System

Abstract

A system is provided.SOLUTION: Means for inputting physical characteristics, genetic information, and lifestyle of a user; means for transmitting the input data to a server; means for analyzing health data and generating a virtual health avatar by the server; and means for transmitting and visually displaying the generated virtual health avatar to a user terminal, wherein the user interacts with the virtual health avatar; A system comprising: means for transmitting a question to a server; means for the server to analyze the question and generate an appropriate health behavior plan and advice; means for transmitting the generated advice to a user device and presenting the advice to the user through an avatar; and means for the user to create a health plan and input the health plan to the device.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, many people lack specific advice for managing their own health and intuitive means for assessing health risks. They also find it difficult to maintain motivation to develop and consistently implement health action plans. These problems hinder the effective provision of preventive medicine and personalized healthcare services. The present invention aims to solve these problems and provide support for users to gain a deeper understanding of their own health status and engage in practical health management. [Means for solving the problem]

[0005] The present invention provides a system including a means for inputting a user's physical characteristics, genetic information, and lifestyle habits and a means for transmitting the input data to a server. The server further includes a means for analyzing the health data and generating a virtual health avatar, and a means for transmitting the generated virtual health avatar to a user terminal and visually displaying it. The user can interact with the virtual health avatar and send questions to the server, which analyzes the questions and generates an appropriate health action plan and advice. The generated advice is sent to the user terminal and presented to the user via the avatar. The user can also create a health action plan and input it into the terminal. The input action plan data is stored on the server and monitored. The system also includes a means for providing feedback and motivation through the virtual health avatar and a means for the server to periodically analyze the user's behavioral data and evaluate the progress of the health action plan. The present invention enables users to intuitively understand their own health status and continuously practice specific health behaviors.

[0006] "User" refers to an individual who uses this system.

[0007] "Physical characteristics" refers to information that indicates the user's biological attributes, such as height, weight, and age.

[0008] "Genetic information" refers to data about a user's genes, such as the results of a DNA analysis.

[0009] "Lifestyle habits" refers to behavioral characteristics in a user's daily life, such as diet, exercise, and sleep patterns.

[0010] "Server" refers to a computer system that analyzes health data received from users and generates virtual health avatars.

[0011] A "virtual health avatar" is a digital character generated based on a user's health data, visually representing the user's health status and risks.

[0012] "Terminal" refers to the device (e.g., smartphone or tablet) that a user uses to input data and interact with an avatar.

[0013] "Health data" is a general term for information about a user's physical characteristics, genetic information, and lifestyle habits.

[0014] "Analysis" refers to the process by which the server performs calculations and evaluations based on the user's health data to assess their health status and risks.

[0015] A "health action plan" refers to a plan of specific actions that a user will take to maintain or improve their health.

[0016] "Monitoring" refers to the process of continuously observing and evaluating the implementation of a user's health action plan.

[0017] "Feedback" refers to the assessment and advice provided by the server based on the user's behavior and health status.

[0018] "Motivation" refers to support provided through avatars that motivates users to continue with their health action plans. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6]FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] As an embodiment of the present invention, the processing of the program will be explained below in natural language.

[0041] 1. Data Collection

[0042] Users: Install the application and create an account.

[0043] User: After creating an account, the user enters physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, sleep patterns) into the device.

[0044] Terminal: Sends the entered data to the server.

[0045] 2. Data Analysis

[0046] Server: Stores the received health data in a database.

[0047] Server: Inputs stored health data into the AI ​​model to assess health status and risks.

[0048] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[0049] 3. Avatar generation and display

[0050] Server: Sends the generated virtual health avatar data to the user terminal.

[0051] Terminal: Visually displays the received avatar data.

[0052] Terminal: Notifies the user that the avatar is ready to be displayed.

[0053] 4. Interaction

[0054] User: Initiates a dialogue with the virtual health avatar. For example, the user asks, "I've been feeling tired a lot lately. What should I do?"

[0055] Terminal: Sends the user's question to the server.

[0056] Server: Analyzes the questions and generates appropriate health action plans and advice.

[0057] Server: Sends the generated advice to the user terminal.

[0058] Terminal: Presents advice to the user through an avatar.

[0059] 5. Health action plan development and monitoring

[0060] User: Create a health action plan based on the avatar's advice. For example, create a plan to "jog three times a week."

[0061] User: Enter the health action plan into the terminal.

[0062] Terminal: Sends the input action plan data to the server.

[0063] Server: Saves the action plan data in the database and starts monitoring.

[0064] 6. Feedback and motivation

[0065] Server: Periodically analyzes user behavior data and evaluates the progress of the plan.

[0066] Server: Generates messages that provide feedback and motivation based on progress.

[0067] Server: Sends generated feedback and motivation messages to the devices.

[0068] Terminal: Presents feedback and motivational messages to the user through an avatar.

[0069] Specific examples

[0070] Example 1: Understanding your health status

[0071] User: A 30-year-old man, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[0072] Terminal: Sends input data to the server.

[0073] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[0074] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[0075] Example 2: Creating a Health Action Plan

[0076] User: Asks avatar, "How can I get more exercise?"

[0077] Terminal: Sends the question to the server.

[0078] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[0079] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[0080] User: Accept the advice and develop a health action plan.

[0081] In this way, the present invention provides users with a deeper understanding of their health status and assistance in implementing specific health behaviors.

[0082] The processing flow will be explained below.

[0083] Step 1:

[0084] User: Installs the application and creates an account. Enters personal information and completes account setup.

[0085] Step 2:

[0086] Terminal: Displays an input screen to collect data on physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) based on user input.

[0087] Step 3:

[0088] User: Follow the collection screen and enter the necessary health data, such as height 170cm, weight 70kg, meal frequency, exercise habits, etc.

[0089] Step 4:

[0090] Terminal: Formats the input data and sends it to the server.

[0091] Step 5:

[0092] Server: Stores the received health data in a database.

[0093] Step 6:

[0094] Server: Inputs stored health data into the AI ​​model to assess the user's health status and potential risks.

[0095] Step 7:

[0096] Server: Based on the analysis results, a virtual health avatar specialized for each user is generated.

[0097] Step 8:

[0098] Server: Sends the generated virtual health avatar data to the user terminal.

[0099] Step 9:

[0100] Terminal: Prepare to visually display the received avatar data.

[0101] Step 10:

[0102] Terminal: Sends a notification to the user that the avatar display is complete.

[0103] Step 11:

[0104] User: Starts a conversation with the virtual health avatar displayed on the device. Enters a question or concern into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[0105] Step 12:

[0106] Terminal: Sends the user's question to the server as text data.

[0107] Step 13:

[0108] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[0109] Step 14:

[0110] Server: Sends the generated advice to the user terminal as text data.

[0111] Step 15:

[0112] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[0113] Step 16:

[0114] User: Create a health action plan based on the avatar's advice. For example, enter a plan such as "jog for 30 minutes three times a week."

[0115] Step 17:

[0116] Terminal: Sends the created health action plan data to the server.

[0117] Step 18:

[0118] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[0119] Step 19:

[0120] User: Follows the plan and regularly records their actions (for example, jogging progress) in the app.

[0121] Step 20:

[0122] Terminal: Sends recorded behavioral data to the server.

[0123] Step 21:

[0124] Server: Analyzes the received behavioral data and evaluates the progress of the health behavior plan.

[0125] Step 22:

[0126] Server: Generates feedback and motivational messages based on progress.

[0127] Step 23:

[0128] Server: Sends the generated feedback and motivation messages to the user terminal.

[0129] Step 24:

[0130] Terminal: Presents feedback and motivational messages to the user through an avatar.

[0131] By repeating the above process, users can gain a deeper understanding of their own health status and continuously practice specific health behaviors.

[0132] Example 1

[0133] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0134] In modern society, it is difficult for users to accurately understand their own health status and develop appropriate health action plans. In particular, health management that takes into account individual physical characteristics, genetic information, and lifestyle habits requires specialized knowledge, making it difficult for many users to effectively maintain their health. In addition, existing systems do not adequately provide continuous monitoring, feedback, or motivation, which means that users' health improvements are not sustainable.

[0135] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0136] In this invention, the server includes: a means for inputting a user's physical characteristics, genetic information, and lifestyle habits; a means for transmitting the input data to the server; a means for analyzing the health data and generating a virtual health avatar; a means for transmitting the generated virtual health avatar to a user terminal and visually displaying it; a means for the user to interact with the virtual health avatar and send questions to the server; a means for the server to analyze the questions and generate an appropriate health action plan and advice; a means for transmitting the generated advice to the user terminal and presenting it to the user via the avatar; a means for the user to create a health action plan and input it into the terminal; a means for storing the input action plan data on the server and monitoring it; a means for periodically analyzing the action data and evaluating progress; and a means for transmitting the generated feedback and motivational messages to the user terminal and presenting them to the user via the avatar. This allows the user to accurately understand their own health status and create and implement an effective health action plan based on their individual characteristics. Furthermore, providing continuous feedback and motivation can be expected to have a lasting effect on the user's health improvement.

[0137] "User" refers to a person who uses the system to manage and improve their health.

[0138] "Physical characteristics" refers to data about the user's body, such as height, weight, and age.

[0139] "Genetic information" refers to data related to genetics, such as the results of a user's DNA analysis.

[0140] "Lifestyle habits" refers to data such as diet, exercise, and sleep patterns in a user's daily life.

[0141] "Terminal" refers to an electronic device used by a user, such as a computer, smartphone, or tablet.

[0142] "Server" refers to a computer system that receives, stores, and analyzes data entered by a user and transmits the generated information to the user terminal.

[0143] "Database" refers to an information management system for storing user health data and action plan data.

[0144] "AI model" refers to the artificial intelligence algorithm used by the server to analyze health status.

[0145] "Virtual health avatar" refers to a digital character that visually represents a user's health status.

[0146] A "question" refers to a health-related inquiry that a user makes to the server through a virtual health avatar.

[0147] A "health action plan" refers to a specific action plan that a user sets out to improve their own health.

[0148] "Monitoring" refers to the process by which the server continuously monitors user behavior data and evaluates progress.

[0149] "Feedback" refers to the evaluation and advice provided by the server regarding the user's behavior and health status.

[0150] "Motivational Message" refers to a message of encouragement or encouragement provided by the server to promote improvement in the user's health.

[0151] This invention is a system that helps users accurately understand their own health status and assists them in formulating and implementing effective health action plans. This system consists of a user, a terminal, and a server.

[0152] Data collection

[0153] First, the user installs the application and creates an account. After creating the account, the user enters their physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, sleep patterns) into the device. The device then sends the entered data to the server. This transmission is performed using an HTTP POST request.

[0154] Data analysis

[0155] The server stores the received health data in a database. The stored data is then fed into an AI model (e.g., TensorFlow or PyTorch) to assess health status and risks. The analysis results are then used to generate a personalized virtual health avatar. This avatar is a digital character that visually represents the user's health status.

[0156] Avatar generation and display

[0157] The generated virtual health avatar is sent from the server to the user's device. The device receives this data and visually displays it. Software such as Unity or Unreal Engine is used for display. The device uses push notifications or alert dialogs to notify the user that the avatar is ready to be displayed.

[0158] Interaction

[0159] The user begins a dialogue with the virtual health avatar. For example, if the user asks, "I've been feeling tired lately. What should I do?", this question is sent from the device to the server. The server analyzes the question using a generative AI model (e.g., GPT-3) and generates an appropriate health action plan and advice. The generated advice is sent from the server to the user's device, which then presents it to the user through the avatar.

[0160] Health action plan development and monitoring

[0161] The user creates a health action plan based on the avatar's advice and enters it into the device. For example, the user may plan to "jog three times a week." The entered action plan data is sent from the device to the server and stored in a database. The server continues to monitor this.

[0162] Feedback and motivation

[0163] The server periodically analyzes the user's behavioral data and evaluates the progress of the plan. It generates feedback and motivational messages based on the progress and sends them to the user's device. The device then presents these messages to the user via an avatar.

[0164] Specific examples

[0165] Understanding your health

[0166] User: A 30-year-old male, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[0167] Terminal: Sends the entered data to the server.

[0168] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[0169] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[0170] Health action plan development

[0171] User: "How can I get more exercise?" asks the avatar.

[0172] Terminal: Sends the question to the server.

[0173] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[0174] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[0175] User: Accept the advice and develop a health action plan.

[0176] Prompt Sentence Examples

[0177] "Calculate BMI based on this user's age, height, and weight and provide appropriate advice."

[0178] In this way, the present invention provides users with a deeper understanding of their health status and assistance in implementing specific health behaviors.

[0179] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0180] Step 1:

[0181] Users: Install the application and create an account.

[0182] Specific actions: Enter your username, email address, password, etc. on the account creation page and click the Register button.

[0183] Input: Username, email address, password, etc.

[0184] Output: Notification that user account creation is complete.

[0185] Step 2:

[0186] User: After creating an account, enter physical characteristics, genetic information, and lifestyle habits into the device.

[0187] Specific actions: Enter the required data into the dedicated input form and click the submit button.

[0188] Input: height, weight, age, DNA results, diet, exercise, sleep patterns, etc.

[0189] Output: Save input data on the device.

[0190] Step 3:

[0191] Terminal: Sends the entered data to the server.

[0192] What happens: The entered data is formatted and then sent to the server using an HTTP POST request.

[0193] Input: height, weight, age, DNA results, diet, exercise, sleep patterns, etc.

[0194] Output: The data sent to the server.

[0195] Step 4:

[0196] Server: Stores the received health data in a database.

[0197] Specific operation: Store the received data in a database such as "MySQL" or "PostgreSQL".

[0198] Input: Health data sent from the device.

[0199] Output: Health data stored in a database.

[0200] Step 5:

[0201] Server: Inputs stored data into an AI model to assess health status and risk.

[0202] Specific operation: Data is retrieved from a database and input into an AI model using a Python script. Possible AI models used include "TensorFlow" and "PyTorch."

[0203] Input: Health data stored in a database.

[0204] Output: Health status and risk assessment results.

[0205] Step 6:

[0206] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[0207] Specific operation: The output from the AI ​​model is processed and passed to an avatar generation algorithm to generate avatar data.

[0208] Input: Health status and risk assessment results.

[0209] Output: Virtual health avatar data.

[0210] Step 7:

[0211] Server: Sends the generated virtual health avatar data to the user terminal.

[0212] Specific operation: The generated avatar data is converted into JSON format and sent to the device via an HTTP POST request.

[0213] Input: Virtual health avatar data.

[0214] Output: Avatar data sent to the device.

[0215] Step 8:

[0216] Terminal: Visually displays the received avatar data.

[0217] Specific operation: Parses JSON data and displays the avatar on the screen using a graphics engine (e.g., "Unity" or "Unreal Engine").

[0218] Input: Received avatar data.

[0219] Output: A visually displayed virtual health avatar.

[0220] Step 9:

[0221] Terminal: Notifies the user that the avatar is ready to be displayed.

[0222] Specific behavior: Notify the user via push notification or alert dialog.

[0223] Input: Avatar display ready status.

[0224] Output: Notification to the user.

[0225] Step 10:

[0226] User: Initiates a dialogue with the virtual health avatar. For example, the user asks, "I've been feeling tired a lot lately. What should I do?"

[0227] Specific actions: Click the text box on the avatar display screen and enter a question.

[0228] Input: Health question text.

[0229] Output: Save the question content on the device.

[0230] Step 11:

[0231] Terminal: Sends the user's question to the server.

[0232] Specific operation: The question text is converted to JSON format and sent to the server via an HTTP POST request.

[0233] Input: Health question text.

[0234] Output: The query data sent to the server.

[0235] Step 12:

[0236] Server: Analyzes questions and generates health action plans and advice. The generative AI model used may be GPT-3.

[0237] Specific operation: The received question text is input into the AI ​​model to generate an answer.

[0238] Input: Question data from the user.

[0239] Output: Generated health action plans and advice.

[0240] Step 13:

[0241] Server: Sends the generated advice to the user terminal.

[0242] Specific operation: The generated advice is converted into JSON format and sent to the terminal via an HTTP POST request.

[0243] Input: Generated advice data.

[0244] Output: Advice data sent to the terminal.

[0245] Step 14:

[0246] Terminal: Presents advice to the user through an avatar.

[0247] Specific operation: The received advice data is displayed, and the avatar provides advice via voice or text.

[0248] Input: Received advice data.

[0249] Output: Advice provided to the user.

[0250] Step 15:

[0251] User: Creates a health action plan based on the avatar's advice and enters it into the device.

[0252] Specific actions: Enter your health action plan using the dedicated form on your device.

[0253] Input: Data on the health action plan you have created.

[0254] Output: Action plan data is saved on the device.

[0255] Step 16:

[0256] Terminal: Sends the input action plan data to the server.

[0257] Specific operation: Convert the action plan data into JSON format and send it to the server via an HTTP POST request.

[0258] Input: Planned action plan data.

[0259] Output: Action plan data sent to the server.

[0260] Step 17:

[0261] Server: Saves the action plan data in the database and starts monitoring.

[0262] Specific behavior: Save planning data to a database and periodically run monitoring scripts.

[0263] Input: Planned action plan data.

[0264] Output: Action plan data stored in a database.

[0265] Step 18:

[0266] Server: Periodically analyzes user behavior data and evaluates progress.

[0267] What it does: It periodically collects data and runs algorithms to evaluate progress.

[0268] Input: Stored action plan data, collected action data.

[0269] Output: Progress assessment results.

[0270] Step 19:

[0271] Server: Generates feedback and motivational messages based on progress and sends them to the user's device.

[0272] Specific operation: A message is generated using the feedback generation algorithm, the generated message is converted to JSON format, and sent to the device via an HTTP POST request.

[0273] Input: Progress assessment results.

[0274] Output: Generated feedback and motivational messages.

[0275] Step 20:

[0276] Terminal: Presents feedback and motivational messages to the user through an avatar.

[0277] Specific operation: A message is displayed on the display screen and provided by an avatar via voice or text.

[0278] Input: Received feedback and motivational messages.

[0279] Output: Feedback and motivational messages to the user.

[0280] (Application example 1)

[0281] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0282] Conventional health management systems are primarily limited to understanding the individual user's health status and formulating action plans, and the scope of these systems is limited to the user. However, managing the operational and maintenance status of robots operating in factories is directly linked to the efficiency and safety of factory operations, and applications in this field are in demand. However, current systems lack the functionality to comprehensively monitor the robot's health status and formulate appropriate maintenance plans. For this reason, there is a strong demand for the development of a system that can reduce robot operational risks and improve production efficiency.

[0283] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0284] In this invention, the server includes a means for inputting a user's physical characteristics, genetic information, and lifestyle habits, a means for transmitting the input data to the server, a means for analyzing the health data and generating a virtual health avatar, a means for visually displaying the generated virtual health avatar and the robot's operating status and component deterioration status, a means for analyzing the robot's operating data and generating a maintenance avatar, and a means for transmitting the generated avatar to a user terminal and a management terminal for interaction. This makes it possible to comprehensively manage the health status of not only users but also robots in the factory and to develop appropriate maintenance plans.

[0285] "User's physical characteristics" refers to the user's physical attributes such as height, weight, age, and gender.

[0286] "Genetic information" refers to DNA analysis results and genetic data.

[0287] "Lifestyle habits" refers to a user's daily life behaviors such as diet, exercise, and sleep patterns.

[0288] "Input Data" refers to information provided by the user relating to physical characteristics, genetic information, and lifestyle habits.

[0289] "Server" refers to a computer system for receiving, storing, and analyzing data.

[0290] "Health Data" refers to data about a user's health status based on their physical characteristics, genetic information, and lifestyle habits.

[0291] A "virtual health avatar" is a digital character that visually represents the user's health status and provides health guidance and advice through interaction.

[0292] "Means for visual display" refers to the function of displaying the generated avatar or data on the screen of a user terminal or an administrative terminal.

[0293] "Robot operation status" refers to data on how much the robot is operating, its operating time, and its condition.

[0294] "Parts deterioration status" refers to data that indicates the degree of deterioration of robot parts.

[0295] A "maintenance avatar" is a digital character that visually represents a robot's health status and maintenance needs, and presents a maintenance plan through interaction.

[0296] "Management terminal" refers to a computer device used by factory staff to manage the operating and maintenance status of robots.

[0297] "Maintenance plan" refers to a schedule of maintenance actions required to reduce robot operation risks and increase production efficiency.

[0298] This invention is a system that inputs a user's physical characteristics, genetic information, and lifestyle habits and uses them to manage their health and the operating status of a robot. Specifically, it is implemented through the following process.

[0299] First, the user installs a dedicated application and inputs their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.). This data is then sent to a server via the device. The server stores the received data in a database and analyzes the health data. Generative AI models such as TensorFlow and PyTorch are used for the analysis.

[0300] Based on the analysis results, the server generates a virtual health avatar and sends the data to the user's device. The generated virtual health avatar is visually displayed on the device, allowing the user to begin a dialogue. For example, if the user asks, "I've been feeling tired a lot lately. What should I do?", the question is sent to the server. The server analyzes the question, generates an appropriate health action plan and advice, and sends it to the user's device. The generated advice is then presented to the user through the virtual health avatar on the device.

[0301] Next, the system collects data on the robots in the factory, including their operating status and the deterioration of their parts, and sends it to a server. This data is also stored in a database and analyzed using a generative AI model. The server generates a maintenance avatar based on the analysis results and sends the data to the robot's management terminal. On the management terminal, the generated maintenance avatar is visually displayed, allowing the manager to initiate a dialogue. For example, if a manager asks, "When should the next maintenance be performed?", the question is sent to the server. The server analyzes the question, generates appropriate maintenance plans and actions, and sends them to the management terminal. On the management terminal, the generated plan is presented to the manager through the maintenance avatar.

[0302] The hardware used to implement these processes includes IoT devices and sensors, and the software includes TensorFlow and PyTorch for generating the health avatars, and a REST API for data transmission.

[0303] Examples:

[0304] 1. Healthcare example:

[0305] Let's say User A is a 30-year-old man, 170 cm tall and weighing 70 kg. He uses a health management app to input his physical characteristics and lifestyle habits. The app sends this data to a server, which analyzes the data and generates advice such as, "Your BMI is a little higher than normal. You should exercise more." A virtual health avatar conveys this advice to User A.

[0306] 2. Robot maintenance example:

[0307] Factory staff member B manages the operating status of a robot. The robot sends data that says, "Operating time: 1500 hours, sensor is deteriorating." The server analyzes the data and generates advice that says, "Perform the next maintenance on 2023-10-15 and replace the sensor." On the management terminal, a maintenance avatar notifies staff member B of this advice.

[0308] Example prompt sentence:

[0309] When should the next maintenance be performed?

[0310] "My robot has reached 1500 hours of operation, what maintenance action should I take next?"

[0311] "If a user's BMI is higher than normal, what kind of exercise should they increase?"

[0312] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0313] Step 1:

[0314] Users install a dedicated application and input their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.). The input data is sent to a server via the user's device. The input data includes physical characteristics such as height, weight, age, genetic information, and lifestyle habits. This allows basic information about the user's own health to be collected.

[0315] Step 2:

[0316] The server stores the received user data in a database. This storage process ensures that each user's health data is securely recorded. The stored data is then input into an AI analysis module to evaluate health status and risks. The AI ​​model used is a generative model based on TensorFlow and PyTorch. The analysis results provide indicators of the user's current health status and potential risks.

[0317] Step 3:

[0318] The server generates a virtual health avatar based on the analysis results. This avatar visually represents the user's health condition. Data on the generated virtual health avatar is sent to the user's device and displayed visually on the device, allowing the user to understand their health condition at a glance.

[0319] Step 4:

[0320] The user starts a dialogue with the virtual health avatar. For example, the user asks the avatar, "I've been feeling tired a lot lately. What should I do?" This question is sent to the server via the user's device. The input is the user's question, and the output is the avatar's answer.

[0321] Step 5:

[0322] The server analyzes the received questions using a natural language processing engine and generates appropriate health action plans and advice. A generative AI model is used for this analysis. The generated advice is then sent back from the server to the user's device and presented to the user via an avatar. For example, specific advice such as "Try jogging for 30 minutes three times a week" is provided.

[0323] Step 6:

[0324] The user creates a health action plan based on the advice provided and enters it into the device through the application. The entered action plan data is then sent back to the server and stored in a database. This records the user's health action plan and allows for future monitoring.

[0325] Step 7:

[0326] The server periodically analyzes the user's behavioral data based on the health action plan and evaluates their progress. This is again done using a generative AI model. Based on the evaluation results, the server generates feedback and motivational messages and sends them to the user's device. For example, a message such as "You're almost there! Keep going!" may be sent.

[0327] Step 8:

[0328] In the factory, the robot's operating status and the deterioration status of its parts are collected and sent to a server. The input data includes operating hours, part status, etc. This allows the robot's health status to be understood.

[0329] Step 9:

[0330] The server stores the received robot data in a database and analyzes it using a generative AI model. Based on the analysis results, a maintenance avatar is generated and sent to a management terminal. This visually displays which robots require maintenance and to what extent.

[0331] Step 10:

[0332] At the management terminal, staff interact with the maintenance avatar and ask questions such as, "When should the next maintenance be performed?" This question is sent to the server and analyzed.

[0333] Step 11:

[0334] The server receives the query, generates an appropriate maintenance plan and actions, and sends it to the management terminal. The plan is then presented to the administrator via an avatar. For example, specific instructions are provided, such as "Perform the next maintenance on 2023-10-15 and replace the sensor."

[0335] Step 12:

[0336] The server monitors the implementation of the plan and provides feedback as needed, ensuring that the plan is carried out reliably.

[0337] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0338] As an embodiment of the present invention, the processing of the program will be explained below in natural language.

[0339] 1. Data Collection

[0340] User: Installs the application and creates an account. Enters personal information and completes account setup.

[0341] User: After creating an account, the user enters physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, sleep patterns) into the device.

[0342] Terminal: Sends the entered data to the server.

[0343] 2. Data Analysis

[0344] Server: Stores the received health data in a database.

[0345] Server: Inputs stored health data into an AI model to assess health status and potential risks.

[0346] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[0347] 3. Avatar generation and display

[0348] Server: Sends the generated virtual health avatar data to the user terminal.

[0349] Terminal: Prepare to visually display the received avatar data.

[0350] Terminal: Sends a notification to the user that the avatar display is complete.

[0351] 4. Interaction

[0352] User: Starts a conversation with the virtual health avatar. Enters a question or concern into the avatar. For example, "I've been feeling tired lately. What should I do?"

[0353] Terminal: Sends the user's question to the server as text data.

[0354] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[0355] Server: Sends the generated advice to the user terminal as text data.

[0356] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[0357] 5. Emotion recognition

[0358] Terminal: The emotion engine analyzes the user's facial expressions, voice, and input patterns.

[0359] Terminal: Sends the recognized emotion data to the server.

[0360] Server: Adjusts health action plans and advice based on emotion data. For example, if a user is feeling stressed, it generates advice on how to reduce stress.

[0361] Server: Sends adjustment advice based on emotion data to the user's device.

[0362] 6. Health action plan development and monitoring

[0363] User: Create a health action plan based on advice from the avatar and emotion engine. For example, create a plan to jog three times a week.

[0364] User: Enter the health action plan into the terminal.

[0365] Terminal: Sends the input action plan data to the server.

[0366] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[0367] 7. Feedback and motivation

[0368] Server: Periodically analyzes user behavior data and evaluates the progress of the plan.

[0369] Server: Generates messages that provide feedback and motivation based on progress. For example, if you are jogging as planned, send a message praising you.

[0370] Server: Sends the generated feedback and motivation messages to the user terminal.

[0371] Terminal: Presents feedback and motivational messages to the user through an avatar.

[0372] Specific examples

[0373] Example 1: Understanding your health status

[0374] User: A 30-year-old man, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[0375] Terminal: Sends input data to the server.

[0376] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[0377] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[0378] Example 2: Creating a Health Action Plan

[0379] User: Asks avatar, "How can I get more exercise?"

[0380] Terminal: Sends the question to the server.

[0381] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[0382] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[0383] User: Accept the advice and develop a health action plan.

[0384] Example 3: Feedback using emotion recognition

[0385] User: Type into your avatar "I've been feeling stressed lately."

[0386] Terminal: The emotion engine recognizes stress from the user's facial expressions and voice, and sends that data to the server.

[0387] Server: Analyzes emotional data and generates stress reduction advice, such as "Try some relaxation techniques."

[0388] Device: The avatar tells the user to "Try some relaxation techniques."

[0389] This system allows users to gain a deeper understanding of their own health and emotional state, enabling them to effectively continue specific health behaviors.

[0390] The processing flow will be explained below.

[0391] Step 1:

[0392] User: Installs the application and creates an account. Enters personal information and completes account setup.

[0393] Step 2:

[0394] Terminal: Displays an input screen to collect data on physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) based on user input.

[0395] Step 3:

[0396] User: Follow the collection screen and enter the necessary health data, such as height 170cm, weight 70kg, meal frequency, exercise habits, etc.

[0397] Step 4:

[0398] Terminal: Formats the input data and sends it to the server.

[0399] Step 5:

[0400] Server: Stores the received health data in a database.

[0401] Step 6:

[0402] Server: Inputs stored health data into the AI ​​model to assess the user's health status and potential risks.

[0403] Step 7:

[0404] Server: Based on the analysis results, a virtual health avatar specialized for each user is generated.

[0405] Step 8:

[0406] Server: Sends the generated virtual health avatar data to the user terminal.

[0407] Step 9:

[0408] Terminal: Prepare to visually display the received avatar data.

[0409] Step 10:

[0410] Terminal: Sends a notification to the user that the avatar display is complete.

[0411] Step 11:

[0412] User: Starts a conversation with the virtual health avatar displayed on the device. Enters a question or concern into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[0413] Step 12:

[0414] Terminal: Sends the user's question to the server as text data.

[0415] Step 13:

[0416] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[0417] Step 14:

[0418] Server: Sends the generated advice to the user terminal as text data.

[0419] Step 15:

[0420] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[0421] Step 16:

[0422] Terminal: The emotion engine analyzes the user's facial expressions, voice, and input patterns.

[0423] Step 17:

[0424] Terminal: Sends the recognized emotion data to the server.

[0425] Step 18:

[0426] Server: Adjusts health action plans and advice based on emotion data. For example, if a user is feeling stressed, it generates advice on how to reduce stress.

[0427] Step 19:

[0428] Server: Sends adjustment advice based on emotion data to the user's device.

[0429] Step 20:

[0430] Terminal: Presents visual and audio advice tailored to the user through an avatar.

[0431] Step 21:

[0432] User: Create a health action plan based on advice from the avatar and emotion engine. For example, enter a plan such as "jog three times a week."

[0433] Step 22:

[0434] Terminal: Sends the created health action plan data to the server.

[0435] Step 23:

[0436] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[0437] Step 24:

[0438] User: Follows the plan and regularly records their actions (for example, jogging progress) in the app.

[0439] Step 25:

[0440] Terminal: Sends recorded behavioral data to the server.

[0441] Step 26:

[0442] Server: Analyzes the received behavioral data and evaluates the progress of the health behavior plan.

[0443] Step 27:

[0444] Server: Generates feedback and motivational messages based on progress. For example, if you are jogging according to plan, send a message praising you.

[0445] Step 28:

[0446] Server: Sends the generated feedback and motivation messages to the user terminal.

[0447] Step 29:

[0448] Terminal: Presents feedback and motivational messages to the user through an avatar.

[0449] By repeating the above process, the user can gain a deeper understanding of their own health and emotional state and effectively continue to take specific health actions.

[0450] Example 2

[0451] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0452] In modern society, many people are interested in managing their health and improving their lifestyles, but the difficulty of self-management and lack of individualized support are issues. In particular, there is a demand for comprehensive support that includes health status monitoring and emotional recognition, and a system that can provide this effectively is necessary.

[0453] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0454] In this invention, the server includes means for inputting a user's physical characteristics, genetic information, and lifestyle habits, means for transmitting the input data to the server, means for the server to analyze the health data and generate a virtual health avatar, means for transmitting the generated virtual health avatar to a user terminal and visually displaying it, means for the user to interact with the virtual health avatar and send questions to the server, means for the server to analyze the questions and generate an appropriate health action plan and advice, means for transmitting the generated advice to the user terminal and presenting it to the user via the avatar, means for the user to formulate a health action plan and input it to the terminal, means for storing the input action plan data on the server and monitoring it, means for the terminal to analyze the user's facial expressions, voice, and input patterns and transmit emotional data to the server, and means for the server to adjust advice based on the emotional data and transmit it to the user terminal, thereby enabling the user to receive support for comprehensive health management and emotional management.

[0455] "User" refers to any individual or entity that uses the System.

[0456] "Physical characteristics" refers to physical data such as a user's height, weight, age, and gender.

[0457] "Genetic information" refers to data relating to a user's DNA analysis results and genetic characteristics.

[0458] "Lifestyle habits" refers to data related to the user's daily life, such as diet, exercise, and sleep patterns.

[0459] "Terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[0460] "Server" refers to a central processing unit for analyzing data received from a user and providing the analysis results to the user.

[0461] "Health data" collectively refers to data such as a user's physical characteristics, genetic information, and lifestyle habits.

[0462] "Virtual health avatar" refers to a digital character generated to visually represent a user's health status.

[0463] "Dialogue" refers to text and / or voice communication between the user and the virtual health avatar.

[0464] A "health action plan" refers to a specific plan that a user makes to maintain or improve their health.

[0465] "Monitoring" refers to the process of tracking the progress of a user's health action plan and recording and evaluating the data.

[0466] "Emotion data" refers to data related to emotions analyzed from the user's facial expressions, voice, input patterns, etc.

[0467] "Advice" refers to specific instructions or suggestions for maintaining or improving health provided to the user by the server.

[0468] As an embodiment of the present invention, the processing of the program will be specifically described below, clearly indicating what hardware and software are used and what data processing and calculations are performed.

[0469] Explanation of program processing

[0470] Data collection

[0471] Users first install the application on their smartphone or tablet, create an account, and then enter personal information (such as name, email address, and password) to complete the setup.

[0472] After creating an account, users enter their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) via their device.

[0473] The device sends these input data to the server using an internet connection and a RESTful API.

[0474] Data analysis

[0475] The server stores the received health data in a relational database (e.g., MySQL).

[0476] The server uses the stored health data to input into a generative AI model, which then assesses the user's health status and potential risks using the generative AI model (e.g., TensorFlow, PyTorch).

[0477] The server generates a virtual health avatar based on the analysis results.

[0478] Avatar generation and display

[0479] The server sends the generated virtual health avatar data (e.g., 3D model data) to the user's device via an internet connection and a RESTful API.

[0480] The device analyzes the received avatar data and prepares it for rendering for visual display using a 3D rendering library (e.g., Unity, Unreal Engine).

[0481] The device notifies the user that the avatar display has been completed by using a push notification or a pop-up message.

[0482] Interaction

[0483] The user begins a conversation with the virtual health avatar. They enter their questions or concerns in text format into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[0484] The device sends the user's questions to the server using an internet connection and a RESTful API.

[0485] The server analyzes the questions using natural language processing (NLP) technology and generates appropriate health action plans and advice, such as suggestions for increasing exercise and guidance on nutritional balance.

[0486] The server transmits the generated advice to the user terminal as text data.

[0487] The terminal presents the advice generated through the avatar to the user visually and audibly.

[0488] emotion recognition

[0489] The device analyzes the user's facial expressions, voice, and input patterns using an emotion engine (e.g., Microsoft Azure Emotion API, Google Cloud Vision API).

[0490] The device transmits the recognized emotion data to a server using an internet connection and a RESTful API.

[0491] The server adjusts health action plans and advice based on emotion data. For example, if the user is feeling stressed, it generates advice on how to reduce stress.

[0492] The server transmits adjustment advice based on the emotion data to the user terminal.

[0493] Health action plan development and monitoring

[0494] The user creates a health action plan based on advice from the avatar and emotion data. For example, the user might plan to "jog three times a week."

[0495] The user inputs the health action plan that has been created into the terminal.

[0496] The terminal transmits the input action plan data to the server.

[0497] The server stores the health action plan data in a database and begins monitoring the plan.

[0498] Feedback and motivation

[0499] The server periodically analyzes user behavior data and evaluates the progress of the plan, using machine learning models (e.g., Scikit-learn).

[0500] The server generates feedback and motivational messages based on progress, e.g., praise messages based on frequency and duration of jogging.

[0501] The server transmits the generated feedback and motivation messages to the user terminal.

[0502] The device presents feedback and motivational messages to the user through the avatar.

[0503] Specific examples

[0504] Example 1: Understanding your health status

[0505] A user enters information such as height 170cm, weight 70kg, and age 30.

[0506] The terminal transmits the input data to the server.

[0507] The server analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[0508] The device displays an avatar telling the user, "Your BMI is a little higher than normal. You should exercise more."

[0509] Example 2: Creating a Health Action Plan

[0510] The user asks the avatar, "How can I get more exercise?"

[0511] The terminal sends a query to the server.

[0512] Based on the user's activity level, the server generates advice such as, "Try jogging for 30 minutes three times a week."

[0513] On the device, an avatar tells the user to "start jogging for 30 minutes three times a week."

[0514] The user accepts the advice and creates a health action plan.

[0515] Example 3: Feedback using emotion recognition

[0516] A user types into their avatar, "I've been feeling stressed lately."

[0517] The device's emotion engine recognizes stress from the user's facial expressions and voice, and sends that data to a server.

[0518] The server analyzes the emotional data and generates stress reduction advice, e.g., "Try relaxation techniques."

[0519] The device has an avatar telling the user to "try some relaxation techniques."

[0520] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0521] Step 1:

[0522] A user installs the application on a smartphone or tablet and creates an account. The user completes the setup by entering personal information such as name, email address, and password. The input data includes, for example, the name "Taro Tanaka," the email address "tanaka@example.com," and the password. The device sends this input data to the server. As an output, the user information is registered on the server and a user ID is generated.

[0523] Step 2:

[0524] After creating an account, users input their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.). The input is done using a form within the application. The device sends this input data to the server. As an output, the user's health data is stored in the server's database.

[0525] Step 3:

[0526] The server stores the received health data in a relational database (e.g., MySQL). The server inputs the stored health data into a generative AI model (e.g., TensorFlow, PyTorch) to evaluate the user's health status and potential risks. During the evaluation process, for example, BMI calculation is performed, and an evaluation result such as "slightly higher than normal" is obtained. The analysis result is generated as an output.

[0527] Step 4:

[0528] The server generates a virtual health avatar based on the analysis results. This uses an algorithm (e.g., Unity, Unreal Engine) to generate a 3D character model. The generated virtual health avatar is saved as digital data. The output is the virtual health avatar data.

[0529] Step 5:

[0530] The server sends the generated virtual health avatar data to the user's device via an internet connection and a RESTful API. The device analyzes the received avatar data and prepares rendering for visual display. As an output, a 3D model of the avatar is ready to be displayed on the device.

[0531] Step 6:

[0532] The device notifies the user that avatar display has been completed. This notification is sent via a push notification or a pop-up message. By receiving this notification, the user can confirm that the system is operating normally. As an output, a notification of avatar display completion is sent to the user.

[0533] Step 7:

[0534] The user starts a dialogue with the virtual health avatar. For example, the user inputs a question such as, "I've been feeling tired a lot recently. What should I do?" The device sends the user's question to the server as text data. The content of the question is sent to the server as output.

[0535] Step 8:

[0536] The server analyzes the received question using natural language processing (NLP) technology. A pre-trained generative AI model (e.g., GPT-3) is used for the analysis. Based on the analysis results, the server generates an appropriate health action plan and advice through the generative AI model. For example, advice such as "suggestions to increase exercise and guidance on nutritional balance" is generated. The advice is obtained as output.

[0537] Step 9:

[0538] The server sends the generated advice to the user's device via an internet connection and a RESTful API. The device then presents the generated advice to the user visually and audibly through an avatar. For example, the avatar might say, "You should exercise more." The user receives the advice as output.

[0539] Step 10:

[0540] The device analyzes the user's facial expressions, voice, and input patterns using an emotion engine (e.g., Microsoft Azure Emotion API, Google Cloud Vision API). The analysis process uses a camera and microphone. The device sends the recognized emotion data to the server. As an output, the emotion data is sent to the server.

[0541] Step 11:

[0542] The server adjusts the health action plan and advice based on the emotion data. An algorithm based on the emotion data is used for the analysis, and generates, for example, "advice on how to reduce stress when the user is feeling stressed." The server then sends the adjusted advice to the user's device. The adjusted advice is obtained as the output.

[0543] Step 12:

[0544] The device presents the adjusted advice to the user through the avatar, for example, the avatar says in a voice, "Try some relaxation techniques." As an output, the user receives the adjusted advice.

[0545] Step 13:

[0546] The user creates a health action plan based on advice from the avatar and emotion data. For example, the user can create a plan to "jog three times a week." The user inputs the created plan into the terminal. The action plan data is obtained as output.

[0547] Step 14:

[0548] The device sends the input action plan data to the server. The transmission is performed using an internet connection and a RESTful API. The server stores the action plan data in a database. As an output, the action plan data is stored on the server.

[0549] Step 15:

[0550] The server periodically analyzes the user's behavioral data and evaluates the progress of the plan. This is done using a machine learning model (e.g., Scikit-learn). The server generates feedback and motivational messages based on the progress made based on the analysis results. For example, it generates a message such as "You're doing great!" based on the frequency and duration of jogging. The feedback message is obtained as an output.

[0551] Step 16:

[0552] The server sends the generated feedback and motivation messages to the user's device using an internet connection and a RESTful API. The device presents the feedback messages to the user through an avatar. For example, the avatar might say "Great! Keep it up!". As an output, the user receives the feedback.

[0553] (Application example 2)

[0554] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0555] While conventional health management systems allow users to plan health behaviors, they struggle to maintain the motivation to actually follow through with them. Furthermore, they lack the means to monitor users' emotions and stress levels and adjust advice accordingly, resulting in a lack of personalized care.

[0556] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for awarding electronic payment points according to the degree of achievement of the health action plan, a means for monitoring the user's emotions and stress level using an emotion recognition engine, and a means for adjusting the health action plan and advice based on the monitoring results. This makes it easier for the user to maintain motivation to carry out the action plan and allows them to receive personalized feedback.

[0557] "User's physical characteristics" refers to the user's physical attributes such as height, weight, body fat percentage, muscle mass, etc.

[0558] "Genetic information" refers to the results of a user's DNA analysis and information about their genes.

[0559] "Lifestyle habits" refers to the user's daily behavior patterns, dietary habits, exercise habits, sleep patterns, and other habits.

[0560] "Server" refers to a central computer system that analyzes and stores data and provides information to users.

[0561] "Virtual health avatar" refers to a digital character generated to visually represent a user's health status.

[0562] "Electronic payment points" refers to digital rewards awarded according to the degree to which a user achieves their action plan.

[0563] An "emotion recognition engine" refers to software that analyzes a user's facial expressions and voice to determine their emotions and stress level.

[0564] A "health action plan" refers to a plan regarding exercise, diet, and lifestyle habits that is drawn up by a user.

[0565] "Monitoring" refers to the server periodically monitoring and evaluating the user's progress in their action plan and their emotional state.

[0566] "Feedback" refers to information that the server provides to the user regarding analysis results and evaluations.

[0567] This invention is a system that allows users to manage their own health status and maintain motivation. Specifically, the system begins when a user enters their physical characteristics, genetic information, and lifestyle habits through an application and sends the data to a server. This data is analyzed by the server and a virtual healthy avatar is generated.

[0568] Technology and hardware used

[0569] Programming language: Python

[0570] Database: MySQL

[0571] AI model: TensorFlow

[0572] Emotion recognition engine: OpenCV, Dlib

[0573] Frontend: React Native

[0574] Server: AWS EC2

[0575] Electronic payment system: Stripe

[0576] Data collection

[0577] Users download the smartphone app and enter data such as physical characteristics, genetic information, and lifestyle habits. The data is sent to the server in real time.

[0578] Data analysis and avatar generation

[0579] The server analyzes the received health data and inputs it into a model that evaluates the user's health status using TensorFlow. Based on the analysis results, a virtual health avatar is generated and sent to the user's device.

[0580] Interacting with avatars

[0581] Users can interact with the virtual health avatar and ask questions or seek advice about their health. This interaction takes place in real time, and the entered questions are sent to the server, which analyzes the questions and generates appropriate health action plans and advice.

[0582] emotion recognition

[0583] The user's facial expressions and voice are captured using the smartphone's camera and microphone, and analyzed using an emotion recognition engine (OpenCV, Dlib). The analysis results are sent to a server, which monitors the user's emotions and stress level.

[0584] Implementing and monitoring health action plans

[0585] The user follows the instructions of the virtual health avatar to create a specific health action plan. This plan is input into the device and stored on the server. The server periodically monitors the progress of the plan and provides feedback to the user on the evaluation results.

[0586] Electronic payment points awarded

[0587] Each time a user completes a health action plan, points are added to the user's account using an electronic payment system (Stripe). These points can then be used to purchase products, etc.

[0588] Specific examples

[0589] Example prompt sentence:

[0590] "I'm a 30-year-old male, 170cm tall and weigh 70kg. I've been feeling tired easily lately. I'd like some suggestions for an exercise plan and stress reduction."

[0591] Example flow:

[0592] 1. A user creates an account and enters data such as height, weight, and age.

[0593] 2. The server receives the data, analyzes it with an AI model, and generates a virtual health avatar.

[0594] 3. The user interacts with the avatar and receives suggestions for exercise plans and stress reduction.

[0595] 4. An emotion recognition engine analyzes the user's emotional state and adjusts advice as needed.

[0596] 5. The user takes action based on the health action plan they created, and the server monitors their progress.

[0597] 6. Electronic payment points are awarded according to the level of achievement, and users can use these points to obtain incentives.

[0598] Through the above steps, the present invention not only enables the user to manage their health condition and create an effective action plan, but also provides the motivation to continue the plan.

[0599] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0600] Step 1: A user creates an account and enters their physical characteristics, genetic information, and lifestyle habits.

[0601] Input: Information such as the user's height, weight, age, exercise habits, dietary patterns, and DNA analysis results.

[0602] Process: The user enters the required information on the smartphone application screen.

[0603] Output: The input information is sent to the cloud server in JSON format.

[0604] Step 2: The server stores the received data.

[0605] Input: Health data submitted by the user in JSON format.

[0606] Processing: Save the received data in a MySQL database.

[0607] Output: User's health information stored in a database.

[0608] Step 3: The server analyzes the stored health data.

[0609] Input: User's health data stored in a database.

[0610] Processing: Analyze health data using TensorFlow to assess the user's health status.

[0611] Output: Health status assessment results (e.g. BMI, body fat percentage, potential risks).

[0612] Step 4: The server generates a virtual health avatar and sends it to the user terminal.

[0613] Input: Health status assessment results.

[0614] Processing: A virtual health avatar is generated based on the evaluation results, and the data is sent to the user terminal.

[0615] Output: Virtual health avatar data sent to the user device.

[0616] Step 5: The device visually displays the virtual health avatar and notifies the user.

[0617] Input: Virtual health avatar data sent from the server.

[0618] Processing: Graphically display the avatar on the user's device and send notifications to the user.

[0619] Output: Visually displayed virtual health avatar and notification.

[0620] Step 6: The user interacts with the virtual health avatar and inputs a health question.

[0621] Input: User's text question (e.g. "I've been feeling tired a lot lately. What should I do?").

[0622] Process: The user enters a question in the application and sends it to the server.

[0623] Output: The user's question data sent to the server.

[0624] Step 7: The server parses the question and generates a health action plan and advice.

[0625] Input: Question data submitted by the user.

[0626] Processing: The question data is fed into a natural language processing engine to generate appropriate health action plans and advice.

[0627] Output: Generated health action plans and advice.

[0628] Step 8: The server sends the generated advice to the user terminal.

[0629] Input: Generated health action plans and advice.

[0630] Processing: The generated advice is sent to the user's terminal.

[0631] Output: Advice data sent to the user terminal.

[0632] Step 9: The terminal presents the generated advice to the user through the avatar.

[0633] Input: Advice data sent by the server.

[0634] Processing: Advice is presented to the user visually and audibly through an avatar.

[0635] Output: Health action plan and advice presented to the user.

[0636] Step 10: The user communicates their emotions and stress to the avatar.

[0637] Input: Text or voice input about the user's emotions or stress (e.g., "I've been feeling stressed lately").

[0638] Processing: The smartphone's camera and microphone are used to capture the user's facial expressions and voice, which are then analyzed by an emotion recognition engine.

[0639] Output: Parsed emotion data.

[0640] Step 11: The server adjusts the advice based on the emotion data.

[0641] Input: Parsed emotion data.

[0642] Processing: Adjusting health action plans and advice based on emotional data.

[0643] Output: Adjusted advice.

[0644] Step 12: The adjusted advice is sent to the user terminal and presented through the avatar.

[0645] Input: Tailored advice.

[0646] Processing: The server sends the adjusted advice to the device and presents it through the avatar.

[0647] Output: Tuning advice presented to the user.

[0648] Step 13: The user creates a health action plan and inputs it into the terminal.

[0649] Input: A health action plan created by the user (e.g., jogging three times a week).

[0650] Processing: An action plan is entered on the terminal and sent to the server.

[0651] Output: Action plan data sent to the server.

[0652] Step 14: The server stores the action plan data and performs monitoring.

[0653] Input: Submitted action plan data.

[0654] Processing: Store in a database and periodically monitor the progress of the plan.

[0655] Output: Monitoring results and progress reports.

[0656] Step 15: The server awards electronic payment points according to the progress.

[0657] Input: Health action plan progress data.

[0658] Processing: Points are awarded based on progress using an electronic payment system.

[0659] Output: Electronic payment points awarded to the user.

[0660] Step 16: The terminal presents feedback and motivational messages to the user.

[0661] Input: Feedback and motivation messages from the server.

[0662] Processing: The message is presented to the user visually and audibly through an avatar.

[0663] Output: Feedback and motivational messages presented to the user.

[0664] This series of processing flows enables users to efficiently manage their own health condition and maintain continuous motivation by carrying out action plans and obtaining incentives.

[0665] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0666] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0667] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0668] [Second embodiment]

[0669] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0670] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0671] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0672] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0673] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0674] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0675] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0676] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0677] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0678] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0679] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0680] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0681] As an embodiment of the present invention, the processing of the program will be explained below in natural language.

[0682] 1. Data Collection

[0683] Users: Install the application and create an account.

[0684] User: After creating an account, the user enters physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, sleep patterns) into the device.

[0685] Terminal: Sends the entered data to the server.

[0686] 2. Data Analysis

[0687] Server: Stores the received health data in a database.

[0688] Server: Inputs stored health data into the AI ​​model to assess health status and risks.

[0689] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[0690] 3. Avatar generation and display

[0691] Server: Sends the generated virtual health avatar data to the user terminal.

[0692] Terminal: Visually displays the received avatar data.

[0693] Terminal: Notifies the user that the avatar is ready to be displayed.

[0694] 4. Interaction

[0695] User: Initiates a dialogue with the virtual health avatar. For example, the user asks, "I've been feeling tired a lot lately. What should I do?"

[0696] Terminal: Sends the user's question to the server.

[0697] Server: Analyzes the questions and generates appropriate health action plans and advice.

[0698] Server: Sends the generated advice to the user terminal.

[0699] Terminal: Presents advice to the user through an avatar.

[0700] 5. Health action plan development and monitoring

[0701] User: Create a health action plan based on the avatar's advice. For example, create a plan to "jog three times a week."

[0702] User: Enter the health action plan into the terminal.

[0703] Terminal: Sends the input action plan data to the server.

[0704] Server: Saves the action plan data in the database and starts monitoring.

[0705] 6. Feedback and motivation

[0706] Server: Periodically analyzes user behavior data and evaluates the progress of the plan.

[0707] Server: Generates messages that provide feedback and motivation based on progress.

[0708] Server: Sends generated feedback and motivation messages to the devices.

[0709] Terminal: Presents feedback and motivational messages to the user through an avatar.

[0710] Specific examples

[0711] Example 1: Understanding your health status

[0712] User: A 30-year-old man, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[0713] Terminal: Sends input data to the server.

[0714] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[0715] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[0716] Example 2: Creating a Health Action Plan

[0717] User: Asks avatar, "How can I get more exercise?"

[0718] Terminal: Sends the question to the server.

[0719] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[0720] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[0721] User: Accept the advice and develop a health action plan.

[0722] In this way, the present invention provides users with a deeper understanding of their health status and assistance in implementing specific health behaviors.

[0723] The processing flow will be explained below.

[0724] Step 1:

[0725] User: Installs the application and creates an account. Enters personal information and completes account setup.

[0726] Step 2:

[0727] Terminal: Displays an input screen to collect data on physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) based on user input.

[0728] Step 3:

[0729] User: Follow the collection screen and enter the necessary health data, such as height 170cm, weight 70kg, meal frequency, exercise habits, etc.

[0730] Step 4:

[0731] Terminal: Formats the input data and sends it to the server.

[0732] Step 5:

[0733] Server: Stores the received health data in a database.

[0734] Step 6:

[0735] Server: Inputs stored health data into the AI ​​model to assess the user's health status and potential risks.

[0736] Step 7:

[0737] Server: Based on the analysis results, a virtual health avatar specialized for each user is generated.

[0738] Step 8:

[0739] Server: Sends the generated virtual health avatar data to the user terminal.

[0740] Step 9:

[0741] Terminal: Prepare to visually display the received avatar data.

[0742] Step 10:

[0743] Terminal: Sends a notification to the user that the avatar display is complete.

[0744] Step 11:

[0745] User: Starts a conversation with the virtual health avatar displayed on the device. Enters a question or concern into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[0746] Step 12:

[0747] Terminal: Sends the user's question to the server as text data.

[0748] Step 13:

[0749] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[0750] Step 14:

[0751] Server: Sends the generated advice to the user terminal as text data.

[0752] Step 15:

[0753] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[0754] Step 16:

[0755] User: Create a health action plan based on the avatar's advice. For example, enter a plan such as "jog for 30 minutes three times a week."

[0756] Step 17:

[0757] Terminal: Sends the created health action plan data to the server.

[0758] Step 18:

[0759] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[0760] Step 19:

[0761] User: Follows the plan and regularly records their actions (for example, jogging progress) in the app.

[0762] Step 20:

[0763] Terminal: Sends recorded behavioral data to the server.

[0764] Step 21:

[0765] Server: Analyzes the received behavioral data and evaluates the progress of the health behavior plan.

[0766] Step 22:

[0767] Server: Generates feedback and motivational messages based on progress.

[0768] Step 23:

[0769] Server: Sends the generated feedback and motivation messages to the user terminal.

[0770] Step 24:

[0771] Terminal: Presents feedback and motivational messages to the user through an avatar.

[0772] By repeating the above process, users can gain a deeper understanding of their own health status and continuously practice specific health behaviors.

[0773] Example 1

[0774] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0775] In modern society, it is difficult for users to accurately understand their own health status and develop appropriate health action plans. In particular, health management that takes into account individual physical characteristics, genetic information, and lifestyle habits requires specialized knowledge, making it difficult for many users to effectively maintain their health. In addition, existing systems do not adequately provide continuous monitoring, feedback, or motivation, which means that users' health improvements are not sustainable.

[0776] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0777] In this invention, the server includes: a means for inputting a user's physical characteristics, genetic information, and lifestyle habits; a means for transmitting the input data to the server; a means for analyzing the health data and generating a virtual health avatar; a means for transmitting the generated virtual health avatar to a user terminal and visually displaying it; a means for the user to interact with the virtual health avatar and send questions to the server; a means for the server to analyze the questions and generate an appropriate health action plan and advice; a means for transmitting the generated advice to the user terminal and presenting it to the user via the avatar; a means for the user to create a health action plan and input it into the terminal; a means for storing the input action plan data on the server and monitoring it; a means for periodically analyzing the action data and evaluating progress; and a means for transmitting the generated feedback and motivational messages to the user terminal and presenting them to the user via the avatar. This allows the user to accurately understand their own health status and create and implement an effective health action plan based on their individual characteristics. Furthermore, providing continuous feedback and motivation can be expected to have a lasting effect on the user's health improvement.

[0778] "User" refers to a person who uses the system to manage and improve their health.

[0779] "Physical characteristics" refers to data about the user's body, such as height, weight, and age.

[0780] "Genetic information" refers to data related to genetics, such as the results of a user's DNA analysis.

[0781] "Lifestyle habits" refers to data such as diet, exercise, and sleep patterns in a user's daily life.

[0782] "Terminal" refers to an electronic device used by a user, such as a computer, smartphone, or tablet.

[0783] "Server" refers to a computer system that receives, stores, and analyzes data entered by a user and transmits the generated information to the user terminal.

[0784] "Database" refers to an information management system for storing user health data and action plan data.

[0785] "AI model" refers to the artificial intelligence algorithm used by the server to analyze health status.

[0786] "Virtual health avatar" refers to a digital character that visually represents a user's health status.

[0787] A "question" refers to a health-related inquiry that a user makes to the server through a virtual health avatar.

[0788] A "health action plan" refers to a specific action plan that a user sets out to improve their own health.

[0789] "Monitoring" refers to the process by which the server continuously monitors user behavior data and evaluates progress.

[0790] "Feedback" refers to the evaluation and advice provided by the server regarding the user's behavior and health status.

[0791] "Motivational Message" refers to a message of encouragement or encouragement provided by the server to promote improvement in the user's health.

[0792] This invention is a system that helps users accurately understand their own health status and assists them in formulating and implementing effective health action plans. This system consists of a user, a terminal, and a server.

[0793] Data collection

[0794] First, the user installs the application and creates an account. After creating the account, the user enters their physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, sleep patterns) into the device. The device then sends the entered data to the server. This transmission is performed using an HTTP POST request.

[0795] Data analysis

[0796] The server stores the received health data in a database. The stored data is then fed into an AI model (e.g., TensorFlow or PyTorch) to assess health status and risks. The analysis results are then used to generate a personalized virtual health avatar. This avatar is a digital character that visually represents the user's health status.

[0797] Avatar generation and display

[0798] The generated virtual health avatar is sent from the server to the user's device. The device receives this data and visually displays it. Software such as Unity or Unreal Engine is used for display. The device uses push notifications or alert dialogs to notify the user that the avatar is ready to be displayed.

[0799] Interaction

[0800] The user begins a dialogue with the virtual health avatar. For example, if the user asks, "I've been feeling tired lately. What should I do?", this question is sent from the device to the server. The server analyzes the question using a generative AI model (e.g., GPT-3) and generates an appropriate health action plan and advice. The generated advice is sent from the server to the user's device, which then presents it to the user through the avatar.

[0801] Health action plan development and monitoring

[0802] The user creates a health action plan based on the avatar's advice and enters it into the device. For example, the user may plan to "jog three times a week." The entered action plan data is sent from the device to the server and stored in a database. The server continues to monitor this.

[0803] Feedback and motivation

[0804] The server periodically analyzes the user's behavioral data and evaluates the progress of the plan. It generates feedback and motivational messages based on the progress and sends them to the user's device. The device then presents these messages to the user via an avatar.

[0805] Specific examples

[0806] Understanding your health

[0807] User: A 30-year-old male, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[0808] Terminal: Sends the entered data to the server.

[0809] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[0810] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[0811] Health action plan development

[0812] User: "How can I get more exercise?" asks the avatar.

[0813] Terminal: Sends the question to the server.

[0814] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[0815] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[0816] User: Accept the advice and develop a health action plan.

[0817] Prompt Sentence Examples

[0818] "Calculate BMI based on this user's age, height, and weight and provide appropriate advice."

[0819] In this way, the present invention provides users with a deeper understanding of their health status and assistance in implementing specific health behaviors.

[0820] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0821] Step 1:

[0822] Users: Install the application and create an account.

[0823] Specific actions: Enter your username, email address, password, etc. on the account creation page and click the Register button.

[0824] Input: Username, email address, password, etc.

[0825] Output: Notification that user account creation is complete.

[0826] Step 2:

[0827] User: After creating an account, enter physical characteristics, genetic information, and lifestyle habits into the device.

[0828] Specific actions: Enter the required data into the dedicated input form and click the submit button.

[0829] Input: height, weight, age, DNA results, diet, exercise, sleep patterns, etc.

[0830] Output: Save input data on the device.

[0831] Step 3:

[0832] Terminal: Sends the entered data to the server.

[0833] What happens: The entered data is formatted and then sent to the server using an HTTP POST request.

[0834] Input: height, weight, age, DNA results, diet, exercise, sleep patterns, etc.

[0835] Output: The data sent to the server.

[0836] Step 4:

[0837] Server: Stores the received health data in a database.

[0838] Specific operation: Store the received data in a database such as "MySQL" or "PostgreSQL".

[0839] Input: Health data sent from the device.

[0840] Output: Health data stored in a database.

[0841] Step 5:

[0842] Server: Inputs stored data into an AI model to assess health status and risk.

[0843] Specific operation: Data is retrieved from a database and input into an AI model using a Python script. Possible AI models used include "TensorFlow" and "PyTorch."

[0844] Input: Health data stored in a database.

[0845] Output: Health status and risk assessment results.

[0846] Step 6:

[0847] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[0848] Specific operation: The output from the AI ​​model is processed and passed to an avatar generation algorithm to generate avatar data.

[0849] Input: Health status and risk assessment results.

[0850] Output: Virtual health avatar data.

[0851] Step 7:

[0852] Server: Sends the generated virtual health avatar data to the user terminal.

[0853] Specific operation: The generated avatar data is converted into JSON format and sent to the device via an HTTP POST request.

[0854] Input: Virtual health avatar data.

[0855] Output: Avatar data sent to the device.

[0856] Step 8:

[0857] Terminal: Visually displays the received avatar data.

[0858] Specific operation: Parses JSON data and displays the avatar on the screen using a graphics engine (e.g., "Unity" or "Unreal Engine").

[0859] Input: Received avatar data.

[0860] Output: A visually displayed virtual health avatar.

[0861] Step 9:

[0862] Terminal: Notifies the user that the avatar is ready to be displayed.

[0863] Specific behavior: Notify the user via push notification or alert dialog.

[0864] Input: Avatar display ready status.

[0865] Output: Notification to the user.

[0866] Step 10:

[0867] User: Initiates a dialogue with the virtual health avatar. For example, the user asks, "I've been feeling tired a lot lately. What should I do?"

[0868] Specific actions: Click the text box on the avatar display screen and enter a question.

[0869] Input: Health question text.

[0870] Output: Save the question content on the device.

[0871] Step 11:

[0872] Terminal: Sends the user's question to the server.

[0873] Specific operation: The question text is converted to JSON format and sent to the server via an HTTP POST request.

[0874] Input: Health question text.

[0875] Output: The query data sent to the server.

[0876] Step 12:

[0877] Server: Analyzes questions and generates health action plans and advice. The generative AI model used may be GPT-3.

[0878] Specific operation: The received question text is input into the AI ​​model to generate an answer.

[0879] Input: Question data from the user.

[0880] Output: Generated health action plans and advice.

[0881] Step 13:

[0882] Server: Sends the generated advice to the user terminal.

[0883] Specific operation: The generated advice is converted into JSON format and sent to the terminal via an HTTP POST request.

[0884] Input: Generated advice data.

[0885] Output: Advice data sent to the terminal.

[0886] Step 14:

[0887] Terminal: Presents advice to the user through an avatar.

[0888] Specific operation: The received advice data is displayed, and the avatar provides advice via voice or text.

[0889] Input: Received advice data.

[0890] Output: Advice provided to the user.

[0891] Step 15:

[0892] User: Creates a health action plan based on the avatar's advice and enters it into the device.

[0893] Specific actions: Enter your health action plan using the dedicated form on your device.

[0894] Input: Data on the health action plan you have created.

[0895] Output: Action plan data is saved on the device.

[0896] Step 16:

[0897] Terminal: Sends the input action plan data to the server.

[0898] Specific operation: Convert the action plan data into JSON format and send it to the server via an HTTP POST request.

[0899] Input: Planned action plan data.

[0900] Output: Action plan data sent to the server.

[0901] Step 17:

[0902] Server: Saves the action plan data in the database and starts monitoring.

[0903] Specific behavior: Save planning data to a database and periodically run monitoring scripts.

[0904] Input: Planned action plan data.

[0905] Output: Action plan data stored in a database.

[0906] Step 18:

[0907] Server: Periodically analyzes user behavior data and evaluates progress.

[0908] What it does: It periodically collects data and runs algorithms to evaluate progress.

[0909] Input: Stored action plan data, collected action data.

[0910] Output: Progress assessment results.

[0911] Step 19:

[0912] Server: Generates feedback and motivational messages based on progress and sends them to the user's device.

[0913] Specific operation: A message is generated using the feedback generation algorithm, the generated message is converted to JSON format, and sent to the device via an HTTP POST request.

[0914] Input: Progress assessment results.

[0915] Output: Generated feedback and motivational messages.

[0916] Step 20:

[0917] Terminal: Presents feedback and motivational messages to the user through an avatar.

[0918] Specific operation: A message is displayed on the display screen and provided by an avatar via voice or text.

[0919] Input: Received feedback and motivational messages.

[0920] Output: Feedback and motivational messages to the user.

[0921] (Application example 1)

[0922] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0923] Conventional health management systems are primarily limited to understanding the individual user's health status and formulating action plans, and the scope of these systems is limited to the user. However, managing the operational and maintenance status of robots operating in factories is directly linked to the efficiency and safety of factory operations, and applications in this field are in demand. However, current systems lack the functionality to comprehensively monitor the robot's health status and formulate appropriate maintenance plans. For this reason, there is a strong demand for the development of a system that can reduce robot operational risks and improve production efficiency.

[0924] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0925] In this invention, the server includes a means for inputting a user's physical characteristics, genetic information, and lifestyle habits, a means for transmitting the input data to the server, a means for analyzing the health data and generating a virtual health avatar, a means for visually displaying the generated virtual health avatar and the robot's operating status and component deterioration status, a means for analyzing the robot's operating data and generating a maintenance avatar, and a means for transmitting the generated avatar to a user terminal and a management terminal for interaction. This makes it possible to comprehensively manage the health status of not only users but also robots in the factory and to develop appropriate maintenance plans.

[0926] "User's physical characteristics" refers to the user's physical attributes such as height, weight, age, and gender.

[0927] "Genetic information" refers to DNA analysis results and genetic data.

[0928] "Lifestyle habits" refers to a user's daily life behaviors such as diet, exercise, and sleep patterns.

[0929] "Input Data" refers to information provided by the user relating to physical characteristics, genetic information, and lifestyle habits.

[0930] "Server" refers to a computer system for receiving, storing, and analyzing data.

[0931] "Health Data" refers to data about a user's health status based on their physical characteristics, genetic information, and lifestyle habits.

[0932] A "virtual health avatar" is a digital character that visually represents the user's health status and provides health guidance and advice through interaction.

[0933] "Means for visual display" refers to the function of displaying the generated avatar or data on the screen of a user terminal or an administrative terminal.

[0934] "Robot operation status" refers to data on how much the robot is operating, its operating time, and its condition.

[0935] "Parts deterioration status" refers to data that indicates the degree of deterioration of robot parts.

[0936] A "maintenance avatar" is a digital character that visually represents a robot's health status and maintenance needs, and presents a maintenance plan through interaction.

[0937] "Management terminal" refers to a computer device used by factory staff to manage the operating and maintenance status of robots.

[0938] "Maintenance plan" refers to a schedule of maintenance actions required to reduce robot operation risks and increase production efficiency.

[0939] This invention is a system that inputs a user's physical characteristics, genetic information, and lifestyle habits and uses them to manage their health and the operating status of a robot. Specifically, it is implemented through the following process.

[0940] First, the user installs a dedicated application and inputs their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.). This data is then sent to a server via the device. The server stores the received data in a database and analyzes the health data. Generative AI models such as TensorFlow and PyTorch are used for the analysis.

[0941] Based on the analysis results, the server generates a virtual health avatar and sends the data to the user's device. The generated virtual health avatar is visually displayed on the device, allowing the user to begin a dialogue. For example, if the user asks, "I've been feeling tired a lot lately. What should I do?", the question is sent to the server. The server analyzes the question, generates an appropriate health action plan and advice, and sends it to the user's device. The generated advice is then presented to the user through the virtual health avatar on the device.

[0942] Next, the system collects data on the robots in the factory, including their operating status and the deterioration of their parts, and sends it to a server. This data is also stored in a database and analyzed using a generative AI model. The server generates a maintenance avatar based on the analysis results and sends the data to the robot's management terminal. On the management terminal, the generated maintenance avatar is visually displayed, allowing the manager to initiate a dialogue. For example, if a manager asks, "When should the next maintenance be performed?", the question is sent to the server. The server analyzes the question, generates appropriate maintenance plans and actions, and sends them to the management terminal. On the management terminal, the generated plan is presented to the manager through the maintenance avatar.

[0943] The hardware used to implement these processes includes IoT devices and sensors, and the software includes TensorFlow and PyTorch for generating the health avatars, and a REST API for data transmission.

[0944] Examples:

[0945] 1. Healthcare example:

[0946] Let's say User A is a 30-year-old man, 170 cm tall and weighing 70 kg. He uses a health management app to input his physical characteristics and lifestyle habits. The app sends this data to a server, which analyzes the data and generates advice such as, "Your BMI is a little higher than normal. You should exercise more." A virtual health avatar conveys this advice to User A.

[0947] 2. Robot maintenance example:

[0948] Factory staff member B manages the operating status of a robot. The robot sends data that says, "Operating time: 1500 hours, sensor is deteriorating." The server analyzes the data and generates advice that says, "Perform the next maintenance on 2023-10-15 and replace the sensor." On the management terminal, a maintenance avatar notifies staff member B of this advice.

[0949] Example prompt sentence:

[0950] When should the next maintenance be performed?

[0951] "My robot has reached 1500 hours of operation, what maintenance action should I take next?"

[0952] "If a user's BMI is higher than normal, what kind of exercise should they increase?"

[0953] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0954] Step 1:

[0955] Users install a dedicated application and input their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.). The input data is sent to a server via the user's device. The input data includes physical characteristics such as height, weight, age, genetic information, and lifestyle habits. This allows basic information about the user's own health to be collected.

[0956] Step 2:

[0957] The server stores the received user data in a database. This storage process ensures that each user's health data is securely recorded. The stored data is then input into an AI analysis module to evaluate health status and risks. The AI ​​model used is a generative model based on TensorFlow and PyTorch. The analysis results provide indicators of the user's current health status and potential risks.

[0958] Step 3:

[0959] The server generates a virtual health avatar based on the analysis results. This avatar visually represents the user's health condition. Data on the generated virtual health avatar is sent to the user's device and displayed visually on the device, allowing the user to understand their health condition at a glance.

[0960] Step 4:

[0961] The user starts a dialogue with the virtual health avatar. For example, the user asks the avatar, "I've been feeling tired a lot lately. What should I do?" This question is sent to the server via the user's device. The input is the user's question, and the output is the avatar's answer.

[0962] Step 5:

[0963] The server analyzes the received questions using a natural language processing engine and generates appropriate health action plans and advice. A generative AI model is used for this analysis. The generated advice is then sent back from the server to the user's device and presented to the user via an avatar. For example, specific advice such as "Try jogging for 30 minutes three times a week" is provided.

[0964] Step 6:

[0965] The user creates a health action plan based on the advice provided and enters it into the device through the application. The entered action plan data is then sent back to the server and stored in a database. This records the user's health action plan and allows for future monitoring.

[0966] Step 7:

[0967] The server periodically analyzes the user's behavioral data based on the health action plan and evaluates their progress. This is again done using a generative AI model. Based on the evaluation results, the server generates feedback and motivational messages and sends them to the user's device. For example, a message such as "You're almost there! Keep going!" may be sent.

[0968] Step 8:

[0969] In the factory, the robot's operating status and the deterioration status of its parts are collected and sent to a server. The input data includes operating hours, part status, etc. This allows the robot's health status to be understood.

[0970] Step 9:

[0971] The server stores the received robot data in a database and analyzes it using a generative AI model. Based on the analysis results, a maintenance avatar is generated and sent to a management terminal. This visually displays which robots require maintenance and to what extent.

[0972] Step 10:

[0973] At the management terminal, staff interact with the maintenance avatar and ask questions such as, "When should the next maintenance be performed?" This question is sent to the server and analyzed.

[0974] Step 11:

[0975] The server receives the query, generates an appropriate maintenance plan and actions, and sends it to the management terminal. The plan is then presented to the administrator via an avatar. For example, specific instructions are provided, such as "Perform the next maintenance on 2023-10-15 and replace the sensor."

[0976] Step 12:

[0977] The server monitors the implementation of the plan and provides feedback as needed, ensuring that the plan is carried out reliably.

[0978] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0979] As an embodiment of the present invention, the processing of the program will be explained below in natural language.

[0980] 1. Data Collection

[0981] User: Installs the application and creates an account. Enters personal information and completes account setup.

[0982] User: After creating an account, the user enters physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, sleep patterns) into the device.

[0983] Terminal: Sends the entered data to the server.

[0984] 2. Data Analysis

[0985] Server: Stores the received health data in a database.

[0986] Server: Inputs stored health data into an AI model to assess health status and potential risks.

[0987] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[0988] 3. Avatar generation and display

[0989] Server: Sends the generated virtual health avatar data to the user terminal.

[0990] Terminal: Prepare to visually display the received avatar data.

[0991] Terminal: Sends a notification to the user that the avatar display is complete.

[0992] 4. Interaction

[0993] User: Starts a conversation with the virtual health avatar. Enters a question or concern into the avatar. For example, "I've been feeling tired lately. What should I do?"

[0994] Terminal: Sends the user's question to the server as text data.

[0995] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[0996] Server: Sends the generated advice to the user terminal as text data.

[0997] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[0998] 5. Emotion recognition

[0999] Terminal: The emotion engine analyzes the user's facial expressions, voice, and input patterns.

[1000] Terminal: Sends the recognized emotion data to the server.

[1001] Server: Adjusts health action plans and advice based on emotion data. For example, if a user is feeling stressed, it generates advice on how to reduce stress.

[1002] Server: Sends adjustment advice based on emotion data to the user's device.

[1003] 6. Health action plan development and monitoring

[1004] User: Create a health action plan based on advice from the avatar and emotion engine. For example, create a plan to jog three times a week.

[1005] User: Enter the health action plan into the terminal.

[1006] Terminal: Sends the input action plan data to the server.

[1007] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[1008] 7. Feedback and motivation

[1009] Server: Periodically analyzes user behavior data and evaluates the progress of the plan.

[1010] Server: Generates messages that provide feedback and motivation based on progress. For example, if you are jogging as planned, send a message praising you.

[1011] Server: Sends the generated feedback and motivation messages to the user terminal.

[1012] Terminal: Presents feedback and motivational messages to the user through an avatar.

[1013] Specific examples

[1014] Example 1: Understanding your health status

[1015] User: A 30-year-old man, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[1016] Terminal: Sends input data to the server.

[1017] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[1018] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[1019] Example 2: Creating a Health Action Plan

[1020] User: Asks avatar, "How can I get more exercise?"

[1021] Terminal: Sends the question to the server.

[1022] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[1023] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[1024] User: Accept the advice and develop a health action plan.

[1025] Example 3: Feedback using emotion recognition

[1026] User: Type into your avatar "I've been feeling stressed lately."

[1027] Terminal: The emotion engine recognizes stress from the user's facial expressions and voice, and sends that data to the server.

[1028] Server: Analyzes emotional data and generates stress reduction advice, such as "Try some relaxation techniques."

[1029] Device: The avatar tells the user to "Try some relaxation techniques."

[1030] This system allows users to gain a deeper understanding of their own health and emotional state, enabling them to effectively continue specific health behaviors.

[1031] The processing flow will be explained below.

[1032] Step 1:

[1033] User: Installs the application and creates an account. Enters personal information and completes account setup.

[1034] Step 2:

[1035] Terminal: Displays an input screen to collect data on physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) based on user input.

[1036] Step 3:

[1037] User: Follow the collection screen and enter the necessary health data, such as height 170cm, weight 70kg, meal frequency, exercise habits, etc.

[1038] Step 4:

[1039] Terminal: Formats the input data and sends it to the server.

[1040] Step 5:

[1041] Server: Stores the received health data in a database.

[1042] Step 6:

[1043] Server: Inputs stored health data into the AI ​​model to assess the user's health status and potential risks.

[1044] Step 7:

[1045] Server: Based on the analysis results, a virtual health avatar specialized for each user is generated.

[1046] Step 8:

[1047] Server: Sends the generated virtual health avatar data to the user terminal.

[1048] Step 9:

[1049] Terminal: Prepare to visually display the received avatar data.

[1050] Step 10:

[1051] Terminal: Sends a notification to the user that the avatar display is complete.

[1052] Step 11:

[1053] User: Starts a conversation with the virtual health avatar displayed on the device. Enters a question or concern into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[1054] Step 12:

[1055] Terminal: Sends the user's question to the server as text data.

[1056] Step 13:

[1057] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[1058] Step 14:

[1059] Server: Sends the generated advice to the user terminal as text data.

[1060] Step 15:

[1061] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[1062] Step 16:

[1063] Terminal: The emotion engine analyzes the user's facial expressions, voice, and input patterns.

[1064] Step 17:

[1065] Terminal: Sends the recognized emotion data to the server.

[1066] Step 18:

[1067] Server: Adjusts health action plans and advice based on emotion data. For example, if a user is feeling stressed, it generates advice on how to reduce stress.

[1068] Step 19:

[1069] Server: Sends adjustment advice based on emotion data to the user's device.

[1070] Step 20:

[1071] Terminal: Presents visual and audio advice tailored to the user through an avatar.

[1072] Step 21:

[1073] User: Create a health action plan based on advice from the avatar and emotion engine. For example, enter a plan such as "jog three times a week."

[1074] Step 22:

[1075] Terminal: Sends the created health action plan data to the server.

[1076] Step 23:

[1077] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[1078] Step 24:

[1079] User: Follows the plan and regularly records their actions (for example, jogging progress) in the app.

[1080] Step 25:

[1081] Terminal: Sends recorded behavioral data to the server.

[1082] Step 26:

[1083] Server: Analyzes the received behavioral data and evaluates the progress of the health behavior plan.

[1084] Step 27:

[1085] Server: Generates feedback and motivational messages based on progress. For example, if you are jogging according to plan, send a message praising you.

[1086] Step 28:

[1087] Server: Sends the generated feedback and motivation messages to the user terminal.

[1088] Step 29:

[1089] Terminal: Presents feedback and motivational messages to the user through an avatar.

[1090] By repeating the above process, the user can gain a deeper understanding of their own health and emotional state and effectively continue to take specific health actions.

[1091] Example 2

[1092] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1093] In modern society, many people are interested in managing their health and improving their lifestyles, but the difficulty of self-management and lack of individualized support are issues. In particular, there is a demand for comprehensive support that includes health status monitoring and emotional recognition, and a system that can provide this effectively is necessary.

[1094] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1095] In this invention, the server includes means for inputting a user's physical characteristics, genetic information, and lifestyle habits, means for transmitting the input data to the server, means for the server to analyze the health data and generate a virtual health avatar, means for transmitting the generated virtual health avatar to a user terminal and visually displaying it, means for the user to interact with the virtual health avatar and send questions to the server, means for the server to analyze the questions and generate an appropriate health action plan and advice, means for transmitting the generated advice to the user terminal and presenting it to the user via the avatar, means for the user to formulate a health action plan and input it to the terminal, means for storing the input action plan data on the server and monitoring it, means for the terminal to analyze the user's facial expressions, voice, and input patterns and transmit emotional data to the server, and means for the server to adjust advice based on the emotional data and transmit it to the user terminal, thereby enabling the user to receive support for comprehensive health management and emotional management.

[1096] "User" refers to any individual or entity that uses the System.

[1097] "Physical characteristics" refers to physical data such as a user's height, weight, age, and gender.

[1098] "Genetic information" refers to data relating to a user's DNA analysis results and genetic characteristics.

[1099] "Lifestyle habits" refers to data related to the user's daily life, such as diet, exercise, and sleep patterns.

[1100] "Terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[1101] "Server" refers to a central processing unit for analyzing data received from a user and providing the analysis results to the user.

[1102] "Health data" collectively refers to data such as a user's physical characteristics, genetic information, and lifestyle habits.

[1103] "Virtual health avatar" refers to a digital character generated to visually represent a user's health status.

[1104] "Dialogue" refers to text and / or voice communication between the user and the virtual health avatar.

[1105] A "health action plan" refers to a specific plan that a user makes to maintain or improve their health.

[1106] "Monitoring" refers to the process of tracking the progress of a user's health action plan and recording and evaluating the data.

[1107] "Emotion data" refers to data related to emotions analyzed from the user's facial expressions, voice, input patterns, etc.

[1108] "Advice" refers to specific instructions or suggestions for maintaining or improving health provided to the user by the server.

[1109] As an embodiment of the present invention, the processing of the program will be specifically described below, clearly indicating what hardware and software are used and what data processing and calculations are performed.

[1110] Explanation of program processing

[1111] Data collection

[1112] Users first install the application on their smartphone or tablet, create an account, and then enter personal information (such as name, email address, and password) to complete the setup.

[1113] After creating an account, users enter their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) via their device.

[1114] The device sends these input data to the server using an internet connection and a RESTful API.

[1115] Data analysis

[1116] The server stores the received health data in a relational database (e.g., MySQL).

[1117] The server uses the stored health data to input into a generative AI model, which then assesses the user's health status and potential risks using the generative AI model (e.g., TensorFlow, PyTorch).

[1118] The server generates a virtual health avatar based on the analysis results.

[1119] Avatar generation and display

[1120] The server sends the generated virtual health avatar data (e.g., 3D model data) to the user's device via an internet connection and a RESTful API.

[1121] The device analyzes the received avatar data and prepares it for rendering for visual display using a 3D rendering library (e.g., Unity, Unreal Engine).

[1122] The device notifies the user that the avatar display has been completed by using a push notification or a pop-up message.

[1123] Interaction

[1124] The user begins a conversation with the virtual health avatar. They enter their questions or concerns in text format into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[1125] The device sends the user's questions to the server using an internet connection and a RESTful API.

[1126] The server analyzes the questions using natural language processing (NLP) technology and generates appropriate health action plans and advice, such as suggestions for increasing exercise and guidance on nutritional balance.

[1127] The server transmits the generated advice to the user terminal as text data.

[1128] The terminal presents the advice generated through the avatar to the user visually and audibly.

[1129] emotion recognition

[1130] The device analyzes the user's facial expressions, voice, and input patterns using an emotion engine (e.g., Microsoft Azure Emotion API, Google Cloud Vision API).

[1131] The device transmits the recognized emotion data to a server using an internet connection and a RESTful API.

[1132] The server adjusts health action plans and advice based on emotion data. For example, if the user is feeling stressed, it generates advice on how to reduce stress.

[1133] The server transmits adjustment advice based on the emotion data to the user terminal.

[1134] Health action plan development and monitoring

[1135] The user creates a health action plan based on advice from the avatar and emotion data. For example, the user might plan to "jog three times a week."

[1136] The user inputs the health action plan that has been created into the terminal.

[1137] The terminal transmits the input action plan data to the server.

[1138] The server stores the health action plan data in a database and begins monitoring the plan.

[1139] Feedback and motivation

[1140] The server periodically analyzes user behavior data and evaluates the progress of the plan, using machine learning models (e.g., Scikit-learn).

[1141] The server generates feedback and motivational messages based on progress, e.g., praise messages based on frequency and duration of jogging.

[1142] The server transmits the generated feedback and motivation messages to the user terminal.

[1143] The device presents feedback and motivational messages to the user through the avatar.

[1144] Specific examples

[1145] Example 1: Understanding your health status

[1146] A user enters information such as height 170cm, weight 70kg, and age 30.

[1147] The terminal transmits the input data to the server.

[1148] The server analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[1149] The device displays an avatar telling the user, "Your BMI is a little higher than normal. You should exercise more."

[1150] Example 2: Creating a Health Action Plan

[1151] The user asks the avatar, "How can I get more exercise?"

[1152] The terminal sends a query to the server.

[1153] Based on the user's activity level, the server generates advice such as, "Try jogging for 30 minutes three times a week."

[1154] On the device, an avatar tells the user to "start jogging for 30 minutes three times a week."

[1155] The user accepts the advice and creates a health action plan.

[1156] Example 3: Feedback using emotion recognition

[1157] A user types into their avatar, "I've been feeling stressed lately."

[1158] The device's emotion engine recognizes stress from the user's facial expressions and voice, and sends that data to a server.

[1159] The server analyzes the emotional data and generates stress reduction advice, e.g., "Try relaxation techniques."

[1160] The device has an avatar telling the user to "try some relaxation techniques."

[1161] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1162] Step 1:

[1163] A user installs the application on a smartphone or tablet and creates an account. The user completes the setup by entering personal information such as name, email address, and password. The input data includes, for example, the name "Taro Tanaka," the email address "tanaka@example.com," and the password. The device sends this input data to the server. As an output, the user information is registered on the server and a user ID is generated.

[1164] Step 2:

[1165] After creating an account, users input their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.). The input is done using a form within the application. The device sends this input data to the server. As an output, the user's health data is stored in the server's database.

[1166] Step 3:

[1167] The server stores the received health data in a relational database (e.g., MySQL). The server inputs the stored health data into a generative AI model (e.g., TensorFlow, PyTorch) to evaluate the user's health status and potential risks. During the evaluation process, for example, BMI calculation is performed, and an evaluation result such as "slightly higher than normal" is obtained. The analysis result is generated as an output.

[1168] Step 4:

[1169] The server generates a virtual health avatar based on the analysis results. This uses an algorithm (e.g., Unity, Unreal Engine) to generate a 3D character model. The generated virtual health avatar is saved as digital data. The output is the virtual health avatar data.

[1170] Step 5:

[1171] The server sends the generated virtual health avatar data to the user's device via an internet connection and a RESTful API. The device analyzes the received avatar data and prepares rendering for visual display. As an output, a 3D model of the avatar is ready to be displayed on the device.

[1172] Step 6:

[1173] The device notifies the user that avatar display has been completed. This notification is sent via a push notification or a pop-up message. By receiving this notification, the user can confirm that the system is operating normally. As an output, a notification of avatar display completion is sent to the user.

[1174] Step 7:

[1175] The user starts a dialogue with the virtual health avatar. For example, the user inputs a question such as, "I've been feeling tired a lot recently. What should I do?" The device sends the user's question to the server as text data. The content of the question is sent to the server as output.

[1176] Step 8:

[1177] The server analyzes the received question using natural language processing (NLP) technology. A pre-trained generative AI model (e.g., GPT-3) is used for the analysis. Based on the analysis results, the server generates an appropriate health action plan and advice through the generative AI model. For example, advice such as "suggestions to increase exercise and guidance on nutritional balance" is generated. The advice is obtained as output.

[1178] Step 9:

[1179] The server sends the generated advice to the user's device via an internet connection and a RESTful API. The device then presents the generated advice to the user visually and audibly through an avatar. For example, the avatar might say, "You should exercise more." The user receives the advice as output.

[1180] Step 10:

[1181] The device analyzes the user's facial expressions, voice, and input patterns using an emotion engine (e.g., Microsoft Azure Emotion API, Google Cloud Vision API). The analysis process uses a camera and microphone. The device sends the recognized emotion data to the server. As an output, the emotion data is sent to the server.

[1182] Step 11:

[1183] The server adjusts the health action plan and advice based on the emotion data. An algorithm based on the emotion data is used for the analysis, and generates, for example, "advice on how to reduce stress when the user is feeling stressed." The server then sends the adjusted advice to the user's device. The adjusted advice is obtained as the output.

[1184] Step 12:

[1185] The device presents the adjusted advice to the user through the avatar, for example, the avatar says in a voice, "Try some relaxation techniques." As an output, the user receives the adjusted advice.

[1186] Step 13:

[1187] The user creates a health action plan based on advice from the avatar and emotion data. For example, the user can create a plan to "jog three times a week." The user inputs the created plan into the terminal. The action plan data is obtained as output.

[1188] Step 14:

[1189] The device sends the input action plan data to the server. The transmission is performed using an internet connection and a RESTful API. The server stores the action plan data in a database. As an output, the action plan data is stored on the server.

[1190] Step 15:

[1191] The server periodically analyzes the user's behavioral data and evaluates the progress of the plan. This is done using a machine learning model (e.g., Scikit-learn). The server generates feedback and motivational messages based on the progress made based on the analysis results. For example, it generates a message such as "You're doing great!" based on the frequency and duration of jogging. The feedback message is obtained as an output.

[1192] Step 16:

[1193] The server sends the generated feedback and motivation messages to the user's device using an internet connection and a RESTful API. The device presents the feedback messages to the user through an avatar. For example, the avatar might say "Great! Keep it up!". As an output, the user receives the feedback.

[1194] (Application example 2)

[1195] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1196] While conventional health management systems allow users to plan health behaviors, they struggle to maintain the motivation to actually follow through with them. Furthermore, they lack the means to monitor users' emotions and stress levels and adjust advice accordingly, resulting in a lack of personalized care.

[1197] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for awarding electronic payment points according to the degree of achievement of the health action plan, a means for monitoring the user's emotions and stress level using an emotion recognition engine, and a means for adjusting the health action plan and advice based on the monitoring results. This makes it easier for the user to maintain motivation to carry out the action plan and allows them to receive personalized feedback.

[1198] "User's physical characteristics" refers to the user's physical attributes such as height, weight, body fat percentage, muscle mass, etc.

[1199] "Genetic information" refers to the results of a user's DNA analysis and information about their genes.

[1200] "Lifestyle habits" refers to the user's daily behavior patterns, dietary habits, exercise habits, sleep patterns, and other habits.

[1201] "Server" refers to a central computer system that analyzes and stores data and provides information to users.

[1202] "Virtual health avatar" refers to a digital character generated to visually represent a user's health status.

[1203] "Electronic payment points" refers to digital rewards awarded according to the degree to which a user achieves their action plan.

[1204] An "emotion recognition engine" refers to software that analyzes a user's facial expressions and voice to determine their emotions and stress level.

[1205] A "health action plan" refers to a plan regarding exercise, diet, and lifestyle habits that is drawn up by a user.

[1206] "Monitoring" refers to the server periodically monitoring and evaluating the user's progress in their action plan and their emotional state.

[1207] "Feedback" refers to information that the server provides to the user regarding analysis results and evaluations.

[1208] This invention is a system that allows users to manage their own health status and maintain motivation. Specifically, the system begins when a user enters their physical characteristics, genetic information, and lifestyle habits through an application and sends the data to a server. This data is analyzed by the server and a virtual healthy avatar is generated.

[1209] Technology and hardware used

[1210] Programming language: Python

[1211] Database: MySQL

[1212] AI model: TensorFlow

[1213] Emotion recognition engine: OpenCV, Dlib

[1214] Frontend: React Native

[1215] Server: AWS EC2

[1216] Electronic payment system: Stripe

[1217] Data collection

[1218] Users download the smartphone app and enter data such as physical characteristics, genetic information, and lifestyle habits. The data is sent to the server in real time.

[1219] Data analysis and avatar generation

[1220] The server analyzes the received health data and inputs it into a model that evaluates the user's health status using TensorFlow. Based on the analysis results, a virtual health avatar is generated and sent to the user's device.

[1221] Interacting with avatars

[1222] Users can interact with the virtual health avatar and ask questions or seek advice about their health. This interaction takes place in real time, and the entered questions are sent to the server, which analyzes the questions and generates appropriate health action plans and advice.

[1223] emotion recognition

[1224] The user's facial expressions and voice are captured using the smartphone's camera and microphone, and analyzed using an emotion recognition engine (OpenCV, Dlib). The analysis results are sent to a server, which monitors the user's emotions and stress level.

[1225] Implementing and monitoring health action plans

[1226] The user follows the instructions of the virtual health avatar to create a specific health action plan. This plan is input into the device and stored on the server. The server periodically monitors the progress of the plan and provides feedback to the user on the evaluation results.

[1227] Electronic payment points awarded

[1228] Each time a user completes a health action plan, points are added to the user's account using an electronic payment system (Stripe). These points can then be used to purchase products, etc.

[1229] Specific examples

[1230] Example prompt sentence:

[1231] "I'm a 30-year-old male, 170cm tall and weigh 70kg. I've been feeling tired easily lately. I'd like some suggestions for an exercise plan and stress reduction."

[1232] Example flow:

[1233] 1. A user creates an account and enters data such as height, weight, and age.

[1234] 2. The server receives the data, analyzes it with an AI model, and generates a virtual health avatar.

[1235] 3. The user interacts with the avatar and receives suggestions for exercise plans and stress reduction.

[1236] 4. An emotion recognition engine analyzes the user's emotional state and adjusts advice as needed.

[1237] 5. The user takes action based on the health action plan they created, and the server monitors their progress.

[1238] 6. Electronic payment points are awarded according to the level of achievement, and users can use these points to obtain incentives.

[1239] Through the above steps, the present invention not only enables the user to manage their health condition and create an effective action plan, but also provides the motivation to continue the plan.

[1240] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1241] Step 1: A user creates an account and enters their physical characteristics, genetic information, and lifestyle habits.

[1242] Input: Information such as the user's height, weight, age, exercise habits, dietary patterns, and DNA analysis results.

[1243] Process: The user enters the required information on the smartphone application screen.

[1244] Output: The input information is sent to the cloud server in JSON format.

[1245] Step 2: The server stores the received data.

[1246] Input: Health data submitted by the user in JSON format.

[1247] Processing: Save the received data in a MySQL database.

[1248] Output: User's health information stored in a database.

[1249] Step 3: The server analyzes the stored health data.

[1250] Input: User's health data stored in a database.

[1251] Processing: Analyze health data using TensorFlow to assess the user's health status.

[1252] Output: Health status assessment results (e.g. BMI, body fat percentage, potential risks).

[1253] Step 4: The server generates a virtual health avatar and sends it to the user terminal.

[1254] Input: Health status assessment results.

[1255] Processing: A virtual health avatar is generated based on the evaluation results, and the data is sent to the user terminal.

[1256] Output: Virtual health avatar data sent to the user device.

[1257] Step 5: The device visually displays the virtual health avatar and notifies the user.

[1258] Input: Virtual health avatar data sent from the server.

[1259] Processing: Graphically display the avatar on the user's device and send notifications to the user.

[1260] Output: Visually displayed virtual health avatar and notification.

[1261] Step 6: The user interacts with the virtual health avatar and inputs a health question.

[1262] Input: User's text question (e.g. "I've been feeling tired a lot lately. What should I do?").

[1263] Process: The user enters a question in the application and sends it to the server.

[1264] Output: The user's question data sent to the server.

[1265] Step 7: The server parses the question and generates a health action plan and advice.

[1266] Input: Question data submitted by the user.

[1267] Processing: The question data is fed into a natural language processing engine to generate appropriate health action plans and advice.

[1268] Output: Generated health action plans and advice.

[1269] Step 8: The server sends the generated advice to the user terminal.

[1270] Input: Generated health action plans and advice.

[1271] Processing: The generated advice is sent to the user's terminal.

[1272] Output: Advice data sent to the user terminal.

[1273] Step 9: The terminal presents the generated advice to the user through the avatar.

[1274] Input: Advice data sent by the server.

[1275] Processing: Advice is presented to the user visually and audibly through an avatar.

[1276] Output: Health action plan and advice presented to the user.

[1277] Step 10: The user communicates their emotions and stress to the avatar.

[1278] Input: Text or voice input about the user's emotions or stress (e.g., "I've been feeling stressed lately").

[1279] Processing: The smartphone's camera and microphone are used to capture the user's facial expressions and voice, which are then analyzed by an emotion recognition engine.

[1280] Output: Parsed emotion data.

[1281] Step 11: The server adjusts the advice based on the emotion data.

[1282] Input: Parsed emotion data.

[1283] Processing: Adjusting health action plans and advice based on emotional data.

[1284] Output: Adjusted advice.

[1285] Step 12: The adjusted advice is sent to the user terminal and presented through the avatar.

[1286] Input: Tailored advice.

[1287] Processing: The server sends the adjusted advice to the device and presents it through the avatar.

[1288] Output: Tuning advice presented to the user.

[1289] Step 13: The user creates a health action plan and inputs it into the terminal.

[1290] Input: A health action plan created by the user (e.g., jogging three times a week).

[1291] Processing: An action plan is entered on the terminal and sent to the server.

[1292] Output: Action plan data sent to the server.

[1293] Step 14: The server stores the action plan data and performs monitoring.

[1294] Input: Submitted action plan data.

[1295] Processing: Store in a database and periodically monitor the progress of the plan.

[1296] Output: Monitoring results and progress reports.

[1297] Step 15: The server awards electronic payment points according to the progress.

[1298] Input: Health action plan progress data.

[1299] Processing: Points are awarded based on progress using an electronic payment system.

[1300] Output: Electronic payment points awarded to the user.

[1301] Step 16: The terminal presents feedback and motivational messages to the user.

[1302] Input: Feedback and motivation messages from the server.

[1303] Processing: The message is presented to the user visually and audibly through an avatar.

[1304] Output: Feedback and motivational messages presented to the user.

[1305] This series of processing flows enables users to efficiently manage their own health condition and maintain continuous motivation by carrying out action plans and obtaining incentives.

[1306] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1307] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1308] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1309] [Third embodiment]

[1310] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1311] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1312] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1313] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1314] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1315] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1316] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1317] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1318] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1319] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1320] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1321] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1322] As an embodiment of the present invention, the processing of the program will be explained below in natural language.

[1323] 1. Data Collection

[1324] Users: Install the application and create an account.

[1325] User: After creating an account, the user enters physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, sleep patterns) into the device.

[1326] Terminal: Sends the entered data to the server.

[1327] 2. Data Analysis

[1328] Server: Stores the received health data in a database.

[1329] Server: Inputs stored health data into the AI ​​model to assess health status and risks.

[1330] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[1331] 3. Avatar generation and display

[1332] Server: Sends the generated virtual health avatar data to the user terminal.

[1333] Terminal: Visually displays the received avatar data.

[1334] Terminal: Notifies the user that the avatar is ready to be displayed.

[1335] 4. Interaction

[1336] User: Initiates a dialogue with the virtual health avatar. For example, the user asks, "I've been feeling tired a lot lately. What should I do?"

[1337] Terminal: Sends the user's question to the server.

[1338] Server: Analyzes the questions and generates appropriate health action plans and advice.

[1339] Server: Sends the generated advice to the user terminal.

[1340] Terminal: Presents advice to the user through an avatar.

[1341] 5. Health action plan development and monitoring

[1342] User: Create a health action plan based on the avatar's advice. For example, create a plan to "jog three times a week."

[1343] User: Enter the health action plan into the terminal.

[1344] Terminal: Sends the input action plan data to the server.

[1345] Server: Saves the action plan data in the database and starts monitoring.

[1346] 6. Feedback and motivation

[1347] Server: Periodically analyzes user behavior data and evaluates the progress of the plan.

[1348] Server: Generates messages that provide feedback and motivation based on progress.

[1349] Server: Sends generated feedback and motivation messages to the devices.

[1350] Terminal: Presents feedback and motivational messages to the user through an avatar.

[1351] Specific examples

[1352] Example 1: Understanding your health status

[1353] User: A 30-year-old man, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[1354] Terminal: Sends input data to the server.

[1355] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[1356] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[1357] Example 2: Creating a Health Action Plan

[1358] User: Asks avatar, "How can I get more exercise?"

[1359] Terminal: Sends the question to the server.

[1360] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[1361] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[1362] User: Accept the advice and develop a health action plan.

[1363] In this way, the present invention provides users with a deeper understanding of their health status and assistance in implementing specific health behaviors.

[1364] The processing flow will be explained below.

[1365] Step 1:

[1366] User: Installs the application and creates an account. Enters personal information and completes account setup.

[1367] Step 2:

[1368] Terminal: Displays an input screen to collect data on physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) based on user input.

[1369] Step 3:

[1370] User: Follow the collection screen and enter the necessary health data, such as height 170cm, weight 70kg, meal frequency, exercise habits, etc.

[1371] Step 4:

[1372] Terminal: Formats the input data and sends it to the server.

[1373] Step 5:

[1374] Server: Stores the received health data in a database.

[1375] Step 6:

[1376] Server: Inputs stored health data into the AI ​​model to assess the user's health status and potential risks.

[1377] Step 7:

[1378] Server: Based on the analysis results, a virtual health avatar specialized for each user is generated.

[1379] Step 8:

[1380] Server: Sends the generated virtual health avatar data to the user terminal.

[1381] Step 9:

[1382] Terminal: Prepare to visually display the received avatar data.

[1383] Step 10:

[1384] Terminal: Sends a notification to the user that the avatar display is complete.

[1385] Step 11:

[1386] User: Starts a conversation with the virtual health avatar displayed on the device. Enters a question or concern into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[1387] Step 12:

[1388] Terminal: Sends the user's question to the server as text data.

[1389] Step 13:

[1390] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[1391] Step 14:

[1392] Server: Sends the generated advice to the user terminal as text data.

[1393] Step 15:

[1394] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[1395] Step 16:

[1396] User: Create a health action plan based on the avatar's advice. For example, enter a plan such as "jog for 30 minutes three times a week."

[1397] Step 17:

[1398] Terminal: Sends the created health action plan data to the server.

[1399] Step 18:

[1400] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[1401] Step 19:

[1402] User: Follows the plan and regularly records their actions (for example, jogging progress) in the app.

[1403] Step 20:

[1404] Terminal: Sends recorded behavioral data to the server.

[1405] Step 21:

[1406] Server: Analyzes the received behavioral data and evaluates the progress of the health behavior plan.

[1407] Step 22:

[1408] Server: Generates feedback and motivational messages based on progress.

[1409] Step 23:

[1410] Server: Sends the generated feedback and motivation messages to the user terminal.

[1411] Step 24:

[1412] Terminal: Presents feedback and motivational messages to the user through an avatar.

[1413] By repeating the above process, users can gain a deeper understanding of their own health status and continuously practice specific health behaviors.

[1414] Example 1

[1415] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1416] In modern society, it is difficult for users to accurately understand their own health status and develop appropriate health action plans. In particular, health management that takes into account individual physical characteristics, genetic information, and lifestyle habits requires specialized knowledge, making it difficult for many users to effectively maintain their health. In addition, existing systems do not adequately provide continuous monitoring, feedback, or motivation, which means that users' health improvements are not sustainable.

[1417] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1418] In this invention, the server includes: a means for inputting a user's physical characteristics, genetic information, and lifestyle habits; a means for transmitting the input data to the server; a means for analyzing the health data and generating a virtual health avatar; a means for transmitting the generated virtual health avatar to a user terminal and visually displaying it; a means for the user to interact with the virtual health avatar and send questions to the server; a means for the server to analyze the questions and generate an appropriate health action plan and advice; a means for transmitting the generated advice to the user terminal and presenting it to the user via the avatar; a means for the user to create a health action plan and input it into the terminal; a means for storing the input action plan data on the server and monitoring it; a means for periodically analyzing the action data and evaluating progress; and a means for transmitting the generated feedback and motivational messages to the user terminal and presenting them to the user via the avatar. This allows the user to accurately understand their own health status and create and implement an effective health action plan based on their individual characteristics. Furthermore, providing continuous feedback and motivation can be expected to have a lasting effect on the user's health improvement.

[1419] "User" refers to a person who uses the system to manage and improve their health.

[1420] "Physical characteristics" refers to data about the user's body, such as height, weight, and age.

[1421] "Genetic information" refers to data related to genetics, such as the results of a user's DNA analysis.

[1422] "Lifestyle habits" refers to data such as diet, exercise, and sleep patterns in a user's daily life.

[1423] "Terminal" refers to an electronic device used by a user, such as a computer, smartphone, or tablet.

[1424] "Server" refers to a computer system that receives, stores, and analyzes data entered by a user and transmits the generated information to the user terminal.

[1425] "Database" refers to an information management system for storing user health data and action plan data.

[1426] "AI model" refers to the artificial intelligence algorithm used by the server to analyze health status.

[1427] "Virtual health avatar" refers to a digital character that visually represents a user's health status.

[1428] A "question" refers to a health-related inquiry that a user makes to the server through a virtual health avatar.

[1429] A "health action plan" refers to a specific action plan that a user sets out to improve their own health.

[1430] "Monitoring" refers to the process by which the server continuously monitors user behavior data and evaluates progress.

[1431] "Feedback" refers to the evaluation and advice provided by the server regarding the user's behavior and health status.

[1432] "Motivational Message" refers to a message of encouragement or encouragement provided by the server to promote improvement in the user's health.

[1433] This invention is a system that helps users accurately understand their own health status and assists them in formulating and implementing effective health action plans. This system consists of a user, a terminal, and a server.

[1434] Data collection

[1435] First, the user installs the application and creates an account. After creating the account, the user enters their physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, sleep patterns) into the device. The device then sends the entered data to the server. This transmission is performed using an HTTP POST request.

[1436] Data analysis

[1437] The server stores the received health data in a database. The stored data is then fed into an AI model (e.g., TensorFlow or PyTorch) to assess health status and risks. The analysis results are then used to generate a personalized virtual health avatar. This avatar is a digital character that visually represents the user's health status.

[1438] Avatar generation and display

[1439] The generated virtual health avatar is sent from the server to the user's device. The device receives this data and visually displays it. Software such as Unity or Unreal Engine is used for display. The device uses push notifications or alert dialogs to notify the user that the avatar is ready to be displayed.

[1440] Interaction

[1441] The user begins a dialogue with the virtual health avatar. For example, if the user asks, "I've been feeling tired lately. What should I do?", this question is sent from the device to the server. The server analyzes the question using a generative AI model (e.g., GPT-3) and generates an appropriate health action plan and advice. The generated advice is sent from the server to the user's device, which then presents it to the user through the avatar.

[1442] Health action plan development and monitoring

[1443] The user creates a health action plan based on the avatar's advice and enters it into the device. For example, the user may plan to "jog three times a week." The entered action plan data is sent from the device to the server and stored in a database. The server continues to monitor this.

[1444] Feedback and motivation

[1445] The server periodically analyzes the user's behavioral data and evaluates the progress of the plan. It generates feedback and motivational messages based on the progress and sends them to the user's device. The device then presents these messages to the user via an avatar.

[1446] Specific examples

[1447] Understanding your health

[1448] User: A 30-year-old male, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[1449] Terminal: Sends the entered data to the server.

[1450] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[1451] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[1452] Health action plan development

[1453] User: "How can I get more exercise?" asks the avatar.

[1454] Terminal: Sends the question to the server.

[1455] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[1456] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[1457] User: Accept the advice and develop a health action plan.

[1458] Prompt Sentence Examples

[1459] "Calculate BMI based on this user's age, height, and weight and provide appropriate advice."

[1460] In this way, the present invention provides users with a deeper understanding of their health status and assistance in implementing specific health behaviors.

[1461] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1462] Step 1:

[1463] Users: Install the application and create an account.

[1464] Specific actions: Enter your username, email address, password, etc. on the account creation page and click the Register button.

[1465] Input: Username, email address, password, etc.

[1466] Output: Notification that user account creation is complete.

[1467] Step 2:

[1468] User: After creating an account, enter physical characteristics, genetic information, and lifestyle habits into the device.

[1469] Specific actions: Enter the required data into the dedicated input form and click the submit button.

[1470] Input: height, weight, age, DNA results, diet, exercise, sleep patterns, etc.

[1471] Output: Save input data on the device.

[1472] Step 3:

[1473] Terminal: Sends the entered data to the server.

[1474] What happens: The entered data is formatted and then sent to the server using an HTTP POST request.

[1475] Input: height, weight, age, DNA results, diet, exercise, sleep patterns, etc.

[1476] Output: The data sent to the server.

[1477] Step 4:

[1478] Server: Stores the received health data in a database.

[1479] Specific operation: Store the received data in a database such as "MySQL" or "PostgreSQL".

[1480] Input: Health data sent from the device.

[1481] Output: Health data stored in a database.

[1482] Step 5:

[1483] Server: Inputs stored data into an AI model to assess health status and risk.

[1484] Specific operation: Data is retrieved from a database and input into an AI model using a Python script. Possible AI models used include "TensorFlow" and "PyTorch."

[1485] Input: Health data stored in a database.

[1486] Output: Health status and risk assessment results.

[1487] Step 6:

[1488] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[1489] Specific operation: The output from the AI ​​model is processed and passed to an avatar generation algorithm to generate avatar data.

[1490] Input: Health status and risk assessment results.

[1491] Output: Virtual health avatar data.

[1492] Step 7:

[1493] Server: Sends the generated virtual health avatar data to the user terminal.

[1494] Specific operation: The generated avatar data is converted into JSON format and sent to the device via an HTTP POST request.

[1495] Input: Virtual health avatar data.

[1496] Output: Avatar data sent to the device.

[1497] Step 8:

[1498] Terminal: Visually displays the received avatar data.

[1499] Specific operation: Parses JSON data and displays the avatar on the screen using a graphics engine (e.g., "Unity" or "Unreal Engine").

[1500] Input: Received avatar data.

[1501] Output: A visually displayed virtual health avatar.

[1502] Step 9:

[1503] Terminal: Notifies the user that the avatar is ready to be displayed.

[1504] Specific behavior: Notify the user via push notification or alert dialog.

[1505] Input: Avatar display ready status.

[1506] Output: Notification to the user.

[1507] Step 10:

[1508] User: Initiates a dialogue with the virtual health avatar. For example, the user asks, "I've been feeling tired a lot lately. What should I do?"

[1509] Specific actions: Click the text box on the avatar display screen and enter a question.

[1510] Input: Health question text.

[1511] Output: Save the question content on the device.

[1512] Step 11:

[1513] Terminal: Sends the user's question to the server.

[1514] Specific operation: The question text is converted to JSON format and sent to the server via an HTTP POST request.

[1515] Input: Health question text.

[1516] Output: The query data sent to the server.

[1517] Step 12:

[1518] Server: Analyzes questions and generates health action plans and advice. The generative AI model used may be GPT-3.

[1519] Specific operation: The received question text is input into the AI ​​model to generate an answer.

[1520] Input: Question data from the user.

[1521] Output: Generated health action plans and advice.

[1522] Step 13:

[1523] Server: Sends the generated advice to the user terminal.

[1524] Specific operation: The generated advice is converted into JSON format and sent to the terminal via an HTTP POST request.

[1525] Input: Generated advice data.

[1526] Output: Advice data sent to the terminal.

[1527] Step 14:

[1528] Terminal: Presents advice to the user through an avatar.

[1529] Specific operation: The received advice data is displayed, and the avatar provides advice via voice or text.

[1530] Input: Received advice data.

[1531] Output: Advice provided to the user.

[1532] Step 15:

[1533] User: Creates a health action plan based on the avatar's advice and enters it into the device.

[1534] Specific actions: Enter your health action plan using the dedicated form on your device.

[1535] Input: Data on the health action plan you have created.

[1536] Output: Action plan data is saved on the device.

[1537] Step 16:

[1538] Terminal: Sends the input action plan data to the server.

[1539] Specific operation: Convert the action plan data into JSON format and send it to the server via an HTTP POST request.

[1540] Input: Planned action plan data.

[1541] Output: Action plan data sent to the server.

[1542] Step 17:

[1543] Server: Saves the action plan data in the database and starts monitoring.

[1544] Specific behavior: Save planning data to a database and periodically run monitoring scripts.

[1545] Input: Planned action plan data.

[1546] Output: Action plan data stored in a database.

[1547] Step 18:

[1548] Server: Periodically analyzes user behavior data and evaluates progress.

[1549] What it does: It periodically collects data and runs algorithms to evaluate progress.

[1550] Input: Stored action plan data, collected action data.

[1551] Output: Progress assessment results.

[1552] Step 19:

[1553] Server: Generates feedback and motivational messages based on progress and sends them to the user's device.

[1554] Specific operation: A message is generated using the feedback generation algorithm, the generated message is converted to JSON format, and sent to the device via an HTTP POST request.

[1555] Input: Progress assessment results.

[1556] Output: Generated feedback and motivational messages.

[1557] Step 20:

[1558] Terminal: Presents feedback and motivational messages to the user through an avatar.

[1559] Specific operation: A message is displayed on the display screen and provided by an avatar via voice or text.

[1560] Input: Received feedback and motivational messages.

[1561] Output: Feedback and motivational messages to the user.

[1562] (Application example 1)

[1563] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1564] Conventional health management systems are primarily limited to understanding the individual user's health status and formulating action plans, and the scope of these systems is limited to the user. However, managing the operational and maintenance status of robots operating in factories is directly linked to the efficiency and safety of factory operations, and applications in this field are in demand. However, current systems lack the functionality to comprehensively monitor the robot's health status and formulate appropriate maintenance plans. For this reason, there is a strong demand for the development of a system that can reduce robot operational risks and improve production efficiency.

[1565] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1566] In this invention, the server includes a means for inputting a user's physical characteristics, genetic information, and lifestyle habits, a means for transmitting the input data to the server, a means for analyzing the health data and generating a virtual health avatar, a means for visually displaying the generated virtual health avatar and the robot's operating status and component deterioration status, a means for analyzing the robot's operating data and generating a maintenance avatar, and a means for transmitting the generated avatar to a user terminal and a management terminal for interaction. This makes it possible to comprehensively manage the health status of not only users but also robots in the factory and to develop appropriate maintenance plans.

[1567] "User's physical characteristics" refers to the user's physical attributes such as height, weight, age, and gender.

[1568] "Genetic information" refers to DNA analysis results and genetic data.

[1569] "Lifestyle habits" refers to a user's daily life behaviors such as diet, exercise, and sleep patterns.

[1570] "Input Data" refers to information provided by the user relating to physical characteristics, genetic information, and lifestyle habits.

[1571] "Server" refers to a computer system for receiving, storing, and analyzing data.

[1572] "Health Data" refers to data about a user's health status based on their physical characteristics, genetic information, and lifestyle habits.

[1573] A "virtual health avatar" is a digital character that visually represents the user's health status and provides health guidance and advice through interaction.

[1574] "Means for visual display" refers to the function of displaying the generated avatar or data on the screen of a user terminal or an administrative terminal.

[1575] "Robot operation status" refers to data on how much the robot is operating, its operating time, and its condition.

[1576] "Parts deterioration status" refers to data that indicates the degree of deterioration of robot parts.

[1577] A "maintenance avatar" is a digital character that visually represents a robot's health status and maintenance needs, and presents a maintenance plan through interaction.

[1578] "Management terminal" refers to a computer device used by factory staff to manage the operating and maintenance status of robots.

[1579] "Maintenance plan" refers to a schedule of maintenance actions required to reduce robot operation risks and increase production efficiency.

[1580] This invention is a system that inputs a user's physical characteristics, genetic information, and lifestyle habits and uses them to manage their health and the operating status of a robot. Specifically, it is implemented through the following process.

[1581] First, the user installs a dedicated application and inputs their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.). This data is then sent to a server via the device. The server stores the received data in a database and analyzes the health data. Generative AI models such as TensorFlow and PyTorch are used for the analysis.

[1582] Based on the analysis results, the server generates a virtual health avatar and sends the data to the user's device. The generated virtual health avatar is visually displayed on the device, allowing the user to begin a dialogue. For example, if the user asks, "I've been feeling tired a lot lately. What should I do?", the question is sent to the server. The server analyzes the question, generates an appropriate health action plan and advice, and sends it to the user's device. The generated advice is then presented to the user through the virtual health avatar on the device.

[1583] Next, the system collects data on the robots in the factory, including their operating status and the deterioration of their parts, and sends it to a server. This data is also stored in a database and analyzed using a generative AI model. The server generates a maintenance avatar based on the analysis results and sends the data to the robot's management terminal. On the management terminal, the generated maintenance avatar is visually displayed, allowing the manager to initiate a dialogue. For example, if a manager asks, "When should the next maintenance be performed?", the question is sent to the server. The server analyzes the question, generates appropriate maintenance plans and actions, and sends them to the management terminal. On the management terminal, the generated plan is presented to the manager through the maintenance avatar.

[1584] The hardware used to implement these processes includes IoT devices and sensors, and the software includes TensorFlow and PyTorch for generating the health avatars, and a REST API for data transmission.

[1585] Examples:

[1586] 1. Healthcare example:

[1587] Let's say User A is a 30-year-old man, 170 cm tall and weighing 70 kg. He uses a health management app to input his physical characteristics and lifestyle habits. The app sends this data to a server, which analyzes the data and generates advice such as, "Your BMI is a little higher than normal. You should exercise more." A virtual health avatar conveys this advice to User A.

[1588] 2. Robot maintenance example:

[1589] Factory staff member B manages the operating status of a robot. The robot sends data that says, "Operating time: 1500 hours, sensor is deteriorating." The server analyzes the data and generates advice that says, "Perform the next maintenance on 2023-10-15 and replace the sensor." On the management terminal, a maintenance avatar notifies staff member B of this advice.

[1590] Example prompt sentence:

[1591] When should the next maintenance be performed?

[1592] "My robot has reached 1500 hours of operation, what maintenance action should I take next?"

[1593] "If a user's BMI is higher than normal, what kind of exercise should they increase?"

[1594] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1595] Step 1:

[1596] Users install a dedicated application and input their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.). The input data is sent to a server via the user's device. The input data includes physical characteristics such as height, weight, age, genetic information, and lifestyle habits. This allows basic information about the user's own health to be collected.

[1597] Step 2:

[1598] The server stores the received user data in a database. This storage process ensures that each user's health data is securely recorded. The stored data is then input into an AI analysis module to evaluate health status and risks. The AI ​​model used is a generative model based on TensorFlow and PyTorch. The analysis results provide indicators of the user's current health status and potential risks.

[1599] Step 3:

[1600] The server generates a virtual health avatar based on the analysis results. This avatar visually represents the user's health condition. Data on the generated virtual health avatar is sent to the user's device and displayed visually on the device, allowing the user to understand their health condition at a glance.

[1601] Step 4:

[1602] The user starts a dialogue with the virtual health avatar. For example, the user asks the avatar, "I've been feeling tired a lot lately. What should I do?" This question is sent to the server via the user's device. The input is the user's question, and the output is the avatar's answer.

[1603] Step 5:

[1604] The server analyzes the received questions using a natural language processing engine and generates appropriate health action plans and advice. A generative AI model is used for this analysis. The generated advice is then sent back from the server to the user's device and presented to the user via an avatar. For example, specific advice such as "Try jogging for 30 minutes three times a week" is provided.

[1605] Step 6:

[1606] The user creates a health action plan based on the advice provided and enters it into the device through the application. The entered action plan data is then sent back to the server and stored in a database. This records the user's health action plan and allows for future monitoring.

[1607] Step 7:

[1608] The server periodically analyzes the user's behavioral data based on the health action plan and evaluates their progress. This is again done using a generative AI model. Based on the evaluation results, the server generates feedback and motivational messages and sends them to the user's device. For example, a message such as "You're almost there! Keep going!" may be sent.

[1609] Step 8:

[1610] In the factory, the robot's operating status and the deterioration status of its parts are collected and sent to a server. The input data includes operating hours, part status, etc. This allows the robot's health status to be understood.

[1611] Step 9:

[1612] The server stores the received robot data in a database and analyzes it using a generative AI model. Based on the analysis results, a maintenance avatar is generated and sent to a management terminal. This visually displays which robots require maintenance and to what extent.

[1613] Step 10:

[1614] At the management terminal, staff interact with the maintenance avatar and ask questions such as, "When should the next maintenance be performed?" This question is sent to the server and analyzed.

[1615] Step 11:

[1616] The server receives the query, generates an appropriate maintenance plan and actions, and sends it to the management terminal. The plan is then presented to the administrator via an avatar. For example, specific instructions are provided, such as "Perform the next maintenance on 2023-10-15 and replace the sensor."

[1617] Step 12:

[1618] The server monitors the implementation of the plan and provides feedback as needed, ensuring that the plan is carried out reliably.

[1619] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1620] As an embodiment of the present invention, the processing of the program will be explained below in natural language.

[1621] 1. Data Collection

[1622] User: Installs the application and creates an account. Enters personal information and completes account setup.

[1623] User: After creating an account, the user enters physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, sleep patterns) into the device.

[1624] Terminal: Sends the entered data to the server.

[1625] 2. Data Analysis

[1626] Server: Stores the received health data in a database.

[1627] Server: Inputs stored health data into an AI model to assess health status and potential risks.

[1628] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[1629] 3. Avatar generation and display

[1630] Server: Sends the generated virtual health avatar data to the user terminal.

[1631] Terminal: Prepare to visually display the received avatar data.

[1632] Terminal: Sends a notification to the user that the avatar display is complete.

[1633] 4. Interaction

[1634] User: Starts a conversation with the virtual health avatar. Enters a question or concern into the avatar. For example, "I've been feeling tired lately. What should I do?"

[1635] Terminal: Sends the user's question to the server as text data.

[1636] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[1637] Server: Sends the generated advice to the user terminal as text data.

[1638] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[1639] 5. Emotion recognition

[1640] Terminal: The emotion engine analyzes the user's facial expressions, voice, and input patterns.

[1641] Terminal: Sends the recognized emotion data to the server.

[1642] Server: Adjusts health action plans and advice based on emotion data. For example, if a user is feeling stressed, it generates advice on how to reduce stress.

[1643] Server: Sends adjustment advice based on emotion data to the user's device.

[1644] 6. Health action plan development and monitoring

[1645] User: Create a health action plan based on advice from the avatar and emotion engine. For example, create a plan to jog three times a week.

[1646] User: Enter the health action plan into the terminal.

[1647] Terminal: Sends the input action plan data to the server.

[1648] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[1649] 7. Feedback and motivation

[1650] Server: Periodically analyzes user behavior data and evaluates the progress of the plan.

[1651] Server: Generates messages that provide feedback and motivation based on progress. For example, if you are jogging as planned, send a message praising you.

[1652] Server: Sends the generated feedback and motivation messages to the user terminal.

[1653] Terminal: Presents feedback and motivational messages to the user through an avatar.

[1654] Specific examples

[1655] Example 1: Understanding your health status

[1656] User: A 30-year-old man, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[1657] Terminal: Sends input data to the server.

[1658] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[1659] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[1660] Example 2: Creating a Health Action Plan

[1661] User: Asks avatar, "How can I get more exercise?"

[1662] Terminal: Sends the question to the server.

[1663] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[1664] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[1665] User: Accept the advice and develop a health action plan.

[1666] Example 3: Feedback using emotion recognition

[1667] User: Type into your avatar "I've been feeling stressed lately."

[1668] Terminal: The emotion engine recognizes stress from the user's facial expressions and voice, and sends that data to the server.

[1669] Server: Analyzes emotional data and generates stress reduction advice, such as "Try some relaxation techniques."

[1670] Device: The avatar tells the user to "Try some relaxation techniques."

[1671] This system allows users to gain a deeper understanding of their own health and emotional state, enabling them to effectively continue specific health behaviors.

[1672] The processing flow will be explained below.

[1673] Step 1:

[1674] User: Installs the application and creates an account. Enters personal information and completes account setup.

[1675] Step 2:

[1676] Terminal: Displays an input screen to collect data on physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) based on user input.

[1677] Step 3:

[1678] User: Follow the collection screen and enter the necessary health data, such as height 170cm, weight 70kg, meal frequency, exercise habits, etc.

[1679] Step 4:

[1680] Terminal: Formats the input data and sends it to the server.

[1681] Step 5:

[1682] Server: Stores the received health data in a database.

[1683] Step 6:

[1684] Server: Inputs stored health data into the AI ​​model to assess the user's health status and potential risks.

[1685] Step 7:

[1686] Server: Based on the analysis results, a virtual health avatar specialized for each user is generated.

[1687] Step 8:

[1688] Server: Sends the generated virtual health avatar data to the user terminal.

[1689] Step 9:

[1690] Terminal: Prepare to visually display the received avatar data.

[1691] Step 10:

[1692] Terminal: Sends a notification to the user that the avatar display is complete.

[1693] Step 11:

[1694] User: Starts a conversation with the virtual health avatar displayed on the device. Enters a question or concern into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[1695] Step 12:

[1696] Terminal: Sends the user's question to the server as text data.

[1697] Step 13:

[1698] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[1699] Step 14:

[1700] Server: Sends the generated advice to the user terminal as text data.

[1701] Step 15:

[1702] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[1703] Step 16:

[1704] Terminal: The emotion engine analyzes the user's facial expressions, voice, and input patterns.

[1705] Step 17:

[1706] Terminal: Sends the recognized emotion data to the server.

[1707] Step 18:

[1708] Server: Adjusts health action plans and advice based on emotion data. For example, if a user is feeling stressed, it generates advice on how to reduce stress.

[1709] Step 19:

[1710] Server: Sends adjustment advice based on emotion data to the user's device.

[1711] Step 20:

[1712] Terminal: Presents visual and audio advice tailored to the user through an avatar.

[1713] Step 21:

[1714] User: Create a health action plan based on advice from the avatar and emotion engine. For example, enter a plan such as "jog three times a week."

[1715] Step 22:

[1716] Terminal: Sends the created health action plan data to the server.

[1717] Step 23:

[1718] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[1719] Step 24:

[1720] User: Follows the plan and regularly records their actions (for example, jogging progress) in the app.

[1721] Step 25:

[1722] Terminal: Sends recorded behavioral data to the server.

[1723] Step 26:

[1724] Server: Analyzes the received behavioral data and evaluates the progress of the health behavior plan.

[1725] Step 27:

[1726] Server: Generates feedback and motivational messages based on progress. For example, if you are jogging according to plan, send a message praising you.

[1727] Step 28:

[1728] Server: Sends the generated feedback and motivation messages to the user terminal.

[1729] Step 29:

[1730] Terminal: Presents feedback and motivational messages to the user through an avatar.

[1731] By repeating the above process, the user can gain a deeper understanding of their own health and emotional state and effectively continue to take specific health actions.

[1732] Example 2

[1733] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1734] In modern society, many people are interested in managing their health and improving their lifestyles, but the difficulty of self-management and lack of individualized support are issues. In particular, there is a demand for comprehensive support that includes health status monitoring and emotional recognition, and a system that can provide this effectively is necessary.

[1735] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1736] In this invention, the server includes means for inputting a user's physical characteristics, genetic information, and lifestyle habits, means for transmitting the input data to the server, means for the server to analyze the health data and generate a virtual health avatar, means for transmitting the generated virtual health avatar to a user terminal and visually displaying it, means for the user to interact with the virtual health avatar and send questions to the server, means for the server to analyze the questions and generate an appropriate health action plan and advice, means for transmitting the generated advice to the user terminal and presenting it to the user via the avatar, means for the user to formulate a health action plan and input it to the terminal, means for storing the input action plan data on the server and monitoring it, means for the terminal to analyze the user's facial expressions, voice, and input patterns and transmit emotional data to the server, and means for the server to adjust advice based on the emotional data and transmit it to the user terminal, thereby enabling the user to receive support for comprehensive health management and emotional management.

[1737] "User" refers to any individual or entity that uses the System.

[1738] "Physical characteristics" refers to physical data such as a user's height, weight, age, and gender.

[1739] "Genetic information" refers to data relating to a user's DNA analysis results and genetic characteristics.

[1740] "Lifestyle habits" refers to data related to the user's daily life, such as diet, exercise, and sleep patterns.

[1741] "Terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[1742] "Server" refers to a central processing unit for analyzing data received from a user and providing the analysis results to the user.

[1743] "Health data" collectively refers to data such as a user's physical characteristics, genetic information, and lifestyle habits.

[1744] "Virtual health avatar" refers to a digital character generated to visually represent a user's health status.

[1745] "Dialogue" refers to text and / or voice communication between the user and the virtual health avatar.

[1746] A "health action plan" refers to a specific plan that a user makes to maintain or improve their health.

[1747] "Monitoring" refers to the process of tracking the progress of a user's health action plan and recording and evaluating the data.

[1748] "Emotion data" refers to data related to emotions analyzed from the user's facial expressions, voice, input patterns, etc.

[1749] "Advice" refers to specific instructions or suggestions for maintaining or improving health provided to the user by the server.

[1750] As an embodiment of the present invention, the processing of the program will be specifically described below, clearly indicating what hardware and software are used and what data processing and calculations are performed.

[1751] Explanation of program processing

[1752] Data collection

[1753] Users first install the application on their smartphone or tablet, create an account, and then enter personal information (such as name, email address, and password) to complete the setup.

[1754] After creating an account, users enter their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) via their device.

[1755] The device sends these input data to the server using an internet connection and a RESTful API.

[1756] Data analysis

[1757] The server stores the received health data in a relational database (e.g., MySQL).

[1758] The server uses the stored health data to input into a generative AI model, which then assesses the user's health status and potential risks using the generative AI model (e.g., TensorFlow, PyTorch).

[1759] The server generates a virtual health avatar based on the analysis results.

[1760] Avatar generation and display

[1761] The server sends the generated virtual health avatar data (e.g., 3D model data) to the user's device via an internet connection and a RESTful API.

[1762] The device analyzes the received avatar data and prepares it for rendering for visual display using a 3D rendering library (e.g., Unity, Unreal Engine).

[1763] The device notifies the user that the avatar display has been completed by using a push notification or a pop-up message.

[1764] Interaction

[1765] The user begins a conversation with the virtual health avatar. They enter their questions or concerns in text format into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[1766] The device sends the user's questions to the server using an internet connection and a RESTful API.

[1767] The server analyzes the questions using natural language processing (NLP) technology and generates appropriate health action plans and advice, such as suggestions for increasing exercise and guidance on nutritional balance.

[1768] The server transmits the generated advice to the user terminal as text data.

[1769] The terminal presents the advice generated through the avatar to the user visually and audibly.

[1770] emotion recognition

[1771] The device analyzes the user's facial expressions, voice, and input patterns using an emotion engine (e.g., Microsoft Azure Emotion API, Google Cloud Vision API).

[1772] The device transmits the recognized emotion data to a server using an internet connection and a RESTful API.

[1773] The server adjusts health action plans and advice based on emotion data. For example, if the user is feeling stressed, it generates advice on how to reduce stress.

[1774] The server transmits adjustment advice based on the emotion data to the user terminal.

[1775] Health action plan development and monitoring

[1776] The user creates a health action plan based on advice from the avatar and emotion data. For example, the user might plan to "jog three times a week."

[1777] The user inputs the health action plan that has been created into the terminal.

[1778] The terminal transmits the input action plan data to the server.

[1779] The server stores the health action plan data in a database and begins monitoring the plan.

[1780] Feedback and motivation

[1781] The server periodically analyzes user behavior data and evaluates the progress of the plan, using machine learning models (e.g., Scikit-learn).

[1782] The server generates feedback and motivational messages based on progress, e.g., praise messages based on frequency and duration of jogging.

[1783] The server transmits the generated feedback and motivation messages to the user terminal.

[1784] The device presents feedback and motivational messages to the user through the avatar.

[1785] Specific examples

[1786] Example 1: Understanding your health status

[1787] A user enters information such as height 170cm, weight 70kg, and age 30.

[1788] The terminal transmits the input data to the server.

[1789] The server analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[1790] The device displays an avatar telling the user, "Your BMI is a little higher than normal. You should exercise more."

[1791] Example 2: Creating a Health Action Plan

[1792] The user asks the avatar, "How can I get more exercise?"

[1793] The terminal sends a query to the server.

[1794] Based on the user's activity level, the server generates advice such as, "Try jogging for 30 minutes three times a week."

[1795] On the device, an avatar tells the user to "start jogging for 30 minutes three times a week."

[1796] The user accepts the advice and creates a health action plan.

[1797] Example 3: Feedback using emotion recognition

[1798] A user types into their avatar, "I've been feeling stressed lately."

[1799] The device's emotion engine recognizes stress from the user's facial expressions and voice, and sends that data to a server.

[1800] The server analyzes the emotional data and generates stress reduction advice, e.g., "Try relaxation techniques."

[1801] The device has an avatar telling the user to "try some relaxation techniques."

[1802] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1803] Step 1:

[1804] A user installs the application on a smartphone or tablet and creates an account. The user completes the setup by entering personal information such as name, email address, and password. The input data includes, for example, the name "Taro Tanaka," the email address "tanaka@example.com," and the password. The device sends this input data to the server. As an output, the user information is registered on the server and a user ID is generated.

[1805] Step 2:

[1806] After creating an account, users input their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.). The input is done using a form within the application. The device sends this input data to the server. As an output, the user's health data is stored in the server's database.

[1807] Step 3:

[1808] The server stores the received health data in a relational database (e.g., MySQL). The server inputs the stored health data into a generative AI model (e.g., TensorFlow, PyTorch) to evaluate the user's health status and potential risks. During the evaluation process, for example, BMI calculation is performed, and an evaluation result such as "slightly higher than normal" is obtained. The analysis result is generated as an output.

[1809] Step 4:

[1810] The server generates a virtual health avatar based on the analysis results. This uses an algorithm (e.g., Unity, Unreal Engine) to generate a 3D character model. The generated virtual health avatar is saved as digital data. The output is the virtual health avatar data.

[1811] Step 5:

[1812] The server sends the generated virtual health avatar data to the user's device via an internet connection and a RESTful API. The device analyzes the received avatar data and prepares rendering for visual display. As an output, a 3D model of the avatar is ready to be displayed on the device.

[1813] Step 6:

[1814] The device notifies the user that avatar display has been completed. This notification is sent via a push notification or a pop-up message. By receiving this notification, the user can confirm that the system is operating normally. As an output, a notification of avatar display completion is sent to the user.

[1815] Step 7:

[1816] The user starts a dialogue with the virtual health avatar. For example, the user inputs a question such as, "I've been feeling tired a lot recently. What should I do?" The device sends the user's question to the server as text data. The content of the question is sent to the server as output.

[1817] Step 8:

[1818] The server analyzes the received question using natural language processing (NLP) technology. A pre-trained generative AI model (e.g., GPT-3) is used for the analysis. Based on the analysis results, the server generates an appropriate health action plan and advice through the generative AI model. For example, advice such as "suggestions to increase exercise and guidance on nutritional balance" is generated. The advice is obtained as output.

[1819] Step 9:

[1820] The server sends the generated advice to the user's device via an internet connection and a RESTful API. The device then presents the generated advice to the user visually and audibly through an avatar. For example, the avatar might say, "You should exercise more." The user receives the advice as output.

[1821] Step 10:

[1822] The device analyzes the user's facial expressions, voice, and input patterns using an emotion engine (e.g., Microsoft Azure Emotion API, Google Cloud Vision API). The analysis process uses a camera and microphone. The device sends the recognized emotion data to the server. As an output, the emotion data is sent to the server.

[1823] Step 11:

[1824] The server adjusts the health action plan and advice based on the emotion data. An algorithm based on the emotion data is used for the analysis, and generates, for example, "advice on how to reduce stress when the user is feeling stressed." The server then sends the adjusted advice to the user's device. The adjusted advice is obtained as the output.

[1825] Step 12:

[1826] The device presents the adjusted advice to the user through the avatar, for example, the avatar says in a voice, "Try some relaxation techniques." As an output, the user receives the adjusted advice.

[1827] Step 13:

[1828] The user creates a health action plan based on advice from the avatar and emotion data. For example, the user can create a plan to "jog three times a week." The user inputs the created plan into the terminal. The action plan data is obtained as output.

[1829] Step 14:

[1830] The device sends the input action plan data to the server. The transmission is performed using an internet connection and a RESTful API. The server stores the action plan data in a database. As an output, the action plan data is stored on the server.

[1831] Step 15:

[1832] The server periodically analyzes the user's behavioral data and evaluates the progress of the plan. This is done using a machine learning model (e.g., Scikit-learn). The server generates feedback and motivational messages based on the progress made based on the analysis results. For example, it generates a message such as "You're doing great!" based on the frequency and duration of jogging. The feedback message is obtained as an output.

[1833] Step 16:

[1834] The server sends the generated feedback and motivation messages to the user's device using an internet connection and a RESTful API. The device presents the feedback messages to the user through an avatar. For example, the avatar might say "Great! Keep it up!". As an output, the user receives the feedback.

[1835] (Application example 2)

[1836] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1837] While conventional health management systems allow users to plan health behaviors, they struggle to maintain the motivation to actually follow through with them. Furthermore, they lack the means to monitor users' emotions and stress levels and adjust advice accordingly, resulting in a lack of personalized care.

[1838] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for awarding electronic payment points according to the degree of achievement of the health action plan, a means for monitoring the user's emotions and stress level using an emotion recognition engine, and a means for adjusting the health action plan and advice based on the monitoring results. This makes it easier for the user to maintain motivation to carry out the action plan and allows them to receive personalized feedback.

[1839] "User's physical characteristics" refers to the user's physical attributes such as height, weight, body fat percentage, muscle mass, etc.

[1840] "Genetic information" refers to the results of a user's DNA analysis and information about their genes.

[1841] "Lifestyle habits" refers to the user's daily behavior patterns, dietary habits, exercise habits, sleep patterns, and other habits.

[1842] "Server" refers to a central computer system that analyzes and stores data and provides information to users.

[1843] "Virtual health avatar" refers to a digital character generated to visually represent a user's health status.

[1844] "Electronic payment points" refers to digital rewards awarded according to the degree to which a user achieves their action plan.

[1845] An "emotion recognition engine" refers to software that analyzes a user's facial expressions and voice to determine their emotions and stress level.

[1846] A "health action plan" refers to a plan regarding exercise, diet, and lifestyle habits that is drawn up by a user.

[1847] "Monitoring" refers to the server periodically monitoring and evaluating the user's progress in their action plan and their emotional state.

[1848] "Feedback" refers to information that the server provides to the user regarding analysis results and evaluations.

[1849] This invention is a system that allows users to manage their own health status and maintain motivation. Specifically, the system begins when a user enters their physical characteristics, genetic information, and lifestyle habits through an application and sends the data to a server. This data is analyzed by the server and a virtual healthy avatar is generated.

[1850] Technology and hardware used

[1851] Programming language: Python

[1852] Database: MySQL

[1853] AI model: TensorFlow

[1854] Emotion recognition engine: OpenCV, Dlib

[1855] Frontend: React Native

[1856] Server: AWS EC2

[1857] Electronic payment system: Stripe

[1858] Data collection

[1859] Users download the smartphone app and enter data such as physical characteristics, genetic information, and lifestyle habits. The data is sent to the server in real time.

[1860] Data analysis and avatar generation

[1861] The server analyzes the received health data and inputs it into a model that evaluates the user's health status using TensorFlow. Based on the analysis results, a virtual health avatar is generated and sent to the user's device.

[1862] Interacting with avatars

[1863] Users can interact with the virtual health avatar and ask questions or seek advice about their health. This interaction takes place in real time, and the entered questions are sent to the server, which analyzes the questions and generates appropriate health action plans and advice.

[1864] emotion recognition

[1865] The user's facial expressions and voice are captured using the smartphone's camera and microphone, and analyzed using an emotion recognition engine (OpenCV, Dlib). The analysis results are sent to a server, which monitors the user's emotions and stress level.

[1866] Implementing and monitoring health action plans

[1867] The user follows the instructions of the virtual health avatar to create a specific health action plan. This plan is input into the device and stored on the server. The server periodically monitors the progress of the plan and provides feedback to the user on the evaluation results.

[1868] Electronic payment points awarded

[1869] Each time a user completes a health action plan, points are added to the user's account using an electronic payment system (Stripe). These points can then be used to purchase products, etc.

[1870] Specific examples

[1871] Example prompt sentence:

[1872] "I'm a 30-year-old male, 170cm tall and weigh 70kg. I've been feeling tired easily lately. I'd like some suggestions for an exercise plan and stress reduction."

[1873] Example flow:

[1874] 1. A user creates an account and enters data such as height, weight, and age.

[1875] 2. The server receives the data, analyzes it with an AI model, and generates a virtual health avatar.

[1876] 3. The user interacts with the avatar and receives suggestions for exercise plans and stress reduction.

[1877] 4. An emotion recognition engine analyzes the user's emotional state and adjusts advice as needed.

[1878] 5. The user takes action based on the health action plan they created, and the server monitors their progress.

[1879] 6. Electronic payment points are awarded according to the level of achievement, and users can use these points to obtain incentives.

[1880] Through the above steps, the present invention not only enables the user to manage their health condition and create an effective action plan, but also provides the motivation to continue the plan.

[1881] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1882] Step 1: A user creates an account and enters their physical characteristics, genetic information, and lifestyle habits.

[1883] Input: Information such as the user's height, weight, age, exercise habits, dietary patterns, and DNA analysis results.

[1884] Process: The user enters the required information on the smartphone application screen.

[1885] Output: The input information is sent to the cloud server in JSON format.

[1886] Step 2: The server stores the received data.

[1887] Input: Health data submitted by the user in JSON format.

[1888] Processing: Save the received data in a MySQL database.

[1889] Output: User's health information stored in a database.

[1890] Step 3: The server analyzes the stored health data.

[1891] Input: User's health data stored in a database.

[1892] Processing: Analyze health data using TensorFlow to assess the user's health status.

[1893] Output: Health status assessment results (e.g. BMI, body fat percentage, potential risks).

[1894] Step 4: The server generates a virtual health avatar and sends it to the user terminal.

[1895] Input: Health status assessment results.

[1896] Processing: A virtual health avatar is generated based on the evaluation results, and the data is sent to the user terminal.

[1897] Output: Virtual health avatar data sent to the user device.

[1898] Step 5: The device visually displays the virtual health avatar and notifies the user.

[1899] Input: Virtual health avatar data sent from the server.

[1900] Processing: Graphically display the avatar on the user's device and send notifications to the user.

[1901] Output: Visually displayed virtual health avatar and notification.

[1902] Step 6: The user interacts with the virtual health avatar and inputs a health question.

[1903] Input: User's text question (e.g. "I've been feeling tired a lot lately. What should I do?").

[1904] Process: The user enters a question in the application and sends it to the server.

[1905] Output: The user's question data sent to the server.

[1906] Step 7: The server parses the question and generates a health action plan and advice.

[1907] Input: Question data submitted by the user.

[1908] Processing: The question data is fed into a natural language processing engine to generate appropriate health action plans and advice.

[1909] Output: Generated health action plans and advice.

[1910] Step 8: The server sends the generated advice to the user terminal.

[1911] Input: Generated health action plans and advice.

[1912] Processing: The generated advice is sent to the user's terminal.

[1913] Output: Advice data sent to the user terminal.

[1914] Step 9: The terminal presents the generated advice to the user through the avatar.

[1915] Input: Advice data sent by the server.

[1916] Processing: Advice is presented to the user visually and audibly through an avatar.

[1917] Output: Health action plan and advice presented to the user.

[1918] Step 10: The user communicates their emotions and stress to the avatar.

[1919] Input: Text or voice input about the user's emotions or stress (e.g., "I've been feeling stressed lately").

[1920] Processing: The smartphone's camera and microphone are used to capture the user's facial expressions and voice, which are then analyzed by an emotion recognition engine.

[1921] Output: Parsed emotion data.

[1922] Step 11: The server adjusts the advice based on the emotion data.

[1923] Input: Parsed emotion data.

[1924] Processing: Adjusting health action plans and advice based on emotional data.

[1925] Output: Adjusted advice.

[1926] Step 12: The adjusted advice is sent to the user terminal and presented through the avatar.

[1927] Input: Tailored advice.

[1928] Processing: The server sends the adjusted advice to the device and presents it through the avatar.

[1929] Output: Tuning advice presented to the user.

[1930] Step 13: The user creates a health action plan and inputs it into the terminal.

[1931] Input: A health action plan created by the user (e.g., jogging three times a week).

[1932] Processing: An action plan is entered on the terminal and sent to the server.

[1933] Output: Action plan data sent to the server.

[1934] Step 14: The server stores the action plan data and performs monitoring.

[1935] Input: Submitted action plan data.

[1936] Processing: Store in a database and periodically monitor the progress of the plan.

[1937] Output: Monitoring results and progress reports.

[1938] Step 15: The server awards electronic payment points according to the progress.

[1939] Input: Health action plan progress data.

[1940] Processing: Points are awarded based on progress using an electronic payment system.

[1941] Output: Electronic payment points awarded to the user.

[1942] Step 16: The terminal presents feedback and motivational messages to the user.

[1943] Input: Feedback and motivation messages from the server.

[1944] Processing: The message is presented to the user visually and audibly through an avatar.

[1945] Output: Feedback and motivational messages presented to the user.

[1946] This series of processing flows enables users to efficiently manage their own health condition and maintain continuous motivation by carrying out action plans and obtaining incentives.

[1947] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1948] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1949] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1950] [Fourth embodiment]

[1951] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1952] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1953] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1954] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1955] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1956] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1957] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1958] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1959] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1960] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1961] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1962] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1963] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1964] As an embodiment of the present invention, the processing of the program will be explained below in natural language.

[1965] 1. Data Collection

[1966] Users: Install the application and create an account.

[1967] User: After creating an account, the user enters physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, sleep patterns) into the device.

[1968] Terminal: Sends the entered data to the server.

[1969] 2. Data Analysis

[1970] Server: Stores the received health data in a database.

[1971] Server: Inputs stored health data into the AI ​​model to assess health status and risks.

[1972] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[1973] 3. Avatar generation and display

[1974] Server: Sends the generated virtual health avatar data to the user terminal.

[1975] Terminal: Visually displays the received avatar data.

[1976] Terminal: Notifies the user that the avatar is ready to be displayed.

[1977] 4. Interaction

[1978] User: Initiates a dialogue with the virtual health avatar. For example, the user asks, "I've been feeling tired a lot lately. What should I do?"

[1979] Terminal: Sends the user's question to the server.

[1980] Server: Analyzes the questions and generates appropriate health action plans and advice.

[1981] Server: Sends the generated advice to the user terminal.

[1982] Terminal: Presents advice to the user through an avatar.

[1983] 5. Health action plan development and monitoring

[1984] User: Create a health action plan based on the avatar's advice. For example, create a plan to "jog three times a week."

[1985] User: Enter the health action plan into the terminal.

[1986] Terminal: Sends the input action plan data to the server.

[1987] Server: Saves the action plan data in the database and starts monitoring.

[1988] 6. Feedback and motivation

[1989] Server: Periodically analyzes user behavior data and evaluates the progress of the plan.

[1990] Server: Generates messages that provide feedback and motivation based on progress.

[1991] Server: Sends generated feedback and motivation messages to the devices.

[1992] Terminal: Presents feedback and motivational messages to the user through an avatar.

[1993] Specific examples

[1994] Example 1: Understanding your health status

[1995] User: A 30-year-old man, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[1996] Terminal: Sends input data to the server.

[1997] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[1998] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[1999] Example 2: Creating a Health Action Plan

[2000] User: Asks avatar, "How can I get more exercise?"

[2001] Terminal: Sends the question to the server.

[2002] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[2003] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[2004] User: Accept the advice and develop a health action plan.

[2005] In this way, the present invention provides users with a deeper understanding of their health status and assistance in implementing specific health behaviors.

[2006] The processing flow will be explained below.

[2007] Step 1:

[2008] User: Installs the application and creates an account. Enters personal information and completes account setup.

[2009] Step 2:

[2010] Terminal: Displays an input screen to collect data on physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) based on user input.

[2011] Step 3:

[2012] User: Follow the collection screen and enter the necessary health data, such as height 170cm, weight 70kg, meal frequency, exercise habits, etc.

[2013] Step 4:

[2014] Terminal: Formats the input data and sends it to the server.

[2015] Step 5:

[2016] Server: Stores the received health data in a database.

[2017] Step 6:

[2018] Server: Inputs stored health data into the AI ​​model to assess the user's health status and potential risks.

[2019] Step 7:

[2020] Server: Based on the analysis results, a virtual health avatar specialized for each user is generated.

[2021] Step 8:

[2022] Server: Sends the generated virtual health avatar data to the user terminal.

[2023] Step 9:

[2024] Terminal: Prepare to visually display the received avatar data.

[2025] Step 10:

[2026] Terminal: Sends a notification to the user that the avatar display is complete.

[2027] Step 11:

[2028] User: Starts a conversation with the virtual health avatar displayed on the device. Enters a question or concern into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[2029] Step 12:

[2030] Terminal: Sends the user's question to the server as text data.

[2031] Step 13:

[2032] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[2033] Step 14:

[2034] Server: Sends the generated advice to the user terminal as text data.

[2035] Step 15:

[2036] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[2037] Step 16:

[2038] User: Create a health action plan based on the avatar's advice. For example, enter a plan such as "jog for 30 minutes three times a week."

[2039] Step 17:

[2040] Terminal: Sends the created health action plan data to the server.

[2041] Step 18:

[2042] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[2043] Step 19:

[2044] User: Follows the plan and regularly records their actions (for example, jogging progress) in the app.

[2045] Step 20:

[2046] Terminal: Sends recorded behavioral data to the server.

[2047] Step 21:

[2048] Server: Analyzes the received behavioral data and evaluates the progress of the health behavior plan.

[2049] Step 22:

[2050] Server: Generates feedback and motivational messages based on progress.

[2051] Step 23:

[2052] Server: Sends the generated feedback and motivation messages to the user terminal.

[2053] Step 24:

[2054] Terminal: Presents feedback and motivational messages to the user through an avatar.

[2055] By repeating the above process, users can gain a deeper understanding of their own health status and continuously practice specific health behaviors.

[2056] Example 1

[2057] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2058] In modern society, it is difficult for users to accurately understand their own health status and develop appropriate health action plans. In particular, health management that takes into account individual physical characteristics, genetic information, and lifestyle habits requires specialized knowledge, making it difficult for many users to effectively maintain their health. In addition, existing systems do not adequately provide continuous monitoring, feedback, or motivation, which means that users' health improvements are not sustainable.

[2059] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2060] In this invention, the server includes: a means for inputting a user's physical characteristics, genetic information, and lifestyle habits; a means for transmitting the input data to the server; a means for analyzing the health data and generating a virtual health avatar; a means for transmitting the generated virtual health avatar to a user terminal and visually displaying it; a means for the user to interact with the virtual health avatar and send questions to the server; a means for the server to analyze the questions and generate an appropriate health action plan and advice; a means for transmitting the generated advice to the user terminal and presenting it to the user via the avatar; a means for the user to create a health action plan and input it into the terminal; a means for storing the input action plan data on the server and monitoring it; a means for periodically analyzing the action data and evaluating progress; and a means for transmitting the generated feedback and motivational messages to the user terminal and presenting them to the user via the avatar. This allows the user to accurately understand their own health status and create and implement an effective health action plan based on their individual characteristics. Furthermore, providing continuous feedback and motivation can be expected to have a lasting effect on the user's health improvement.

[2061] "User" refers to a person who uses the system to manage and improve their health.

[2062] "Physical characteristics" refers to data about the user's body, such as height, weight, and age.

[2063] "Genetic information" refers to data related to genetics, such as the results of a user's DNA analysis.

[2064] "Lifestyle habits" refers to data such as diet, exercise, and sleep patterns in a user's daily life.

[2065] "Terminal" refers to an electronic device used by a user, such as a computer, smartphone, or tablet.

[2066] "Server" refers to a computer system that receives, stores, and analyzes data entered by a user and transmits the generated information to the user terminal.

[2067] "Database" refers to an information management system for storing user health data and action plan data.

[2068] "AI model" refers to the artificial intelligence algorithm used by the server to analyze health status.

[2069] "Virtual health avatar" refers to a digital character that visually represents a user's health status.

[2070] A "question" refers to a health-related inquiry that a user makes to the server through a virtual health avatar.

[2071] A "health action plan" refers to a specific action plan that a user sets out to improve their own health.

[2072] "Monitoring" refers to the process by which the server continuously monitors user behavior data and evaluates progress.

[2073] "Feedback" refers to the evaluation and advice provided by the server regarding the user's behavior and health status.

[2074] "Motivational Message" refers to a message of encouragement or encouragement provided by the server to promote improvement in the user's health.

[2075] This invention is a system that helps users accurately understand their own health status and assists them in formulating and implementing effective health action plans. This system consists of a user, a terminal, and a server.

[2076] Data collection

[2077] First, a user installs the application and creates an account. After creating the account, the user enters their physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, and sleep patterns) into the device. The device then sends the entered data to the server. This transmission is performed using an HTTP POST request.

[2078] Data analysis

[2079] The server stores the received health data in a database. The stored data is then fed into an AI model (e.g., TensorFlow or PyTorch) to assess health status and risks. The analysis results are then used to generate a personalized virtual health avatar. This avatar is a digital character that visually represents the user's health status.

[2080] Avatar generation and display

[2081] The generated virtual health avatar is sent from the server to the user's device. The device receives this data and visually displays it. Software such as Unity or Unreal Engine is used for display. The device uses push notifications or alert dialogs to notify the user that the avatar is ready to be displayed.

[2082] Interaction

[2083] The user begins a dialogue with the virtual health avatar. For example, if the user asks, "I've been feeling tired lately. What should I do?", this question is sent from the device to the server. The server analyzes the question using a generative AI model (e.g., GPT-3) and generates an appropriate health action plan and advice. The generated advice is sent from the server to the user's device, which then presents it to the user through the avatar.

[2084] Health action plan development and monitoring

[2085] The user creates a health action plan based on the avatar's advice and enters it into the device. For example, the user may plan to "jog three times a week." The entered action plan data is sent from the device to the server and stored in a database. The server continues to monitor this.

[2086] Feedback and motivation

[2087] The server periodically analyzes the user's behavioral data and evaluates the progress of the plan. It generates feedback and motivational messages based on the progress and sends them to the user's device. The device then presents these messages to the user via an avatar.

[2088] Specific examples

[2089] Understanding your health

[2090] User: A 30-year-old male, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[2091] Terminal: Sends the entered data to the server.

[2092] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[2093] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[2094] Health action plan development

[2095] User: "How can I get more exercise?" asks the avatar.

[2096] Terminal: Sends the question to the server.

[2097] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[2098] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[2099] User: Accept the advice and develop a health action plan.

[2100] Prompt Sentence Examples

[2101] "Calculate BMI based on this user's age, height, and weight and provide appropriate advice."

[2102] In this way, the present invention provides users with a deeper understanding of their health status and assistance in implementing specific health behaviors.

[2103] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2104] Step 1:

[2105] Users: Install the application and create an account.

[2106] Specific actions: Enter your username, email address, password, etc. on the account creation page and click the Register button.

[2107] Input: Username, email address, password, etc.

[2108] Output: Notification that user account creation is complete.

[2109] Step 2:

[2110] User: After creating an account, enter physical characteristics, genetic information, and lifestyle habits into the device.

[2111] Specific actions: Enter the required data into the dedicated input form and click the submit button.

[2112] Input: height, weight, age, DNA results, diet, exercise, sleep patterns, etc.

[2113] Output: Save input data on the device.

[2114] Step 3:

[2115] Terminal: Sends the entered data to the server.

[2116] What happens: The entered data is formatted and then sent to the server using an HTTP POST request.

[2117] Input: height, weight, age, DNA results, diet, exercise, sleep patterns, etc.

[2118] Output: The data sent to the server.

[2119] Step 4:

[2120] Server: Stores the received health data in a database.

[2121] Specific operation: Store the received data in a database such as "MySQL" or "PostgreSQL".

[2122] Input: Health data sent from the device.

[2123] Output: Health data stored in a database.

[2124] Step 5:

[2125] Server: Inputs stored data into an AI model to assess health status and risk.

[2126] Specific operation: Data is retrieved from a database and input into an AI model using a Python script. Possible AI models used include "TensorFlow" and "PyTorch."

[2127] Input: Health data stored in a database.

[2128] Output: Health status and risk assessment results.

[2129] Step 6:

[2130] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[2131] Specific operation: The output from the AI ​​model is processed and passed to an avatar generation algorithm to generate avatar data.

[2132] Input: Health status and risk assessment results.

[2133] Output: Virtual health avatar data.

[2134] Step 7:

[2135] Server: Sends the generated virtual health avatar data to the user terminal.

[2136] Specific operation: The generated avatar data is converted into JSON format and sent to the device via an HTTP POST request.

[2137] Input: Virtual health avatar data.

[2138] Output: Avatar data sent to the device.

[2139] Step 8:

[2140] Terminal: Visually displays the received avatar data.

[2141] Specific operation: Parses JSON data and displays the avatar on the screen using a graphics engine (e.g., "Unity" or "Unreal Engine").

[2142] Input: Received avatar data.

[2143] Output: A visually displayed virtual health avatar.

[2144] Step 9:

[2145] Terminal: Notifies the user that the avatar is ready to be displayed.

[2146] Specific behavior: Notify the user via push notification or alert dialog.

[2147] Input: Avatar display ready status.

[2148] Output: Notification to the user.

[2149] Step 10:

[2150] User: Initiates a dialogue with the virtual health avatar. For example, the user asks, "I've been feeling tired a lot lately. What should I do?"

[2151] Specific actions: Click the text box on the avatar display screen and enter a question.

[2152] Input: Health question text.

[2153] Output: Save the question content on the device.

[2154] Step 11:

[2155] Terminal: Sends the user's question to the server.

[2156] Specific operation: The question text is converted to JSON format and sent to the server via an HTTP POST request.

[2157] Input: Health question text.

[2158] Output: The query data sent to the server.

[2159] Step 12:

[2160] Server: Analyzes questions and generates health action plans and advice. The generative AI model used may be GPT-3.

[2161] Specific operation: The received question text is input into the AI ​​model to generate an answer.

[2162] Input: Question data from the user.

[2163] Output: Generated health action plans and advice.

[2164] Step 13:

[2165] Server: Sends the generated advice to the user terminal.

[2166] Specific operation: The generated advice is converted into JSON format and sent to the terminal via an HTTP POST request.

[2167] Input: Generated advice data.

[2168] Output: Advice data sent to the terminal.

[2169] Step 14:

[2170] Terminal: Presents advice to the user through an avatar.

[2171] Specific operation: The received advice data is displayed, and the avatar provides advice via voice or text.

[2172] Input: Received advice data.

[2173] Output: Advice provided to the user.

[2174] Step 15:

[2175] User: Creates a health action plan based on the avatar's advice and enters it into the device.

[2176] Specific actions: Enter your health action plan using the dedicated form on your device.

[2177] Input: Data on the health action plan you have created.

[2178] Output: Action plan data is saved on the device.

[2179] Step 16:

[2180] Terminal: Sends the input action plan data to the server.

[2181] Specific operation: Convert the action plan data into JSON format and send it to the server via an HTTP POST request.

[2182] Input: Planned action plan data.

[2183] Output: Action plan data sent to the server.

[2184] Step 17:

[2185] Server: Saves the action plan data in the database and starts monitoring.

[2186] Specific behavior: Save planning data to a database and periodically run monitoring scripts.

[2187] Input: Planned action plan data.

[2188] Output: Action plan data stored in a database.

[2189] Step 18:

[2190] Server: Periodically analyzes user behavior data and evaluates progress.

[2191] What it does: It periodically collects data and runs algorithms to evaluate progress.

[2192] Input: Stored action plan data, collected action data.

[2193] Output: Progress assessment results.

[2194] Step 19:

[2195] Server: Generates feedback and motivational messages based on progress and sends them to the user's device.

[2196] Specific operation: A message is generated using the feedback generation algorithm, the generated message is converted to JSON format, and sent to the device via an HTTP POST request.

[2197] Input: Progress assessment results.

[2198] Output: Generated feedback and motivational messages.

[2199] Step 20:

[2200] Terminal: Presents feedback and motivational messages to the user through an avatar.

[2201] Specific operation: A message is displayed on the display screen and provided by an avatar via voice or text.

[2202] Input: Received feedback and motivational messages.

[2203] Output: Feedback and motivational messages to the user.

[2204] (Application example 1)

[2205] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2206] Conventional health management systems are primarily limited to understanding the individual user's health status and formulating action plans, and the scope of these systems is limited to the user. However, managing the operational and maintenance status of robots operating in factories is directly linked to the efficiency and safety of factory operations, and applications in this field are in demand. However, current systems lack the functionality to comprehensively monitor the robot's health status and formulate appropriate maintenance plans. For this reason, there is a strong demand for the development of a system that can reduce robot operational risks and improve production efficiency.

[2207] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2208] In this invention, the server includes a means for inputting a user's physical characteristics, genetic information, and lifestyle habits, a means for transmitting the input data to the server, a means for analyzing the health data and generating a virtual health avatar, a means for visually displaying the generated virtual health avatar and the robot's operating status and component deterioration status, a means for analyzing the robot's operating data and generating a maintenance avatar, and a means for transmitting the generated avatar to a user terminal and a management terminal for interaction. This makes it possible to comprehensively manage the health status of not only users but also robots in the factory and to develop appropriate maintenance plans.

[2209] "User's physical characteristics" refers to the user's physical attributes such as height, weight, age, and gender.

[2210] "Genetic information" refers to DNA analysis results and genetic data.

[2211] "Lifestyle habits" refers to a user's daily life behaviors such as diet, exercise, and sleep patterns.

[2212] "Input Data" refers to information provided by the user relating to physical characteristics, genetic information, and lifestyle habits.

[2213] "Server" refers to a computer system for receiving, storing, and analyzing data.

[2214] "Health Data" refers to data about a user's health status based on their physical characteristics, genetic information, and lifestyle habits.

[2215] A "virtual health avatar" is a digital character that visually represents the user's health status and provides health guidance and advice through interaction.

[2216] "Means for visual display" refers to the function of displaying the generated avatar or data on the screen of a user terminal or an administrative terminal.

[2217] "Robot operation status" refers to data on how much the robot is operating, its operating time, and its condition.

[2218] "Parts deterioration status" refers to data that indicates the degree of deterioration of robot parts.

[2219] A "maintenance avatar" is a digital character that visually represents a robot's health status and maintenance needs, and presents a maintenance plan through interaction.

[2220] "Management terminal" refers to a computer device used by factory staff to manage the operating and maintenance status of robots.

[2221] "Maintenance plan" refers to a schedule of maintenance actions required to reduce robot operation risks and increase production efficiency.

[2222] This invention is a system that inputs a user's physical characteristics, genetic information, and lifestyle habits and uses them to manage their health and the operating status of a robot. Specifically, it is implemented through the following process.

[2223] First, the user installs a dedicated application and inputs their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.). This data is then sent to a server via the device. The server stores the received data in a database and analyzes the health data. Generative AI models such as TensorFlow and PyTorch are used for the analysis.

[2224] Based on the analysis results, the server generates a virtual health avatar and sends the data to the user's device. The generated virtual health avatar is visually displayed on the device, allowing the user to begin a dialogue. For example, if the user asks, "I've been feeling tired a lot lately. What should I do?", the question is sent to the server. The server analyzes the question, generates an appropriate health action plan and advice, and sends it to the user's device. The generated advice is then presented to the user through the virtual health avatar on the device.

[2225] Next, the system collects data on the robots in the factory, including their operating status and the deterioration of their parts, and sends it to a server. This data is also stored in a database and analyzed using a generative AI model. The server generates a maintenance avatar based on the analysis results and sends the data to the robot's management terminal. On the management terminal, the generated maintenance avatar is visually displayed, allowing the manager to initiate a dialogue. For example, if a manager asks, "When should the next maintenance be performed?", the question is sent to the server. The server analyzes the question, generates appropriate maintenance plans and actions, and sends them to the management terminal. On the management terminal, the generated plan is presented to the manager through the maintenance avatar.

[2226] The hardware used to implement these processes includes IoT devices and sensors, and the software includes TensorFlow and PyTorch for generating the health avatars, and a REST API for data transmission.

[2227] Examples:

[2228] 1. Healthcare example:

[2229] Let's say User A is a 30-year-old man, 170 cm tall and weighing 70 kg. He uses a health management app to input his physical characteristics and lifestyle habits. The app sends this data to a server, which analyzes the data and generates advice such as, "Your BMI is a little higher than normal. You should exercise more." A virtual health avatar conveys this advice to User A.

[2230] 2. Robot maintenance example:

[2231] Factory staff member B manages the operating status of a robot. The robot sends data that says, "Operating time: 1500 hours, sensor is deteriorating." The server analyzes the data and generates advice that says, "Perform the next maintenance on 2023-10-15 and replace the sensor." On the management terminal, a maintenance avatar notifies staff member B of this advice.

[2232] Example prompt sentence:

[2233] When should the next maintenance be performed?

[2234] "My robot has reached 1500 hours of operation, what maintenance action should I take next?"

[2235] "If a user's BMI is higher than normal, what kind of exercise should they increase?"

[2236] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2237] Step 1:

[2238] Users install a dedicated application and input their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.). The input data is sent to a server via the user's device. The input data includes physical characteristics such as height, weight, age, genetic information, and lifestyle habits. This allows basic information about the user's own health to be collected.

[2239] Step 2:

[2240] The server stores the received user data in a database. This storage process ensures that each user's health data is securely recorded. The stored data is then input into an AI analysis module to evaluate health status and risks. The AI ​​model used is a generative model based on TensorFlow and PyTorch. The analysis results provide indicators of the user's current health status and potential risks.

[2241] Step 3:

[2242] The server generates a virtual health avatar based on the analysis results. This avatar visually represents the user's health condition. Data on the generated virtual health avatar is sent to the user's device and displayed visually on the device, allowing the user to understand their health condition at a glance.

[2243] Step 4:

[2244] The user starts a dialogue with the virtual health avatar. For example, the user asks the avatar, "I've been feeling tired a lot lately. What should I do?" This question is sent to the server via the user's device. The input is the user's question, and the output is the avatar's answer.

[2245] Step 5:

[2246] The server analyzes the received questions using a natural language processing engine and generates appropriate health action plans and advice. A generative AI model is used for this analysis. The generated advice is then sent back from the server to the user's device and presented to the user via an avatar. For example, specific advice such as "Try jogging for 30 minutes three times a week" is provided.

[2247] Step 6:

[2248] The user creates a health action plan based on the advice provided and enters it into the device through the application. The entered action plan data is then sent back to the server and stored in a database. This records the user's health action plan and allows for future monitoring.

[2249] Step 7:

[2250] The server periodically analyzes the user's behavioral data based on the health action plan and evaluates their progress. This is again done using a generative AI model. Based on the evaluation results, the server generates feedback and motivational messages and sends them to the user's device. For example, a message such as "You're almost there! Keep going!" may be sent.

[2251] Step 8:

[2252] In the factory, the robot's operating status and the deterioration status of its parts are collected and sent to a server. The input data includes operating hours, part status, etc. This allows the robot's health status to be understood.

[2253] Step 9:

[2254] The server stores the received robot data in a database and analyzes it using a generative AI model. Based on the analysis results, a maintenance avatar is generated and sent to a management terminal. This visually displays which robots require maintenance and to what extent.

[2255] Step 10:

[2256] At the management terminal, staff interact with the maintenance avatar and ask questions such as, "When should the next maintenance be performed?" This question is sent to the server and analyzed.

[2257] Step 11:

[2258] The server receives the query, generates an appropriate maintenance plan and actions, and sends it to the management terminal. The plan is then presented to the administrator via an avatar. For example, specific instructions are provided, such as "Perform the next maintenance on 2023-10-15 and replace the sensor."

[2259] Step 12:

[2260] The server monitors the implementation of the plan and provides feedback as needed, ensuring that the plan is carried out reliably.

[2261] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[2262] As an embodiment of the present invention, the processing of the program will be explained below in natural language.

[2263] 1. Data Collection

[2264] User: Installs the application and creates an account. Enters personal information and completes account setup.

[2265] User: After creating an account, the user enters physical characteristics (e.g., height, weight, age), genetic information (e.g., DNA analysis results), and lifestyle habits (e.g., diet, exercise, sleep patterns) into the device.

[2266] Terminal: Sends the entered data to the server.

[2267] 2. Data Analysis

[2268] Server: Stores the received health data in a database.

[2269] Server: Inputs stored health data into an AI model to assess health status and potential risks.

[2270] Server: Generates a virtual health avatar specific to the user based on the analysis results.

[2271] 3. Avatar generation and display

[2272] Server: Sends the generated virtual health avatar data to the user terminal.

[2273] Terminal: Prepare to visually display the received avatar data.

[2274] Terminal: Sends a notification to the user that the avatar display is complete.

[2275] 4. Interaction

[2276] User: Starts a conversation with the virtual health avatar. Enters a question or concern into the avatar. For example, "I've been feeling tired lately. What should I do?"

[2277] Terminal: Sends the user's question to the server as text data.

[2278] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[2279] Server: Sends the generated advice to the user terminal as text data.

[2280] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[2281] 5. Emotion recognition

[2282] Terminal: The emotion engine analyzes the user's facial expressions, voice, and input patterns.

[2283] Terminal: Sends the recognized emotion data to the server.

[2284] Server: Adjusts health action plans and advice based on emotion data. For example, if a user is feeling stressed, it generates advice on how to reduce stress.

[2285] Server: Sends adjustment advice based on emotion data to the user's device.

[2286] 6. Health action plan development and monitoring

[2287] User: Create a health action plan based on advice from the avatar and emotion engine. For example, create a plan to jog three times a week.

[2288] User: Enter the health action plan into the terminal.

[2289] Terminal: Sends the input action plan data to the server.

[2290] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[2291] 7. Feedback and motivation

[2292] Server: Periodically analyzes user behavior data and evaluates the progress of the plan.

[2293] Server: Generates messages that provide feedback and motivation based on progress. For example, if you are jogging as planned, send a message praising you.

[2294] Server: Sends the generated feedback and motivation messages to the user terminal.

[2295] Terminal: Presents feedback and motivational messages to the user through an avatar.

[2296] Specific examples

[2297] Example 1: Understanding your health status

[2298] User: A 30-year-old man, 170cm tall and weighing 70kg, creates an account and enters his physical characteristics and lifestyle habits.

[2299] Terminal: Sends input data to the server.

[2300] Server: Analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[2301] Device: The avatar tells the user, "Your BMI is a little higher than normal. You should exercise more."

[2302] Example 2: Creating a Health Action Plan

[2303] User: Asks avatar, "How can I get more exercise?"

[2304] Terminal: Sends the question to the server.

[2305] Server: Based on the user's activity level, generate advice such as "Try jogging for 30 minutes three times a week."

[2306] Device: The avatar tells the user, "Try jogging for 30 minutes three times a week."

[2307] User: Accept the advice and develop a health action plan.

[2308] Example 3: Feedback using emotion recognition

[2309] User: Type into your avatar "I've been feeling stressed lately."

[2310] Terminal: The emotion engine recognizes stress from the user's facial expressions and voice, and sends that data to the server.

[2311] Server: Analyzes emotional data and generates stress reduction advice, such as "Try some relaxation techniques."

[2312] Device: The avatar tells the user to "Try some relaxation techniques."

[2313] This system allows users to gain a deeper understanding of their own health and emotional state, enabling them to effectively continue specific health behaviors.

[2314] The processing flow will be explained below.

[2315] Step 1:

[2316] User: Installs the application and creates an account. Enters personal information and completes account setup.

[2317] Step 2:

[2318] Terminal: Displays an input screen to collect data on physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) based on user input.

[2319] Step 3:

[2320] User: Follow the collection screen and enter the necessary health data, such as height 170cm, weight 70kg, meal frequency, exercise habits, etc.

[2321] Step 4:

[2322] Terminal: Formats the input data and sends it to the server.

[2323] Step 5:

[2324] Server: Stores the received health data in a database.

[2325] Step 6:

[2326] Server: Inputs stored health data into the AI ​​model to assess the user's health status and potential risks.

[2327] Step 7:

[2328] Server: Based on the analysis results, a virtual health avatar specialized for each user is generated.

[2329] Step 8:

[2330] Server: Sends the generated virtual health avatar data to the user terminal.

[2331] Step 9:

[2332] Terminal: Prepare to visually display the received avatar data.

[2333] Step 10:

[2334] Terminal: Sends a notification to the user that the avatar display is complete.

[2335] Step 11:

[2336] User: Starts a conversation with the virtual health avatar displayed on the device. Enters a question or concern into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[2337] Step 12:

[2338] Terminal: Sends the user's question to the server as text data.

[2339] Step 13:

[2340] Server: Analyzes the questions and generates appropriate health action plans and advice, such as suggestions for increasing exercise and providing guidance on nutritional balance.

[2341] Step 14:

[2342] Server: Sends the generated advice to the user terminal as text data.

[2343] Step 15:

[2344] Terminal: The advice generated through the avatar is presented to the user visually and audibly.

[2345] Step 16:

[2346] Terminal: The emotion engine analyzes the user's facial expressions, voice, and input patterns.

[2347] Step 17:

[2348] Terminal: Sends the recognized emotion data to the server.

[2349] Step 18:

[2350] Server: Adjusts health action plans and advice based on emotion data. For example, if a user is feeling stressed, it generates advice on how to reduce stress.

[2351] Step 19:

[2352] Server: Sends adjustment advice based on emotion data to the user's device.

[2353] Step 20:

[2354] Terminal: Presents visual and audio advice tailored to the user through an avatar.

[2355] Step 21:

[2356] User: Create a health action plan based on advice from the avatar and emotion engine. For example, enter a plan such as "jog three times a week."

[2357] Step 22:

[2358] Terminal: Sends the created health action plan data to the server.

[2359] Step 23:

[2360] Server: Stores the health action plan data in a database and initiates monitoring of the plan.

[2361] Step 24:

[2362] User: Follows the plan and regularly records their actions (for example, jogging progress) in the app.

[2363] Step 25:

[2364] Terminal: Sends recorded behavioral data to the server.

[2365] Step 26:

[2366] Server: Analyzes the received behavioral data and evaluates the progress of the health behavior plan.

[2367] Step 27:

[2368] Server: Generates feedback and motivational messages based on progress. For example, if you are jogging according to plan, send a message praising you.

[2369] Step 28:

[2370] Server: Sends the generated feedback and motivation messages to the user terminal.

[2371] Step 29:

[2372] Terminal: Presents feedback and motivational messages to the user through an avatar.

[2373] By repeating the above process, the user can gain a deeper understanding of their own health and emotional state and effectively continue to take specific health actions.

[2374] Example 2

[2375] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2376] In modern society, many people are interested in managing their health and improving their lifestyles, but the difficulty of self-management and lack of individualized support are issues. In particular, there is a demand for comprehensive support that includes health status monitoring and emotional recognition, and a system that can provide this effectively is necessary.

[2377] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2378] In this invention, the server includes means for inputting a user's physical characteristics, genetic information, and lifestyle habits, means for transmitting the input data to the server, means for the server to analyze the health data and generate a virtual health avatar, means for transmitting the generated virtual health avatar to a user terminal and visually displaying it, means for the user to interact with the virtual health avatar and send questions to the server, means for the server to analyze the questions and generate an appropriate health action plan and advice, means for transmitting the generated advice to the user terminal and presenting it to the user via the avatar, means for the user to formulate a health action plan and input it to the terminal, means for storing the input action plan data on the server and monitoring it, means for the terminal to analyze the user's facial expressions, voice, and input patterns and transmit emotional data to the server, and means for the server to adjust advice based on the emotional data and transmit it to the user terminal, thereby enabling the user to receive support for comprehensive health management and emotional management.

[2379] "User" refers to any individual or entity that uses the System.

[2380] "Physical characteristics" refers to physical data such as a user's height, weight, age, and gender.

[2381] "Genetic information" refers to data relating to a user's DNA analysis results and genetic characteristics.

[2382] "Lifestyle habits" refers to data related to the user's daily life, such as diet, exercise, and sleep patterns.

[2383] "Terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[2384] "Server" refers to a central processing unit for analyzing data received from a user and providing the analysis results to the user.

[2385] "Health data" collectively refers to data such as a user's physical characteristics, genetic information, and lifestyle habits.

[2386] "Virtual health avatar" refers to a digital character generated to visually represent a user's health status.

[2387] "Dialogue" refers to text and / or voice communication between the user and the virtual health avatar.

[2388] A "health action plan" refers to a specific plan that a user makes to maintain or improve their health.

[2389] "Monitoring" refers to the process of tracking the progress of a user's health action plan and recording and evaluating the data.

[2390] "Emotion data" refers to data related to emotions analyzed from the user's facial expressions, voice, input patterns, etc.

[2391] "Advice" refers to specific instructions or suggestions for maintaining or improving health provided to the user by the server.

[2392] As an embodiment of the present invention, the processing of the program will be specifically described below, clearly indicating what hardware and software are used and what data processing and calculations are performed.

[2393] Explanation of program processing

[2394] Data collection

[2395] Users first install the application on their smartphone or tablet, create an account, and then enter personal information (such as name, email address, and password) to complete the setup.

[2396] After creating an account, users enter their physical characteristics (height, weight, age, etc.), genetic information (DNA analysis results, etc.), and lifestyle habits (diet, exercise, sleep patterns, etc.) via their device.

[2397] The device sends these input data to the server using an internet connection and a RESTful API.

[2398] Data analysis

[2399] The server stores the received health data in a relational database (e.g., MySQL).

[2400] The server uses the stored health data to input into a generative AI model, which then assesses the user's health status and potential risks using the generative AI model (e.g., TensorFlow, PyTorch).

[2401] The server generates a virtual health avatar based on the analysis results.

[2402] Avatar generation and display

[2403] The server sends the generated virtual health avatar data (e.g., 3D model data) to the user's device via an internet connection and a RESTful API.

[2404] The device analyzes the received avatar data and prepares it for rendering for visual display using a 3D rendering library (e.g., Unity, Unreal Engine).

[2405] The device notifies the user that the avatar display has been completed by using a push notification or a pop-up message.

[2406] Interaction

[2407] The user begins a conversation with the virtual health avatar. They enter their questions or concerns in text format into the avatar. For example, "I've been feeling tired a lot lately. What should I do?"

[2408] The device sends the user's questions to the server using an internet connection and a RESTful API.

[2409] The server analyzes the questions using natural language processing (NLP) technology and generates appropriate health action plans and advice, such as suggestions for increasing exercise and guidance on nutritional balance.

[2410] The server transmits the generated advice to the user terminal as text data.

[2411] The terminal presents the advice generated through the avatar to the user visually and audibly.

[2412] emotion recognition

[2413] The device analyzes the user's facial expressions, voice, and input patterns using an emotion engine (e.g., Microsoft Azure Emotion API, Google Cloud Vision API).

[2414] The device transmits the recognized emotion data to a server using an internet connection and a RESTful API.

[2415] The server adjusts health action plans and advice based on emotion data. For example, if the user is feeling stressed, it generates advice on how to reduce stress.

[2416] The server transmits adjustment advice based on the emotion data to the user terminal.

[2417] Health action plan development and monitoring

[2418] The user creates a health action plan based on advice from the avatar and emotion data. For example, the user might plan to "jog three times a week."

[2419] The user inputs the health action plan that has been created into the terminal.

[2420] The terminal transmits the input action plan data to the server.

[2421] The server stores the health action plan data in a database and begins monitoring the plan.

[2422] Feedback and motivation

[2423] The server periodically analyzes user behavior data and evaluates the progress of the plan, using machine learning models (e.g., Scikit-learn).

[2424] The server generates feedback and motivational messages based on progress, e.g., praise messages based on frequency and duration of jogging.

[2425] The server transmits the generated feedback and motivation messages to the user terminal.

[2426] The device presents feedback and motivational messages to the user through the avatar.

[2427] Specific examples

[2428] Example 1: Understanding your health status

[2429] A user enters information such as height 170cm, weight 70kg, and age 30.

[2430] The terminal transmits the input data to the server.

[2431] The server analyzes the data and generates an assessment such as, "Your BMI is a little higher than normal. You should exercise more."

[2432] The device displays an avatar telling the user, "Your BMI is a little higher than normal. You should exercise more."

[2433] Example 2: Creating a Health Action Plan

[2434] The user asks the avatar, "How can I get more exercise?"

[2435] The terminal sends a query to the server.

[2436] Based on the user's activity level, the server generates advice such as, "Try jogging for 30 minutes three times a week."

[2437] On the device, an avatar tells the user to "start jogging for 30 minutes three times a week."

[2438] The user accepts the advice and creates a health action plan.

[2439] Example 3: Feedback using emotion recognition

[2440] A user types into their avatar, "I've been feeling stressed lately."

[2441] The device's emotion engine recognizes stress from the user's facial expressions and voice, and sends that data to a server.

[2442] The server analyzes the emotional data and generates stress reduction advice, e.g., "Try relaxation techniques."

[2443] The device has an avatar telling the user to "try some relaxation techniques."

[2444] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2445] Step 1:

[2446] A user installs the application on a smartphone or tablet and creates an account. The user completes the setup by entering personal information such as name, email address, and p...

Claims

1. a means for inputting the user's physical characteristics, genetic information, and lifestyle habits; means for transmitting the input data to a server; A means for the server to analyze the health data and generate a virtual health avatar; a means for transmitting the generated virtual health avatar to a user terminal and visually displaying the same; a means for a user to interact with the virtual health avatar and send questions to the server; means for the server to analyze the question and generate an appropriate health action plan and advice; means for transmitting the generated advice to a user terminal and presenting the advice to the user through an avatar; A means for a user to create a health action plan and input it into a terminal; A means for storing the input action plan data on a server and for monitoring the same; A system including:

2. The system of claim 1 further comprising means for providing feedback and motivation to the user through the virtual health avatar.

3. The system of claim 1 , further comprising means for the server to periodically analyze the user's behavioral data and evaluate progress of the health action plan.

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