System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving daily health condition information as voice or text data from a user; means for storing the received health condition information in a database; means for comparing and analyzing the stored health condition information with past data and general medical knowledge based on the stored health condition information; means for generating specific advice for the user based on the analysis result; means for providing the generated advice to the user; and means for recording and updating the generated advice and a diagnosis result in a user-specific medical chart.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, aging and labor shortages are serious problems. While many people recognize the importance of daily health management and disease prevention, they often find it difficult to visit a medical institution at the appropriate time. Furthermore, it is difficult to immediately obtain specific advice on how to deal with everyday illnesses and declines in work performance, making it difficult to properly manage one's own health. There is a need for a system that can solve these problems and help individual users understand their own health status and take preventive actions. [Means for solving the problem]

[0005] The present invention solves the problems by using the following means. Specifically, it provides a means for receiving daily health condition information from a user as voice or text data, and a means for storing the received health condition information in a database. Furthermore, it analyzes the user's health condition by combining a means for comparing and analyzing the stored health condition information with past data and general medical knowledge. It also provides a means for generating specific advice for the user based on the analysis results and providing the generated advice to the user. It also includes a means for recording and updating the generated advice and diagnosis results in the user's individual medical record, making it easier for users to manage their own health condition over the long term. In this way, it provides a system that solves the issues of an aging population and labor shortages and contributes to preventing illness.

[0006] "User" refers to an individual who uses the system to manage their own health status and receive advice.

[0007] "Voice or text data" refers to the data format used by users to input their health status, where voice data includes information converted from voice input into text, while text data refers to directly entered text information.

[0008] "Health status information" refers to information provided by the user regarding their daily physical condition, including symptoms, sensations, and fluctuations in physical condition.

[0009] "Database" refers to a centralized data storage system that stores received health status information, analysis results, advice, etc., and can be referenced as needed.

[0010] "Comparative and analytical means" refers to the processes and techniques used to analyze stored health status information against historical data and general medical knowledge.

[0011] "Advice" refers to specific guidelines for action or improvements suggested to the user based on the analysis results, which are useful for the user in managing their health and improving their performance.

[0012] A "medical record" refers to a digital document that comprehensively records a user's health condition, diagnosis results, advice provided, etc., and is used for long-term health management of the user. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0014] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0017] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0018] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0019] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0026] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0033] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0034] The present invention is a system that collects, stores, analyzes, and provides advice on a user's daily health status. This system makes it easier for users to manage their own health status and supports the prevention of illness and the improvement of daily performance. To implement the present invention, a program based on the following processing steps is generated, and the operation of each step is explained in detail. Each major process is explained below.

[0035] User Registration / Login

[0036] When a user uses the system for the first time, they enter their personal information and initial health status information. This data is sent from the device to the server, which stores it in a database. The server then generates a user ID and returns it to the device. From then on, the user can log in using this ID.

[0037] For example, when User A uses the system for the first time, he or she enters his or her name, age, gender, medical history, etc. This information is sent from the terminal to the server. The server then creates an individual medical record for User A based on this information, generates a user ID, and sends it back to the terminal. After logging in and completing the initial settings, User A can easily log in next time.

[0038] Daily medical questionnaire entry

[0039] When a user inputs their health status for the day, they input information about their health status by voice or text. The device receives this input, converts it into text if it is voice, and sends it to the server. The server stores this information in a database for later analysis.

[0040] For example, if user B says "I have a headache today," the device converts this speech into text and sends it to the server. The server receives the text information "headache" and stores it in user B's health database.

[0041] Data collection and analysis

[0042] The server compares and analyzes the received data with past data and general medical knowledge. For example, it compares it with other data from a time when headaches were frequent in the past to infer the cause. It also compares it with general medical knowledge to find likely causes and countermeasures.

[0043] For example, if User C has frequently entered "headache" data in the past, the server compares and analyzes this past data with the current data, identifying past patterns and triggering factors (such as climate change or stress levels), and performs a detailed analysis based on general medical knowledge.

[0044] Generating Advice

[0045] The server generates specific advice for the user based on the analysis results. For example, if the accumulated data indicates that a headache is caused by caffeine intake or lack of sleep, the server generates advice such as "Reduce your caffeine intake today and drink plenty of water."

[0046] If User D inputs "I have a headache today," and the server determines through analysis that "it's likely due to caffeine intake," the generated advice will read, "Reduce your caffeine intake today and drink plenty of water." This advice will be provided to User D via the terminal.

[0047] Providing advice

[0048] The generated advice is provided to the user via the device, which then communicates it to the user using an AI speaker or chat interface. The user can then receive this advice and use it in their daily activities and health management.

[0049] For example, after user E enters their morning physical condition, the AI ​​speaker will provide voice advice such as, "It would be good for you to get plenty of rest today. I recommend you drink plenty of water."

[0050] Medical record updates

[0051] The server records and updates the advice and diagnosis results provided that day in the user's individual medical record, making it easier for users to understand their own health condition over the long term. It also makes it possible to detect health trends and abnormalities early in the future.

[0052] For example, all health information entered by user F over the past month and advice provided can be stored in a database and used for future health management and medical consultations.

[0053] As described above, the system of the present invention effectively supports the user's health management and prevention of illness. Users can maintain and improve their health by simply inputting their daily physical condition, receiving analysis and advice from the server, and taking actions based on this information.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] The user starts the application and accesses the user registration screen. The terminal displays the user registration form.

[0057] Step 2:

[0058] The user enters personal information such as name, age, gender, email address, chronic illnesses and allergies. The device temporarily stores the entered information and waits for the user to click the registration button.

[0059] Step 3:

[0060] The user clicks the registration button. The device sends the input information to the server.

[0061] Step 4:

[0062] The server stores the received information in a database, generates a user ID, and returns the generated user ID to the device.

[0063] Step 5:

[0064] The terminal receives the user ID and logs the user in. At this stage, the initial user settings are complete.

[0065] Step 6:

[0066] The user inputs their physical condition for the day by voice, and the device converts the voice input into text data.

[0067] Step 7:

[0068] The terminal transmits the converted text data to the server. For example, if the user inputs "I have a headache today," the text data is transmitted to the server.

[0069] Step 8:

[0070] The server stores the received text data in a database. New health status information is added to the database.

[0071] Step 9:

[0072] The server compares and analyzes the stored data with past data and general medical knowledge, for example, to identify the cause of headaches and consider general countermeasures.

[0073] Step 10:

[0074] Based on the analysis results, the server generates specific advice for the user, such as "Reduce your caffeine intake today and drink plenty of water."

[0075] Step 11:

[0076] The server sends the generated advice to the terminal, which receives the advice.

[0077] Step 12:

[0078] The device will provide advice to the user through an AI speaker or chat interface, for example, the AI ​​speaker will tell the user to "limit your caffeine intake today and drink plenty of water."

[0079] Step 13:

[0080] The server records and updates the diagnosis results and advice for that day in the user's individual medical record, enabling long-term health management.

[0081] Example 1

[0082] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0083] In modern society, individual health management is extremely important, and there is a growing need for methods to efficiently collect and analyze this information and provide appropriate advice. However, conventional systems have limitations in effectively collecting and analyzing users' health status information and providing appropriate advice, particularly in terms of comparison and analysis with past data and general medical knowledge. Furthermore, there is a lack of methods for generating appropriate advice using generative AI models and for reliably providing this advice to users. These issues are being addressed.

[0084] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0085] In this invention, the server includes means for receiving daily health condition information from a user as voice or text data, means for storing the received health condition information in a database, means for comparing and analyzing the stored health condition information with past data and general medical knowledge, means for generating specific advice for the user based on the analysis results using a generative AI model, means for providing the generated advice to the user, and means for recording and updating the generated advice and diagnosis results in the user's individual medical record. This makes it possible to efficiently collect, compare, and analyze a user's health condition information, and generate and provide appropriate advice.

[0086] "User" refers to each individual who uses the system.

[0087] "Voice data" refers to data containing health information provided by a user through voice input.

[0088] "Text data" refers to data including health condition information provided by the user through character input.

[0089] "Means for receiving" refers to means for obtaining voice or text data from a user within the system.

[0090] "Database" refers to a structured collection of data for storing received health status information.

[0091] "Means for storing" refers to the system's ability to record received health status information in a database.

[0092] "Means for comparison and analysis" refers to the function of comparing stored data with past data and general medical knowledge and analyzing the information.

[0093] "Generative AI model" refers to an artificial intelligence model used to generate specific advice for users based on the results of data analysis.

[0094] "Means for generating advice" refers to the system's function of using a generative AI model to create specific advice from the analysis results.

[0095] The "means for providing advice" refers to a function for displaying or notifying the user of the generated advice.

[0096] A "medical record" refers to an individual health record that includes a user's health status information, past diagnostic results, advice information, etc.

[0097] "Means of recording and updating" refers to the system's functionality for adding advice and diagnostic results generated each day to a user's individual chart and keeping it up to date.

[0098] The present invention is a system for collecting and analyzing a user's daily health condition and providing appropriate advice based on the collected data. Specific embodiments of this system will be described below.

[0099] The system includes the following main components: a terminal, a server, a database, and a generative AI model.

[0100] User Registration / Login

[0101] When a user uses the system for the first time, they use a terminal to enter their personal information and initial health information. For example, the user enters their name, age, gender, medical history, etc., and the terminal sends this data to the server. The server stores the received data in a database and generates a user ID. This user ID is returned to the terminal, and the user can use this ID to log in from the next time onwards.

[0102] Daily medical questionnaire entry

[0103] To record their daily physical condition, users use the device to input information by voice or text. In the case of voice input, the device uses the Google® Cloud Speech-to-Text API to convert the voice into text. The converted text data is sent to a server, which then stores it in a database.

[0104] Data collection and analysis

[0105] The server compares and analyzes the received data with past data and general medical knowledge. Specifically, the server retrieves past data from the database and compares it using a Python data analysis library (e.g., Pandas). It then analyzes the data using a natural language processing library (e.g., NLTK) to identify likely causes and countermeasures.

[0106] Generating Advice

[0107] Based on the results of the comparison and analysis, the server uses a generative AI model (such as GPT-4 (registered trademark)) to generate specific advice for the user. For example, if a comparison of past data determines that "caffeine intake is the cause," the generated advice might include "limit your caffeine intake today and drink plenty of water."

[0108] Providing advice

[0109] The generated advice is provided to the user via the device, which then communicates the advice to the user as a notification or voice message. Specifically, the advice is provided via the notification function of Android (registered trademark) or iOS devices, or through an AI speaker.

[0110] Medical record updates

[0111] The server records and updates the advice and diagnosis results generated that day in the user's medical record. This allows the user to easily understand long-term fluctuations in their health condition and the recurrence of certain symptoms. The server also uses this information to contribute to future health management and early detection of abnormalities.

[0112] Examples of concrete examples and prompts

[0113] For example, if User A says, "I have a headache today," the device converts the voice input into text and sends it to the server. The server then analyzes the data based on past health data and general medical knowledge. Using the generative AI model based on the analysis results, the server generates advice such as "Reduce your caffeine intake and drink plenty of water today," which is then provided to User A via the device. This is important information that the user can use to improve their future behavior and health management.

[0114] An example prompt is:

[0115] "What AI model would you use to analyze what advice should be generated after a user types, 'I have a headache today,' and provide an example of the advice you would generate?"

[0116] By linking these functions, this system will efficiently and effectively support users in managing their health.

[0117] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0118] Step 1:

[0119] The user enters personal information the first time they use the service.

[0120] The user starts the application and enters personal information such as name, age, gender, and medical history into the registration screen. Input data: Name, age, gender, medical history

[0121] Output data: Personal information input data

[0122] Step 2:

[0123] The device sends the input data to the server

[0124] The device sends the entered personal information to the server via an HTTP request. Specifically, it posts the data using an HTTP client library. Input data: Personal information input data

[0125] Output data: Status of completion of sending to server

[0126] Step 3:

[0127] The server saves the user's data to the database and generates a user ID.

[0128] The server saves the received data in a database (e.g. MySQL (registered trademark)) using the INSERT statement and generates a new user ID. Input data: Input data of personal information

[0129] Output: Generated user ID

[0130] Step 4:

[0131] The server returns the generated user ID to the device.

[0132] The server returns an HTTP response containing the generated user ID to the terminal. Specifically, a status code of 200 and JSON data containing the user ID are returned. Input data: Generated user ID

[0133] Output data: User ID response data

[0134] Step 5:

[0135] The user will then log in with the generated user ID.

[0136] The next time the user logs in, they will be authenticated using their user ID and password. Input data: User ID, password

[0137] Output data: Authentication success / failure status

[0138] Step 6:

[0139] The user inputs their daily physical condition by voice or text.

[0140] The user opens the app's questionnaire screen and records their physical condition for the day by voice or text. Input data: Voice or text physical condition data

[0141] Output data: Converted text data

[0142] Step 7:

[0143] Your device converts your voice input into text

[0144] The device uses the Google Cloud Speech-to-Text API to convert voice input into text. Input data: Voice data

[0145] Output data: Text data

[0146] Step 8:

[0147] The device sends the converted text data to the server.

[0148] The converted text data is sent from the terminal to the server via an HTTP request. Input data: Text data

[0149] Output data: Status of completion of sending to server

[0150] Step 9:

[0151] The server stores the received data in the database

[0152] The server saves the received data in the user's database. This also uses the MySQL INSERT statement. Input data: Text data

[0153] Output data: Status of completion of saving to database

[0154] Step 10:

[0155] The server retrieves the received data from the database

[0156] The server retrieves past health data from the database using a SELECT statement. Input data: User ID

[0157] Output data: Past health data

[0158] Step 11:

[0159] The server compares past data with current data

[0160] The server compares the past and current data using a Python data analysis library (e.g., Pandas). Input data: past health data, current health data

[0161] Output data: Comparison results

[0162] Step 12:

[0163] The server analyzes the comparison results against general medical knowledge

[0164] The server uses a natural language processing library (e.g., NLTK) to analyze the comparison results against general medical knowledge. Input data: Comparison results, medical knowledge data

[0165] Output data: Analysis results

[0166] Step 13:

[0167] The server generates advice based on the analysis results.

[0168] The server generates specific advice using a generative AI model (e.g., GPT-4) based on the analysis results. Input data: Analysis results

[0169] Output data: Generated advice

[0170] Step 14:

[0171] Sends server-generated advice to the device

[0172] The generated advice is sent to the terminal in JSON format. Input data: Generated advice

[0173] Output data: Status of completion of transmission to the terminal

[0174] Step 15:

[0175] The device displays or reads the generated advice to the user.

[0176] The device notifies the user of the advice using the app's notification function or voice alert function.

[0177] Output data: Notification content to the user

[0178] Step 16:

[0179] The server records and updates the diagnosis results and advice for that day in the patient chart.

[0180] The server saves the diagnosis results and advice for the day in the user's chart and updates it to the latest version. Input data: diagnosis results, advice

[0181] Output data: Updated medical record data

[0182] (Application example 1)

[0183] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0184] Conventional health management systems allow users to input their own health status and receive advice based on the analysis results. However, these systems rely on devices such as smartphones and computers, and users may not always have easy access to these devices. In addition, there are limitations to voice input and real-time notification functions, which can reduce the convenience of health management. This has made it difficult for users to quickly and appropriately manage their health in their daily lives.

[0185] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0186] In this invention, the server includes: means for receiving daily health condition information from a user as voice or text data; means for storing the received health condition information in a database; means for comparing and analyzing the stored health condition information with past data and general medical knowledge; means for generating specific advice for the user based on the analysis results; means for providing the generated advice to the user; means for recording and updating the generated advice and diagnosis results in the user's individual medical record; and means for receiving health condition information from the user using smart glasses and providing the information as visual or audio notifications, thereby enabling users to quickly and easily input and receive feedback on their health condition via the smart glasses in their daily lives.

[0187] "Health condition information" refers to information related to the user's physical condition and health, such as data on body temperature, blood pressure, whether or not the user has a headache, and sleep duration.

[0188] "Voice or Text Data" means information provided by a User through spoken or written input.

[0189] "Database" means a system for systematically storing and managing health status information and user information.

[0190] "Comparison and analysis" refers to the process of evaluating stored data using statistical methods and machine learning algorithms to derive meaningful results.

[0191] "Specific advice" means specific suggestions or instructions generated based on analyzed data that can help the user improve or maintain their health.

[0192] "Means for providing to the user" means a mechanism for conveying the generated advice to the user through audio notification or visual display.

[0193] "Medical Record" means a digital file that records a user's individual health status information, diagnostic results, and the history of advice provided.

[0194] "Smart glasses" refers to a wearable device that has built-in functions such as information display and voice input, and that allows users to integrate digital information with the physical world when wearing it.

[0195] "Visual or audio notification" means a method of providing information to a user through a display or audio speaker.

[0196] To realize this invention, a system in which a user, a server, and smart glasses work together is required. A specific embodiment of this system will be described below.

[0197] Hardware and software used

[0198] Hardware:

[0199] Smart glasses: Wearable devices with functions such as information display and voice input. Examples include Google Glass (registered trademark) and Vuzix Blade.

[0200] Server: A central processing unit that receives, stores, analyzes data, and generates advice.

[0201] software:

[0202] Speech Recognition: Converts voice input into text data using the Google Cloud Speech-to-Text API.

[0203] Database: Firebase is used to store user health and personal information.

[0204] Data analysis: Compare and analyze data using Python's pandas and scikit-learn.

[0205] Advice generation: Using a generative AI model (e.g., GPT-4 API), specific advice is generated based on the analysis results.

[0206] System Operation

[0207] User Registration and Login

[0208] When a user uses the system for the first time, they scan the QR code (registered trademark) displayed on the screen of the smart glasses with their smartphone to sign up for the application. The user enters information such as their name, age, gender, and medical history by voice or text, and this data is sent to Firebase. Once registration is complete, the server generates a user ID and notifies the user. From then on, the user logs in to the system using this ID.

[0209] Enter your health status

[0210] To input their daily health status, users can use the microphone in their smart glasses to voice-report their health status. For example, if they say, "I have a slight headache today," the smart glasses will convert this voice data into text data using the Google Cloud Speech-to-Text API. The text data will then be sent to Firebase and stored in the user's individual database.

[0211] Data analysis and advice generation

[0212] The server periodically collects health status data stored in Firebase and analyzes it using Python's pandas and scikit-learn. Based on the analysis results, a generative AI model (such as the GPT-4 API) is used to generate specific advice appropriate for the user. For example, if the data indicates frequent headaches or elevated stress levels, the server generates advice such as "It would be a good idea to limit caffeine and drink more water today."

[0213] Providing advice

[0214] The generated advice is provided to the user in real time via the smart glasses as a visual or audio notification, such as a message on the smart glasses display saying "You should get plenty of rest today. We recommend you drink plenty of water," or a similar message through the audio speaker.

[0215] Medical record updates

[0216] The server manages long-term health conditions by recording and updating the generated advice and diagnosis results in the user's individual medical record, allowing users to easily check their past health conditions and the advice they received.

[0217] Examples of concrete examples and prompts

[0218] For example, the following prompt could be input to a generative AI model:

[0219] Today's health data:

[0220] Headache: Yes

[0221] Sleep time: 6 hours

[0222] Caffeine intake: 2 cups

[0223] Stress level: High

[0224] Generate health advice for this user based on historical data and medical knowledge.

[0225] As described above, this system allows users to quickly and easily input and receive feedback on their health status through smart glasses in their daily lives, enabling more efficient and effective health management.

[0226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0227] Step 1:

[0228] User Registration:

[0229] A user puts on the smart glasses and begins signing up for the application by scanning a QR code displayed on the glasses with their smartphone for initial registration. They enter their information (name, age, gender, medical history, etc.) via voice and text. This data is sent to Firebase, and the server generates a user ID and notifies the user of that ID.

[0230] Input: Name, age, gender, medical history, etc.

[0231] Output: User ID

[0232] Step 2:

[0233] Login:

[0234] The user logs into the system via the smart glasses using the generated user ID and password, and the server authenticates this and allows the user to access their individual database.

[0235] Input: User ID, Password

[0236] Output: Authentication status, access rights

[0237] Step 3:

[0238] Enter your health status:

[0239] Users report their daily health status by voice using the microphone in their smart glasses. The voice data is converted into text data using the Google Cloud Speech-to-Text API. The text data is sent to Firebase and stored in the user's individual database. For example, if a user voice-inputs, "I have a slight headache today," that information is stored as text data.

[0240] Input: Speech data (e.g., "I have a slight headache today")

[0241] Output: Text data, information stored in the user database

[0242] Step 4:

[0243] Data Analysis:

[0244] The server periodically collects health status data stored in Firebase and performs data analysis using Python's pandas and scikit-learn. These tools are used to compare the data with historical data and general medical knowledge to identify specific patterns or trends, such as detecting frequent headaches or elevated stress levels.

[0245] Input: Health condition data (e.g., "headache" as text data)

[0246] Output: Analysis results (e.g., estimated cause of headache)

[0247] Step 5:

[0248] Advice Generation:

[0249] Based on the analysis results, the server generates appropriate advice using a generative AI model (such as the GPT-4 API). For example, if data analysis predicts that frequent headaches are caused by excessive caffeine intake, the server generates the advice, "It would be good to limit your caffeine intake and drink plenty of water."

[0250] Input: Analysis results (e.g., headache is caused by excessive caffeine intake)

[0251] Output: Generated advice (e.g., "Reduce your caffeine intake and drink plenty of water.")

[0252] Step 6:

[0253] Providing advice:

[0254] The generated advice is provided to the user in real time through the smart glasses as visual and audio notifications, such as a message on the smart glasses display saying "Avoid caffeine today" or a similar advice being spoken through the audio speaker.

[0255] Input: Generated advice

[0256] Output: Advice given to the user

[0257] Step 7:

[0258] Update medical records:

[0259] The server records and updates the generated advice and diagnosis results in the user's individual medical record, enabling long-term health management. Users can easily check their past health status and the advice they received.

[0260] Input: Generated advice, diagnostic results

[0261] Output: Updated user record

[0262] These steps will enable users to quickly and easily input and receive feedback on their health status through the smart glasses, enabling more effective long-term health management.

[0263] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0264] The present invention is a system that combines a conventional system that collects, stores, analyzes, and provides advice on a user's daily health status with an emotion engine that recognizes the user's emotions. This system makes it easier for users to manage their own health and emotional status, and supports the prevention of illness and the improvement of daily performance. Furthermore, by taking emotional information into account, it becomes possible to provide more personalized advice. Each major process in the embodiment of the present invention is specifically described below.

[0265] User Registration / Login

[0266] When a user uses the system for the first time, they enter their personal information and initial health status information. This data is sent from the device to the server, which stores it in a database. The server then generates a user ID and returns it to the device. From then on, the user can log in using this ID.

[0267] For example, when User A uses the system for the first time, he or she enters his or her name, age, gender, medical history, etc. This information is sent from the terminal to the server. The server then creates an individual medical record for User A based on this information, generates a user ID, and sends it back to the terminal. After logging in and completing the initial settings, User A can easily log in next time.

[0268] Daily questionnaire entry and emotion recognition

[0269] When a user inputs their physical condition and emotions for the day, they input information about their physical condition by voice or text. The device receives this input, converts it into text if it is voice, and sends it to the server. The device also uses an emotion engine to extract emotional information from the user's voice. The extracted emotional information is also sent to the server.

[0270] For example, if user B says, "I have a headache today and I'm a little irritated," the device converts this speech into text and uses the emotion engine to recognize the emotion "irritated." This data is then sent to the server.

[0271] Data collection and analysis

[0272] The server stores the received health condition and emotion information in a database. The stored data is then analyzed in conjunction with past data and general medical knowledge. For example, by comparing past health condition and emotion data, the cause of the health condition and the influence of emotions can be inferred.

[0273] For example, if User C frequently entered data on "headaches" and "irritability" in the past, the server would compare and analyze this past data with the current data. It may conclude that headaches are likely to occur in conjunction with emotional states.

[0274] Generating Advice

[0275] Based on the analysis results, the server generates specific and personalized advice for the user. By taking emotional information into account, more appropriate advice becomes possible. For example, in addition to the usual advice of "limit your caffeine intake and drink plenty of water today," the server can generate advice such as "try relaxation techniques to reduce stress."

[0276] If user D inputs data such as "I have a headache today and I'm feeling a little irritated," and the server determines from the analysis results that "stress is likely to be a contributing factor to the headache," the following personalized advice will be created.

[0277] Providing advice

[0278] The generated advice is provided to the user via the device, which then uses an AI speaker and chat interface to communicate specific advice to the user. The user can then receive this advice and apply it to their daily activities and health management.

[0279] For example, after User E inputs his / her morning physical condition, the AI ​​speaker will give him / her advice in voice, such as, "Avoid caffeine intake today and drink plenty of water. Also, I recommend taking deep breaths as a relaxation technique."

[0280] Medical record updates

[0281] The server records and updates the diagnosis results and advice for that day in the user's individual medical record. This allows users to easily understand their own health condition and emotional fluctuations over the long term. It also makes it possible to detect health trends and abnormalities early in the future.

[0282] For example, all health condition information entered by user F in the past month, advice provided, and emotional information are stored in a database, which can be used for future health management and medical consultations.

[0283] As described above, the system of the present invention effectively supports the management of a user's health and emotional state and the prevention of illness. Users can maintain and improve their health by simply inputting their daily physical condition and emotions, receiving analysis and advice from the server, and taking actions based on this information.

[0284] The processing flow will be explained below.

[0285] Step 1:

[0286] The user starts the application and accesses the user registration screen. The terminal displays the user registration form.

[0287] Step 2:

[0288] The user enters personal information such as name, age, gender, email address, chronic illnesses and allergies. The device temporarily stores the entered information and waits for the user to click the registration button.

[0289] Step 3:

[0290] The user clicks the registration button. The device sends the input information to the server.

[0291] Step 4:

[0292] The server stores the received information in a database, generates a user ID, and returns the generated user ID to the device.

[0293] Step 5:

[0294] The terminal receives the user ID and logs the user in. At this stage, the initial user settings are complete.

[0295] Step 6:

[0296] The user inputs their physical condition for the day by voice. The device converts the voice input into text data. The device also uses an emotion engine to extract emotional information from the user's voice.

[0297] Step 7:

[0298] The terminal transmits the converted text data and emotion data to the server. For example, if the user inputs "I have a headache today and I'm a little irritated," the text data and the emotion data "irritated" are transmitted to the server.

[0299] Step 8:

[0300] The server stores the received text data and emotion data in a database. New health status information and emotion information are added to the database.

[0301] Step 9:

[0302] The server analyzes the stored data in comparison with past data and general medical knowledge, for example, to identify the cause of headaches or consider the influence of emotions.

[0303] Step 10:

[0304] Based on the analysis results, the server generates specific advice for the user. For example, in addition to the usual advice of "limit your caffeine intake and drink plenty of water today," it generates advice such as "try relaxation techniques to reduce stress."

[0305] Step 11:

[0306] The server sends the generated advice to the terminal, which receives the advice.

[0307] Step 12:

[0308] The device will provide advice to the user through an AI speaker or chat interface. For example, the AI ​​speaker will tell the user, "Today, limit your caffeine intake and drink plenty of water. I also recommend taking deep breaths as a relaxation technique."

[0309] Step 13:

[0310] The server records and updates the diagnosis results and advice for that day in the user's individual medical record, enabling long-term health management.

[0311] Example 2

[0312] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0313] Conventional health management systems focus on collecting and analyzing users' health status information, but they are unable to consider users' emotional information, making it difficult to provide more personalized and accurate advice. Furthermore, by ignoring the impact of emotions on health status, important factors in user health management are often overlooked. As a result, prevention and performance improvement may not be sufficiently effective.

[0314] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving daily health condition information and emotional information from the user as voice or text data, means for storing the received health condition information and emotional information in a database, and means for comparing and analyzing the stored health condition information and emotional information with past data and general medical knowledge. This makes it possible to generate and provide more personalized and specific advice that takes the user's emotional information into consideration.

[0315] "User" refers to a person who utilizes the system to input and manage their own health and emotional state.

[0316] "Audio or text data" refers to an information format used by a user to express his or her health condition or emotional state, and is in the form of audio data or text data.

[0317] "Health status information" refers to data recorded by a user regarding their daily physical condition and symptoms.

[0318] "Emotion information" is data in which a user records their daily emotional state, and includes information about specific emotions (for example, happiness, sadness, anger, etc.).

[0319] "Database" refers to a system that stores and manages received health status information and emotional information over the long term.

[0320] "Historical Data" refers to health and emotional information previously collected from a user that is stored in the system.

[0321] "General medical knowledge" refers to the basic information based on medical knowledge and research results, which is used to analyze health conditions and generate advice.

[0322] "Analysis" refers to the process of analyzing the received and stored data to identify patterns and causes of the user's health and emotional state.

[0323] "Advice" refers to specific suggestions that are generated based on the analysis results and are useful for the user's lifestyle and health management.

[0324] "Medical Record" refers to a digital record for recording and storing a User's individual health and emotional information.

[0325] "Emotion engine" refers to software or algorithms for extracting emotional information from a user's voice or text data.

[0326] "Speech recognition technology" refers to technology that converts speech into text data and is used to process user speech input.

[0327] MODE FOR CARRYING OUT THE INVENTION

[0328] The present invention is a system that collects and analyzes a user's daily health and emotional state to provide personalized advice. The system receives voice or text data entered by the user, stores it in a database, and compares and analyzes it with past data and general medical knowledge.

[0329] User Registration / Login

[0330] When a user uses the system for the first time, they enter their personal information (name, age, gender, medical history, etc.) into the terminal. The terminal checks the entered data to see if there are any omissions or errors. Next, the terminal sends the user's registration information to the server, which stores the received data in a database. The server generates a new user ID and returns it to the terminal. From then on, the user can log in to the system using this user ID.

[0331] Examples:

[0332] User A uses the system for the first time and enters his / her name, age, and gender. The device sends the input data to the server, which saves the data and then generates a user ID and sends it back to the device. User A can then easily log in using the generated ID from the next time.

[0333] Daily questionnaire entry and emotion recognition

[0334] The user inputs their physical and emotional state for the day into the device by voice or text. The device uses voice recognition technology (e.g., Google Cloud Speech-to-Text) to convert the voice input into text. Next, the device uses an emotion engine (e.g., IBM Watson® Tone Analyzer) to recognize emotions from the input information and format the recognition results along with the text. Finally, the device sends the formatted physical and emotional information to the server.

[0335] Examples:

[0336] When User B says, "I have a headache today and I'm a little irritated," the device converts the speech into text and sends it to the server, where the emotion engine analyzes the emotion "irritated." This data is then sent to the server.

[0337] Data collection and analysis

[0338] The server receives and stores the received health and emotional information in a database, assigning a timestamp to the data and managing it in chronological order. The server then analyzes the stored data using an analysis engine (e.g., using Python's pandas library) and compares it with past data to identify patterns in health and emotional states.

[0339] Examples:

[0340] If User C frequently inputs past data on "headaches" and "irritability," the server compares and analyzes this data to identify the frequency and timing of these events. For example, it identifies that these events frequently occur during certain times of the day or in certain situations.

[0341] Generating and providing advice

[0342] The server generates appropriate advice for the user based on the analysis results, taking emotional information into account and suggesting stress management methods or specific actions (e.g., "Try taking deep breaths to relax"). The generated advice is sent to the device, which then communicates it to the user using an AI speaker or chat interface.

[0343] Examples:

[0344] After User D inputs his / her morning physical condition, the AI ​​speaker provides audio advice such as, "Today, limit your caffeine intake and drink plenty of water. Also, I recommend taking deep breaths as a relaxation technique."

[0345] Medical record updates

[0346] The server records the results of that day's diagnosis and advice based on that result in the user's medical record, allowing the user to understand their own health condition and emotional fluctuations over the long term.

[0347] Examples:

[0348] User F's health condition data, emotional data, and provided advice for the past month are organized and stored in a database. The server uses this information to understand the user's health trends.

[0349] Prompt Sentence Examples

[0350] "When a user inputs their emotions and health status, the system converts that information into text, extracts emotional information using an emotion engine, records it in an individual medical record, and provides appropriate advice based on the analysis results. For example, if you input, 'I have a headache today and I'm a little irritated,' the device converts the speech into text, the emotion engine recognizes the irritation, the server analyzes it, and generates appropriate advice."

[0351] This system aims to support users' daily health management, prevent illness, and improve daily performance.

[0352] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0353] System program processing steps

[0354] Step 1: Enter your user registration information

[0355] 1. The user enters personal information such as their name, age, gender, and medical history into the device.

[0356] 2. The terminal checks the entered data to make sure there are no missing or incorrect information.

[0357] 3. Input: User's personal information (name, age, gender, medical history, etc.)

[0358] 4. Output: Checked user personal information

[0359] Examples:

[0360] User A uses the system for the first time and enters his / her name, age, gender, medical history, etc. The terminal checks this information to make sure there are no errors.

[0361] Step 2: Sending data

[0362] 1. The device sends the checked user personal information to the server.

[0363] 2. Use HTTPS as the data transmission protocol to ensure secure communication.

[0364] 3. Input: Checked user personal information

[0365] 4. Output: User personal information sent to the server

[0366] Examples:

[0367] User A's personal information is sent from the terminal to the server via secure communication.

[0368] Step 3: Generate and return a user ID

[0369] 1. The server stores the received user personal information in a database.

[0370] 2. The server generates a new user ID and returns it to the device.

[0371] 3. Input: User personal information sent to the server

[0372] 4. Output: Generated user ID (returned to the terminal)

[0373] Examples:

[0374] The server saves User A's information in a database, generates a user ID, and returns it to the terminal. User A will use this ID from the next time.

[0375] Step 4: Fill out the daily questionnaire

[0376] 1. The user inputs their health condition and emotions for the day into the device by voice or text.

[0377] 2. If the device supports voice input, convert the voice to text (using voice recognition technology).

[0378] 3. Input: User voice or text data

[0379] 4. Output: Data converted to text (in the case of voice input)

[0380] Examples:

[0381] User B speaks, "I have a headache today and I'm feeling a little irritated," and the device converts this into text using voice recognition technology.

[0382] Step 5: Extracting emotional information

[0383] 1. The device uses an emotion engine to recognize emotions from input information.

[0384] 2. Format the recognition results along with the text.

[0385] 3. Input: Data converted to text

[0386] 4. Output: Formatted physical condition information and emotional information

[0387] Examples:

[0388] The text converted from user B's voice data as "I have a headache today and I'm a little irritated" and the emotional information "irritated" extracted by the emotion engine are formatted.

[0389] Step 6: Sending data

[0390] 1. The device sends the formatted physical condition information and emotional information to the server.

[0391] 2. Input: Formatted physical condition information and emotional information

[0392] 3. Output: Physical condition and emotional information sent to the server

[0393] Examples:

[0394] The device transmits user B's physical condition information and emotional information to the server.

[0395] Step 7: Save your data

[0396] 1. The server stores the received physical condition information and emotional information in a database.

[0397] 2. Stored data is time-stamped and managed in chronological order.

[0398] 3. Input: Physical condition and emotional information sent to the server

[0399] 4. Output: Physical condition and emotional information stored in the database

[0400] Examples:

[0401] The server stores user B's physical condition and emotional information in a database and assigns a timestamp.

[0402] Step 8: Data analysis

[0403] 1. The server analyzes the stored data using an analytical engine.

[0404] 2. Compare with historical data to identify patterns in your health and emotions.

[0405] 3. Input: Physical condition information and emotional information in the database

[0406] 4. Output: Analysis results

[0407] Examples:

[0408] Analyze User C's data from the past month and identify the relationship between "headache" and "irritability."

[0409] Step 9: Generating Advice

[0410] 1. The server generates specific advice appropriate for the user based on the analysis results.

[0411] 2. Consider emotional information and suggest stress management strategies and specific actions.

[0412] 3. Input: Analysis results

[0413] 4. Output: Specific advice

[0414] Examples:

[0415] The server generates advice such as, "Reduce your caffeine intake today and drink plenty of water. Try deep breathing as a relaxation technique."

[0416] Step 10: Providing advice

[0417] 1. The generated advice is sent from the server to the device.

[0418] 2. The device uses an AI speaker or chat interface to provide advice to the user.

[0419] 3. Input: Specific advice

[0420] 4. Output: Advice provided to the user

[0421] Examples:

[0422] The AI ​​speaker tells User D, "Reduce your caffeine intake and drink plenty of water. We also recommend taking deep breaths as a relaxation technique."

[0423] Step 11: Update the medical record

[0424] 1. The server records the day's diagnosis results and advice in the user's medical record.

[0425] 2. Allow users to understand fluctuations in their health status over the long term.

[0426] 3. Input: Physical condition information, emotional information, diagnosis results, and advice stored on the server

[0427] 4. Output: Updated medical record

[0428] Examples:

[0429] The server updates and records the health condition, emotional information, diagnosis results, and advice for the past month in the medical record of user F.

[0430] (Application example 2)

[0431] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0432] Conventional health management systems provide advice by collecting and analyzing a user's daily health status, but they do not take the user's emotional state into account, making it difficult to provide personalized advice. Furthermore, there is no mechanism for providing personalized content, and appropriate support based on the user's emotional and health status is not adequately provided. Therefore, there is a need for a system that comprehensively considers both the user's health status and emotional state to provide personalized advice and content.

[0433] The identification process by the identification 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 receiving daily health condition information and emotional information from the user as voice or text data; means for storing the received health condition information and emotional information in a database; means for comparing and analyzing the stored health condition information and emotional information with past data and general medical knowledge; means for generating specific advice for the user based on the analysis results and providing personalized content according to the user's emotional state; means for providing the generated advice and personalized content to the user; and means for recording and updating the generated advice, diagnosis results, and provided content in the user's individual medical record. This makes it possible to comprehensively evaluate both the user's health condition and emotional state and provide more appropriate and individualized advice and personalized content.

[0434] "Audio or text data" is data that provides health and emotional information in audio or text form for a user to input into the system.

[0435] "Health status information" refers to information about the user's physical condition and symptoms, and is data used for daily health management and diagnosis.

[0436] "Emotional information" refers to information about a user's emotions and psychological state, and is data used to understand the user's emotional state.

[0437] "Database" means a system or location for systematically storing and managing health status information and emotional information collected from users.

[0438] "Means for comparison and analysis" refers to methods and technologies for comparing stored health status information and emotional information with historical data and general medical knowledge to evaluate and analyze the user's condition.

[0439] "Means for generating advice" refers to methods and techniques for generating specific and personalized advice for a user based on the results of the comparison and analysis.

[0440] "Means for providing personalized content" refers to methods and technologies for selecting and providing specific content (e.g., videos, music, articles, etc.) to users based on their emotional state.

[0441] "Individual User's Medical Record" means an individual record for recording and updating each user's health status information and emotional information, as well as advice and provided content based on that information.

[0442] To implement this invention, it is necessary to build a system that allows users to input daily health status information and emotional information using a device such as a smartphone or smart glasses, analyzes the information, and provides personalized advice and content. A specific example of this is shown below.

[0443] User Registration / Login

[0444] When a user uses the system for the first time, they enter their personal information and initial health information. This information is sent from the device to the server, which then stores it in a database. The server generates a user ID and sends it back to the device, allowing the user to easily log in from the next time onwards. For example, when a user enters their name, age, gender, and medical history, all of this information is sent to the server, and an individual medical record is created.

[0445] Input and recognition of daily health status and emotional information

[0446] The user inputs their physical condition and emotions for the day in voice or text format. In the case of voice input, the device converts the voice into text data, and then the emotion engine extracts the emotional information. For example, if the user inputs, "I have a headache today and I'm a little irritated," the device converts this voice data into text, recognizes the emotional information of "irritation," and sends this data to the server.

[0447] Data collection and analysis

[0448] The server stores the received health condition information and emotional information in a database. The stored data is then analyzed against past data and general medical knowledge. This data is compared with the user's past health condition and emotional data to infer the cause of the health condition and the influence of emotions. For example, if a user frequently entered data on "headaches" and "irritability" in the past, comparing and analyzing this data can explore the possibility that headaches are linked to emotions.

[0449] Advice and content generation

[0450] Based on the analysis results, the server generates specific and individualized advice for the user, while also providing personalized content according to the user's emotional state. For example, if the user is feeling stressed, relaxation music or meditation videos will be recommended. An example of advice might be, "Today, you should limit your caffeine intake, drink plenty of water, and try relaxation techniques to reduce stress."

[0451] Providing advice and content

[0452] The provided advice and content is communicated to the user via a device. The device can be a smartphone or smart glasses, and these devices provide information to the user through audio and visual means. For example, after the user enters their physical condition information, the AI ​​speaker can provide audio advice such as, "Reduce your caffeine intake today and drink more fluids. We also recommend taking deep breaths as a relaxation technique."

[0453] Medical record updates

[0454] The server records and updates the advice and diagnosis results provided, as well as the history of personalized content provided, in each user's individual medical record. This makes it easier for users to understand their own health condition and emotional fluctuations over the long term, which is useful for future health management and medical consultations. For example, users can record their health condition and emotional fluctuations over the past month and receive advice based on that information at a glance.

[0455] Usage example

[0456] The user launches the app and enters a prompt like this:

[0457] Example prompt: "I have a headache today and I'm feeling a bit irritable."

[0458] Based on the prompts, the system first converts the voice to text, analyzes emotions, and sends the received data to a server, which then analyzes it based on past data and general medical knowledge to generate personalized content, such as specific advice and relaxation music, and delivers it to the user.

[0459] This allows users to improve their health while also taking care of their emotions, improving the quality of their daily lives.

[0460] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0461] Step 1:

[0462] Users use their smartphones or smart glasses to register their personal information and initial health status information, including name, age, gender, medical history, etc. The entered data is sent from the device to the server. The input is in text format, and the server stores it in a database and generates a user ID, which is returned to the device.

[0463] Step 2:

[0464] The user inputs their daily health condition and emotional information into the device. For example, they can input a prompt phrase such as "I have a headache today and I'm a little irritated" by voice. This voice data is converted into text data by the device, and the emotional information is extracted by the emotion engine. The extracted data (health condition information and emotional information) is sent to the server.

[0465] Step 3:

[0466] The server then stores the received health condition and emotional information in a database. This data is compared with similar past data and analyzed against general medical knowledge. For example, the frequency and correlation between "headaches" and "irritability" can be analyzed to infer the causes of health conditions and the influence of emotions.

[0467] Step 4:

[0468] Based on the analysis results, the server generates specific and personalized advice for the user. At the same time, it selects personalized content (e.g., relaxation music or meditation videos) according to the user's emotional state. The generated advice and content are intended to optimally manage the user's health and emotional state.

[0469] Step 5:

[0470] The generated advice and personalized content are then delivered to the user via the device. The smartphone or smart glasses process this information and provide the user with visual or audio information. For example, the device might say, "Today, we recommend limiting your caffeine intake and drinking plenty of water. We also recommend taking deep breaths as a relaxation technique."

[0471] Step 6:

[0472] The server records and updates the history of the advice and content provided in the user's individual medical record. This medical record will be used to understand the user's long-term health and emotional state fluctuations and for future medical consultations and health management. For example, the fluctuations in health and emotional state over the past month can be visualized and saved as graphs.

[0473] This allows users to comprehensively manage their health and emotional state, and improve their quality of life with appropriate advice and content.

[0474] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0475] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0476] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0477] [Second embodiment]

[0478] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0479] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0480] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0481] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0482] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0483] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0484] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0485] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0486] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0487] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0488] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0489] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0490] The present invention is a system that collects, stores, analyzes, and provides advice on a user's daily health status. This system makes it easier for users to manage their own health status and supports the prevention of illness and the improvement of daily performance. To implement the present invention, a program based on the following processing steps is generated, and the operation of each step is explained in detail. Each major process is explained below.

[0491] User Registration / Login

[0492] When a user uses the system for the first time, they enter their personal information and initial health status information. This data is sent from the device to the server, which stores it in a database. The server then generates a user ID and returns it to the device. From then on, the user can log in using this ID.

[0493] For example, when User A uses the system for the first time, he or she enters his or her name, age, gender, medical history, etc. This information is sent from the terminal to the server. The server then creates an individual medical record for User A based on this information, generates a user ID, and sends it back to the terminal. After logging in and completing the initial settings, User A can easily log in next time.

[0494] Daily medical questionnaire entry

[0495] When a user inputs their health status for the day, they input information about their health status by voice or text. The device receives this input, converts it into text if it is voice, and sends it to the server. The server stores this information in a database for later analysis.

[0496] For example, if user B says "I have a headache today," the device converts this speech into text and sends it to the server. The server receives the text information "headache" and stores it in user B's health database.

[0497] Data collection and analysis

[0498] The server compares and analyzes the received data with past data and general medical knowledge. For example, it compares it with other data from a time when headaches were frequent in the past to infer the cause. It also compares it with general medical knowledge to find likely causes and countermeasures.

[0499] For example, if User C has frequently entered "headache" data in the past, the server compares and analyzes this past data with the current data, identifying past patterns and triggering factors (such as climate change or stress levels), and performs a detailed analysis based on general medical knowledge.

[0500] Generating Advice

[0501] The server generates specific advice for the user based on the analysis results. For example, if the accumulated data indicates that a headache is caused by caffeine intake or lack of sleep, the server generates advice such as "Reduce your caffeine intake today and drink plenty of water."

[0502] If User D inputs "I have a headache today," and the server determines through analysis that "it's likely due to caffeine intake," the generated advice will read, "Reduce your caffeine intake today and drink plenty of water." This advice will be provided to User D via the terminal.

[0503] Providing advice

[0504] The generated advice is provided to the user via the device, which then communicates it to the user using an AI speaker or chat interface. The user can then receive this advice and use it in their daily activities and health management.

[0505] For example, after user E enters their morning physical condition, the AI ​​speaker will provide voice advice such as, "It would be good for you to get plenty of rest today. I recommend you drink plenty of water."

[0506] Medical record updates

[0507] The server records and updates the advice and diagnosis results provided that day in the user's individual medical record, making it easier for users to understand their own health condition over the long term. It also makes it possible to detect health trends and abnormalities early in the future.

[0508] For example, all health information entered by user F over the past month and advice provided can be stored in a database and used for future health management and medical consultations.

[0509] As described above, the system of the present invention effectively supports the user's health management and prevention of illness. Users can maintain and improve their health by simply inputting their daily physical condition, receiving analysis and advice from the server, and taking actions based on this information.

[0510] The processing flow will be explained below.

[0511] Step 1:

[0512] The user starts the application and accesses the user registration screen. The terminal displays the user registration form.

[0513] Step 2:

[0514] The user enters personal information such as name, age, gender, email address, chronic illnesses and allergies. The device temporarily stores the entered information and waits for the user to click the registration button.

[0515] Step 3:

[0516] The user clicks the registration button. The device sends the input information to the server.

[0517] Step 4:

[0518] The server stores the received information in a database, generates a user ID, and returns the generated user ID to the device.

[0519] Step 5:

[0520] The terminal receives the user ID and logs the user in. At this stage, the initial user settings are complete.

[0521] Step 6:

[0522] The user inputs their physical condition for the day by voice, and the device converts the voice input into text data.

[0523] Step 7:

[0524] The terminal transmits the converted text data to the server. For example, if the user inputs "I have a headache today," the text data is transmitted to the server.

[0525] Step 8:

[0526] The server stores the received text data in a database. New health status information is added to the database.

[0527] Step 9:

[0528] The server compares and analyzes the stored data with past data and general medical knowledge, for example, to identify the cause of headaches and consider general countermeasures.

[0529] Step 10:

[0530] Based on the analysis results, the server generates specific advice for the user, such as "Reduce your caffeine intake today and drink plenty of water."

[0531] Step 11:

[0532] The server sends the generated advice to the terminal, which receives the advice.

[0533] Step 12:

[0534] The device will provide advice to the user through an AI speaker or chat interface, for example, the AI ​​speaker will tell the user to "limit your caffeine intake today and drink plenty of water."

[0535] Step 13:

[0536] The server records and updates the diagnosis results and advice for that day in the user's individual medical record, enabling long-term health management.

[0537] Example 1

[0538] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0539] In modern society, individual health management is extremely important, and there is a growing need for methods to efficiently collect and analyze this information and provide appropriate advice. However, conventional systems have limitations in effectively collecting and analyzing users' health status information and providing appropriate advice, particularly in terms of comparison and analysis with past data and general medical knowledge. Furthermore, there is a lack of methods for generating appropriate advice using generative AI models and for reliably providing this advice to users. These issues are being addressed.

[0540] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0541] In this invention, the server includes means for receiving daily health condition information from a user as voice or text data, means for storing the received health condition information in a database, means for comparing and analyzing the stored health condition information with past data and general medical knowledge, means for generating specific advice for the user based on the analysis results using a generative AI model, means for providing the generated advice to the user, and means for recording and updating the generated advice and diagnosis results in the user's individual medical record. This makes it possible to efficiently collect, compare, and analyze a user's health condition information, and generate and provide appropriate advice.

[0542] "User" refers to each individual who uses the system.

[0543] "Voice data" refers to data containing health information provided by a user through voice input.

[0544] "Text data" refers to data including health condition information provided by the user through character input.

[0545] "Means for receiving" refers to means for obtaining voice or text data from a user within the system.

[0546] "Database" refers to a structured collection of data for storing received health status information.

[0547] "Means for storing" refers to the system's ability to record received health status information in a database.

[0548] "Means for comparison and analysis" refers to the function of comparing stored data with past data and general medical knowledge and analyzing the information.

[0549] "Generative AI model" refers to an artificial intelligence model used to generate specific advice for users based on the results of data analysis.

[0550] "Means for generating advice" refers to the system's function of using a generative AI model to create specific advice from the analysis results.

[0551] The "means for providing advice" refers to a function for displaying or notifying the user of the generated advice.

[0552] A "medical record" refers to an individual health record that includes a user's health status information, past diagnostic results, advice information, etc.

[0553] "Means of recording and updating" refers to the system's functionality for adding advice and diagnostic results generated each day to a user's individual chart and keeping it up to date.

[0554] The present invention is a system for collecting and analyzing a user's daily health condition and providing appropriate advice based on the collected data. Specific embodiments of this system will be described below.

[0555] The system includes the following main components: a terminal, a server, a database, and a generative AI model.

[0556] User Registration / Login

[0557] When a user uses the system for the first time, they use a terminal to enter their personal information and initial health information. For example, the user enters their name, age, gender, medical history, etc., and the terminal sends this data to the server. The server stores the received data in a database and generates a user ID. This user ID is returned to the terminal, and the user can use this ID to log in from the next time onwards.

[0558] Daily medical questionnaire entry

[0559] To record their daily health status, users use the device to input information by voice or text. In the case of voice input, the device uses the Google Cloud Speech-to-Text API to convert the voice to text. The converted text data is sent to a server, which then stores it in a database.

[0560] Data collection and analysis

[0561] The server compares and analyzes the received data with past data and general medical knowledge. Specifically, the server retrieves past data from the database and compares it using a Python data analysis library (e.g., Pandas). It then analyzes the data using a natural language processing library (e.g., NLTK) to identify likely causes and countermeasures.

[0562] Generating Advice

[0563] Based on the results of the comparison and analysis, the server uses a generative AI model (such as GPT-4) to generate specific advice for the user. For example, if a comparison of past data determines that caffeine intake is the cause, the generated advice might include "limit your caffeine intake today and drink plenty of water."

[0564] Providing advice

[0565] The generated advice is provided to the user via the device, which then communicates the advice to the user as a notification or voice message. Specifically, the advice is provided via the notification function of Android or iOS devices or an AI speaker.

[0566] Medical record updates

[0567] The server records and updates the advice and diagnosis results generated that day in the user's medical record. This allows the user to easily understand long-term fluctuations in their health condition and the recurrence of certain symptoms. The server also uses this information to contribute to future health management and early detection of abnormalities.

[0568] Examples of concrete examples and prompts

[0569] For example, if User A says, "I have a headache today," the device converts the voice input into text and sends it to the server. The server then analyzes the data based on past health data and general medical knowledge. Using the generative AI model based on the analysis results, the server generates advice such as "Reduce your caffeine intake and drink plenty of water today," which is then provided to User A via the device. This is important information that the user can use to improve their future behavior and health management.

[0570] An example prompt is:

[0571] "What AI model would you use to analyze what advice should be generated after a user types, 'I have a headache today,' and provide an example of the advice you would generate?"

[0572] By linking these functions, this system will efficiently and effectively support users in managing their health.

[0573] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0574] Step 1:

[0575] The user enters personal information the first time they use the service.

[0576] The user starts the application and enters personal information such as name, age, gender, and medical history into the registration screen. Input data: Name, age, gender, medical history

[0577] Output data: Personal information input data

[0578] Step 2:

[0579] The device sends the input data to the server

[0580] The device sends the entered personal information to the server via an HTTP request. Specifically, it posts the data using an HTTP client library. Input data: Personal information input data

[0581] Output data: Status of completion of sending to server

[0582] Step 3:

[0583] The server saves the user's data to the database and generates a user ID.

[0584] The server saves the received data in a database (e.g. MySQL) using the INSERT statement and generates a new user ID. Input data: Input data of personal information

[0585] Output: Generated user ID

[0586] Step 4:

[0587] The server returns the generated user ID to the device.

[0588] The server returns an HTTP response containing the generated user ID to the terminal. Specifically, a status code of 200 and JSON data containing the user ID are returned. Input data: Generated user ID

[0589] Output data: User ID response data

[0590] Step 5:

[0591] The user will then log in with the generated user ID.

[0592] The next time the user logs in, they will be authenticated using their user ID and password. Input data: User ID, password

[0593] Output data: Authentication success / failure status

[0594] Step 6:

[0595] The user inputs their daily physical condition by voice or text.

[0596] The user opens the app's questionnaire screen and records their physical condition for the day by voice or text. Input data: Voice or text physical condition data

[0597] Output data: Converted text data

[0598] Step 7:

[0599] Your device converts your voice input into text

[0600] The device uses the Google Cloud Speech-to-Text API to convert voice input into text. Input data: Voice data

[0601] Output data: Text data

[0602] Step 8:

[0603] The device sends the converted text data to the server.

[0604] The converted text data is sent from the terminal to the server via an HTTP request. Input data: Text data

[0605] Output data: Status of completion of sending to server

[0606] Step 9:

[0607] The server stores the received data in the database

[0608] The server saves the received data in the user's database. This also uses the MySQL INSERT statement. Input data: Text data

[0609] Output data: Status of completion of saving to database

[0610] Step 10:

[0611] The server retrieves the received data from the database

[0612] The server retrieves past health data from the database using a SELECT statement. Input data: User ID

[0613] Output data: Past health data

[0614] Step 11:

[0615] The server compares past data with current data

[0616] The server compares the past and current data using a Python data analysis library (e.g., Pandas). Input data: past health data, current health data

[0617] Output data: Comparison results

[0618] Step 12:

[0619] The server analyzes the comparison results against general medical knowledge

[0620] The server uses a natural language processing library (e.g., NLTK) to analyze the comparison results against general medical knowledge. Input data: Comparison results, medical knowledge data

[0621] Output data: Analysis results

[0622] Step 13:

[0623] The server generates advice based on the analysis results.

[0624] The server generates specific advice using a generative AI model (e.g., GPT-4) based on the analysis results. Input data: Analysis results

[0625] Output data: Generated advice

[0626] Step 14:

[0627] Sends server-generated advice to the device

[0628] The generated advice is sent to the terminal in JSON format. Input data: Generated advice

[0629] Output data: Status of completion of transmission to the terminal

[0630] Step 15:

[0631] The device displays or reads the generated advice to the user.

[0632] The device notifies the user of the advice using the app's notification function or voice alert function.

[0633] Output data: Notification content to the user

[0634] Step 16:

[0635] The server records and updates the diagnosis results and advice for that day in the patient chart.

[0636] The server saves the diagnosis results and advice for the day in the user's chart and updates it to the latest version. Input data: diagnosis results, advice

[0637] Output data: Updated medical record data

[0638] (Application example 1)

[0639] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0640] Conventional health management systems allow users to input their own health status and receive advice based on the analysis results. However, these systems rely on devices such as smartphones and computers, and users may not always have easy access to these devices. In addition, there are limitations to voice input and real-time notification functions, which can reduce the convenience of health management. This has made it difficult for users to quickly and appropriately manage their health in their daily lives.

[0641] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0642] In this invention, the server includes: means for receiving daily health condition information from a user as voice or text data; means for storing the received health condition information in a database; means for comparing and analyzing the stored health condition information with past data and general medical knowledge; means for generating specific advice for the user based on the analysis results; means for providing the generated advice to the user; means for recording and updating the generated advice and diagnosis results in the user's individual medical record; and means for receiving health condition information from the user using smart glasses and providing the information as visual or audio notifications, thereby enabling users to quickly and easily input and receive feedback on their health condition via the smart glasses in their daily lives.

[0643] "Health condition information" refers to information related to the user's physical condition and health, such as data on body temperature, blood pressure, whether or not the user has a headache, and sleep duration.

[0644] "Voice or Text Data" means information provided by a User through spoken or written input.

[0645] "Database" means a system for systematically storing and managing health status information and user information.

[0646] "Comparison and analysis" refers to the process of evaluating stored data using statistical methods and machine learning algorithms to derive meaningful results.

[0647] "Specific advice" means specific suggestions or instructions generated based on analyzed data that can help the user improve or maintain their health.

[0648] "Means for providing to the user" means a mechanism for conveying the generated advice to the user through audio notification or visual display.

[0649] "Medical Record" means a digital file that records a user's individual health status information, diagnostic results, and the history of advice provided.

[0650] "Smart glasses" refers to a wearable device that has built-in functions such as information display and voice input, and that allows users to integrate digital information with the physical world when wearing it.

[0651] "Visual or audio notification" means a method of providing information to a user through a display or audio speaker.

[0652] To realize this invention, a system in which a user, a server, and smart glasses work together is required. A specific embodiment of this system will be described below.

[0653] Hardware and software used

[0654] Hardware:

[0655] Smart glasses: Wearable devices with functions such as information display and voice input. Examples include Google Glass and Vuzix Blade.

[0656] Server: A central processing unit that receives, stores, analyzes data, and generates advice.

[0657] software:

[0658] Speech Recognition: Converts voice input into text data using the Google Cloud Speech-to-Text API.

[0659] Database: Firebase is used to store user health and personal information.

[0660] Data analysis: Compare and analyze data using Python's pandas and scikit-learn.

[0661] Advice generation: Using a generative AI model (e.g., GPT-4 API), specific advice is generated based on the analysis results.

[0662] System Operation

[0663] User Registration and Login

[0664] When a user uses the system for the first time, they scan the QR code displayed on the smart glasses screen with their smartphone to sign up for the application. The user enters information such as their name, age, gender, and medical history by voice or text, and this data is sent to Firebase. Once registration is complete, the server generates a user ID and notifies the user. From then on, the user logs in to the system using this ID.

[0665] Enter your health status

[0666] To input their daily health status, users can use the microphone in their smart glasses to voice-report their health status. For example, if they say, "I have a slight headache today," the smart glasses will convert this voice data into text data using the Google Cloud Speech-to-Text API. The text data will then be sent to Firebase and stored in the user's individual database.

[0667] Data analysis and advice generation

[0668] The server periodically collects health status data stored in Firebase and analyzes it using Python's pandas and scikit-learn. Based on the analysis results, a generative AI model (such as the GPT-4 API) is used to generate specific advice appropriate for the user. For example, if the data indicates frequent headaches or elevated stress levels, the server generates advice such as "It would be a good idea to limit caffeine and drink more water today."

[0669] Providing advice

[0670] The generated advice is provided to the user in real time via the smart glasses as a visual or audio notification, such as a message on the smart glasses display saying "You should get plenty of rest today. We recommend you drink plenty of water," or a similar message through the audio speaker.

[0671] Medical record updates

[0672] The server manages long-term health conditions by recording and updating the generated advice and diagnosis results in the user's individual medical record, allowing users to easily check their past health conditions and the advice they received.

[0673] Examples of concrete examples and prompts

[0674] For example, the following prompt could be input to a generative AI model:

[0675] Today's health data:

[0676] Headache: Yes

[0677] Sleep time: 6 hours

[0678] Caffeine intake: 2 cups

[0679] Stress level: High

[0680] Generate health advice for this user based on historical data and medical knowledge.

[0681] As described above, this system allows users to quickly and easily input and receive feedback on their health status through smart glasses in their daily lives, enabling more efficient and effective health management.

[0682] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0683] Step 1:

[0684] User Registration:

[0685] A user puts on the smart glasses and begins signing up for the application by scanning a QR code displayed on the glasses with their smartphone for initial registration. They enter their information (name, age, gender, medical history, etc.) via voice and text. This data is sent to Firebase, and the server generates a user ID and notifies the user of that ID.

[0686] Input: Name, age, gender, medical history, etc.

[0687] Output: User ID

[0688] Step 2:

[0689] Login:

[0690] The user logs into the system via the smart glasses using the generated user ID and password, and the server authenticates this and allows the user to access their individual database.

[0691] Input: User ID, Password

[0692] Output: Authentication status, access rights

[0693] Step 3:

[0694] Enter your health status:

[0695] Users report their daily health status by voice using the microphone in their smart glasses. The voice data is converted into text data using the Google Cloud Speech-to-Text API. The text data is sent to Firebase and stored in the user's individual database. For example, if a user voice-inputs, "I have a slight headache today," that information is stored as text data.

[0696] Input: Speech data (e.g., "I have a slight headache today")

[0697] Output: Text data, information stored in the user database

[0698] Step 4:

[0699] Data Analysis:

[0700] The server periodically collects health status data stored in Firebase and performs data analysis using Python's pandas and scikit-learn. These tools are used to compare the data with historical data and general medical knowledge to identify specific patterns or trends, such as detecting frequent headaches or elevated stress levels.

[0701] Input: Health condition data (e.g., "headache" as text data)

[0702] Output: Analysis results (e.g., estimated cause of headache)

[0703] Step 5:

[0704] Advice Generation:

[0705] Based on the analysis results, the server generates appropriate advice using a generative AI model (such as the GPT-4 API). For example, if data analysis predicts that frequent headaches are caused by excessive caffeine intake, the server generates the advice, "It would be good to limit your caffeine intake and drink plenty of water."

[0706] Input: Analysis results (e.g., headache is caused by excessive caffeine intake)

[0707] Output: Generated advice (e.g., "Reduce your caffeine intake and drink plenty of water.")

[0708] Step 6:

[0709] Providing advice:

[0710] The generated advice is provided to the user in real time through the smart glasses as visual and audio notifications, such as a message on the smart glasses display saying "Avoid caffeine today" or a similar advice being spoken through the audio speaker.

[0711] Input: Generated advice

[0712] Output: Advice given to the user

[0713] Step 7:

[0714] Update medical records:

[0715] The server records and updates the generated advice and diagnosis results in the user's individual medical record, enabling long-term health management. Users can easily check their past health status and the advice they received.

[0716] Input: Generated advice, diagnostic results

[0717] Output: Updated user record

[0718] These steps will enable users to quickly and easily input and receive feedback on their health status through the smart glasses, enabling more effective long-term health management.

[0719] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0720] The present invention is a system that combines a conventional system that collects, stores, analyzes, and provides advice on a user's daily health status with an emotion engine that recognizes the user's emotions. This system makes it easier for users to manage their own health and emotional status, and supports the prevention of illness and the improvement of daily performance. Furthermore, by taking emotional information into account, it becomes possible to provide more personalized advice. Each major process in the embodiment of the present invention is specifically described below.

[0721] User Registration / Login

[0722] When a user uses the system for the first time, they enter their personal information and initial health status information. This data is sent from the device to the server, which stores it in a database. The server then generates a user ID and returns it to the device. From then on, the user can log in using this ID.

[0723] For example, when User A uses the system for the first time, he or she enters his or her name, age, gender, medical history, etc. This information is sent from the terminal to the server. The server then creates an individual medical record for User A based on this information, generates a user ID, and sends it back to the terminal. After logging in and completing the initial settings, User A can easily log in next time.

[0724] Daily questionnaire entry and emotion recognition

[0725] When a user inputs their physical condition and emotions for the day, they input information about their physical condition by voice or text. The device receives this input, converts it into text if it is voice, and sends it to the server. The device also uses an emotion engine to extract emotional information from the user's voice. The extracted emotional information is also sent to the server.

[0726] For example, if user B says, "I have a headache today and I'm a little irritated," the device converts this speech into text and uses the emotion engine to recognize the emotion "irritated." This data is then sent to the server.

[0727] Data collection and analysis

[0728] The server stores the received health condition and emotion information in a database. The stored data is then analyzed in conjunction with past data and general medical knowledge. For example, by comparing past health condition and emotion data, the cause of the health condition and the influence of emotions can be inferred.

[0729] For example, if User C frequently entered data on "headaches" and "irritability" in the past, the server would compare and analyze this past data with the current data. It may conclude that headaches are likely to occur in conjunction with emotional states.

[0730] Generating Advice

[0731] Based on the analysis results, the server generates specific and personalized advice for the user. By taking emotional information into account, more appropriate advice becomes possible. For example, in addition to the usual advice of "limit your caffeine intake and drink plenty of water today," the server can generate advice such as "try relaxation techniques to reduce stress."

[0732] If user D inputs data such as "I have a headache today and I'm feeling a little irritated," and the server determines from the analysis results that "stress is likely to be a contributing factor to the headache," the following personalized advice will be created.

[0733] Providing advice

[0734] The generated advice is provided to the user via the device, which then uses an AI speaker and chat interface to communicate specific advice to the user. The user can then receive this advice and apply it to their daily activities and health management.

[0735] For example, after User E inputs his / her morning physical condition, the AI ​​speaker will give him / her advice in voice, such as, "Avoid caffeine intake today and drink plenty of water. Also, I recommend taking deep breaths as a relaxation technique."

[0736] Medical record updates

[0737] The server records and updates the diagnosis results and advice for that day in the user's individual medical record. This allows users to easily understand their own health condition and emotional fluctuations over the long term. It also makes it possible to detect health trends and abnormalities early in the future.

[0738] For example, all health condition information entered by user F in the past month, advice provided, and emotional information are stored in a database, which can be used for future health management and medical consultations.

[0739] As described above, the system of the present invention effectively supports the management of a user's health and emotional state and the prevention of illness. Users can maintain and improve their health by simply inputting their daily physical condition and emotions, receiving analysis and advice from the server, and taking actions based on this information.

[0740] The processing flow will be explained below.

[0741] Step 1:

[0742] The user starts the application and accesses the user registration screen. The terminal displays the user registration form.

[0743] Step 2:

[0744] The user enters personal information such as name, age, gender, email address, chronic illnesses and allergies. The device temporarily stores the entered information and waits for the user to click the registration button.

[0745] Step 3:

[0746] The user clicks the registration button. The device sends the input information to the server.

[0747] Step 4:

[0748] The server stores the received information in a database, generates a user ID, and returns the generated user ID to the device.

[0749] Step 5:

[0750] The terminal receives the user ID and logs the user in. At this stage, the initial user settings are complete.

[0751] Step 6:

[0752] The user inputs their physical condition for the day by voice. The device converts the voice input into text data. The device also uses an emotion engine to extract emotional information from the user's voice.

[0753] Step 7:

[0754] The terminal transmits the converted text data and emotion data to the server. For example, if the user inputs "I have a headache today and I'm a little irritated," the text data and the emotion data "irritated" are transmitted to the server.

[0755] Step 8:

[0756] The server stores the received text data and emotion data in a database. New health status information and emotion information are added to the database.

[0757] Step 9:

[0758] The server analyzes the stored data in comparison with past data and general medical knowledge, for example, to identify the cause of headaches or consider the influence of emotions.

[0759] Step 10:

[0760] Based on the analysis results, the server generates specific advice for the user. For example, in addition to the usual advice of "limit your caffeine intake and drink plenty of water today," it generates advice such as "try relaxation techniques to reduce stress."

[0761] Step 11:

[0762] The server sends the generated advice to the terminal, which receives the advice.

[0763] Step 12:

[0764] The device will provide advice to the user through an AI speaker or chat interface. For example, the AI ​​speaker will tell the user, "Today, limit your caffeine intake and drink plenty of water. I also recommend taking deep breaths as a relaxation technique."

[0765] Step 13:

[0766] The server records and updates the diagnosis results and advice for that day in the user's individual medical record, enabling long-term health management.

[0767] Example 2

[0768] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0769] Conventional health management systems focus on collecting and analyzing users' health status information, but they are unable to consider users' emotional information, making it difficult to provide more personalized and accurate advice. Furthermore, by ignoring the impact of emotions on health status, important factors in user health management are often overlooked. As a result, prevention and performance improvement may not be sufficiently effective.

[0770] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving daily health condition information and emotional information from the user as voice or text data, means for storing the received health condition information and emotional information in a database, and means for comparing and analyzing the stored health condition information and emotional information with past data and general medical knowledge. This makes it possible to generate and provide more personalized and specific advice that takes the user's emotional information into consideration.

[0771] "User" refers to a person who utilizes the system to input and manage their own health and emotional state.

[0772] "Audio or text data" refers to an information format used by a user to express his or her health condition or emotional state, and is in the form of audio data or text data.

[0773] "Health status information" refers to data recorded by a user regarding their daily physical condition and symptoms.

[0774] "Emotion information" is data in which a user records their daily emotional state, and includes information about specific emotions (for example, happiness, sadness, anger, etc.).

[0775] "Database" refers to a system that stores and manages received health status information and emotional information over the long term.

[0776] "Historical Data" refers to health and emotional information previously collected from a user that is stored in the system.

[0777] "General medical knowledge" refers to the basic information based on medical knowledge and research results, which is used to analyze health conditions and generate advice.

[0778] "Analysis" refers to the process of analyzing the received and stored data to identify patterns and causes of the user's health and emotional state.

[0779] "Advice" refers to specific suggestions that are generated based on the analysis results and are useful for the user's lifestyle and health management.

[0780] "Medical Record" refers to a digital record for recording and storing a User's individual health and emotional information.

[0781] "Emotion engine" refers to software or algorithms for extracting emotional information from a user's voice or text data.

[0782] "Speech recognition technology" refers to technology that converts speech into text data and is used to process user speech input.

[0783] MODE FOR CARRYING OUT THE INVENTION

[0784] The present invention is a system that collects and analyzes a user's daily health and emotional state to provide personalized advice. The system receives voice or text data entered by the user, stores it in a database, and compares and analyzes it with past data and general medical knowledge.

[0785] User Registration / Login

[0786] When a user uses the system for the first time, they enter their personal information (name, age, gender, medical history, etc.) into the terminal. The terminal checks the entered data to see if there are any omissions or errors. Next, the terminal sends the user's registration information to the server, which stores the received data in a database. The server generates a new user ID and returns it to the terminal. From then on, the user can log in to the system using this user ID.

[0787] Examples:

[0788] User A uses the system for the first time and enters his / her name, age, and gender. The device sends the input data to the server, which saves the data and then generates a user ID and sends it back to the device. User A can then easily log in using the generated ID from the next time.

[0789] Daily questionnaire entry and emotion recognition

[0790] The user inputs their physical and emotional state for the day into the device via voice or text. The device uses speech recognition technology (e.g., Google Cloud Speech-to-Text) to convert the voice input into text. Next, the device uses an emotion engine (e.g., IBM Watson Tone Analyzer) to recognize emotions from the input information and format the recognition results along with the text. Finally, the device sends the formatted physical and emotional information to the server.

[0791] Examples:

[0792] When User B says, "I have a headache today and I'm a little irritated," the device converts the speech into text and sends it to the server, where the emotion engine analyzes the emotion "irritated." This data is then sent to the server.

[0793] Data collection and analysis

[0794] The server receives and stores the received health and emotional information in a database, assigning a timestamp to the data and managing it in chronological order. The server then analyzes the stored data using an analysis engine (e.g., using Python's pandas library) and compares it with past data to identify patterns in health and emotional states.

[0795] Examples:

[0796] If User C frequently inputs past data on "headaches" and "irritability," the server compares and analyzes this data to identify the frequency and timing of these events. For example, it identifies that these events frequently occur during certain times of the day or in certain situations.

[0797] Generating and providing advice

[0798] The server generates appropriate advice for the user based on the analysis results, taking emotional information into account and suggesting stress management methods or specific actions (e.g., "Try taking deep breaths to relax"). The generated advice is sent to the device, which then communicates it to the user using an AI speaker or chat interface.

[0799] Examples:

[0800] After User D inputs his / her morning physical condition, the AI ​​speaker provides audio advice such as, "Today, limit your caffeine intake and drink plenty of water. Also, I recommend taking deep breaths as a relaxation technique."

[0801] Medical record updates

[0802] The server records the results of that day's diagnosis and advice based on that result in the user's medical record, allowing the user to understand their own health condition and emotional fluctuations over the long term.

[0803] Examples:

[0804] User F's health condition data, emotional data, and provided advice for the past month are organized and stored in a database. The server uses this information to understand the user's health trends.

[0805] Prompt Sentence Examples

[0806] "When a user inputs their emotions and health status, the system converts that information into text, extracts emotional information using an emotion engine, records it in an individual medical record, and provides appropriate advice based on the analysis results. For example, if you input, 'I have a headache today and I'm a little irritated,' the device converts the speech into text, the emotion engine recognizes the irritation, the server analyzes it, and generates appropriate advice."

[0807] This system aims to support users' daily health management, prevent illness, and improve daily performance.

[0808] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0809] System program processing steps

[0810] Step 1: Enter your user registration information

[0811] 1. The user enters personal information such as their name, age, gender, and medical history into the device.

[0812] 2. The terminal checks the entered data to make sure there are no missing or incorrect information.

[0813] 3. Input: User's personal information (name, age, gender, medical history, etc.)

[0814] 4. Output: Checked user personal information

[0815] Examples:

[0816] User A uses the system for the first time and enters his / her name, age, gender, medical history, etc. The terminal checks this information to make sure there are no errors.

[0817] Step 2: Sending data

[0818] 1. The device sends the checked user personal information to the server.

[0819] 2. Use HTTPS as the data transmission protocol to ensure secure communication.

[0820] 3. Input: Checked user personal information

[0821] 4. Output: User personal information sent to the server

[0822] Examples:

[0823] User A's personal information is sent from the terminal to the server via secure communication.

[0824] Step 3: Generate and return a user ID

[0825] 1. The server stores the received user personal information in a database.

[0826] 2. The server generates a new user ID and returns it to the device.

[0827] 3. Input: User personal information sent to the server

[0828] 4. Output: Generated user ID (returned to the terminal)

[0829] Examples:

[0830] The server saves User A's information in a database, generates a user ID, and returns it to the terminal. User A will use this ID from the next time.

[0831] Step 4: Fill out the daily questionnaire

[0832] 1. The user inputs their health condition and emotions for the day into the device by voice or text.

[0833] 2. If the device supports voice input, convert the voice to text (using voice recognition technology).

[0834] 3. Input: User voice or text data

[0835] 4. Output: Data converted to text (in the case of voice input)

[0836] Examples:

[0837] User B speaks, "I have a headache today and I'm feeling a little irritated," and the device converts this into text using voice recognition technology.

[0838] Step 5: Extracting emotional information

[0839] 1. The device uses an emotion engine to recognize emotions from input information.

[0840] 2. Format the recognition results along with the text.

[0841] 3. Input: Data converted to text

[0842] 4. Output: Formatted physical condition information and emotional information

[0843] Examples:

[0844] The text converted from user B's voice data as "I have a headache today and I'm a little irritated" and the emotional information "irritated" extracted by the emotion engine are formatted.

[0845] Step 6: Sending data

[0846] 1. The device sends the formatted physical condition information and emotional information to the server.

[0847] 2. Input: Formatted physical condition information and emotional information

[0848] 3. Output: Physical condition and emotional information sent to the server

[0849] Examples:

[0850] The device transmits user B's physical condition information and emotional information to the server.

[0851] Step 7: Save your data

[0852] 1. The server stores the received physical condition information and emotional information in a database.

[0853] 2. Stored data is time-stamped and managed in chronological order.

[0854] 3. Input: Physical condition and emotional information sent to the server

[0855] 4. Output: Physical condition and emotional information stored in the database

[0856] Examples:

[0857] The server stores user B's physical condition and emotional information in a database and assigns a timestamp.

[0858] Step 8: Data analysis

[0859] 1. The server analyzes the stored data using an analytical engine.

[0860] 2. Compare with historical data to identify patterns in your health and emotions.

[0861] 3. Input: Physical condition information and emotional information in the database

[0862] 4. Output: Analysis results

[0863] Examples:

[0864] Analyze User C's data from the past month and identify the relationship between "headache" and "irritability."

[0865] Step 9: Generating Advice

[0866] 1. The server generates specific advice appropriate for the user based on the analysis results.

[0867] 2. Consider emotional information and suggest stress management strategies and specific actions.

[0868] 3. Input: Analysis results

[0869] 4. Output: Specific advice

[0870] Examples:

[0871] The server generates advice such as, "Reduce your caffeine intake today and drink plenty of water. Try deep breathing as a relaxation technique."

[0872] Step 10: Providing advice

[0873] 1. The generated advice is sent from the server to the device.

[0874] 2. The device uses an AI speaker or chat interface to provide advice to the user.

[0875] 3. Input: Specific advice

[0876] 4. Output: Advice provided to the user

[0877] Examples:

[0878] The AI ​​speaker tells User D, "Reduce your caffeine intake and drink plenty of water. We also recommend taking deep breaths as a relaxation technique."

[0879] Step 11: Update the medical record

[0880] 1. The server records the day's diagnosis results and advice in the user's medical record.

[0881] 2. Allow users to understand fluctuations in their health status over the long term.

[0882] 3. Input: Physical condition information, emotional information, diagnosis results, and advice stored on the server

[0883] 4. Output: Updated medical record

[0884] Examples:

[0885] The server updates and records the health condition, emotional information, diagnosis results, and advice for the past month in the medical record of user F.

[0886] (Application example 2)

[0887] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0888] Conventional health management systems provide advice by collecting and analyzing a user's daily health status, but they do not take the user's emotional state into account, making it difficult to provide personalized advice. Furthermore, there is no mechanism for providing personalized content, and appropriate support based on the user's emotional and health status is not adequately provided. Therefore, there is a need for a system that comprehensively considers both the user's health status and emotional state to provide personalized advice and content.

[0889] The identification process by the identification 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 receiving daily health condition information and emotional information from the user as voice or text data; means for storing the received health condition information and emotional information in a database; means for comparing and analyzing the stored health condition information and emotional information with past data and general medical knowledge; means for generating specific advice for the user based on the analysis results and providing personalized content according to the user's emotional state; means for providing the generated advice and personalized content to the user; and means for recording and updating the generated advice, diagnosis results, and provided content in the user's individual medical record. This makes it possible to comprehensively evaluate both the user's health condition and emotional state and provide more appropriate and individualized advice and personalized content.

[0890] "Audio or text data" is data that provides health and emotional information in audio or text form for a user to input into the system.

[0891] "Health status information" refers to information about the user's physical condition and symptoms, and is data used for daily health management and diagnosis.

[0892] "Emotional information" refers to information about a user's emotions and psychological state, and is data used to understand the user's emotional state.

[0893] "Database" means a system or location for systematically storing and managing health status information and emotional information collected from users.

[0894] "Means for comparison and analysis" refers to methods and technologies for comparing stored health status information and emotional information with historical data and general medical knowledge to evaluate and analyze the user's condition.

[0895] "Means for generating advice" refers to methods and techniques for generating specific and personalized advice for a user based on the results of the comparison and analysis.

[0896] "Means for providing personalized content" refers to methods and technologies for selecting and providing specific content (e.g., videos, music, articles, etc.) to users based on their emotional state.

[0897] "Individual User's Medical Record" means an individual record for recording and updating each user's health status information and emotional information, as well as advice and provided content based on that information.

[0898] To implement this invention, it is necessary to build a system that allows users to input daily health status information and emotional information using a device such as a smartphone or smart glasses, analyzes the information, and provides personalized advice and content. A specific example of this is shown below.

[0899] User Registration / Login

[0900] When a user uses the system for the first time, they enter their personal information and initial health information. This information is sent from the device to the server, which then stores it in a database. The server generates a user ID and sends it back to the device, allowing the user to easily log in from the next time onwards. For example, when a user enters their name, age, gender, and medical history, all of this information is sent to the server, and an individual medical record is created.

[0901] Input and recognition of daily health status and emotional information

[0902] The user inputs their physical condition and emotions for the day in voice or text format. In the case of voice input, the device converts the voice into text data, and then the emotion engine extracts the emotional information. For example, if the user inputs, "I have a headache today and I'm a little irritated," the device converts this voice data into text, recognizes the emotional information of "irritation," and sends this data to the server.

[0903] Data collection and analysis

[0904] The server stores the received health condition information and emotional information in a database. The stored data is then analyzed against past data and general medical knowledge. This data is compared with the user's past health condition and emotional data to infer the cause of the health condition and the influence of emotions. For example, if a user frequently entered data on "headaches" and "irritability" in the past, comparing and analyzing this data can explore the possibility that headaches are linked to emotions.

[0905] Advice and content generation

[0906] Based on the analysis results, the server generates specific and individualized advice for the user, while also providing personalized content according to the user's emotional state. For example, if the user is feeling stressed, relaxation music or meditation videos will be recommended. An example of advice might be, "Today, you should limit your caffeine intake, drink plenty of water, and try relaxation techniques to reduce stress."

[0907] Providing advice and content

[0908] The provided advice and content is communicated to the user via a device. The device can be a smartphone or smart glasses, and these devices provide information to the user through audio and visual means. For example, after the user enters their physical condition information, the AI ​​speaker can provide audio advice such as, "Reduce your caffeine intake today and drink more fluids. We also recommend taking deep breaths as a relaxation technique."

[0909] Medical record updates

[0910] The server records and updates the advice and diagnosis results provided, as well as the history of personalized content provided, in each user's individual medical record. This makes it easier for users to understand their own health condition and emotional fluctuations over the long term, which is useful for future health management and medical consultations. For example, users can record their health condition and emotional fluctuations over the past month and receive advice based on that information at a glance.

[0911] Usage example

[0912] The user launches the app and enters a prompt like this:

[0913] Example prompt: "I have a headache today and I'm feeling a bit irritable."

[0914] Based on the prompts, the system first converts the voice to text, analyzes emotions, and sends the received data to a server, which then analyzes it based on past data and general medical knowledge to generate personalized content, such as specific advice and relaxation music, and delivers it to the user.

[0915] This allows users to improve their health while also taking care of their emotions, improving the quality of their daily lives.

[0916] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0917] Step 1:

[0918] Users use their smartphones or smart glasses to register their personal information and initial health status information, including name, age, gender, medical history, etc. The entered data is sent from the device to the server. The input is in text format, and the server stores it in a database and generates a user ID, which is returned to the device.

[0919] Step 2:

[0920] The user inputs their daily health condition and emotional information into the device. For example, they can input a prompt phrase such as "I have a headache today and I'm a little irritated" by voice. This voice data is converted into text data by the device, and the emotional information is extracted by the emotion engine. The extracted data (health condition information and emotional information) is sent to the server.

[0921] Step 3:

[0922] The server then stores the received health condition and emotional information in a database. This data is compared with similar past data and analyzed against general medical knowledge. For example, the frequency and correlation between "headaches" and "irritability" can be analyzed to infer the causes of health conditions and the influence of emotions.

[0923] Step 4:

[0924] Based on the analysis results, the server generates specific and personalized advice for the user. At the same time, it selects personalized content (e.g., relaxation music or meditation videos) according to the user's emotional state. The generated advice and content are intended to optimally manage the user's health and emotional state.

[0925] Step 5:

[0926] The generated advice and personalized content are then delivered to the user via the device. The smartphone or smart glasses process this information and provide the user with visual or audio information. For example, the device might say, "Today, we recommend limiting your caffeine intake and drinking plenty of water. We also recommend taking deep breaths as a relaxation technique."

[0927] Step 6:

[0928] The server records and updates the history of the advice and content provided in the user's individual medical record. This medical record will be used to understand the user's long-term health and emotional state fluctuations and for future medical consultations and health management. For example, the fluctuations in health and emotional state over the past month can be visualized and saved as graphs.

[0929] This allows users to comprehensively manage their health and emotional state, and improve their quality of life with appropriate advice and content.

[0930] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0931] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0932] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0933] [Third embodiment]

[0934] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0935] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0936] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0937] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0938] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0939] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0940] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0941] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0942] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0943] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0944] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0945] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0946] The present invention is a system that collects, stores, analyzes, and provides advice on a user's daily health status. This system makes it easier for users to manage their own health status and supports the prevention of illness and the improvement of daily performance. To implement the present invention, a program based on the following processing steps is generated, and the operation of each step is explained in detail. Each major process is explained below.

[0947] User Registration / Login

[0948] When a user uses the system for the first time, they enter their personal information and initial health status information. This data is sent from the device to the server, which stores it in a database. The server then generates a user ID and returns it to the device. From then on, the user can log in using this ID.

[0949] For example, when User A uses the system for the first time, he or she enters his or her name, age, gender, medical history, etc. This information is sent from the terminal to the server. The server then creates an individual medical record for User A based on this information, generates a user ID, and sends it back to the terminal. After logging in and completing the initial settings, User A can easily log in next time.

[0950] Daily medical questionnaire entry

[0951] When a user inputs their health status for the day, they input information about their health status by voice or text. The device receives this input, converts it into text if it is voice, and sends it to the server. The server stores this information in a database for later analysis.

[0952] For example, if user B says "I have a headache today," the device converts this speech into text and sends it to the server. The server receives the text information "headache" and stores it in user B's health database.

[0953] Data collection and analysis

[0954] The server compares and analyzes the received data with past data and general medical knowledge. For example, it compares it with other data from a time when headaches were frequent in the past to infer the cause. It also compares it with general medical knowledge to find likely causes and countermeasures.

[0955] For example, if User C has frequently entered "headache" data in the past, the server compares and analyzes this past data with the current data, identifying past patterns and triggering factors (such as climate change or stress levels), and performs a detailed analysis based on general medical knowledge.

[0956] Generating Advice

[0957] The server generates specific advice for the user based on the analysis results. For example, if the accumulated data indicates that a headache is caused by caffeine intake or lack of sleep, the server generates advice such as "Reduce your caffeine intake today and drink plenty of water."

[0958] If User D inputs "I have a headache today," and the server determines through analysis that "it's likely due to caffeine intake," the generated advice will read, "Reduce your caffeine intake today and drink plenty of water." This advice will be provided to User D via the terminal.

[0959] Providing advice

[0960] The generated advice is provided to the user via the device, which then communicates it to the user using an AI speaker or chat interface. The user can then receive this advice and use it in their daily activities and health management.

[0961] For example, after user E enters their morning physical condition, the AI ​​speaker will provide voice advice such as, "It would be good for you to get plenty of rest today. I recommend you drink plenty of water."

[0962] Medical record updates

[0963] The server records and updates the advice and diagnosis results provided that day in the user's individual medical record, making it easier for users to understand their own health condition over the long term. It also makes it possible to detect health trends and abnormalities early in the future.

[0964] For example, all health information entered by user F over the past month and advice provided can be stored in a database and used for future health management and medical consultations.

[0965] As described above, the system of the present invention effectively supports the user's health management and prevention of illness. Users can maintain and improve their health by simply inputting their daily physical condition, receiving analysis and advice from the server, and taking actions based on this information.

[0966] The processing flow will be explained below.

[0967] Step 1:

[0968] The user starts the application and accesses the user registration screen. The terminal displays the user registration form.

[0969] Step 2:

[0970] The user enters personal information such as name, age, gender, email address, chronic illnesses and allergies. The device temporarily stores the entered information and waits for the user to click the registration button.

[0971] Step 3:

[0972] The user clicks the registration button. The device sends the input information to the server.

[0973] Step 4:

[0974] The server stores the received information in a database, generates a user ID, and returns the generated user ID to the device.

[0975] Step 5:

[0976] The terminal receives the user ID and logs the user in. At this stage, the initial user settings are complete.

[0977] Step 6:

[0978] The user inputs their physical condition for the day by voice, and the device converts the voice input into text data.

[0979] Step 7:

[0980] The terminal transmits the converted text data to the server. For example, if the user inputs "I have a headache today," the text data is transmitted to the server.

[0981] Step 8:

[0982] The server stores the received text data in a database. New health status information is added to the database.

[0983] Step 9:

[0984] The server compares and analyzes the stored data with past data and general medical knowledge, for example, to identify the cause of headaches and consider general countermeasures.

[0985] Step 10:

[0986] Based on the analysis results, the server generates specific advice for the user, such as "Reduce your caffeine intake today and drink plenty of water."

[0987] Step 11:

[0988] The server sends the generated advice to the terminal, which receives the advice.

[0989] Step 12:

[0990] The device will provide advice to the user through an AI speaker or chat interface, for example, the AI ​​speaker will tell the user to "limit your caffeine intake today and drink plenty of water."

[0991] Step 13:

[0992] The server records and updates the diagnosis results and advice for that day in the user's individual medical record, enabling long-term health management.

[0993] Example 1

[0994] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0995] In modern society, individual health management is extremely important, and there is a growing need for methods to efficiently collect and analyze this information and provide appropriate advice. However, conventional systems have limitations in effectively collecting and analyzing users' health status information and providing appropriate advice, particularly in terms of comparison and analysis with past data and general medical knowledge. Furthermore, there is a lack of methods for generating appropriate advice using generative AI models and for reliably providing this advice to users. These issues are being addressed.

[0996] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0997] In this invention, the server includes means for receiving daily health condition information from a user as voice or text data, means for storing the received health condition information in a database, means for comparing and analyzing the stored health condition information with past data and general medical knowledge, means for generating specific advice for the user based on the analysis results using a generative AI model, means for providing the generated advice to the user, and means for recording and updating the generated advice and diagnosis results in the user's individual medical record. This makes it possible to efficiently collect, compare, and analyze a user's health condition information, and generate and provide appropriate advice.

[0998] "User" refers to each individual who uses the system.

[0999] "Voice data" refers to data containing health information provided by a user through voice input.

[1000] "Text data" refers to data including health condition information provided by the user through character input.

[1001] "Means for receiving" refers to means for obtaining voice or text data from a user within the system.

[1002] "Database" refers to a structured collection of data for storing received health status information.

[1003] "Means for storing" refers to the system's ability to record received health status information in a database.

[1004] "Means for comparison and analysis" refers to the function of comparing stored data with past data and general medical knowledge and analyzing the information.

[1005] "Generative AI model" refers to an artificial intelligence model used to generate specific advice for users based on the results of data analysis.

[1006] "Means for generating advice" refers to the system's function of using a generative AI model to create specific advice from the analysis results.

[1007] The "means for providing advice" refers to a function for displaying or notifying the user of the generated advice.

[1008] A "medical record" refers to an individual health record that includes a user's health status information, past diagnostic results, advice information, etc.

[1009] "Means of recording and updating" refers to the system's functionality for adding advice and diagnostic results generated each day to a user's individual chart and keeping it up to date.

[1010] The present invention is a system for collecting and analyzing a user's daily health condition and providing appropriate advice based on the collected data. Specific embodiments of this system will be described below.

[1011] The system includes the following main components: a terminal, a server, a database, and a generative AI model.

[1012] User Registration / Login

[1013] When a user uses the system for the first time, they use a terminal to enter their personal information and initial health information. For example, the user enters their name, age, gender, medical history, etc., and the terminal sends this data to the server. The server stores the received data in a database and generates a user ID. This user ID is returned to the terminal, and the user can use this ID to log in from the next time onwards.

[1014] Daily medical questionnaire entry

[1015] To record their daily health status, users use the device to input information by voice or text. In the case of voice input, the device uses the Google Cloud Speech-to-Text API to convert the voice to text. The converted text data is sent to a server, which then stores it in a database.

[1016] Data collection and analysis

[1017] The server compares and analyzes the received data with past data and general medical knowledge. Specifically, the server retrieves past data from the database and compares it using a Python data analysis library (e.g., Pandas). It then analyzes the data using a natural language processing library (e.g., NLTK) to identify likely causes and countermeasures.

[1018] Generating Advice

[1019] Based on the results of the comparison and analysis, the server uses a generative AI model (such as GPT-4) to generate specific advice for the user. For example, if a comparison of past data determines that caffeine intake is the cause, the generated advice might include "limit your caffeine intake today and drink plenty of water."

[1020] Providing advice

[1021] The generated advice is provided to the user via the device, which then communicates the advice to the user as a notification or voice message. Specifically, the advice is provided via the notification function of Android or iOS devices or an AI speaker.

[1022] Medical record updates

[1023] The server records and updates the advice and diagnosis results generated that day in the user's medical record. This allows the user to easily understand long-term fluctuations in their health condition and the recurrence of certain symptoms. The server also uses this information to contribute to future health management and early detection of abnormalities.

[1024] Examples of concrete examples and prompts

[1025] For example, if User A says, "I have a headache today," the device converts the voice input into text and sends it to the server. The server then analyzes the data based on past health data and general medical knowledge. Using the generative AI model based on the analysis results, the server generates advice such as "Reduce your caffeine intake and drink plenty of water today," which is then provided to User A via the device. This is important information that the user can use to improve their future behavior and health management.

[1026] An example prompt is:

[1027] "What AI model would you use to analyze what advice should be generated after a user types, 'I have a headache today,' and provide an example of the advice you would generate?"

[1028] By linking these functions, this system will efficiently and effectively support users in managing their health.

[1029] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1030] Step 1:

[1031] The user enters personal information the first time they use the service.

[1032] The user starts the application and enters personal information such as name, age, gender, and medical history into the registration screen. Input data: Name, age, gender, medical history

[1033] Output data: Personal information input data

[1034] Step 2:

[1035] The device sends the input data to the server

[1036] The device sends the entered personal information to the server via an HTTP request. Specifically, it posts the data using an HTTP client library. Input data: Personal information input data

[1037] Output data: Status of completion of sending to server

[1038] Step 3:

[1039] The server saves the user's data to the database and generates a user ID.

[1040] The server saves the received data in a database (e.g. MySQL) using the INSERT statement and generates a new user ID. Input data: Input data of personal information

[1041] Output: Generated user ID

[1042] Step 4:

[1043] The server returns the generated user ID to the device.

[1044] The server returns an HTTP response containing the generated user ID to the terminal. Specifically, a status code of 200 and JSON data containing the user ID are returned. Input data: Generated user ID

[1045] Output data: User ID response data

[1046] Step 5:

[1047] The user will then log in with the generated user ID.

[1048] The next time the user logs in, they will be authenticated using their user ID and password. Input data: User ID, password

[1049] Output data: Authentication success / failure status

[1050] Step 6:

[1051] The user inputs their daily physical condition by voice or text.

[1052] The user opens the app's questionnaire screen and records their physical condition for the day by voice or text. Input data: Voice or text physical condition data

[1053] Output data: Converted text data

[1054] Step 7:

[1055] Your device converts your voice input into text

[1056] The device uses the Google Cloud Speech-to-Text API to convert voice input into text. Input data: Voice data

[1057] Output data: Text data

[1058] Step 8:

[1059] The device sends the converted text data to the server.

[1060] The converted text data is sent from the terminal to the server via an HTTP request. Input data: Text data

[1061] Output data: Status of completion of sending to server

[1062] Step 9:

[1063] The server stores the received data in the database

[1064] The server saves the received data in the user's database. This also uses the MySQL INSERT statement. Input data: Text data

[1065] Output data: Status of completion of saving to database

[1066] Step 10:

[1067] The server retrieves the received data from the database

[1068] The server retrieves past health data from the database using a SELECT statement. Input data: User ID

[1069] Output data: Past health data

[1070] Step 11:

[1071] The server compares past data with current data

[1072] The server compares the past and current data using a Python data analysis library (e.g., Pandas). Input data: past health data, current health data

[1073] Output data: Comparison results

[1074] Step 12:

[1075] The server analyzes the comparison results against general medical knowledge

[1076] The server uses a natural language processing library (e.g., NLTK) to analyze the comparison results against general medical knowledge. Input data: Comparison results, medical knowledge data

[1077] Output data: Analysis results

[1078] Step 13:

[1079] The server generates advice based on the analysis results.

[1080] The server generates specific advice using a generative AI model (e.g., GPT-4) based on the analysis results. Input data: Analysis results

[1081] Output data: Generated advice

[1082] Step 14:

[1083] Sends server-generated advice to the device

[1084] The generated advice is sent to the terminal in JSON format. Input data: Generated advice

[1085] Output data: Status of completion of transmission to the terminal

[1086] Step 15:

[1087] The device displays or reads the generated advice to the user.

[1088] The device notifies the user of the advice using the app's notification function or voice alert function.

[1089] Output data: Notification content to the user

[1090] Step 16:

[1091] The server records and updates the diagnosis results and advice for that day in the patient chart.

[1092] The server saves the diagnosis results and advice for the day in the user's chart and updates it to the latest version. Input data: diagnosis results, advice

[1093] Output data: Updated medical record data

[1094] (Application example 1)

[1095] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1096] Conventional health management systems allow users to input their own health status and receive advice based on the analysis results. However, these systems rely on devices such as smartphones and computers, and users may not always have easy access to these devices. In addition, there are limitations to voice input and real-time notification functions, which can reduce the convenience of health management. This has made it difficult for users to quickly and appropriately manage their health in their daily lives.

[1097] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1098] In this invention, the server includes: means for receiving daily health condition information from a user as voice or text data; means for storing the received health condition information in a database; means for comparing and analyzing the stored health condition information with past data and general medical knowledge; means for generating specific advice for the user based on the analysis results; means for providing the generated advice to the user; means for recording and updating the generated advice and diagnosis results in the user's individual medical record; and means for receiving health condition information from the user using smart glasses and providing the information as visual or audio notifications, thereby enabling users to quickly and easily input and receive feedback on their health condition via the smart glasses in their daily lives.

[1099] "Health condition information" refers to information related to the user's physical condition and health, such as data on body temperature, blood pressure, whether or not the user has a headache, and sleep duration.

[1100] "Voice or Text Data" means information provided by a User through spoken or written input.

[1101] "Database" means a system for systematically storing and managing health status information and user information.

[1102] "Comparison and analysis" refers to the process of evaluating stored data using statistical methods and machine learning algorithms to derive meaningful results.

[1103] "Specific advice" means specific suggestions or instructions generated based on analyzed data that can help the user improve or maintain their health.

[1104] "Means for providing to the user" means a mechanism for conveying the generated advice to the user through audio notification or visual display.

[1105] "Medical Record" means a digital file that records a user's individual health status information, diagnostic results, and the history of advice provided.

[1106] "Smart glasses" refers to a wearable device that has built-in functions such as information display and voice input, and that allows users to integrate digital information with the physical world when wearing it.

[1107] "Visual or audio notification" means a method of providing information to a user through a display or audio speaker.

[1108] To realize this invention, a system in which a user, a server, and smart glasses work together is required. A specific embodiment of this system will be described below.

[1109] Hardware and software used

[1110] Hardware:

[1111] Smart glasses: Wearable devices with functions such as information display and voice input. Examples include Google Glass and Vuzix Blade.

[1112] Server: A central processing unit that receives, stores, analyzes data, and generates advice.

[1113] software:

[1114] Speech Recognition: Converts voice input into text data using the Google Cloud Speech-to-Text API.

[1115] Database: Firebase is used to store user health and personal information.

[1116] Data analysis: Compare and analyze data using Python's pandas and scikit-learn.

[1117] Advice generation: Using a generative AI model (e.g., GPT-4 API), specific advice is generated based on the analysis results.

[1118] System Operation

[1119] User Registration and Login

[1120] When a user uses the system for the first time, they scan the QR code displayed on the smart glasses screen with their smartphone to sign up for the application. The user enters information such as their name, age, gender, and medical history by voice or text, and this data is sent to Firebase. Once registration is complete, the server generates a user ID and notifies the user. From then on, the user logs in to the system using this ID.

[1121] Enter your health status

[1122] To input their daily health status, users can use the microphone in their smart glasses to voice-report their health status. For example, if they say, "I have a slight headache today," the smart glasses will convert this voice data into text data using the Google Cloud Speech-to-Text API. The text data will then be sent to Firebase and stored in the user's individual database.

[1123] Data analysis and advice generation

[1124] The server periodically collects health status data stored in Firebase and analyzes it using Python's pandas and scikit-learn. Based on the analysis results, a generative AI model (such as the GPT-4 API) is used to generate specific advice appropriate for the user. For example, if the data indicates frequent headaches or elevated stress levels, the server generates advice such as "It would be a good idea to limit caffeine and drink more water today."

[1125] Providing advice

[1126] The generated advice is provided to the user in real time via the smart glasses as a visual or audio notification, such as a message on the smart glasses display saying "You should get plenty of rest today. We recommend you drink plenty of water," or a similar message through the audio speaker.

[1127] Medical record updates

[1128] The server manages long-term health conditions by recording and updating the generated advice and diagnosis results in the user's individual medical record, allowing users to easily check their past health conditions and the advice they received.

[1129] Examples of concrete examples and prompts

[1130] For example, the following prompt could be input to a generative AI model:

[1131] Today's health data:

[1132] Headache: Yes

[1133] Sleep time: 6 hours

[1134] Caffeine intake: 2 cups

[1135] Stress level: High

[1136] Generate health advice for this user based on historical data and medical knowledge.

[1137] As described above, this system allows users to quickly and easily input and receive feedback on their health status through smart glasses in their daily lives, enabling more efficient and effective health management.

[1138] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1139] Step 1:

[1140] User Registration:

[1141] A user puts on the smart glasses and begins signing up for the application by scanning a QR code displayed on the glasses with their smartphone for initial registration. They enter their information (name, age, gender, medical history, etc.) via voice and text. This data is sent to Firebase, and the server generates a user ID and notifies the user of that ID.

[1142] Input: Name, age, gender, medical history, etc.

[1143] Output: User ID

[1144] Step 2:

[1145] Login:

[1146] The user logs into the system via the smart glasses using the generated user ID and password, and the server authenticates this and allows the user to access their individual database.

[1147] Input: User ID, Password

[1148] Output: Authentication status, access rights

[1149] Step 3:

[1150] Enter your health status:

[1151] Users report their daily health status by voice using the microphone in their smart glasses. The voice data is converted into text data using the Google Cloud Speech-to-Text API. The text data is sent to Firebase and stored in the user's individual database. For example, if a user voice-inputs, "I have a slight headache today," that information is stored as text data.

[1152] Input: Speech data (e.g., "I have a slight headache today")

[1153] Output: Text data, information stored in the user database

[1154] Step 4:

[1155] Data Analysis:

[1156] The server periodically collects health status data stored in Firebase and performs data analysis using Python's pandas and scikit-learn. These tools are used to compare the data with historical data and general medical knowledge to identify specific patterns or trends, such as detecting frequent headaches or elevated stress levels.

[1157] Input: Health condition data (e.g., "headache" as text data)

[1158] Output: Analysis results (e.g., estimated cause of headache)

[1159] Step 5:

[1160] Advice Generation:

[1161] Based on the analysis results, the server generates appropriate advice using a generative AI model (such as the GPT-4 API). For example, if data analysis predicts that frequent headaches are caused by excessive caffeine intake, the server generates the advice, "It would be good to limit your caffeine intake and drink plenty of water."

[1162] Input: Analysis results (e.g., headache is caused by excessive caffeine intake)

[1163] Output: Generated advice (e.g., "Reduce your caffeine intake and drink plenty of water.")

[1164] Step 6:

[1165] Providing advice:

[1166] The generated advice is provided to the user in real time through the smart glasses as visual and audio notifications, such as a message on the smart glasses display saying "Avoid caffeine today" or a similar advice being spoken through the audio speaker.

[1167] Input: Generated advice

[1168] Output: Advice given to the user

[1169] Step 7:

[1170] Update medical records:

[1171] The server records and updates the generated advice and diagnosis results in the user's individual medical record, enabling long-term health management. Users can easily check their past health status and the advice they received.

[1172] Input: Generated advice, diagnostic results

[1173] Output: Updated user record

[1174] These steps will enable users to quickly and easily input and receive feedback on their health status through the smart glasses, enabling more effective long-term health management.

[1175] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1176] The present invention is a system that combines a conventional system that collects, stores, analyzes, and provides advice on a user's daily health status with an emotion engine that recognizes the user's emotions. This system makes it easier for users to manage their own health and emotional status, and supports the prevention of illness and the improvement of daily performance. Furthermore, by taking emotional information into account, it becomes possible to provide more personalized advice. Each major process in the embodiment of the present invention is specifically described below.

[1177] User Registration / Login

[1178] When a user uses the system for the first time, they enter their personal information and initial health status information. This data is sent from the device to the server, which stores it in a database. The server then generates a user ID and returns it to the device. From then on, the user can log in using this ID.

[1179] For example, when User A uses the system for the first time, he or she enters his or her name, age, gender, medical history, etc. This information is sent from the terminal to the server. The server then creates an individual medical record for User A based on this information, generates a user ID, and sends it back to the terminal. After logging in and completing the initial settings, User A can easily log in next time.

[1180] Daily questionnaire entry and emotion recognition

[1181] When a user inputs their physical condition and emotions for the day, they input information about their physical condition by voice or text. The device receives this input, converts it into text if it is voice, and sends it to the server. The device also uses an emotion engine to extract emotional information from the user's voice. The extracted emotional information is also sent to the server.

[1182] For example, if user B says, "I have a headache today and I'm a little irritated," the device converts this speech into text and uses the emotion engine to recognize the emotion "irritated." This data is then sent to the server.

[1183] Data collection and analysis

[1184] The server stores the received health condition and emotion information in a database. The stored data is then analyzed in conjunction with past data and general medical knowledge. For example, by comparing past health condition and emotion data, the cause of the health condition and the influence of emotions can be inferred.

[1185] For example, if User C frequently entered data on "headaches" and "irritability" in the past, the server would compare and analyze this past data with the current data. It may conclude that headaches are likely to occur in conjunction with emotional states.

[1186] Generating Advice

[1187] Based on the analysis results, the server generates specific and personalized advice for the user. By taking emotional information into account, more appropriate advice becomes possible. For example, in addition to the usual advice of "limit your caffeine intake and drink plenty of water today," the server can generate advice such as "try relaxation techniques to reduce stress."

[1188] If user D inputs data such as "I have a headache today and I'm feeling a little irritated," and the server determines from the analysis results that "stress is likely to be a contributing factor to the headache," the following personalized advice will be created.

[1189] Providing advice

[1190] The generated advice is provided to the user via the device, which then uses an AI speaker and chat interface to communicate specific advice to the user. The user can then receive this advice and apply it to their daily activities and health management.

[1191] For example, after User E inputs his / her morning physical condition, the AI ​​speaker will give him / her advice in voice, such as, "Avoid caffeine intake today and drink plenty of water. Also, I recommend taking deep breaths as a relaxation technique."

[1192] Medical record updates

[1193] The server records and updates the diagnosis results and advice for that day in the user's individual medical record. This allows users to easily understand their own health condition and emotional fluctuations over the long term. It also makes it possible to detect health trends and abnormalities early in the future.

[1194] For example, all health condition information entered by user F in the past month, advice provided, and emotional information are stored in a database, which can be used for future health management and medical consultations.

[1195] As described above, the system of the present invention effectively supports the management of a user's health and emotional state and the prevention of illness. Users can maintain and improve their health by simply inputting their daily physical condition and emotions, receiving analysis and advice from the server, and taking actions based on this information.

[1196] The processing flow will be explained below.

[1197] Step 1:

[1198] The user starts the application and accesses the user registration screen. The terminal displays the user registration form.

[1199] Step 2:

[1200] The user enters personal information such as name, age, gender, email address, chronic illnesses and allergies. The device temporarily stores the entered information and waits for the user to click the registration button.

[1201] Step 3:

[1202] The user clicks the registration button. The device sends the input information to the server.

[1203] Step 4:

[1204] The server stores the received information in a database, generates a user ID, and returns the generated user ID to the device.

[1205] Step 5:

[1206] The terminal receives the user ID and logs the user in. At this stage, the initial user settings are complete.

[1207] Step 6:

[1208] The user inputs their physical condition for the day by voice. The device converts the voice input into text data. The device also uses an emotion engine to extract emotional information from the user's voice.

[1209] Step 7:

[1210] The terminal transmits the converted text data and emotion data to the server. For example, if the user inputs "I have a headache today and I'm a little irritated," the text data and the emotion data "irritated" are transmitted to the server.

[1211] Step 8:

[1212] The server stores the received text data and emotion data in a database. New health status information and emotion information are added to the database.

[1213] Step 9:

[1214] The server analyzes the stored data in comparison with past data and general medical knowledge, for example, to identify the cause of headaches or consider the influence of emotions.

[1215] Step 10:

[1216] Based on the analysis results, the server generates specific advice for the user. For example, in addition to the usual advice of "limit your caffeine intake and drink plenty of water today," it generates advice such as "try relaxation techniques to reduce stress."

[1217] Step 11:

[1218] The server sends the generated advice to the terminal, which receives the advice.

[1219] Step 12:

[1220] The device will provide advice to the user through an AI speaker or chat interface. For example, the AI ​​speaker will tell the user, "Today, limit your caffeine intake and drink plenty of water. I also recommend taking deep breaths as a relaxation technique."

[1221] Step 13:

[1222] The server records and updates the diagnosis results and advice for that day in the user's individual medical record, enabling long-term health management.

[1223] Example 2

[1224] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1225] Conventional health management systems focus on collecting and analyzing users' health status information, but they are unable to consider users' emotional information, making it difficult to provide more personalized and accurate advice. Furthermore, by ignoring the impact of emotions on health status, important factors in user health management are often overlooked. As a result, prevention and performance improvement may not be sufficiently effective.

[1226] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving daily health condition information and emotional information from the user as voice or text data, means for storing the received health condition information and emotional information in a database, and means for comparing and analyzing the stored health condition information and emotional information with past data and general medical knowledge. This makes it possible to generate and provide more personalized and specific advice that takes the user's emotional information into consideration.

[1227] "User" refers to a person who utilizes the system to input and manage their own health and emotional state.

[1228] "Audio or text data" refers to an information format used by a user to express his or her health condition or emotional state, and is in the form of audio data or text data.

[1229] "Health status information" refers to data recorded by a user regarding their daily physical condition and symptoms.

[1230] "Emotion information" is data in which a user records their daily emotional state, and includes information about specific emotions (for example, happiness, sadness, anger, etc.).

[1231] "Database" refers to a system that stores and manages received health status information and emotional information over the long term.

[1232] "Historical Data" refers to health and emotional information previously collected from a user that is stored in the system.

[1233] "General medical knowledge" refers to the basic information based on medical knowledge and research results, which is used to analyze health conditions and generate advice.

[1234] "Analysis" refers to the process of analyzing the received and stored data to identify patterns and causes of the user's health and emotional state.

[1235] "Advice" refers to specific suggestions that are generated based on the analysis results and are useful for the user's lifestyle and health management.

[1236] "Medical Record" refers to a digital record for recording and storing a User's individual health and emotional information.

[1237] "Emotion engine" refers to software or algorithms for extracting emotional information from a user's voice or text data.

[1238] "Speech recognition technology" refers to technology that converts speech into text data and is used to process user speech input.

[1239] MODE FOR CARRYING OUT THE INVENTION

[1240] The present invention is a system that collects and analyzes a user's daily health and emotional state to provide personalized advice. The system receives voice or text data entered by the user, stores it in a database, and compares and analyzes it with past data and general medical knowledge.

[1241] User Registration / Login

[1242] When a user uses the system for the first time, they enter their personal information (name, age, gender, medical history, etc.) into the terminal. The terminal checks the entered data to see if there are any omissions or errors. Next, the terminal sends the user's registration information to the server, which stores the received data in a database. The server generates a new user ID and returns it to the terminal. From then on, the user can log in to the system using this user ID.

[1243] Examples:

[1244] User A uses the system for the first time and enters his / her name, age, and gender. The device sends the input data to the server, which saves the data and then generates a user ID and sends it back to the device. User A can then easily log in using the generated ID from the next time.

[1245] Daily questionnaire entry and emotion recognition

[1246] The user inputs their physical and emotional state for the day into the device via voice or text. The device uses speech recognition technology (e.g., Google Cloud Speech-to-Text) to convert the voice input into text. Next, the device uses an emotion engine (e.g., IBM Watson Tone Analyzer) to recognize emotions from the input information and format the recognition results along with the text. Finally, the device sends the formatted physical and emotional information to the server.

[1247] Examples:

[1248] When User B says, "I have a headache today and I'm a little irritated," the device converts the speech into text and sends it to the server, where the emotion engine analyzes the emotion "irritated." This data is then sent to the server.

[1249] Data collection and analysis

[1250] The server receives and stores the received health and emotional information in a database, assigning a timestamp to the data and managing it in chronological order. The server then analyzes the stored data using an analysis engine (e.g., using Python's pandas library) and compares it with past data to identify patterns in health and emotional states.

[1251] Examples:

[1252] If User C frequently inputs past data on "headaches" and "irritability," the server compares and analyzes this data to identify the frequency and timing of these events. For example, it identifies that these events frequently occur during certain times of the day or in certain situations.

[1253] Generating and providing advice

[1254] The server generates appropriate advice for the user based on the analysis results, taking emotional information into account and suggesting stress management methods or specific actions (e.g., "Try taking deep breaths to relax"). The generated advice is sent to the device, which then communicates it to the user using an AI speaker or chat interface.

[1255] Examples:

[1256] After User D inputs his / her morning physical condition, the AI ​​speaker provides audio advice such as, "Today, limit your caffeine intake and drink plenty of water. Also, I recommend taking deep breaths as a relaxation technique."

[1257] Medical record updates

[1258] The server records the results of that day's diagnosis and advice based on that result in the user's medical record, allowing the user to understand their own health condition and emotional fluctuations over the long term.

[1259] Examples:

[1260] User F's health condition data, emotional data, and provided advice for the past month are organized and stored in a database. The server uses this information to understand the user's health trends.

[1261] Prompt Sentence Examples

[1262] "When a user inputs their emotions and health status, the system converts that information into text, extracts emotional information using an emotion engine, records it in an individual medical record, and provides appropriate advice based on the analysis results. For example, if you input, 'I have a headache today and I'm a little irritated,' the device converts the speech into text, the emotion engine recognizes the irritation, the server analyzes it, and generates appropriate advice."

[1263] This system aims to support users' daily health management, prevent illness, and improve daily performance.

[1264] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1265] System program processing steps

[1266] Step 1: Enter your user registration information

[1267] 1. The user enters personal information such as their name, age, gender, and medical history into the device.

[1268] 2. The terminal checks the entered data to make sure there are no missing or incorrect information.

[1269] 3. Input: User's personal information (name, age, gender, medical history, etc.)

[1270] 4. Output: Checked user personal information

[1271] Examples:

[1272] User A uses the system for the first time and enters his / her name, age, gender, medical history, etc. The terminal checks this information to make sure there are no errors.

[1273] Step 2: Sending data

[1274] 1. The device sends the checked user personal information to the server.

[1275] 2. Use HTTPS as the data transmission protocol to ensure secure communication.

[1276] 3. Input: Checked user personal information

[1277] 4. Output: User personal information sent to the server

[1278] Examples:

[1279] User A's personal information is sent from the terminal to the server via secure communication.

[1280] Step 3: Generate and return a user ID

[1281] 1. The server stores the received user personal information in a database.

[1282] 2. The server generates a new user ID and returns it to the device.

[1283] 3. Input: User personal information sent to the server

[1284] 4. Output: Generated user ID (returned to the terminal)

[1285] Examples:

[1286] The server saves User A's information in a database, generates a user ID, and returns it to the terminal. User A will use this ID from the next time.

[1287] Step 4: Fill out the daily questionnaire

[1288] 1. The user inputs their health condition and emotions for the day into the device by voice or text.

[1289] 2. If the device supports voice input, convert the voice to text (using voice recognition technology).

[1290] 3. Input: User voice or text data

[1291] 4. Output: Data converted to text (in the case of voice input)

[1292] Examples:

[1293] User B speaks, "I have a headache today and I'm feeling a little irritated," and the device converts this into text using voice recognition technology.

[1294] Step 5: Extracting emotional information

[1295] 1. The device uses an emotion engine to recognize emotions from input information.

[1296] 2. Format the recognition results along with the text.

[1297] 3. Input: Data converted to text

[1298] 4. Output: Formatted physical condition information and emotional information

[1299] Examples:

[1300] The text converted from user B's voice data as "I have a headache today and I'm a little irritated" and the emotional information "irritated" extracted by the emotion engine are formatted.

[1301] Step 6: Sending data

[1302] 1. The device sends the formatted physical condition information and emotional information to the server.

[1303] 2. Input: Formatted physical condition information and emotional information

[1304] 3. Output: Physical condition and emotional information sent to the server

[1305] Examples:

[1306] The device transmits user B's physical condition information and emotional information to the server.

[1307] Step 7: Save your data

[1308] 1. The server stores the received physical condition information and emotional information in a database.

[1309] 2. Stored data is time-stamped and managed in chronological order.

[1310] 3. Input: Physical condition and emotional information sent to the server

[1311] 4. Output: Physical condition and emotional information stored in the database

[1312] Examples:

[1313] The server stores user B's physical condition and emotional information in a database and assigns a timestamp.

[1314] Step 8: Data analysis

[1315] 1. The server analyzes the stored data using an analytical engine.

[1316] 2. Compare with historical data to identify patterns in your health and emotions.

[1317] 3. Input: Physical condition information and emotional information in the database

[1318] 4. Output: Analysis results

[1319] Examples:

[1320] Analyze User C's data from the past month and identify the relationship between "headache" and "irritability."

[1321] Step 9: Generating Advice

[1322] 1. The server generates specific advice appropriate for the user based on the analysis results.

[1323] 2. Consider emotional information and suggest stress management strategies and specific actions.

[1324] 3. Input: Analysis results

[1325] 4. Output: Specific advice

[1326] Examples:

[1327] The server generates advice such as, "Reduce your caffeine intake today and drink plenty of water. Try deep breathing as a relaxation technique."

[1328] Step 10: Providing advice

[1329] 1. The generated advice is sent from the server to the device.

[1330] 2. The device uses an AI speaker or chat interface to provide advice to the user.

[1331] 3. Input: Specific advice

[1332] 4. Output: Advice provided to the user

[1333] Examples:

[1334] The AI ​​speaker tells User D, "Reduce your caffeine intake and drink plenty of water. We also recommend taking deep breaths as a relaxation technique."

[1335] Step 11: Update the medical record

[1336] 1. The server records the day's diagnosis results and advice in the user's medical record.

[1337] 2. Allow users to understand fluctuations in their health status over the long term.

[1338] 3. Input: Physical condition information, emotional information, diagnosis results, and advice stored on the server

[1339] 4. Output: Updated medical record

[1340] Examples:

[1341] The server updates and records the health condition, emotional information, diagnosis results, and advice for the past month in the medical record of user F.

[1342] (Application example 2)

[1343] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1344] Conventional health management systems provide advice by collecting and analyzing a user's daily health status, but they do not take the user's emotional state into account, making it difficult to provide personalized advice. Furthermore, there is no mechanism for providing personalized content, and appropriate support based on the user's emotional and health status is not adequately provided. Therefore, there is a need for a system that comprehensively considers both the user's health status and emotional state to provide personalized advice and content.

[1345] The identification process by the identification 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 receiving daily health condition information and emotional information from the user as voice or text data; means for storing the received health condition information and emotional information in a database; means for comparing and analyzing the stored health condition information and emotional information with past data and general medical knowledge; means for generating specific advice for the user based on the analysis results and providing personalized content according to the user's emotional state; means for providing the generated advice and personalized content to the user; and means for recording and updating the generated advice, diagnosis results, and provided content in the user's individual medical record. This makes it possible to comprehensively evaluate both the user's health condition and emotional state and provide more appropriate and individualized advice and personalized content.

[1346] "Audio or text data" is data that provides health and emotional information in audio or text form for a user to input into the system.

[1347] "Health status information" refers to information about the user's physical condition and symptoms, and is data used for daily health management and diagnosis.

[1348] "Emotional information" refers to information about a user's emotions and psychological state, and is data used to understand the user's emotional state.

[1349] "Database" means a system or location for systematically storing and managing health status information and emotional information collected from users.

[1350] "Means for comparison and analysis" refers to methods and technologies for comparing stored health status information and emotional information with historical data and general medical knowledge to evaluate and analyze the user's condition.

[1351] "Means for generating advice" refers to methods and techniques for generating specific and personalized advice for a user based on the results of the comparison and analysis.

[1352] "Means for providing personalized content" refers to methods and technologies for selecting and providing specific content (e.g., videos, music, articles, etc.) to users based on their emotional state.

[1353] "Individual User's Medical Record" means an individual record for recording and updating each user's health status information and emotional information, as well as advice and provided content based on that information.

[1354] To implement this invention, it is necessary to build a system that allows users to input daily health status information and emotional information using a device such as a smartphone or smart glasses, analyzes the information, and provides personalized advice and content. A specific example of this is shown below.

[1355] User Registration / Login

[1356] When a user uses the system for the first time, they enter their personal information and initial health information. This information is sent from the device to the server, which then stores it in a database. The server generates a user ID and sends it back to the device, allowing the user to easily log in from the next time onwards. For example, when a user enters their name, age, gender, and medical history, all of this information is sent to the server, and an individual medical record is created.

[1357] Input and recognition of daily health status and emotional information

[1358] The user inputs their physical condition and emotions for the day in voice or text format. In the case of voice input, the device converts the voice into text data, and then the emotion engine extracts the emotional information. For example, if the user inputs, "I have a headache today and I'm a little irritated," the device converts this voice data into text, recognizes the emotional information of "irritation," and sends this data to the server.

[1359] Data collection and analysis

[1360] The server stores the received health condition information and emotional information in a database. The stored data is then analyzed against past data and general medical knowledge. This data is compared with the user's past health condition and emotional data to infer the cause of the health condition and the influence of emotions. For example, if a user frequently entered data on "headaches" and "irritability" in the past, comparing and analyzing this data can explore the possibility that headaches are linked to emotions.

[1361] Advice and content generation

[1362] Based on the analysis results, the server generates specific and individualized advice for the user, while also providing personalized content according to the user's emotional state. For example, if the user is feeling stressed, relaxation music or meditation videos will be recommended. An example of advice might be, "Today, you should limit your caffeine intake, drink plenty of water, and try relaxation techniques to reduce stress."

[1363] Providing advice and content

[1364] The provided advice and content is communicated to the user via a device. The device can be a smartphone or smart glasses, and these devices provide information to the user through audio and visual means. For example, after the user enters their physical condition information, the AI ​​speaker can provide audio advice such as, "Reduce your caffeine intake today and drink more fluids. We also recommend taking deep breaths as a relaxation technique."

[1365] Medical record updates

[1366] The server records and updates the advice and diagnosis results provided, as well as the history of personalized content provided, in each user's individual medical record. This makes it easier for users to understand their own health condition and emotional fluctuations over the long term, which is useful for future health management and medical consultations. For example, users can record their health condition and emotional fluctuations over the past month and receive advice based on that information at a glance.

[1367] Usage example

[1368] The user launches the app and enters a prompt like this:

[1369] Example prompt: "I have a headache today and I'm feeling a bit irritable."

[1370] Based on the prompts, the system first converts the voice to text, analyzes emotions, and sends the received data to a server, which then analyzes it based on past data and general medical knowledge to generate personalized content, such as specific advice and relaxation music, and delivers it to the user.

[1371] This allows users to improve their health while also taking care of their emotions, improving the quality of their daily lives.

[1372] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1373] Step 1:

[1374] Users use their smartphones or smart glasses to register their personal information and initial health status information, including name, age, gender, medical history, etc. The entered data is sent from the device to the server. The input is in text format, and the server stores it in a database and generates a user ID, which is returned to the device.

[1375] Step 2:

[1376] The user inputs their daily health condition and emotional information into the device. For example, they can input a prompt phrase such as "I have a headache today and I'm a little irritated" by voice. This voice data is converted into text data by the device, and the emotional information is extracted by the emotion engine. The extracted data (health condition information and emotional information) is sent to the server.

[1377] Step 3:

[1378] The server then stores the received health condition and emotional information in a database. This data is compared with similar past data and analyzed against general medical knowledge. For example, the frequency and correlation between "headaches" and "irritability" can be analyzed to infer the causes of health conditions and the influence of emotions.

[1379] Step 4:

[1380] Based on the analysis results, the server generates specific and personalized advice for the user. At the same time, it selects personalized content (e.g., relaxation music or meditation videos) according to the user's emotional state. The generated advice and content are intended to optimally manage the user's health and emotional state.

[1381] Step 5:

[1382] The generated advice and personalized content are then delivered to the user via the device. The smartphone or smart glasses process this information and provide the user with visual or audio information. For example, the device might say, "Today, we recommend limiting your caffeine intake and drinking plenty of water. We also recommend taking deep breaths as a relaxation technique."

[1383] Step 6:

[1384] The server records and updates the history of the advice and content provided in the user's individual medical record. This medical record will be used to understand the user's long-term health and emotional state fluctuations and for future medical consultations and health management. For example, the fluctuations in health and emotional state over the past month can be visualized and saved as graphs.

[1385] This allows users to comprehensively manage their health and emotional state, and improve their quality of life with appropriate advice and content.

[1386] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1387] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1388] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1389] [Fourth embodiment]

[1390] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1391] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1392] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1393] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1394] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1395] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1396] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1397] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1398] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1399] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1400] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1401] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1402] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1403] The present invention is a system that collects, stores, analyzes, and provides advice on a user's daily health status. This system makes it easier for users to manage their own health status and supports the prevention of illness and the improvement of daily performance. To implement the present invention, a program based on the following processing steps is generated, and the operation of each step is explained in detail. Each major process is explained below.

[1404] User Registration / Login

[1405] When a user uses the system for the first time, they enter their personal information and initial health status information. This data is sent from the device to the server, which stores it in a database. The server then generates a user ID and returns it to the device. From then on, the user can log in using this ID.

[1406] For example, when User A uses the system for the first time, he or she enters his or her name, age, gender, medical history, etc. This information is sent from the terminal to the server. The server then creates an individual medical record for User A based on this information, generates a user ID, and sends it back to the terminal. After logging in and completing the initial settings, User A can easily log in next time.

[1407] Daily medical questionnaire entry

[1408] When a user inputs their health status for the day, they input information about their health status by voice or text. The device receives this input, converts it into text if it is voice, and sends it to the server. The server stores this information in a database for later analysis.

[1409] For example, if user B says "I have a headache today," the device converts this speech into text and sends it to the server. The server receives the text information "headache" and stores it in user B's health database.

[1410] Data collection and analysis

[1411] The server compares and analyzes the received data with past data and general medical knowledge. For example, it compares it with other data from a time when headaches were frequent in the past to infer the cause. It also compares it with general medical knowledge to find likely causes and countermeasures.

[1412] For example, if User C has frequently entered "headache" data in the past, the server compares and analyzes this past data with the current data, identifying past patterns and triggering factors (such as climate change or stress levels), and performs a detailed analysis based on general medical knowledge.

[1413] Generating Advice

[1414] The server generates specific advice for the user based on the analysis results. For example, if the accumulated data indicates that a headache is caused by caffeine intake or lack of sleep, the server generates advice such as "Reduce your caffeine intake today and drink plenty of water."

[1415] If User D inputs "I have a headache today," and the server determines through analysis that "it's likely due to caffeine intake," the generated advice will read, "Reduce your caffeine intake today and drink plenty of water." This advice will be provided to User D via the terminal.

[1416] Providing advice

[1417] The generated advice is provided to the user via the device, which then communicates it to the user using an AI speaker or chat interface. The user can then receive this advice and use it in their daily activities and health management.

[1418] For example, after user E enters their morning physical condition, the AI ​​speaker will provide voice advice such as, "It would be good for you to get plenty of rest today. I recommend you drink plenty of water."

[1419] Medical record updates

[1420] The server records and updates the advice and diagnosis results provided that day in the user's individual medical record, making it easier for users to understand their own health condition over the long term. It also makes it possible to detect health trends and abnormalities early in the future.

[1421] For example, all health information entered by user F over the past month and advice provided can be stored in a database and used for future health management and medical consultations.

[1422] As described above, the system of the present invention effectively supports the user's health management and prevention of illness. Users can maintain and improve their health by simply inputting their daily physical condition, receiving analysis and advice from the server, and taking actions based on this information.

[1423] The processing flow will be explained below.

[1424] Step 1:

[1425] The user starts the application and accesses the user registration screen. The terminal displays the user registration form.

[1426] Step 2:

[1427] The user enters personal information such as name, age, gender, email address, chronic illnesses and allergies. The device temporarily stores the entered information and waits for the user to click the registration button.

[1428] Step 3:

[1429] The user clicks the registration button. The device sends the input information to the server.

[1430] Step 4:

[1431] The server stores the received information in a database, generates a user ID, and returns the generated user ID to the device.

[1432] Step 5:

[1433] The terminal receives the user ID and logs the user in. At this stage, the initial user settings are complete.

[1434] Step 6:

[1435] The user inputs their physical condition for the day by voice, and the device converts the voice input into text data.

[1436] Step 7:

[1437] The terminal transmits the converted text data to the server. For example, if the user inputs "I have a headache today," the text data is transmitted to the server.

[1438] Step 8:

[1439] The server stores the received text data in a database. New health status information is added to the database.

[1440] Step 9:

[1441] The server compares and analyzes the stored data with past data and general medical knowledge, for example, to identify the cause of headaches and consider general countermeasures.

[1442] Step 10:

[1443] Based on the analysis results, the server generates specific advice for the user, such as "Reduce your caffeine intake today and drink plenty of water."

[1444] Step 11:

[1445] The server sends the generated advice to the terminal, which receives the advice.

[1446] Step 12:

[1447] The device will provide advice to the user through an AI speaker or chat interface, for example, the AI ​​speaker will tell the user to "limit your caffeine intake today and drink plenty of water."

[1448] Step 13:

[1449] The server records and updates the diagnosis results and advice for that day in the user's individual medical record, enabling long-term health management.

[1450] Example 1

[1451] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1452] In modern society, individual health management is extremely important, and there is a growing need for methods to efficiently collect and analyze this information and provide appropriate advice. However, conventional systems have limitations in effectively collecting and analyzing users' health status information and providing appropriate advice, particularly in terms of comparison and analysis with past data and general medical knowledge. Furthermore, there is a lack of methods for generating appropriate advice using generative AI models and for reliably providing this advice to users. These issues are being addressed.

[1453] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1454] In this invention, the server includes means for receiving daily health condition information from a user as voice or text data, means for storing the received health condition information in a database, means for comparing and analyzing the stored health condition information with past data and general medical knowledge, means for generating specific advice for the user based on the analysis results using a generative AI model, means for providing the generated advice to the user, and means for recording and updating the generated advice and diagnosis results in the user's individual medical record. This makes it possible to efficiently collect, compare, and analyze a user's health condition information, and generate and provide appropriate advice.

[1455] "User" refers to each individual who uses the system.

[1456] "Voice data" refers to data containing health information provided by a user through voice input.

[1457] "Text data" refers to data including health condition information provided by the user through character input.

[1458] "Means for receiving" refers to means for obtaining voice or text data from a user within the system.

[1459] "Database" refers to a structured collection of data for storing received health status information.

[1460] "Means for storing" refers to the system's ability to record received health status information in a database.

[1461] "Means for comparison and analysis" refers to the function of comparing stored data with past data and general medical knowledge and analyzing the information.

[1462] "Generative AI model" refers to an artificial intelligence model used to generate specific advice for users based on the results of data analysis.

[1463] "Means for generating advice" refers to the system's function of using a generative AI model to create specific advice from the analysis results.

[1464] The "means for providing advice" refers to a function for displaying or notifying the user of the generated advice.

[1465] A "medical record" refers to an individual health record that includes a user's health status information, past diagnostic results, advice information, etc.

[1466] "Means of recording and updating" refers to the system's functionality for adding advice and diagnostic results generated each day to a user's individual chart and keeping it up to date.

[1467] The present invention is a system for collecting and analyzing a user's daily health condition and providing appropriate advice based on the collected data. Specific embodiments of this system will be described below.

[1468] The system includes the following main components: a terminal, a server, a database, and a generative AI model.

[1469] User Registration / Login

[1470] When a user uses the system for the first time, they use a terminal to enter their personal information and initial health information. For example, the user enters their name, age, gender, medical history, etc., and the terminal sends this data to the server. The server stores the received data in a database and generates a user ID. This user ID is returned to the terminal, and the user can use this ID to log in from the next time onwards.

[1471] Daily medical questionnaire entry

[1472] To record their daily health status, users use the device to input information by voice or text. In the case of voice input, the device uses the Google Cloud Speech-to-Text API to convert the voice to text. The converted text data is sent to a server, which then stores it in a database.

[1473] Data collection and analysis

[1474] The server compares and analyzes the received data with past data and general medical knowledge. Specifically, the server retrieves past data from the database and compares it using a Python data analysis library (e.g., Pandas). It then analyzes the data using a natural language processing library (e.g., NLTK) to identify likely causes and countermeasures.

[1475] Generating Advice

[1476] Based on the results of the comparison and analysis, the server uses a generative AI model (such as GPT-4) to generate specific advice for the user. For example, if a comparison of past data determines that caffeine intake is the cause, the generated advice might include "limit your caffeine intake today and drink plenty of water."

[1477] Providing advice

[1478] The generated advice is provided to the user via the device, which then communicates the advice to the user as a notification or voice message. Specifically, the advice is provided via the notification function of Android or iOS devices or an AI speaker.

[1479] Medical record updates

[1480] The server records and updates the advice and diagnosis results generated that day in the user's medical record. This allows the user to easily understand long-term fluctuations in their health condition and the recurrence of certain symptoms. The server also uses this information to contribute to future health management and early detection of abnormalities.

[1481] Examples of concrete examples and prompts

[1482] For example, if User A says, "I have a headache today," the device converts the voice input into text and sends it to the server. The server then analyzes the data based on past health data and general medical knowledge. Using the generative AI model based on the analysis results, the server generates advice such as "Reduce your caffeine intake and drink plenty of water today," which is then provided to User A via the device. This is important information that the user can use to improve their future behavior and health management.

[1483] An example prompt is:

[1484] "What AI model would you use to analyze what advice should be generated after a user types, 'I have a headache today,' and provide an example of the advice you would generate?"

[1485] By linking these functions, this system will efficiently and effectively support users in managing their health.

[1486] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1487] Step 1:

[1488] The user enters personal information the first time they use the service.

[1489] The user starts the application and enters personal information such as name, age, gender, and medical history into the registration screen. Input data: Name, age, gender, medical history

[1490] Output data: Personal information input data

[1491] Step 2:

[1492] The device sends the input data to the server

[1493] The device sends the entered personal information to the server via an HTTP request. Specifically, it posts the data using an HTTP client library. Input data: Personal information input data

[1494] Output data: Status of completion of sending to server

[1495] Step 3:

[1496] The server saves the user's data to the database and generates a user ID.

[1497] The server saves the received data in a database (e.g. MySQL) using the INSERT statement and generates a new user ID. Input data: Input data of personal information

[1498] Output: Generated user ID

[1499] Step 4:

[1500] The server returns the generated user ID to the device.

[1501] The server returns an HTTP response containing the generated user ID to the terminal. Specifically, a status code of 200 and JSON data containing the user ID are returned. Input data: Generated user ID

[1502] Output data: User ID response data

[1503] Step 5:

[1504] The user will then log in with the generated user ID.

[1505] The next time the user logs in, they will be authenticated using their user ID and password. Input data: User ID, password

[1506] Output data: Authentication success / failure status

[1507] Step 6:

[1508] The user inputs their daily physical condition by voice or text.

[1509] The user opens the app's questionnaire screen and records their physical condition for the day by voice or text. Input data: Voice or text physical condition data

[1510] Output data: Converted text data

[1511] Step 7:

[1512] Your device converts your voice input into text

[1513] The device uses the Google Cloud Speech-to-Text API to convert voice input into text. Input data: Voice data

[1514] Output data: Text data

[1515] Step 8:

[1516] The device sends the converted text data to the server.

[1517] The converted text data is sent from the terminal to the server via an HTTP request. Input data: Text data

[1518] Output data: Status of completion of sending to server

[1519] Step 9:

[1520] The server stores the received data in the database

[1521] The server saves the received data in the user's database. This also uses the MySQL INSERT statement. Input data: Text data

[1522] Output data: Status of completion of saving to database

[1523] Step 10:

[1524] The server retrieves the received data from the database

[1525] The server retrieves past health data from the database using a SELECT statement. Input data: User ID

[1526] Output data: Past health data

[1527] Step 11:

[1528] The server compares past data with current data

[1529] The server compares the past and current data using a Python data analysis library (e.g., Pandas). Input data: past health data, current health data

[1530] Output data: Comparison results

[1531] Step 12:

[1532] The server analyzes the comparison results against general medical knowledge

[1533] The server uses a natural language processing library (e.g., NLTK) to analyze the comparison results against general medical knowledge. Input data: Comparison results, medical knowledge data

[1534] Output data: Analysis results

[1535] Step 13:

[1536] The server generates advice based on the analysis results.

[1537] The server generates specific advice using a generative AI model (e.g., GPT-4) based on the analysis results. Input data: Analysis results

[1538] Output data: Generated advice

[1539] Step 14:

[1540] Sends server-generated advice to the device

[1541] The generated advice is sent to the terminal in JSON format. Input data: Generated advice

[1542] Output data: Status of completion of transmission to the terminal

[1543] Step 15:

[1544] The device displays or reads the generated advice to the user.

[1545] The device notifies the user of the advice using the app's notification function or voice alert function.

[1546] Output data: Notification content to the user

[1547] Step 16:

[1548] The server records and updates the diagnosis results and advice for that day in the patient chart.

[1549] The server saves the diagnosis results and advice for the day in the user's chart and updates it to the latest version. Input data: diagnosis results, advice

[1550] Output data: Updated medical record data

[1551] (Application example 1)

[1552] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1553] Conventional health management systems allow users to input their own health status and receive advice based on the analysis results. However, these systems rely on devices such as smartphones and computers, and users may not always have easy access to these devices. In addition, there are limitations to voice input and real-time notification functions, which can reduce the convenience of health management. This has made it difficult for users to quickly and appropriately manage their health in their daily lives.

[1554] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1555] In this invention, the server includes: means for receiving daily health condition information from a user as voice or text data; means for storing the received health condition information in a database; means for comparing and analyzing the stored health condition information with past data and general medical knowledge; means for generating specific advice for the user based on the analysis results; means for providing the generated advice to the user; means for recording and updating the generated advice and diagnosis results in the user's individual medical record; and means for receiving health condition information from the user using smart glasses and providing the information as visual or audio notifications, thereby enabling users to quickly and easily input and receive feedback on their health condition via the smart glasses in their daily lives.

[1556] "Health condition information" refers to information related to the user's physical condition and health, such as data on body temperature, blood pressure, whether or not the user has a headache, and sleep duration.

[1557] "Voice or Text Data" means information provided by a User through spoken or written input.

[1558] "Database" means a system for systematically storing and managing health status information and user information.

[1559] "Comparison and analysis" refers to the process of evaluating stored data using statistical methods and machine learning algorithms to derive meaningful results.

[1560] "Specific advice" means specific suggestions or instructions generated based on analyzed data that can help the user improve or maintain their health.

[1561] "Means for providing to the user" means a mechanism for conveying the generated advice to the user through audio notification or visual display.

[1562] "Medical Record" means a digital file that records a user's individual health status information, diagnostic results, and the history of advice provided.

[1563] "Smart glasses" refers to a wearable device that has built-in functions such as information display and voice input, and that allows users to integrate digital information with the physical world when wearing it.

[1564] "Visual or audio notification" means a method of providing information to a user through a display or audio speaker.

[1565] To realize this invention, a system in which a user, a server, and smart glasses work together is required. A specific embodiment of this system will be described below.

[1566] Hardware and software used

[1567] Hardware:

[1568] Smart glasses: Wearable devices with functions such as information display and voice input. Examples include Google Glass and Vuzix Blade.

[1569] Server: A central processing unit that receives, stores, analyzes data, and generates advice.

[1570] software:

[1571] Speech Recognition: Converts voice input into text data using the Google Cloud Speech-to-Text API.

[1572] Database: Firebase is used to store user health and personal information.

[1573] Data analysis: Compare and analyze data using Python's pandas and scikit-learn.

[1574] Advice generation: Using a generative AI model (e.g., GPT-4 API), specific advice is generated based on the analysis results.

[1575] System Operation

[1576] User Registration and Login

[1577] When a user uses the system for the first time, they scan the QR code displayed on the smart glasses screen with their smartphone to sign up for the application. The user enters information such as their name, age, gender, and medical history by voice or text, and this data is sent to Firebase. Once registration is complete, the server generates a user ID and notifies the user. From then on, the user logs in to the system using this ID.

[1578] Enter your health status

[1579] To input their daily health status, users can use the microphone in their smart glasses to voice-report their health status. For example, if they say, "I have a slight headache today," the smart glasses will convert this voice data into text data using the Google Cloud Speech-to-Text API. The text data will then be sent to Firebase and stored in the user's individual database.

[1580] Data analysis and advice generation

[1581] The server periodically collects health status data stored in Firebase and analyzes it using Python's pandas and scikit-learn. Based on the analysis results, a generative AI model (such as the GPT-4 API) is used to generate specific advice appropriate for the user. For example, if the data indicates frequent headaches or elevated stress levels, the server generates advice such as "It would be a good idea to limit caffeine and drink more water today."

[1582] Providing advice

[1583] The generated advice is provided to the user in real time via the smart glasses as a visual or audio notification, such as a message on the smart glasses display saying "You should get plenty of rest today. We recommend you drink plenty of water," or a similar message through the audio speaker.

[1584] Medical record updates

[1585] The server manages long-term health conditions by recording and updating the generated advice and diagnosis results in the user's individual medical record, allowing users to easily check their past health conditions and the advice they received.

[1586] Examples of concrete examples and prompts

[1587] For example, the following prompt could be input to a generative AI model:

[1588] Today's health data:

[1589] Headache: Yes

[1590] Sleep time: 6 hours

[1591] Caffeine intake: 2 cups

[1592] Stress level: High

[1593] Generate health advice for this user based on historical data and medical knowledge.

[1594] As described above, this system allows users to quickly and easily input and receive feedback on their health status through smart glasses in their daily lives, enabling more efficient and effective health management.

[1595] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1596] Step 1:

[1597] User Registration:

[1598] A user puts on the smart glasses and begins signing up for the application by scanning a QR code displayed on the glasses with their smartphone for initial registration. They enter their information (name, age, gender, medical history, etc.) via voice and text. This data is sent to Firebase, and the server generates a user ID and notifies the user of that ID.

[1599] Input: Name, age, gender, medical history, etc.

[1600] Output: User ID

[1601] Step 2:

[1602] Login:

[1603] The user logs into the system via the smart glasses using the generated user ID and password, and the server authenticates this and allows the user to access their individual database.

[1604] Input: User ID, Password

[1605] Output: Authentication status, access rights

[1606] Step 3:

[1607] Enter your health status:

[1608] Users report their daily health status by voice using the microphone in their smart glasses. The voice data is converted into text data using the Google Cloud Speech-to-Text API. The text data is sent to Firebase and stored in the user's individual database. For example, if a user voice-inputs, "I have a slight headache today," that information is stored as text data.

[1609] Input: Speech data (e.g., "I have a slight headache today")

[1610] Output: Text data, information stored in the user database

[1611] Step 4:

[1612] Data Analysis:

[1613] The server periodically collects health status data stored in Firebase and performs data analysis using Python's pandas and scikit-learn. These tools are used to compare the data with historical data and general medical knowledge to identify specific patterns or trends, such as detecting frequent headaches or elevated stress levels.

[1614] Input: Health condition data (e.g., "headache" as text data)

[1615] Output: Analysis results (e.g., estimated cause of headache)

[1616] Step 5:

[1617] Advice Generation:

[1618] Based on the analysis results, the server generates appropriate advice using a generative AI model (such as the GPT-4 API). For example, if data analysis predicts that frequent headaches are caused by excessive caffeine intake, the server generates the advice, "It would be good to limit your caffeine intake and drink plenty of water."

[1619] Input: Analysis results (e.g., headache is caused by excessive caffeine intake)

[1620] Output: Generated advice (e.g., "Reduce your caffeine intake and drink plenty of water.")

[1621] Step 6:

[1622] Providing advice:

[1623] The generated advice is provided to the user in real time through the smart glasses as visual and audio notifications, such as a message on the smart glasses display saying "Avoid caffeine today" or a similar advice being spoken through the audio speaker.

[1624] Input: Generated advice

[1625] Output: Advice given to the user

[1626] Step 7:

[1627] Update medical records:

[1628] The server records and updates the generated advice and diagnosis results in the user's individual medical record, enabling long-term health management. Users can easily check their past health status and the advice they received.

[1629] Input: Generated advice, diagnostic results

[1630] Output: Updated user record

[1631] These steps will enable users to quickly and easily input and receive feedback on their health status through the smart glasses, enabling more effective long-term health management.

[1632] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1633] The present invention is a system that combines a conventional system that collects, stores, analyzes, and provides advice on a user's daily health status with an emotion engine that recognizes the user's emotions. This system makes it easier for users to manage their own health and emotional status, and supports the prevention of illness and the improvement of daily performance. Furthermore, by taking emotional information into account, it becomes possible to provide more personalized advice. Each major process in the embodiment of the present invention is specifically described below.

[1634] User Registration / Login

[1635] When a user uses the system for the first time, they enter their personal information and initial health status information. This data is sent from the device to the server, which stores it in a database. The server then generates a user ID and returns it to the device. From then on, the user can log in using this ID.

[1636] For example, when User A uses the system for the first time, he or she enters his or her name, age, gender, medical history, etc. This information is sent from the terminal to the server. The server then creates an individual medical record for User A based on this information, generates a user ID, and sends it back to the terminal. After logging in and completing the initial settings, User A can easily log in next time.

[1637] Daily questionnaire entry and emotion recognition

[1638] When a user inputs their physical condition and emotions for the day, they input information about their physical condition by voice or text. The device receives this input, converts it into text if it is voice, and sends it to the server. The device also uses an emotion engine to extract emotional information from the user's voice. The extracted emotional information is also sent to the server.

[1639] For example, if user B says, "I have a headache today and I'm a little irritated," the device converts this speech into text and uses the emotion engine to recognize the emotion "irritated." This data is then sent to the server.

[1640] Data collection and analysis

[1641] The server stores the received health condition and emotion information in a database. The stored data is then analyzed in conjunction with past data and general medical knowledge. For example, by comparing past health condition and emotion data, the cause of the health condition and the influence of emotions can be inferred.

[1642] For example, if User C frequently entered data on "headaches" and "irritability" in the past, the server would compare and analyze this past data with the current data. It may conclude that headaches are likely to occur in conjunction with emotional states.

[1643] Generating Advice

[1644] Based on the analysis results, the server generates specific and personalized advice for the user. By taking emotional information into account, more appropriate advice becomes possible. For example, in addition to the usual advice of "limit your caffeine intake and drink plenty of water today," the server can generate advice such as "try relaxation techniques to reduce stress."

[1645] If user D inputs data such as "I have a headache today and I'm feeling a little irritated," and the server determines from the analysis results that "stress is likely to be a contributing factor to the headache," the following personalized advice will be created.

[1646] Providing advice

[1647] The generated advice is provided to the user via the device, which then uses an AI speaker and chat interface to communicate specific advice to the user. The user can then receive this advice and apply it to their daily activities and health management.

[1648] For example, after User E inputs his / her morning physical condition, the AI ​​speaker will give him / her advice in voice, such as, "Avoid caffeine intake today and drink plenty of water. Also, I recommend taking deep breaths as a relaxation technique."

[1649] Medical record updates

[1650] The server records and updates the diagnosis results and advice for that day in the user's individual medical record. This allows users to easily understand their own health condition and emotional fluctuations over the long term. It also makes it possible to detect health trends and abnormalities early in the future.

[1651] For example, all health condition information entered by user F in the past month, advice provided, and emotional information are stored in a database, which can be used for future health management and medical consultations.

[1652] As described above, the system of the present invention effectively supports the management of a user's health and emotional state and the prevention of illness. Users can maintain and improve their health by simply inputting their daily physical condition and emotions, receiving analysis and advice from the server, and taking actions based on this information.

[1653] The processing flow will be explained below.

[1654] Step 1:

[1655] The user starts the application and accesses the user registration screen. The terminal displays the user registration form.

[1656] Step 2:

[1657] The user enters personal information such as name, age, gender, email address, chronic illnesses and allergies. The device temporarily stores the entered information and waits for the user to click the registration button.

[1658] Step 3:

[1659] The user clicks the registration button. The device sends the input information to the server.

[1660] Step 4:

[1661] The server stores the received information in a database, generates a user ID, and returns the generated user ID to the device.

[1662] Step 5:

[1663] The terminal receives the user ID and logs the user in. At this stage, the initial user settings are complete.

[1664] Step 6:

[1665] The user inputs their physical condition for the day by voice. The device converts the voice input into text data. The device also uses an emotion engine to extract emotional information from the user's voice.

[1666] Step 7:

[1667] The terminal transmits the converted text data and emotion data to the server. For example, if the user inputs "I have a headache today and I'm a little irritated," the text data and the emotion data "irritated" are transmitted to the server.

[1668] Step 8:

[1669] The server stores the received text data and emotion data in a database. New health status information and emotion information are added to the database.

[1670] Step 9:

[1671] The server analyzes the stored data in comparison with past data and general medical knowledge, for example, to identify the cause of headaches or consider the influence of emotions.

[1672] Step 10:

[1673] Based on the analysis results, the server generates specific advice for the user. For example, in addition to the usual advice of "limit your caffeine intake and drink plenty of water today," it generates advice such as "try relaxation techniques to reduce stress."

[1674] Step 11:

[1675] The server sends the generated advice to the terminal, which receives the advice.

[1676] Step 12:

[1677] The device will provide advice to the user through an AI speaker or chat interface. For example, the AI ​​speaker will tell the user, "Today, limit your caffeine intake and drink plenty of water. I also recommend taking deep breaths as a relaxation technique."

[1678] Step 13:

[1679] The server records and updates the diagnosis results and advice for that day in the user's individual medical record, enabling long-term health management.

[1680] Example 2

[1681] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1682] Conventional health management systems focus on collecting and analyzing users' health status information, but they are unable to consider users' emotional information, making it difficult to provide more personalized and accurate advice. Furthermore, by ignoring the impact of emotions on health status, important factors in user health management are often overlooked. As a result, prevention and performance improvement may not be sufficiently effective.

[1683] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving daily health condition information and emotional information from the user as voice or text data, means for storing the received health condition information and emotional information in a database, and means for comparing and analyzing the stored health condition information and emotional information with past data and general medical knowledge. This makes it possible to generate and provide more personalized and specific advice that takes the user's emotional information into consideration.

[1684] "User" refers to a person who utilizes the system to input and manage their own health and emotional state.

[1685] "Audio or text data" refers to an information format used by a user to express his or her health condition or emotional state, and is in the form of audio data or text data.

[1686] "Health status information" refers to data recorded by a user regarding their daily physical condition and symptoms.

[1687] "Emotion information" is data in which a user records their daily emotional state, and includes information about specific emotions (for example, happiness, sadness, anger, etc.).

[1688] "Database" refers to a system that stores and manages received health status information and emotional information over the long term.

[1689] "Historical Data" refers to health and emotional information previously collected from a user that is stored in the system.

[1690] "General medical knowledge" refers to the basic information based on medical knowledge and research results, which is used to analyze health conditions and generate advice.

[1691] "Analysis" refers to the process of analyzing the received and stored data to identify patterns and causes of the user's health and emotional state.

[1692] "Advice" refers to specific suggestions that are generated based on the analysis results and are useful for the user's lifestyle and health management.

[1693] "Medical Record" refers to a digital record for recording and storing a User's individual health and emotional information.

[1694] "Emotion engine" refers to software or algorithms for extracting emotional information from a user's voice or text data.

[1695] "Speech recognition technology" refers to technology that converts speech into text data and is used to process user speech input.

[1696] MODE FOR CARRYING OUT THE INVENTION

[1697] The present invention is a system that collects and analyzes a user's daily health and emotional state to provide personalized advice. The system receives voice or text data entered by the user, stores it in a database, and compares and analyzes it with past data and general medical knowledge.

[1698] User Registration / Login

[1699] When a user uses the system for the first time, they enter their personal information (name, age, gender, medical history, etc.) into the terminal. The terminal checks the entered data to see if there are any omissions or errors. Next, the terminal sends the user's registration information to the server, which stores the received data in a database. The server generates a new user ID and returns it to the terminal. From then on, the user can log in to the system using this user ID.

[1700] Examples:

[1701] User A uses the system for the first time and enters his / her name, age, and gender. The device sends the input data to the server, which saves the data and then generates a user ID and sends it back to the device. User A can then easily log in using the generated ID from the next time.

[1702] Daily questionnaire entry and emotion recognition

[1703] The user inputs their physical and emotional state for the day into the device via voice or text. The device uses speech recognition technology (e.g., Google Cloud Speech-to-Text) to convert the voice input into text. Next, the device uses an emotion engine (e.g., IBM Watson Tone Analyzer) to recognize emotions from the input information and format the recognition results along with the text. Finally, the device sends the formatted physical and emotional information to the server.

[1704] Examples:

[1705] When User B says, "I have a headache today and I'm a little irritated," the device converts the speech into text and sends it to the server, where the emotion engine analyzes the emotion "irritated." This data is then sent to the server.

[1706] Data collection and analysis

[1707] The server receives and stores the received health and emotional information in a database, assigning a timestamp to the data and managing it in chronological order. The server then analyzes the stored data using an analysis engine (e.g., using Python's pandas library) and compares it with past data to identify patterns in health and emotional states.

[1708] Examples:

[1709] If User C frequently inputs past data on "headaches" and "irritability," the server compares and analyzes this data to identify the frequency and timing of these events. For example, it identifies that these events frequently occur during certain times of the day or in certain situations.

[1710] Generating and providing advice

[1711] The server generates appropriate advice for the user based on the analysis results, taking emotional information into account and suggesting stress management methods or specific actions (e.g., "Try taking deep breaths to relax"). The generated advice is sent to the device, which then communicates it to the user using an AI speaker or chat interface.

[1712] Examples:

[1713] After User D inputs his / her morning physical condition, the AI ​​speaker provides audio advice such as, "Today, limit your caffeine intake and drink plenty of water. Also, I recommend taking deep breaths as a relaxation technique."

[1714] Medical record updates

[1715] The server records the results of that day's diagnosis and advice based on that result in the user's medical record, allowing the user to understand their own health condition and emotional fluctuations over the long term.

[1716] Examples:

[1717] User F's health condition data, emotional data, and provided advice for the past month are organized and stored in a database. The server uses this information to understand the user's health trends.

[1718] Prompt Sentence Examples

[1719] "When a user inputs their emotions and health status, the system converts that information into text, extracts emotional information using an emotion engine, records it in an individual medical record, and provides appropriate advice based on the analysis results. For example, if you input, 'I have a headache today and I'm a little irritated,' the device converts the speech into text, the emotion engine recognizes the irritation, the server analyzes it, and generates appropriate advice."

[1720] This system aims to support users' daily health management, prevent illness, and improve daily performance.

[1721] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1722] System program processing steps

[1723] Step 1: Enter your user registration information

[1724] 1. The user enters personal information such as their name, age, gender, and medical history into the device.

[1725] 2. The terminal checks the entered data to make sure there are no missing or incorrect information.

[1726] 3. Input: User's personal information (name, age, gender, medical history, etc.)

[1727] 4. Output: Checked user personal information

[1728] Examples:

[1729] User A uses the system for the first time and enters his / her name, age, gender, medical history, etc. The terminal checks this information to make sure there are no errors.

[1730] Step 2: Sending data

[1731] 1. The device sends the checked user personal information to the server.

[1732] 2. Use HTTPS as the data transmission protocol to ensure secure communication.

[1733] 3. Input: Checked user personal information

[1734] 4. Output: User personal information sent to the server

[1735] Examples:

[1736] User A's personal information is sent from the terminal to the server via secure communication.

[1737] Step 3: Generate and return a user ID

[1738] 1. The server stores the received user personal information in a database.

[1739] 2. The server generates a new user ID and returns it to the device.

[1740] 3. Input: User personal information sent to the server

[1741] 4. Output: Generated user ID (returned to the terminal)

[1742] Examples:

[1743] The server saves User A's information in a database, generates a user ID, and returns it to the terminal. User A will use this ID from the next time.

[1744] Step 4: Fill out the daily questionnaire

[1745] 1. The user inputs their health condition and emotions for the day into the device by voice or text.

[1746] 2. If the device supports voice input, convert the voice to text (using voice recognition technology).

[1747] 3. Input: User voice or text data

[1748] 4. Output: Data converted to text (in the case of voice input)

[1749] Examples:

[1750] User B speaks, "I have a headache today and I'm feeling a little irritated," and the device converts this into text using voice recognition technology.

[1751] Step 5: Extracting emotional information

[1752] 1. The device uses an emotion engine to recognize emotions from input information.

[1753] 2. Format the recognition results along with the text.

[1754] 3. Input: Data converted to text

[1755] 4. Output: Formatted physical condition information and emotional information

[1756] Examples:

[1757] The text converted from user B's voice data as "I have a headache today and I'm a little irritated" and the emotional information "irritated" extracted by the emotion engine are formatted.

[1758] Step 6: Sending data

[1759] 1. The device sends the formatted physical condition information and emotional information to the server.

[1760] 2. Input: Formatted physical condition information and emotional information

[1761] 3. Output: Physical condition and emotional information sent to the server

[1762] Examples:

[1763] The device transmits user B's physical condition information and emotional information to the server.

[1764] Step 7: Save your data

[1765] 1. The server stores the received physical condition information and emotional information in a database.

[1766] 2. Stored data is time-stamped and managed in chronological order.

[1767] 3. Input: Physical condition and emotional information sent to the server

[1768] 4. Output: Physical condition and emotional information stored in the database

[1769] Examples:

[1770] The server stores user B's physical condition and emotional information in a database and assigns a timestamp.

[1771] Step 8: Data analysis

[1772] 1. The server analyzes the stored data using an analytical engine.

[1773] 2. Compare with historical data to identify patterns in your health and emotions.

[1774] 3. Input: Physical condition information and emotional information in the database

[1775] 4. Output: Analysis results

[1776] Examples:

[1777] Analyze User C's data from the past month and identify the relationship between "headache" and "irritability."

[1778] Step 9: Generating Advice

[1779] 1. The server generates specific advice appropriate for the user based on the analysis results.

[1780] 2. Consider emotional information and suggest stress management strategies and specific actions.

[1781] 3. Input: Analysis results

[1782] 4. Output: Specific advice

[1783] Examples:

[1784] The server generates advice such as, "Reduce your caffeine intake today and drink plenty of water. Try deep breathing as a relaxation technique."

[1785] Step 10: Providing advice

[1786] 1. The generated advice is sent from the server to the device.

[1787] 2. The device uses an AI speaker or chat interface to provide advice to the user.

[1788] 3. Input: Specific advice

[1789] 4. Output: Advice provided to the user

[1790] Examples:

[1791] The AI ​​speaker tells User D, "Reduce your caffeine intake and drink plenty of water. We also recommend taking deep breaths as a relaxation technique."

[1792] Step 11: Update the medical record

[1793] 1. The server records the day's diagnosis results and advice in the user's medical record.

[1794] 2. Allow users to understand fluctuations in their health status over the long term.

[1795] 3. Input: Physical condition information, emotional information, diagnosis results, and advice stored on the server

[1796] 4. Output: Updated medical record

[1797] Examples:

[1798] The server updates and records the health condition, emotional information, diagnosis results, and advice for the past month in the medical record of user F.

[1799] (Application example 2)

[1800] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1801] Conventional health management systems provide advice by collecting and analyzing a user's daily health status, but they do not take the user's emotional state into account, making it difficult to provide personalized advice. Furthermore, there is no mechanism for providing personalized content, and appropriate support based on the user's emotional and health status is not adequately provided. Therefore, there is a need for a system that comprehensively considers both the user's health status and emotional state to provide personalized advice and content.

[1802] The identification process by the identification 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 receiving daily health condition information and emotional information from the user as voice or text data; means for storing the received health condition information and emotional information in a database; means for comparing and analyzing the stored health condition information and emotional information with past data and general medical knowledge; means for generating specific advice for the user based on the analysis results and providing personalized content according to the user's emotional state; means for providing the generated advice and personalized content to the user; and means for recording and updating the generated advice, diagnosis results, and provided content in the user's individual medical record. This makes it possible to comprehensively evaluate both the user's health condition and emotional state and provide more appropriate and individualized advice and personalized content.

[1803] "Audio or text data" is data that provides health and emotional information in audio or text form for a user to input into the system.

[1804] "Health status information" refers to information about the user's physical condition and symptoms, and is data used for daily health management and diagnosis.

[1805] "Emotional information" refers to information about a user's emotions and psychological state, and is data used to understand the user's emotional state.

[1806] "Database" means a system or location for systematically storing and managing health status information and emotional information collected from users.

[1807] "Means for comparison and analysis" refers to methods and technologies for comparing stored health status information and emotional information with historical data and general medical knowledge to evaluate and analyze the user's condition.

[1808] "Means for generating advice" refers to methods and techniques for generating specific and personalized advice for a user based on the results of the comparison and analysis.

[1809] "Means for providing personalized content" refers to methods and technologies for selecting and providing specific content (e.g., videos, music, articles, etc.) to users based on their emotional state.

[1810] "Individual User's Medical Record" means an individual record for recording and updating each user's health status information and emotional information, as well as advice and provided content based on that information.

[1811] To implement this invention, it is necessary to build a system that allows users to input daily health status information and emotional information using a device such as a smartphone or smart glasses, analyzes the information, and provides personalized advice and content. A specific example of this is shown below.

[1812] User Registration / Login

[1813] When a user uses the system for the first time, they enter their personal information and initial health information. This information is sent from the device to the server, which then stores it in a database. The server generates a user ID and sends it back to the device, allowing the user to easily log in from the next time onwards. For example, when a user enters their name, age, gender, and medical history, all of this information is sent to the server, and an individual medical record is created.

[1814] Input and recognition of daily health status and emotional information

[1815] The user inputs their physical condition and emotions for the day in voice or text format. In the case of voice input, the device converts the voice into text data, and then the emotion engine extracts the emotional information. For example, if the user inputs, "I have a headache today and I'm a little irritated," the device converts this voice data into text, recognizes the emotional information of "irritation," and sends this data to the server.

[1816] Data collection and analysis

[1817] The server stores the received health condition information and emotional information in a database. The stored data is then analyzed against past data and general medical knowledge. This data is compared with the user's past health condition and emotional data to infer the cause of the health condition and the influence of emotions. For example, if a user frequently entered data on "headaches" and "irritability" in the past, comparing and analyzing this data can explore the possibility that headaches are linked to emotions.

[1818] Advice and content generation

[1819] Based on the analysis results, the server generates specific and individualized advice for the user, while also providing personalized content according to the user's emotional state. For example, if the user is feeling stressed, relaxation music or meditation videos will be recommended. An example of advice might be, "Today, you should limit your caffeine intake, drink plenty of water, and try relaxation techniques to reduce stress."

[1820] Providing advice and content

[1821] The provided advice and content is communicated to the user via a device. The device can be a smartphone or smart glasses, and these devices provide information to the user through audio and visual means. For example, after the user enters their physical condition information, the AI ​​speaker can provide audio advice such as, "Reduce your caffeine intake today and drink more fluids. We also recommend taking deep breaths as a relaxation technique."

[1822] Medical record updates

[1823] The server records and updates the advice and diagnosis results provided, as well as the history of personalized content provided, in each user's individual medical record. This makes it easier for users to understand their own health condition and emotional fluctuations over the long term, which is useful for future health management and medical consultations. For example, users can record their health condition and emotional fluctuations over the past month and receive advice based on that information at a glance.

[1824] Usage example

[1825] The user launches the app and enters a prompt like this:

[1826] Example prompt: "I have a headache today and I'm feeling a bit irritable."

[1827] Based on the prompts, the system first converts the voice to text, analyzes emotions, and sends the received data to a server, which then analyzes it based on past data and general medical knowledge to generate personalized content, such as specific advice and relaxation music, and delivers it to the user.

[1828] This allows users to improve their health while also taking care of their emotions, improving the quality of their daily lives.

[1829] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1830] Step 1:

[1831] Users use their smartphones or smart glasses to register their personal information and initial health status information, including name, age, gender, medical history, etc. The entered data is sent from the device to the server. The input is in text format, and the server stores it in a database and generates a user ID, which is returned to the device.

[1832] Step 2:

[1833] The user inputs their daily health condition and emotional information into the device. For example, they can input a prompt phrase such as "I have a headache today and I'm a little irritated" by voice. This voice data is converted into text data by the device, and the emotional information is extracted by the emotion engine. The extracted data (health condition information and emotional information) is sent to the server.

[1834] Step 3:

[1835] The server then stores the received health condition and emotional information in a database. This data is compared with similar past data and analyzed against general medical knowledge. For example, the frequency and correlation between "headaches" and "irritability" can be analyzed to infer the causes of health conditions and the influence of emotions.

[1836] Step 4:

[1837] Based on the analysis results, the server generates specific and personalized advice for the user. At the same time, it selects personalized content (e.g., relaxation music or meditation videos) according to the user's emotional state. The generated advice and content are intended to optimally manage the user's health and emotional state.

[1838] Step 5:

[1839] The generated advice and personalized content are then delivered to the user via the device. The smartphone or smart glasses process this information and provide the user with visual or audio information. For example, the device might say, "Today, we recommend limiting your caffeine intake and drinking plenty of water. We also recommend taking deep breaths as a relaxation technique."

[1840] Step 6:

[1841] The server records and updates the history of the advice and content provided in the user's individual medical record. This medical record will be used to understand the user's long-term health and emotional state fluctuations and for future medical consultations and health management. For example, the fluctuations in health and emotional state over the past month can be visualized and saved as graphs.

[1842] This allows users to comprehensively manage their health and emotional state, and improve their quality of life with appropriate advice and content.

[1843] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1844] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1845] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1846] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1847] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1848] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1849] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1850] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1851] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1852] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1853] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1854] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1855] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1856] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1857] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1858] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1859] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1860] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1861] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1862] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1863] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1864] The following is further disclosed regarding the above embodiment.

[1865] (Claim 1)

[1866] means for receiving daily health status information from a user as voice or text data;

[1867] means for storing the received health status information in a database;

[1868] A means of comparing and analyzing stored health status information with past data and general medical knowledge;

[1869] means for generating specific advice for the user based on the analysis results;

[1870] means for providing the generated advice to a user;

[1871] A means for recording and updating the generated advice and diagnostic results in the user's individual medical record;

[1872] A system including:

[1873] (Claim 2)

[1874] 10. The system of claim 1, further comprising means for converting voice input into text data.

[1875] (Claim 3)

[1876] 10. The system of claim 1, further comprising means for registering and storing the user's personal information and initial health status information.

[1877] "Example 1"

[1878] (Claim 1)

[1879] means for receiving daily health status information from a user as voice or text data;

[1880] means for storing the received health status information in a database;

[1881] A means of comparing and analyzing stored health status information with past data and general medical knowledge;

[1882] A means for generating specific advice for a user based on the analysis results using a generative AI model;

[1883] means for providing the generated advice to a user;

[1884] A means for recording and updating the generated advice and diagnostic results in the user's individual medical record;

[1885] A system including:

[1886] (Claim 2)

[1887] 10. The system of claim 1, further comprising means for converting voice input into text data.

[1888] (Claim 3)

[1889] 10. The system of claim 1, further comprising means for registering and storing the user's personal information and initial health status information.

[1890] "Application Example 1"

[1891] (Claim 1)

[1892] means for receiving daily health status information from a user as voice or text data;

[1893] means for storing the received health status information in a database;

[1894] A means of comparing and analyzing stored health status information with past data and general medical knowledge;

[1895] means for generating specific advice for the user based on the analysis results;

[1896] means for providing the generated advice to a user;

[1897] A means for recording and updating the generated advice and diagnostic results in the user's individual medical record;

[1898] means for receiving health status information from a user using the smart glasses and providing the information as a visual or audio notification;

[1899] A system including:

[1900] (Claim 2)

[1901] 10. The system of claim 1, further comprising means for converting voice input into text data.

[1902] (Claim 3)

[1903] 10. The system of claim 1, further comprising means for registering and storing the user's personal information and initial health status information.

[1904] "Example 2: Combining Emotion Engines"

[1905] (Claim 1)

[1906] means for receiving daily health status information and emotion information from a user as voice or text data;

[1907] means for storing the received health status information and emotion information in a database;

[1908] A means for comparing and analyzing stored health status information and emotional information with past data and general medical knowledge;

[1909] means for generating specific advice for the user based on the analysis results;

[1910] means for providing the generated advice to a user;

[1911] A means for recording and updating the generated advice and diagnostic results in the user's individual medical record;

[1912] A system including:

[1913] (Claim 2)

[1914] 10. The system of claim 1, further comprising means for converting the speech input into text data and means for extracting emotion information.

[1915] (Claim 3)

[1916] 10. The system of claim 1, further comprising means for registering and storing the u...

Claims

1. means for receiving daily health status information from a user as voice or text data; means for storing the received health status information in a database; A means of comparing and analyzing stored health status information with past data and general medical knowledge; means for generating specific advice for the user based on the analysis results; means for providing the generated advice to a user; A means for recording and updating the generated advice and diagnostic results in the user's individual medical record; A system including:

2. 10. The system of claim 1, further comprising means for converting speech input into text data.

3. The system of claim 1 , further comprising means for registering and storing personal information and initial health status information of the user.

Images