system

Abstract

We provide the system. [Solution] A means of generating virtual characters specialized in multiple fields using an image generation engine, A means for obtaining health-related goals and data from the user through the aforementioned virtual character, The server includes means for analyzing the acquired data and personalizing the health support provided by the virtual character, The means for transmitting and displaying the aforementioned personalized support information on a terminal, A means of generating reminders and new challenges based on the user's progress toward their health goals, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, individuals with busy schedules and remote workers find it difficult to have a high awareness of health management and thus tend to lead an unhealthy lifestyle. Also, even when health information is accessible, there is a lack of specific support on how to utilize it to achieve goals. Therefore, there is a need to provide effective health support tailored to individual needs.

Means for Solving the Problems

[0005] To address this challenge, the present invention provides a system that generates virtual characters specialized in different fields using an image generation engine. Through these virtual characters, the system acquires health-related goals and data from users, and by analyzing this data on a server, it provides personalized health support. Furthermore, it displays personalized support information on the user's device and generates reminders and new challenges tailored to health goals, thereby supporting the user's health maintenance.

[0006] An "image generation engine" is a system that creates visual content using advanced algorithms based on user requests.

[0007] A "virtual character" is a visual and interactive artificial being created within a computer that has specific functions and roles.

[0008] "Health support" refers to a set of activities, including information, guidance, and motivation, provided to improve the health of users.

[0009] A "server" is a computing system that provides data and services to multiple users via a network.

[0010] A "terminal" is an electronic device primarily used by users to access information and utilize services.

[0011] A "reminder" is a feature that sends notifications to users based on specific times or conditions to prompt them to take action.

[0012] A "challenge" refers to specific activities or missions provided to support users in achieving their health goals.

[0013] A "health goal" is a specific health-related objective that an individual user sets for themselves to achieve.

[0014] "Personality" is a general term for the characteristics and behavioral styles assigned to a virtual character. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine.

Embodiments for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention realizes a system that provides personalized health support to individual users by utilizing virtual characters generated using an image generation engine. The embodiments are described in detail below.

[0037] The server initializes the image generation engine and creates virtual characters specializing in various health fields. This provides users with characters that address areas such as nutrition, fitness, mental health, stress management, and sleep improvement.

[0038] Users access the application using their device, set health goals, and input daily activity data. This information includes calorie intake, exercise status, mental state, stress levels, and sleep quality. The device then sends this data to the server.

[0039] The server analyzes the received user data and generates health support content tailored to the user's current state and goals. For example, the server personalizes a week's worth of meal plans and exercise programs based on the goals set by the user.

[0040] The generated advice and challenges are sent to the device and presented to the user through a virtual character. The device visually displays this when the user opens the application, and the character provides support by interacting with the user.

[0041] For example, if a user aims to lose weight, the server will suggest calorie management for meals and exercises to increase calorie expenditure. A virtual character will send daily motivational messages and support the user in completing their set health challenges.

[0042] Furthermore, the server monitors the user's progress and provides rewards each time a goal is achieved, thus maintaining motivation. This reward system makes it easier for users to continue managing their health in a gamified way.

[0043] Thus, this invention provides an effective form that offers continuous health support to users and contributes to improving their lifestyles.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The server uses an image generation engine to create virtual characters specialized in each field. This includes visual design and persona creation for each character.

[0047] Step 2:

[0048] Users access the application from their device and enter their profile information and health goals. They also record daily health data such as their diet, exercise level, and sleep duration.

[0049] Step 3:

[0050] The terminal sends the entered user data to the server. The data is encrypted and transmitted securely.

[0051] Step 4:

[0052] The server analyzes the received user data. This analysis includes comparing the user's current health status with their set goals.

[0053] Step 5:

[0054] The server generates personalized health support content based on the analysis results. This content includes daily activity plans, meal suggestions, and guidelines for improving mental health.

[0055] Step 6:

[0056] The generated support content is sent from the server to the device. This may include real-time feedback.

[0057] Step 7:

[0058] The device displays the content through a virtual character so that the user can review it. The character provides advice and challenges through interaction with the user.

[0059] Step 8:

[0060] Users perform their daily activities according to the advice and challenges presented. Furthermore, continuous monitoring is possible by recording progress and achievements on the device.

[0061] Step 9:

[0062] The server tracks user progress and updates content as needed. It may also provide users with new challenges or reminders to help them achieve their goals.

[0063] Step 10:

[0064] When users achieve their goals, they receive rewards through their devices. This helps them stay motivated and continue healthy behaviors in a gamified way.

[0065] (Example 1)

[0066] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0067] In modern society, while awareness of personal health management is increasing, consistent health management is difficult due to busy daily lives. In particular, the lack of personalization tailored to individual needs is a challenge. It has been found that conventional systems have difficulty providing effective health support tailored to individuals, and that maintaining motivation is difficult.

[0068] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0069] In this invention, the server includes means for generating a virtual entity adapted to various domains using an image generation device, means for acquiring health-related objectives and information from a user through the virtual entity, and means for analyzing the acquired information in a processing device and personalizing the health support provided by the virtual entity. This enables personalized health support for individual users and continuous health management.

[0070] An "image generation device" is a device that creates visual information based on input digital instructions, and generates display elements according to specific conditions or themes.

[0071] A "virtual entity" is a character or agent constructed digitally that interacts with users by having a specific role or function.

[0072] "User information" refers to health-related data and goals provided by users, which form the basis for providing individualized services and suggestions.

[0073] A "processing device" is a device used for calculating and analyzing data. It performs analysis and processing based on information obtained from users and generates results.

[0074] "Personalized support" refers to advice and programs customized according to the user's characteristics and needs, meaning health support optimized for each individual user.

[0075] "Rewards" are incentives or rewards given to users when they achieve a specific goal, and they are elements that increase motivation and encourage continued effort.

[0076] A "challenge" is a specific action goal or challenge that the user should aim to achieve, and it is set up to support the process of improving health.

[0077] This invention is a system for personalizing individual health support, enabling continuous health management for users. The embodiments of the system will be described in detail below.

[0078] The server uses an image generation device and generative AI models such as Stable Diffusion and Midjourney to generate virtual entities adapted to diverse areas such as nutrition, fitness, mental health, stress management, and sleep improvement. These virtual entities incorporate design elements tailored to each health area and interact naturally with the user.

[0079] Users access the application from their smartphones or tablets using their devices. Through the device's interface, users set health goals and input daily activity information such as calorie intake, exercise levels, mental state, stress levels, and sleep quality. The device then transmits this information to the server.

[0080] The server analyzes the received user information using data analysis tools such as Python and R, and generates personalized health support tailored to the user's condition and goals. For example, based on a user's goal of "consuming 1,500 kcal per day and jogging three times a week," the server creates a healthy meal plan and exercise program for one week.

[0081] The generated support content is delivered to the user visually through the device. A virtual entity sends motivational messages such as "Let's do our best today!" to support the user and encourage actions toward achieving their goals.

[0082] Furthermore, the server continuously monitors the user's progress and provides rewards such as points and badges each time a goal is achieved. This allows users to engage in health management in a gamified way.

[0083] Specific examples of prompts include "Please provide a healthy meal plan" and "Create a message to motivate me to jog."

[0084] In this way, this invention enables the provision of personalized health support to users and efficient lifestyle improvements.

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] The server initializes the image generation device and generates a virtual subject using a generation AI model. It takes prompt text for each health domain (e.g., "Fitness Instructor Character") as input. The server inputs the prompts into the generation AI model and outputs the design data for the virtual subject. Specifically, the server calls the AI ​​model's API to retrieve the generated image data.

[0088] Step 2:

[0089] Users access the application using their device and input their health goals and activity information. This activity information includes, for example, calorie intake and exercise status. The device sends the input data to the server. Specifically, when a user enters data into the interface and presses the "Send" button, the data is uploaded to the server.

[0090] Step 3:

[0091] The server analyzes received user information using data analysis tools. Input includes health goals and activity information sent from the terminal. The server executes a Python script and outputs the user's health status and challenges as analysis results. Specifically, the server's analysis script processes the user's data and identifies areas for improvement.

[0092] Step 4:

[0093] The server generates health support content optimized for the user based on the analysis results. It uses health status assessments and goal setting as input. The server generates health support content and provides a one-week meal plan and exercise program as output. Specifically, logic runs within the server to build a personalized health plan.

[0094] Step 5:

[0095] The generated content is presented to the user by a virtual entity via the device. The input is personalized content from the server. The device displays the virtual entity and provides interactive feedback to the user. Specifically, the virtual entity displays messages such as "Let's achieve today's goal!" on the device's display.

[0096] Step 6:

[0097] The server monitors the user's ongoing progress and generates rewards when goals are achieved. Inputs include the user's activity history and goal achievement status. The server generates reward information and provides rewards to the user as output. Specifically, the server cross-checks the user's progress data and adds points according to their achievement status.

[0098] (Application Example 1)

[0099] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0100] In modern society, individual health management is highly valued, but there is a lack of easily accessible personalized health support. Traditional methods require information gathering through visits to specialists or books, making it difficult to maintain motivation towards daily health goals. To solve these problems, there is a need for a system that allows users to receive personalized health advice and exercise suggestions through a virtual character.

[0101] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0102] In this invention, the server includes means for generating a virtual character specialized in health support using an image generation mechanism, means for acquiring health-related goals and information from the user, and means for analyzing the acquired information and providing personalized health support. As a result, the user can easily receive personalized health plans and exercise suggestions through the virtual character, enabling them to continue daily health management and maintain motivation.

[0103] An "image generation mechanism" is a system that generates virtual visual representations using specific algorithms and techniques.

[0104] A "virtual character" is a character in the form of a person or animal, generated from digital data, that serves a role in providing specific functions or information.

[0105] A "user" is an individual who uses this system to set their own health management goals and provides information.

[0106] An "information processing device" is a device such as a computer or server that analyzes acquired data and derives specific results.

[0107] A "user device" is a terminal device that allows the user to receive information and interact with a virtual character.

[0108] A "notification function" is a system feature that communicates pre-set alerts and reminders to the user.

[0109] A "challenge" refers to a specific task or initiative designed to help users achieve their health goals.

[0110] The system for realizing this invention operates by coordinating multiple hardware and software components. The main hardware components include a server for information processing and a user-facing terminal device. The terminal device is a mobile device such as a smartphone or tablet, providing the user interface. The server utilizes software platforms such as TENSORFLOW® and DALL-E to perform data analysis and image generation.

[0111] The server first generates a virtual character specifically for health support using an image generation mechanism. Using the DALL-E generation AI model, it visualizes a personalized character tailored to the user's health status and goals. Next, it sends health-related data obtained from the user to the server. This information includes the user's daily exercise and diet records, as well as their mental state.

[0112] The server analyzes the received data using TensorFlow and develops an optimal health support plan for the user. This plan includes specific exercise suggestions and dietary advice, which are provided to the user through a virtual character. The user interface is built using Flutter® so that the user can receive and visually confirm this information on their device.

[0113] Furthermore, the server monitors the user's progress toward their health goals and automatically generates notifications and new challenges tailored to those goals. This supports the user in continuing to manage their health and maintaining their motivation.

[0114] For example, if a user requests meditation for relaxation, a virtual character will create an original meditation plan and guide the user through it. An example of a prompt would be: "Generate a suitable virtual character based on the user's desired health goals and provide personalized health support. For example, how do I generate a virtual instructor character for a user who wants meditation to relieve stress?"

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] Users input health goals and daily data using a device. This input data includes exercise levels, diet, and mental state. The device then sends the entered data to a server.

[0118] Step 2:

[0119] The server analyzes the received data. This analysis utilizes machine learning algorithms based on TensorFlow. As a result of the data analysis, the user's current health status and progress toward goals are quantified.

[0120] Step 3:

[0121] Based on the analysis results, the server uses the DALL-E AI model to generate a virtual character specialized in health support. The input is the analysis results, and the output is a visual representation of a character suitable for the user.

[0122] Step 4:

[0123] The server develops a health support plan. It generates a personalized plan for the user, including exercise suggestions and dietary advice. This support plan is generated using analysis results as input and output as plan data.

[0124] Step 5:

[0125] The terminal displays a virtual character and support plan received from the server. Using Flutter, a user interface is built that allows the user to interact with the character and provides support information visually.

[0126] Step 6:

[0127] Users implement the support plan in their daily lives and report the results to the server via their device. The user's results are sent to the server and become input data for the next analysis cycle.

[0128] Step 7:

[0129] The server monitors the user's progress and automatically generates new challenges and notifications. It uses the analyzed progress data as input to output appropriate reminders and new health challenges.

[0130] Step 8:

[0131] The device provides users with generated notifications and challenges to help them stay motivated. Users review these and move on to their next health goal.

[0132] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0133] This invention is a system that provides personalized health support to users using a virtual character that combines an image generation engine and an emotion engine. Its specific form is described below.

[0134] The server initializes the image generation engine to generate virtual characters corresponding to multiple health specialties. These characters incorporate designs tailored to areas such as nutrition, fitness, and mental health. The generated virtual characters have visuals and personas for interacting with the user.

[0135] The device provides users with a means to access applications and input their health goals and daily activity data. Users can record data such as eating habits, exercise levels, mental state, and sleep information. The device transmits this information to a server.

[0136] The server analyzes received user data and automatically generates personalized health support content. Furthermore, it uses an emotion engine to recognize emotions from the user's facial expressions and voice, and adjusts the character's response accordingly. This ensures that reliable advice is provided that is tailored to the user's emotional state.

[0137] For example, if the emotion engine recognizes a user's frustration, the server generates instructions introducing relaxation techniques and stress reduction methods. Conversely, if positive emotions are recognized, it provides content that motivates the user to set even higher goals.

[0138] The device displays content retrieved from the server to the user through a virtual character. The character suggests reminders and new challenges to the user based on their daily health activities and progress towards their goals.

[0139] Users aim to achieve their goals by continuing their daily activities and recording their progress on their devices. The emotion engine continuously monitors their emotional state, providing long-term insights into the user's mental health.

[0140] Thus, the present invention provides advanced personalization functions that take into account the user's emotional state, and has a form that enables more effective health support.

[0141] The following describes the processing flow.

[0142] Step 1:

[0143] The server uses an image generation engine to generate virtual characters corresponding to each area of ​​expertise. These characters will have visual designs and personas tailored to the user's needs.

[0144] Step 2:

[0145] The device accepts users to input their health goals and daily health data. Users log in to their account and enter their calorie intake, exercise history, stress levels, and sleep data.

[0146] Step 3:

[0147] The device transmits health data acquired from the user to the server. The data is sent using a secure protocol and stored on the server.

[0148] Step 4:

[0149] The server analyzes the received health data. This analysis compares the current data with the set health goals to determine how well the user is achieving those goals.

[0150] Step 5:

[0151] The server further uses an emotion engine to analyze the user's facial expressions and voice transmitted from the device, recognizing their current emotional state. This information is then incorporated into health support content.

[0152] Step 6:

[0153] The server generates personalized health support content based on the user's health status and perceived emotions. For example, if stress is detected, relaxation techniques are suggested; if positive emotions are detected, new challenges are offered.

[0154] Step 7:

[0155] The server sends the generated health support content to the terminal. This content is displayed to the user through a virtual character.

[0156] Step 8:

[0157] The virtual character interacts with the user and supports their daily activities. The character provides reminders and new challenges based on progress, encouraging the user to achieve their health goals.

[0158] Step 9:

[0159] Users continue their daily activities through their devices and record their progress toward their goals. This allows the server to accumulate long-term data, improving the accuracy of analysis by the sentiment engine.

[0160] Step 10:

[0161] The server will use users' past emotional and health data to improve future support content, enabling the provision of more accurate health support.

[0162] (Example 2)

[0163] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0164] In recent years, the importance of health management has increased significantly, leading to a growing demand for personalized health support. However, conventional health support systems have struggled to personalize services while adequately considering the emotional state of individual users, failing to provide optimal support. Furthermore, they often only provide general information, lacking specific feedback on individual health goals and progress. As a result, there is a challenge in motivating users to continue managing their health over the long term.

[0165] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0166] In this invention, the server includes means for generating virtual characters specialized in multiple fields using image generation means, means for analyzing data acquired using a generation AI model and providing personalized health support, and means for evaluating and adjusting the user's emotional state using emotion recognition technology. This makes it possible to provide personalized health support optimized for each individual user and to provide feedback that is in line with the user's emotional state.

[0167] "Image generation means" refers to a device or technology that generates virtual characters specialized in multiple fields.

[0168] A "virtual character" refers to a digital character whose visuals and persona are designed to suit a specific field, and which forms the basis of interaction with the user.

[0169] "Acquired data" refers to information about health goals and daily activities provided by users.

[0170] A "generative AI model" refers to a computational model that uses artificial intelligence to generate new information or instructions based on given data.

[0171] "Personalized health support" refers to customized health advice or content provided based on a user's individual data and condition.

[0172] "Emotion recognition technology" refers to technology that analyzes and identifies a user's emotional state from their facial expressions, voice, and other actions.

[0173] A "terminal" refers to a digital device used by a user, specifically hardware that receives and displays information from a server.

[0174] A "reminder" refers to a prompt or notification set to support a user in achieving their health goals.

[0175] "New challenges" refer to new tasks or goals that are provided to users based on their progress.

[0176] This invention is a health support system in which servers, terminals, and users work together in coordination.

[0177] The server first generates virtual characters using image generation methods. This involves using graphic software and image generation engines to create character designs tailored to specific health fields. For example, it incorporates visual elements specific to nutrition, fitness, and mental health. The server then utilizes a generative AI model to collect and analyze the user's health data. This model learns patterns from, for example, the user's diet and exercise history, and generates personalized health support.

[0178] The device functions as a platform for users to input health information. Through applications on smartphones and tablets, users can record daily activity data (e.g., diet, exercise, sleep, emotional state). The entered data is sent to a server and used for necessary analysis.

[0179] Users utilize health support provided through a virtual character displayed on their device. The character offers personalized advice and reminders to help maintain motivation for health management. In particular, emotion recognition technology assesses the user's emotional state in real time and provides corresponding feedback. This process enables effective health support tailored to the user's emotional state.

[0180] As a concrete example, if a user feels they are not getting enough exercise, a prompt message generated by a generative AI model might be: "Check the user's exercise history and suggest a simple exercise plan for three times a week." This would give the user a concrete action plan, making it easier to work towards their health goals.

[0181] This system provides personalized health support to users and takes their emotional state into consideration, enabling long-term health management.

[0182] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0183] Step 1:

[0184] The server initializes the image generation system and generates a virtual character. It incorporates design elements tailored to multiple areas related to the user's health (e.g., nutrition, fitness, mental health). The input includes character design information for each area, and the output is a virtual character. Specifically, the image generation engine is used to construct the character's visual appearance and persona.

[0185] Step 2:

[0186] Users input daily health information through their devices. This includes data such as diet, exercise levels, sleep duration, and emotional state. The entered data is acquired through application forms and sensors and sent to a server as a digital record. Specifically, users input data by operating their smartphone's touchscreen or using voice input.

[0187] Step 3:

[0188] The server receives user health data sent from the terminal and begins data analysis. Based on the input data, it generates personalized health support content using a generative AI model. As output, it generates personalized advice and reminders for the user. Specifically, it prompts the AI ​​model with a message such as "Generate daily health behavior suggestions based on the user's input data" and receives a response.

[0189] Step 4:

[0190] The server uses emotion recognition technology to evaluate the user's emotional state. It extracts emotions from the user's facial expression data and voice, and adjusts the feedback accordingly. Input includes the user's real-time facial image and voice data, and output is an evaluation of the emotional state. Specifically, the emotion analysis engine processes the image and voice data and calculates an emotion score.

[0191] Step 5:

[0192] The device displays personalized content provided by the server to the user through a virtual character. Input includes health support instructions from the server, and output is presented to the user visually and audibly. Specifically, the character appears on the device's display and uses speech synthesis to convey recommendations to the user.

[0193] Step 6:

[0194] Users adjust their daily health behaviors based on instructions and advice from a virtual character. They modify their action plan based on input and implement the improved health behaviors as output. Specifically, users incorporate the suggested actions into their real lives and record their progress again on the device. This feedback loop optimizes the user's health management.

[0195] (Application Example 2)

[0196] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0197] In the fields of health management and fitness, providing personalized support tailored to the individual needs and emotional states of users is a challenging task. Furthermore, there is a lack of interactive systems that can dynamically respond to users' emotions, in addition to static information provision. In this context, there is a growing need for health support systems with advanced personalization capabilities that take users' emotional states into account.

[0198] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0199] In this invention, the server includes means for generating virtual characters specialized in multiple domains using an image generation module, means for acquiring health-related goals and data from users through the virtual characters, means for analyzing the acquired data in a central computing device and customizing the health support provided by the virtual characters for each user, and means for recognizing emotions from the user's facial expressions and voice using an emotion analysis engine and adjusting the virtual characters' responses according to the emotional state. This enables appropriate and interactive health support for users that is tailored to their individual circumstances and emotions.

[0200] An "image generation module" is a software component used to generate visual characters related to a specific area.

[0201] A "virtual character" is a digital agent generated by an image generation module and designed to interact with the user.

[0202] The "central computing unit" is a central processing unit that analyzes acquired user data and personalizes support information.

[0203] An "emotion analysis engine" is a technology that analyzes a user's facial expressions and voice to recognize their emotional state.

[0204] "Support information" refers to advice and instructions provided to users to help them achieve their health goals and improve their motivation.

[0205] A "health support system" is a system that supports users' health management and provides support through an optimized approach tailored to individual needs.

[0206] In this invention, the server first uses an image generation module to generate a virtual character tailored to the user's purpose. This virtual character is designed to correspond to multiple areas of health management. Subsequently, the user can input health-related goals and daily activity data using a terminal. This includes data such as diet, exercise levels, mental state, and sleep information. This data is transmitted to the server and analyzed.

[0207] The server utilizes a central computing device to reconstruct acquired data into personalized health support information for each individual user. This support information includes advice and challenges tailored to the user's progress and emotional state. Furthermore, an emotion analysis engine is used to analyze emotional data from the user's facial expressions and voice, dynamically adjusting the virtual character's responses.

[0208] Through virtual characters displayed on smartphones and tablets, users can receive reminders and goal setting to help them continue their daily health activities. For example, if a user feels like relaxing after exercise, the character will suggest a 10-minute stretching routine. Conversely, if the user is in a positive emotional state, the character will suggest a new exercise program.

[0209] Throughout this entire system, long-term mental health support is possible based on progress data recorded on the terminal and data from the emotion analysis engine.

[0210] (Specific example)

[0211] A gym user, wanting to relax after their workout, enters their daily health status into a terminal. In response, a virtual character suggests, "Great job! You seem a little sluggish today, but let's refresh ourselves with 10 minutes of stretching!" The system also recognizes the user's enjoyment from their facial expressions and provides information about fitness events for the following weekend.

[0212] (Example of prompts for a generative AI model)

[0213] "Please generate an emotional, interactive dialogue-style script in which a virtual character suggests ways to relax after exercise, based on the user's health data and emotional state."

[0214] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0215] Step 1:

[0216] Users input their health goals and daily activity data using a device. This input includes information such as diet, exercise levels, mental state, and sleep information. The device collects this data and sends it to a server. The output is a collection of user data.

[0217] Step 2:

[0218] The server analyzes the received user data. This analysis utilizes a central computing system to assess the user's health status and generate personalized support information. During this process, a generating AI model dynamically uses prompts to create draft advice. The output is personalized health support information for each user.

[0219] Step 3:

[0220] The server invokes an image generation module to generate a virtual character based on the user's health status and goals. Each character has elements corresponding to a specific health area. Based on the generated character, advice for the user is visually represented. The output is a digital character.

[0221] Step 4:

[0222] The server uses an emotion analysis engine to analyze the user's facial expressions and voice. The input is real-time audio and visual data. Based on the analysis results, the server evaluates the user's emotional state and adjusts the virtual character's response. The output of this step is interaction information based on the emotional state.

[0223] Step 5:

[0224] The device displays health support information and a virtual character received from the server to the user. This allows the user to receive personalized reminders and advice from the character. New challenges and motivational content tailored to daily activities and emotions are also displayed. The output is an interactive user interface.

[0225] Through these steps, users will be able to continuously receive personalized advice tailored to their health condition in real time.

[0226] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0227] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0228] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0229] [Second Embodiment]

[0230] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0231] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0232] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0233] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0234] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0235] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0236] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0237] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0238] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0239] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0240] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0241] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0242] This invention realizes a system that provides personalized health support to individual users by utilizing virtual characters generated using an image generation engine. The embodiments are described in detail below.

[0243] The server initializes the image generation engine and creates virtual characters specializing in various health fields. This provides users with characters that address areas such as nutrition, fitness, mental health, stress management, and sleep improvement.

[0244] Users access the application using their device, set health goals, and input daily activity data. This information includes calorie intake, exercise status, mental state, stress levels, and sleep quality. The device then sends this data to the server.

[0245] The server analyzes the received user data and generates health support content tailored to the user's current state and goals. For example, the server personalizes a week's worth of meal plans and exercise programs based on the goals set by the user.

[0246] The generated advice and challenges are sent to the device and presented to the user through a virtual character. The device visually displays this when the user opens the application, and the character provides support by interacting with the user.

[0247] For example, if a user aims to lose weight, the server will suggest calorie management for meals and exercises to increase calorie expenditure. A virtual character will send daily motivational messages and support the user in completing their set health challenges.

[0248] Furthermore, the server monitors the user's progress and provides rewards each time a goal is achieved, thus maintaining motivation. This reward system makes it easier for users to continue managing their health in a gamified way.

[0249] Thus, this invention provides an effective form that offers continuous health support to users and contributes to improving their lifestyles.

[0250] The following describes the processing flow.

[0251] Step 1:

[0252] The server uses an image generation engine to create virtual characters specialized in each field. This includes visual design and persona creation for each character.

[0253] Step 2:

[0254] Users access the application from their device and enter their profile information and health goals. They also record daily health data such as their diet, exercise level, and sleep duration.

[0255] Step 3:

[0256] The terminal sends the entered user data to the server. The data is encrypted and transmitted securely.

[0257] Step 4:

[0258] The server analyzes the received user data. This analysis includes comparing the user's current health status with their set goals.

[0259] Step 5:

[0260] The server generates personalized health support content based on the analysis results. This content includes daily activity plans, meal suggestions, and guidelines for improving mental health.

[0261] Step 6:

[0262] The generated support content is sent from the server to the device. This may include real-time feedback.

[0263] Step 7:

[0264] The device displays the content through a virtual character so that the user can review it. The character provides advice and challenges through interaction with the user.

[0265] Step 8:

[0266] Users perform their daily activities according to the advice and challenges presented. Furthermore, continuous monitoring is possible by recording progress and achievements on the device.

[0267] Step 9:

[0268] The server tracks user progress and updates content as needed. It may also provide users with new challenges or reminders to help them achieve their goals.

[0269] Step 10:

[0270] When users achieve their goals, they receive rewards through their devices. This helps them stay motivated and continue healthy behaviors in a gamified way.

[0271] (Example 1)

[0272] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0273] In modern society, while awareness of personal health management is increasing, consistent health management is difficult due to busy daily lives. In particular, the lack of personalization tailored to individual needs is a challenge. It has been found that conventional systems have difficulty providing effective health support tailored to individuals, and that maintaining motivation is difficult.

[0274] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0275] In this invention, the server includes means for generating a virtual entity adapted to various domains using an image generation device, means for acquiring health-related objectives and information from a user through the virtual entity, and means for analyzing the acquired information in a processing device and personalizing the health support provided by the virtual entity. This enables personalized health support for individual users and continuous health management.

[0276] An "image generation device" is a device that creates visual information based on input digital instructions, and generates display elements according to specific conditions or themes.

[0277] A "virtual entity" is a character or agent constructed digitally that interacts with users by having a specific role or function.

[0278] "User information" refers to health-related data and goals provided by users, which form the basis for providing individualized services and suggestions.

[0279] A "processing device" is a device used for calculating and analyzing data. It performs analysis and processing based on information obtained from users and generates results.

[0280] "Personalized support" refers to advice and programs customized according to the user's characteristics and needs, meaning health support optimized for each individual user.

[0281] "Rewards" are incentives or rewards given to users when they achieve a specific goal, and they are elements that increase motivation and encourage continued effort.

[0282] A "challenge" is a specific action goal or challenge that the user should aim to achieve, and it is set up to support the process of improving health.

[0283] This invention is a system for personalizing individual health support and enables continuous health management for users. Hereinafter, embodiments of the system will be described in detail.

[0284] The server uses an image generation device to generate virtual entities adapted to various fields such as nutrition, fitness, mental health, stress management, and sleep improvement by generative AI models such as Stable Diffusion and Midjourney. This virtual entity incorporates design elements corresponding to individual health areas and interacts naturally with the user.

[0285] The user accesses the application from a smartphone or tablet using a terminal. The user sets health goals through the terminal interface and inputs daily activity information such as calorie intake, exercise status, mental state, stress level, and sleep quality. The terminal transmits this information to the server.

[0286] The server analyzes the received user information using data analysis tools such as Python and R and generates individualized health support content according to the user's condition and goals. For example, based on the user's goal of "consuming 1,500 kcal per day and jogging three times a week," the server creates a one-week healthy diet plan and exercise program.

[0287] The generated support content is visually provided to the user through the terminal. By the virtual entity sending motivation messages such as "Keep up the good work today!" and supporting the user, it promotes actions towards achieving the goal.

[0288] Furthermore, the server continuously monitors the user's progress and provides rewards such as points and badges every time the goal is achieved. As a result, the user can engage in health management in a game-like manner.

[0289] Specific examples of prompts include "Please provide a healthy meal plan" and "Create a message to motivate me to jog."

[0290] In this way, this invention enables the provision of personalized health support to users and efficient lifestyle improvements.

[0291] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0292] Step 1:

[0293] The server initializes the image generation device and generates a virtual subject using a generation AI model. It takes prompt text for each health domain (e.g., "Fitness Instructor Character") as input. The server inputs the prompts into the generation AI model and outputs the design data for the virtual subject. Specifically, the server calls the AI ​​model's API to retrieve the generated image data.

[0294] Step 2:

[0295] Users access the application using their device and input their health goals and activity information. This activity information includes, for example, calorie intake and exercise status. The device sends the input data to the server. Specifically, when a user enters data into the interface and presses the "Send" button, the data is uploaded to the server.

[0296] Step 3:

[0297] The server analyzes received user information using data analysis tools. Input includes health goals and activity information sent from the terminal. The server executes a Python script and outputs the user's health status and challenges as analysis results. Specifically, the server's analysis script processes the user's data and identifies areas for improvement.

[0298] Step 4:

[0299] The server generates health support content optimized for the user based on the analysis results. It uses health status assessments and goal setting as input. The server generates health support content and provides a one-week meal plan and exercise program as output. Specifically, logic runs within the server to build a personalized health plan.

[0300] Step 5:

[0301] The generated content is presented to the user by a virtual entity via the device. The input is personalized content from the server. The device displays the virtual entity and provides interactive feedback to the user. Specifically, the virtual entity displays messages such as "Let's achieve today's goal!" on the device's display.

[0302] Step 6:

[0303] The server monitors the user's ongoing progress and generates rewards when goals are achieved. Inputs include the user's activity history and goal achievement status. The server generates reward information and provides rewards to the user as output. Specifically, the server cross-checks the user's progress data and adds points according to their achievement status.

[0304] (Application Example 1)

[0305] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0306] In modern society, individual health management is highly emphasized, but there is a lack of convenient means to receive personalized health support. Conventional methods require information collection through visits by experts or books, etc., and it is difficult to maintain motivation towards daily health goals. To solve these problems, there is a demand for a system that can receive health advice and exercise proposals tailored to individual users through virtual characters.

[0307] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0308] In this invention, the server includes means for generating a virtual character specialized for health support by an image generation mechanism, means for acquiring health-related goals and information from a user, and means for analyzing the acquired information and providing individualized health support. Thereby, users can easily receive individualized health plans and exercise proposals through virtual characters, and it becomes possible to continue daily health management and maintain motivation.

[0309] The "image generation mechanism" is a system that generates virtual visual representations using specific algorithms or technologies.

[0310] The "virtual character" is a character in the form of a person or animal generated by digital data and has the role of providing specific functions and information.

[0311] The "user" is an individual who uses this system and sets goals and provides information regarding their own health management.

[0312] The "information processing device" is a device such as a computer or server that analyzes the acquired data and derives specific results.

[0313] The "utilization device" is a terminal device through which a user receives information and enables interaction with a virtual character.

[0314] A "notification function" is a system feature that communicates pre-set alerts and reminders to the user.

[0315] A "challenge" refers to a specific task or initiative designed to help users achieve their health goals.

[0316] The system for realizing this invention operates by coordinating multiple hardware and software components. The main hardware components include a server for information processing and a terminal device used by the user. The terminal device is a mobile device such as a smartphone or tablet, providing the user interface. The server utilizes software platforms such as TensorFlow and DALL-E to perform data analysis and image generation.

[0317] The server first generates a virtual character specifically for health support using an image generation mechanism. Using the DALL-E generation AI model, it visualizes a personalized character tailored to the user's health status and goals. Next, it sends health-related data obtained from the user to the server. This information includes the user's daily exercise and diet records, as well as their mental state.

[0318] The server analyzes the received data using TensorFlow and develops an optimal health support plan for the user. This plan includes specific exercise suggestions and dietary advice, which are provided to the user through a virtual character. A user interface is built using Flutter so that the user can receive and visually confirm this information on their device.

[0319] Furthermore, the server monitors the user's progress toward their health goals and automatically generates notifications and new challenges tailored to those goals. This supports the user in continuing to manage their health and maintaining their motivation.

[0320] For example, if a user requests meditation for relaxation, a virtual character will create an original meditation plan and guide the user through it. An example of a prompt would be: "Generate a suitable virtual character based on the user's desired health goals and provide personalized health support. For example, how do I generate a virtual instructor character for a user who wants meditation to relieve stress?"

[0321] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0322] Step 1:

[0323] Users input health goals and daily data using a device. This input data includes exercise levels, diet, and mental state. The device then sends the entered data to a server.

[0324] Step 2:

[0325] The server analyzes the received data. This analysis utilizes machine learning algorithms based on TensorFlow. As a result of the data analysis, the user's current health status and progress toward goals are quantified.

[0326] Step 3:

[0327] Based on the analysis results, the server uses the DALL-E AI model to generate a virtual character specialized in health support. The input is the analysis results, and the output is a visual representation of a character suitable for the user.

[0328] Step 4:

[0329] The server develops a health support plan. It generates a personalized plan for the user, including exercise suggestions and dietary advice. This support plan is generated using analysis results as input and output as plan data.

[0330] Step 5:

[0331] The terminal displays a virtual character and support plan received from the server. Using Flutter, a user interface is built that allows the user to interact with the character and provides support information visually.

[0332] Step 6:

[0333] Users implement the support plan in their daily lives and report the results to the server via their device. The user's results are sent to the server and become input data for the next analysis cycle.

[0334] Step 7:

[0335] The server monitors the user's progress and automatically generates new challenges and notifications. It uses the analyzed progress data as input to output appropriate reminders and new health challenges.

[0336] Step 8:

[0337] The device provides users with generated notifications and challenges to help them stay motivated. Users review these and move on to their next health goal.

[0338] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0339] This invention is a system that provides personalized health support to users using a virtual character that combines an image generation engine and an emotion engine. Its specific form is described below.

[0340] The server initializes the image generation engine to generate virtual characters corresponding to multiple health specialties. These characters incorporate designs tailored to areas such as nutrition, fitness, and mental health. The generated virtual characters have visuals and personas for interacting with the user.

[0341] The device provides users with a means to access applications and input their health goals and daily activity data. Users can record data such as eating habits, exercise levels, mental state, and sleep information. The device transmits this information to a server.

[0342] The server analyzes received user data and automatically generates personalized health support content. Furthermore, it uses an emotion engine to recognize emotions from the user's facial expressions and voice, and adjusts the character's response accordingly. This ensures that reliable advice is provided that is tailored to the user's emotional state.

[0343] For example, if the emotion engine recognizes a user's frustration, the server generates instructions introducing relaxation techniques and stress reduction methods. Conversely, if positive emotions are recognized, it provides content that motivates the user to set even higher goals.

[0344] The device displays content retrieved from the server to the user through a virtual character. The character suggests reminders and new challenges to the user based on their daily health activities and progress towards their goals.

[0345] Users aim to achieve their goals by continuing their daily activities and recording their progress on their devices. The emotion engine continuously monitors their emotional state, providing long-term insights into the user's mental health.

[0346] Thus, the present invention provides advanced personalization functions that take into account the user's emotional state, and has a form that enables more effective health support.

[0347] The following describes the processing flow.

[0348] Step 1:

[0349] The server uses an image generation engine to generate virtual characters corresponding to each area of ​​expertise. These characters will have visual designs and personas tailored to the user's needs.

[0350] Step 2:

[0351] The device accepts users to input their health goals and daily health data. Users log in to their account and enter their calorie intake, exercise history, stress levels, and sleep data.

[0352] Step 3:

[0353] The device transmits health data acquired from the user to the server. The data is sent using a secure protocol and stored on the server.

[0354] Step 4:

[0355] The server analyzes the received health data. This analysis compares the current data with the set health goals to determine how well the user is achieving those goals.

[0356] Step 5:

[0357] The server further uses an emotion engine to analyze the user's facial expressions and voice transmitted from the device, recognizing their current emotional state. This information is then incorporated into health support content.

[0358] Step 6:

[0359] The server generates personalized health support content based on the user's health status and perceived emotions. For example, if stress is detected, relaxation techniques are suggested; if positive emotions are detected, new challenges are offered.

[0360] Step 7:

[0361] The server sends the generated health support content to the terminal. This content is displayed to the user through a virtual character.

[0362] Step 8:

[0363] The virtual character interacts with the user and supports their daily activities. The character provides reminders and new challenges based on progress, encouraging the user to achieve their health goals.

[0364] Step 9:

[0365] Users continue their daily activities through their devices and record their progress toward their goals. This allows the server to accumulate long-term data, improving the accuracy of analysis by the sentiment engine.

[0366] Step 10:

[0367] The server will use users' past emotional and health data to improve future support content, enabling the provision of more accurate health support.

[0368] (Example 2)

[0369] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0370] In recent years, the importance of health management has increased significantly, leading to a growing demand for personalized health support. However, conventional health support systems have struggled to personalize services while adequately considering the emotional state of individual users, failing to provide optimal support. Furthermore, they often only provide general information, lacking specific feedback on individual health goals and progress. As a result, there is a challenge in motivating users to continue managing their health over the long term.

[0371] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0372] In this invention, the server includes means for generating virtual characters specialized in multiple fields using image generation means, means for analyzing data acquired using a generation AI model and providing personalized health support, and means for evaluating and adjusting the user's emotional state using emotion recognition technology. This makes it possible to provide personalized health support optimized for each individual user and to provide feedback that is in line with the user's emotional state.

[0373] "Image generation means" refers to a device or technology that generates virtual characters specialized in multiple fields.

[0374] A "virtual character" refers to a digital character whose visuals and persona are designed to suit a specific field, and which forms the basis of interaction with the user.

[0375] "Acquired data" refers to information about health goals and daily activities provided by users.

[0376] A "generative AI model" refers to a computational model that uses artificial intelligence to generate new information or instructions based on given data.

[0377] "Personalized health support" refers to customized health advice or content provided based on a user's individual data and condition.

[0378] "Emotion recognition technology" refers to technology that analyzes and identifies a user's emotional state from their facial expressions, voice, and other actions.

[0379] A "terminal" refers to a digital device used by a user, specifically hardware that receives and displays information from a server.

[0380] A "reminder" refers to a prompt or notification set to support a user in achieving their health goals.

[0381] "New challenges" refer to new tasks or goals that are provided to users based on their progress.

[0382] This invention is a health support system in which servers, terminals, and users work together in coordination.

[0383] The server first generates virtual characters using image generation methods. This involves using graphic software and image generation engines to create character designs tailored to specific health fields. For example, it incorporates visual elements specific to nutrition, fitness, and mental health. The server then utilizes a generative AI model to collect and analyze the user's health data. This model learns patterns from, for example, the user's diet and exercise history, and generates personalized health support.

[0384] The device functions as a platform for users to input health information. Through applications on smartphones and tablets, users can record daily activity data (e.g., diet, exercise, sleep, emotional state). The entered data is sent to a server and used for necessary analysis.

[0385] Users utilize health support provided through a virtual character displayed on their device. The character offers personalized advice and reminders to help maintain motivation for health management. In particular, emotion recognition technology assesses the user's emotional state in real time and provides corresponding feedback. This process enables effective health support tailored to the user's emotional state.

[0386] As a concrete example, if a user feels they are not getting enough exercise, a prompt message generated by a generative AI model might be: "Check the user's exercise history and suggest a simple exercise plan for three times a week." This would give the user a concrete action plan, making it easier to work towards their health goals.

[0387] This system provides personalized health support to users and takes their emotional state into consideration, enabling long-term health management.

[0388] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0389] Step 1:

[0390] The server initializes the image generation system and generates a virtual character. It incorporates design elements tailored to multiple areas related to the user's health (e.g., nutrition, fitness, mental health). The input includes character design information for each area, and the output is a virtual character. Specifically, the image generation engine is used to construct the character's visual appearance and persona.

[0391] Step 2:

[0392] Users input daily health information through their devices. This includes data such as diet, exercise levels, sleep duration, and emotional state. The entered data is acquired through application forms and sensors and sent to a server as a digital record. Specifically, users input data by operating their smartphone's touchscreen or using voice input.

[0393] Step 3:

[0394] The server receives user health data sent from the terminal and begins data analysis. Based on the input data, it generates personalized health support content using a generative AI model. As output, it generates personalized advice and reminders for the user. Specifically, it prompts the AI ​​model with a message such as "Generate daily health behavior suggestions based on the user's input data" and receives a response.

[0395] Step 4:

[0396] The server uses emotion recognition technology to evaluate the user's emotional state. It extracts emotions from the user's facial expression data and voice, and adjusts the feedback accordingly. Input includes the user's real-time facial image and voice data, and output is an evaluation of the emotional state. Specifically, the emotion analysis engine processes the image and voice data and calculates an emotion score.

[0397] Step 5:

[0398] The device displays personalized content provided by the server to the user through a virtual character. Input includes health support instructions from the server, and output is presented to the user visually and audibly. Specifically, the character appears on the device's display and uses speech synthesis to convey recommendations to the user.

[0399] Step 6:

[0400] Users adjust their daily health behaviors based on instructions and advice from a virtual character. They modify their action plan based on input and implement the improved health behaviors as output. Specifically, users incorporate the suggested actions into their real lives and record their progress again on the device. This feedback loop optimizes the user's health management.

[0401] (Application Example 2)

[0402] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0403] In the fields of health management and fitness, providing personalized support tailored to the individual needs and emotional states of users is a challenging task. Furthermore, there is a lack of interactive systems that can dynamically respond to users' emotions, in addition to static information provision. In this context, there is a growing need for health support systems with advanced personalization capabilities that take users' emotional states into account.

[0404] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0405] In this invention, the server includes means for generating virtual characters specialized in multiple domains using an image generation module, means for acquiring health-related goals and data from users through the virtual characters, means for analyzing the acquired data in a central computing device and customizing the health support provided by the virtual characters for each user, and means for recognizing emotions from the user's facial expressions and voice using an emotion analysis engine and adjusting the virtual characters' responses according to the emotional state. This enables appropriate and interactive health support for users that is tailored to their individual circumstances and emotions.

[0406] An "image generation module" is a software component used to generate visual characters related to a specific area.

[0407] A "virtual character" is a digital agent generated by an image generation module and designed to interact with the user.

[0408] The "central computing unit" is a central processing unit that analyzes acquired user data and personalizes support information.

[0409] An "emotion analysis engine" is a technology that analyzes a user's facial expressions and voice to recognize their emotional state.

[0410] "Support information" refers to advice and instructions provided to users to help them achieve their health goals and improve their motivation.

[0411] A "health support system" is a system that supports users' health management and provides support through an optimized approach tailored to individual needs.

[0412] In this invention, the server first uses an image generation module to generate a virtual character tailored to the user's purpose. This virtual character is designed to correspond to multiple areas of health management. Subsequently, the user can input health-related goals and daily activity data using a terminal. This includes data such as diet, exercise levels, mental state, and sleep information. This data is transmitted to the server and analyzed.

[0413] The server utilizes a central computing device to reconstruct acquired data into personalized health support information for each individual user. This support information includes advice and challenges tailored to the user's progress and emotional state. Furthermore, an emotion analysis engine is used to analyze emotional data from the user's facial expressions and voice, dynamically adjusting the virtual character's responses.

[0414] Through virtual characters displayed on smartphones and tablets, users can receive reminders and goal setting to help them continue their daily health activities. For example, if a user feels like relaxing after exercise, the character will suggest a 10-minute stretching routine. Conversely, if the user is in a positive emotional state, the character will suggest a new exercise program.

[0415] Throughout this entire system, long-term mental health support is possible based on progress data recorded on the terminal and data from the emotion analysis engine.

[0416] (Specific example)

[0417] A gym user, wanting to relax after their workout, enters their daily health status into a terminal. In response, a virtual character suggests, "Great job! You seem a little sluggish today, but let's refresh ourselves with 10 minutes of stretching!" The system also recognizes the user's enjoyment from their facial expressions and provides information about fitness events for the following weekend.

[0418] (Example of prompts for a generative AI model)

[0419] "Please generate an emotional, interactive dialogue-style script in which a virtual character suggests ways to relax after exercise, based on the user's health data and emotional state."

[0420] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0421] Step 1:

[0422] Users input their health goals and daily activity data using a device. This input includes information such as diet, exercise levels, mental state, and sleep information. The device collects this data and sends it to a server. The output is a collection of user data.

[0423] Step 2:

[0424] The server analyzes the received user data. This analysis utilizes a central computing system to assess the user's health status and generate personalized support information. During this process, a generating AI model dynamically uses prompts to create draft advice. The output is personalized health support information for each user.

[0425] Step 3:

[0426] The server invokes an image generation module to generate a virtual character based on the user's health status and goals. Each character has elements corresponding to a specific health area. Based on the generated character, advice for the user is visually represented. The output is a digital character.

[0427] Step 4:

[0428] The server uses an emotion analysis engine to analyze the user's facial expressions and voice. The input is real-time audio and visual data. Based on the analysis results, the server evaluates the user's emotional state and adjusts the virtual character's response. The output of this step is interaction information based on the emotional state.

[0429] Step 5:

[0430] The device displays health support information and a virtual character received from the server to the user. This allows the user to receive personalized reminders and advice from the character. New challenges and motivational content tailored to daily activities and emotions are also displayed. The output is an interactive user interface.

[0431] Through these steps, users will be able to continuously receive personalized advice tailored to their health condition in real time.

[0432] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0433] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0434] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0435] [Third Embodiment]

[0436] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0437] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0438] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0439] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0440] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0441] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0442] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0443] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0444] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0445] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0446] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0447] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0448] This invention realizes a system that provides personalized health support to individual users by utilizing virtual characters generated using an image generation engine. The embodiments are described in detail below.

[0449] The server initializes the image generation engine and creates virtual characters specializing in various health fields. This provides users with characters that address areas such as nutrition, fitness, mental health, stress management, and sleep improvement.

[0450] Users access the application using their device, set health goals, and input daily activity data. This information includes calorie intake, exercise status, mental state, stress levels, and sleep quality. The device then sends this data to the server.

[0451] The server analyzes the received user data and generates health support content tailored to the user's current state and goals. For example, the server personalizes a week's worth of meal plans and exercise programs based on the goals set by the user.

[0452] The generated advice and challenges are sent to the device and presented to the user through a virtual character. The device visually displays this when the user opens the application, and the character provides support by interacting with the user.

[0453] For example, if a user aims to lose weight, the server will suggest calorie management for meals and exercises to increase calorie expenditure. A virtual character will send daily motivational messages and support the user in completing their set health challenges.

[0454] Furthermore, the server monitors the user's progress and provides rewards each time a goal is achieved, thus maintaining motivation. This reward system makes it easier for users to continue managing their health in a gamified way.

[0455] Thus, this invention provides an effective form that offers continuous health support to users and contributes to improving their lifestyles.

[0456] The following describes the processing flow.

[0457] Step 1:

[0458] The server uses an image generation engine to create virtual characters specialized in each field. This includes visual design and persona creation for each character.

[0459] Step 2:

[0460] Users access the application from their device and enter their profile information and health goals. They also record daily health data such as their diet, exercise level, and sleep duration.

[0461] Step 3:

[0462] The terminal sends the entered user data to the server. The data is encrypted and transmitted securely.

[0463] Step 4:

[0464] The server analyzes the received user data. This analysis includes comparing the user's current health status with their set goals.

[0465] Step 5:

[0466] The server generates personalized health support content based on the analysis results. This content includes daily activity plans, meal suggestions, and guidelines for improving mental health.

[0467] Step 6:

[0468] The generated support content is sent from the server to the device. This may include real-time feedback.

[0469] Step 7:

[0470] The device displays the content through a virtual character so that the user can review it. The character provides advice and challenges through interaction with the user.

[0471] Step 8:

[0472] Users perform their daily activities according to the advice and challenges presented. Furthermore, continuous monitoring is possible by recording progress and achievements on the device.

[0473] Step 9:

[0474] The server tracks user progress and updates content as needed. It may also provide users with new challenges or reminders to help them achieve their goals.

[0475] Step 10:

[0476] When users achieve their goals, they receive rewards through their devices. This helps them stay motivated and continue healthy behaviors in a gamified way.

[0477] (Example 1)

[0478] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0479] In modern society, while awareness of personal health management is increasing, consistent health management is difficult due to busy daily lives. In particular, the lack of personalization tailored to individual needs is a challenge. It has been found that conventional systems have difficulty providing effective health support tailored to individuals, and that maintaining motivation is difficult.

[0480] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0481] In this invention, the server includes means for generating a virtual entity adapted to various domains using an image generation device, means for acquiring health-related objectives and information from a user through the virtual entity, and means for analyzing the acquired information in a processing device and personalizing the health support provided by the virtual entity. This enables personalized health support for individual users and continuous health management.

[0482] An "image generation device" is a device that creates visual information based on input digital instructions, and generates display elements according to specific conditions or themes.

[0483] A "virtual entity" is a character or agent constructed digitally that interacts with users by having a specific role or function.

[0484] "User information" refers to health-related data and goals provided by users, which form the basis for providing individualized services and suggestions.

[0485] A "processing device" is a device used for calculating and analyzing data. It performs analysis and processing based on information obtained from users and generates results.

[0486] "Personalized support" refers to advice and programs customized according to the user's characteristics and needs, meaning health support optimized for each individual user.

[0487] "Rewards" are incentives or rewards given to users when they achieve a specific goal, and they are elements that increase motivation and encourage continued effort.

[0488] A "challenge" is a specific action goal or challenge that the user should aim to achieve, and it is set up to support the process of improving health.

[0489] This invention is a system for personalizing individual health support, enabling continuous health management for users. The embodiments of the system will be described in detail below.

[0490] The server uses an image generation device and generative AI models such as Stable Diffusion and Midjourney to generate virtual entities adapted to diverse areas such as nutrition, fitness, mental health, stress management, and sleep improvement. These virtual entities incorporate design elements tailored to each health area and interact naturally with the user.

[0491] Users access the application from their smartphones or tablets using their devices. Through the device's interface, users set health goals and input daily activity information such as calorie intake, exercise levels, mental state, stress levels, and sleep quality. The device then transmits this information to the server.

[0492] The server analyzes the received user information using data analysis tools such as Python and R, and generates personalized health support tailored to the user's condition and goals. For example, based on a user's goal of "consuming 1,500 kcal per day and jogging three times a week," the server creates a healthy meal plan and exercise program for one week.

[0493] The generated support content is delivered to the user visually through the device. A virtual entity sends motivational messages such as "Let's do our best today!" to support the user and encourage actions toward achieving their goals.

[0494] Furthermore, the server continuously monitors the user's progress and provides rewards such as points and badges each time a goal is achieved. This allows users to engage in health management in a gamified way.

[0495] Specific examples of prompts include "Please provide a healthy meal plan" and "Create a message to motivate me to jog."

[0496] In this way, this invention enables the provision of personalized health support to users and efficient lifestyle improvements.

[0497] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0498] Step 1:

[0499] The server initializes the image generation device and generates a virtual subject using a generation AI model. It takes prompt text for each health domain (e.g., "Fitness Instructor Character") as input. The server inputs the prompts into the generation AI model and outputs the design data for the virtual subject. Specifically, the server calls the AI ​​model's API to retrieve the generated image data.

[0500] Step 2:

[0501] Users access the application using their device and input their health goals and activity information. This activity information includes, for example, calorie intake and exercise status. The device sends the input data to the server. Specifically, when a user enters data into the interface and presses the "Send" button, the data is uploaded to the server.

[0502] Step 3:

[0503] The server analyzes received user information using data analysis tools. Input includes health goals and activity information sent from the terminal. The server executes a Python script and outputs the user's health status and challenges as analysis results. Specifically, the server's analysis script processes the user's data and identifies areas for improvement.

[0504] Step 4:

[0505] The server generates health support content optimized for the user based on the analysis results. It uses health status assessments and goal setting as input. The server generates health support content and provides a one-week meal plan and exercise program as output. Specifically, logic runs within the server to build a personalized health plan.

[0506] Step 5:

[0507] The generated content is presented to the user by a virtual entity via the device. The input is personalized content from the server. The device displays the virtual entity and provides interactive feedback to the user. Specifically, the virtual entity displays messages such as "Let's achieve today's goal!" on the device's display.

[0508] Step 6:

[0509] The server monitors the user's ongoing progress and generates rewards when goals are achieved. Inputs include the user's activity history and goal achievement status. The server generates reward information and provides rewards to the user as output. Specifically, the server cross-checks the user's progress data and adds points according to their achievement status.

[0510] (Application Example 1)

[0511] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0512] In modern society, individual health management is highly valued, but there is a lack of easily accessible personalized health support. Traditional methods require information gathering through visits to specialists or books, making it difficult to maintain motivation towards daily health goals. To solve these problems, there is a need for a system that allows users to receive personalized health advice and exercise suggestions through a virtual character.

[0513] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0514] In this invention, the server includes means for generating a virtual character specialized in health support using an image generation mechanism, means for acquiring health-related goals and information from the user, and means for analyzing the acquired information and providing personalized health support. As a result, the user can easily receive personalized health plans and exercise suggestions through the virtual character, enabling them to continue daily health management and maintain motivation.

[0515] An "image generation mechanism" is a system that generates virtual visual representations using specific algorithms and techniques.

[0516] A "virtual character" is a character in the form of a person or animal, generated from digital data, that serves a role in providing specific functions or information.

[0517] A "user" is an individual who uses this system to set their own health management goals and provides information.

[0518] An "information processing device" is a device such as a computer or server that analyzes acquired data and derives specific results.

[0519] A "user device" is a terminal device that allows the user to receive information and interact with a virtual character.

[0520] A "notification function" is a system feature that communicates pre-set alerts and reminders to the user.

[0521] A "challenge" refers to a specific task or initiative designed to help users achieve their health goals.

[0522] The system for realizing this invention operates by coordinating multiple hardware and software components. The main hardware components include a server for information processing and a terminal device used by the user. The terminal device is a mobile device such as a smartphone or tablet, providing the user interface. The server utilizes software platforms such as TensorFlow and DALL-E to perform data analysis and image generation.

[0523] The server first generates a virtual character specifically for health support using an image generation mechanism. Using the DALL-E generation AI model, it visualizes a personalized character tailored to the user's health status and goals. Next, it sends health-related data obtained from the user to the server. This information includes the user's daily exercise and diet records, as well as their mental state.

[0524] The server analyzes the received data using TensorFlow and develops an optimal health support plan for the user. This plan includes specific exercise suggestions and dietary advice, which are provided to the user through a virtual character. A user interface is built using Flutter so that the user can receive and visually confirm this information on their device.

[0525] Furthermore, the server monitors the user's progress toward their health goals and automatically generates notifications and new challenges tailored to those goals. This supports the user in continuing to manage their health and maintaining their motivation.

[0526] For example, if a user requests meditation for relaxation, a virtual character will create an original meditation plan and guide the user through it. An example of a prompt would be: "Generate a suitable virtual character based on the user's desired health goals and provide personalized health support. For example, how do I generate a virtual instructor character for a user who wants meditation to relieve stress?"

[0527] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0528] Step 1:

[0529] Users input health goals and daily data using a device. This input data includes exercise levels, diet, and mental state. The device then sends the entered data to a server.

[0530] Step 2:

[0531] The server analyzes the received data. This analysis utilizes machine learning algorithms based on TensorFlow. As a result of the data analysis, the user's current health status and progress toward goals are quantified.

[0532] Step 3:

[0533] Based on the analysis results, the server uses the DALL-E AI model to generate a virtual character specialized in health support. The input is the analysis results, and the output is a visual representation of a character suitable for the user.

[0534] Step 4:

[0535] The server develops a health support plan. It generates a personalized plan for the user, including exercise suggestions and dietary advice. This support plan is generated using analysis results as input and output as plan data.

[0536] Step 5:

[0537] The terminal displays a virtual character and support plan received from the server. Using Flutter, a user interface is built that allows the user to interact with the character and provides support information visually.

[0538] Step 6:

[0539] Users implement the support plan in their daily lives and report the results to the server via their device. The user's results are sent to the server and become input data for the next analysis cycle.

[0540] Step 7:

[0541] The server monitors the user's progress and automatically generates new challenges and notifications. It uses the analyzed progress data as input to output appropriate reminders and new health challenges.

[0542] Step 8:

[0543] The device provides users with generated notifications and challenges to help them stay motivated. Users review these and move on to their next health goal.

[0544] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0545] This invention is a system that provides personalized health support to users using a virtual character that combines an image generation engine and an emotion engine. Its specific form is described below.

[0546] The server initializes the image generation engine to generate virtual characters corresponding to multiple health specialties. These characters incorporate designs tailored to areas such as nutrition, fitness, and mental health. The generated virtual characters have visuals and personas for interacting with the user.

[0547] The device provides users with a means to access applications and input their health goals and daily activity data. Users can record data such as eating habits, exercise levels, mental state, and sleep information. The device transmits this information to a server.

[0548] The server analyzes received user data and automatically generates personalized health support content. Furthermore, it uses an emotion engine to recognize emotions from the user's facial expressions and voice, and adjusts the character's response accordingly. This ensures that reliable advice is provided that is tailored to the user's emotional state.

[0549] For example, if the emotion engine recognizes a user's frustration, the server generates instructions introducing relaxation techniques and stress reduction methods. Conversely, if positive emotions are recognized, it provides content that motivates the user to set even higher goals.

[0550] The device displays content retrieved from the server to the user through a virtual character. The character suggests reminders and new challenges to the user based on their daily health activities and progress towards their goals.

[0551] Users aim to achieve their goals by continuing their daily activities and recording their progress on their devices. The emotion engine continuously monitors their emotional state, providing long-term insights into the user's mental health.

[0552] Thus, the present invention provides advanced personalization functions that take into account the user's emotional state, and has a form that enables more effective health support.

[0553] The following describes the processing flow.

[0554] Step 1:

[0555] The server uses an image generation engine to generate virtual characters corresponding to each area of ​​expertise. These characters will have visual designs and personas tailored to the user's needs.

[0556] Step 2:

[0557] The device accepts users to input their health goals and daily health data. Users log in to their account and enter their calorie intake, exercise history, stress levels, and sleep data.

[0558] Step 3:

[0559] The device transmits health data acquired from the user to the server. The data is sent using a secure protocol and stored on the server.

[0560] Step 4:

[0561] The server analyzes the received health data. This analysis compares the current data with the set health goals to determine how well the user is achieving those goals.

[0562] Step 5:

[0563] The server further uses an emotion engine to analyze the user's facial expressions and voice transmitted from the device, recognizing their current emotional state. This information is then incorporated into health support content.

[0564] Step 6:

[0565] The server generates personalized health support content based on the user's health status and perceived emotions. For example, if stress is detected, relaxation techniques are suggested; if positive emotions are detected, new challenges are offered.

[0566] Step 7:

[0567] The server sends the generated health support content to the terminal. This content is displayed to the user through a virtual character.

[0568] Step 8:

[0569] The virtual character interacts with the user and supports their daily activities. The character provides reminders and new challenges based on progress, encouraging the user to achieve their health goals.

[0570] Step 9:

[0571] Users continue their daily activities through their devices and record their progress toward their goals. This allows the server to accumulate long-term data, improving the accuracy of analysis by the sentiment engine.

[0572] Step 10:

[0573] The server will use users' past emotional and health data to improve future support content, enabling the provision of more accurate health support.

[0574] (Example 2)

[0575] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0576] In recent years, the importance of health management has increased significantly, leading to a growing demand for personalized health support. However, conventional health support systems have struggled to personalize services while adequately considering the emotional state of individual users, failing to provide optimal support. Furthermore, they often only provide general information, lacking specific feedback on individual health goals and progress. As a result, there is a challenge in motivating users to continue managing their health over the long term.

[0577] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0578] In this invention, the server includes means for generating virtual characters specialized in multiple fields using image generation means, means for analyzing data acquired using a generation AI model and providing personalized health support, and means for evaluating and adjusting the user's emotional state using emotion recognition technology. This makes it possible to provide personalized health support optimized for each individual user and to provide feedback that is in line with the user's emotional state.

[0579] "Image generation means" refers to a device or technology that generates virtual characters specialized in multiple fields.

[0580] A "virtual character" refers to a digital character whose visuals and persona are designed to suit a specific field, and which forms the basis of interaction with the user.

[0581] "Acquired data" refers to information about health goals and daily activities provided by users.

[0582] A "generative AI model" refers to a computational model that uses artificial intelligence to generate new information or instructions based on given data.

[0583] "Personalized health support" refers to customized health advice or content provided based on a user's individual data and condition.

[0584] "Emotion recognition technology" refers to technology that analyzes and identifies a user's emotional state from their facial expressions, voice, and other actions.

[0585] A "terminal" refers to a digital device used by a user, specifically hardware that receives and displays information from a server.

[0586] A "reminder" refers to a prompt or notification set to support a user in achieving their health goals.

[0587] "New challenges" refer to new tasks or goals that are provided to users based on their progress.

[0588] This invention is a health support system in which servers, terminals, and users work together in coordination.

[0589] The server first generates virtual characters using image generation methods. This involves using graphic software and image generation engines to create character designs tailored to specific health fields. For example, it incorporates visual elements specific to nutrition, fitness, and mental health. The server then utilizes a generative AI model to collect and analyze the user's health data. This model learns patterns from, for example, the user's diet and exercise history, and generates personalized health support.

[0590] The device functions as a platform for users to input health information. Through applications on smartphones and tablets, users can record daily activity data (e.g., diet, exercise, sleep, emotional state). The entered data is sent to a server and used for necessary analysis.

[0591] Users utilize health support provided through a virtual character displayed on their device. The character offers personalized advice and reminders to help maintain motivation for health management. In particular, emotion recognition technology assesses the user's emotional state in real time and provides corresponding feedback. This process enables effective health support tailored to the user's emotional state.

[0592] As a concrete example, if a user feels they are not getting enough exercise, a prompt message generated by a generative AI model might be: "Check the user's exercise history and suggest a simple exercise plan for three times a week." This would give the user a concrete action plan, making it easier to work towards their health goals.

[0593] This system provides personalized health support to users and takes their emotional state into consideration, enabling long-term health management.

[0594] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0595] Step 1:

[0596] The server initializes the image generation system and generates a virtual character. It incorporates design elements tailored to multiple areas related to the user's health (e.g., nutrition, fitness, mental health). The input includes character design information for each area, and the output is a virtual character. Specifically, the image generation engine is used to construct the character's visual appearance and persona.

[0597] Step 2:

[0598] Users input daily health information through their devices. This includes data such as diet, exercise levels, sleep duration, and emotional state. The entered data is acquired through application forms and sensors and sent to a server as a digital record. Specifically, users input data by operating their smartphone's touchscreen or using voice input.

[0599] Step 3:

[0600] The server receives user health data sent from the terminal and begins data analysis. Based on the input data, it generates personalized health support content using a generative AI model. As output, it generates personalized advice and reminders for the user. Specifically, it prompts the AI ​​model with a message such as "Generate daily health behavior suggestions based on the user's input data" and receives a response.

[0601] Step 4:

[0602] The server uses emotion recognition technology to evaluate the user's emotional state. It extracts emotions from the user's facial expression data and voice, and adjusts the feedback accordingly. Input includes the user's real-time facial image and voice data, and output is an evaluation of the emotional state. Specifically, the emotion analysis engine processes the image and voice data and calculates an emotion score.

[0603] Step 5:

[0604] The device displays personalized content provided by the server to the user through a virtual character. Input includes health support instructions from the server, and output is presented to the user visually and audibly. Specifically, the character appears on the device's display and uses speech synthesis to convey recommendations to the user.

[0605] Step 6:

[0606] Users adjust their daily health behaviors based on instructions and advice from a virtual character. They modify their action plan based on input and implement the improved health behaviors as output. Specifically, users incorporate the suggested actions into their real lives and record their progress again on the device. This feedback loop optimizes the user's health management.

[0607] (Application Example 2)

[0608] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0609] In the fields of health management and fitness, providing personalized support tailored to the individual needs and emotional states of users is a challenging task. Furthermore, there is a lack of interactive systems that can dynamically respond to users' emotions, in addition to static information provision. In this context, there is a growing need for health support systems with advanced personalization capabilities that take users' emotional states into account.

[0610] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0611] In this invention, the server includes means for generating virtual characters specialized in multiple domains using an image generation module, means for acquiring health-related goals and data from users through the virtual characters, means for analyzing the acquired data in a central computing device and customizing the health support provided by the virtual characters for each user, and means for recognizing emotions from the user's facial expressions and voice using an emotion analysis engine and adjusting the virtual characters' responses according to the emotional state. This enables appropriate and interactive health support for users that is tailored to their individual circumstances and emotions.

[0612] An "image generation module" is a software component used to generate visual characters related to a specific area.

[0613] A "virtual character" is a digital agent generated by an image generation module and designed to interact with the user.

[0614] The "central computing unit" is a central processing unit that analyzes acquired user data and personalizes support information.

[0615] An "emotion analysis engine" is a technology that analyzes a user's facial expressions and voice to recognize their emotional state.

[0616] "Support information" refers to advice and instructions provided to users to help them achieve their health goals and improve their motivation.

[0617] A "health support system" is a system that supports users' health management and provides support through an optimized approach tailored to individual needs.

[0618] In this invention, the server first uses an image generation module to generate a virtual character tailored to the user's purpose. This virtual character is designed to correspond to multiple areas of health management. Subsequently, the user can input health-related goals and daily activity data using a terminal. This includes data such as diet, exercise levels, mental state, and sleep information. This data is transmitted to the server and analyzed.

[0619] The server utilizes a central computing device to reconstruct acquired data into personalized health support information for each individual user. This support information includes advice and challenges tailored to the user's progress and emotional state. Furthermore, an emotion analysis engine is used to analyze emotional data from the user's facial expressions and voice, dynamically adjusting the virtual character's responses.

[0620] Through virtual characters displayed on smartphones and tablets, users can receive reminders and goal setting to help them continue their daily health activities. For example, if a user feels like relaxing after exercise, the character will suggest a 10-minute stretching routine. Conversely, if the user is in a positive emotional state, the character will suggest a new exercise program.

[0621] Throughout this entire system, long-term mental health support is possible based on progress data recorded on the terminal and data from the emotion analysis engine.

[0622] (Specific example)

[0623] A gym user, wanting to relax after their workout, enters their daily health status into a terminal. In response, a virtual character suggests, "Great job! You seem a little sluggish today, but let's refresh ourselves with 10 minutes of stretching!" The system also recognizes the user's enjoyment from their facial expressions and provides information about fitness events for the following weekend.

[0624] (Example of prompts for a generative AI model)

[0625] "Please generate an emotional, interactive dialogue-style script in which a virtual character suggests ways to relax after exercise, based on the user's health data and emotional state."

[0626] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0627] Step 1:

[0628] Users input their health goals and daily activity data using a device. This input includes information such as diet, exercise levels, mental state, and sleep information. The device collects this data and sends it to a server. The output is a collection of user data.

[0629] Step 2:

[0630] The server analyzes the received user data. This analysis utilizes a central computing system to assess the user's health status and generate personalized support information. During this process, a generating AI model dynamically uses prompts to create draft advice. The output is personalized health support information for each user.

[0631] Step 3:

[0632] The server invokes an image generation module to generate a virtual character based on the user's health status and goals. Each character has elements corresponding to a specific health area. Based on the generated character, advice for the user is visually represented. The output is a digital character.

[0633] Step 4:

[0634] The server uses an emotion analysis engine to analyze the user's facial expressions and voice. The input is real-time audio and visual data. Based on the analysis results, the server evaluates the user's emotional state and adjusts the virtual character's response. The output of this step is interaction information based on the emotional state.

[0635] Step 5:

[0636] The device displays health support information and a virtual character received from the server to the user. This allows the user to receive personalized reminders and advice from the character. New challenges and motivational content tailored to daily activities and emotions are also displayed. The output is an interactive user interface.

[0637] Through these steps, users will be able to continuously receive personalized advice tailored to their health condition in real time.

[0638] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0639] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0640] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0641] [Fourth Embodiment]

[0642] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0643] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0644] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0645] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0646] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0647] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0648] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0649] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0650] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0651] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0652] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0653] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0654] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0655] This invention realizes a system that provides personalized health support to individual users by utilizing virtual characters generated using an image generation engine. The embodiments are described in detail below.

[0656] The server initializes the image generation engine and creates virtual characters specializing in various health fields. This provides users with characters that address areas such as nutrition, fitness, mental health, stress management, and sleep improvement.

[0657] Users access the application using their device, set health goals, and input daily activity data. This information includes calorie intake, exercise status, mental state, stress levels, and sleep quality. The device then sends this data to the server.

[0658] The server analyzes the received user data and generates health support content tailored to the user's current state and goals. For example, the server personalizes a week's worth of meal plans and exercise programs based on the goals set by the user.

[0659] The generated advice and challenges are sent to the device and presented to the user through a virtual character. The device visually displays this when the user opens the application, and the character provides support by interacting with the user.

[0660] For example, if a user aims to lose weight, the server will suggest calorie management for meals and exercises to increase calorie expenditure. A virtual character will send daily motivational messages and support the user in completing their set health challenges.

[0661] Furthermore, the server monitors the user's progress and provides rewards each time a goal is achieved, thus maintaining motivation. This reward system makes it easier for users to continue managing their health in a gamified way.

[0662] Thus, this invention provides an effective form that offers continuous health support to users and contributes to improving their lifestyles.

[0663] The following describes the processing flow.

[0664] Step 1:

[0665] The server uses an image generation engine to create virtual characters specialized in each field. This includes visual design and persona creation for each character.

[0666] Step 2:

[0667] Users access the application from their device and enter their profile information and health goals. They also record daily health data such as their diet, exercise level, and sleep duration.

[0668] Step 3:

[0669] The terminal sends the entered user data to the server. The data is encrypted and transmitted securely.

[0670] Step 4:

[0671] The server analyzes the received user data. This analysis includes comparing the user's current health status with their set goals.

[0672] Step 5:

[0673] The server generates personalized health support content based on the analysis results. This content includes daily activity plans, meal suggestions, and guidelines for improving mental health.

[0674] Step 6:

[0675] The generated support content is sent from the server to the device. This may include real-time feedback.

[0676] Step 7:

[0677] The device displays the content through a virtual character so that the user can review it. The character provides advice and challenges through interaction with the user.

[0678] Step 8:

[0679] Users perform their daily activities according to the advice and challenges presented. Furthermore, continuous monitoring is possible by recording progress and achievements on the device.

[0680] Step 9:

[0681] The server tracks user progress and updates content as needed. It may also provide users with new challenges or reminders to help them achieve their goals.

[0682] Step 10:

[0683] When users achieve their goals, they receive rewards through their devices. This helps them stay motivated and continue healthy behaviors in a gamified way.

[0684] (Example 1)

[0685] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0686] In modern society, while awareness of personal health management is increasing, consistent health management is difficult due to busy daily lives. In particular, the lack of personalization tailored to individual needs is a challenge. It has been found that conventional systems have difficulty providing effective health support tailored to individuals, and that maintaining motivation is difficult.

[0687] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0688] In this invention, the server includes means for generating a virtual entity adapted to various domains using an image generation device, means for acquiring health-related objectives and information from a user through the virtual entity, and means for analyzing the acquired information in a processing device and personalizing the health support provided by the virtual entity. This enables personalized health support for individual users and continuous health management.

[0689] An "image generation device" is a device that creates visual information based on input digital instructions, and generates display elements according to specific conditions or themes.

[0690] A "virtual entity" is a character or agent constructed digitally that interacts with users by having a specific role or function.

[0691] "User information" refers to health-related data and goals provided by users, which form the basis for providing individualized services and suggestions.

[0692] A "processing device" is a device used for calculating and analyzing data. It performs analysis and processing based on information obtained from users and generates results.

[0693] "Personalized support" refers to advice and programs customized according to the user's characteristics and needs, meaning health support optimized for each individual user.

[0694] "Rewards" are incentives or rewards given to users when they achieve a specific goal, and they are elements that increase motivation and encourage continued effort.

[0695] A "challenge" is a specific action goal or challenge that the user should aim to achieve, and it is set up to support the process of improving health.

[0696] This invention is a system for personalizing individual health support, enabling continuous health management for users. The embodiments of the system will be described in detail below.

[0697] The server uses an image generation device and generative AI models such as Stable Diffusion and Midjourney to generate virtual entities adapted to diverse areas such as nutrition, fitness, mental health, stress management, and sleep improvement. These virtual entities incorporate design elements tailored to each health area and interact naturally with the user.

[0698] Users access the application from their smartphones or tablets using their devices. Through the device's interface, users set health goals and input daily activity information such as calorie intake, exercise levels, mental state, stress levels, and sleep quality. The device then transmits this information to the server.

[0699] The server analyzes the received user information using data analysis tools such as Python and R, and generates personalized health support tailored to the user's condition and goals. For example, based on a user's goal of "consuming 1,500 kcal per day and jogging three times a week," the server creates a healthy meal plan and exercise program for one week.

[0700] The generated support content is delivered to the user visually through the device. A virtual entity sends motivational messages such as "Let's do our best today!" to support the user and encourage actions toward achieving their goals.

[0701] Furthermore, the server continuously monitors the user's progress and provides rewards such as points and badges each time a goal is achieved. This allows users to engage in health management in a gamified way.

[0702] Specific examples of prompts include "Please provide a healthy meal plan" and "Create a message to motivate me to jog."

[0703] In this way, this invention enables the provision of personalized health support to users and efficient lifestyle improvements.

[0704] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0705] Step 1:

[0706] The server initializes the image generation device and generates a virtual subject using a generation AI model. It takes prompt text for each health domain (e.g., "Fitness Instructor Character") as input. The server inputs the prompts into the generation AI model and outputs the design data for the virtual subject. Specifically, the server calls the AI ​​model's API to retrieve the generated image data.

[0707] Step 2:

[0708] Users access the application using their device and input their health goals and activity information. This activity information includes, for example, calorie intake and exercise status. The device sends the input data to the server. Specifically, when a user enters data into the interface and presses the "Send" button, the data is uploaded to the server.

[0709] Step 3:

[0710] The server analyzes received user information using data analysis tools. Input includes health goals and activity information sent from the terminal. The server executes a Python script and outputs the user's health status and challenges as analysis results. Specifically, the server's analysis script processes the user's data and identifies areas for improvement.

[0711] Step 4:

[0712] The server generates health support content optimized for the user based on the analysis results. It uses health status assessments and goal setting as input. The server generates health support content and provides a one-week meal plan and exercise program as output. Specifically, logic runs within the server to build a personalized health plan.

[0713] Step 5:

[0714] The generated content is presented to the user by a virtual entity via the device. The input is personalized content from the server. The device displays the virtual entity and provides interactive feedback to the user. Specifically, the virtual entity displays messages such as "Let's achieve today's goal!" on the device's display.

[0715] Step 6:

[0716] The server monitors the user's ongoing progress and generates rewards when goals are achieved. Inputs include the user's activity history and goal achievement status. The server generates reward information and provides rewards to the user as output. Specifically, the server cross-checks the user's progress data and adds points according to their achievement status.

[0717] (Application Example 1)

[0718] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0719] In modern society, individual health management is highly valued, but there is a lack of easily accessible personalized health support. Traditional methods require information gathering through visits to specialists or books, making it difficult to maintain motivation towards daily health goals. To solve these problems, there is a need for a system that allows users to receive personalized health advice and exercise suggestions through a virtual character.

[0720] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0721] In this invention, the server includes means for generating a virtual character specialized in health support using an image generation mechanism, means for acquiring health-related goals and information from the user, and means for analyzing the acquired information and providing personalized health support. As a result, the user can easily receive personalized health plans and exercise suggestions through the virtual character, enabling them to continue daily health management and maintain motivation.

[0722] An "image generation mechanism" is a system that generates virtual visual representations using specific algorithms and techniques.

[0723] A "virtual character" is a character in the form of a person or animal, generated from digital data, that serves a role in providing specific functions or information.

[0724] A "user" is an individual who uses this system to set their own health management goals and provides information.

[0725] An "information processing device" is a device such as a computer or server that analyzes acquired data and derives specific results.

[0726] A "user device" is a terminal device that allows the user to receive information and interact with a virtual character.

[0727] A "notification function" is a system feature that communicates pre-set alerts and reminders to the user.

[0728] A "challenge" refers to a specific task or initiative designed to help users achieve their health goals.

[0729] The system for realizing this invention operates by coordinating multiple hardware and software components. The main hardware components include a server for information processing and a terminal device used by the user. The terminal device is a mobile device such as a smartphone or tablet, providing the user interface. The server utilizes software platforms such as TensorFlow and DALL-E to perform data analysis and image generation.

[0730] The server first generates a virtual character specifically for health support using an image generation mechanism. Using the DALL-E generation AI model, it visualizes a personalized character tailored to the user's health status and goals. Next, it sends health-related data obtained from the user to the server. This information includes the user's daily exercise and diet records, as well as their mental state.

[0731] The server analyzes the received data using TensorFlow and develops an optimal health support plan for the user. This plan includes specific exercise suggestions and dietary advice, which are provided to the user through a virtual character. A user interface is built using Flutter so that the user can receive and visually confirm this information on their device.

[0732] Furthermore, the server monitors the user's progress toward their health goals and automatically generates notifications and new challenges tailored to those goals. This supports the user in continuing to manage their health and maintaining their motivation.

[0733] For example, if a user requests meditation for relaxation, a virtual character will create an original meditation plan and guide the user through it. An example of a prompt would be: "Generate a suitable virtual character based on the user's desired health goals and provide personalized health support. For example, how do I generate a virtual instructor character for a user who wants meditation to relieve stress?"

[0734] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0735] Step 1:

[0736] Users input health goals and daily data using a device. This input data includes exercise levels, diet, and mental state. The device then sends the entered data to a server.

[0737] Step 2:

[0738] The server analyzes the received data. This analysis utilizes machine learning algorithms based on TensorFlow. As a result of the data analysis, the user's current health status and progress toward goals are quantified.

[0739] Step 3:

[0740] Based on the analysis results, the server uses the DALL-E AI model to generate a virtual character specialized in health support. The input is the analysis results, and the output is a visual representation of a character suitable for the user.

[0741] Step 4:

[0742] The server develops a health support plan. It generates a personalized plan for the user, including exercise suggestions and dietary advice. This support plan is generated using analysis results as input and output as plan data.

[0743] Step 5:

[0744] The terminal displays a virtual character and support plan received from the server. Using Flutter, a user interface is built that allows the user to interact with the character and provides support information visually.

[0745] Step 6:

[0746] Users implement the support plan in their daily lives and report the results to the server via their device. The user's results are sent to the server and become input data for the next analysis cycle.

[0747] Step 7:

[0748] The server monitors the user's progress and automatically generates new challenges and notifications. It uses the analyzed progress data as input to output appropriate reminders and new health challenges.

[0749] Step 8:

[0750] The device provides users with generated notifications and challenges to help them stay motivated. Users review these and move on to their next health goal.

[0751] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0752] This invention is a system that provides personalized health support to users using a virtual character that combines an image generation engine and an emotion engine. Its specific form is described below.

[0753] The server initializes the image generation engine to generate virtual characters corresponding to multiple health specialties. These characters incorporate designs tailored to areas such as nutrition, fitness, and mental health. The generated virtual characters have visuals and personas for interacting with the user.

[0754] The device provides users with a means to access applications and input their health goals and daily activity data. Users can record data such as eating habits, exercise levels, mental state, and sleep information. The device transmits this information to a server.

[0755] The server analyzes received user data and automatically generates personalized health support content. Furthermore, it uses an emotion engine to recognize emotions from the user's facial expressions and voice, and adjusts the character's response accordingly. This ensures that reliable advice is provided that is tailored to the user's emotional state.

[0756] For example, if the emotion engine recognizes a user's frustration, the server generates instructions introducing relaxation techniques and stress reduction methods. Conversely, if positive emotions are recognized, it provides content that motivates the user to set even higher goals.

[0757] The device displays content retrieved from the server to the user through a virtual character. The character suggests reminders and new challenges to the user based on their daily health activities and progress towards their goals.

[0758] Users aim to achieve their goals by continuing their daily activities and recording their progress on their devices. The emotion engine continuously monitors their emotional state, providing long-term insights into the user's mental health.

[0759] Thus, the present invention provides advanced personalization functions that take into account the user's emotional state, and has a form that enables more effective health support.

[0760] The following describes the processing flow.

[0761] Step 1:

[0762] The server uses an image generation engine to generate virtual characters corresponding to each area of ​​expertise. These characters will have visual designs and personas tailored to the user's needs.

[0763] Step 2:

[0764] The device accepts users to input their health goals and daily health data. Users log in to their account and enter their calorie intake, exercise history, stress levels, and sleep data.

[0765] Step 3:

[0766] The device transmits health data acquired from the user to the server. The data is sent using a secure protocol and stored on the server.

[0767] Step 4:

[0768] The server analyzes the received health data. This analysis compares the current data with the set health goals to determine how well the user is achieving those goals.

[0769] Step 5:

[0770] The server further uses an emotion engine to analyze the user's facial expressions and voice transmitted from the device, recognizing their current emotional state. This information is then incorporated into health support content.

[0771] Step 6:

[0772] The server generates personalized health support content based on the user's health status and perceived emotions. For example, if stress is detected, relaxation techniques are suggested; if positive emotions are detected, new challenges are offered.

[0773] Step 7:

[0774] The server sends the generated health support content to the terminal. This content is displayed to the user through a virtual character.

[0775] Step 8:

[0776] The virtual character interacts with the user and supports their daily activities. The character provides reminders and new challenges based on progress, encouraging the user to achieve their health goals.

[0777] Step 9:

[0778] Users continue their daily activities through their devices and record their progress toward their goals. This allows the server to accumulate long-term data, improving the accuracy of analysis by the sentiment engine.

[0779] Step 10:

[0780] The server will use users' past emotional and health data to improve future support content, enabling the provision of more accurate health support.

[0781] (Example 2)

[0782] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0783] In recent years, the importance of health management has increased significantly, leading to a growing demand for personalized health support. However, conventional health support systems have struggled to personalize services while adequately considering the emotional state of individual users, failing to provide optimal support. Furthermore, they often only provide general information, lacking specific feedback on individual health goals and progress. As a result, there is a challenge in motivating users to continue managing their health over the long term.

[0784] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0785] In this invention, the server includes means for generating virtual characters specialized in multiple fields using image generation means, means for analyzing data acquired using a generation AI model and providing personalized health support, and means for evaluating and adjusting the user's emotional state using emotion recognition technology. This makes it possible to provide personalized health support optimized for each individual user and to provide feedback that is in line with the user's emotional state.

[0786] "Image generation means" refers to a device or technology that generates virtual characters specialized in multiple fields.

[0787] A "virtual character" refers to a digital character whose visuals and persona are designed to suit a specific field, and which forms the basis of interaction with the user.

[0788] "Acquired data" refers to information about health goals and daily activities provided by users.

[0789] A "generative AI model" refers to a computational model that uses artificial intelligence to generate new information or instructions based on given data.

[0790] "Personalized health support" refers to customized health advice or content provided based on a user's individual data and condition.

[0791] "Emotion recognition technology" refers to technology that analyzes and identifies a user's emotional state from their facial expressions, voice, and other actions.

[0792] A "terminal" refers to a digital device used by a user, specifically hardware that receives and displays information from a server.

[0793] A "reminder" refers to a prompt or notification set to support a user in achieving their health goals.

[0794] "New challenges" refer to new tasks or goals that are provided to users based on their progress.

[0795] This invention is a health support system in which servers, terminals, and users work together in coordination.

[0796] The server first generates virtual characters using image generation methods. This involves using graphic software and image generation engines to create character designs tailored to specific health fields. For example, it incorporates visual elements specific to nutrition, fitness, and mental health. The server then utilizes a generative AI model to collect and analyze the user's health data. This model learns patterns from, for example, the user's diet and exercise history, and generates personalized health support.

[0797] The device functions as a platform for users to input health information. Through applications on smartphones and tablets, users can record daily activity data (e.g., diet, exercise, sleep, emotional state). The entered data is sent to a server and used for necessary analysis.

[0798] Users utilize health support provided through a virtual character displayed on their device. The character offers personalized advice and reminders to help maintain motivation for health management. In particular, emotion recognition technology assesses the user's emotional state in real time and provides corresponding feedback. This process enables effective health support tailored to the user's emotional state.

[0799] As a concrete example, if a user feels they are not getting enough exercise, a prompt message generated by a generative AI model might be: "Check the user's exercise history and suggest a simple exercise plan for three times a week." This would give the user a concrete action plan, making it easier to work towards their health goals.

[0800] This system provides personalized health support to users and takes their emotional state into consideration, enabling long-term health management.

[0801] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0802] Step 1:

[0803] The server initializes the image generation system and generates a virtual character. It incorporates design elements tailored to multiple areas related to the user's health (e.g., nutrition, fitness, mental health). The input includes character design information for each area, and the output is a virtual character. Specifically, the image generation engine is used to construct the character's visual appearance and persona.

[0804] Step 2:

[0805] Users input daily health information through their devices. This includes data such as diet, exercise levels, sleep duration, and emotional state. The entered data is acquired through application forms and sensors and sent to a server as a digital record. Specifically, users input data by operating their smartphone's touchscreen or using voice input.

[0806] Step 3:

[0807] The server receives user health data sent from the terminal and begins data analysis. Based on the input data, it generates personalized health support content using a generative AI model. As output, it generates personalized advice and reminders for the user. Specifically, it prompts the AI ​​model with a message such as "Generate daily health behavior suggestions based on the user's input data" and receives a response.

[0808] Step 4:

[0809] The server uses emotion recognition technology to evaluate the user's emotional state. It extracts emotions from the user's facial expression data and voice, and adjusts the feedback accordingly. Input includes the user's real-time facial image and voice data, and output is an evaluation of the emotional state. Specifically, the emotion analysis engine processes the image and voice data and calculates an emotion score.

[0810] Step 5:

[0811] The device displays personalized content provided by the server to the user through a virtual character. Input includes health support instructions from the server, and output is presented to the user visually and audibly. Specifically, the character appears on the device's display and uses speech synthesis to convey recommendations to the user.

[0812] Step 6:

[0813] Users adjust their daily health behaviors based on instructions and advice from a virtual character. They modify their action plan based on input and implement the improved health behaviors as output. Specifically, users incorporate the suggested actions into their real lives and record their progress again on the device. This feedback loop optimizes the user's health management.

[0814] (Application Example 2)

[0815] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0816] In the fields of health management and fitness, providing personalized support tailored to the individual needs and emotional states of users is a challenging task. Furthermore, there is a lack of interactive systems that can dynamically respond to users' emotions, in addition to static information provision. In this context, there is a growing need for health support systems with advanced personalization capabilities that take users' emotional states into account.

[0817] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0818] In this invention, the server includes means for generating virtual characters specialized in multiple domains using an image generation module, means for acquiring health-related goals and data from users through the virtual characters, means for analyzing the acquired data in a central computing device and customizing the health support provided by the virtual characters for each user, and means for recognizing emotions from the user's facial expressions and voice using an emotion analysis engine and adjusting the virtual characters' responses according to the emotional state. This enables appropriate and interactive health support for users that is tailored to their individual circumstances and emotions.

[0819] An "image generation module" is a software component used to generate visual characters related to a specific area.

[0820] A "virtual character" is a digital agent generated by an image generation module and designed to interact with the user.

[0821] The "central computing unit" is a central processing unit that analyzes acquired user data and personalizes support information.

[0822] An "emotion analysis engine" is a technology that analyzes a user's facial expressions and voice to recognize their emotional state.

[0823] "Support information" refers to advice and instructions provided to users to help them achieve their health goals and improve their motivation.

[0824] A "health support system" is a system that supports users' health management and provides support through an optimized approach tailored to individual needs.

[0825] In this invention, the server first uses an image generation module to generate a virtual character tailored to the user's purpose. This virtual character is designed to correspond to multiple areas of health management. Subsequently, the user can input health-related goals and daily activity data using a terminal. This includes data such as diet, exercise levels, mental state, and sleep information. This data is transmitted to the server and analyzed.

[0826] The server utilizes a central computing device to reconstruct acquired data into personalized health support information for each individual user. This support information includes advice and challenges tailored to the user's progress and emotional state. Furthermore, an emotion analysis engine is used to analyze emotional data from the user's facial expressions and voice, dynamically adjusting the virtual character's responses.

[0827] Through virtual characters displayed on smartphones and tablets, users can receive reminders and goal setting to help them continue their daily health activities. For example, if a user feels like relaxing after exercise, the character will suggest a 10-minute stretching routine. Conversely, if the user is in a positive emotional state, the character will suggest a new exercise program.

[0828] Throughout this entire system, long-term mental health support is possible based on progress data recorded on the terminal and data from the emotion analysis engine.

[0829] (Specific example)

[0830] A gym user, wanting to relax after their workout, enters their daily health status into a terminal. In response, a virtual character suggests, "Great job! You seem a little sluggish today, but let's refresh ourselves with 10 minutes of stretching!" The system also recognizes the user's enjoyment from their facial expressions and provides information about fitness events for the following weekend.

[0831] (Example of prompts for a generative AI model)

[0832] "Please generate an emotional, interactive dialogue-style script in which a virtual character suggests ways to relax after exercise, based on the user's health data and emotional state."

[0833] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0834] Step 1:

[0835] Users input their health goals and daily activity data using a device. This input includes information such as diet, exercise levels, mental state, and sleep information. The device collects this data and sends it to a server. The output is a collection of user data.

[0836] Step 2:

[0837] The server analyzes the received user data. This analysis utilizes a central computing system to assess the user's health status and generate personalized support information. During this process, a generating AI model dynamically uses prompts to create draft advice. The output is personalized health support information for each user.

[0838] Step 3:

[0839] The server invokes an image generation module to generate a virtual character based on the user's health status and goals. Each character has elements corresponding to a specific health area. Based on the generated character, advice for the user is visually represented. The output is a digital character.

[0840] Step 4:

[0841] The server uses an emotion analysis engine to analyze the user's facial expressions and voice. The input is real-time audio and visual data. Based on the analysis results, the server evaluates the user's emotional state and adjusts the virtual character's response. The output of this step is interaction information based on the emotional state.

[0842] Step 5:

[0843] The device displays health support information and a virtual character received from the server to the user. This allows the user to receive personalized reminders and advice from the character. New challenges and motivational content tailored to daily activities and emotions are also displayed. The output is an interactive user interface.

[0844] Through these steps, users will be able to continuously receive personalized advice tailored to their health condition in real time.

[0845] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0846] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0847] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0848] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0849] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0850] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0851] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0852] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0853] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0854] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0855] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0856] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0857] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0858] 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.

[0859] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0860] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0861] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0862] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0863] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0864] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0865] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0866] The following is further disclosed regarding the embodiments described above.

[0867] (Claim 1)

[0868] A means of generating virtual characters specialized in multiple fields using an image generation engine,

[0869] A means for obtaining health-related goals and data from the user through the aforementioned virtual character,

[0870] The server includes means for analyzing the acquired data and personalizing the health support provided by the virtual character,

[0871] The means for transmitting and displaying the aforementioned personalized support information on a terminal,

[0872] A means of generating reminders and new challenges based on the user's progress toward their health goals,

[0873] A system that includes this.

[0874] (Claim 2)

[0875] The system according to claim 1, wherein the image generation engine generates virtual characters that incorporate different design elements for each field.

[0876] (Claim 3)

[0877] The system according to claim 1, wherein the server continuously updates the personality and appearance of the virtual character based on the acquired user data.

[0878] "Example 1"

[0879] (Claim 1)

[0880] An image generation device provides means for generating virtual subjects adapted to diverse domains,

[0881] A means of obtaining health-related purposes and information from the user through the aforementioned virtual entity,

[0882] The processing device includes means for analyzing the acquired information and personalizing the health support provided by the virtual entity,

[0883] A means for transmitting the aforementioned personalized support details to the user terminal for visualization,

[0884] A means of generating rewards and new challenges based on the user's progress toward their health goals,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, wherein the image generation device generates a virtual subject that incorporates different design elements for each region.

[0888] (Claim 3)

[0889] The system according to claim 1, wherein the processing device continuously updates the personality and appearance of the virtual entity based on acquired user information.

[0890] "Application Example 1"

[0891] (Claim 1)

[0892] A means for generating virtual characters specialized in multiple domains by an image generation mechanism,

[0893] A means for obtaining health-related goals and information from the user through the aforementioned virtual character,

[0894] An information processing device includes means for analyzing the acquired information and personalizing the health support provided by the virtual character,

[0895] The means for transmitting and displaying the personalized support information to the user device,

[0896] A means of generating notification functions and new challenges based on the user's progress toward their health goals,

[0897] Through the aforementioned virtual character, a means of providing personalized health plans and exercise suggestions, and interactively supporting the user,

[0898] A system that includes this.

[0899] (Claim 2)

[0900] The system according to claim 1, wherein the image generation mechanism generates virtual characters incorporating different design elements for each region, and presents advice and activity plans tailored to the user's situation.

[0901] (Claim 3)

[0902] The system according to claim 1, wherein the information processing device continuously updates the personality and appearance of a virtual character based on acquired user information and provides appropriate health support content.

[0903] "Example 2 of combining an emotion engine"

[0904] (Claim 1)

[0905] A means for generating virtual characters specialized in multiple fields using image generation means,

[0906] A means for obtaining health-related goals and data from the user through the aforementioned virtual character,

[0907] A computing device includes means for analyzing the acquired data and using a generated AI model to personalize the health support provided by the virtual character,

[0908] A means of evaluating the user's emotional state using emotion recognition technology and adjusting the virtual character's response based on that evaluation,

[0909] The means for transmitting and displaying the aforementioned personalized support information on a terminal,

[0910] A means of generating reminders and new challenges based on the user's progress toward their health goals,

[0911] A system that includes this.

[0912] (Claim 2)

[0913] The system according to claim 1, wherein the image generation means generates virtual characters that incorporate different design elements for each field.

[0914] (Claim 3)

[0915] The system according to claim 1, wherein the computing device continuously updates the characteristics and appearance of the virtual character based on acquired user data.

[0916] "Application example 2 of combining emotional engines"

[0917] (Claim 1)

[0918] The image generation module provides a means for generating virtual characters specialized in multiple domains,

[0919] A means for obtaining health-related goals and data from users through the aforementioned virtual character,

[0920] In the central computing device, means for analyzing the acquired data and customizing the health support provided by the virtual character for each user,

[0921] A means for transmitting and displaying the customized support information on a terminal,

[0922] A means of generating instructions and new tasks based on the user's progress toward achieving their health goals,

[0923] An emotion analysis engine recognizes emotions from the user's facial expressions and voice, and adjusts the virtual character's responses according to that emotional state.

[0924] A system that includes this.

[0925] (Claim 2)

[0926] The system according to claim 1, wherein the image generation module generates a virtual character using different design elements for each region.

[0927] (Claim 3)

[0928] The system according to claim 1, wherein the central computing device continuously updates the personality and appearance of the virtual character based on acquired user data and provides real-time interaction. [Explanation of Symbols]

[0929] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of generating virtual characters specialized in multiple fields using an image generation engine, A means for obtaining health-related goals and data from the user through the aforementioned virtual character, The server includes means for analyzing the acquired data and personalizing the health support provided by the virtual character, The means for transmitting and displaying the aforementioned personalized support information on a terminal, A means of generating reminders and new challenges based on the user's progress toward their health goals, A system that includes this.

2. The system according to claim 1, wherein the image generation engine generates virtual characters that incorporate different design elements for each field.

3. The system according to claim 1, wherein the server continuously updates the personality and appearance of the virtual character based on the acquired user data.

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