan, and means for collecting the user's progress and reactions as feedback and adjusting the health plan, thereby enabling the provision of a comprehensive health plan based on the user's genetic risks, daily life data, and emotional states.

[0718] "Individual genetic information" refers to data that indicates an individual's biological characteristics obtained through genetic testing.

[0719] "Nutrient intake data" refers to information about the foods and their nutritional components that a user consumes in their daily lives.

[0720] "Physical activity data" is information about the exercise and daily physical activity of the user.

[0721] "Sleep pattern data" is data that indicates information related to the user's sleep state, sleep duration, and sleep quality.

[0722] "Emotional data" refers to information such as the user's psychological state, motivation, stress level, etc., analyzed from the user's voice, facial expressions, and behavior.

[0723] "Means of integration" refers to methods or technologies for centrally collecting, linking, and organizing various types of data.

[0724] An "artificial intelligence engine" is software or a system that analyzes large amounts of data and replicates human knowledge and pattern recognition.

[0725] "Genetic risk" is a risk assessment that indicates the likelihood of developing a particular disease or health problem based on genetic information.

[0726] "Health trends" is information that indicates trends regarding an individual's health condition and lifestyle habits based on daily life data.

[0727] "Personalized health plan" refers to a course of action or plan proposed for optimal health maintenance or improvement based on a user's individual genetic information, daily life data, and emotional data.

[0728] "Virtual reality" is a technology that uses computer technology to create a virtual 3D environment in which users can interact.

[0729] "Augmented reality" is a technology that overlays digital information and 3D objects onto a real environment, providing users with an experience that blends reality and virtuality.

[0730] "Means for collecting feedback" refers to methods or techniques for collecting progress and reactions from users and using them to evaluate and improve the system.

[0731] A "means for adjusting a health plan" is a method or technology for analyzing collected feedback data and revising the health plan to best suit the user.

[0732] This invention is a system that provides a health plan by integrating and analyzing an individual's genetic information, daily life data, and emotional data, and specific embodiments thereof will be described below.

[0733] Collection of genetic information

[0734] A user collects their own sample using a genetic testing kit. This sample is then digitally entered through an application that comes with the kit. The entered genetic information is then sent from the device to a server. This process involves the use of a genetic analysis kit and application.

[0735] Collection of daily life data

[0736] The device (e.g., smartwatch or mobile app) collects data on the user's daily life, including nutritional intake data, physical activity data, and sleep pattern data, and automatically uploads this data to a server. Specifically, the smartwatch measures exercise volume and sleep patterns, and the food recording app records nutritional intake data.

[0737] Collecting Emotional Data

[0738] The device (e.g., a smartphone or special sensor) analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. This data, including the user's motivation and stress level, is sent to a server. Speech recognition software and facial expression recognition algorithms are used.

[0739] Data integration and transmission

[0740] The device automatically sends all data to the server, which receives and centrally integrates this data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0741] Data analysis

[0742] An artificial intelligence engine on the server analyzes the integrated data. The analysis is carried out to assess the user's genetic risk, health trends, and emotional state. For example, genetic data and lifestyle data are used to analyze diabetes risk. The AI ​​engine analyzes this data and assesses health risks.

[0743] Health plan generation

[0744] The server's AI engine then generates a personalized health plan based on the analysis results. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, instructions include "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," and also includes instructions such as "add relaxation exercises on days when you're under high stress."

[0745] Providing VR / AR content

[0746] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user experiences this content using a smartphone or VR device. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction based on emotional data.

[0747] Gather feedback and adjust your plan

[0748] The device records the user's progress and reactions and sends them to the server. Feedback includes the results of exercise and diet, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates and adjusts the health plan to determine whether it is appropriate. If necessary, the health plan is revised appropriately and the updated plan is provided to the user via the device.

[0749] Prompt Sentence Examples

[0750] Here are some examples of prompts to input to a generative AI model:

[0751] Prompt: Analyze the health risks of users based on their genetic information, daily life data, and emotional data, and generate a personalized health plan. For example, what advice would you give to a user who is at risk of diabetes?

[0752] By feeding this prompt into a generative AI model, we can understand how the system processes the data and provides specific health advice.

[0753] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0754] Step 1: Collecting genetic information

[0755] A user collects a sample using a genetic testing kit, enters genetic information digitally through the kit's application, and transmits it to a server via a terminal.

[0756] Specific behavior:

[0757] The user uses a cotton swab to collect cells from inside the mouth.

[0758] Launch the application and scan or enter your genetic information.

[0759] The device will use Wi-Fi or mobile data to send genetic information to a server.

[0760] Input: Gene sample

[0761] Output: Genetic information in digital form

[0762] Step 2: Collecting daily life data

[0763] The device (smartwatch or mobile app) collects data about the user's daily life and automatically uploads it to a server.

[0764] Specific behavior:

[0765] The smartwatch measures the user's steps and exercise volume.

[0766] The food recording app inputs the user's meal details.

[0767] A sleep tracker analyzes your sleep patterns.

[0768] The device periodically uploads this data to the server.

[0769] Input: User's daily living activities

[0770] Output: Digital daily life data

[0771] Step 3: Collecting emotion data

[0772] The device analyzes the user's voice, facial expressions, and behavioral patterns, acquires emotional data, and sends it to the server.

[0773] Specific behavior:

[0774] The smartphone camera captures and analyzes the user's facial expressions.

[0775] It uses speech recognition technology to analyze the content and tone of what a user is saying.

[0776] The terminal transmits this emotion data to the server.

[0777] Input: User's voice, facial expressions, and actions

[0778] Output: Digital emotional data

[0779] Step 4: Integrate and send data

[0780] The genetic information, daily life data, and emotional data collected by the device are sent to a server, which then stores them in a centralized integrated database.

[0781] Specific behavior:

[0782] The device sends each piece of data to the server using Wi-Fi or mobile data.

[0783] The server receives all the data, organizes it and consolidates it based on the personal identification code (user ID).

[0784] Input: Genetic information, daily life data, emotional data

[0785] Output: Integrated database

[0786] Step 5: Data analysis

[0787] An artificial intelligence engine within the server analyzes the integrated data and assesses the user's genetic risks, health trends and emotional state.

[0788] Specific behavior:

[0789] The AI ​​engine extracts risk factors from genetic data.

[0790] Analyze health trends based on daily life data.

[0791] Evaluate stress levels and motivation from emotional data.

[0792] Input: Integrated database

[0793] Output: Analysis results (genetic risk, health trends, emotional state)

[0794] Step 6: Generate a health plan

[0795] The server's AI engine generates a personalized health plan based on the analysis results.

[0796] Specific behavior:

[0797] The AI ​​engine generates specific guidelines for action, such as "30 minutes of aerobic exercise every day."

[0798] It suggests relaxation exercises based on the user's stress level.

[0799] Input: Analysis results

[0800] Output: personalized health plan

[0801] Step 7: Providing VR / AR content

[0802] The server creates VR / AR content based on the generated health plan and provides it to the user via their device, where the user can experience it.

[0803] Specific behavior:

[0804] Create VR / AR content using dedicated software.

[0805] The device delivers VR / AR content to the user.

[0806] Users experience the content using a smartphone or VR device.

[0807] Enter: personalized health plans.

[0808] Output: VR / AR content experience

[0809] Step 8: Gather feedback and refine your plan

[0810] The device records the user's progress and reactions and sends them to a server, which analyzes the feedback data and adjusts and updates the health plan.

[0811] Specific behavior:

[0812] The device records the user's exercise log, meal log, and emotional changes.

[0813] The server analyzes the feedback data and adjusts the health plan.

[0814] Input: User progress and feedback

[0815] Output: Coordinated Health Plan

[0816] (Application example 2)

[0817] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0818] Conventional health management systems generate health plans based solely on genetic information and daily life data, failing to fully consider the user's emotional state and motivation, making it difficult to effectively improve their health. Furthermore, they lacked personalized product recommendations and interactive experiences, resulting in low user engagement. This led to a decline in users' motivation to continue managing their health, making it difficult to effectively improve their health.

[0819] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0820] In this invention, the server includes: means for collecting personal genetic information; means for collecting nutritional intake data, physical activity data, and sleep pattern data; means for collecting emotional data from voice, facial expressions, and behavioral patterns; means for integrating and analyzing the genetic information, the daily life data, and the emotional data; means for generating a personalized health plan based on the analysis results; means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan; and means for recommending products in a virtual store based on the health plan. This makes it possible to provide a personalized health plan that takes into account the user's genetic risks and health trends, as well as their emotional state and motivation, and further makes it possible to more effectively support the user's health improvement by recommending appropriate products in the virtual store.

[0821] "Genetic information" is data that indicates the genetic characteristics of a user, and is information obtained through DNA analysis.

[0822] "Daily life data" refers to data relating to the user's daily activities and lifestyle habits, including information on nutritional intake, physical activity, sleep patterns, and the like.

[0823] "Emotion data" is data obtained from the user's voice, facial expressions, and behavioral patterns, and is information that indicates the user's emotional state, such as stress level and motivation.

[0824] "Integration" means bringing together multiple different data into a single database and managing them in a correlated manner.

[0825] "Analysis" is an information processing activity that uses collected data to clarify its content and meaning.

[0826] A "health plan" is a plan that includes specific, personalized actions and advice to improve a user's health.

[0827] "Virtual reality" is a technology that uses computer technology to provide users with virtual environments and experiences that do not exist in reality.

[0828] "Augmented reality" is a technology that displays digital information overlaid on visual information from the real world, enhancing the user's experience.

[0829] An "interactive health improvement experience" refers to activities and training for improving health that are provided in a way that allows users to actively participate, and that enhances effectiveness through two-way interaction.

[0830] A "virtual store" is a virtual store accessible via the Internet, an online platform where users can browse, select and purchase products in a digital environment.

[0831] "Product recommendation" refers to selecting and suggesting specific products that match the user's needs and preferences.

[0832] This invention is a system that integrates and analyzes an individual's genetic information, daily life data, and emotional data to provide a personalized health plan to the user. A specific implementation method is described below.

[0833] Data collection methods

[0834] First, the user collects a sample using a genetic test kit and digitally enters their genetic information through a dedicated application. This genetic information is then sent to a server from a device such as a smartphone. Furthermore, the user's daily life data (nutritional intake, physical activity, and sleep pattern data) is continuously collected via a smartwatch or mobile application, and this data is also automatically uploaded to the server. Additionally, the device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. This emotional data includes the user's motivation and stress level and is then sent to the server.

[0835] Data Integration Methods

[0836] The server checks the consistency of the received genetic information, daily life data, and emotional data, and integrates them. All data is linked based on a personal identification code (user ID) and stored in an integrated database. The hardware used is compatible with AWS (Amazon Web Services) databases.

[0837] Data Analysis Methods

[0838] An artificial intelligence engine on the server analyzes the integrated data to assess the user's genetic risk, health trends, and emotional state. For example, this is done using Python and TensorFlow. If the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results. The system also takes into account the user's stress level and motivation based on emotional data.

[0839] Health plan generator

[0840] Based on the analysis results, the server's AI engine generates a personalized health plan. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, in addition to advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it may also include advice such as "add relaxation exercises on days when you are under high stress."

[0841] Means of providing VR / AR experiences

[0842] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user can experience the provided content using their smartphone or VR device. For example, they can use an Oculus Quest to experience an AR trainer that guides exercise, or a relaxation program that reduces stress based on emotional data.

[0843] Feedback and Adjustments

[0844] The device records the user's progress and reactions and sends them to the server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health and emotional status in real time and increases engagement.

[0845] Examples and prompts

[0846] As a concrete example, let's consider the case where User B uses this system. User B provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. In addition, emotional data is obtained from User B's voice and facial expressions. The server integrates this data, and an artificial intelligence engine analyzes it, revealing that User B has a high stress level and is at risk of diabetes. The generated health plan includes daily exercise and a balanced diet, as well as relaxation exercises to reduce stress. This plan is provided as VR content, and User B experiences interactive relaxation training within the VR environment. User B provides feedback during and after the plan, and the server uses that data to adjust the health plan and continuously provide optimal improvement guidelines.

[0847] Example prompt sentence:

[0848] "Generate a personalized health plan and related product recommendations based on the user's genetic information, daily life data (activity, nutrition, sleep patterns), and emotional data (facial expressions, voice). The health plan should include specific exercise instructions, dietary suggestions, and advice on stress reduction. Related products should suggest fitness equipment, supplements, and relaxation tools available for purchase in a virtual store."

[0849] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0850] Step 1:

[0851] Users use a genetic test kit to collect a genetic sample and input the results into the application, which then sends the data from a device such as a smartphone to a server.

[0852] Input: Genetic sample results

[0853] Output: Sending genetic information to the server

[0854] Step 2:

[0855] The device (smartwatch or mobile application) continuously collects data on the user's daily life (nutritional intake data, physical activity data, sleep pattern data) and automatically uploads this data to a server.

[0856] Input: Daily life data (exercise, nutrition, sleep data)

[0857] Output: Sending daily life data to the server

[0858] Step 3:

[0859] The device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. It uses voice recognition and facial expression analysis algorithms to determine the user's emotional state. This data is then sent to the server.

[0860] Input: Voice data, facial expression data, behavior patterns

[0861] Output: Sending emotion data to the server

[0862] Step 4:

[0863] The server integrates the received genetic information, daily life data, and emotion data. Using Python and AWS databases, the data is integrated and stored in a database. This process verifies the integrity of the data and generates a single linked dataset.

[0864] Input: Genetic information, daily life data, emotional data

[0865] Output: A consolidated dataset

[0866] Step 5:

[0867] The AI ​​engine on the server analyzes the integrated data set to assess the user's genetic risk, health trends, and emotional state. It uses AI tools such as TensorFlow to perform the analysis and then predicts health risks and evaluates emotional state based on the results.

[0868] Input: Integrated dataset

[0869] Output: Analysis results (health risk assessment, emotional state assessment)

[0870] Step 6:

[0871] The server's AI engine generates a personalized health plan based on the analysis results. This health plan includes specific guidelines for action and takes into account the user's emotional state. For example, instructions include "30 minutes of aerobic exercise every day," "eat at least three servings of vegetables per week," and "add relaxation exercises on days when you're under high stress."

[0872] Input: Analysis results

[0873] Output: personalized health plan

[0874] Step 7:

[0875] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user experiences the content using a VR device such as Oculus Quest. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction.

[0876] Enter: personalized health plans.

[0877] Output: VR / AR content

[0878] Step 8:

[0879] The device records the user's progress and reactions and sends them to a server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data, evaluates whether the health plan is appropriate, and adjusts the health plan accordingly, if necessary.

[0880] Input: User feedback data

[0881] Output: Coordinated Health Plan

[0882] The above are the processing steps of the system that realizes the application example.

[0883] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0884] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0885] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0886] [Third embodiment]

[0887] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0888] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0889] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0890] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0891] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0892] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0893] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0894] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0895] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0896] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0897] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0898] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0899] The present invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data, and is implemented as follows.

[0900] Data collection methods

[0901] First, the user collects a sample using a genetic test kit to obtain genetic information. The device (smartphone app) digitally inputs this genetic information and sends it to a server. The device also continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application. This data is periodically sent from the device to a cloud server.

[0902] Data Integration Methods

[0903] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0904] Data Analysis Methods

[0905] An artificial intelligence engine on the server analyzes the data in the integrated database to assess the user's genetic risk and health trends. For example, if a user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[0906] Health plan generator

[0907] Based on the analysis results, the server's AI engine generates a personalized health plan with specific action items and recommendations tailored to the user's needs, such as "do 30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[0908] Means of providing VR / AR experiences

[0909] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their own VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutritional information.

[0910] Feedback and Adjustments

[0911] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[0912] Specific examples

[0913] As a concrete example, let's consider the case where User A uses this system. User A provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and after analysis by an artificial intelligence engine, it is determined that User A is at risk of diabetes. As a result, a health plan including daily aerobic exercise and calorie restriction is created. This plan is provided as VR content, and User A can receive interactive exercise guidance within the VR environment. As User A implements the plan and provides feedback, the server adjusts the plan based on that data, continuously providing optimal health improvements.

[0914] The above is an embodiment of the present invention.

[0915] The processing flow will be explained below.

[0916] Step 1:

[0917] A user collects a sample using a genetic testing kit and digitally inputs genetic information through an application provided with the kit, which then transmits the input genetic information from the device to a server.

[0918] Step 2:

[0919] The device continuously collects daily life data through the user's smartwatch or mobile application, including nutritional intake data, physical activity data, and sleep pattern data, which is then automatically uploaded to a server.

[0920] Step 3:

[0921] The server checks the consistency of the received genetic information and daily life data. If there is missing or inconsistent data, the server notifies the user and requests that the data be resent.

[0922] Step 4:

[0923] The server stores verified genetic information and daily life data in an integrated database, which is linked based on a personal identification code (user ID).

[0924] Step 5:

[0925] An artificial intelligence engine on the server analyzes the integrated data, assessing genetic risks and health trends and providing a specific diagnosis for each user. For example, it may say, "User A is at high risk for type 2 diabetes."

[0926] Step 6:

[0927] The server's AI engine generates a personalized health plan based on the analysis results, which includes specific guidelines for action, such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[0928] Step 7:

[0929] The server then creates VR / AR content based on the generated health plan, which can be interactively experienced by users, such as exercise guides in VR or meal planners using AR.

[0930] Step 8:

[0931] The device provides the created VR / AR content to the user, who then experiences the content using their smartphone or VR device.

[0932] Step 9:

[0933] As users follow their health plan, they input feedback via the device, including the results of their exercise and diet, and changes in their health status.

[0934] Step 10:

[0935] The device sends the collected feedback data to a server, which analyzes this feedback and adjusts the health plan as needed.

[0936] Step 11:

[0937] The server then generates an adjusted health plan and provides it to the user via the device, thereby optimizing the user's health status in real time.

[0938] The above is the specific processing flow of the program.

[0939] Example 1

[0940] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0941] For health management, there is a need for a system that provides more accurate, personalized health plans by integrating and analyzing not only an individual's genetic information but also their daily life data. However, there are challenges in that the integrated analysis of genetic information and daily life data has not been sufficiently carried out, and there is a lack of a mechanism for providing real-time feedback and adjustments on the effectiveness of the health plans provided.

[0942] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0943] In this invention, the server includes means for collecting an individual's genetic information, means for collecting nutritional intake data, physical activity data, and sleep pattern data, means for integrating and analyzing the genetic information and the daily life data, means for generating a personalized health plan based on the analysis results, means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan, means for recording the implementation status and feedback of the health plan and transmitting it to the server, and means for analyzing the feedback data and reevaluating and adjusting the health plan, thereby enabling the provision of a highly accurate personalized health plan and the ability to provide feedback on its effectiveness and adjust it in real time.

[0944] "Genetic information" is data based on an individual's DNA that indicates genetic characteristics and risks.

[0945] "Nutrition intake data" refers to information about the foods and nutrients that an individual consumes in their daily lives.

[0946] "Physical activity data" refers to information relating to the amount and pattern of exercise in an individual's daily life.

[0947] "Sleep pattern data" is information about an individual's sleep duration, sleep quality, and sleep cycle.

[0948] "Synthesis" is the process of combining different types of data into a single, coherent data set.

[0949] "Analysis" is the process of analyzing collected data and extracting meaningful information and patterns.

[0950] A "health plan" is a written plan that includes specific action guidelines and recommendations for improving an individual's health.

[0951] "Virtual reality" refers to a virtual environment or experience created using computer technology.

[0952] "Augmented reality" is a technology that overlays computer-generated images and information on real-world scenes.

[0953] An "interactive health improvement experience" is a health improvement program designed to allow users to actively participate, often using virtual reality or augmented reality.

[0954] "Feedback" refers to the data and opinions obtained after a user implements a health plan, and is information used to reevaluate and adjust the plan.

[0955] "Reevaluation" is the process of reassessing the effectiveness of current health plans based on collected feedback data and making adjustments as necessary.

[0956] "Adjustment" is the process of modifying and improving existing plans and systems based on evaluation results and feedback.

[0957] This invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data. The system is implemented as follows:

[0958] Data collection

[0959] First, the user collects a sample using a genetic test kit to obtain genetic information. The device (smartphone app) digitally inputs this genetic information and sends it to a server. The device also continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application. This data is periodically sent from the device to a cloud server.

[0960] Data Integration

[0961] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[0962] Data analysis

[0963] The server's AI engine analyzes the data in the integrated database to assess the user's genetic risk and health trends. For example, if the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[0964] Health plan generation

[0965] Based on the analysis, the server's AI engine generates a personalized health plan with specific action items and recommendations tailored to the user's needs, such as "do 30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[0966] Providing VR / AR experiences

[0967] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutrition information.

[0968] Feedback and Adjustments

[0969] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[0970] Specific examples

[0971] For example, when User A uses this system, the process goes as follows: User A provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and the AI ​​engine analyzes it to determine whether User A is at risk of diabetes. The generated health plan includes instructions for daily aerobic exercise and calorie restriction and is provided as VR content. When User A implements the plan and provides feedback, the server reevaluates and adjusts the plan based on that data, continuously providing User A with optimal health improvements.

[0972] Prompt Sentence Examples

[0973] Below is an example of a prompt sentence to be input to the generative AI model of this system.

[0974] Describe a system that integrates a user's genetic information and daily life data to generate a personalized health plan. Illustrate how a health plan is created and provided to a user at risk for diabetes.

[0975] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0976] Step 1:

[0977] A user collects a sample (e.g., saliva) using a genetic test kit and mails it to a testing institution. The genetic information obtained from the testing institution is provided in digital format and entered into a terminal (smartphone app). The terminal sends this input data (genetic information) to a server. The input is the user ID and genetic information, and the output is the digital genetic information sent to the server.

[0978] Step 2:

[0979] The device continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) using a smartwatch or mobile application. For example, the smartwatch records heart rate and exercise volume, and the mobile application inputs the user's dietary information. This data (input) is periodically sent to a server (output) and stored on the server.

[0980] Step 3:

[0981] The server checks the integrity of all received data. Specifically, it checks the format of the genetic information and checks for abnormal values ​​in the daily life data. The input is the genetic information and daily life data sent from the device, and the output is the verified integrated data. This data is stored in the server's integrated database.

[0982] Step 4:

[0983] The AI ​​engine on the server analyzes the data in the integrated database. The input data is genetic information and daily life data, and the output is the results of the user's genetic risk assessment and health trend analysis. For example, it determines whether or not a person is at high risk for diabetes. These analyses are performed using machine learning algorithms.

[0984] Step 5:

[0985] Based on the analysis results, the server's AI engine generates a personalized health plan. The input is the analysis results by the AI ​​engine, and the output is a health plan including specific action items (e.g., "30 minutes of aerobic exercise every day" and "eat at least three vegetables per week"). This plan is customized based on the user's lifestyle and genetic risk.

[0986] Step 6:

[0987] The server generates VR / AR content based on the generated health plan and provides it to the user through the device. The input is the generated health plan, and the output is interactive content that can be displayed on a VR device or smartphone. For example, it includes an AR trainer for exercise guidance and a meal planner for nutritional information.

[0988] Step 7:

[0989] The device records the user's progress and feedback. For example, the user enters the results of implementing a health plan and their thoughts about it into the app. The input is the user's feedback data, and the output is a progress record including the feedback. This data is sent from the device to the server.

[0990] Step 8:

[0991] The server analyzes the collected feedback data and evaluates whether the health plan is appropriate. If necessary, it reevaluates the health plan and generates a new, adjusted plan. The input is the feedback data and the current health plan, and the output is the adjusted health plan. The updated plan is again provided to the user via the terminal.

[0992] (Application example 1)

[0993] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0994] In today's world, personal health management is becoming an increasingly important issue, and there is a demand for providing personalized health plans that utilize genetic information and daily life data. However, conventional systems struggle to efficiently integrate and analyze genetic information and daily life data, and lack the means to interactively provide personalized health improvement content in real time. Furthermore, the generation of prompts that provide information tailored to each user's needs when generating individual health plans is not automated, making it difficult to provide personalized services.

[0995] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0996] In this invention, the server includes: means for collecting an individual's genetic information; means for collecting nutritional intake data, physical activity data, and sleep pattern data; means for integrating and analyzing the genetic information and daily life data; means for generating a personalized health plan based on the analysis results; means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan; and means for generating individual prompts using a generative AI model when generating the health plan. This enables efficient integration and analysis of genetic information and daily life data, and personalized health improvement content to be provided interactively in real time. Furthermore, automatic generation of individual prompts tailored to the needs of each user enables the provision of even more advanced personalized services.

[0997] "Personal genetic information" is data that indicates the genetic characteristics and risks of individual users.

[0998] "Nutrition intake data" is information about the foods and nutrients that a user takes in on a daily basis.

[0999] "Physical activity data" is information relating to the amount of exercise and activity level of the user in their daily life.

[1000] "Sleep pattern data" is information relating to the user's sleep duration, quality, and patterns.

[1001] "Analysis means" refers to technologies such as artificial intelligence engines that integrate collected genetic information with daily life data to assess the user's health status and risks.

[1002] A "health plan" is a plan that includes specific advice and recommendations for individualized health improvement based on the results of the analysis.

[1003] "Virtual reality" is a technology that allows users to have interactive experiences in a virtual space.

[1004] "Augmented reality" is a technology that overlays digital information and objects onto the real world.

[1005] An "interactive health improvement experience" is an experience in which users actively participate and interact with the experience through virtual reality or augmented reality to improve their health.

[1006] A "generative AI model" is a model that uses artificial intelligence to analyze data and generate appropriate output.

[1007] A "prompt" is a sentence output by a generative AI model that contains instructions or questions designed to elicit a specific action or response.

[1008] This invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data, with the aim of helping users effectively improve their health.

[1009] Data collection methods

[1010] First, the user collects a genetic sample using a genetic test kit and digitally inputs the information into a device (smartphone app). The device then transmits the genetic information to a server. Furthermore, the device also continuously collects daily life data (nutritional intake, physical activity, and sleep patterns) via a smartwatch or mobile app, and periodically transmits this data to a cloud-based server.

[1011] Data Integration Methods

[1012] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[1013] Data Analysis Methods

[1014] An artificial intelligence engine (e.g., TensorFlow) on the server analyzes the data in the integrated database. The analysis is performed to evaluate the user's genetic risk and health trends. For example, if the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[1015] Health plan generator

[1016] Based on the analysis results, the server's AI engine generates a personalized health plan, which includes specific action items and recommendations tailored to the user's needs, such as "30 minutes of aerobic exercise every day" and "eat at least three vegetables per week."

[1017] Means of providing VR / AR experiences

[1018] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their own VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutritional information.

[1019] Feedback and Adjustments

[1020] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[1021] Prompt generation method

[1022] When generating a health plan, the server uses a generative AI model to generate personalized prompts that provide information and instructions tailored to the user's needs and circumstances. For example, prompts such as "Did you achieve your exercise goal today?" or "Are you satisfied with your meal plan this week?"

[1023] Specific examples

[1024] When User A uses this system, he or she provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and after analysis by an artificial intelligence engine, it determines that User A is at risk of diabetes. As a result, a health plan including daily aerobic exercise and calorie restriction is created. This plan is provided as VR content, and User A can receive interactive exercise guidance within the VR environment. As User A implements the plan and provides feedback, the server adjusts the plan based on that data, continuously providing optimal health improvements.

[1025] Prompt Sentence Examples

[1026] "Did you achieve your exercise goal today?"

[1027] "Are you happy with your meal plan this week?"

[1028] "How was your sleep quality?"

[1029] In this way, users can enjoy a continuous, personalized health improvement experience.

[1030] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1031] Step 1:

[1032] Users use a genetic testing kit to collect genetic samples and enter the genetic information into a device (smartphone app).

[1033] Input: Gene sample, user ID

[1034] Output: Genetic information in digital form

[1035] Specific behavior:

[1036] The user collects a sample using a genetic testing kit.

[1037] The genetic information is read within the app and transferred to the screen.

[1038] Step 2:

[1039] The device transmits the genetic information in digital form to a server.

[1040] Input: Digital genetic information, user ID

[1041] Output: Genetic information is stored on the server.

[1042] Specific behavior:

[1043] The app combines the genetic information with the user ID and sends it to the server.

[1044] Step 3:

[1045] The device continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application and periodically transmits it to a server.

[1046] Input: User's daily life data (nutrition, physical activity, sleep), user ID

[1047] Output: Daily life data is saved on the server.

[1048] Specific behavior:

[1049] Smartwatches and apps automatically record daily life data.

[1050] The terminal sends the collected data to the server.

[1051] Step 4:

[1052] The server checks the consistency of the received genetic information and daily life data and integrates them.

[1053] Input: Genetic information, daily life data, user ID

[1054] Output: Integrated data stored in an integrated database

[1055] Specific behavior:

[1056] The server associates genetic information with daily life data in a database.

[1057] Check the integrity of the data format and save it in the integrated database.

[1058] Step 5:

[1059] An artificial intelligence engine within the server analyzes the integrated data to assess the user's genetic risks and health trends.

[1060] Input: Integrated data in the integrated database

[1061] Output: Analysis results (health risks, health trends)

[1062] Specific behavior:

[1063] The AI ​​engine processes and analyzes the integrated data.

[1064] Evaluate health risks and trends and generate analytical results.

[1065] Step 6:

[1066] Based on the analysis results, the server's AI engine generates a personalized health plan.

[1067] Input: Analysis results, user ID

[1068] Output: A health plan with specific action items and recommendations

[1069] Specific behavior:

[1070] The AI ​​engine will create the optimal health plan based on the analysis results.

[1071] Step 7:

[1072] The server uses a generative AI model to generate personalized prompts related to the health plan.

[1073] Input: Health plan, user ID

[1074] Output: prompt statement

[1075] Specific behavior:

[1076] Parse the health plan and generate the appropriate prompt.

[1077] For example: "Did you achieve your exercise goal today?", "Are you happy with your meal plan this week?"

[1078] Step 8:

[1079] The server generates VR / AR content based on the health plan and provides it to the user through the device.

[1080] Input: Health plan, prompt, user ID

[1081] Output: VR / AR content

[1082] Specific behavior:

[1083] Create VR / AR content and distribute it to devices.

[1084] Examples: interactive exercise guides, meal planners, etc.

[1085] Step 9:

[1086] The device records the user's progress and reactions and sends them to the server.

[1087] Input: User progress data, feedback

[1088] Output: Progress data, feedback sent to the server.

[1089] Specific behavior:

[1090] Log user actions and feedback.

[1091] Sends progress data to the server.

[1092] Step 10:

[1093] The server analyzes the progress data and feedback and adjusts the health plan accordingly.

[1094] Inputs: progress data, feedback, existing health plan

[1095] Output: Coordinated Health Plan

[1096] Specific behavior:

[1097] Analyze progress data and generate a plan with appropriate modifications.

[1098] The updated plan will be delivered to your device.

[1099] Through these steps, users can enjoy a continuously personalized health improvement experience.

[1100] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1101] The present invention is an AI-driven health coaching system that integrates and analyzes personal genetic information, daily life data, and user emotional data, and is implemented as follows.

[1102] Data collection methods

[1103] First, the user collects a sample using a genetic testing kit and digitally inputs their genetic information through the app that comes with the kit. The input genetic information is then sent from the device to a server. The device also continuously collects daily life data (nutritional intake, physical activity, and sleep patterns) via a smartwatch or mobile app. This data is automatically uploaded to the server.

[1104] Furthermore, the device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data, including the user's motivation and stress level, which is then sent to the server.

[1105] Data Integration Methods

[1106] The server checks the consistency of the received genetic information, daily life data, and emotional data, and then integrates these data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[1107] Data Analysis Methods

[1108] An artificial intelligence engine on the server analyzes the integrated data to assess the user's genetic risk, health trends, and emotional state. For example, if a user is at risk for diabetes, a specific health plan is generated based on the risk assessment results. The system also takes into account the user's stress level and motivation based on emotional data.

[1109] Health plan generator

[1110] Based on the analysis results, the server's AI engine generates a personalized health plan. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, in addition to advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it may also include advice such as "add relaxation exercises on days when you are under high stress."

[1111] Means of providing VR / AR experiences

[1112] The server creates VR / AR content based on the generated health plan and provides it to the user via the device. The user experiences the provided content using their smartphone or VR device. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction based on emotional data.

[1113] Feedback and Adjustments

[1114] The device records the user's progress and reactions and sends them to the server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health and emotional status in real time and increases engagement.

[1115] Specific examples

[1116] As a concrete example, let's consider the case where User B uses this system. User B provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. In addition, emotional data is obtained from User B's voice and facial expressions. The server integrates this data, and an artificial intelligence engine analyzes it, revealing that User B has a high stress level and is at risk of diabetes. The generated health plan includes daily exercise and a balanced diet, as well as relaxation exercises to reduce stress. This plan is provided as VR content, and User B experiences interactive relaxation training within the VR environment. User B provides feedback during and after the plan, and the server uses that data to adjust the health plan and continuously provide optimal improvement guidelines.

[1117] The above is an embodiment of the present invention.

[1118] The processing flow will be explained below.

[1119] Step 1:

[1120] A user collects a sample using a genetic testing kit and digitally inputs genetic information through an application provided with the kit, which then transmits the input genetic information from the device to a server.

[1121] Step 2:

[1122] The device continuously collects daily life data through the user's smartwatch or mobile application, including nutritional intake data, physical activity data, and sleep pattern data, which is then automatically uploaded to a server.

[1123] Step 3:

[1124] The device analyzes the user's voice, facial expressions, and behavioral patterns to acquire emotional data, including the user's motivation and stress level, and transmits the acquired emotional data to a server.

[1125] Step 4:

[1126] The server checks the consistency of genetic information, daily life data, and emotional data, checking for inconsistencies or missing data, and notifying the user if necessary.

[1127] Step 5:

[1128] The server stores the verified data in a consolidated database, where the data is linked based on a personal identification code (user ID).

[1129] Step 6:

[1130] The server's artificial intelligence engine analyzes the integrated data. Specifically, it evaluates genetic risk, health trends, and emotional state, and makes a specific diagnosis for each user. For example, it might say, "User B is in a high stress state and has a high genetic risk of diabetes."

[1131] Step 7:

[1132] The server's AI engine generates a personalized health plan based on the analysis results. The health plan includes specific guidelines for action and takes emotional data into consideration. For example, in addition to basic advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it also includes specific suggestions such as "add relaxation exercises on days when you're under high stress."

[1133] Step 8:

[1134] The server then creates VR / AR content based on the generated health plan, which users can experience interactively, such as an exercise guide in VR or a meal planner using AR.

[1135] Step 9:

[1136] The device provides the created VR / AR content to the user, who then experiences the content using their smartphone or VR device.

[1137] Step 10:

[1138] The device provides feedback on the results of activities and emotional responses as the user follows a health plan, including the type and duration of exercise, dietary content, and changes in emotional state.

[1139] Step 11:

[1140] The device sends the collected feedback data to a server, which analyzes the feedback and evaluates whether the health plan is appropriate.

[1141] Step 12:

[1142] The server adjusts the health plan as needed and generates an updated version, which is then provided to the user via the device again, optimizing the user's health and emotional state in real time.

[1143] The above is the specific processing flow of the program of the present invention combined with the emotion engine.

[1144] Example 2

[1145] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1146] Although there are systems that comprehensively integrate an individual's genetic information, daily life data, and emotional data to provide personalized health plans, many of them lack the ability to integrate and analyze data in a comprehensive manner, making it difficult to provide real-time feedback and adjustments. Another issue is that it is difficult to provide health plans that take into account the user's emotional state.

[1147] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1148] In this invention, the server includes: means for collecting personal genetic information, means for collecting nutritional intake data, physical activity data, and sleep pattern data, means for analyzing the user's voice, facial expressions, and behavioral patterns to obtain emotional data, means for transmitting the genetic information, daily life data, and emotional data to the server and integrating these data, means for analyzing the integrated data using an artificial intelligence engine to evaluate genetic risks, health trends, and emotional states, means for generating a personalized health plan based on the analysis results, means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan, and means for collecting the user's progress and reactions as feedback and adjusting the health plan, thereby enabling the provision of a comprehensive health plan based on the user's genetic risks, daily life data, and emotional states.

[1149] "Individual genetic information" refers to data that indicates an individual's biological characteristics obtained through genetic testing.

[1150] "Nutrient intake data" refers to information about the foods and their nutritional components that a user consumes in their daily lives.

[1151] "Physical activity data" is information about the exercise and daily physical activity of the user.

[1152] "Sleep pattern data" is data that indicates information related to the user's sleep state, sleep duration, and sleep quality.

[1153] "Emotional data" refers to information such as the user's psychological state, motivation, stress level, etc., analyzed from the user's voice, facial expressions, and behavior.

[1154] "Means of integration" refers to methods or technologies for centrally collecting, linking, and organizing various types of data.

[1155] An "artificial intelligence engine" is software or a system that analyzes large amounts of data and replicates human knowledge and pattern recognition.

[1156] "Genetic risk" is a risk assessment that indicates the likelihood of developing a particular disease or health problem based on genetic information.

[1157] "Health trends" is information that indicates trends regarding an individual's health condition and lifestyle habits based on daily life data.

[1158] "Personalized health plan" refers to a course of action or plan proposed for optimal health maintenance or improvement based on a user's individual genetic information, daily life data, and emotional data.

[1159] "Virtual reality" is a technology that uses computer technology to create a virtual 3D environment in which users can interact.

[1160] "Augmented reality" is a technology that overlays digital information and 3D objects onto a real environment, providing users with an experience that blends reality and virtuality.

[1161] "Means for collecting feedback" refers to methods or techniques for collecting progress and reactions from users and using them to evaluate and improve the system.

[1162] A "means for adjusting a health plan" is a method or technology for analyzing collected feedback data and revising the health plan to best suit the user.

[1163] This invention is a system that provides a health plan by integrating and analyzing an individual's genetic information, daily life data, and emotional data, and specific embodiments thereof will be described below.

[1164] Collection of genetic information

[1165] A user collects their own sample using a genetic testing kit. This sample is then digitally entered through an application that comes with the kit. The entered genetic information is then sent from the device to a server. This process involves the use of a genetic analysis kit and application.

[1166] Collection of daily life data

[1167] The device (e.g., smartwatch or mobile app) collects data on the user's daily life, including nutritional intake data, physical activity data, and sleep pattern data, and automatically uploads this data to a server. Specifically, the smartwatch measures exercise volume and sleep patterns, and the food recording app records nutritional intake data.

[1168] Collecting Emotional Data

[1169] The device (e.g., a smartphone or special sensor) analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. This data, including the user's motivation and stress level, is sent to a server. Speech recognition software and facial expression recognition algorithms are used.

[1170] Data integration and transmission

[1171] The device automatically sends all data to the server, which receives and centrally integrates this data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[1172] Data analysis

[1173] An artificial intelligence engine on the server analyzes the integrated data. The analysis is carried out to assess the user's genetic risk, health trends, and emotional state. For example, genetic data and lifestyle data are used to analyze diabetes risk. The AI ​​engine analyzes this data and assesses health risks.

[1174] Health plan generation

[1175] The server's AI engine then generates a personalized health plan based on the analysis results. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, instructions include "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," and also includes instructions such as "add relaxation exercises on days when you're under high stress."

[1176] Providing VR / AR content

[1177] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user experiences this content using a smartphone or VR device. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction based on emotional data.

[1178] Gather feedback and adjust your plan

[1179] The device records the user's progress and reactions and sends them to the server. Feedback includes the results of exercise and diet, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates and adjusts the health plan to determine whether it is appropriate. If necessary, the health plan is revised appropriately and the updated plan is provided to the user via the device.

[1180] Prompt Sentence Examples

[1181] Here are some examples of prompts to input to a generative AI model:

[1182] Prompt: Analyze the health risks of users based on their genetic information, daily life data, and emotional data, and generate a personalized health plan. For example, what advice would you give to a user who is at risk of diabetes?

[1183] By feeding this prompt into a generative AI model, we can understand how the system processes the data and provides specific health advice.

[1184] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1185] Step 1: Collecting genetic information

[1186] A user collects a sample using a genetic testing kit, enters genetic information digitally through the kit's application, and transmits it to a server via a terminal.

[1187] Specific behavior:

[1188] The user uses a cotton swab to collect cells from inside the mouth.

[1189] Launch the application and scan or enter your genetic information.

[1190] The device will use Wi-Fi or mobile data to send genetic information to a server.

[1191] Input: Gene sample

[1192] Output: Genetic information in digital form

[1193] Step 2: Collecting daily life data

[1194] The device (smartwatch or mobile app) collects data about the user's daily life and automatically uploads it to a server.

[1195] Specific behavior:

[1196] The smartwatch measures the user's steps and exercise volume.

[1197] The food recording app inputs the user's meal details.

[1198] A sleep tracker analyzes your sleep patterns.

[1199] The device periodically uploads this data to the server.

[1200] Input: User's daily living activities

[1201] Output: Digital daily life data

[1202] Step 3: Collecting emotion data

[1203] The device analyzes the user's voice, facial expressions, and behavioral patterns, acquires emotional data, and sends it to the server.

[1204] Specific behavior:

[1205] The smartphone camera captures and analyzes the user's facial expressions.

[1206] It uses speech recognition technology to analyze the content and tone of what a user is saying.

[1207] The terminal transmits this emotion data to the server.

[1208] Input: User's voice, facial expressions, and actions

[1209] Output: Digital emotional data

[1210] Step 4: Integrate and send data

[1211] The genetic information, daily life data, and emotional data collected by the device are sent to a server, which then stores them in a centralized integrated database.

[1212] Specific behavior:

[1213] The device sends each piece of data to the server using Wi-Fi or mobile data.

[1214] The server receives all the data, organizes it and consolidates it based on the personal identification code (user ID).

[1215] Input: Genetic information, daily life data, emotional data

[1216] Output: Integrated database

[1217] Step 5: Data analysis

[1218] An artificial intelligence engine within the server analyzes the integrated data and assesses the user's genetic risks, health trends and emotional state.

[1219] Specific behavior:

[1220] The AI ​​engine extracts risk factors from genetic data.

[1221] Analyze health trends based on daily life data.

[1222] Evaluate stress levels and motivation from emotional data.

[1223] Input: Integrated database

[1224] Output: Analysis results (genetic risk, health trends, emotional state)

[1225] Step 6: Generate a health plan

[1226] The server's AI engine generates a personalized health plan based on the analysis results.

[1227] Specific behavior:

[1228] The AI ​​engine generates specific guidelines for action, such as "30 minutes of aerobic exercise every day."

[1229] It suggests relaxation exercises based on the user's stress level.

[1230] Input: Analysis results

[1231] Output: personalized health plan

[1232] Step 7: Providing VR / AR content

[1233] The server creates VR / AR content based on the generated health plan and provides it to the user via their device, where the user can experience it.

[1234] Specific behavior:

[1235] Create VR / AR content using dedicated software.

[1236] The device delivers VR / AR content to the user.

[1237] Users experience the content using a smartphone or VR device.

[1238] Enter: personalized health plans.

[1239] Output: VR / AR content experience

[1240] Step 8: Gather feedback and refine your plan

[1241] The device records the user's progress and reactions and sends them to a server, which analyzes the feedback data and adjusts and updates the health plan.

[1242] Specific behavior:

[1243] The device records the user's exercise log, meal log, and emotional changes.

[1244] The server analyzes the feedback data and adjusts the health plan.

[1245] Input: User progress and feedback

[1246] Output: Coordinated Health Plan

[1247] (Application example 2)

[1248] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1249] Conventional health management systems generate health plans based solely on genetic information and daily life data, failing to fully consider the user's emotional state and motivation, making it difficult to effectively improve their health. Furthermore, they lacked personalized product recommendations and interactive experiences, resulting in low user engagement. This led to a decline in users' motivation to continue managing their health, making it difficult to effectively improve their health.

[1250] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1251] In this invention, the server includes: means for collecting personal genetic information; means for collecting nutritional intake data, physical activity data, and sleep pattern data; means for collecting emotional data from voice, facial expressions, and behavioral patterns; means for integrating and analyzing the genetic information, the daily life data, and the emotional data; means for generating a personalized health plan based on the analysis results; means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan; and means for recommending products in a virtual store based on the health plan. This makes it possible to provide a personalized health plan that takes into account the user's genetic risks and health trends, as well as their emotional state and motivation, and further makes it possible to more effectively support the user's health improvement by recommending appropriate products in the virtual store.

[1252] "Genetic information" is data that indicates the genetic characteristics of a user, and is information obtained through DNA analysis.

[1253] "Daily life data" refers to data relating to the user's daily activities and lifestyle habits, including information on nutritional intake, physical activity, sleep patterns, and the like.

[1254] "Emotion data" is data obtained from the user's voice, facial expressions, and behavioral patterns, and is information that indicates the user's emotional state, such as stress level and motivation.

[1255] "Integration" means bringing together multiple different data into a single database and managing them in a correlated manner.

[1256] "Analysis" is an information processing activity that uses collected data to clarify its content and meaning.

[1257] A "health plan" is a plan that includes specific, personalized actions and advice to improve a user's health.

[1258] "Virtual reality" is a technology that uses computer technology to provide users with virtual environments and experiences that do not exist in reality.

[1259] "Augmented reality" is a technology that displays digital information overlaid on visual information from the real world, enhancing the user's experience.

[1260] An "interactive health improvement experience" refers to activities and training for improving health that are provided in a way that allows users to actively participate, and that enhances effectiveness through two-way interaction.

[1261] A "virtual store" is a virtual store accessible via the Internet, an online platform where users can browse, select and purchase products in a digital environment.

[1262] "Product recommendation" refers to selecting and suggesting specific products that match the user's needs and preferences.

[1263] This invention is a system that integrates and analyzes an individual's genetic information, daily life data, and emotional data to provide a personalized health plan to the user. A specific implementation method is described below.

[1264] Data collection methods

[1265] First, the user collects a sample using a genetic test kit and digitally enters their genetic information through a dedicated application. This genetic information is then sent to a server from a device such as a smartphone. Furthermore, the user's daily life data (nutritional intake, physical activity, and sleep pattern data) is continuously collected via a smartwatch or mobile application, and this data is also automatically uploaded to the server. Additionally, the device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. This emotional data includes the user's motivation and stress level and is then sent to the server.

[1266] Data Integration Methods

[1267] The server checks the consistency of the received genetic information, daily life data, and emotional data, and integrates them. All data is linked based on a personal identification code (user ID) and stored in an integrated database. The hardware used is compatible with AWS (Amazon Web Services) databases.

[1268] Data Analysis Methods

[1269] An artificial intelligence engine on the server analyzes the integrated data to assess the user's genetic risk, health trends, and emotional state. For example, this is done using Python and TensorFlow. If the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results. The system also takes into account the user's stress level and motivation based on emotional data.

[1270] Health plan generator

[1271] Based on the analysis results, the server's AI engine generates a personalized health plan. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, in addition to advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it may also include advice such as "add relaxation exercises on days when you are under high stress."

[1272] Means of providing VR / AR experiences

[1273] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user can experience the provided content using their smartphone or VR device. For example, they can use an Oculus Quest to experience an AR trainer that guides exercise, or a relaxation program that reduces stress based on emotional data.

[1274] Feedback and Adjustments

[1275] The device records the user's progress and reactions and sends them to the server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health and emotional status in real time and increases engagement.

[1276] Examples and prompts

[1277] As a concrete example, let's consider the case where User B uses this system. User B provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. In addition, emotional data is obtained from User B's voice and facial expressions. The server integrates this data, and an artificial intelligence engine analyzes it, revealing that User B has a high stress level and is at risk of diabetes. The generated health plan includes daily exercise and a balanced diet, as well as relaxation exercises to reduce stress. This plan is provided as VR content, and User B experiences interactive relaxation training within the VR environment. User B provides feedback during and after the plan, and the server uses that data to adjust the health plan and continuously provide optimal improvement guidelines.

[1278] Example prompt sentence:

[1279] "Generate a personalized health plan and related product recommendations based on the user's genetic information, daily life data (activity, nutrition, sleep patterns), and emotional data (facial expressions, voice). The health plan should include specific exercise instructions, dietary suggestions, and advice on stress reduction. Related products should suggest fitness equipment, supplements, and relaxation tools available for purchase in a virtual store."

[1280] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1281] Step 1:

[1282] Users use a genetic test kit to collect a genetic sample and input the results into the application, which then sends the data from a device such as a smartphone to a server.

[1283] Input: Genetic sample results

[1284] Output: Sending genetic information to the server

[1285] Step 2:

[1286] The device (smartwatch or mobile application) continuously collects data on the user's daily life (nutritional intake data, physical activity data, sleep pattern data) and automatically uploads this data to a server.

[1287] Input: Daily life data (exercise, nutrition, sleep data)

[1288] Output: Sending daily life data to the server

[1289] Step 3:

[1290] The device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. It uses voice recognition and facial expression analysis algorithms to determine the user's emotional state. This data is then sent to the server.

[1291] Input: Voice data, facial expression data, behavior patterns

[1292] Output: Sending emotion data to the server

[1293] Step 4:

[1294] The server integrates the received genetic information, daily life data, and emotion data. Using Python and AWS databases, the data is integrated and stored in a database. This process verifies the integrity of the data and generates a single linked dataset.

[1295] Input: Genetic information, daily life data, emotional data

[1296] Output: A consolidated dataset

[1297] Step 5:

[1298] The AI ​​engine on the server analyzes the integrated data set to assess the user's genetic risk, health trends, and emotional state. It uses AI tools such as TensorFlow to perform the analysis and then predicts health risks and evaluates emotional state based on the results.

[1299] Input: Integrated dataset

[1300] Output: Analysis results (health risk assessment, emotional state assessment)

[1301] Step 6:

[1302] The server's AI engine generates a personalized health plan based on the analysis results. This health plan includes specific guidelines for action and takes into account the user's emotional state. For example, instructions include "30 minutes of aerobic exercise every day," "eat at least three servings of vegetables per week," and "add relaxation exercises on days when you're under high stress."

[1303] Input: Analysis results

[1304] Output: personalized health plan

[1305] Step 7:

[1306] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user experiences the content using a VR device such as Oculus Quest. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction.

[1307] Enter: personalized health plans.

[1308] Output: VR / AR content

[1309] Step 8:

[1310] The device records the user's progress and reactions and sends them to a server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data, evaluates whether the health plan is appropriate, and adjusts the health plan accordingly, if necessary.

[1311] Input: User feedback data

[1312] Output: Coordinated Health Plan

[1313] The above are the processing steps of the system that realizes the application example.

[1314] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1315] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1316] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1317] [Fourth embodiment]

[1318] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1319] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1320] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1321] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1322] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1323] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1324] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1325] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1326] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1327] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1328] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1329] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1330] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1331] The present invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data, and is implemented as follows.

[1332] Data collection methods

[1333] First, the user collects a sample using a genetic test kit to obtain genetic information. The device (smartphone app) digitally inputs this genetic information and sends it to a server. The device also continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application. This data is periodically sent from the device to a cloud server.

[1334] Data Integration Methods

[1335] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[1336] Data Analysis Methods

[1337] An artificial intelligence engine on the server analyzes the data in the integrated database to assess the user's genetic risk and health trends. For example, if a user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[1338] Health plan generator

[1339] Based on the analysis results, the server's AI engine generates a personalized health plan with specific action items and recommendations tailored to the user's needs, such as "do 30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[1340] Means of providing VR / AR experiences

[1341] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their own VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutritional information.

[1342] Feedback and Adjustments

[1343] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[1344] Specific examples

[1345] As a concrete example, let's consider the case where User A uses this system. User A provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and after analysis by an artificial intelligence engine, it is determined that User A is at risk of diabetes. As a result, a health plan including daily aerobic exercise and calorie restriction is created. This plan is provided as VR content, and User A can receive interactive exercise guidance within the VR environment. As User A implements the plan and provides feedback, the server adjusts the plan based on that data, continuously providing optimal health improvements.

[1346] The above is an embodiment of the present invention.

[1347] The processing flow will be explained below.

[1348] Step 1:

[1349] A user collects a sample using a genetic testing kit and digitally inputs genetic information through an application provided with the kit, which then transmits the input genetic information from the device to a server.

[1350] Step 2:

[1351] The device continuously collects daily life data through the user's smartwatch or mobile application, including nutritional intake data, physical activity data, and sleep pattern data, which is then automatically uploaded to a server.

[1352] Step 3:

[1353] The server checks the consistency of the received genetic information and daily life data. If there is missing or inconsistent data, the server notifies the user and requests that the data be resent.

[1354] Step 4:

[1355] The server stores verified genetic information and daily life data in an integrated database, which is linked based on a personal identification code (user ID).

[1356] Step 5:

[1357] An artificial intelligence engine on the server analyzes the integrated data, assessing genetic risks and health trends and providing a specific diagnosis for each user. For example, it may say, "User A is at high risk for type 2 diabetes."

[1358] Step 6:

[1359] The server's AI engine generates a personalized health plan based on the analysis results, which includes specific guidelines for action, such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[1360] Step 7:

[1361] The server then creates VR / AR content based on the generated health plan, which can be interactively experienced by users, such as exercise guides in VR or meal planners using AR.

[1362] Step 8:

[1363] The device provides the created VR / AR content to the user, who then experiences the content using their smartphone or VR device.

[1364] Step 9:

[1365] As users follow their health plan, they input feedback via the device, including the results of their exercise and diet, and changes in their health status.

[1366] Step 10:

[1367] The device sends the collected feedback data to a server, which analyzes this feedback and adjusts the health plan as needed.

[1368] Step 11:

[1369] The server then generates an adjusted health plan and provides it to the user via the device, thereby optimizing the user's health status in real time.

[1370] The above is the specific processing flow of the program.

[1371] Example 1

[1372] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1373] For health management, there is a need for a system that provides more accurate, personalized health plans by integrating and analyzing not only an individual's genetic information but also their daily life data. However, there are challenges in that the integrated analysis of genetic information and daily life data has not been sufficiently carried out, and there is a lack of a mechanism for providing real-time feedback and adjustments on the effectiveness of the health plans provided.

[1374] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1375] In this invention, the server includes means for collecting an individual's genetic information, means for collecting nutritional intake data, physical activity data, and sleep pattern data, means for integrating and analyzing the genetic information and the daily life data, means for generating a personalized health plan based on the analysis results, means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan, means for recording the implementation status and feedback of the health plan and transmitting it to the server, and means for analyzing the feedback data and reevaluating and adjusting the health plan, thereby enabling the provision of a highly accurate personalized health plan and the ability to provide feedback on its effectiveness and adjust it in real time.

[1376] "Genetic information" is data based on an individual's DNA that indicates genetic characteristics and risks.

[1377] "Nutrition intake data" refers to information about the foods and nutrients that an individual consumes in their daily lives.

[1378] "Physical activity data" refers to information relating to the amount and pattern of exercise in an individual's daily life.

[1379] "Sleep pattern data" is information about an individual's sleep duration, sleep quality, and sleep cycle.

[1380] "Synthesis" is the process of combining different types of data into a single, coherent data set.

[1381] "Analysis" is the process of analyzing collected data and extracting meaningful information and patterns.

[1382] A "health plan" is a written plan that includes specific action guidelines and recommendations for improving an individual's health.

[1383] "Virtual reality" refers to a virtual environment or experience created using computer technology.

[1384] "Augmented reality" is a technology that overlays computer-generated images and information on real-world scenes.

[1385] An "interactive health improvement experience" is a health improvement program designed to allow users to actively participate, often using virtual reality or augmented reality.

[1386] "Feedback" refers to the data and opinions obtained after a user implements a health plan, and is information used to reevaluate and adjust the plan.

[1387] "Reevaluation" is the process of reassessing the effectiveness of current health plans based on collected feedback data and making adjustments as necessary.

[1388] "Adjustment" is the process of modifying and improving existing plans and systems based on evaluation results and feedback.

[1389] This invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data. The system is implemented as follows:

[1390] Data collection

[1391] First, the user collects a sample using a genetic test kit to obtain genetic information. The device (smartphone app) digitally inputs this genetic information and sends it to a server. The device also continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application. This data is periodically sent from the device to a cloud server.

[1392] Data Integration

[1393] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[1394] Data analysis

[1395] The server's AI engine analyzes the data in the integrated database to assess the user's genetic risk and health trends. For example, if the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[1396] Health plan generation

[1397] Based on the analysis, the server's AI engine generates a personalized health plan with specific action items and recommendations tailored to the user's needs, such as "do 30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week."

[1398] Providing VR / AR experiences

[1399] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutrition information.

[1400] Feedback and Adjustments

[1401] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[1402] Specific examples

[1403] For example, when User A uses this system, the process goes as follows: User A provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and the AI ​​engine analyzes it to determine whether User A is at risk of diabetes. The generated health plan includes instructions for daily aerobic exercise and calorie restriction and is provided as VR content. When User A implements the plan and provides feedback, the server reevaluates and adjusts the plan based on that data, continuously providing User A with optimal health improvements.

[1404] Prompt Sentence Examples

[1405] Below is an example of a prompt sentence to be input to the generative AI model of this system.

[1406] Describe a system that integrates a user's genetic information and daily life data to generate a personalized health plan. Illustrate how a health plan is created and provided to a user at risk for diabetes.

[1407] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1408] Step 1:

[1409] A user collects a sample (e.g., saliva) using a genetic test kit and mails it to a testing institution. The genetic information obtained from the testing institution is provided in digital format and entered into a terminal (smartphone app). The terminal sends this input data (genetic information) to a server. The input is the user ID and genetic information, and the output is the digital genetic information sent to the server.

[1410] Step 2:

[1411] The device continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) using a smartwatch or mobile application. For example, the smartwatch records heart rate and exercise volume, and the mobile application inputs the user's dietary information. This data (input) is periodically sent to a server (output) and stored on the server.

[1412] Step 3:

[1413] The server checks the integrity of all received data. Specifically, it checks the format of the genetic information and checks for abnormal values ​​in the daily life data. The input is the genetic information and daily life data sent from the device, and the output is the verified integrated data. This data is stored in the server's integrated database.

[1414] Step 4:

[1415] The AI ​​engine on the server analyzes the data in the integrated database. The input data is genetic information and daily life data, and the output is the results of the user's genetic risk assessment and health trend analysis. For example, it determines whether or not a person is at high risk for diabetes. These analyses are performed using machine learning algorithms.

[1416] Step 5:

[1417] Based on the analysis results, the server's AI engine generates a personalized health plan. The input is the analysis results by the AI ​​engine, and the output is a health plan including specific action items (e.g., "30 minutes of aerobic exercise every day" and "eat at least three vegetables per week"). This plan is customized based on the user's lifestyle and genetic risk.

[1418] Step 6:

[1419] The server generates VR / AR content based on the generated health plan and provides it to the user through the device. The input is the generated health plan, and the output is interactive content that can be displayed on a VR device or smartphone. For example, it includes an AR trainer for exercise guidance and a meal planner for nutritional information.

[1420] Step 7:

[1421] The device records the user's progress and feedback. For example, the user enters the results of implementing a health plan and their thoughts about it into the app. The input is the user's feedback data, and the output is a progress record including the feedback. This data is sent from the device to the server.

[1422] Step 8:

[1423] The server analyzes the collected feedback data and evaluates whether the health plan is appropriate. If necessary, it reevaluates the health plan and generates a new, adjusted plan. The input is the feedback data and the current health plan, and the output is the adjusted health plan. The updated plan is again provided to the user via the terminal.

[1424] (Application example 1)

[1425] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1426] In today's world, personal health management is becoming an increasingly important issue, and there is a demand for providing personalized health plans that utilize genetic information and daily life data. However, conventional systems struggle to efficiently integrate and analyze genetic information and daily life data, and lack the means to interactively provide personalized health improvement content in real time. Furthermore, the generation of prompts that provide information tailored to each user's needs when generating individual health plans is not automated, making it difficult to provide personalized services.

[1427] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1428] In this invention, the server includes: means for collecting an individual's genetic information; means for collecting nutritional intake data, physical activity data, and sleep pattern data; means for integrating and analyzing the genetic information and daily life data; means for generating a personalized health plan based on the analysis results; means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan; and means for generating individual prompts using a generative AI model when generating the health plan. This enables efficient integration and analysis of genetic information and daily life data, and personalized health improvement content to be provided interactively in real time. Furthermore, automatic generation of individual prompts tailored to the needs of each user enables the provision of even more advanced personalized services.

[1429] "Personal genetic information" is data that indicates the genetic characteristics and risks of individual users.

[1430] "Nutrition intake data" is information about the foods and nutrients that a user takes in on a daily basis.

[1431] "Physical activity data" is information relating to the amount of exercise and activity level of the user in their daily life.

[1432] "Sleep pattern data" is information relating to the user's sleep duration, quality, and patterns.

[1433] "Analysis means" refers to technologies such as artificial intelligence engines that integrate collected genetic information with daily life data to assess the user's health status and risks.

[1434] A "health plan" is a plan that includes specific advice and recommendations for individualized health improvement based on the results of the analysis.

[1435] "Virtual reality" is a technology that allows users to have interactive experiences in a virtual space.

[1436] "Augmented reality" is a technology that overlays digital information and objects onto the real world.

[1437] An "interactive health improvement experience" is an experience in which users actively participate and interact with the experience through virtual reality or augmented reality to improve their health.

[1438] A "generative AI model" is a model that uses artificial intelligence to analyze data and generate appropriate output.

[1439] A "prompt" is a sentence output by a generative AI model that contains instructions or questions designed to elicit a specific action or response.

[1440] This invention is an AI-driven health coaching system that integrates and analyzes personal genetic information and daily life data, with the aim of helping users effectively improve their health.

[1441] Data collection methods

[1442] First, the user collects a genetic sample using a genetic test kit and digitally inputs the information into a device (smartphone app). The device then transmits the genetic information to a server. Furthermore, the device also continuously collects daily life data (nutritional intake, physical activity, and sleep patterns) via a smartwatch or mobile app, and periodically transmits this data to a cloud-based server.

[1443] Data Integration Methods

[1444] The server checks the integrity of all received data and integrates the genetic information with daily life data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[1445] Data Analysis Methods

[1446] An artificial intelligence engine (e.g., TensorFlow) on the server analyzes the data in the integrated database. The analysis is performed to evaluate the user's genetic risk and health trends. For example, if the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results.

[1447] Health plan generator

[1448] Based on the analysis results, the server's AI engine generates a personalized health plan, which includes specific action items and recommendations tailored to the user's needs, such as "30 minutes of aerobic exercise every day" and "eat at least three vegetables per week."

[1449] Means of providing VR / AR experiences

[1450] The server generates VR / AR content based on the generated health plan and provides it to the user through the terminal. The user can use their own VR device or smartphone to experience this interactive health improvement experience. Examples include an AR trainer for exercise guidance and an interactive meal planner for nutritional information.

[1451] Feedback and Adjustments

[1452] The device records the user's progress and reactions and sends them to the server. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health status in real time and increases engagement.

[1453] Prompt generation method

[1454] When generating a health plan, the server uses a generative AI model to generate personalized prompts that provide information and instructions tailored to the user's needs and circumstances. For example, prompts such as "Did you achieve your exercise goal today?" or "Are you satisfied with your meal plan this week?"

[1455] Specific examples

[1456] When User A uses this system, he or she provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. The server integrates this data, and after analysis by an artificial intelligence engine, it determines that User A is at risk of diabetes. As a result, a health plan including daily aerobic exercise and calorie restriction is created. This plan is provided as VR content, and User A can receive interactive exercise guidance within the VR environment. As User A implements the plan and provides feedback, the server adjusts the plan based on that data, continuously providing optimal health improvements.

[1457] Prompt Sentence Examples

[1458] "Did you achieve your exercise goal today?"

[1459] "Are you happy with your meal plan this week?"

[1460] "How was your sleep quality?"

[1461] In this way, users can enjoy a continuous, personalized health improvement experience.

[1462] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1463] Step 1:

[1464] Users use a genetic testing kit to collect genetic samples and enter the genetic information into a device (smartphone app).

[1465] Input: Gene sample, user ID

[1466] Output: Genetic information in digital form

[1467] Specific behavior:

[1468] The user collects a sample using a genetic testing kit.

[1469] The genetic information is read within the app and transferred to the screen.

[1470] Step 2:

[1471] The device transmits the genetic information in digital form to a server.

[1472] Input: Digital genetic information, user ID

[1473] Output: Genetic information is stored on the server.

[1474] Specific behavior:

[1475] The app combines the genetic information with the user ID and sends it to the server.

[1476] Step 3:

[1477] The device continuously collects daily life data (nutritional intake data, physical activity data, sleep pattern data) via a smartwatch or mobile application and periodically transmits it to a server.

[1478] Input: User's daily life data (nutrition, physical activity, sleep), user ID

[1479] Output: Daily life data is saved on the server.

[1480] Specific behavior:

[1481] Smartwatches and apps automatically record daily life data.

[1482] The terminal sends the collected data to the server.

[1483] Step 4:

[1484] The server checks the consistency of the received genetic information and daily life data and integrates them.

[1485] Input: Genetic information, daily life data, user ID

[1486] Output: Integrated data stored in an integrated database

[1487] Specific behavior:

[1488] The server associates genetic information with daily life data in a database.

[1489] Check the integrity of the data format and save it in the integrated database.

[1490] Step 5:

[1491] An artificial intelligence engine within the server analyzes the integrated data to assess the user's genetic risks and health trends.

[1492] Input: Integrated data in the integrated database

[1493] Output: Analysis results (health risks, health trends)

[1494] Specific behavior:

[1495] The AI ​​engine processes and analyzes the integrated data.

[1496] Evaluate health risks and trends and generate analytical results.

[1497] Step 6:

[1498] Based on the analysis results, the server's AI engine generates a personalized health plan.

[1499] Input: Analysis results, user ID

[1500] Output: A health plan with specific action items and recommendations

[1501] Specific behavior:

[1502] The AI ​​engine will create the optimal health plan based on the analysis results.

[1503] Step 7:

[1504] The server uses a generative AI model to generate personalized prompts related to the health plan.

[1505] Input: Health plan, user ID

[1506] Output: prompt statement

[1507] Specific behavior:

[1508] Parse the health plan and generate the appropriate prompt.

[1509] For example: "Did you achieve your exercise goal today?", "Are you happy with your meal plan this week?"

[1510] Step 8:

[1511] The server generates VR / AR content based on the health plan and provides it to the user through the device.

[1512] Input: Health plan, prompt, user ID

[1513] Output: VR / AR content

[1514] Specific behavior:

[1515] Create VR / AR content and distribute it to devices.

[1516] Examples: interactive exercise guides, meal planners, etc.

[1517] Step 9:

[1518] The device records the user's progress and reactions and sends them to the server.

[1519] Input: User progress data, feedback

[1520] Output: Progress data, feedback sent to the server.

[1521] Specific behavior:

[1522] Log user actions and feedback.

[1523] Sends progress data to the server.

[1524] Step 10:

[1525] The server analyzes the progress data and feedback and adjusts the health plan accordingly.

[1526] Inputs: progress data, feedback, existing health plan

[1527] Output: Coordinated Health Plan

[1528] Specific behavior:

[1529] Analyze progress data and generate a plan with appropriate modifications.

[1530] The updated plan will be delivered to your device.

[1531] Through these steps, users can enjoy a continuously personalized health improvement experience.

[1532] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1533] The present invention is an AI-driven health coaching system that integrates and analyzes personal genetic information, daily life data, and user emotional data, and is implemented as follows.

[1534] Data collection methods

[1535] First, the user collects a sample using a genetic testing kit and digitally inputs their genetic information through the app that comes with the kit. The input genetic information is then sent from the device to a server. The device also continuously collects daily life data (nutritional intake, physical activity, and sleep patterns) via a smartwatch or mobile app. This data is automatically uploaded to the server.

[1536] Furthermore, the device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data, including the user's motivation and stress level, which is then sent to the server.

[1537] Data Integration Methods

[1538] The server checks the consistency of the received genetic information, daily life data, and emotional data, and then integrates these data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[1539] Data Analysis Methods

[1540] An artificial intelligence engine on the server analyzes the integrated data to assess the user's genetic risk, health trends, and emotional state. For example, if a user is at risk for diabetes, a specific health plan is generated based on the risk assessment results. The system also takes into account the user's stress level and motivation based on emotional data.

[1541] Health plan generator

[1542] Based on the analysis results, the server's AI engine generates a personalized health plan. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, in addition to advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it may also include advice such as "add relaxation exercises on days when you are under high stress."

[1543] Means of providing VR / AR experiences

[1544] The server creates VR / AR content based on the generated health plan and provides it to the user via the device. The user experiences the provided content using their smartphone or VR device. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction based on emotional data.

[1545] Feedback and Adjustments

[1546] The device records the user's progress and reactions and sends them to the server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health and emotional status in real time and increases engagement.

[1547] Specific examples

[1548] As a concrete example, let's consider the case where User B uses this system. User B provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. In addition, emotional data is obtained from User B's voice and facial expressions. The server integrates this data, and an artificial intelligence engine analyzes it, revealing that User B has a high stress level and is at risk of diabetes. The generated health plan includes daily exercise and a balanced diet, as well as relaxation exercises to reduce stress. This plan is provided as VR content, and User B experiences interactive relaxation training within the VR environment. User B provides feedback during and after the plan, and the server uses that data to adjust the health plan and continuously provide optimal improvement guidelines.

[1549] The above is an embodiment of the present invention.

[1550] The processing flow will be explained below.

[1551] Step 1:

[1552] A user collects a sample using a genetic testing kit and digitally inputs genetic information through an application provided with the kit, which then transmits the input genetic information from the device to a server.

[1553] Step 2:

[1554] The device continuously collects daily life data through the user's smartwatch or mobile application, including nutritional intake data, physical activity data, and sleep pattern data, which is then automatically uploaded to a server.

[1555] Step 3:

[1556] The device analyzes the user's voice, facial expressions, and behavioral patterns to acquire emotional data, including the user's motivation and stress level, and transmits the acquired emotional data to a server.

[1557] Step 4:

[1558] The server checks the consistency of genetic information, daily life data, and emotional data, checking for inconsistencies or missing data, and notifying the user if necessary.

[1559] Step 5:

[1560] The server stores the verified data in a consolidated database, where the data is linked based on a personal identification code (user ID).

[1561] Step 6:

[1562] The server's artificial intelligence engine analyzes the integrated data. Specifically, it evaluates genetic risk, health trends, and emotional state, and makes a specific diagnosis for each user. For example, it might say, "User B is in a high stress state and has a high genetic risk of diabetes."

[1563] Step 7:

[1564] The server's AI engine generates a personalized health plan based on the analysis results. The health plan includes specific guidelines for action and takes emotional data into consideration. For example, in addition to basic advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it also includes specific suggestions such as "add relaxation exercises on days when you're under high stress."

[1565] Step 8:

[1566] The server then creates VR / AR content based on the generated health plan, which users can experience interactively, such as an exercise guide in VR or a meal planner using AR.

[1567] Step 9:

[1568] The device provides the created VR / AR content to the user, who then experiences the content using their smartphone or VR device.

[1569] Step 10:

[1570] The device provides feedback on the results of activities and emotional responses as the user follows a health plan, including the type and duration of exercise, dietary content, and changes in emotional state.

[1571] Step 11:

[1572] The device sends the collected feedback data to a server, which analyzes the feedback and evaluates whether the health plan is appropriate.

[1573] Step 12:

[1574] The server adjusts the health plan as needed and generates an updated version, which is then provided to the user via the device again, optimizing the user's health and emotional state in real time.

[1575] The above is the specific processing flow of the program of the present invention combined with the emotion engine.

[1576] Example 2

[1577] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1578] Although there are systems that comprehensively integrate an individual's genetic information, daily life data, and emotional data to provide personalized health plans, many of them lack the ability to integrate and analyze data in a comprehensive manner, making it difficult to provide real-time feedback and adjustments. Another issue is that it is difficult to provide health plans that take into account the user's emotional state.

[1579] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1580] In this invention, the server includes: means for collecting personal genetic information, means for collecting nutritional intake data, physical activity data, and sleep pattern data, means for analyzing the user's voice, facial expressions, and behavioral patterns to obtain emotional data, means for transmitting the genetic information, daily life data, and emotional data to the server and integrating these data, means for analyzing the integrated data using an artificial intelligence engine to evaluate genetic risks, health trends, and emotional states, means for generating a personalized health plan based on the analysis results, means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan, and means for collecting the user's progress and reactions as feedback and adjusting the health plan, thereby enabling the provision of a comprehensive health plan based on the user's genetic risks, daily life data, and emotional states.

[1581] "Individual genetic information" refers to data that indicates an individual's biological characteristics obtained through genetic testing.

[1582] "Nutrient intake data" refers to information about the foods and their nutritional components that a user consumes in their daily lives.

[1583] "Physical activity data" is information about the exercise and daily physical activity of the user.

[1584] "Sleep pattern data" is data that indicates information related to the user's sleep state, sleep duration, and sleep quality.

[1585] "Emotional data" refers to information such as the user's psychological state, motivation, stress level, etc., analyzed from the user's voice, facial expressions, and behavior.

[1586] "Means of integration" refers to methods or technologies for centrally collecting, linking, and organizing various types of data.

[1587] An "artificial intelligence engine" is software or a system that analyzes large amounts of data and replicates human knowledge and pattern recognition.

[1588] "Genetic risk" is a risk assessment that indicates the likelihood of developing a particular disease or health problem based on genetic information.

[1589] "Health trends" is information that indicates trends regarding an individual's health condition and lifestyle habits based on daily life data.

[1590] "Personalized health plan" refers to a course of action or plan proposed for optimal health maintenance or improvement based on a user's individual genetic information, daily life data, and emotional data.

[1591] "Virtual reality" is a technology that uses computer technology to create a virtual 3D environment in which users can interact.

[1592] "Augmented reality" is a technology that overlays digital information and 3D objects onto a real environment, providing users with an experience that blends reality and virtuality.

[1593] "Means for collecting feedback" refers to methods or techniques for collecting progress and reactions from users and using them to evaluate and improve the system.

[1594] A "means for adjusting a health plan" is a method or technology for analyzing collected feedback data and revising the health plan to best suit the user.

[1595] This invention is a system that provides a health plan by integrating and analyzing an individual's genetic information, daily life data, and emotional data, and specific embodiments thereof will be described below.

[1596] Collection of genetic information

[1597] A user collects their own sample using a genetic testing kit. This sample is then digitally entered through an application that comes with the kit. The entered genetic information is then sent from the device to a server. This process involves the use of a genetic analysis kit and application.

[1598] Collection of daily life data

[1599] The device (e.g., smartwatch or mobile app) collects data on the user's daily life, including nutritional intake data, physical activity data, and sleep pattern data, and automatically uploads this data to a server. Specifically, the smartwatch measures exercise volume and sleep patterns, and the food recording app records nutritional intake data.

[1600] Collecting Emotional Data

[1601] The device (e.g., a smartphone or special sensor) analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. This data, including the user's motivation and stress level, is sent to a server. Speech recognition software and facial expression recognition algorithms are used.

[1602] Data integration and transmission

[1603] The device automatically sends all data to the server, which receives and centrally integrates this data. All data is linked based on a personal identification code (user ID) and stored in an integrated database.

[1604] Data analysis

[1605] An artificial intelligence engine on the server analyzes the integrated data. The analysis is carried out to assess the user's genetic risk, health trends, and emotional state. For example, genetic data and lifestyle data are used to analyze diabetes risk. The AI ​​engine analyzes this data and assesses health risks.

[1606] Health plan generation

[1607] The server's AI engine then generates a personalized health plan based on the analysis results. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, instructions include "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," and also includes instructions such as "add relaxation exercises on days when you're under high stress."

[1608] Providing VR / AR content

[1609] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user experiences this content using a smartphone or VR device. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction based on emotional data.

[1610] Gather feedback and adjust your plan

[1611] The device records the user's progress and reactions and sends them to the server. Feedback includes the results of exercise and diet, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates and adjusts the health plan to determine whether it is appropriate. If necessary, the health plan is revised appropriately and the updated plan is provided to the user via the device.

[1612] Prompt Sentence Examples

[1613] Here are some examples of prompts to input to a generative AI model:

[1614] Prompt: Analyze the health risks of users based on their genetic information, daily life data, and emotional data, and generate a personalized health plan. For example, what advice would you give to a user who is at risk of diabetes?

[1615] By feeding this prompt into a generative AI model, we can understand how the system processes the data and provides specific health advice.

[1616] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1617] Step 1: Collecting genetic information

[1618] A user collects a sample using a genetic testing kit, enters genetic information digitally through the kit's application, and transmits it to a server via a terminal.

[1619] Specific behavior:

[1620] The user uses a cotton swab to collect cells from inside the mouth.

[1621] Launch the application and scan or enter your genetic information.

[1622] The device will use Wi-Fi or mobile data to send genetic information to a server.

[1623] Input: Gene sample

[1624] Output: Genetic information in digital form

[1625] Step 2: Collecting daily life data

[1626] The device (smartwatch or mobile app) collects data about the user's daily life and automatically uploads it to a server.

[1627] Specific behavior:

[1628] The smartwatch measures the user's steps and exercise volume.

[1629] The food recording app inputs the user's meal details.

[1630] A sleep tracker analyzes your sleep patterns.

[1631] The device periodically uploads this data to the server.

[1632] Input: User's daily living activities

[1633] Output: Digital daily life data

[1634] Step 3: Collecting emotion data

[1635] The device analyzes the user's voice, facial expressions, and behavioral patterns, acquires emotional data, and sends it to the server.

[1636] Specific behavior:

[1637] The smartphone camera captures and analyzes the user's facial expressions.

[1638] It uses speech recognition technology to analyze the content and tone of what a user is saying.

[1639] The terminal transmits this emotion data to the server.

[1640] Input: User's voice, facial expressions, and actions

[1641] Output: Digital emotional data

[1642] Step 4: Integrate and send data

[1643] The genetic information, daily life data, and emotional data collected by the device are sent to a server, which then stores them in a centralized integrated database.

[1644] Specific behavior:

[1645] The device sends each piece of data to the server using Wi-Fi or mobile data.

[1646] The server receives all the data, organizes it and consolidates it based on the personal identification code (user ID).

[1647] Input: Genetic information, daily life data, emotional data

[1648] Output: Integrated database

[1649] Step 5: Data analysis

[1650] An artificial intelligence engine within the server analyzes the integrated data and assesses the user's genetic risks, health trends and emotional state.

[1651] Specific behavior:

[1652] The AI ​​engine extracts risk factors from genetic data.

[1653] Analyze health trends based on daily life data.

[1654] Evaluate stress levels and motivation from emotional data.

[1655] Input: Integrated database

[1656] Output: Analysis results (genetic risk, health trends, emotional state)

[1657] Step 6: Generate a health plan

[1658] The server's AI engine generates a personalized health plan based on the analysis results.

[1659] Specific behavior:

[1660] The AI ​​engine generates specific guidelines for action, such as "30 minutes of aerobic exercise every day."

[1661] It suggests relaxation exercises based on the user's stress level.

[1662] Input: Analysis results

[1663] Output: personalized health plan

[1664] Step 7: Providing VR / AR content

[1665] The server creates VR / AR content based on the generated health plan and provides it to the user via their device, where the user can experience it.

[1666] Specific behavior:

[1667] Create VR / AR content using dedicated software.

[1668] The device delivers VR / AR content to the user.

[1669] Users experience the content using a smartphone or VR device.

[1670] Enter: personalized health plans.

[1671] Output: VR / AR content experience

[1672] Step 8: Gather feedback and refine your plan

[1673] The device records the user's progress and reactions and sends them to a server, which analyzes the feedback data and adjusts and updates the health plan.

[1674] Specific behavior:

[1675] The device records the user's exercise log, meal log, and emotional changes.

[1676] The server analyzes the feedback data and adjusts the health plan.

[1677] Input: User progress and feedback

[1678] Output: Coordinated Health Plan

[1679] (Application example 2)

[1680] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1681] Conventional health management systems generate health plans based solely on genetic information and daily life data, failing to fully consider the user's emotional state and motivation, making it difficult to effectively improve their health. Furthermore, they lacked personalized product recommendations and interactive experiences, resulting in low user engagement. This led to a decline in users' motivation to continue managing their health, making it difficult to effectively improve their health.

[1682] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1683] In this invention, the server includes: means for collecting personal genetic information; means for collecting nutritional intake data, physical activity data, and sleep pattern data; means for collecting emotional data from voice, facial expressions, and behavioral patterns; means for integrating and analyzing the genetic information, the daily life data, and the emotional data; means for generating a personalized health plan based on the analysis results; means for providing an interactive health improvement experience through virtual reality or augmented reality based on the health plan; and means for recommending products in a virtual store based on the health plan. This makes it possible to provide a personalized health plan that takes into account the user's genetic risks and health trends, as well as their emotional state and motivation, and further makes it possible to more effectively support the user's health improvement by recommending appropriate products in the virtual store.

[1684] "Genetic information" is data that indicates the genetic characteristics of a user, and is information obtained through DNA analysis.

[1685] "Daily life data" refers to data relating to the user's daily activities and lifestyle habits, including information on nutritional intake, physical activity, sleep patterns, and the like.

[1686] "Emotion data" is data obtained from the user's voice, facial expressions, and behavioral patterns, and is information that indicates the user's emotional state, such as stress level and motivation.

[1687] "Integration" means bringing together multiple different data into a single database and managing them in a correlated manner.

[1688] "Analysis" is an information processing activity that uses collected data to clarify its content and meaning.

[1689] A "health plan" is a plan that includes specific, personalized actions and advice to improve a user's health.

[1690] "Virtual reality" is a technology that uses computer technology to provide users with virtual environments and experiences that do not exist in reality.

[1691] "Augmented reality" is a technology that displays digital information overlaid on visual information from the real world, enhancing the user's experience.

[1692] An "interactive health improvement experience" refers to activities and training for improving health that are provided in a way that allows users to actively participate, and that enhances effectiveness through two-way interaction.

[1693] A "virtual store" is a virtual store accessible via the Internet, an online platform where users can browse, select and purchase products in a digital environment.

[1694] "Product recommendation" refers to selecting and suggesting specific products that match the user's needs and preferences.

[1695] This invention is a system that integrates and analyzes an individual's genetic information, daily life data, and emotional data to provide a personalized health plan to the user. A specific implementation method is described below.

[1696] Data collection methods

[1697] First, the user collects a sample using a genetic test kit and digitally enters their genetic information through a dedicated application. This genetic information is then sent to a server from a device such as a smartphone. Furthermore, the user's daily life data (nutritional intake, physical activity, and sleep pattern data) is continuously collected via a smartwatch or mobile application, and this data is also automatically uploaded to the server. Additionally, the device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. This emotional data includes the user's motivation and stress level and is then sent to the server.

[1698] Data Integration Methods

[1699] The server checks the consistency of the received genetic information, daily life data, and emotional data, and integrates them. All data is linked based on a personal identification code (user ID) and stored in an integrated database. The hardware used is compatible with AWS (Amazon Web Services) databases.

[1700] Data Analysis Methods

[1701] An artificial intelligence engine on the server analyzes the integrated data to assess the user's genetic risk, health trends, and emotional state. For example, this is done using Python and TensorFlow. If the user is at risk for diabetes, a specific health plan is generated based on the risk assessment results. The system also takes into account the user's stress level and motivation based on emotional data.

[1702] Health plan generator

[1703] Based on the analysis results, the server's AI engine generates a personalized health plan. The health plan includes specific guidelines for action and takes the user's emotional state into account. For example, in addition to advice such as "30 minutes of aerobic exercise every day" and "eat at least three servings of vegetables per week," it may also include advice such as "add relaxation exercises on days when you are under high stress."

[1704] Means of providing VR / AR experiences

[1705] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user can experience the provided content using their smartphone or VR device. For example, they can use an Oculus Quest to experience an AR trainer that guides exercise, or a relaxation program that reduces stress based on emotional data.

[1706] Feedback and Adjustments

[1707] The device records the user's progress and reactions and sends them to the server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data and evaluates whether the health plan is appropriate. If necessary, it adjusts the health plan accordingly and provides the updated plan to the user via the device. This process optimizes the user's health and emotional status in real time and increases engagement.

[1708] Examples and prompts

[1709] As a concrete example, let's consider the case where User B uses this system. User B provides genetic information using a genetic test kit and collects daily life data (exercise volume, sleep patterns) from a smartwatch. In addition, emotional data is obtained from User B's voice and facial expressions. The server integrates this data, and an artificial intelligence engine analyzes it, revealing that User B has a high stress level and is at risk of diabetes. The generated health plan includes daily exercise and a balanced diet, as well as relaxation exercises to reduce stress. This plan is provided as VR content, and User B experiences interactive relaxation training within the VR environment. User B provides feedback during and after the plan, and the server uses that data to adjust the health plan and continuously provide optimal improvement guidelines.

[1710] Example prompt sentence:

[1711] "Generate a personalized health plan and related product recommendations based on the user's genetic information, daily life data (activity, nutrition, sleep patterns), and emotional data (facial expressions, voice). The health plan should include specific exercise instructions, dietary suggestions, and advice on stress reduction. Related products should suggest fitness equipment, supplements, and relaxation tools available for purchase in a virtual store."

[1712] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1713] Step 1:

[1714] Users use a genetic test kit to collect a genetic sample and input the results into the application, which then sends the data from a device such as a smartphone to a server.

[1715] Input: Genetic sample results

[1716] Output: Sending genetic information to the server

[1717] Step 2:

[1718] The device (smartwatch or mobile application) continuously collects data on the user's daily life (nutritional intake data, physical activity data, sleep pattern data) and automatically uploads this data to a server.

[1719] Input: Daily life data (exercise, nutrition, sleep data)

[1720] Output: Sending daily life data to the server

[1721] Step 3:

[1722] The device analyzes the user's voice, facial expressions, and behavioral patterns to obtain emotional data. It uses voice recognition and facial expression analysis algorithms to determine the user's emotional state. This data is then sent to the server.

[1723] Input: Voice data, facial expression data, behavior patterns

[1724] Output: Sending emotion data to the server

[1725] Step 4:

[1726] The server integrates the received genetic information, daily life data, and emotion data. Using Python and AWS databases, the data is integrated and stored in a database. This process verifies the integrity of the data and generates a single linked dataset.

[1727] Input: Genetic information, daily life data, emotional data

[1728] Output: A consolidated dataset

[1729] Step 5:

[1730] The AI ​​engine on the server analyzes the integrated data set to assess the user's genetic risk, health trends, and emotional state. It uses AI tools such as TensorFlow to perform the analysis and then predicts health risks and evaluates emotional state based on the results.

[1731] Input: Integrated dataset

[1732] Output: Analysis results (health risk assessment, emotional state assessment)

[1733] Step 6:

[1734] The server's AI engine generates a personalized health plan based on the analysis results. This health plan includes specific guidelines for action and takes into account the user's emotional state. For example, instructions include "30 minutes of aerobic exercise every day," "eat at least three servings of vegetables per week," and "add relaxation exercises on days when you're under high stress."

[1735] Input: Analysis results

[1736] Output: personalized health plan

[1737] Step 7:

[1738] The server creates VR / AR content based on the generated health plan and provides it to the user via their device. The user experiences the content using a VR device such as Oculus Quest. Examples include an AR trainer for exercise guidance and a relaxation program for stress reduction.

[1739] Enter: personalized health plans.

[1740] Output: VR / AR content

[1741] Step 8:

[1742] The device records the user's progress and reactions and sends them to a server. Feedback includes exercise and diet results, changes in health status, and emotional changes. The server analyzes this feedback data, evaluates whether the health plan is appropriate, and adjusts the health plan accordingly, if necessary.

[1743] Input: User feedback data

[1744] Output: Coordinated Health Plan

[1745] The above are the processing steps of the system that realizes the application example.

[1746] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1747] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1748] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1749] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1750] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1751] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1752] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1753] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, motorcycles, and other devices, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1754] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1755] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1756] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1757] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1758] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1759] 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.

[1760] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1761] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1762] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1763] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1764] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1765] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1766] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1767] The following is further disclosed regarding the above embodiment.

[1768] (Claim 1)

[1769] means of collecting genetic information about individuals;

[1770] means for collecting nutritional intake data, physical activity data and sleep pattern data;

[1771] a means for integrating and analyzing the genetic information and the daily life data;

[1772] means for generating a personalized health plan based on the analysis results;

[1773] A system including means for providing an interactive health improvement experience through virtual reality or augmented reality based on said health plan.

[1774] (Claim 2)

[1775] 2. The system of claim 1, wherein the means for collecting daily life data utilizes the user's smartwatch and a mobile application to automatically record data regarding nutritional intake, physical activity, and sleep patterns.

[1776] (Claim 3)

[1777] 10. The system of claim 1, wherein the analysis means uses an artificial intelligence engine to assess genetic risks and health trends and provide personalized advice.

[1778] "Example 1"

[1779] (Claim 1)

[1780] means of collecting genetic information about individuals;

[1781] means for collecting nutritional intake data, physical activity data and sleep pattern data;

[1782] a means for integrating and analyzing the genetic information and the daily life data;

[1783] means for generating a personalized health plan based on the analysis results;

[1784] means for providing an interactive health improvement experience through virtual reality or augmented reality based on said health plan;

[1785] a means for recording the implementation status and feedback of the health plan and transmitting the recording to a server;

[1786] means for analyzing said feedback data and reevaluating and adjusting health plans;

[1787] A system including:

[1788] (Claim 2)

[1789] 2. The system of claim 1, wherein the means for collecting daily life data utilizes the user's smart device to automatically record data regarding nutritional intake, physical activity, and sleep patterns.

[1790] (Claim 3)

[1791] 10. The system of claim 1, wherein the analysis means uses an artificial intelligence system to assess genetic risks and health trends and provide personalized advice.

[1792] "Application Example 1"

[1793] (Claim 1)

[1794] means of collecting genetic information about individuals;

[1795] means for collecting nutritional intake data, physical activity data and sleep pattern data;

[1796] a means for integrating and analyzing the genetic information and the daily life data;

[1797] means for generating a personalized health plan based on the analysis results;

[1798] means for providing an interactive health improvement experience through virtual reality or augmented reality based on said health plan;

[1799] means for generating personalized prompt sentences using a generative AI model when generating the health plan;

[1800] A system including:

[1801] (Claim 2)

[1802] 2. The system of claim 1, wherein the means for collecting daily life data utilizes the user's smartwatch and a mobile application to automatically record data regarding nutritional intake, physical activity, and sleep patterns.

[1803] (Claim 3)

[1804] 10. The system of claim 1, wherein the analysis means uses an artificial intelligence engine to assess genetic risks and health trends and provide personalized advice.

[1805] "Example 2: Combining Emotion Engines"

[1806] (Claim 1)

[1807] means of collecting genetic information about individuals;

[1808] means for collecting nutritional intake data, physical activity data and sleep pattern data;

[1809] A means for analyzing a user's voice, facial expression, and behavioral patterns to acquire emotion data;

[1810] a means for transmitting the genetic information, daily life data, and emotion data to a server and integrating these data;

[1811] means for analyzing the integrated data using an artificial intelligence engine to assess genetic risks, health trends, and emotional states;

[1812] means for generating a personalized health plan based on the analysis results;

[1813] means for providing an interactive health improvement experience through virtual reality or augmented reality based on said health plan;

[1814] A means of collecting feedback on the user's progress and reactions and adjusting the health plan;

[1815] A system including:

[1816] (Claim 2)

[1817] 2. The system of claim 1, wherein the means for collecting daily life data utilizes a user's wearable device and a mobile application to automatically record data regarding nutritional intake, physical activity, and sleep patterns.

[1818] (Claim 3)

[1819] 2. The system of claim 1, wherein the analysis means uses an artificial intelligence engine to assess genetic risks, health trends, and emotional states and provide personalized advice.

[1820] "Application example 2 when combining emotion engines"

[1821] (Claim 1)

[1822] means of collecting genetic information about individuals;

[1823] means for collecting nutritional intake data, physical activity data and sleep pattern data;

[1824] means for collecting emotion data from voice, facial expressions and behavioral patterns;

[1825] a means for integrating and analyzing the genetic information, the daily life data, and the emotion data;

[1826] means for generating a personalized health plan based on the analysis results;

[1827] means for providing an interactive health improvement experience through virtual reality or augmented reality based on said health plan;

[1828] The system includes a means for making product recommendations in a virtual store based on the health plan.

[1829] (Claim 2)

[1830] 2. The system of claim 1, wherein the means for collecting daily life data and emotion data utilizes the user's smartwatch, a mobile application, and facial expression recognition technology to automatically record data regarding nutritional intake, physical activity, sleep patterns, and emotions.

[1831] (Claim 3)

[1832] 2. The system of claim 1, wherein the analysis means uses an artificial intelligence engine to assess genetic risks, health trends, and emotional states and provide personalized advice and product recommendations. [Explanation of symbols]

[1833] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means of collecting genetic information about individuals; means for collecting nutritional intake data, physical activity data and sleep pattern data; a means for integrating and analyzing the genetic information and the daily life data; means for generating a personalized health plan based on the analysis results; A system including means for providing an interactive health improvement experience through virtual reality or augmented reality based on said health plan.

2. 2. The system of claim 1, wherein the means for collecting daily living data utilizes the user's smartwatch and a mobile application to automatically record data regarding nutritional intake, physical activity, and sleep patterns.

3. 10. The system of claim 1, wherein the analysis means uses an artificial intelligence engine to assess genetic risks and health trends and provide personalized advice.

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