system

Abstract

We provide the system. [Solution] A means for inputting and transmitting the user's health information, A server means for storing the transmitted health information, A means of analyzing the user's mental state in response to user input, A means for generating stress management methods and lifestyle suggestions based on analysis results, A terminal means for displaying the generated proposal, A means of collecting and storing user feedback, Means for generating and providing information on basic knowledge and support methods related to diabetes. A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Diabetic patients often feel mental stress due to blood glucose management and restrictions in daily life. Furthermore, since this stress also becomes a factor in worsening the medical condition, effective stress management is required. However, in the current medical system, mental care is not sufficiently thorough, and there is also a lack of specific information provided to family members and friends to deepen their understanding of diabetes and support the patients. Against this background, there is a need to develop a system that provides specific methods for diabetic patients and their family members and friends to reduce stress and lead a healthy life.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides the following means: means for inputting and transmitting the user's health information; server means for storing the transmitted health information; means for analyzing the user's mental state in response to the user's input; means for generating stress management methods and lifestyle suggestions based on the analysis results; terminal means for displaying the generated suggestions; means for collecting and storing user feedback; means for generating and providing information on basic knowledge and support methods related to diabetes; and further, means for using an artificial intelligence engine to evaluate the user's mental state; and means for enabling the sharing of support information with the user and their family and friends. The aim is to improve the mental and physical health of diabetic patients by enabling users to receive stress management methods and healthy lifestyle suggestions tailored to their individual needs, and by making it easier to effectively share information and receive support from family and friends.

[0006] "Users" refers to diabetic patients who use the system, as well as their families and friends.

[0007] "Health information" refers to data provided by users, such as blood glucose levels, weight, height, medical history, and lifestyle habits.

[0008] "Sending" refers to the action of the terminal sending data entered by the user to the server.

[0009] A "server" refers to a central system that stores transmitted data and performs processing such as analysis.

[0010] "Mental state" refers to psychological indicators that represent the user's stress level and emotional state.

[0011] "Analysis" refers to data processing used to evaluate a person's mental state based on the transmitted data.

[0012] "Stress management methods" refer to specific actions and medical advice aimed at reducing mental stress.

[0013] "Lifestyle suggestions" refer to advice on diet, exercise, sleep, and other aspects of living a healthy life.

[0014] A "terminal" refers to a device used by users to input data and receive results and advice.

[0015] "Feedback" refers to a record of the responses and actions taken by users in response to suggestions they receive.

[0016] An "artificial intelligence engine" refers to AI technology used for natural language processing and data analysis.

[0017] "Basic knowledge about diabetes" refers to information about the causes, symptoms, treatments, and prevention methods of diabetes.

[0018] "Support information" refers to specific advice and information that users' families and friends can use to support patients.

[0019] "Sharing" refers to the exchange and distribution of generated information with other people. [Brief explanation of the drawing]

[0020] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0021] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0022] First, the language used in the following description will be explained.

[0023] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0024] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0025] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0026] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0028] [First Embodiment]

[0029] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0030] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0031] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0033] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0034] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0036] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0038] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0040] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0041] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends.

[0042] System Configuration

[0043] The main components are as follows:

[0044] 1. User's device

[0045] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[0046] 2. Server

[0047] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[0048] 3. Artificial Intelligence Engine

[0049] A module that uses AI technologies for natural language processing and data analysis.

[0050] Operation details

[0051] Data collection and initial setup

[0052] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[0053] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[0054] 2. Terminal: Sends the provided information to the server.

[0055] Specific example: When the user confirms their input, the device sends the data to the server.

[0056] 3. Server: Saves the received data as the initial settings.

[0057] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[0058] User interaction

[0059] 1. User: Use the in-app chat function to enter questions or your current mental state.

[0060] Example: Enter "I've been feeling stressed lately and it's bothering me."

[0061] 2. Terminal: Sends user responses to the server in real time.

[0062] Specific example: Immediately relaying user messages to the server.

[0063] 3. Server: Analyzes the received data and assesses the user's stress level and current health status.

[0064] Specific example: The server uses a natural language processing engine to analyze user messages for signs of stress.

[0065] Stress management and lifestyle suggestions

[0066] 1. Server: Based on the evaluation results, it generates customized stress management methods and lifestyle suggestions (e.g., relaxation exercises, dietary advice).

[0067] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[0068] 2. Terminal: Displays suggestions received from the server to the user.

[0069] Specific example: Present the proposal content as a chat screen or notification.

[0070] 3. User: Either implement the suggested method or ask further questions.

[0071] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[0072] Support provision and education

[0073] 1. Server: Provides information to deepen basic knowledge and understanding of diabetes, and also offers specific advice on how family and friends can support people with diabetes.

[0074] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[0075] 2. Device: Displays the provided information to the user, their family, and friends.

[0076] Specific example: Display educational content in text, video, or infographic format.

[0077] 3. User: Share the suggested ideas and receive support from family and friends.

[0078] Specific example: Use the share button within the app to share the provided information with family.

[0079] Example of implementation

[0080] 1. User: Enters "I am 170cm tall, weigh 70kg, and eat three meals a day."

[0081] 2. Terminal: Sends the entered information to the server.

[0082] 3. Server: Stores user information.

[0083] 4. User: Type "I've been feeling stressed lately and it's bothering me."

[0084] 5. Terminal: Sends a message to the server.

[0085] 6. Server: Analyze stress levels.

[0086] 7. Server: Generates a suggestion that says, "We recommend doing deep breathing exercises for 10 minutes every day."

[0087] 8. Terminal: Display the suggested content.

[0088] 9. User: "I will try the deep breathing exercises," provides feedback.

[0089] 10. Server: Save feedback.

[0090] 11. Server: Generates information that reads, "Basic knowledge about diabetes: Blood sugar management is important. Share this with your family and friends."

[0091] 12. Device: Displays educational information.

[0092] 13. User: Share information with family.

[0093] In this way, the present invention can provide diabetic patients and their families with effective stress management and healthy lifestyle suggestions, thereby improving the mental and physical health of patients.

[0094] The following describes the processing flow.

[0095] Step 1:

[0096] The user launches the application and enters basic information such as name, email address, password, height, weight, and blood sugar level on the new registration screen.

[0097] Step 2:

[0098] The terminal sends the entered information to the server.

[0099] Step 3:

[0100] The server saves the received information to the database.

[0101] Step 4:

[0102] The user accesses the in-app chat function and enters a message such as, "I've been under a lot of stress lately."

[0103] Step 5:

[0104] The device sends the user's message to the server.

[0105] Step 6:

[0106] The server analyzes the messages it receives and uses an artificial intelligence engine to evaluate the user's mental state.

[0107] Step 7:

[0108] Based on the evaluation results, the server generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle suggestions (e.g., dietary improvements, exercise recommendations).

[0109] Step 8:

[0110] The terminal displays the suggestions received from the server to the user.

[0111] Step 9:

[0112] The user reviews the proposal, decides whether to implement it, and if they decide to implement it, provides feedback such as "I'll give it a try."

[0113] Step 10:

[0114] The device sends user feedback to the server.

[0115] Step 11:

[0116] The server saves user feedback and uses it to improve future suggestions.

[0117] Step 12:

[0118] The server generates information on basic knowledge and support methods related to diabetes, and creates content for sharing with family and friends.

[0119] Step 13:

[0120] The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[0121] Step 14:

[0122] Users click the share button to share information with family and friends.

[0123] Step 15:

[0124] The device notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[0125] In this way, the overall processing flow of the system operates in concrete terms.

[0126] (Example 1)

[0127] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0128] There is a need for a system that improves the mental and physical health of diabetic patients and their families and friends by providing effective stress management and lifestyle suggestions. Furthermore, a system is needed to generate personalized suggestions for each patient and to continuously evaluate and improve their effectiveness.

[0129] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0130] In this invention, the server includes means for inputting and transmitting user health information; server means for storing transmitted health information; means for analyzing the user's mental state in response to user input; means for generating stress management methods and lifestyle suggestions based on the analysis results; terminal means for displaying the generated suggestions; means for collecting and storing user feedback; means for generating and providing information on basic knowledge and support methods regarding diabetes; means for creating an account and storing personal information; means for analyzing messages using a natural language processing engine; means for presenting customized suggestions and storing feedback for use in generating suggestions in the future; and means for generating educational information and providing it in text, video, and infographic formats. This enables the provision of individually customized suggestions and continuous support to diabetic patients and their families, thereby improving their mental and physical health.

[0131] "Means for inputting and transmitting user health information" refers to devices or applications that allow diabetic patients and their families to input information about their health status (e.g., blood glucose levels, weight, exercise habits) into a system and transmit it to a server.

[0132] "A server system for storing transmitted health information" refers to a central system for securely and efficiently storing health information transmitted by users.

[0133] "Means for analyzing a user's mental state in response to their input" refers to artificial intelligence engines and natural language processing technologies that analyze messages entered by users and evaluate their stress levels and mental state.

[0134] "Means for generating stress management methods and lifestyle suggestions based on analysis results" refers to a system component that automatically generates individually customized stress management methods and lifestyle improvement suggestions based on the results of an analysis of a person's mental state.

[0135] "Terminal means for displaying generated proposals" refers to a device (e.g., smartphone, tablet, PC) that displays the proposal content sent from the server to the user.

[0136] "Means for collecting and saving user feedback" refers to a system that collects feedback provided by users and saves that feedback for generating future suggestions.

[0137] "Means for generating and providing information on basic knowledge and support methods related to diabetes" refers to a system component that generates and provides users with educational knowledge and support methods related to diabetes.

[0138] "A means of creating an account and storing personal information" refers to a system that allows users to create an account and securely store their personal information.

[0139] "Means of analyzing messages using a natural language processing engine" refers to a system that utilizes natural language processing technology to analyze messages entered by users and understand their content.

[0140] "A means of presenting customized suggestions and saving feedback for use in generating future suggestions" refers to a system that presents individually customized suggestions to users and saves user feedback for use in generating future suggestions.

[0141] "Means for generating and providing educational information in text, video, and infographic formats" refers to a system that generates educational information about diabetes and provides it to users in text, video, and infographic formats.

[0142] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends.

[0143] System Configuration

[0144] The main components are as follows:

[0145] 1. User's device

[0146] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[0147] 2. Server

[0148] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[0149] 3. Artificial Intelligence Engine

[0150] A module that uses AI technologies for natural language processing and data analysis.

[0151] Operation details

[0152] Data collection and initial setup

[0153] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[0154] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[0155] 2. Terminal: Sends the provided information to the server.

[0156] Specific example: When the user confirms their input, the device sends the data to the server.

[0157] 3. Server: Saves the received data as the initial settings.

[0158] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[0159] User interaction

[0160] 1. User: Use the in-app chat function to enter questions or your current mental state.

[0161] Example: Enter "I've been feeling stressed lately and it's bothering me."

[0162] 2. Terminal: Sends user responses to the server in real time.

[0163] Specific example: Immediately relaying user messages to the server.

[0164] 3. Server: Analyzes the received data and assesses the user's stress level and current health status.

[0165] Specific example: The server uses a natural language processing engine to analyze user messages for signs of stress.

[0166] Example of technology used: Text analysis is performed using Python NLP libraries (e.g., SpaCy, NLTK).

[0167] Stress management and lifestyle suggestions

[0168] 1. Server: Based on the evaluation results, it generates customized stress management methods and lifestyle suggestions.

[0169] Example of a generative AI model: The GPT-3® model from OpenAI® is used to generate the proposal text.

[0170] Prompt example: "The user has reported feeling stressed recently. Please provide advice on deep breathing exercises and dietary improvements."

[0171] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[0172] 2. Terminal: Displays suggestions received from the server to the user.

[0173] Specific example: Present the proposal content as a chat screen or notification.

[0174] Feedback and support

[0175] 1. User: Either implement the suggested method or ask further questions.

[0176] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[0177] 2. Terminal: Sends user feedback to the server.

[0178] Specific example: Send the feedback content to the server immediately.

[0179] 3. Server: The server saves the feedback to a database and uses it to generate suggestions for the next time.

[0180] Specific example: Record user feedback to incorporate it into future analyses and suggestions.

[0181] Provision of educational information

[0182] 1. Server: Generates and provides users with basic knowledge and support methods regarding diabetes.

[0183] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[0184] 2. Terminal: Displays the provided information to the user.

[0185] Display format examples: Display educational content as text, video, and infographics.

[0186] 3. User: Share the suggested ideas and receive support from family and friends.

[0187] Specific example: Use the in-app share button to share the provided information with family.

[0188] This invention provides a system that allows users to evaluate their physical and mental state in real time and receive appropriate suggestions and support. By using this system, users can maintain healthier lifestyles and improve their diabetes management.

[0189] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0190] Step 1:

[0191] User: Install and launch the application. The user enters the required personal information (e.g., name, age, gender) on the account creation screen and creates an account.

[0192] Enter the following information: "Name: Taro Yamada", "Age: 45", "Gender: Male".

[0193] Output: Request to create an account and save personal information.

[0194] Step 2:

[0195] Terminal: Sends the entered personal information to the server.

[0196] Input: Personal information entered by the user.

[0197] Output: Data sent to the server.

[0198] Step 3:

[0199] Server: Stores received personal information in the database.

[0200] Input: Personal information sent from the device.

[0201] Output: Personal information stored in the database.

[0202] Step 4:

[0203] User: Enter your health information (e.g., blood sugar level, weight, exercise frequency) on the health information input screen.

[0204] Input: Enter "Blood glucose level: 110 mg / dL", "Weight: 70 kg", "Exercise frequency: 3 times a week".

[0205] Output: Health information entry complete.

[0206] Step 5:

[0207] Terminal: Sends health information to the server.

[0208] Input: Health information entered by the user.

[0209] Output: Data sent to the server.

[0210] Step 6:

[0211] Server: Receives health information and stores it in the database.

[0212] Input: Health information sent from the device.

[0213] Output: Health information stored in the database.

[0214] Step 7:

[0215] User: Use the chat function to enter your current mental state or questions.

[0216] Input: Type "I've been under a lot of stress lately and it's bothering me."

[0217] Output: Mental state input complete.

[0218] Step 8:

[0219] Terminal: Sends entered messages to the server in real time.

[0220] Input: Message from the user.

[0221] Output: Data sent to the server.

[0222] Step 9:

[0223] Server: Uses a natural language processing engine to analyze user input messages and assess stress levels.

[0224] Input: Message received from the user.

[0225] Data processing: Text analysis is performed using Python NLP libraries (e.g., SpaCy, NLTK).

[0226] Output: Evaluation results regarding stress levels.

[0227] Step 10:

[0228] Server: Generates customized stress management methods and lifestyle suggestions based on stress level assessments.

[0229] Input: Stress level assessment results.

[0230] Data processing: Generate proposal text using a generative AI model (e.g., OpenAI's GPT-3).

[0231] Prompt example: "The user has reported feeling stressed recently. Please provide advice on deep breathing exercises and dietary improvements."

[0232] Output: Customized proposal text.

[0233] Step 11:

[0234] Terminal: Displays the suggested text received from the server to the user.

[0235] Input: Proposal text sent from the server.

[0236] Output: The suggested text displayed to the user.

[0237] Specific example of action: The chat screen displays the message, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing your intake of whole grains in your diet."

[0238] Step 12:

[0239] User: Either implement the suggested method or enter further questions.

[0240] Input: Type "I will try the deep breathing exercise" and send feedback.

[0241] Output: Successfully submitted practice report and new questions.

[0242] Step 13:

[0243] Terminal: Sends user feedback to the server.

[0244] Input: User feedback.

[0245] Output: Data sent to the server.

[0246] Step 14:

[0247] Server: The feedback is saved to a database and used to generate suggestions for the next time.

[0248] Input: Feedback sent from the device.

[0249] Output: Feedback stored in the database.

[0250] Step 15:

[0251] Server: Generates and provides users with basic knowledge and support methods regarding diabetes.

[0252] Input: User's current health information and feedback.

[0253] Data processing: Generate educational content using natural language generation technology.

[0254] Output: Educational text about diabetes.

[0255] Step 16:

[0256] Terminal: Displays the provided information to the user.

[0257] Input: Educational message sent from the server.

[0258] Output: Displaying information on the screen.

[0259] Specific example of actions: Present educational content as text, video, and infographics.

[0260] Step 17:

[0261] User: Share the suggested information and receive support from family and friends.

[0262] Input: Share the provided information via the app's share button.

[0263] Output: Information sharing complete.

[0264] (Application Example 1)

[0265] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0266] Diabetic patients often face not only physical health management challenges but also mental stress management and financial burdens. However, there is no system in place to comprehensively manage these aspects and provide appropriate lifestyle and financial suggestions. Therefore, there is a need for systems and methods to alleviate the mental and financial stress of diabetic patients and promote healthy living.

[0267] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0268] In this invention, the server includes: means for inputting and transmitting the user's health and economic information; server means for storing and analyzing the transmitted information; means for analyzing the user's mental and economic state in response to user input; means for generating stress management methods, lifestyle habits, and economic suggestions based on the analysis results; terminal means for displaying the generated suggestions; means for collecting and storing user feedback; and means for generating and providing information on basic knowledge and support methods related to diabetes. This makes it possible for diabetic patients and their related parties to comprehensively manage their health, mental state, and economic state and receive appropriate suggestions.

[0269] "User health information" refers to physiological data such as height, weight, blood glucose levels, and meal frequency that diabetic patients record on a daily basis.

[0270] "Economic information" refers to economic data such as users' spending, budgets, and monthly expenses.

[0271] A "server" refers to a central control unit that stores transmitted data, performs analysis, and provides the results to users.

[0272] "Mental state" refers to information that represents the user's stress level and emotional health.

[0273] "Economic status" refers to information that represents the user's financial health and spending habits.

[0274] "Stress management methods" refer to methods and techniques for reducing the mental stress of users (e.g., deep breathing exercises and relaxation techniques).

[0275] "Lifestyle suggestions" refer to specific suggestions for improving the user's daily life (e.g., dietary advice or recommendations for exercise).

[0276] "Economic proposal" refers to specific advice for improving the user's economic situation (e.g., selection of foods with good cost performance or recommendation of exercise plans).

[0277] "Terminal" refers to a device (e.g., smartphone or tablet) that displays proposals and information to the user and performs data input and transmission.

[0278] "Feedback" refers to the evaluation and comments made by the user to the system.

[0279] "Basic knowledge about diabetes" refers to methods for managing blood sugar levels and basic information about diet and exercise.

[0280] The system of the present invention is for providing integrated health management, mental stress management, and economic proposals to diabetic patients and their related persons. As an embodiment for implementing the present invention, the specific system configuration and its operation will be described below.

[0281] System Configuration

[0282] The main components of this system are as follows.

[0283] 1. User's terminal: A device (smartphone, tablet) for the user to input health information and economic information and receive proposals.

[0284] 2. Server: A central system that stores, analyzes, and generates proposals for the data transmitted from the user.

[0285] 3. Artificial intelligence engine: A module that uses AI technology for natural language processing and data analysis (e.g., TENSORFLOW (registered trademark)).

[0286] Details of Operation

[0287] Data Collection and Initial Setting

[0288] 1. User: Launch the application and enter the necessary personal information, health information, and financial information (e.g., blood sugar levels, weight, exercise habits, monthly expenses).

[0289] 2. Terminal: Sends the provided information to the server.

[0290] 3. Server: Saves the received data as the initial settings.

[0291] User interaction

[0292] 1. User: Use the in-app chat function to enter questions, current mental state, and financial status.

[0293] 2. Terminal: Sends user responses to the server in real time.

[0294] 3. Server: Analyzes received data to assess the user's stress level, current health status, and financial status.

[0295] Stress management, lifestyle, and economic suggestions

[0296] 1. Server: Based on the evaluation results, it generates customized stress management methods, lifestyle habits, and economic suggestions (e.g., relaxation exercises, dietary advice, recommendations for cost-effective health foods).

[0297] 2. Terminal: Displays suggestions received from the server to the user.

[0298] Support provision and education

[0299] 1. Server: Provides information to deepen basic knowledge and understanding of diabetes, and also offers specific advice on how family and friends can support people with diabetes.

[0300] 2. Terminal: Displays the provided information to the user and their family and friends.

[0301] Hardware and software to be used

[0302] Front-end: Built using React Native. Provides a UI for collecting information entered by the user and sending it to the server.

[0303] Back-end: Built using Node.js and Express. Saves and analyzes the received data and generates proposals.

[0304] Database: Uses MongoDB to store the user's health information, economic information, feedback, etc.

[0305] AI Engine: Uses TensorFlow to perform natural language processing and data analysis.

[0306] Specific examples

[0307] Suppose the user enters the following information.

[0308] Height: 170 cm

[0309] Weight: 70 kg

[0310] Blood sugar level: 140 mg / dL

[0311] Number of meals per day: 3 times

[0312] Monthly expenses: 60,000 yen

[0313] <00009​​​​​

[0315] Question: The user has entered the following information. Please provide appropriate health and financial suggestions.

[0316] Height: 170cm

[0317] Weight: 70kg

[0318] Blood glucose level: 140 mg / dL

[0319] Number of meals per day: 3

[0320] Monthly expenses: 60,000 yen

[0321] Answer: Your stress levels are high. Focus on daily deep breathing exercises and a healthy diet. Your financial situation is also high, so review your balanced diet and exercise plan.

[0322] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0323] Step 1:

[0324] Data entry (health information and economic information)

[0325] The user launches the application and enters information such as height, weight, blood sugar level, number of meals per day, and monthly expenses.

[0326] Input: Height, weight, blood sugar level, number of meals, expenses

[0327] Output: Data in JSON format (Example: { "height": 170, "weight": 70, "glucose": 140, "mealsPerDay": 3, "expenses": 60000})

[0328] Step 2:

[0329] Data transmission

[0330] The terminal sends the data entered by the user to the server.

[0331] Input: User data in JSON format

[0332] Output: Data sent to the server

[0333] Step 3:

[0334] Data storage

[0335] The server saves the received data to a database (MongoDB).

[0336] Input: Received data (JSON format)

[0337] Output: Records stored in the database

[0338] Step 4:

[0339] Data Analysis

[0340] The server uses a natural language processing engine (TensorFlow) to analyze the user's mental and economic state.

[0341] Input: User information retrieved from the database

[0342] Data processing: Stress levels are calculated based on blood glucose levels, meal frequency, etc., and economic status is evaluated based on monthly expenses.

[0343] Output: Assessment of stress level and economic status (e.g., { "stressLevel": "High", "economicStatus": "High"})

[0344] Step 5:

[0345] Proposal generation

[0346] Based on the analysis results, the server generates stress management methods, lifestyle suggestions, and economic advice.

[0347] Input: Stress level, assessment of economic status

[0348] Data processing: The program generates exercise and dietary advice for stress reduction, as well as specific suggestions for improving financial conditions.

[0349] Output: Suggestions (e.g., deep breathing exercises, healthy eating, recommendations for cost-effective foods)

[0350] Step 6:

[0351] Suggestion display

[0352] The terminal displays suggestions received from the server to the user.

[0353] Input: Proposal (string in JSON format)

[0354] Output: Suggestions displayed on the device's UI

[0355] Step 7:

[0356] Feedback Collection

[0357] Users provide feedback on suggestions within the application.

[0358] Input: Feedback (e.g., "I tried the deep breathing exercises")

[0359] Output: Feedback data in JSON format

[0360] Step 8:

[0361] Send and save feedback

[0362] The device sends the collected feedback to the server, which then stores it in a database.

[0363] Input: User feedback data

[0364] Output: Feedback stored in the database

[0365] Step 9:

[0366] Support information provided

[0367] The server generates information on basic knowledge and support methods related to diabetes and provides it to users and their related parties.

[0368] Input: None (Information generated periodically)

[0369] Output: Educational content (e.g., text, video, infographics)

[0370] Step 10:

[0371] Support information display

[0372] The device displays educational content received from the server to the user.

[0373] Input: Data from educational content

[0374] Output: Educational content displayed on the device's UI

[0375] Through these steps, this system enables diabetic patients and their families to comprehensively manage their health, mental state, and financial situation, and to receive appropriate suggestions.

[0376] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0377] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends, and further incorporates an emotion engine to recognize the user's emotions and reflect them in the analysis results.

[0378] System Configuration

[0379] The main components are as follows:

[0380] 1. User's device

[0381] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[0382] 2. Server

[0383] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[0384] 3. Artificial Intelligence Engine

[0385] A module that uses AI technologies for natural language processing and data analysis. It integrates an emotion engine and has the ability to analyze the user's emotions from input data.

[0386] 4. Emotional Engine

[0387] A module that recognizes emotions based on user input and incorporates them into the assessment of mental state.

[0388] Operation details

[0389] Data collection and initial setup

[0390] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[0391] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[0392] 2. Terminal: Sends the provided information to the server.

[0393] Specific example: When the user confirms their input, the device sends the data to the server.

[0394] 3. Server: Saves the received data as the initial settings.

[0395] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[0396] User interaction

[0397] 1. User: Use the in-app chat function to enter questions or your current mental state.

[0398] Example: Enter "I've been feeling stressed lately and it's bothering me."

[0399] 2. Terminal: Sends user responses to the server in real time.

[0400] Specific example: Immediately relaying user messages to the server.

[0401] 3. Server: Analyzes the received data, uses the emotion engine to recognize the user's emotions, and evaluates their overall mental state.

[0402] Specific example: The server uses an emotion engine to analyze the user's message and recognize emotions such as "lonely."

[0403] Stress management and lifestyle suggestions

[0404] 1. Server: Based on the emotion analysis results, it generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle suggestions (e.g., dietary improvements, exercise recommendations).

[0405] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[0406] 2. Terminal: Displays the suggestions received from the server to the user.

[0407] Specific example: Present the proposal content as a chat screen or notification.

[0408] 3. User: Decide whether or not to implement the suggested method, and if so, provide feedback such as "I will try it."

[0409] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[0410] 4. Terminal: Sends user feedback to the server.

[0411] Specific example: Send the feedback content to the server.

[0412] 5. Server: Save user feedback and use it to improve future suggestions.

[0413] Specific example: Store feedback in a database and use it for individual suggestions.

[0414] Support provision and education

[0415] 1. Server: Generates information on basic knowledge and support methods regarding diabetes, and creates content for sharing with family and friends.

[0416] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[0417] 2. Device: Display educational information to the user and provide options (e.g., a share button) for sharing with family and friends.

[0418] Specific example: Display educational content in text, video, or infographic format.

[0419] 3. User: Click the share button to share the provided information with family and friends.

[0420] Specific example: Click the share button to send the provided information to family members via email.

[0421] 4. Terminal: Notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[0422] Specific example: An email sent to a family member contains educational information.

[0423] In this way, by combining the emotional engine, the present invention can provide diabetic patients and their families with more detailed and personalized stress management and healthy lifestyle suggestions, thereby improving the mental and physical health of users.

[0424] The following describes the processing flow.

[0425] Step 1:

[0426] The user launches the application and enters basic information such as name, email address, password, height, weight, and blood sugar level on the new registration screen.

[0427] Step 2:

[0428] The terminal sends the entered information to the server.

[0429] Step 3:

[0430] The server saves the received information to the database.

[0431] Step 4:

[0432] The user accesses the in-app chat function and enters their feelings or mental state, such as "I've been feeling stressed lately."

[0433] Step 5:

[0434] The device sends the user's message to the server.

[0435] Step 6:

[0436] The server uses an emotion engine to analyze the user's message to determine their emotions. For example, it might extract emotions like "stress" and "worry" from the user's input, "I've been feeling stressed lately and it's really bothering me."

[0437] Step 7:

[0438] The server evaluates the mental state based on the results of the emotion analysis and determines the stress level.

[0439] Step 8:

[0440] Based on the emotion analysis results, the server generates personalized stress management methods (e.g., deep breathing exercises, meditation) and lifestyle suggestions (e.g., balanced diet, regular exercise).

[0441] Step 9:

[0442] The terminal displays suggestions received from the server to the user. For example, "We recommend doing deep breathing exercises for 10 minutes every day."

[0443] Step 10:

[0444] The user reviews the proposal and decides whether to implement it. If they decide to implement it, they provide feedback such as "I'll give it a try."

[0445] Step 11:

[0446] The device sends user feedback to the server.

[0447] Step 12:

[0448] The server saves user feedback and uses it to improve future suggestions. It also evaluates the effectiveness of suggestions based on the feedback.

[0449] Step 13:

[0450] The server generates information on basic knowledge and support methods related to diabetes, and creates content for sharing with family and friends.

[0451] Step 14:

[0452] The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[0453] Step 15:

[0454] Users click the share button to share information with family and friends.

[0455] Step 16:

[0456] The device notifies the server of the sharing action.

[0457] Step 17:

[0458] The server sends information using the selected sharing method (e.g., email, social media). For example, it might send an email containing educational information to a family member.

[0459] In this way, the overall processing flow of the system operates in concrete terms.

[0460] (Example 2)

[0461] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0462] To provide effective mental stress management and lifestyle improvement suggestions to diabetic patients and their families and friends, it is necessary to accurately analyze the health and mental state of each individual user and generate customized suggestions. However, conventional systems have faced challenges in providing individually tailored suggestions due to insufficient emotional analysis and detailed feedback collection.

[0463] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0464] In this invention, the server includes means for users to input and transmit personal information and health-related information; means for storing the transmitted information and recording it in a database; means for using an artificial intelligence module to analyze the user's input data; means for customizing and generating stress management methods and lifestyle suggestions based on the input data and analysis results; terminal device means for presenting the generated suggestions to the user; means for collecting, analyzing, and storing user feedback; and means for generating and providing health-related educational and support information. This makes it possible to provide customized suggestions in real time based on each user's individual health and mental state.

[0465] "User" refers to an individual who uses the system to manage and receive suggestions regarding their health information and mental state.

[0466] "Personal information" refers to basic data used to identify a user, such as name, age, and gender.

[0467] "Health-related information" refers to data that indicates the user's health status, such as blood glucose levels, weight, and exercise habits.

[0468] A "server" refers to a central computing system that stores data, performs analysis, and generates proposals.

[0469] A "sentiment analysis engine" refers to a technology module that recognizes and analyzes a user's emotions from input text and data.

[0470] An "artificial intelligence module" refers to a program that uses AI technology to perform data analysis and proposal generation.

[0471] "Stress management" refers to methods and techniques for improving mental health.

[0472] "Lifestyle suggestions" refer to suggestions that indicate recommended actions and habits for maintaining or improving health.

[0473] "Feedback" refers to suggestions, reactions, and opinions on services collected from users.

[0474] "Educational information" refers to data that provides users, their families, and friends with knowledge and support methods regarding diabetes.

[0475] "Shareable" refers to a feature that allows users to share information with other people.

[0476] This invention is a system that uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends. This system incorporates an emotion engine to recognize the user's emotions and reflect them in the analysis results.

[0477] System Configuration

[0478] The main components are as follows:

[0479] 1. User's device

[0480] These are devices that allow users to input health information and receive suggestions. Examples include smartphones, tablets, and PCs.

[0481] 2. Server

[0482] This is a central system that stores, analyzes, and generates suggestions based on data submitted by users.

[0483] 3. Artificial Intelligence Module

[0484] This program uses AI technologies for natural language processing and data analysis. It integrates an emotion analysis engine to analyze the user's emotions from the input data.

[0485] 4. Emotion Analysis Engine

[0486] This is a technology module for recognizing emotions based on user input and incorporating them into the assessment of mental state.

[0487] Operation details

[0488] The system works as follows:

[0489] Data collection and initial setup

[0490] 1. The user launches the application and enters necessary personal and health information (e.g., blood sugar level, weight, exercise habits). For example, they might enter, "Height 170cm, weight 70kg, blood sugar level 110mg / dL, I eat 3 meals a day."

[0491] 2. The terminal sends the provided information to the server. Once the user confirms the input, the terminal sends the data to the server.

[0492] 3. The server saves the received data as initial settings. Specifically, the server records the user's basic health information in a database and uses it as initial settings.

[0493] User interaction

[0494] 1. Users use the chat function to enter questions or their current mental state. For example, they might type, "I've been feeling stressed lately and it's bothering me."

[0495] 2. The terminal sends user responses to the server in real time.

[0496] 3. The server analyzes the received data, uses an emotion analysis engine to recognize the user's emotions, and evaluates their overall mental state. For example, the server uses the emotion analysis engine to analyze "stress" from the user's message.

[0497] Stress management and lifestyle suggestions

[0498] 1. Based on the emotion analysis results, the server generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle recommendations. For example, it might generate, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing your intake of whole grains in your diet."

[0499] 2. The terminal displays the suggestions received from the server to the user.

[0500] 3. The user decides whether or not to implement the suggested method, and if so, provides feedback such as "I'll try it."

[0501] 4. The device sends user feedback to the server.

[0502] 5. The server saves user feedback and uses it to improve future suggestions.

[0503] Support provision and education

[0504] 1. The server generates information on basic knowledge and support methods regarding diabetes, and creates content for sharing with family and friends. For example, it might generate information such as, "Managing blood sugar levels is important for diabetes. By helping family and friends understand this, you can get support with diet management and exercise."

[0505] 2. The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[0506] 3. The user clicks the share button to share the provided information with family and friends.

[0507] 4. The device notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[0508] This allows the system, which combines an emotion analysis engine and an artificial intelligence module, to provide personalized stress management and healthy lifestyle suggestions to diabetic patients and their families, thereby improving the users' mental and physical health.

[0509] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0510] Step 1:

[0511] User: Launches the application and enters personal and health-related information (e.g., height, weight, blood sugar level, exercise habits). The entered information (input data) is sent to the terminal.

[0512] Input: Personal information, health-related information

[0513] Output: Input data sent to the terminal

[0514] Specific actions: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, I eat 3 meals a day" into the app's form and press the confirm button.

[0515] Step 2:

[0516] Terminal: Sends user-entered data to the server.

[0517] Input: Data entered by the user

[0518] Output: Data to send to the server

[0519] Specific action: When the confirmation button is pressed, the device sends the data to the server via the internet.

[0520] Step 3:

[0521] Server: Saves the transmitted data to the database and records it as initial settings.

[0522] Input: Data sent from the device

[0523] Output: User data stored in the database

[0524] Specific operation: The server receives data, records it in the database, and creates a profile for each user.

[0525] Step 4:

[0526] User: Use the chat function to enter your current mental state or questions.

[0527] Input: Text of mental state or question

[0528] Output: Input data sent to the terminal

[0529] Specific action: Type "I've been feeling stressed lately" into the chat window and press the send button.

[0530] Step 5:

[0531] Terminal: Sends user messages to the server in real time.

[0532] Input: User input message

[0533] Output: Message sent to the server

[0534] Specific operation: The message is transferred to the server the moment the send button is pressed.

[0535] Step 6:

[0536] Server: Analyzes received messages using an emotion analysis engine and evaluates the emotional state.

[0537] Input: Message sent by the user

[0538] Data processing: The sentiment analysis engine analyzes the message content.

[0539] Output: Emotional state (e.g., "stress")

[0540] Specific operation: The server uses an emotion analysis engine to analyze "stress" from the input "high stress level" and records it as an emotional state.

[0541] Step 7:

[0542] Server: Based on the emotion analysis results, it generates customized stress management methods and lifestyle suggestions.

[0543] Input: Sentiment analysis results

[0544] Data processing: Generative AI model generates suggestions.

[0545] Output: Proposed content (Example: "Perform deep breathing exercises for 10 minutes every day")

[0546] Specific operation: The server prompts the AI ​​model with "suggestions based on the user's sentiment analysis results" and generates suggestions.

[0547] Step 8:

[0548] Terminal: Displays the suggestions received from the server to the user.

[0549] Input: Suggestions from the server

[0550] Output: Suggestions displayed to the user

[0551] Specific action: Use the application's notification function to display the suggested content as a pop-up on the screen.

[0552] Step 9:

[0553] User: Decide whether to implement the suggestion and provide feedback.

[0554] Input: User feedback

[0555] Output: Feedback sent to the device

[0556] Specific action: Send feedback saying "I'll try the deep breathing exercise" and press the submit button.

[0557] Step 10:

[0558] Terminal: Sends user feedback to the server.

[0559] Input: User feedback

[0560] Output: Feedback sent to the server

[0561] Specific action: The feedback content is sent directly to the server.

[0562] Step 11:

[0563] Server: Saves user feedback to a database and uses it to improve future suggestions.

[0564] Input: User feedback

[0565] Output: Feedback stored in the database

[0566] Specific operation: The feedback is saved to a database and referenced when generating suggestions in the future.

[0567] Step 12:

[0568] Server: Generates basic knowledge and support information about diabetes, and creates content for sharing with family and friends.

[0569] Input: Health-related information stored on the server

[0570] Data processing: Generative AI model generates educational information.

[0571] Output: Health education content (e.g., "Key Points for Diabetes Management")

[0572] Specific operation: The server prompts the AI ​​model to generate "educational information on diabetes management" and generates the content.

[0573] Step 13:

[0574] Terminal: Displays generated educational information to the user and provides the option to share it with family and friends.

[0575] Input: Educational information from the server

[0576] Output: Educational content and sharing options displayed to the user

[0577] Specific actions: Display educational content in text or video format and include a share button.

[0578] Step 14:

[0579] User: Click the share button to share the provided information with family and friends.

[0580] Input: Share Action

[0581] Output: Instructions for sharing information

[0582] Specific actions: Click the share button and select the sharing method (e.g., email, social media).

[0583] Step 15:

[0584] Terminal: Notifies the server of the sharing action, and the server sends the information using the selected sharing method.

[0585] Input: Shared Action Notification

[0586] Output: Information sent to family and friends

[0587] Specific operation: A share action trigger is sent to the server, and the information is shared in the selected manner.

[0588] (Application Example 2)

[0589] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0590] A system is needed to monitor the mental stress and health status of passengers in autonomous vehicles in real time and to provide appropriate stress management and lifestyle suggestions. Conventional systems have been unable to adequately monitor the mental and health status of passengers, which is crucial for maintaining safe driving, and have been unable to take appropriate action.

[0591] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using a biosensor to monitor health status, means for using a camera to analyze emotions, and means for evaluating the passenger's mental state based on data from the camera and biosensor. This makes it possible to monitor the stress level and health status of passengers in an autonomous vehicle in real time and to immediately provide appropriate stress management and lifestyle suggestions.

[0592] "Means for inputting and transmitting health information" refers to a device that allows users to input their own health data (e.g., blood sugar levels, heart rate, weight, etc.) and transmit that information to a server within the system.

[0593] A "server system for storing transmitted health information" refers to a central system for receiving health information transmitted by users and securely storing it in a database.

[0594] "Means for analyzing mental state" refers to devices or software that analyze user input or data from biosensors to evaluate the user's emotions and mental state.

[0595] "Means for generating stress management methods and lifestyle suggestions" refers to a device or software that generates stress management methods and lifestyle improvement suggestions suitable for the user based on analyzed information about the user's mental state.

[0596] "Display device for displaying generated suggestions" refers to a device for visually presenting to the user stress management and lifestyle habit suggestions generated by the system.

[0597] "Means for collecting and storing user feedback" refers to a device or software for collecting feedback on suggestions made by users and storing that information in a database within the system.

[0598] "Methods using biosensors to monitor health status" refer to devices that collect physiological data from users in real time, such as heart rate and skin electrical responses.

[0599] "Methods using cameras to analyze emotions" refer to imaging devices that detect the user's facial expressions and posture and evaluate their emotions based on that information.

[0600] "Means for evaluating passengers' mental state based on data from cameras and biosensors" refers to a device or software that analyzes data collected from cameras and biosensors to comprehensively evaluate the mental state of users.

[0601] "Means of suggesting relaxation music or exercises while driving" refers to a device or software that suggests music or exercise methods with relaxation effects based on the user's mental state.

[0602] "Means for generating and providing information on basic knowledge and support methods regarding diabetes" refers to devices or software that generate and provide information to help users and their families understand and appropriately manage diabetes.

[0603] This invention provides a system that monitors the mental stress and health status of passengers in autonomous vehicles in real time and offers appropriate stress management and lifestyle suggestions. The specific system configuration and its operation are described below.

[0604] System Configuration

[0605] The system consists of the following main components:

[0606] 1. User's equipment

[0607] A device (e.g., smartphone, tablet) for entering health information and receiving suggestions.

[0608] 2. Sensor devices

[0609] A heart rate sensor that measures heart rate (e.g., Polar H9).

[0610] A skin electromechanist (e.g., Empatica E4) that measures the electrical response of the skin.

[0611] 3. Camera device

[0612] A camera used to capture facial expressions and analyze emotions (e.g., a camera built into a vehicle).

[0613] 4. Server

[0614] A central system that stores and analyzes health information and emotional data, and generates recommendations.

[0615] 5. Artificial Intelligence Engine

[0616] A module that uses AI technologies for natural language processing and data analysis. It integrates an emotion engine and has the ability to analyze the user's emotions from input data.

[0617] 6. Display Device

[0618] A device for displaying generated suggestions.

[0619] Operation details

[0620] 1. Data Collection

[0621] The user's device inputs health information (e.g., blood glucose levels, weight, exercise habits) and sends it to the server.

[0622] The system collects heart rate and skin electrical response data in real time from sensor devices and captures passenger facial expression data from camera devices.

[0623] 2. Data Analysis and Evaluation

[0624] The server receives and stores transmitted health information, heart rate data from biosensors, and skin electrical response data.

[0625] The system analyzes facial expression data from camera devices and uses an emotion engine to evaluate the emotional state of passengers.

[0626] 3. Proposal generation

[0627] The server uses an AI engine to generate stress management methods and lifestyle suggestions based on health information, heart rate, skin electrical responses, and emotional data.

[0628] Specific examples include "recommending the playback of relaxation music" and "suggesting deep breathing exercises."

[0629] 4. Proposal display and feedback collection

[0630] The generated suggestions are presented to the user through a display device.

[0631] Users provide feedback on the suggestions and send that feedback information to the server.

[0632] The server receives feedback information and incorporates it into the next proposal generation.

[0633] Specific example

[0634] Example prompt message: When your heart rate is high and emotion analysis identifies you as "anxious".

[0635] Prompt message: Heart rate 95, skin electrical response 0.75, anxiety

[0636] This system will enable real-time monitoring of passengers' stress levels and health status in autonomous vehicles, and will immediately provide appropriate stress management and lifestyle suggestions.

[0637] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0638] Step 1:

[0639] The user inputs health information. Specifically, the user uses an input device such as a smartphone to enter health information such as blood glucose levels, weight, and exercise habits into the application. The entered data is sent to the server by the device. The input consists of numerical data such as blood glucose levels and weight, which is then sent to the server.

[0640] Step 2:

[0641] The server receives the transmitted health information and stores it in the database. The server receives the user's health information and records it in the database. The health information is stored accurately because it will be used for subsequent analysis. At this stage, the input is the health information from the user, and the output is the health information stored in the database.

[0642] Step 3:

[0643] Real-time data collection begins using sensor devices (heart rate sensor and electrodermal meter) and a camera device. The terminal collects heart rate and electrodermal response data from the heart rate sensor and electrodermal meter, and captures the passenger's facial expressions with the camera device. The inputs collected are heart rate, electrodermal response, and facial expression data, which are then sent to the server.

[0644] Step 4:

[0645] The server receives and stores the collected biosensor data and camera device data. The received data is recorded in a database. The input is biometric data from the sensor device and camera device, and the output is the stored biometric data.

[0646] Step 5:

[0647] The server analyzes facial expression data from the camera device and uses an artificial intelligence engine to evaluate emotional states. Specifically, the collected facial expression data is processed as images and input into an emotion recognition model. The AI ​​engine analyzes the emotional state and identifies emotions such as "anxiety" or "loneliness." The input is facial expression data, and the output is the result of the emotion analysis.

[0648] Step 6:

[0649] The server uses a generative AI model to generate stress management methods and lifestyle suggestions based on stored health information, biosensor data, and emotional states. The AI ​​engine comprehensively analyzes multiple data points to generate suggestions tailored to the user. Specific examples include "Play relaxation music" and "Perform deep breathing exercises." Inputs are health information, biosensor data, and emotional analysis results, while output is the suggested content.

[0650] Step 7:

[0651] The server sends the generated suggestions to the terminal. The terminal displays the received suggestions on a display device, visually presenting them to the user. As output, the user can then review the suggestions.

[0652] Step 8:

[0653] The user decides whether to implement the suggested method and enters feedback. If the user implements the suggested method, they enter feedback such as "I tried it" or "It was effective" into the terminal. This input is the feedback content and is sent to the server.

[0654] Step 9:

[0655] The server receives user feedback and stores it in a database. This feedback information is used to generate suggestions for future updates. The input is user feedback, and the output is the stored feedback information.

[0656] This allows the system to monitor the user's health and mental state in real time and provide appropriate stress management and lifestyle suggestions.

[0657] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0658] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0659] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0660] [Second Embodiment]

[0661] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0662] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0663] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0664] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0665] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0666] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0667] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0668] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0669] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0670] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0671] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0672] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0673] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends.

[0674] System Configuration

[0675] The main components are as follows:

[0676] 1. User's device

[0677] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[0678] 2. Server

[0679] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[0680] 3. Artificial Intelligence Engine

[0681] A module that uses AI technologies for natural language processing and data analysis.

[0682] Operation details

[0683] Data collection and initial setup

[0684] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[0685] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[0686] 2. Terminal: Sends the provided information to the server.

[0687] Specific example: When the user confirms their input, the device sends the data to the server.

[0688] 3. Server: Saves the received data as the initial settings.

[0689] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[0690] User interaction

[0691] 1. User: Use the in-app chat function to enter questions or your current mental state.

[0692] Example: Enter "I've been feeling stressed lately and it's bothering me."

[0693] 2. Terminal: Sends user responses to the server in real time.

[0694] Specific example: Immediately relaying user messages to the server.

[0695] 3. Server: Analyzes the received data and assesses the user's stress level and current health status.

[0696] Specific example: The server uses a natural language processing engine to analyze user messages for signs of stress.

[0697] Stress management and lifestyle suggestions

[0698] 1. Server: Based on the evaluation results, it generates customized stress management methods and lifestyle suggestions (e.g., relaxation exercises, dietary advice).

[0699] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[0700] 2. Terminal: Displays suggestions received from the server to the user.

[0701] Specific example: Present the proposal content as a chat screen or notification.

[0702] 3. User: Either implement the suggested method or ask further questions.

[0703] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[0704] Support provision and education

[0705] 1. Server: Provides information to deepen basic knowledge and understanding of diabetes, and also offers specific advice on how family and friends can support people with diabetes.

[0706] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[0707] 2. Device: Displays the provided information to the user, their family, and friends.

[0708] Specific example: Display educational content in text, video, or infographic format.

[0709] 3. User: Share the suggested ideas and receive support from family and friends.

[0710] Specific example: Use the share button within the app to share the provided information with family.

[0711] Example of implementation

[0712] 1. User: Enters "I am 170cm tall, weigh 70kg, and eat three meals a day."

[0713] 2. Terminal: Sends the entered information to the server.

[0714] 3. Server: Stores user information.

[0715] 4. User: Type "I've been feeling stressed lately and it's bothering me."

[0716] 5. Terminal: Sends a message to the server.

[0717] 6. Server: Analyze stress levels.

[0718] 7. Server: Generates a suggestion that says, "We recommend doing deep breathing exercises for 10 minutes every day."

[0719] 8. Terminal: Display the suggested content.

[0720] 9. User: "I will try the deep breathing exercises," provides feedback.

[0721] 10. Server: Save feedback.

[0722] 11. Server: Generates information that reads, "Basic knowledge about diabetes: Blood sugar management is important. Share this with your family and friends."

[0723] 12. Device: Displays educational information.

[0724] 13. User: Share information with family.

[0725] In this way, the present invention can provide diabetic patients and their families with effective stress management and healthy lifestyle suggestions, thereby improving the mental and physical health of patients.

[0726] The following describes the processing flow.

[0727] Step 1:

[0728] The user launches the application and enters basic information such as name, email address, password, height, weight, and blood sugar level on the new registration screen.

[0729] Step 2:

[0730] The terminal sends the entered information to the server.

[0731] Step 3:

[0732] The server saves the received information to the database.

[0733] Step 4:

[0734] The user accesses the in-app chat function and enters a message such as, "I've been under a lot of stress lately."

[0735] Step 5:

[0736] The device sends the user's message to the server.

[0737] Step 6:

[0738] The server analyzes the messages it receives and uses an artificial intelligence engine to evaluate the user's mental state.

[0739] Step 7:

[0740] Based on the evaluation results, the server generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle suggestions (e.g., dietary improvements, exercise recommendations).

[0741] Step 8:

[0742] The terminal displays the suggestions received from the server to the user.

[0743] Step 9:

[0744] The user reviews the proposal, decides whether to implement it, and if they decide to implement it, provides feedback such as "I'll give it a try."

[0745] Step 10:

[0746] The device sends user feedback to the server.

[0747] Step 11:

[0748] The server saves user feedback and uses it to improve future suggestions.

[0749] Step 12:

[0750] The server generates information on basic knowledge and support methods related to diabetes, and creates content for sharing with family and friends.

[0751] Step 13:

[0752] The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[0753] Step 14:

[0754] Users click the share button to share information with family and friends.

[0755] Step 15:

[0756] The device notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[0757] In this way, the overall processing flow of the system operates in concrete terms.

[0758] (Example 1)

[0759] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0760] There is a need for a system that improves the mental and physical health of diabetic patients and their families and friends by providing effective stress management and lifestyle suggestions. Furthermore, a system is needed to generate personalized suggestions for each patient and to continuously evaluate and improve their effectiveness.

[0761] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0762] In this invention, the server includes means for inputting and transmitting user health information; server means for storing transmitted health information; means for analyzing the user's mental state in response to user input; means for generating stress management methods and lifestyle suggestions based on the analysis results; terminal means for displaying the generated suggestions; means for collecting and storing user feedback; means for generating and providing information on basic knowledge and support methods regarding diabetes; means for creating an account and storing personal information; means for analyzing messages using a natural language processing engine; means for presenting customized suggestions and storing feedback for use in generating suggestions in the future; and means for generating educational information and providing it in text, video, and infographic formats. This enables the provision of individually customized suggestions and continuous support to diabetic patients and their families, thereby improving their mental and physical health.

[0763] "Means for inputting and transmitting user health information" refers to devices or applications that allow diabetic patients and their families to input information about their health status (e.g., blood glucose levels, weight, exercise habits) into a system and transmit it to a server.

[0764] "A server system for storing transmitted health information" refers to a central system for securely and efficiently storing health information transmitted by users.

[0765] "Means for analyzing a user's mental state in response to their input" refers to artificial intelligence engines and natural language processing technologies that analyze messages entered by users and evaluate their stress levels and mental state.

[0766] "Means for generating stress management methods and lifestyle suggestions based on analysis results" refers to a system component that automatically generates individually customized stress management methods and lifestyle improvement suggestions based on the results of an analysis of a person's mental state.

[0767] "Terminal means for displaying generated proposals" refers to a device (e.g., smartphone, tablet, PC) that displays the proposal content sent from the server to the user.

[0768] "Means for collecting and saving user feedback" refers to a system that collects feedback provided by users and saves that feedback for generating future suggestions.

[0769] "Means for generating and providing information on basic knowledge and support methods related to diabetes" refers to a system component that generates and provides users with educational knowledge and support methods related to diabetes.

[0770] "A means of creating an account and storing personal information" refers to a system that allows users to create an account and securely store their personal information.

[0771] "Means of analyzing messages using a natural language processing engine" refers to a system that utilizes natural language processing technology to analyze messages entered by users and understand their content.

[0772] "A means of presenting customized suggestions and saving feedback for use in generating future suggestions" refers to a system that presents individually customized suggestions to users and saves user feedback for use in generating future suggestions.

[0773] "Means for generating and providing educational information in text, video, and infographic formats" refers to a system that generates educational information about diabetes and provides it to users in text, video, and infographic formats.

[0774] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends.

[0775] System Configuration

[0776] The main components are as follows:

[0777] 1. User's device

[0778] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[0779] 2. Server

[0780] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[0781] 3. Artificial Intelligence Engine

[0782] A module that uses AI technologies for natural language processing and data analysis.

[0783] Operation details

[0784] Data collection and initial setup

[0785] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[0786] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[0787] 2. Terminal: Sends the provided information to the server.

[0788] Specific example: When the user confirms their input, the device sends the data to the server.

[0789] 3. Server: Saves the received data as the initial settings.

[0790] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[0791] User interaction

[0792] 1. User: Use the in-app chat function to enter questions or your current mental state.

[0793] Example: Enter "I've been feeling stressed lately and it's bothering me."

[0794] 2. Terminal: Sends user responses to the server in real time.

[0795] Specific example: Immediately relaying user messages to the server.

[0796] 3. Server: Analyzes the received data and assesses the user's stress level and current health status.

[0797] Specific example: The server uses a natural language processing engine to analyze user messages for signs of stress.

[0798] Example of technology used: Text analysis is performed using Python NLP libraries (e.g., SpaCy, NLTK).

[0799] Stress management and lifestyle suggestions

[0800] 1. Server: Based on the evaluation results, it generates customized stress management methods and lifestyle suggestions.

[0801] Example of a generative AI model: Generates proposal text using OpenAI's GPT-3 model.

[0802] Prompt example: "The user has reported feeling stressed recently. Please provide advice on deep breathing exercises and dietary improvements."

[0803] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[0804] 2. Terminal: Displays suggestions received from the server to the user.

[0805] Specific example: Present the proposal content as a chat screen or notification.

[0806] Feedback and support

[0807] 1. User: Either implement the suggested method or ask further questions.

[0808] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[0809] 2. Terminal: Sends user feedback to the server.

[0810] Specific example: Send the feedback content to the server immediately.

[0811] 3. Server: The server saves the feedback to a database and uses it to generate suggestions for the next time.

[0812] Specific example: Record user feedback to incorporate it into future analyses and suggestions.

[0813] Provision of educational information

[0814] 1. Server: Generates and provides users with basic knowledge and support methods regarding diabetes.

[0815] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[0816] 2. Terminal: Displays the provided information to the user.

[0817] Display format examples: Display educational content as text, video, and infographics.

[0818] 3. User: Share the suggested ideas and receive support from family and friends.

[0819] Specific example: Use the in-app share button to share the provided information with family.

[0820] This invention provides a system that allows users to evaluate their physical and mental state in real time and receive appropriate suggestions and support. By using this system, users can maintain healthier lifestyles and improve their diabetes management.

[0821] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0822] Step 1:

[0823] User: Install and launch the application. The user enters the required personal information (e.g., name, age, gender) on the account creation screen and creates an account.

[0824] Enter the following information: "Name: Taro Yamada", "Age: 45", "Gender: Male".

[0825] Output: Request to create an account and save personal information.

[0826] Step 2:

[0827] Terminal: Sends the entered personal information to the server.

[0828] Input: Personal information entered by the user.

[0829] Output: Data sent to the server.

[0830] Step 3:

[0831] Server: Stores received personal information in the database.

[0832] Input: Personal information sent from the device.

[0833] Output: Personal information stored in the database.

[0834] Step 4:

[0835] User: Enter your health information (e.g., blood sugar level, weight, exercise frequency) on the health information input screen.

[0836] Input: Enter "Blood glucose level: 110 mg / dL", "Weight: 70 kg", "Exercise frequency: 3 times a week".

[0837] Output: Health information entry complete.

[0838] Step 5:

[0839] Terminal: Sends health information to the server.

[0840] Input: Health information entered by the user.

[0841] Output: Data sent to the server.

[0842] Step 6:

[0843] Server: Receives health information and stores it in the database.

[0844] Input: Health information sent from the device.

[0845] Output: Health information stored in the database.

[0846] Step 7:

[0847] User: Use the chat function to enter your current mental state or questions.

[0848] Input: Type "I've been under a lot of stress lately and it's bothering me."

[0849] Output: Mental state input complete.

[0850] Step 8:

[0851] Terminal: Sends entered messages to the server in real time.

[0852] Input: Message from the user.

[0853] Output: Data sent to the server.

[0854] Step 9:

[0855] Server: Uses a natural language processing engine to analyze user input messages and assess stress levels.

[0856] Input: Message received from the user.

[0857] Data processing: Text analysis is performed using Python NLP libraries (e.g., SpaCy, NLTK).

[0858] Output: Evaluation results regarding stress levels.

[0859] Step 10:

[0860] Server: Generates customized stress management methods and lifestyle suggestions based on stress level assessments.

[0861] Input: Stress level assessment results.

[0862] Data processing: Generate proposal text using a generative AI model (e.g., OpenAI's GPT-3).

[0863] Prompt example: "The user has reported feeling stressed recently. Please provide advice on deep breathing exercises and dietary improvements."

[0864] Output: Customized proposal text.

[0865] Step 11:

[0866] Terminal: Displays the suggested text received from the server to the user.

[0867] Input: Proposal text sent from the server.

[0868] Output: The suggested text displayed to the user.

[0869] Specific example of action: The chat screen displays the message, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing your intake of whole grains in your diet."

[0870] Step 12:

[0871] User: Either implement the suggested method or enter further questions.

[0872] Input: Type "I will try the deep breathing exercise" and send feedback.

[0873] Output: Successfully submitted practice report and new questions.

[0874] Step 13:

[0875] Terminal: Sends user feedback to the server.

[0876] Input: User feedback.

[0877] Output: Data sent to the server.

[0878] Step 14:

[0879] Server: The feedback is saved to a database and used to generate suggestions for the next time.

[0880] Input: Feedback sent from the device.

[0881] Output: Feedback stored in the database.

[0882] Step 15:

[0883] Server: Generates and provides users with basic knowledge and support methods regarding diabetes.

[0884] Input: User's current health information and feedback.

[0885] Data processing: Generate educational content using natural language generation technology.

[0886] Output: Educational text about diabetes.

[0887] Step 16:

[0888] Terminal: Displays the provided information to the user.

[0889] Input: Educational message sent from the server.

[0890] Output: Displaying information on the screen.

[0891] Specific example of actions: Present educational content as text, video, and infographics.

[0892] Step 17:

[0893] User: Share the suggested information and receive support from family and friends.

[0894] Input: Share the provided information via the app's share button.

[0895] Output: Information sharing complete.

[0896] (Application Example 1)

[0897] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0898] Diabetic patients often face not only physical health management challenges but also mental stress management and financial burdens. However, there is no system in place to comprehensively manage these aspects and provide appropriate lifestyle and financial suggestions. Therefore, there is a need for systems and methods to alleviate the mental and financial stress of diabetic patients and promote healthy living.

[0899] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0900] In this invention, the server includes: means for inputting and transmitting the user's health and economic information; server means for storing and analyzing the transmitted information; means for analyzing the user's mental and economic state in response to user input; means for generating stress management methods, lifestyle habits, and economic suggestions based on the analysis results; terminal means for displaying the generated suggestions; means for collecting and storing user feedback; and means for generating and providing information on basic knowledge and support methods related to diabetes. This makes it possible for diabetic patients and their related parties to comprehensively manage their health, mental state, and economic state and receive appropriate suggestions.

[0901] "User health information" refers to physiological data such as height, weight, blood glucose levels, and meal frequency that diabetic patients record on a daily basis.

[0902] "Economic information" refers to economic data such as users' spending, budgets, and monthly expenses.

[0903] A "server" refers to a central control unit that stores transmitted data, performs analysis, and provides the results to users.

[0904] "Mental state" refers to information that represents the user's stress level and emotional health.

[0905] "Economic status" refers to information that represents the user's financial health and spending habits.

[0906] "Stress management methods" refer to methods and techniques for reducing the mental stress of users (e.g., deep breathing exercises and relaxation techniques).

[0907] "Lifestyle suggestions" refer to specific suggestions for improving the user's daily life (e.g., dietary advice or recommendations for exercise).

[0908] "Economic suggestions" refer to specific advice aimed at improving the user's financial situation (e.g., selecting cost-effective foods or recommending exercise plans).

[0909] A "terminal" refers to a device (e.g., a smartphone or tablet) that displays suggestions and information to the user and allows for data input and transmission.

[0910] "Feedback" refers to the evaluations and comments that users provide to the system.

[0911] "Basic knowledge about diabetes" refers to fundamental information regarding blood sugar management methods, diet, and exercise.

[0912] The system of the present invention is intended to provide integrated health management, mental stress management, and economic solutions to diabetic patients and their families. As an example of implementing the present invention, a specific system configuration and its operation are described below.

[0913] System Configuration

[0914] The main components of this system are as follows:

[0915] 1. User's device: A device (smartphone, tablet) used by the user to input health and financial information and receive suggestions.

[0916] 2. Server: A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[0917] 3. Artificial Intelligence Engine: A module that uses AI technologies for natural language processing and data analysis (e.g., TensorFlow).

[0918] Operation details

[0919] Data collection and initial setup

[0920] 1. User: Launch the application and enter the necessary personal information, health information, and financial information (e.g., blood sugar levels, weight, exercise habits, monthly expenses).

[0921] 2. Terminal: Sends the provided information to the server.

[0922] 3. Server: Saves the received data as the initial settings.

[0923] User interaction

[0924] 1. User: Use the in-app chat function to enter questions, current mental state, and financial status.

[0925] 2. Terminal: Sends user responses to the server in real time.

[0926] 3. Server: Analyzes received data to assess the user's stress level, current health status, and financial status.

[0927] Stress management, lifestyle, and economic suggestions

[0928] 1. Server: Based on the evaluation results, it generates customized stress management methods, lifestyle habits, and economic suggestions (e.g., relaxation exercises, dietary advice, recommendations for cost-effective health foods).

[0929] 2. Terminal: Displays suggestions received from the server to the user.

[0930] Support provision and education

[0931] 1. Server: Provides information to deepen basic knowledge and understanding of diabetes, and also offers specific advice on how family and friends can support people with diabetes.

[0932] 2. Device: Displays the provided information to the user, their family, and friends.

[0933] Hardware and software to be used

[0934] Frontend: Built using React Native. Provides a UI for collecting user-entered information and sending it to the server.

[0935] Backend: Built using Node.js and Express. It stores and parses incoming data and generates suggestions.

[0936] Database: MongoDB is used to store user health information, financial information, feedback, etc.

[0937] AI Engine: Uses TensorFlow for natural language processing and data analysis.

[0938] Specific example

[0939] Let's assume the user enters the following information.

[0940] Height: 170cm

[0941] Weight: 70kg

[0942] Blood glucose level: 140 mg / dL

[0943] Number of meals per day: 3

[0944] Monthly expenses: 60,000 yen

[0945] Based on this information, the server generates a suggestion that reads, "Your stress level is high. Try incorporating daily deep breathing exercises and a healthy diet. Your financial situation is also high, so review your balanced diet and exercise plan."

[0946] Example of a prompt

[0947] Question: The user has entered the following information. Please provide appropriate health and financial suggestions.

[0948] Height: 170cm

[0949] Weight: 70kg

[0950] Blood glucose level: 140 mg / dL

[0951] Number of meals per day: 3

[0952] Monthly expenses: 60,000 yen

[0953] Answer: Your stress levels are high. Focus on daily deep breathing exercises and a healthy diet. Your financial situation is also high, so review your balanced diet and exercise plan.

[0954] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0955] Step 1:

[0956] Data entry (health information and economic information)

[0957] The user launches the application and enters information such as height, weight, blood sugar level, number of meals per day, and monthly expenses.

[0958] Input: Height, weight, blood sugar level, number of meals, expenses

[0959] Output: Data in JSON format (Example: { "height": 170, "weight": 70, "glucose": 140, "mealsPerDay": 3, "expenses": 60000})

[0960] Step 2:

[0961] Data transmission

[0962] The terminal sends the data entered by the user to the server.

[0963] Input: User data in JSON format

[0964] Output: Data sent to the server

[0965] Step 3:

[0966] Data storage

[0967] The server saves the received data to a database (MongoDB).

[0968] Input: Received data (JSON format)

[0969] Output: Records stored in the database

[0970] Step 4:

[0971] Data Analysis

[0972] The server uses a natural language processing engine (TensorFlow) to analyze the user's mental and economic state.

[0973] Input: User information retrieved from the database

[0974] Data processing: Stress levels are calculated based on blood glucose levels, meal frequency, etc., and economic status is evaluated based on monthly expenses.

[0975] Output: Assessment of stress level and economic status (e.g., { "stressLevel": "High", "economicStatus": "High"})

[0976] Step 5:

[0977] Proposal generation

[0978] Based on the analysis results, the server generates stress management methods, lifestyle suggestions, and economic advice.

[0979] Input: Stress level, assessment of economic status

[0980] Data processing: The program generates exercise and dietary advice for stress reduction, as well as specific suggestions for improving financial conditions.

[0981] Output: Suggestions (e.g., deep breathing exercises, healthy eating, recommendations for cost-effective foods)

[0982] Step 6:

[0983] Suggestion display

[0984] The terminal displays suggestions received from the server to the user.

[0985] Input: Proposal (string in JSON format)

[0986] Output: Suggestions displayed on the device's UI

[0987] Step 7:

[0988] Feedback Collection

[0989] Users provide feedback on suggestions within the application.

[0990] Input: Feedback (e.g., "I tried the deep breathing exercises")

[0991] Output: Feedback data in JSON format

[0992] Step 8:

[0993] Send and save feedback

[0994] The device sends the collected feedback to the server, which then stores it in a database.

[0995] Input: User feedback data

[0996] Output: Feedback stored in the database

[0997] Step 9:

[0998] Support information provided

[0999] The server generates information on basic knowledge and support methods related to diabetes and provides it to users and their related parties.

[1000] Input: None (Information generated periodically)

[1001] Output: Educational content (e.g., text, video, infographics)

[1002] Step 10:

[1003] Support information display

[1004] The device displays educational content received from the server to the user.

[1005] Input: Data from educational content

[1006] Output: Educational content displayed on the device's UI

[1007] Through these steps, this system enables diabetic patients and their families to comprehensively manage their health, mental state, and financial situation, and to receive appropriate suggestions.

[1008] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1009] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends, and further incorporates an emotion engine to recognize the user's emotions and reflect them in the analysis results.

[1010] System Configuration

[1011] The main components are as follows:

[1012] 1. User's device

[1013] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[1014] 2. Server

[1015] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[1016] 3. Artificial Intelligence Engine

[1017] A module that uses AI technologies for natural language processing and data analysis. It integrates an emotion engine and has the ability to analyze the user's emotions from input data.

[1018] 4. Emotional Engine

[1019] A module that recognizes emotions based on user input and incorporates them into the assessment of mental state.

[1020] Operation details

[1021] Data collection and initial setup

[1022] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[1023] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[1024] 2. Terminal: Sends the provided information to the server.

[1025] Specific example: When the user confirms their input, the device sends the data to the server.

[1026] 3. Server: Saves the received data as the initial settings.

[1027] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[1028] User interaction

[1029] 1. User: Use the in-app chat function to enter questions or your current mental state.

[1030] Example: Enter "I've been feeling stressed lately and it's bothering me."

[1031] 2. Terminal: Sends user responses to the server in real time.

[1032] Specific example: Immediately relaying user messages to the server.

[1033] 3. Server: Analyzes the received data, uses the emotion engine to recognize the user's emotions, and evaluates their overall mental state.

[1034] Specific example: The server uses an emotion engine to analyze the user's message and recognize emotions such as "lonely."

[1035] Stress management and lifestyle suggestions

[1036] 1. Server: Based on the emotion analysis results, it generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle suggestions (e.g., dietary improvements, exercise recommendations).

[1037] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[1038] 2. Terminal: Displays the suggestions received from the server to the user.

[1039] Specific example: Present the proposal content as a chat screen or notification.

[1040] 3. User: Decide whether or not to implement the suggested method, and if so, provide feedback such as "I will try it."

[1041] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[1042] 4. Terminal: Sends user feedback to the server.

[1043] Specific example: Send the feedback content to the server.

[1044] 5. Server: Save user feedback and use it to improve future suggestions.

[1045] Specific example: Store feedback in a database and use it for individual suggestions.

[1046] Support provision and education

[1047] 1. Server: Generates information on basic knowledge and support methods regarding diabetes, and creates content for sharing with family and friends.

[1048] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[1049] 2. Device: Display educational information to the user and provide options (e.g., a share button) for sharing with family and friends.

[1050] Specific example: Display educational content in text, video, or infographic format.

[1051] 3. User: Click the share button to share the provided information with family and friends.

[1052] Specific example: Click the share button to send the provided information to family members via email.

[1053] 4. Terminal: Notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[1054] Specific example: An email sent to a family member contains educational information.

[1055] In this way, by combining the emotional engine, the present invention can provide diabetic patients and their families with more detailed and personalized stress management and healthy lifestyle suggestions, thereby improving the mental and physical health of users.

[1056] The following describes the processing flow.

[1057] Step 1:

[1058] The user launches the application and enters basic information such as name, email address, password, height, weight, and blood sugar level on the new registration screen.

[1059] Step 2:

[1060] The terminal sends the entered information to the server.

[1061] Step 3:

[1062] The server saves the received information to the database.

[1063] Step 4:

[1064] The user accesses the in-app chat function and enters their feelings or mental state, such as "I've been feeling stressed lately."

[1065] Step 5:

[1066] The device sends the user's message to the server.

[1067] Step 6:

[1068] The server uses an emotion engine to analyze the user's message to determine their emotions. For example, it might extract emotions like "stress" and "worry" from the user's input, "I've been feeling stressed lately and it's really bothering me."

[1069] Step 7:

[1070] The server evaluates the mental state based on the results of the emotion analysis and determines the stress level.

[1071] Step 8:

[1072] Based on the emotion analysis results, the server generates personalized stress management methods (e.g., deep breathing exercises, meditation) and lifestyle suggestions (e.g., balanced diet, regular exercise).

[1073] Step 9:

[1074] The terminal displays suggestions received from the server to the user. For example, "We recommend doing deep breathing exercises for 10 minutes every day."

[1075] Step 10:

[1076] The user reviews the proposal and decides whether to implement it. If they decide to implement it, they provide feedback such as "I'll give it a try."

[1077] Step 11:

[1078] The device sends user feedback to the server.

[1079] Step 12:

[1080] The server saves user feedback and uses it to improve future suggestions. It also evaluates the effectiveness of suggestions based on the feedback.

[1081] Step 13:

[1082] The server generates information on basic knowledge and support methods related to diabetes, and creates content for sharing with family and friends.

[1083] Step 14:

[1084] The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[1085] Step 15:

[1086] Users click the share button to share information with family and friends.

[1087] Step 16:

[1088] The device notifies the server of the sharing action.

[1089] Step 17:

[1090] The server sends information using the selected sharing method (e.g., email, social media). For example, it might send an email containing educational information to a family member.

[1091] In this way, the overall processing flow of the system operates in concrete terms.

[1092] (Example 2)

[1093] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[1094] To provide effective mental stress management and lifestyle improvement suggestions to diabetic patients and their families and friends, it is necessary to accurately analyze the health and mental state of each individual user and generate customized suggestions. However, conventional systems have faced challenges in providing individually tailored suggestions due to insufficient emotional analysis and detailed feedback collection.

[1095] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1096] In this invention, the server includes means for users to input and transmit personal information and health-related information; means for storing the transmitted information and recording it in a database; means for using an artificial intelligence module to analyze the user's input data; means for customizing and generating stress management methods and lifestyle suggestions based on the input data and analysis results; terminal device means for presenting the generated suggestions to the user; means for collecting, analyzing, and storing user feedback; and means for generating and providing health-related educational and support information. This makes it possible to provide customized suggestions in real time based on each user's individual health and mental state.

[1097] "User" refers to an individual who uses the system to manage and receive suggestions regarding their health information and mental state.

[1098] "Personal information" refers to basic data used to identify a user, such as name, age, and gender.

[1099] "Health-related information" refers to data that indicates the user's health status, such as blood glucose levels, weight, and exercise habits.

[1100] A "server" refers to a central computing system that stores data, performs analysis, and generates proposals.

[1101] A "sentiment analysis engine" refers to a technology module that recognizes and analyzes a user's emotions from input text and data.

[1102] An "artificial intelligence module" refers to a program that uses AI technology to perform data analysis and proposal generation.

[1103] "Stress management" refers to methods and techniques for improving mental health.

[1104] "Lifestyle suggestions" refer to suggestions that indicate recommended actions and habits for maintaining or improving health.

[1105] "Feedback" refers to suggestions, reactions, and opinions on services collected from users.

[1106] "Educational information" refers to data that provides users, their families, and friends with knowledge and support methods regarding diabetes.

[1107] "Shareable" refers to a feature that allows users to share information with other people.

[1108] This invention is a system that uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends. This system incorporates an emotion engine to recognize the user's emotions and reflect them in the analysis results.

[1109] System Configuration

[1110] The main components are as follows:

[1111] 1. User's device

[1112] These are devices that allow users to input health information and receive suggestions. Examples include smartphones, tablets, and PCs.

[1113] 2. Server

[1114] This is a central system that stores, analyzes, and generates suggestions based on data submitted by users.

[1115] 3. Artificial Intelligence Module

[1116] This program uses AI technologies for natural language processing and data analysis. It integrates an emotion analysis engine to analyze the user's emotions from the input data.

[1117] 4. Emotion Analysis Engine

[1118] This is a technology module for recognizing emotions based on user input and incorporating them into the assessment of mental state.

[1119] Operation details

[1120] The system works as follows:

[1121] Data collection and initial setup

[1122] 1. The user launches the application and enters necessary personal and health information (e.g., blood sugar level, weight, exercise habits). For example, they might enter, "Height 170cm, weight 70kg, blood sugar level 110mg / dL, I eat 3 meals a day."

[1123] 2. The terminal sends the provided information to the server. Once the user confirms the input, the terminal sends the data to the server.

[1124] 3. The server saves the received data as initial settings. Specifically, the server records the user's basic health information in a database and uses it as initial settings.

[1125] User interaction

[1126] 1. Users use the chat function to enter questions or their current mental state. For example, they might type, "I've been feeling stressed lately and it's bothering me."

[1127] 2. The terminal sends user responses to the server in real time.

[1128] 3. The server analyzes the received data, uses an emotion analysis engine to recognize the user's emotions, and evaluates their overall mental state. For example, the server uses the emotion analysis engine to analyze "stress" from the user's message.

[1129] Stress management and lifestyle suggestions

[1130] 1. Based on the emotion analysis results, the server generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle recommendations. For example, it might generate, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing your intake of whole grains in your diet."

[1131] 2. The terminal displays the suggestions received from the server to the user.

[1132] 3. The user decides whether or not to implement the suggested method, and if so, provides feedback such as "I'll try it."

[1133] 4. The device sends user feedback to the server.

[1134] 5. The server saves user feedback and uses it to improve future suggestions.

[1135] Support provision and education

[1136] 1. The server generates information on basic knowledge and support methods regarding diabetes, and creates content for sharing with family and friends. For example, it might generate information such as, "Managing blood sugar levels is important for diabetes. By helping family and friends understand this, you can get support with diet management and exercise."

[1137] 2. The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[1138] 3. The user clicks the share button to share the provided information with family and friends.

[1139] 4. The device notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[1140] This allows the system, which combines an emotion analysis engine and an artificial intelligence module, to provide personalized stress management and healthy lifestyle suggestions to diabetic patients and their families, thereby improving the users' mental and physical health.

[1141] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1142] Step 1:

[1143] User: Launches the application and enters personal and health-related information (e.g., height, weight, blood sugar level, exercise habits). The entered information (input data) is sent to the terminal.

[1144] Input: Personal information, health-related information

[1145] Output: Input data sent to the terminal

[1146] Specific actions: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, I eat 3 meals a day" into the app's form and press the confirm button.

[1147] Step 2:

[1148] Terminal: Sends user-entered data to the server.

[1149] Input: Data entered by the user

[1150] Output: Data to send to the server

[1151] Specific action: When the confirmation button is pressed, the device sends the data to the server via the internet.

[1152] Step 3:

[1153] Server: Saves the transmitted data to the database and records it as initial settings.

[1154] Input: Data sent from the device

[1155] Output: User data stored in the database

[1156] Specific operation: The server receives data, records it in the database, and creates a profile for each user.

[1157] Step 4:

[1158] User: Use the chat function to enter your current mental state or questions.

[1159] Input: Text of mental state or question

[1160] Output: Input data sent to the terminal

[1161] Specific action: Type "I've been feeling stressed lately" into the chat window and press the send button.

[1162] Step 5:

[1163] Terminal: Sends user messages to the server in real time.

[1164] Input: User input message

[1165] Output: Message sent to the server

[1166] Specific operation: The message is transferred to the server the moment the send button is pressed.

[1167] Step 6:

[1168] Server: Analyzes received messages using an emotion analysis engine and evaluates the emotional state.

[1169] Input: Message sent by the user

[1170] Data processing: The sentiment analysis engine analyzes the message content.

[1171] Output: Emotional state (e.g., "stress")

[1172] Specific operation: The server uses an emotion analysis engine to analyze "stress" from the input "high stress level" and records it as an emotional state.

[1173] Step 7:

[1174] Server: Based on the emotion analysis results, it generates customized stress management methods and lifestyle suggestions.

[1175] Input: Sentiment analysis results

[1176] Data processing: Generative AI model generates suggestions.

[1177] Output: Proposed content (Example: "Perform deep breathing exercises for 10 minutes every day")

[1178] Specific operation: The server prompts the AI ​​model with "suggestions based on the user's sentiment analysis results" and generates suggestions.

[1179] Step 8:

[1180] Terminal: Displays the suggestions received from the server to the user.

[1181] Input: Suggestions from the server

[1182] Output: Suggestions displayed to the user

[1183] Specific action: Use the application's notification function to display the suggested content as a pop-up on the screen.

[1184] Step 9:

[1185] User: Decide whether to implement the suggestion and provide feedback.

[1186] Input: User feedback

[1187] Output: Feedback sent to the device

[1188] Specific action: Send feedback saying "I'll try the deep breathing exercise" and press the submit button.

[1189] Step 10:

[1190] Terminal: Sends user feedback to the server.

[1191] Input: User feedback

[1192] Output: Feedback sent to the server

[1193] Specific action: The feedback content is sent directly to the server.

[1194] Step 11:

[1195] Server: Saves user feedback to a database and uses it to improve future suggestions.

[1196] Input: User feedback

[1197] Output: Feedback stored in the database

[1198] Specific operation: The feedback is saved to a database and referenced when generating suggestions in the future.

[1199] Step 12:

[1200] Server: Generates basic knowledge and support information about diabetes, and creates content for sharing with family and friends.

[1201] Input: Health-related information stored on the server

[1202] Data processing: Generative AI model generates educational information.

[1203] Output: Health education content (e.g., "Key Points for Diabetes Management")

[1204] Specific operation: The server prompts the AI ​​model to generate "educational information on diabetes management" and generates the content.

[1205] Step 13:

[1206] Terminal: Displays generated educational information to the user and provides the option to share it with family and friends.

[1207] Input: Educational information from the server

[1208] Output: Educational content and sharing options displayed to the user

[1209] Specific actions: Display educational content in text or video format and include a share button.

[1210] Step 14:

[1211] User: Click the share button to share the provided information with family and friends.

[1212] Input: Share Action

[1213] Output: Instructions for sharing information

[1214] Specific actions: Click the share button and select the sharing method (e.g., email, social media).

[1215] Step 15:

[1216] Terminal: Notifies the server of the sharing action, and the server sends the information using the selected sharing method.

[1217] Input: Shared Action Notification

[1218] Output: Information sent to family and friends

[1219] Specific operation: A share action trigger is sent to the server, and the information is shared in the selected manner.

[1220] (Application Example 2)

[1221] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[1222] A system is needed to monitor the mental stress and health status of passengers in autonomous vehicles in real time and to provide appropriate stress management and lifestyle suggestions. Conventional systems have been unable to adequately monitor the mental and health status of passengers, which is crucial for maintaining safe driving, and have been unable to take appropriate action.

[1223] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using a biosensor to monitor health status, means for using a camera to analyze emotions, and means for evaluating the passenger's mental state based on data from the camera and biosensor. This makes it possible to monitor the stress level and health status of passengers in an autonomous vehicle in real time and to immediately provide appropriate stress management and lifestyle suggestions.

[1224] "Means for inputting and transmitting health information" refers to a device that allows users to input their own health data (e.g., blood sugar levels, heart rate, weight, etc.) and transmit that information to a server within the system.

[1225] A "server system for storing transmitted health information" refers to a central system for receiving health information transmitted by users and securely storing it in a database.

[1226] "Means for analyzing mental state" refers to devices or software that analyze user input or data from biosensors to evaluate the user's emotions and mental state.

[1227] "Means for generating stress management methods and lifestyle suggestions" refers to a device or software that generates stress management methods and lifestyle improvement suggestions suitable for the user based on analyzed information about the user's mental state.

[1228] "Display device for displaying generated suggestions" refers to a device for visually presenting to the user stress management and lifestyle habit suggestions generated by the system.

[1229] "Means for collecting and storing user feedback" refers to a device or software for collecting feedback on suggestions made by users and storing that information in a database within the system.

[1230] "Methods using biosensors to monitor health status" refer to devices that collect physiological data from users in real time, such as heart rate and skin electrical responses.

[1231] "Methods using cameras to analyze emotions" refer to imaging devices that detect the user's facial expressions and posture and evaluate their emotions based on that information.

[1232] "Means for evaluating passengers' mental state based on data from cameras and biosensors" refers to a device or software that analyzes data collected from cameras and biosensors to comprehensively evaluate the mental state of users.

[1233] "Means of suggesting relaxation music or exercises while driving" refers to a device or software that suggests music or exercise methods with relaxation effects based on the user's mental state.

[1234] "Means for generating and providing information on basic knowledge and support methods regarding diabetes" refers to devices or software that generate and provide information to help users and their families understand and appropriately manage diabetes.

[1235] This invention provides a system that monitors the mental stress and health status of passengers in autonomous vehicles in real time and offers appropriate stress management and lifestyle suggestions. The specific system configuration and its operation are described below.

[1236] System Configuration

[1237] The system consists of the following main components:

[1238] 1. User's equipment

[1239] A device (e.g., smartphone, tablet) for entering health information and receiving suggestions.

[1240] 2. Sensor devices

[1241] A heart rate sensor that measures heart rate (e.g., Polar H9).

[1242] A skin electromechanist (e.g., Empatica E4) that measures the electrical response of the skin.

[1243] 3. Camera device

[1244] A camera used to capture facial expressions and analyze emotions (e.g., a camera built into a vehicle).

[1245] 4. Server

[1246] A central system that stores and analyzes health information and emotional data, and generates recommendations.

[1247] 5. Artificial Intelligence Engine

[1248] A module that uses AI technologies for natural language processing and data analysis. It integrates an emotion engine and has the ability to analyze the user's emotions from input data.

[1249] 6. Display Device

[1250] A device for displaying generated suggestions.

[1251] Operation details

[1252] 1. Data Collection

[1253] The user's device inputs health information (e.g., blood glucose levels, weight, exercise habits) and sends it to the server.

[1254] The system collects heart rate and skin electrical response data in real time from sensor devices and captures passenger facial expression data from camera devices.

[1255] 2. Data Analysis and Evaluation

[1256] The server receives and stores transmitted health information, heart rate data from biosensors, and skin electrical response data.

[1257] The system analyzes facial expression data from camera devices and uses an emotion engine to evaluate the emotional state of passengers.

[1258] 3. Proposal generation

[1259] The server uses an AI engine to generate stress management methods and lifestyle suggestions based on health information, heart rate, skin electrical responses, and emotional data.

[1260] Specific examples include "recommending the playback of relaxation music" and "suggesting deep breathing exercises."

[1261] 4. Proposal display and feedback collection

[1262] The generated suggestions are presented to the user through a display device.

[1263] Users provide feedback on the suggestions and send that feedback information to the server.

[1264] The server receives feedback information and incorporates it into the next proposal generation.

[1265] Specific example

[1266] Example prompt message: When your heart rate is high and emotion analysis identifies you as "anxious".

[1267] Prompt message: Heart rate 95, skin electrical response 0.75, anxiety

[1268] This system will enable real-time monitoring of passengers' stress levels and health status in autonomous vehicles, and will immediately provide appropriate stress management and lifestyle suggestions.

[1269] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1270] Step 1:

[1271] The user inputs health information. Specifically, the user uses an input device such as a smartphone to enter health information such as blood glucose levels, weight, and exercise habits into the application. The entered data is sent to the server by the device. The input consists of numerical data such as blood glucose levels and weight, which is then sent to the server.

[1272] Step 2:

[1273] The server receives the transmitted health information and stores it in the database. The server receives the user's health information and records it in the database. The health information is stored accurately because it will be used for subsequent analysis. At this stage, the input is the health information from the user, and the output is the health information stored in the database.

[1274] Step 3:

[1275] Real-time data collection begins using sensor devices (heart rate sensor and electrodermal meter) and a camera device. The terminal collects heart rate and electrodermal response data from the heart rate sensor and electrodermal meter, and captures the passenger's facial expressions with the camera device. The inputs collected are heart rate, electrodermal response, and facial expression data, which are then sent to the server.

[1276] Step 4:

[1277] The server receives and stores the collected biosensor data and camera device data. The received data is recorded in a database. The input is biometric data from the sensor device and camera device, and the output is the stored biometric data.

[1278] Step 5:

[1279] The server analyzes facial expression data from the camera device and uses an artificial intelligence engine to evaluate emotional states. Specifically, the collected facial expression data is processed as images and input into an emotion recognition model. The AI ​​engine analyzes the emotional state and identifies emotions such as "anxiety" or "loneliness." The input is facial expression data, and the output is the result of the emotion analysis.

[1280] Step 6:

[1281] The server uses a generative AI model to generate stress management methods and lifestyle suggestions based on stored health information, biosensor data, and emotional states. The AI ​​engine comprehensively analyzes multiple data points to generate suggestions tailored to the user. Specific examples include "Play relaxation music" and "Perform deep breathing exercises." Inputs are health information, biosensor data, and emotional analysis results, while output is the suggested content.

[1282] Step 7:

[1283] The server sends the generated suggestions to the terminal. The terminal displays the received suggestions on a display device, visually presenting them to the user. As output, the user can then review the suggestions.

[1284] Step 8:

[1285] The user decides whether to implement the suggested method and enters feedback. If the user implements the suggested method, they enter feedback such as "I tried it" or "It was effective" into the terminal. This input is the feedback content and is sent to the server.

[1286] Step 9:

[1287] The server receives user feedback and stores it in a database. This feedback information is used to generate suggestions for future updates. The input is user feedback, and the output is the stored feedback information.

[1288] This allows the system to monitor the user's health and mental state in real time and provide appropriate stress management and lifestyle suggestions.

[1289] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1290] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1291] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1292] [Third Embodiment]

[1293] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1294] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1295] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1296] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1297] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1298] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1299] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1300] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1301] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1302] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1303] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1304] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1305] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends.

[1306] System Configuration

[1307] The main components are as follows:

[1308] 1. User's device

[1309] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[1310] 2. Server

[1311] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[1312] 3. Artificial Intelligence Engine

[1313] A module that uses AI technologies for natural language processing and data analysis.

[1314] Operation details

[1315] Data collection and initial setup

[1316] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[1317] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[1318] 2. Terminal: Sends the provided information to the server.

[1319] Specific example: When the user confirms their input, the device sends the data to the server.

[1320] 3. Server: Saves the received data as the initial settings.

[1321] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[1322] User interaction

[1323] 1. User: Use the in-app chat function to enter questions or your current mental state.

[1324] Example: Enter "I've been feeling stressed lately and it's bothering me."

[1325] 2. Terminal: Sends user responses to the server in real time.

[1326] Specific example: Immediately relaying user messages to the server.

[1327] 3. Server: Analyzes the received data and assesses the user's stress level and current health status.

[1328] Specific example: The server uses a natural language processing engine to analyze user messages for signs of stress.

[1329] Stress management and lifestyle suggestions

[1330] 1. Server: Based on the evaluation results, it generates customized stress management methods and lifestyle suggestions (e.g., relaxation exercises, dietary advice).

[1331] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[1332] 2. Terminal: Displays suggestions received from the server to the user.

[1333] Specific example: Present the proposal content as a chat screen or notification.

[1334] 3. User: Either implement the suggested method or ask further questions.

[1335] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[1336] Support provision and education

[1337] 1. Server: Provides information to deepen basic knowledge and understanding of diabetes, and also offers specific advice on how family and friends can support people with diabetes.

[1338] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[1339] 2. Device: Displays the provided information to the user, their family, and friends.

[1340] Specific example: Display educational content in text, video, or infographic format.

[1341] 3. User: Share the suggested ideas and receive support from family and friends.

[1342] Specific example: Use the share button within the app to share the provided information with family.

[1343] Example of implementation

[1344] 1. User: Enters "I am 170cm tall, weigh 70kg, and eat three meals a day."

[1345] 2. Terminal: Sends the entered information to the server.

[1346] 3. Server: Stores user information.

[1347] 4. User: Type "I've been feeling stressed lately and it's bothering me."

[1348] 5. Terminal: Sends a message to the server.

[1349] 6. Server: Analyze stress levels.

[1350] 7. Server: Generates a suggestion that says, "We recommend doing deep breathing exercises for 10 minutes every day."

[1351] 8. Terminal: Display the suggested content.

[1352] 9. User: "I will try the deep breathing exercises," provides feedback.

[1353] 10. Server: Save feedback.

[1354] 11. Server: Generates information that reads, "Basic knowledge about diabetes: Blood sugar management is important. Share this with your family and friends."

[1355] 12. Device: Displays educational information.

[1356] 13. User: Share information with family.

[1357] In this way, the present invention can provide diabetic patients and their families with effective stress management and healthy lifestyle suggestions, thereby improving the mental and physical health of patients.

[1358] The following describes the processing flow.

[1359] Step 1:

[1360] The user launches the application and enters basic information such as name, email address, password, height, weight, and blood sugar level on the new registration screen.

[1361] Step 2:

[1362] The terminal sends the entered information to the server.

[1363] Step 3:

[1364] The server saves the received information to the database.

[1365] Step 4:

[1366] The user accesses the in-app chat function and enters a message such as, "I've been under a lot of stress lately."

[1367] Step 5:

[1368] The device sends the user's message to the server.

[1369] Step 6:

[1370] The server analyzes the messages it receives and uses an artificial intelligence engine to evaluate the user's mental state.

[1371] Step 7:

[1372] Based on the evaluation results, the server generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle suggestions (e.g., dietary improvements, exercise recommendations).

[1373] Step 8:

[1374] The terminal displays the suggestions received from the server to the user.

[1375] Step 9:

[1376] The user reviews the proposal, decides whether to implement it, and if they decide to implement it, provides feedback such as "I'll give it a try."

[1377] Step 10:

[1378] The device sends user feedback to the server.

[1379] Step 11:

[1380] The server saves user feedback and uses it to improve future suggestions.

[1381] Step 12:

[1382] The server generates information on basic knowledge and support methods related to diabetes, and creates content for sharing with family and friends.

[1383] Step 13:

[1384] The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[1385] Step 14:

[1386] Users click the share button to share information with family and friends.

[1387] Step 15:

[1388] The device notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[1389] In this way, the overall processing flow of the system operates in concrete terms.

[1390] (Example 1)

[1391] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1392] There is a need for a system that improves the mental and physical health of diabetic patients and their families and friends by providing effective stress management and lifestyle suggestions. Furthermore, a system is needed to generate personalized suggestions for each patient and to continuously evaluate and improve their effectiveness.

[1393] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1394] In this invention, the server includes means for inputting and transmitting user health information; server means for storing transmitted health information; means for analyzing the user's mental state in response to user input; means for generating stress management methods and lifestyle suggestions based on the analysis results; terminal means for displaying the generated suggestions; means for collecting and storing user feedback; means for generating and providing information on basic knowledge and support methods regarding diabetes; means for creating an account and storing personal information; means for analyzing messages using a natural language processing engine; means for presenting customized suggestions and storing feedback for use in generating suggestions in the future; and means for generating educational information and providing it in text, video, and infographic formats. This enables the provision of individually customized suggestions and continuous support to diabetic patients and their families, thereby improving their mental and physical health.

[1395] "Means for inputting and transmitting user health information" refers to devices or applications that allow diabetic patients and their families to input information about their health status (e.g., blood glucose levels, weight, exercise habits) into a system and transmit it to a server.

[1396] "A server system for storing transmitted health information" refers to a central system for securely and efficiently storing health information transmitted by users.

[1397] "Means for analyzing a user's mental state in response to their input" refers to artificial intelligence engines and natural language processing technologies that analyze messages entered by users and evaluate their stress levels and mental state.

[1398] "Means for generating stress management methods and lifestyle suggestions based on analysis results" refers to a system component that automatically generates individually customized stress management methods and lifestyle improvement suggestions based on the results of an analysis of a person's mental state.

[1399] "Terminal means for displaying generated proposals" refers to a device (e.g., smartphone, tablet, PC) that displays the proposal content sent from the server to the user.

[1400] "Means for collecting and saving user feedback" refers to a system that collects feedback provided by users and saves that feedback for generating future suggestions.

[1401] "Means for generating and providing information on basic knowledge and support methods related to diabetes" refers to a system component that generates and provides users with educational knowledge and support methods related to diabetes.

[1402] "A means of creating an account and storing personal information" refers to a system that allows users to create an account and securely store their personal information.

[1403] "Means of analyzing messages using a natural language processing engine" refers to a system that utilizes natural language processing technology to analyze messages entered by users and understand their content.

[1404] "A means of presenting customized suggestions and saving feedback for use in generating future suggestions" refers to a system that presents individually customized suggestions to users and saves user feedback for use in generating future suggestions.

[1405] "Means for generating and providing educational information in text, video, and infographic formats" refers to a system that generates educational information about diabetes and provides it to users in text, video, and infographic formats.

[1406] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends.

[1407] System Configuration

[1408] The main components are as follows:

[1409] 1. User's device

[1410] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[1411] 2. Server

[1412] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[1413] 3. Artificial Intelligence Engine

[1414] A module that uses AI technologies for natural language processing and data analysis.

[1415] Operation details

[1416] Data collection and initial setup

[1417] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[1418] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[1419] 2. Terminal: Sends the provided information to the server.

[1420] Specific example: When the user confirms their input, the device sends the data to the server.

[1421] 3. Server: Saves the received data as the initial settings.

[1422] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[1423] User interaction

[1424] 1. User: Use the in-app chat function to enter questions or your current mental state.

[1425] Example: Enter "I've been feeling stressed lately and it's bothering me."

[1426] 2. Terminal: Sends user responses to the server in real time.

[1427] Specific example: Immediately relaying user messages to the server.

[1428] 3. Server: Analyzes the received data and assesses the user's stress level and current health status.

[1429] Specific example: The server uses a natural language processing engine to analyze user messages for signs of stress.

[1430] Example of technology used: Text analysis is performed using Python NLP libraries (e.g., SpaCy, NLTK).

[1431] Stress management and lifestyle suggestions

[1432] 1. Server: Based on the evaluation results, it generates customized stress management methods and lifestyle suggestions.

[1433] Example of a generative AI model: Generates proposal text using OpenAI's GPT-3 model.

[1434] Prompt example: "The user has reported feeling stressed recently. Please provide advice on deep breathing exercises and dietary improvements."

[1435] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[1436] 2. Terminal: Displays suggestions received from the server to the user.

[1437] Specific example: Present the proposal content as a chat screen or notification.

[1438] Feedback and support

[1439] 1. User: Either implement the suggested method or ask further questions.

[1440] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[1441] 2. Terminal: Sends user feedback to the server.

[1442] Specific example: Send the feedback content to the server immediately.

[1443] 3. Server: The server saves the feedback to a database and uses it to generate suggestions for the next time.

[1444] Specific example: Record user feedback to incorporate it into future analyses and suggestions.

[1445] Provision of educational information

[1446] 1. Server: Generates and provides users with basic knowledge and support methods regarding diabetes.

[1447] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[1448] 2. Terminal: Displays the provided information to the user.

[1449] Display format examples: Display educational content as text, video, and infographics.

[1450] 3. User: Share the suggested ideas and receive support from family and friends.

[1451] Specific example: Use the in-app share button to share the provided information with family.

[1452] This invention provides a system that allows users to evaluate their physical and mental state in real time and receive appropriate suggestions and support. By using this system, users can maintain healthier lifestyles and improve their diabetes management.

[1453] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1454] Step 1:

[1455] User: Install and launch the application. The user enters the required personal information (e.g., name, age, gender) on the account creation screen and creates an account.

[1456] Enter the following information: "Name: Taro Yamada", "Age: 45", "Gender: Male".

[1457] Output: Request to create an account and save personal information.

[1458] Step 2:

[1459] Terminal: Sends the entered personal information to the server.

[1460] Input: Personal information entered by the user.

[1461] Output: Data sent to the server.

[1462] Step 3:

[1463] Server: Stores received personal information in the database.

[1464] Input: Personal information sent from the device.

[1465] Output: Personal information stored in the database.

[1466] Step 4:

[1467] User: Enter your health information (e.g., blood sugar level, weight, exercise frequency) on the health information input screen.

[1468] Input: Enter "Blood glucose level: 110 mg / dL", "Weight: 70 kg", "Exercise frequency: 3 times a week".

[1469] Output: Health information entry complete.

[1470] Step 5:

[1471] Terminal: Sends health information to the server.

[1472] Input: Health information entered by the user.

[1473] Output: Data sent to the server.

[1474] Step 6:

[1475] Server: Receives health information and stores it in the database.

[1476] Input: Health information sent from the device.

[1477] Output: Health information stored in the database.

[1478] Step 7:

[1479] User: Use the chat function to enter your current mental state or questions.

[1480] Input: Type "I've been under a lot of stress lately and it's bothering me."

[1481] Output: Mental state input complete.

[1482] Step 8:

[1483] Terminal: Sends entered messages to the server in real time.

[1484] Input: Message from the user.

[1485] Output: Data sent to the server.

[1486] Step 9:

[1487] Server: Uses a natural language processing engine to analyze user input messages and assess stress levels.

[1488] Input: Message received from the user.

[1489] Data processing: Text analysis is performed using Python NLP libraries (e.g., SpaCy, NLTK).

[1490] Output: Evaluation results regarding stress levels.

[1491] Step 10:

[1492] Server: Generates customized stress management methods and lifestyle suggestions based on stress level assessments.

[1493] Input: Stress level assessment results.

[1494] Data processing: Generate proposal text using a generative AI model (e.g., OpenAI's GPT-3).

[1495] Prompt example: "The user has reported feeling stressed recently. Please provide advice on deep breathing exercises and dietary improvements."

[1496] Output: Customized proposal text.

[1497] Step 11:

[1498] Terminal: Displays the suggested text received from the server to the user.

[1499] Input: Proposal text sent from the server.

[1500] Output: The suggested text displayed to the user.

[1501] Specific example of action: The chat screen displays the message, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing your intake of whole grains in your diet."

[1502] Step 12:

[1503] User: Either implement the suggested method or enter further questions.

[1504] Input: Type "I will try the deep breathing exercise" and send feedback.

[1505] Output: Successfully submitted practice report and new questions.

[1506] Step 13:

[1507] Terminal: Sends user feedback to the server.

[1508] Input: User feedback.

[1509] Output: Data sent to the server.

[1510] Step 14:

[1511] Server: The feedback is saved to a database and used to generate suggestions for the next time.

[1512] Input: Feedback sent from the device.

[1513] Output: Feedback stored in the database.

[1514] Step 15:

[1515] Server: Generates and provides users with basic knowledge and support methods regarding diabetes.

[1516] Input: User's current health information and feedback.

[1517] Data processing: Generate educational content using natural language generation technology.

[1518] Output: Educational text about diabetes.

[1519] Step 16:

[1520] Terminal: Displays the provided information to the user.

[1521] Input: Educational message sent from the server.

[1522] Output: Displaying information on the screen.

[1523] Specific example of actions: Present educational content as text, video, and infographics.

[1524] Step 17:

[1525] User: Share the suggested information and receive support from family and friends.

[1526] Input: Share the provided information via the app's share button.

[1527] Output: Information sharing complete.

[1528] (Application Example 1)

[1529] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1530] Diabetic patients often face not only physical health management challenges but also mental stress management and financial burdens. However, there is no system in place to comprehensively manage these aspects and provide appropriate lifestyle and financial suggestions. Therefore, there is a need for systems and methods to alleviate the mental and financial stress of diabetic patients and promote healthy living.

[1531] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1532] In this invention, the server includes: means for inputting and transmitting the user's health and economic information; server means for storing and analyzing the transmitted information; means for analyzing the user's mental and economic state in response to user input; means for generating stress management methods, lifestyle habits, and economic suggestions based on the analysis results; terminal means for displaying the generated suggestions; means for collecting and storing user feedback; and means for generating and providing information on basic knowledge and support methods related to diabetes. This makes it possible for diabetic patients and their related parties to comprehensively manage their health, mental state, and economic state and receive appropriate suggestions.

[1533] "User health information" refers to physiological data such as height, weight, blood glucose levels, and meal frequency that diabetic patients record on a daily basis.

[1534] "Economic information" refers to economic data such as users' spending, budgets, and monthly expenses.

[1535] A "server" refers to a central control unit that stores transmitted data, performs analysis, and provides the results to users.

[1536] "Mental state" refers to information that represents the user's stress level and emotional health.

[1537] "Economic status" refers to information that represents the user's financial health and spending habits.

[1538] "Stress management methods" refer to methods and techniques for reducing the mental stress of users (e.g., deep breathing exercises and relaxation techniques).

[1539] "Lifestyle suggestions" refer to specific suggestions for improving the user's daily life (e.g., dietary advice or recommendations for exercise).

[1540] "Economic suggestions" refer to specific advice aimed at improving the user's financial situation (e.g., selecting cost-effective foods or recommending exercise plans).

[1541] A "terminal" refers to a device (e.g., a smartphone or tablet) that displays suggestions and information to the user and allows for data input and transmission.

[1542] "Feedback" refers to the evaluations and comments that users provide to the system.

[1543] "Basic knowledge about diabetes" refers to fundamental information regarding blood sugar management methods, diet, and exercise.

[1544] The system of the present invention is intended to provide integrated health management, mental stress management, and economic solutions to diabetic patients and their families. As an example of implementing the present invention, a specific system configuration and its operation are described below.

[1545] System Configuration

[1546] The main components of this system are as follows:

[1547] 1. User's device: A device (smartphone, tablet) used by the user to input health and financial information and receive suggestions.

[1548] 2. Server: A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[1549] 3. Artificial Intelligence Engine: A module that uses AI technologies for natural language processing and data analysis (e.g., TensorFlow).

[1550] Operation details

[1551] Data collection and initial setup

[1552] 1. User: Launch the application and enter the necessary personal information, health information, and financial information (e.g., blood sugar levels, weight, exercise habits, monthly expenses).

[1553] 2. Terminal: Sends the provided information to the server.

[1554] 3. Server: Saves the received data as the initial settings.

[1555] User interaction

[1556] 1. User: Use the in-app chat function to enter questions, current mental state, and financial status.

[1557] 2. Terminal: Sends user responses to the server in real time.

[1558] 3. Server: Analyzes received data to assess the user's stress level, current health status, and financial status.

[1559] Stress management, lifestyle, and economic suggestions

[1560] 1. Server: Based on the evaluation results, it generates customized stress management methods, lifestyle habits, and economic suggestions (e.g., relaxation exercises, dietary advice, recommendations for cost-effective health foods).

[1561] 2. Terminal: Displays suggestions received from the server to the user.

[1562] Support provision and education

[1563] 1. Server: Provides information to deepen basic knowledge and understanding of diabetes, and also offers specific advice on how family and friends can support people with diabetes.

[1564] 2. Device: Displays the provided information to the user, their family, and friends.

[1565] Hardware and software to be used

[1566] Frontend: Built using React Native. Provides a UI for collecting user-entered information and sending it to the server.

[1567] Backend: Built using Node.js and Express. It stores and parses incoming data and generates suggestions.

[1568] Database: MongoDB is used to store user health information, financial information, feedback, etc.

[1569] AI Engine: Uses TensorFlow for natural language processing and data analysis.

[1570] Specific example

[1571] Let's assume the user enters the following information.

[1572] Height: 170cm

[1573] Weight: 70kg

[1574] Blood glucose level: 140 mg / dL

[1575] Number of meals per day: 3

[1576] Monthly expenses: 60,000 yen

[1577] Based on this information, the server generates a suggestion that reads, "Your stress level is high. Try incorporating daily deep breathing exercises and a healthy diet. Your financial situation is also high, so review your balanced diet and exercise plan."

[1578] Example of a prompt

[1579] Question: The user has entered the following information. Please provide appropriate health and financial suggestions.

[1580] Height: 170cm

[1581] Weight: 70kg

[1582] Blood glucose level: 140 mg / dL

[1583] Number of meals per day: 3

[1584] Monthly expenses: 60,000 yen

[1585] Answer: Your stress levels are high. Focus on daily deep breathing exercises and a healthy diet. Your financial situation is also high, so review your balanced diet and exercise plan.

[1586] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1587] Step 1:

[1588] Data entry (health information and economic information)

[1589] The user launches the application and enters information such as height, weight, blood sugar level, number of meals per day, and monthly expenses.

[1590] Input: Height, weight, blood sugar level, number of meals, expenses

[1591] Output: Data in JSON format (Example: { "height": 170, "weight": 70, "glucose": 140, "mealsPerDay": 3, "expenses": 60000})

[1592] Step 2:

[1593] Data transmission

[1594] The terminal sends the data entered by the user to the server.

[1595] Input: User data in JSON format

[1596] Output: Data sent to the server

[1597] Step 3:

[1598] Data storage

[1599] The server saves the received data to a database (MongoDB).

[1600] Input: Received data (JSON format)

[1601] Output: Records stored in the database

[1602] Step 4:

[1603] Data Analysis

[1604] The server uses a natural language processing engine (TensorFlow) to analyze the user's mental and economic state.

[1605] Input: User information retrieved from the database

[1606] Data processing: Stress levels are calculated based on blood glucose levels, meal frequency, etc., and economic status is evaluated based on monthly expenses.

[1607] Output: Assessment of stress level and economic status (e.g., { "stressLevel": "High", "economicStatus": "High"})

[1608] Step 5:

[1609] Proposal generation

[1610] Based on the analysis results, the server generates stress management methods, lifestyle suggestions, and economic advice.

[1611] Input: Stress level, assessment of economic status

[1612] Data processing: The program generates exercise and dietary advice for stress reduction, as well as specific suggestions for improving financial conditions.

[1613] Output: Suggestions (e.g., deep breathing exercises, healthy eating, recommendations for cost-effective foods)

[1614] Step 6:

[1615] Suggestion display

[1616] The terminal displays suggestions received from the server to the user.

[1617] Input: Proposal (string in JSON format)

[1618] Output: Suggestions displayed on the device's UI

[1619] Step 7:

[1620] Feedback Collection

[1621] Users provide feedback on suggestions within the application.

[1622] Input: Feedback (e.g., "I tried the deep breathing exercises")

[1623] Output: Feedback data in JSON format

[1624] Step 8:

[1625] Send and save feedback

[1626] The device sends the collected feedback to the server, which then stores it in a database.

[1627] Input: User feedback data

[1628] Output: Feedback stored in the database

[1629] Step 9:

[1630] Support information provided

[1631] The server generates information on basic knowledge and support methods related to diabetes and provides it to users and their related parties.

[1632] Input: None (Information generated periodically)

[1633] Output: Educational content (e.g., text, video, infographics)

[1634] Step 10:

[1635] Support information display

[1636] The device displays educational content received from the server to the user.

[1637] Input: Data from educational content

[1638] Output: Educational content displayed on the device's UI

[1639] Through these steps, this system enables diabetic patients and their families to comprehensively manage their health, mental state, and financial situation, and to receive appropriate suggestions.

[1640] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1641] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends, and further incorporates an emotion engine to recognize the user's emotions and reflect them in the analysis results.

[1642] System Configuration

[1643] The main components are as follows:

[1644] 1. User's device

[1645] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[1646] 2. Server

[1647] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[1648] 3. Artificial Intelligence Engine

[1649] A module that uses AI technologies for natural language processing and data analysis. It integrates an emotion engine and has the ability to analyze the user's emotions from input data.

[1650] 4. Emotional Engine

[1651] A module that recognizes emotions based on user input and incorporates them into the assessment of mental state.

[1652] Operation details

[1653] Data collection and initial setup

[1654] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[1655] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[1656] 2. Terminal: Sends the provided information to the server.

[1657] Specific example: When the user confirms their input, the device sends the data to the server.

[1658] 3. Server: Saves the received data as the initial settings.

[1659] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[1660] User interaction

[1661] 1. User: Use the in-app chat function to enter questions or your current mental state.

[1662] Example: Enter "I've been feeling stressed lately and it's bothering me."

[1663] 2. Terminal: Sends user responses to the server in real time.

[1664] Specific example: Immediately relaying user messages to the server.

[1665] 3. Server: Analyzes the received data, uses the emotion engine to recognize the user's emotions, and evaluates their overall mental state.

[1666] Specific example: The server uses an emotion engine to analyze the user's message and recognize emotions such as "lonely."

[1667] Stress management and lifestyle suggestions

[1668] 1. Server: Based on the emotion analysis results, it generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle suggestions (e.g., dietary improvements, exercise recommendations).

[1669] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[1670] 2. Terminal: Displays the suggestions received from the server to the user.

[1671] Specific example: Present the proposal content as a chat screen or notification.

[1672] 3. User: Decide whether or not to implement the suggested method, and if so, provide feedback such as "I will try it."

[1673] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[1674] 4. Terminal: Sends user feedback to the server.

[1675] Specific example: Send the feedback content to the server.

[1676] 5. Server: Save user feedback and use it to improve future suggestions.

[1677] Specific example: Store feedback in a database and use it for individual suggestions.

[1678] Support provision and education

[1679] 1. Server: Generates information on basic knowledge and support methods regarding diabetes, and creates content for sharing with family and friends.

[1680] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[1681] 2. Device: Display educational information to the user and provide options (e.g., a share button) for sharing with family and friends.

[1682] Specific example: Display educational content in text, video, or infographic format.

[1683] 3. User: Click the share button to share the provided information with family and friends.

[1684] Specific example: Click the share button to send the provided information to family members via email.

[1685] 4. Terminal: Notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[1686] Specific example: An email sent to a family member contains educational information.

[1687] In this way, by combining the emotional engine, the present invention can provide diabetic patients and their families with more detailed and personalized stress management and healthy lifestyle suggestions, thereby improving the mental and physical health of users.

[1688] The following describes the processing flow.

[1689] Step 1:

[1690] The user launches the application and enters basic information such as name, email address, password, height, weight, and blood sugar level on the new registration screen.

[1691] Step 2:

[1692] The terminal sends the entered information to the server.

[1693] Step 3:

[1694] The server saves the received information to the database.

[1695] Step 4:

[1696] The user accesses the in-app chat function and enters their feelings or mental state, such as "I've been feeling stressed lately."

[1697] Step 5:

[1698] The device sends the user's message to the server.

[1699] Step 6:

[1700] The server uses an emotion engine to analyze the user's message to determine their emotions. For example, it might extract emotions like "stress" and "worry" from the user's input, "I've been feeling stressed lately and it's really bothering me."

[1701] Step 7:

[1702] The server evaluates the mental state based on the results of the emotion analysis and determines the stress level.

[1703] Step 8:

[1704] Based on the emotion analysis results, the server generates personalized stress management methods (e.g., deep breathing exercises, meditation) and lifestyle suggestions (e.g., balanced diet, regular exercise).

[1705] Step 9:

[1706] The terminal displays suggestions received from the server to the user. For example, "We recommend doing deep breathing exercises for 10 minutes every day."

[1707] Step 10:

[1708] The user reviews the proposal and decides whether to implement it. If they decide to implement it, they provide feedback such as "I'll give it a try."

[1709] Step 11:

[1710] The device sends user feedback to the server.

[1711] Step 12:

[1712] The server saves user feedback and uses it to improve future suggestions. It also evaluates the effectiveness of suggestions based on the feedback.

[1713] Step 13:

[1714] The server generates information on basic knowledge and support methods related to diabetes, and creates content for sharing with family and friends.

[1715] Step 14:

[1716] The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[1717] Step 15:

[1718] Users click the share button to share information with family and friends.

[1719] Step 16:

[1720] The device notifies the server of the sharing action.

[1721] Step 17:

[1722] The server sends information using the selected sharing method (e.g., email, social media). For example, it might send an email containing educational information to a family member.

[1723] In this way, the overall processing flow of the system operates in concrete terms.

[1724] (Example 2)

[1725] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1726] To provide effective mental stress management and lifestyle improvement suggestions to diabetic patients and their families and friends, it is necessary to accurately analyze the health and mental state of each individual user and generate customized suggestions. However, conventional systems have faced challenges in providing individually tailored suggestions due to insufficient emotional analysis and detailed feedback collection.

[1727] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1728] In this invention, the server includes means for users to input and transmit personal information and health-related information; means for storing the transmitted information and recording it in a database; means for using an artificial intelligence module to analyze the user's input data; means for customizing and generating stress management methods and lifestyle suggestions based on the input data and analysis results; terminal device means for presenting the generated suggestions to the user; means for collecting, analyzing, and storing user feedback; and means for generating and providing health-related educational and support information. This makes it possible to provide customized suggestions in real time based on each user's individual health and mental state.

[1729] "User" refers to an individual who uses the system to manage and receive suggestions regarding their health information and mental state.

[1730] "Personal information" refers to basic data used to identify a user, such as name, age, and gender.

[1731] "Health-related information" refers to data that indicates the user's health status, such as blood glucose levels, weight, and exercise habits.

[1732] A "server" refers to a central computing system that stores data, performs analysis, and generates proposals.

[1733] A "sentiment analysis engine" refers to a technology module that recognizes and analyzes a user's emotions from input text and data.

[1734] An "artificial intelligence module" refers to a program that uses AI technology to perform data analysis and proposal generation.

[1735] "Stress management" refers to methods and techniques for improving mental health.

[1736] "Lifestyle suggestions" refer to suggestions that indicate recommended actions and habits for maintaining or improving health.

[1737] "Feedback" refers to suggestions, reactions, and opinions on services collected from users.

[1738] "Educational information" refers to data that provides users, their families, and friends with knowledge and support methods regarding diabetes.

[1739] "Shareable" refers to a feature that allows users to share information with other people.

[1740] This invention is a system that uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends. This system incorporates an emotion engine to recognize the user's emotions and reflect them in the analysis results.

[1741] System Configuration

[1742] The main components are as follows:

[1743] 1. User's device

[1744] These are devices that allow users to input health information and receive suggestions. Examples include smartphones, tablets, and PCs.

[1745] 2. Server

[1746] This is a central system that stores, analyzes, and generates suggestions based on data submitted by users.

[1747] 3. Artificial Intelligence Module

[1748] This program uses AI technologies for natural language processing and data analysis. It integrates an emotion analysis engine to analyze the user's emotions from the input data.

[1749] 4. Emotion Analysis Engine

[1750] This is a technology module for recognizing emotions based on user input and incorporating them into the assessment of mental state.

[1751] Operation details

[1752] The system works as follows:

[1753] Data collection and initial setup

[1754] 1. The user launches the application and enters necessary personal and health information (e.g., blood sugar level, weight, exercise habits). For example, they might enter, "Height 170cm, weight 70kg, blood sugar level 110mg / dL, I eat 3 meals a day."

[1755] 2. The terminal sends the provided information to the server. Once the user confirms the input, the terminal sends the data to the server.

[1756] 3. The server saves the received data as initial settings. Specifically, the server records the user's basic health information in a database and uses it as initial settings.

[1757] User interaction

[1758] 1. Users use the chat function to enter questions or their current mental state. For example, they might type, "I've been feeling stressed lately and it's bothering me."

[1759] 2. The terminal sends user responses to the server in real time.

[1760] 3. The server analyzes the received data, uses an emotion analysis engine to recognize the user's emotions, and evaluates their overall mental state. For example, the server uses the emotion analysis engine to analyze "stress" from the user's message.

[1761] Stress management and lifestyle suggestions

[1762] 1. Based on the emotion analysis results, the server generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle recommendations. For example, it might generate, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing your intake of whole grains in your diet."

[1763] 2. The terminal displays the suggestions received from the server to the user.

[1764] 3. The user decides whether or not to implement the suggested method, and if so, provides feedback such as "I'll try it."

[1765] 4. The device sends user feedback to the server.

[1766] 5. The server saves user feedback and uses it to improve future suggestions.

[1767] Support provision and education

[1768] 1. The server generates information on basic knowledge and support methods regarding diabetes, and creates content for sharing with family and friends. For example, it might generate information such as, "Managing blood sugar levels is important for diabetes. By helping family and friends understand this, you can get support with diet management and exercise."

[1769] 2. The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[1770] 3. The user clicks the share button to share the provided information with family and friends.

[1771] 4. The device notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[1772] This allows the system, which combines an emotion analysis engine and an artificial intelligence module, to provide personalized stress management and healthy lifestyle suggestions to diabetic patients and their families, thereby improving the users' mental and physical health.

[1773] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1774] Step 1:

[1775] User: Launches the application and enters personal and health-related information (e.g., height, weight, blood sugar level, exercise habits). The entered information (input data) is sent to the terminal.

[1776] Input: Personal information, health-related information

[1777] Output: Input data sent to the terminal

[1778] Specific actions: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, I eat 3 meals a day" into the app's form and press the confirm button.

[1779] Step 2:

[1780] Terminal: Sends user-entered data to the server.

[1781] Input: Data entered by the user

[1782] Output: Data to send to the server

[1783] Specific action: When the confirmation button is pressed, the device sends the data to the server via the internet.

[1784] Step 3:

[1785] Server: Saves the transmitted data to the database and records it as initial settings.

[1786] Input: Data sent from the device

[1787] Output: User data stored in the database

[1788] Specific operation: The server receives data, records it in the database, and creates a profile for each user.

[1789] Step 4:

[1790] User: Use the chat function to enter your current mental state or questions.

[1791] Input: Text of mental state or question

[1792] Output: Input data sent to the terminal

[1793] Specific action: Type "I've been feeling stressed lately" into the chat window and press the send button.

[1794] Step 5:

[1795] Terminal: Sends user messages to the server in real time.

[1796] Input: User input message

[1797] Output: Message sent to the server

[1798] Specific operation: The message is transferred to the server the moment the send button is pressed.

[1799] Step 6:

[1800] Server: Analyzes received messages using an emotion analysis engine and evaluates the emotional state.

[1801] Input: Message sent by the user

[1802] Data processing: The sentiment analysis engine analyzes the message content.

[1803] Output: Emotional state (e.g., "stress")

[1804] Specific operation: The server uses an emotion analysis engine to analyze "stress" from the input "high stress level" and records it as an emotional state.

[1805] Step 7:

[1806] Server: Based on the emotion analysis results, it generates customized stress management methods and lifestyle suggestions.

[1807] Input: Sentiment analysis results

[1808] Data processing: Generative AI model generates suggestions.

[1809] Output: Proposed content (Example: "Perform deep breathing exercises for 10 minutes every day")

[1810] Specific operation: The server prompts the AI ​​model with "suggestions based on the user's sentiment analysis results" and generates suggestions.

[1811] Step 8:

[1812] Terminal: Displays the suggestions received from the server to the user.

[1813] Input: Suggestions from the server

[1814] Output: Suggestions displayed to the user

[1815] Specific action: Use the application's notification function to display the suggested content as a pop-up on the screen.

[1816] Step 9:

[1817] User: Decide whether to implement the suggestion and provide feedback.

[1818] Input: User feedback

[1819] Output: Feedback sent to the device

[1820] Specific action: Send feedback saying "I'll try the deep breathing exercise" and press the submit button.

[1821] Step 10:

[1822] Terminal: Sends user feedback to the server.

[1823] Input: User feedback

[1824] Output: Feedback sent to the server

[1825] Specific action: The feedback content is sent directly to the server.

[1826] Step 11:

[1827] Server: Saves user feedback to a database and uses it to improve future suggestions.

[1828] Input: User feedback

[1829] Output: Feedback stored in the database

[1830] Specific operation: The feedback is saved to a database and referenced when generating suggestions in the future.

[1831] Step 12:

[1832] Server: Generates basic knowledge and support information about diabetes, and creates content for sharing with family and friends.

[1833] Input: Health-related information stored on the server

[1834] Data processing: Generative AI model generates educational information.

[1835] Output: Health education content (e.g., "Key Points for Diabetes Management")

[1836] Specific operation: The server prompts the AI ​​model to generate "educational information on diabetes management" and generates the content.

[1837] Step 13:

[1838] Terminal: Displays generated educational information to the user and provides the option to share it with family and friends.

[1839] Input: Educational information from the server

[1840] Output: Educational content and sharing options displayed to the user

[1841] Specific actions: Display educational content in text or video format and include a share button.

[1842] Step 14:

[1843] User: Click the share button to share the provided information with family and friends.

[1844] Input: Share Action

[1845] Output: Instructions for sharing information

[1846] Specific actions: Click the share button and select the sharing method (e.g., email, social media).

[1847] Step 15:

[1848] Terminal: Notifies the server of the sharing action, and the server sends the information using the selected sharing method.

[1849] Input: Shared Action Notification

[1850] Output: Information sent to family and friends

[1851] Specific operation: A share action trigger is sent to the server, and the information is shared in the selected manner.

[1852] (Application Example 2)

[1853] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1854] A system is needed to monitor the mental stress and health status of passengers in autonomous vehicles in real time and to provide appropriate stress management and lifestyle suggestions. Conventional systems have been unable to adequately monitor the mental and health status of passengers, which is crucial for maintaining safe driving, and have been unable to take appropriate action.

[1855] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using a biosensor to monitor health status, means for using a camera to analyze emotions, and means for evaluating the passenger's mental state based on data from the camera and biosensor. This makes it possible to monitor the stress level and health status of passengers in an autonomous vehicle in real time and to immediately provide appropriate stress management and lifestyle suggestions.

[1856] "Means for inputting and transmitting health information" refers to a device that allows users to input their own health data (e.g., blood sugar levels, heart rate, weight, etc.) and transmit that information to a server within the system.

[1857] A "server system for storing transmitted health information" refers to a central system for receiving health information transmitted by users and securely storing it in a database.

[1858] "Means for analyzing mental state" refers to devices or software that analyze user input or data from biosensors to evaluate the user's emotions and mental state.

[1859] "Means for generating stress management methods and lifestyle suggestions" refers to a device or software that generates stress management methods and lifestyle improvement suggestions suitable for the user based on analyzed information about the user's mental state.

[1860] "Display device for displaying generated suggestions" refers to a device for visually presenting to the user stress management and lifestyle habit suggestions generated by the system.

[1861] "Means for collecting and storing user feedback" refers to a device or software for collecting feedback on suggestions made by users and storing that information in a database within the system.

[1862] "Methods using biosensors to monitor health status" refer to devices that collect physiological data from users in real time, such as heart rate and skin electrical responses.

[1863] "Methods using cameras to analyze emotions" refer to imaging devices that detect the user's facial expressions and posture and evaluate their emotions based on that information.

[1864] "Means for evaluating passengers' mental state based on data from cameras and biosensors" refers to a device or software that analyzes data collected from cameras and biosensors to comprehensively evaluate the mental state of users.

[1865] "Means of suggesting relaxation music or exercises while driving" refers to a device or software that suggests music or exercise methods with relaxation effects based on the user's mental state.

[1866] "Means for generating and providing information on basic knowledge and support methods regarding diabetes" refers to devices or software that generate and provide information to help users and their families understand and appropriately manage diabetes.

[1867] This invention provides a system that monitors the mental stress and health status of passengers in autonomous vehicles in real time and offers appropriate stress management and lifestyle suggestions. The specific system configuration and its operation are described below.

[1868] System Configuration

[1869] The system consists of the following main components:

[1870] 1. User's equipment

[1871] A device (e.g., smartphone, tablet) for entering health information and receiving suggestions.

[1872] 2. Sensor devices

[1873] A heart rate sensor that measures heart rate (e.g., Polar H9).

[1874] A skin electromechanist (e.g., Empatica E4) that measures the electrical response of the skin.

[1875] 3. Camera device

[1876] A camera used to capture facial expressions and analyze emotions (e.g., a camera built into a vehicle).

[1877] 4. Server

[1878] A central system that stores and analyzes health information and emotional data, and generates recommendations.

[1879] 5. Artificial Intelligence Engine

[1880] A module that uses AI technologies for natural language processing and data analysis. It integrates an emotion engine and has the ability to analyze the user's emotions from input data.

[1881] 6. Display Device

[1882] A device for displaying generated suggestions.

[1883] Operation details

[1884] 1. Data Collection

[1885] The user's device inputs health information (e.g., blood glucose levels, weight, exercise habits) and sends it to the server.

[1886] The system collects heart rate and skin electrical response data in real time from sensor devices and captures passenger facial expression data from camera devices.

[1887] 2. Data Analysis and Evaluation

[1888] The server receives and stores transmitted health information, heart rate data from biosensors, and skin electrical response data.

[1889] The system analyzes facial expression data from camera devices and uses an emotion engine to evaluate the emotional state of passengers.

[1890] 3. Proposal generation

[1891] The server uses an AI engine to generate stress management methods and lifestyle suggestions based on health information, heart rate, skin electrical responses, and emotional data.

[1892] Specific examples include "recommending the playback of relaxation music" and "suggesting deep breathing exercises."

[1893] 4. Proposal display and feedback collection

[1894] The generated suggestions are presented to the user through a display device.

[1895] Users provide feedback on the suggestions and send that feedback information to the server.

[1896] The server receives feedback information and incorporates it into the next proposal generation.

[1897] Specific example

[1898] Example prompt message: When your heart rate is high and emotion analysis identifies you as "anxious".

[1899] Prompt message: Heart rate 95, skin electrical response 0.75, anxiety

[1900] This system will enable real-time monitoring of passengers' stress levels and health status in autonomous vehicles, and will immediately provide appropriate stress management and lifestyle suggestions.

[1901] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1902] Step 1:

[1903] The user inputs health information. Specifically, the user uses an input device such as a smartphone to enter health information such as blood glucose levels, weight, and exercise habits into the application. The entered data is sent to the server by the device. The input consists of numerical data such as blood glucose levels and weight, which is then sent to the server.

[1904] Step 2:

[1905] The server receives the transmitted health information and stores it in the database. The server receives the user's health information and records it in the database. The health information is stored accurately because it will be used for subsequent analysis. At this stage, the input is the health information from the user, and the output is the health information stored in the database.

[1906] Step 3:

[1907] Real-time data collection begins using sensor devices (heart rate sensor and electrodermal meter) and a camera device. The terminal collects heart rate and electrodermal response data from the heart rate sensor and electrodermal meter, and captures the passenger's facial expressions with the camera device. The inputs collected are heart rate, electrodermal response, and facial expression data, which are then sent to the server.

[1908] Step 4:

[1909] The server receives and stores the collected biosensor data and camera device data. The received data is recorded in a database. The input is biometric data from the sensor device and camera device, and the output is the stored biometric data.

[1910] Step 5:

[1911] The server analyzes facial expression data from the camera device and uses an artificial intelligence engine to evaluate emotional states. Specifically, the collected facial expression data is processed as images and input into an emotion recognition model. The AI ​​engine analyzes the emotional state and identifies emotions such as "anxiety" or "loneliness." The input is facial expression data, and the output is the result of the emotion analysis.

[1912] Step 6:

[1913] The server uses a generative AI model to generate stress management methods and lifestyle suggestions based on stored health information, biosensor data, and emotional states. The AI ​​engine comprehensively analyzes multiple data points to generate suggestions tailored to the user. Specific examples include "Play relaxation music" and "Perform deep breathing exercises." Inputs are health information, biosensor data, and emotional analysis results, while output is the suggested content.

[1914] Step 7:

[1915] The server sends the generated suggestions to the terminal. The terminal displays the received suggestions on a display device, visually presenting them to the user. As output, the user can then review the suggestions.

[1916] Step 8:

[1917] The user decides whether to implement the suggested method and enters feedback. If the user implements the suggested method, they enter feedback such as "I tried it" or "It was effective" into the terminal. This input is the feedback content and is sent to the server.

[1918] Step 9:

[1919] The server receives user feedback and stores it in a database. This feedback information is used to generate suggestions for future updates. The input is user feedback, and the output is the stored feedback information.

[1920] This allows the system to monitor the user's health and mental state in real time and provide appropriate stress management and lifestyle suggestions.

[1921] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1922] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1923] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1924] [Fourth Embodiment]

[1925] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1926] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1927] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1928] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1929] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1930] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1931] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1932] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1933] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1934] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1935] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1936] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1937] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1938] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends.

[1939] System Configuration

[1940] The main components are as follows:

[1941] 1. User's device

[1942] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[1943] 2. Server

[1944] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[1945] 3. Artificial Intelligence Engine

[1946] A module that uses AI technologies for natural language processing and data analysis.

[1947] Operation details

[1948] Data collection and initial setup

[1949] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[1950] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[1951] 2. Terminal: Sends the provided information to the server.

[1952] Specific example: When the user confirms their input, the device sends the data to the server.

[1953] 3. Server: Saves the received data as the initial settings.

[1954] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[1955] User interaction

[1956] 1. User: Use the in-app chat function to enter questions or your current mental state.

[1957] Example: Enter "I've been feeling stressed lately and it's bothering me."

[1958] 2. Terminal: Sends user responses to the server in real time.

[1959] Specific example: Immediately relaying user messages to the server.

[1960] 3. Server: Analyzes the received data and assesses the user's stress level and current health status.

[1961] Specific example: The server uses a natural language processing engine to analyze user messages for signs of stress.

[1962] Stress management and lifestyle suggestions

[1963] 1. Server: Based on the evaluation results, it generates customized stress management methods and lifestyle suggestions (e.g., relaxation exercises, dietary advice).

[1964] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[1965] 2. Terminal: Displays suggestions received from the server to the user.

[1966] Specific example: Present the proposal content as a chat screen or notification.

[1967] 3. User: Either implement the suggested method or ask further questions.

[1968] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[1969] Support provision and education

[1970] 1. Server: Provides information to deepen basic knowledge and understanding of diabetes, and also offers specific advice on how family and friends can support people with diabetes.

[1971] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[1972] 2. Device: Displays the provided information to the user, their family, and friends.

[1973] Specific example: Display educational content in text, video, or infographic format.

[1974] 3. User: Share the suggested ideas and receive support from family and friends.

[1975] Specific example: Use the share button within the app to share the provided information with family.

[1976] Example of implementation

[1977] 1. User: Enters "I am 170cm tall, weigh 70kg, and eat three meals a day."

[1978] 2. Terminal: Sends the entered information to the server.

[1979] 3. Server: Stores user information.

[1980] 4. User: Type "I've been feeling stressed lately and it's bothering me."

[1981] 5. Terminal: Sends a message to the server.

[1982] 6. Server: Analyze stress levels.

[1983] 7. Server: Generates a suggestion that says, "We recommend doing deep breathing exercises for 10 minutes every day."

[1984] 8. Terminal: Display the suggested content.

[1985] 9. User: "I will try the deep breathing exercises," provides feedback.

[1986] 10. Server: Save feedback.

[1987] 11. Server: Generates information that reads, "Basic knowledge about diabetes: Blood sugar management is important. Share this with your family and friends."

[1988] 12. Device: Displays educational information.

[1989] 13. User: Share information with family.

[1990] In this way, the present invention can provide diabetic patients and their families with effective stress management and healthy lifestyle suggestions, thereby improving the mental and physical health of patients.

[1991] The following describes the processing flow.

[1992] Step 1:

[1993] The user launches the application and enters basic information such as name, email address, password, height, weight, and blood sugar level on the new registration screen.

[1994] Step 2:

[1995] The terminal sends the entered information to the server.

[1996] Step 3:

[1997] The server saves the received information to the database.

[1998] Step 4:

[1999] The user accesses the in-app chat function and enters a message such as, "I've been under a lot of stress lately."

[2000] Step 5:

[2001] The device sends the user's message to the server.

[2002] Step 6:

[2003] The server analyzes the messages it receives and uses an artificial intelligence engine to evaluate the user's mental state.

[2004] Step 7:

[2005] Based on the evaluation results, the server generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle suggestions (e.g., dietary improvements, exercise recommendations).

[2006] Step 8:

[2007] The terminal displays the suggestions received from the server to the user.

[2008] Step 9:

[2009] The user reviews the proposal, decides whether to implement it, and if they decide to implement it, provides feedback such as "I'll give it a try."

[2010] Step 10:

[2011] The device sends user feedback to the server.

[2012] Step 11:

[2013] The server saves user feedback and uses it to improve future suggestions.

[2014] Step 12:

[2015] The server generates information on basic knowledge and support methods related to diabetes, and creates content for sharing with family and friends.

[2016] Step 13:

[2017] The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[2018] Step 14:

[2019] Users click the share button to share information with family and friends.

[2020] Step 15:

[2021] The device notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[2022] In this way, the overall processing flow of the system operates in concrete terms.

[2023] (Example 1)

[2024] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2025] There is a need for a system that improves the mental and physical health of diabetic patients and their families and friends by providing effective stress management and lifestyle suggestions. Furthermore, a system is needed to generate personalized suggestions for each patient and to continuously evaluate and improve their effectiveness.

[2026] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[2027] In this invention, the server includes means for inputting and transmitting user health information; server means for storing transmitted health information; means for analyzing the user's mental state in response to user input; means for generating stress management methods and lifestyle suggestions based on the analysis results; terminal means for displaying the generated suggestions; means for collecting and storing user feedback; means for generating and providing information on basic knowledge and support methods regarding diabetes; means for creating an account and storing personal information; means for analyzing messages using a natural language processing engine; means for presenting customized suggestions and storing feedback for use in generating suggestions in the future; and means for generating educational information and providing it in text, video, and infographic formats. This enables the provision of individually customized suggestions and continuous support to diabetic patients and their families, thereby improving their mental and physical health.

[2028] "Means for inputting and transmitting user health information" refers to devices or applications that allow diabetic patients and their families to input information about their health status (e.g., blood glucose levels, weight, exercise habits) into a system and transmit it to a server.

[2029] "A server system for storing transmitted health information" refers to a central system for securely and efficiently storing health information transmitted by users.

[2030] "Means for analyzing a user's mental state in response to their input" refers to artificial intelligence engines and natural language processing technologies that analyze messages entered by users and evaluate their stress levels and mental state.

[2031] "Means for generating stress management methods and lifestyle suggestions based on analysis results" refers to a system component that automatically generates individually customized stress management methods and lifestyle improvement suggestions based on the results of an analysis of a person's mental state.

[2032] "Terminal means for displaying generated proposals" refers to a device (e.g., smartphone, tablet, PC) that displays the proposal content sent from the server to the user.

[2033] "Means for collecting and saving user feedback" refers to a system that collects feedback provided by users and saves that feedback for generating future suggestions.

[2034] "Means for generating and providing information on basic knowledge and support methods related to diabetes" refers to a system component that generates and provides users with educational knowledge and support methods related to diabetes.

[2035] "A means of creating an account and storing personal information" refers to a system that allows users to create an account and securely store their personal information.

[2036] "Means of analyzing messages using a natural language processing engine" refers to a system that utilizes natural language processing technology to analyze messages entered by users and understand their content.

[2037] "A means of presenting customized suggestions and saving feedback for use in generating future suggestions" refers to a system that presents individually customized suggestions to users and saves user feedback for use in generating future suggestions.

[2038] "Means for generating and providing educational information in text, video, and infographic formats" refers to a system that generates educational information about diabetes and provides it to users in text, video, and infographic formats.

[2039] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends.

[2040] System Configuration

[2041] The main components are as follows:

[2042] 1. User's device

[2043] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[2044] 2. Server

[2045] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[2046] 3. Artificial Intelligence Engine

[2047] A module that uses AI technologies for natural language processing and data analysis.

[2048] Operation details

[2049] Data collection and initial setup

[2050] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[2051] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[2052] 2. Terminal: Sends the provided information to the server.

[2053] Specific example: When the user confirms their input, the device sends the data to the server.

[2054] 3. Server: Saves the received data as the initial settings.

[2055] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[2056] User interaction

[2057] 1. User: Use the in-app chat function to enter questions or your current mental state.

[2058] Example: Enter "I've been feeling stressed lately and it's bothering me."

[2059] 2. Terminal: Sends user responses to the server in real time.

[2060] Specific example: Immediately relaying user messages to the server.

[2061] 3. Server: Analyzes the received data and assesses the user's stress level and current health status.

[2062] Specific example: The server uses a natural language processing engine to analyze user messages for signs of stress.

[2063] Example of technology used: Text analysis is performed using Python NLP libraries (e.g., SpaCy, NLTK).

[2064] Stress management and lifestyle suggestions

[2065] 1. Server: Based on the evaluation results, it generates customized stress management methods and lifestyle suggestions.

[2066] Example of a generative AI model: Generates proposal text using OpenAI's GPT-3 model.

[2067] Prompt example: "The user has reported feeling stressed recently. Please provide advice on deep breathing exercises and dietary improvements."

[2068] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[2069] 2. Terminal: Displays suggestions received from the server to the user.

[2070] Specific example: Present the proposal content as a chat screen or notification.

[2071] Feedback and support

[2072] 1. User: Either implement the suggested method or ask further questions.

[2073] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[2074] 2. Terminal: Sends user feedback to the server.

[2075] Specific example: Send the feedback content to the server immediately.

[2076] 3. Server: The server saves the feedback to a database and uses it to generate suggestions for the next time.

[2077] Specific example: Record user feedback to incorporate it into future analyses and suggestions.

[2078] Provision of educational information

[2079] 1. Server: Generates and provides users with basic knowledge and support methods regarding diabetes.

[2080] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[2081] 2. Terminal: Displays the provided information to the user.

[2082] Display format examples: Display educational content as text, video, and infographics.

[2083] 3. User: Share the suggested ideas and receive support from family and friends.

[2084] Specific example: Use the in-app share button to share the provided information with family.

[2085] This invention provides a system that allows users to evaluate their physical and mental state in real time and receive appropriate suggestions and support. By using this system, users can maintain healthier lifestyles and improve their diabetes management.

[2086] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2087] Step 1:

[2088] User: Install and launch the application. The user enters the required personal information (e.g., name, age, gender) on the account creation screen and creates an account.

[2089] Enter the following information: "Name: Taro Yamada", "Age: 45", "Gender: Male".

[2090] Output: Request to create an account and save personal information.

[2091] Step 2:

[2092] Terminal: Sends the entered personal information to the server.

[2093] Input: Personal information entered by the user.

[2094] Output: Data sent to the server.

[2095] Step 3:

[2096] Server: Stores received personal information in the database.

[2097] Input: Personal information sent from the device.

[2098] Output: Personal information stored in the database.

[2099] Step 4:

[2100] User: Enter your health information (e.g., blood sugar level, weight, exercise frequency) on the health information input screen.

[2101] Input: Enter "Blood glucose level: 110 mg / dL", "Weight: 70 kg", "Exercise frequency: 3 times a week".

[2102] Output: Health information entry complete.

[2103] Step 5:

[2104] Terminal: Sends health information to the server.

[2105] Input: Health information entered by the user.

[2106] Output: Data sent to the server.

[2107] Step 6:

[2108] Server: Receives health information and stores it in the database.

[2109] Input: Health information sent from the device.

[2110] Output: Health information stored in the database.

[2111] Step 7:

[2112] User: Use the chat function to enter your current mental state or questions.

[2113] Input: Type "I've been under a lot of stress lately and it's bothering me."

[2114] Output: Mental state input complete.

[2115] Step 8:

[2116] Terminal: Sends entered messages to the server in real time.

[2117] Input: Message from the user.

[2118] Output: Data sent to the server.

[2119] Step 9:

[2120] Server: Uses a natural language processing engine to analyze user input messages and assess stress levels.

[2121] Input: Message received from the user.

[2122] Data processing: Text analysis is performed using Python NLP libraries (e.g., SpaCy, NLTK).

[2123] Output: Evaluation results regarding stress levels.

[2124] Step 10:

[2125] Server: Generates customized stress management methods and lifestyle suggestions based on stress level assessments.

[2126] Input: Stress level assessment results.

[2127] Data processing: Generate proposal text using a generative AI model (e.g., OpenAI's GPT-3).

[2128] Prompt example: "The user has reported feeling stressed recently. Please provide advice on deep breathing exercises and dietary improvements."

[2129] Output: Customized proposal text.

[2130] Step 11:

[2131] Terminal: Displays the suggested text received from the server to the user.

[2132] Input: Proposal text sent from the server.

[2133] Output: The suggested text displayed to the user.

[2134] Specific example of action: The chat screen displays the message, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing your intake of whole grains in your diet."

[2135] Step 12:

[2136] User: Either implement the suggested method or enter further questions.

[2137] Input: Type "I will try the deep breathing exercise" and send feedback.

[2138] Output: Successfully submitted practice report and new questions.

[2139] Step 13:

[2140] Terminal: Sends user feedback to the server.

[2141] Input: User feedback.

[2142] Output: Data sent to the server.

[2143] Step 14:

[2144] Server: The feedback is saved to a database and used to generate suggestions for the next time.

[2145] Input: Feedback sent from the device.

[2146] Output: Feedback stored in the database.

[2147] Step 15:

[2148] Server: Generates and provides users with basic knowledge and support methods regarding diabetes.

[2149] Input: User's current health information and feedback.

[2150] Data processing: Generate educational content using natural language generation technology.

[2151] Output: Educational text about diabetes.

[2152] Step 16:

[2153] Terminal: Displays the provided information to the user.

[2154] Input: Educational message sent from the server.

[2155] Output: Displaying information on the screen.

[2156] Specific example of actions: Present educational content as text, video, and infographics.

[2157] Step 17:

[2158] User: Share the suggested information and receive support from family and friends.

[2159] Input: Share the provided information via the app's share button.

[2160] Output: Information sharing complete.

[2161] (Application Example 1)

[2162] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2163] Diabetic patients often face not only physical health management challenges but also mental stress management and financial burdens. However, there is no system in place to comprehensively manage these aspects and provide appropriate lifestyle and financial suggestions. Therefore, there is a need for systems and methods to alleviate the mental and financial stress of diabetic patients and promote healthy living.

[2164] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[2165] In this invention, the server includes: means for inputting and transmitting the user's health and economic information; server means for storing and analyzing the transmitted information; means for analyzing the user's mental and economic state in response to user input; means for generating stress management methods, lifestyle habits, and economic suggestions based on the analysis results; terminal means for displaying the generated suggestions; means for collecting and storing user feedback; and means for generating and providing information on basic knowledge and support methods related to diabetes. This makes it possible for diabetic patients and their related parties to comprehensively manage their health, mental state, and economic state and receive appropriate suggestions.

[2166] "User health information" refers to physiological data such as height, weight, blood glucose levels, and meal frequency that diabetic patients record on a daily basis.

[2167] "Economic information" refers to economic data such as users' spending, budgets, and monthly expenses.

[2168] A "server" refers to a central control unit that stores transmitted data, performs analysis, and provides the results to users.

[2169] "Mental state" refers to information that represents the user's stress level and emotional health.

[2170] "Economic status" refers to information that represents the user's financial health and spending habits.

[2171] "Stress management methods" refer to methods and techniques for reducing the mental stress of users (e.g., deep breathing exercises and relaxation techniques).

[2172] "Lifestyle suggestions" refer to specific suggestions for improving the user's daily life (e.g., dietary advice or recommendations for exercise).

[2173] "Economic suggestions" refer to specific advice aimed at improving the user's financial situation (e.g., selecting cost-effective foods or recommending exercise plans).

[2174] A "terminal" refers to a device (e.g., a smartphone or tablet) that displays suggestions and information to the user and allows for data input and transmission.

[2175] "Feedback" refers to the evaluations and comments that users provide to the system.

[2176] "Basic knowledge about diabetes" refers to fundamental information regarding blood sugar management methods, diet, and exercise.

[2177] The system of the present invention is intended to provide integrated health management, mental stress management, and economic solutions to diabetic patients and their families. As an example of implementing the present invention, a specific system configuration and its operation are described below.

[2178] System Configuration

[2179] The main components of this system are as follows:

[2180] 1. User's device: A device (smartphone, tablet) used by the user to input health and financial information and receive suggestions.

[2181] 2. Server: A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[2182] 3. Artificial Intelligence Engine: A module that uses AI technologies for natural language processing and data analysis (e.g., TensorFlow).

[2183] Operation details

[2184] Data collection and initial setup

[2185] 1. User: Launch the application and enter the necessary personal information, health information, and financial information (e.g., blood sugar levels, weight, exercise habits, monthly expenses).

[2186] 2. Terminal: Sends the provided information to the server.

[2187] 3. Server: Saves the received data as the initial settings.

[2188] User interaction

[2189] 1. User: Use the in-app chat function to enter questions, current mental state, and financial status.

[2190] 2. Terminal: Sends user responses to the server in real time.

[2191] 3. Server: Analyzes received data to assess the user's stress level, current health status, and financial status.

[2192] Stress management, lifestyle, and economic suggestions

[2193] 1. Server: Based on the evaluation results, it generates customized stress management methods, lifestyle habits, and economic suggestions (e.g., relaxation exercises, dietary advice, recommendations for cost-effective health foods).

[2194] 2. Terminal: Displays suggestions received from the server to the user.

[2195] Support provision and education

[2196] 1. Server: Provides information to deepen basic knowledge and understanding of diabetes, and also offers specific advice on how family and friends can support people with diabetes.

[2197] 2. Device: Displays the provided information to the user, their family, and friends.

[2198] Hardware and software to be used

[2199] Frontend: Built using React Native. Provides a UI for collecting user-entered information and sending it to the server.

[2200] Backend: Built using Node.js and Express. It stores and parses incoming data and generates suggestions.

[2201] Database: MongoDB is used to store user health information, financial information, feedback, etc.

[2202] AI Engine: Uses TensorFlow for natural language processing and data analysis.

[2203] Specific example

[2204] Let's assume the user enters the following information.

[2205] Height: 170cm

[2206] Weight: 70kg

[2207] Blood glucose level: 140 mg / dL

[2208] Number of meals per day: 3

[2209] Monthly expenses: 60,000 yen

[2210] Based on this information, the server generates a suggestion that reads, "Your stress level is high. Try incorporating daily deep breathing exercises and a healthy diet. Your financial situation is also high, so review your balanced diet and exercise plan."

[2211] Example of a prompt

[2212] Question: The user has entered the following information. Please provide appropriate health and financial suggestions.

[2213] Height: 170cm

[2214] Weight: 70kg

[2215] Blood glucose level: 140 mg / dL

[2216] Number of meals per day: 3

[2217] Monthly expenses: 60,000 yen

[2218] Answer: Your stress levels are high. Focus on daily deep breathing exercises and a healthy diet. Your financial situation is also high, so review your balanced diet and exercise plan.

[2219] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2220] Step 1:

[2221] Data entry (health information and economic information)

[2222] The user launches the application and enters information such as height, weight, blood sugar level, number of meals per day, and monthly expenses.

[2223] Input: Height, weight, blood sugar level, number of meals, expenses

[2224] Output: Data in JSON format (Example: { "height": 170, "weight": 70, "glucose": 140, "mealsPerDay": 3, "expenses": 60000})

[2225] Step 2:

[2226] Data transmission

[2227] The terminal sends the data entered by the user to the server.

[2228] Input: User data in JSON format

[2229] Output: Data sent to the server

[2230] Step 3:

[2231] Data storage

[2232] The server saves the received data to a database (MongoDB).

[2233] Input: Received data (JSON format)

[2234] Output: Records stored in the database

[2235] Step 4:

[2236] Data Analysis

[2237] The server uses a natural language processing engine (TensorFlow) to analyze the user's mental and economic state.

[2238] Input: User information retrieved from the database

[2239] Data processing: Stress levels are calculated based on blood glucose levels, meal frequency, etc., and economic status is evaluated based on monthly expenses.

[2240] Output: Assessment of stress level and economic status (e.g., { "stressLevel": "High", "economicStatus": "High"})

[2241] Step 5:

[2242] Proposal generation

[2243] Based on the analysis results, the server generates stress management methods, lifestyle suggestions, and economic advice.

[2244] Input: Stress level, assessment of economic status

[2245] Data processing: The program generates exercise and dietary advice for stress reduction, as well as specific suggestions for improving financial conditions.

[2246] Output: Suggestions (e.g., deep breathing exercises, healthy eating, recommendations for cost-effective foods)

[2247] Step 6:

[2248] Suggestion display

[2249] The terminal displays suggestions received from the server to the user.

[2250] Input: Proposal (string in JSON format)

[2251] Output: Suggestions displayed on the device's UI

[2252] Step 7:

[2253] Feedback Collection

[2254] Users provide feedback on suggestions within the application.

[2255] Input: Feedback (e.g., "I tried the deep breathing exercises")

[2256] Output: Feedback data in JSON format

[2257] Step 8:

[2258] Send and save feedback

[2259] The device sends the collected feedback to the server, which then stores it in a database.

[2260] Input: User feedback data

[2261] Output: Feedback stored in the database

[2262] Step 9:

[2263] Support information provided

[2264] The server generates information on basic knowledge and support methods related to diabetes and provides it to users and their related parties.

[2265] Input: None (Information generated periodically)

[2266] Output: Educational content (e.g., text, video, infographics)

[2267] Step 10:

[2268] Support information display

[2269] The device displays educational content received from the server to the user.

[2270] Input: Data from educational content

[2271] Output: Educational content displayed on the device's UI

[2272] Through these steps, this system enables diabetic patients and their families to comprehensively manage their health, mental state, and financial situation, and to receive appropriate suggestions.

[2273] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[2274] The following describes a specific system configuration and its operation as an embodiment for carrying out the present invention. This system uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends, and further incorporates an emotion engine to recognize the user's emotions and reflect them in the analysis results.

[2275] System Configuration

[2276] The main components are as follows:

[2277] 1. User's device

[2278] A device (e.g., smartphone, tablet, PC) that allows users to input health information and receive suggestions.

[2279] 2. Server

[2280] A central system that stores, analyzes, and generates suggestions based on data submitted by users.

[2281] 3. Artificial Intelligence Engine

[2282] A module that uses AI technologies for natural language processing and data analysis. It integrates an emotion engine and has the ability to analyze the user's emotions from input data.

[2283] 4. Emotional Engine

[2284] A module that recognizes emotions based on user input and incorporates them into the assessment of mental state.

[2285] Operation details

[2286] Data collection and initial setup

[2287] 1. User: Launch the application and enter the necessary personal and health information (e.g., blood sugar levels, weight, exercise habits).

[2288] Example: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, eats 3 meals a day".

[2289] 2. Terminal: Sends the provided information to the server.

[2290] Specific example: When the user confirms their input, the device sends the data to the server.

[2291] 3. Server: Saves the received data as the initial settings.

[2292] Specific example: The server records the user's basic health information in a database and uses it as initial settings.

[2293] User interaction

[2294] 1. User: Use the in-app chat function to enter questions or your current mental state.

[2295] Example: Enter "I've been feeling stressed lately and it's bothering me."

[2296] 2. Terminal: Sends user responses to the server in real time.

[2297] Specific example: Immediately relaying user messages to the server.

[2298] 3. Server: Analyzes the received data, uses the emotion engine to recognize the user's emotions, and evaluates their overall mental state.

[2299] Specific example: The server uses an emotion engine to analyze the user's message and recognize emotions such as "lonely."

[2300] Stress management and lifestyle suggestions

[2301] 1. Server: Based on the emotion analysis results, it generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle suggestions (e.g., dietary improvements, exercise recommendations).

[2302] Specific example: It generates a message saying, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing the amount of whole grains in your diet."

[2303] 2. Terminal: Displays the suggestions received from the server to the user.

[2304] Specific example: Present the proposal content as a chat screen or notification.

[2305] 3. User: Decide whether or not to implement the suggested method, and if so, provide feedback such as "I will try it."

[2306] Specific example: Give feedback such as, "I'll try the deep breathing exercise."

[2307] 4. Terminal: Sends user feedback to the server.

[2308] Specific example: Send the feedback content to the server.

[2309] 5. Server: Save user feedback and use it to improve future suggestions.

[2310] Specific example: Store feedback in a database and use it for individual suggestions.

[2311] Support provision and education

[2312] 1. Server: Generates information on basic knowledge and support methods regarding diabetes, and creates content for sharing with family and friends.

[2313] Specific example: Generate information such as, "Managing blood sugar levels is crucial for diabetes. By helping family and friends understand this, you can get them to support you with diet management and exercise."

[2314] 2. Device: Display educational information to the user and provide options (e.g., a share button) for sharing with family and friends.

[2315] Specific example: Display educational content in text, video, or infographic format.

[2316] 3. User: Click the share button to share the provided information with family and friends.

[2317] Specific example: Click the share button to send the provided information to family members via email.

[2318] 4. Terminal: Notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[2319] Specific example: An email sent to a family member contains educational information.

[2320] In this way, by combining the emotional engine, the present invention can provide diabetic patients and their families with more detailed and personalized stress management and healthy lifestyle suggestions, thereby improving the mental and physical health of users.

[2321] The following describes the processing flow.

[2322] Step 1:

[2323] The user launches the application and enters basic information such as name, email address, password, height, weight, and blood sugar level on the new registration screen.

[2324] Step 2:

[2325] The terminal sends the entered information to the server.

[2326] Step 3:

[2327] The server saves the received information to the database.

[2328] Step 4:

[2329] The user accesses the in-app chat function and enters their feelings or mental state, such as "I've been feeling stressed lately."

[2330] Step 5:

[2331] The device sends the user's message to the server.

[2332] Step 6:

[2333] The server uses an emotion engine to analyze the user's message to determine their emotions. For example, it might extract emotions like "stress" and "worry" from the user's input, "I've been feeling stressed lately and it's really bothering me."

[2334] Step 7:

[2335] The server evaluates the mental state based on the results of the emotion analysis and determines the stress level.

[2336] Step 8:

[2337] Based on the emotion analysis results, the server generates personalized stress management methods (e.g., deep breathing exercises, meditation) and lifestyle suggestions (e.g., balanced diet, regular exercise).

[2338] Step 9:

[2339] The terminal displays suggestions received from the server to the user. For example, "We recommend doing deep breathing exercises for 10 minutes every day."

[2340] Step 10:

[2341] The user reviews the proposal and decides whether to implement it. If they decide to implement it, they provide feedback such as "I'll give it a try."

[2342] Step 11:

[2343] The device sends user feedback to the server.

[2344] Step 12:

[2345] The server saves user feedback and uses it to improve future suggestions. It also evaluates the effectiveness of suggestions based on the feedback.

[2346] Step 13:

[2347] The server generates information on basic knowledge and support methods related to diabetes, and creates content for sharing with family and friends.

[2348] Step 14:

[2349] The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[2350] Step 15:

[2351] Users click the share button to share information with family and friends.

[2352] Step 16:

[2353] The device notifies the server of the sharing action.

[2354] Step 17:

[2355] The server sends information using the selected sharing method (e.g., email, social media). For example, it might send an email containing educational information to a family member.

[2356] In this way, the overall processing flow of the system operates in concrete terms.

[2357] (Example 2)

[2358] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2359] To provide effective mental stress management and lifestyle improvement suggestions to diabetic patients and their families and friends, it is necessary to accurately analyze the health and mental state of each individual user and generate customized suggestions. However, conventional systems have faced challenges in providing individually tailored suggestions due to insufficient emotional analysis and detailed feedback collection.

[2360] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[2361] In this invention, the server includes means for users to input and transmit personal information and health-related information; means for storing the transmitted information and recording it in a database; means for using an artificial intelligence module to analyze the user's input data; means for customizing and generating stress management methods and lifestyle suggestions based on the input data and analysis results; terminal device means for presenting the generated suggestions to the user; means for collecting, analyzing, and storing user feedback; and means for generating and providing health-related educational and support information. This makes it possible to provide customized suggestions in real time based on each user's individual health and mental state.

[2362] "User" refers to an individual who uses the system to manage and receive suggestions regarding their health information and mental state.

[2363] "Personal information" refers to basic data used to identify a user, such as name, age, and gender.

[2364] "Health-related information" refers to data that indicates the user's health status, such as blood glucose levels, weight, and exercise habits.

[2365] A "server" refers to a central computing system that stores data, performs analysis, and generates proposals.

[2366] A "sentiment analysis engine" refers to a technology module that recognizes and analyzes a user's emotions from input text and data.

[2367] An "artificial intelligence module" refers to a program that uses AI technology to perform data analysis and proposal generation.

[2368] "Stress management" refers to methods and techniques for improving mental health.

[2369] "Lifestyle suggestions" refer to suggestions that indicate recommended actions and habits for maintaining or improving health.

[2370] "Feedback" refers to suggestions, reactions, and opinions on services collected from users.

[2371] "Educational information" refers to data that provides users, their families, and friends with knowledge and support methods regarding diabetes.

[2372] "Shareable" refers to a feature that allows users to share information with other people.

[2373] This invention is a system that uses AI to provide mental stress management and lifestyle suggestions to diabetic patients and their families and friends. This system incorporates an emotion engine to recognize the user's emotions and reflect them in the analysis results.

[2374] System Configuration

[2375] The main components are as follows:

[2376] 1. User's device

[2377] These are devices that allow users to input health information and receive suggestions. Examples include smartphones, tablets, and PCs.

[2378] 2. Server

[2379] This is a central system that stores, analyzes, and generates suggestions based on data submitted by users.

[2380] 3. Artificial Intelligence Module

[2381] This program uses AI technologies for natural language processing and data analysis. It integrates an emotion analysis engine to analyze the user's emotions from the input data.

[2382] 4. Emotion Analysis Engine

[2383] This is a technology module for recognizing emotions based on user input and incorporating them into the assessment of mental state.

[2384] Operation details

[2385] The system works as follows:

[2386] Data collection and initial setup

[2387] 1. The user launches the application and enters necessary personal and health information (e.g., blood sugar level, weight, exercise habits). For example, they might enter, "Height 170cm, weight 70kg, blood sugar level 110mg / dL, I eat 3 meals a day."

[2388] 2. The terminal sends the provided information to the server. Once the user confirms the input, the terminal sends the data to the server.

[2389] 3. The server saves the received data as initial settings. Specifically, the server records the user's basic health information in a database and uses it as initial settings.

[2390] User interaction

[2391] 1. Users use the chat function to enter questions or their current mental state. For example, they might type, "I've been feeling stressed lately and it's bothering me."

[2392] 2. The terminal sends user responses to the server in real time.

[2393] 3. The server analyzes the received data, uses an emotion analysis engine to recognize the user's emotions, and evaluates their overall mental state. For example, the server uses the emotion analysis engine to analyze "stress" from the user's message.

[2394] Stress management and lifestyle suggestions

[2395] 1. Based on the emotion analysis results, the server generates customized stress management methods (e.g., deep breathing exercises, meditation suggestions) and lifestyle recommendations. For example, it might generate, "We recommend doing deep breathing exercises for 10 minutes every day. Also, consider increasing your intake of whole grains in your diet."

[2396] 2. The terminal displays the suggestions received from the server to the user.

[2397] 3. The user decides whether or not to implement the suggested method, and if so, provides feedback such as "I'll try it."

[2398] 4. The device sends user feedback to the server.

[2399] 5. The server saves user feedback and uses it to improve future suggestions.

[2400] Support provision and education

[2401] 1. The server generates information on basic knowledge and support methods regarding diabetes, and creates content for sharing with family and friends. For example, it might generate information such as, "Managing blood sugar levels is important for diabetes. By helping family and friends understand this, you can get support with diet management and exercise."

[2402] 2. The device displays educational information to the user and provides options (e.g., a share button) for sharing it with family and friends.

[2403] 3. The user clicks the share button to share the provided information with family and friends.

[2404] 4. The device notifies the server of the sharing action, and the server sends the information using the selected sharing method (e.g., email, social media).

[2405] This allows the system, which combines an emotion analysis engine and an artificial intelligence module, to provide personalized stress management and healthy lifestyle suggestions to diabetic patients and their families, thereby improving the users' mental and physical health.

[2406] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2407] Step 1:

[2408] User: Launches the application and enters personal and health-related information (e.g., height, weight, blood sugar level, exercise habits). The entered information (input data) is sent to the terminal.

[2409] Input: Personal information, health-related information

[2410] Output: Input data sent to the terminal

[2411] Specific actions: Enter "Height 170cm, weight 70kg, blood sugar level 110mg / dL, I eat 3 meals a day" into the app's form and press the confirm button.

[2412] Step 2:

[2413] Terminal: Sends user-entered data to the server.

[2414] Input: Data entered by the user

[2415] Output: Data to send to the server

[2416] Specific action: When the confirmation button is pressed, the device sends the data to the server via the internet.

[2417] Step 3:

[2418] Server: Saves the transmitted data to the database and records it as initial settings.

[2419] Input: Data sent from the device

[2420] Output: User data stored in the database

[2421] Specific operation: The server receives data, records it in the database, and creates a profile for each user.

[2422] Step 4:

[2423] User: Use the chat function to enter your current mental state or questions.

[2424] Input: Text of mental state or question

[2425] Output: Input data sent to the terminal

[2426] Specific action: Type "I've been feeling stressed lately" into the chat window and press the send button.

[2427] Step 5:

[2428] Terminal: Sends user messages to the server in real time.

[2429] Input: User input message

[2430] Output: Message sent to the server

[2431] Specific operation: The message is transferred to the server the moment the send button is pressed.

[2432] Step 6:

[2433] Server: Analyzes received messages using an emotion analysis engine and evaluates the emotional state.

[2434] Input: Message sent by the user

[2435] Data processing: The sentiment analysis engine analyzes the message content.

[2436] Output: Emotional state (e.g., "stress")

[2437] Specific operation: The server uses an emotion analysis engine to analyze "stress" from the input "high stress level" and records it as an emotional state.

[2438] Step 7:

[2439] Server: Based on the emotion analysis results, it generates customized stress management methods and lifestyle suggestions.

[2440] Input: Sentiment analysis results

[2441] Data processing: Generative AI model generates suggestions.

[2442] Output: Proposed content (Example: "Perform deep breathing exercises for 10 minutes every day")

[2443] Specific operation: The server prompts the AI ​​model with "suggestions based on the user's sentiment analysis results" and generates suggestions.

[2444] Step 8:

[2445] Terminal: Displays the suggestions received from the server to the user.

[2446] Input: Suggestions from the server

[2447] Output: Suggestions displayed to the user

[2448] Specific action: Use the application's notification function to display the suggested content as a pop-up on the screen.

[2449] Step 9:

[2450] User: Decide whether to implement the suggestion and provide feedback.

[2451] Input: User feedback

[2452] Output: Feedback sent to the device

[2453] Specific action: Send feedback saying "I'll try the deep breathing exercise" and press the submit button.

[2454] Step 10:

[2455] Terminal: Sends user feedback to the server.

[2456] Input: User feedback

[2457] Output: Feedback sent to the server

[2458] Specific action: The feedback content is sent directly to the server.

[2459] Step 11:

[2460] Server: Saves user feedback to a database and uses it to improve future suggestions.

[2461] Input: User feedback

[2462] Output: Feedback stored in the database

[2463] Specific operation: The feedback is saved to a database and referenced when generating suggestions in the future.

[2464] Step 12:

[2465] Server: Generates basic knowledge and support information about diabetes, and creates content for sharing with family and friends.

[2466] Input: Health-related information stored on the server

[2467] Data processing: Generative AI model generates educational information.

[2468] Output: Health education content (e.g., "Key Points for Diabetes Management")

[2469] Specific operation: The server prompts the AI ​​model to generate "educational information on diabetes management" and generates the content.

[2470] Step 13:

[2471] Terminal: Displays generated educational information to the user and provides the option to share it with family and friends.

[2472] Input: Educational information from the server

[2473] Output: Educational content and sharing options displayed to the user

[2474] Specific actions: Display educational content in text or video format and include a share button.

[2475] Step 14:

[2476] User: Click the share button to share the provided information with family and friends.

[2477] Input: Share Action

[2478] Output: Instructions for sharing information

[2479] Specific actions: Click the share button and select the sharing method (e.g., email, social media).

[2480] Step 15:

[2481] Terminal: Notifies the server of the sharing action, and the server sends the information using the selected sharing method.

[2482] Input: Shared Action Notification

[2483] Output: Information sent to family and friends

[2484] Specific operation: A share action trigger is sent to the server, and the information is shared in the selected manner.

[2485] (Application Example 2)

[2486] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2487] A system is needed to monitor the mental stress and health status of passengers in autonomous vehicles in real time and to provide appropriate stress management and lifestyle suggestions. Conventional systems have been unable to adequately monitor the mental and health status of passengers, which is crucial for maintaining safe driving, and have been unable to take appropriate action.

[2488] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using a biosensor to monitor health status, means for using a camera to analyze emotions, and means for evaluating the passenger's mental state based on data from the camera and biosensor. This makes it possible to monitor the stress level and health status of passengers in an autonomous vehicle in real time and to immediately provide appropriate stress management and lifestyle suggestions.

[2489] "Means for inputting and transmitting health information" refers to a device that allows users to input their own health data (e.g., blood sugar levels, heart rate, weight, etc.) and transmit that information to a server within the system.

[2490] A "server system for storing transmitted health information" refers to a central system for receiving health information transmitted by users and securely storing it in a database.

[2491] "Means for analyzing mental state" refers to devices or software that analyze user input or data from biosensors to evaluate the user's emotions and mental state.

[2492] "Means for generating stress management methods and lifestyle suggestions" refers to a device or software that generates stress management methods and lifestyle improvement suggestions suitable for the user based on analyzed information about the user's mental state.

[2493] "Display device for displaying generated suggestions" refers to a device for visually presenting to the user stress management and lifestyle habit suggestions generated by the system.

[2494] "Means for collecting and storing user feedback" refers to a device or software for collecting feedback on suggestions made by users and storing that information in a database within the system.

[2495] "Methods using biosensors to monitor health status" refer to devices that collect physiological data from users in real time, such as heart rate and skin electrical responses.

[2496] "Methods using cameras to analyze emotions" refer to imaging devices that detect the user's facial expressions and posture and evaluate their emotions based on that information.

[2497] "Means for evaluating passengers' mental state based on data from cameras and biosensors" refers to a device or software that analyzes data collected from cameras and biosensors to comprehensively evaluate the mental state of users.

[2498] "Means of suggesting relaxation music or exercises while driving" refers to a device or software that suggests music or exercise methods with relaxation effects based on the user's mental state.

[2499] "Means for generating and providing information on basic knowledge and support methods regarding diabetes" refers to devices or software that generate and provide information to help users and their families understand and appropriately manage diabetes.

[2500] This invention provides a system that monitors the mental stress and health status of passengers in autonomous vehicles in real time and offers appropriate stress management and lifestyle suggestions. The specific system configuration and its operation are described below.

[2501] System Configuration

[2502] The system consists of the following main components:

[2503] 1. User's equipment

[2504] A device (e.g., smartphone, tablet) for entering health information and receiving suggestions.

[2505] 2. Sensor devices

[2506] A heart rate sensor that measures heart rate (e.g., Polar H9).

[2507] A skin electromechanist (e.g., Empatica E4) that measures the electrical response of the skin.

[2508] 3. Camera device

[2509] A camera used to capture facial expressions and analyze emotions (e.g., a camera built into a vehicle).

[2510] 4. Server

[2511] A central system that stores and analyzes health information and emotional data, and generates recommendations.

[2512] 5. Artificial Intelligence Engine

[2513] A module that uses AI technologies for natural language processing and data analysis. It integrates an emotion engine and has the ability to analyze the user's emotions from input data.

[2514] 6. Display Device

[2515] A device for displaying generated suggestions.

[2516] Operation details

[2517] 1. Data Collection

[2518] The user's device inputs health information (e.g., blood glucose levels, weight, exercise habits) and sends it to the server.

[2519] The system collects heart rate and skin electrical response data in real time from sensor devices and captures passenger facial expression data from camera devices.

[2520] 2. Data Analysis and Evaluation

[2521] The server receives and stores transmitted health information, heart rate data from biosensors, and skin electrical response data.

[2522] The system analyzes facial expression data from camera devices and uses an emotion engine to evaluate the emotional state of passengers.

[2523] 3. Proposal generation

[2524] The server uses an AI engine to generate stress management methods and lifestyle suggestions based on health information, heart rate, skin electrical responses, and emotional data.

[2525] Specific examples include "recommending the playback of relaxation music" and "suggesting deep breathing exercises."

[2526] 4. Proposal display and feedback collection

[2527] The generated suggestions are presented to the user through a display device.

[2528] Users provide feedback on the suggestions and send that feedback information to the server.

[2529] The server receives feedback information and incorporates it into the next proposal generation.

[2530] Specific example

[2531] Example prompt message: When your heart rate is high and emotion analysis identifies you as "anxious".

[2532] Prompt message: Heart rate 95, skin electrical response 0.75, anxiety

[2533] This system will enable real-time monitoring of passengers' stress levels and health status in autonomous vehicles, and will immediately provide appropriate stress management and lifestyle suggestions.

[2534] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2535] Step 1:

[2536] The user inputs health information. Specifically, the user uses an input device such as a smartphone to enter health information such as blood glucose levels, weight, and exercise habits into the application. The entered data is sent to the server by the device. The input consists of numerical data such as blood glucose levels and weight, which is then sent to the server.

[2537] Step 2:

[2538] The server receives the transmitted health information and stores it in the database. The server receives the user's health information and records it in the database. The health information is stored accurately because it will be used for subsequent analysis. At this stage, the input is the health information from the user, and the output is the health information stored in the database.

[2539] Step 3:

[2540] Real-time data collection begins using sensor devices (heart rate sensor and electrodermal meter) and a camera device. The terminal collects heart rate and electrodermal response data from the heart rate sensor and electrodermal meter, and captures the passenger's facial expressions with the camera device. The inputs collected are heart rate, electrodermal response, and facial expression data, which are then sent to the server.

[2541] Step 4:

[2542] The server receives and stores the collected biosensor data and camera device data. The received data is recorded in a database. The input is biometric data from the sensor device and camera device, and the output is the stored biometric data.

[2543] Step 5:

[2544] The server analyzes facial expression data from the camera device and uses an artificial intelligence engine to evaluate emotional states. Specifically, the collected facial expression data is processed as images and input into an emotion recognition model. The AI ​​engine analyzes the emotional state and identifies emotions such as "anxiety" or "loneliness." The input is facial expression data, and the output is the result of the emotion analysis.

[2545] Step 6:

[2546] The server uses a generative AI model to generate stress management methods and lifestyle suggestions based on stored health information, biosensor data, and emotional states. The AI ​​engine comprehensively analyzes multiple data points to generate suggestions tailored to the user. Specific examples include "Play relaxation music" and "Perform deep breathing exercises." Inputs are health information, biosensor data, and emotional analysis results, while output is the suggested content.

[2547] Step 7:

[2548] The server sends the generated suggestions to the terminal. The terminal displays the received suggestions on a display device, visually presenting them to the user. As output, the user can then review the suggestions.

[2549] Step 8:

[2550] The user decides whether to implement the suggested method and enters feedback. If the user implements the suggested method, they enter feedback such as "I tried it" or "It was effective" into the terminal. This input is the feedback content and is sent to the server.

[2551] Step 9:

[2552] The server receives user feedback and stores it in a database. This feedback information is used to generate suggestions for future updates. The input is user feedback, and the output is the stored feedback information.

[2553] This allows the system to monitor the user's health and mental state in real time and provide appropriate stress management and lifestyle suggestions.

[2554] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2555] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2556] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2557] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2558] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2559] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2560] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2561] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2562] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[2563] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[2564] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure ma...

Claims

1. A means for inputting and transmitting the user's health information, A server means for storing the transmitted health information, A means of analyzing the user's mental state in response to user input, A means for generating stress management methods and lifestyle suggestions based on analysis results, A terminal means for displaying the generated proposal, A means of collecting and storing user feedback, Means for generating and providing information on basic knowledge and support methods related to diabetes. A system that includes this.

2. The system according to claim 1, comprising means for using an artificial intelligence engine to evaluate the mental state of a user.

3. The system according to claim 1, comprising means for enabling the sharing of support information with the user and their family and friends.

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