System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting basic and medical information of a user; means for receiving and storing the inputted information in a database; means for generating a user profile based on the stored information; means for displaying the generated menu to the user and receiving a selection; means for recording the user's selection information; means for periodically checking and notifying the user's performance; means for collecting and storing the user's feedback; and means for analyzing the collected data and notifying the user of the result.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] Traditionally, medical dietary guidance for elderly people and patients who cannot be hospitalized has been provided by specialized facilities, and there has been a lack of systems to support appropriate medical diet intake at home. Furthermore, it has been difficult to suggest medical diets that reflect individual health conditions and dietary preferences, and efficient feedback collection and subsequent reflection in treatment plans have been insufficient. The purpose of this invention is to provide a system that allows users to consume appropriate medical diets at home and maintain and improve their health, thereby solving the above problems. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including: means for inputting a user's basic information and medical information; means for receiving the input information and storing it in a database; means for generating a user profile based on the stored information; means for generating an appropriate medical diet menu based on the generated user profile; means for displaying the generated menu to the user and accepting selections; means for recording the user's selection information; means for periodically checking and notifying the user's progress; means for collecting and storing user feedback; and means for analyzing the collected data and notifying the user of the results. This system allows users to receive individually customized medical diet suggestions at home, enabling efficient health management.

[0006] "Users" refer to individuals who use this system, such as elderly people who require medical food or patients who cannot be hospitalized.

[0007] "Basic information" refers to basic personal information such as the user's name, age, and gender.

[0008] "Medical Information" refers to detailed medical information about a user, such as chronic illnesses, allergies, and current health conditions.

[0009] "Database" refers to a system that stores and manages a user's basic information, medical information, and related data.

[0010] "Profile" refers to individual health management information generated based on a user's basic information and medical information.

[0011] "Menu" refers to a list of appropriate medical foods generated by AI based on the user's profile.

[0012] "Feedback" refers to information entered by the user regarding changes in physical condition and impressions after consuming a medical diet.

[0013] "Analysis" refers to the process of analyzing collected feedback and other data to assess the user's health and the effectiveness of their diet.

[0014] "Notification" refers to the means by which the system communicates information to users, such as confirmation of implementation status or new menu suggestions. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

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

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

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

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0030] 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.

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

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] MODE FOR CARRYING OUT THE INVENTION

[0037] This invention is a system that aims to enable elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home and maintain or improve their health. The system creates a user profile based on the user's basic information and medical information, and proposes medical food menus generated by AI. It also collects the user's progress and feedback, and proposes further customized menus based on the analysis results.

[0038] Program processing

[0039] Initial Setup

[0040] Server: Loads the necessary libraries and datasets when the app starts, including the AI ​​engine, database connection module, notification service, etc.

[0041] On the device: After the user installs the app, the app displays a screen for entering basic and medical information when the user launches it for the first time. This provides an interface that makes it easy for users to enter their information.

[0042] User: When launching the app for the first time, users enter basic information such as their name, age, and gender, and then enter medical information such as chronic illnesses and allergies.

[0043] Creating a User Profile

[0044] Server: Receives the basic and medical information entered and stores it in a database. It generates an individual user profile based on the information entered. This profile also takes into account the user's dietary preferences and lifestyle.

[0045] On the device: It displays customized questions based on the user's profile information and provides an interface to gather further information.

[0046] User: Answers customization questions and enters additional information, such as whether the user likes certain foods or whether there are foods they want to avoid.

[0047] Menu suggestions

[0048] Server: Based on the user profile, the AI ​​engine generates an appropriate medical meal menu, which is customized based on the user's health condition and dietary preferences.

[0049] Terminal: Provides an interface that displays the proposed menus on the user's screen and allows the user to select the desired menu.

[0050] User: Selects from the menu of options and confirms. This information is sent to the server and reflected in the user profile.

[0051] Recording implementation and feedback

[0052] Server: Periodically records the menu selections made by the user and their implementation status. Also, accumulates feedback and reflects it in the next menu proposal.

[0053] Terminal: Periodically notify the user and display a screen to check the status of the menu, helping the user remember to enter information.

[0054] User: Records the meals they have actually cooked and eaten, and inputs their impressions and changes in their physical condition. For example, they report changes in blood sugar levels after meals and whether their physical condition is good or bad.

[0055] Data storage and analysis

[0056] Server: Based on the accumulated data, the server analyzes the user's health trends and reflects them in future menu suggestions, enabling more effective medical diet suggestions.

[0057] Device: The analysis results are fed back to the user and displayed as reference information when suggesting menu items next time.

[0058] Users: Review the feedback and use it to make better menu choices next time, leading to healthier choices.

[0059] Specific examples

[0060] For example, consider the case where a 60-year-old person uses this system.

[0061] Initial Setup

[0062] When a user installs the app and launches it for the first time, they enter their basic and medical information. The server stores this information in a database and creates a user profile.

[0063] Creating a User Profile

[0064] The device displays customized questions and the user enters details, which the server uses to update the profile and suggest a personalized medical diet menu.

[0065] Menu suggestions

[0066] The server uses an AI engine to generate an appropriate menu based on the user profile and displays it on the device. The user then selects and confirms the desired menu.

[0067] Recording implementation and feedback

[0068] The server periodically records the user's menu selection and the progress of the meal, and collects feedback. The device periodically notifies the user, allowing them to input their impressions after the meal and any changes in their physical condition.

[0069] Data storage and analysis

[0070] The server analyzes the collected data and reflects it in the next menu suggestion, while the device notifies the user of the analysis results and helps them use them to make their next selection.

[0071] The system allows users to easily consume the right medical diet to maintain and improve their health at home.

[0072] The processing flow will be explained below.

[0073] Step 1:

[0074] When a device launches an app, it loads the necessary libraries and datasets, including the user interface, database connection modules, and AI engine.

[0075] Step 2:

[0076] The device displays the initial registration screen to the user, providing an interface for entering basic information such as name, age, and gender.

[0077] Step 3:

[0078] The user enters basic information such as name, age, and gender, which is later used to create a user profile.

[0079] Step 4:

[0080] The server receives the basic information entered and stores it in a database, which is managed in a secure environment.

[0081] Step 5:

[0082] The device then displays a medical information entry screen, which provides an interface for entering detailed medical information such as chronic illnesses, allergies, and current health conditions.

[0083] Step 6:

[0084] The user enters medical information such as chronic illnesses, allergies, and current health conditions.

[0085] Step 7:

[0086] The server receives the entered medical information and stores it in a database, which gathers the information needed to create a user profile.

[0087] Step 8:

[0088] The server uses basic and medical information to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[0089] Step 9:

[0090] The device presents the user with customized questions based on their user profile, including information about dietary preferences and specific foods.

[0091] Step 10:

[0092] Users answer customization questions and enter further details, such as whether they want to avoid certain foods or what foods they prefer.

[0093] Step 11:

[0094] The server receives the user's response and updates the user profile, which is always updated with the latest information.

[0095] Step 12:

[0096] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, which reflects the user's health condition and dietary preferences.

[0097] Step 13:

[0098] The terminal displays the generated menu on the user's screen, and the user can select the desired menu from multiple options.

[0099] Step 14:

[0100] The user selects and confirms the desired menu item, and this information is sent to the system.

[0101] Step 15:

[0102] The server receives the user's selection information and records it in a database, which is then used for feedback and analysis.

[0103] Step 16:

[0104] The server periodically checks and notifies the user about their progress, including reminders and progress checks.

[0105] Step 17:

[0106] The device periodically displays a status confirmation message to the user, allowing the user to enter information accordingly.

[0107] Step 18:

[0108] Users can input the status of the meal they have actually cooked and eaten, their impressions, and any changes in their physical condition. For example, they can report changes in blood sugar levels and their physical condition after eating.

[0109] Step 19:

[0110] The server receives user feedback and stores it in a database. The collected data is used to suggest new menu items for future visits.

[0111] Step 20:

[0112] The server analyzes the user's health trends based on the collected data, including the effects of foods consumed and changes in physical condition.

[0113] Step 21:

[0114] The device will notify the user of the analysis results and display them as reference information for the next meal plan, allowing the user to plan their next meal based on this information.

[0115] Step 22:

[0116] Users can check the analysis results and use them as a reference for their next menu selection, allowing them to make appropriate choices that lead to better health.

[0117] Example 1

[0118] 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."

[0119] It is important for elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home to maintain or improve their health. However, it is difficult to easily obtain medical foods tailored to individual health conditions and dietary preferences at home. Furthermore, there is a lack of systems for ensuring that meals are consumed at the appropriate time and for continuously monitoring their effects. As a result, many patients are unable to consume appropriate medical foods, which can lead to a deterioration in their health.

[0120] 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.

[0121] In this invention, the server includes means for inputting a user's basic information and medical information, means for receiving the input information and saving it in a database, means for generating a user profile based on the saved information, means for generating an appropriate medical diet menu based on the generated user profile, means for displaying the generated medical diet menu to the user and accepting selections, means for recording the user's selection information and reflecting it in the user profile, means for periodically checking and notifying the user's progress, means for collecting and saving user feedback, and means for analyzing the user's health condition based on the collected data and notifying the user of the results. This allows users to easily consume a medical diet appropriate for them at home and continuously monitor its effects.

[0122] "Basic user information" refers to information for identifying an individual, such as the user's name, age, and gender.

[0123] "Medical information" refers to information related to a user's health condition and treatment, such as chronic illnesses, allergies, and medications currently being taken.

[0124] A "database" is a system that centrally manages and stores information, allowing it to be quickly searched and retrieved as needed.

[0125] A "user profile" is a detailed data structure about an individual user that is generated based on the user's basic information and medical information.

[0126] A "medical diet menu" is a meal plan customized to the user's health condition and dietary preferences.

[0127] The "AI engine" is a software module that uses artificial intelligence technology to generate appropriate medical diet menus based on user profiles.

[0128] A "notification service" is a mechanism for notifying users of specific information or actions.

[0129] A "prompt sentence" is an input sentence that causes the AI ​​engine to perform tasks such as generating a menu.

[0130] "Feedback" refers to information provided by users after a meal, such as their impressions and changes in their physical condition, and is reflected in future menu suggestions.

[0131] "Analysis results" are the results of analysis performed by the AI ​​engine based on collected data, and are data that indicate the user's health condition and the effects of their diet.

[0132] "Health trends" are information about fluctuations and patterns in health status obtained through analysis of a user's ongoing health data.

[0133] "Customized questions" are questions that are used to obtain more detailed information about the lifestyle and dietary preferences of individual users in order to create a user profile.

[0134] "Periodic notification" is a notification that prompts the user to input information and check the meal status at regular intervals.

[0135] This invention is a system that aims to enable elderly people and patients who cannot be hospitalized to ingest appropriate medical foods at home and maintain or improve their health. Specific embodiments for carrying out this invention are described below.

[0136] Initial Setup

[0137] Server: When the app starts, it first imports the AI ​​engine (e.g., TensorFlow, PyTorch), database connection module (e.g., MySQL connection library), and notification service library to load the necessary libraries and datasets. This ensures that the necessary data and models are immediately available.

[0138] Device: After installing the app, the user will be prompted to enter basic and medical information when they first launch it. This screen provides a UI (user interface) for entering information such as name, age, gender, chronic illnesses, and allergies.

[0139] User: When launching the app for the first time, the user enters basic information such as name, age, and gender, followed by medical information such as chronic illnesses and allergies. This information is sent to the server.

[0140] Creating a User Profile

[0141] Server: Receives the basic and medical information entered and stores it in a database (e.g., MySQL, PostgreSQL). Based on the stored information, a user profile is generated for each individual user, including the user's dietary preferences and lifestyle.

[0142] On the device: Based on the user's profile information, the device will ask customized questions (e.g., whether they like certain foods or avoid certain foods) and provide an interface to gather more detailed information.

[0143] Users: Answer customization questions and enter additional information, such as details about specific food preferences or foods they avoid.

[0144] Menu suggestions

[0145] Server: Generates appropriate medical meal menus using a generative AI model (e.g., GPT-4) based on the user profile. The generated menus are customized based on the user's health condition and dietary preferences.

[0146] Terminal: Provides an interface that displays the proposed menus on the user's screen and allows the user to select the desired menu.

[0147] User: Selects desired option from the menu of suggestions and confirms. This information is sent to the server and reflected in the user profile.

[0148] Recording implementation and feedback

[0149] Server: Periodically records the menu selections and their implementation status, and collects feedback to be reflected in the next menu suggestions.

[0150] Terminal: Periodically notify the user and display a screen to check the status of the menu, helping the user remember to enter information.

[0151] User: Records the meals they have actually cooked and eaten, and inputs their impressions and changes in their physical condition. For example, they report changes in blood sugar levels after meals and whether their physical condition is good or bad.

[0152] Data storage and analysis

[0153] Server: Based on the accumulated data, the server analyzes the user's health trends and reflects them in future menu suggestions, enabling more effective medical diet suggestions.

[0154] Device: The analysis results are fed back to the user and displayed as reference information when suggesting menu items next time.

[0155] Users: Review the feedback and use it to make better menu choices next time, leading to healthier choices.

[0156] Specific examples

[0157] For example, consider the case where a 60-year-old person uses this system.

[0158] Initial Setup

[0159] When a user installs the app and launches it for the first time, they enter their basic and medical information. The server stores this information in a database and creates a user profile.

[0160] Creating a User Profile

[0161] The device displays customized questions and the user enters further details, which the server uses to update the profile and suggest a personalized medical diet menu.

[0162] Menu suggestions

[0163] The server uses a generative AI model based on the user profile to generate an appropriate menu and displays it on the device. The user then selects and confirms the desired menu.

[0164] Recording implementation and feedback

[0165] The server records the user's menu selection and the progress of the meal, and collects feedback. The device periodically sends notifications, allowing the user to input their impressions after the meal and any changes in their physical condition.

[0166] Data storage and analysis

[0167] The server analyzes the collected data and reflects it in the next menu suggestion, while the device notifies the user of the analysis results and helps them use them to make their next selection.

[0168] Example of input prompt for generative AI model

[0169] "Please suggest an appropriate medical diet menu for a 60-year-old male user with diabetes. His preference is fish dishes, and he wants to avoid fried foods."

[0170] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0171] Processing Steps

[0172] Step 1: Initial Setup

[0173] server

[0174] What it does: Loads required libraries and datasets when the app starts.

[0175] Input: N / A

[0176] Output: Loaded libraries and datasets

[0177] Specific operation:

[0178] 1. Import the AI ​​engine (e.g. TensorFlow or PyTorch) library.

[0179] 2. Import the database connection module (for example, the MySQL connection library).

[0180] 3. Load the initial dataset for menu generation (e.g., a CSV file of a medical food database) into memory.

[0181] Terminal

[0182] How it works: After the user installs the app, the first time they launch it, they are prompted to enter their basic and medical information.

[0183] Input: N / A

[0184] Output: User information input screen

[0185] Specific operation:

[0186] 1. Check the first boot flag.

[0187] 2. If this is your first time, you will be prompted to enter your name, age, gender, medical conditions, and allergies.

[0188] User

[0189] How it works: When you first launch the app, you enter basic information such as your name, age, and gender, and then enter medical information such as any chronic illnesses or allergies.

[0190] Input: Name, age, gender, chronic illness, allergy information

[0191] Output: User information entered

[0192] Specific operation:

[0193] 1. Enter the information in each input field.

[0194] 2. Press the send button.

[0195] Step 2: Create a user profile

[0196] server

[0197] How it works: Receives basic and medical information entered and stores it in a database. Creates a user profile based on the stored information.

[0198] Input: User's basic and medical information

[0199] Output: User profile data

[0200] Specific operation:

[0201] 1. Parse the user information received in the HTTP request.

[0202] 2. Execute an INSERT query to the database to save the user information.

[0203] 3. Run the profile generation logic based on the stored information.

[0204] Terminal

[0205] What it does: Shows users customized questions based on their profile information.

[0206] Input: User profile data

[0207] Output: Custom question input screen

[0208] Specific operation:

[0209] 1. Retrieve profile data from the server with a GET request.

[0210] 2. Generate customized questions based on your profile.

[0211] 3. The question input screen will be displayed.

[0212] User

[0213] What it does: Answer customization questions and enter additional information.

[0214] Input: Answer to customization question

[0215] Output: Added user information

[0216] Specific operation:

[0217] 1. Enter text and options for the question.

[0218] 2. Press the send button.

[0219] Step 3: Menu proposal

[0220] server

[0221] How it works: Generates appropriate medical meal menus using a generative AI model based on a user profile.

[0222] Input: User profile data

[0223] Output: Suggested menu list

[0224] Specific operation:

[0225] 1. Query the user profile from the database.

[0226] 2. Generate a prompt sentence and input it into the generative AI model.

[0227] 3. Convert the results received from the AI ​​engine into a menu list.

[0228] Terminal

[0229] Behavior: Displays the suggested menu on the user's screen.

[0230] Input: Suggestion menu list

[0231] Output: Suggestion menu screen

[0232] Specific operation:

[0233] 1. Get the suggested menu list from the server with a GET request.

[0234] 2. Render the menu UI and display the list.

[0235] User

[0236] Action: Select the desired option from the menu of suggestions and confirm.

[0237] Enter: Selected menu

[0238] Output: Confirmed menu information

[0239] Specific operation:

[0240] 1. Scroll through the menu list and select the desired menu.

[0241] 2. Press the Confirm button.

[0242] Step 4: Recording progress and feedback

[0243] server

[0244] Behavior: Periodically records the user's menu selections and their implementation status, and collects feedback to be reflected in the next menu suggestions.

[0245] Input: User selection data and feedback

[0246] Output: Recorded data and analysis results

[0247] Specific operation:

[0248] 1. Save the selection data received in the HTTP request to the database.

[0249] 2. Periodically send feedback data to the analysis logic and accumulate the results.

[0250] Terminal

[0251] Behavior: Sends periodic notifications and displays a screen to the user to check the status of the menu.

[0252] Input: Implementation status confirmation request

[0253] Output: Implementation status input screen

[0254] Specific operation:

[0255] 1. Set up local notifications and schedule them to run.

[0256] 2. A pop-up screen will appear asking you to confirm the implementation status.

[0257] User

[0258] Operation: Record the meals you have actually cooked and eaten, and enter your impressions and changes in your physical condition.

[0259] Input: Impressions and changes in physical condition

[0260] Output: Feedback data

[0261] Specific operation:

[0262] 1. Enter your thoughts in the text area and select the changes in your physical condition using the check boxes.

[0263] 2. Press the send button.

[0264] Step 5: Store and analyze data

[0265] server

[0266] How it works: Analyzes the user's health trends based on accumulated data.

[0267] Input: Collected feedback data

[0268] Output: Health status analysis results

[0269] Specific operation:

[0270] 1. Run data analysis algorithms to visualize health trends.

[0271] 2. The analysis results are saved in a database and used to generate the next menu.

[0272] Terminal

[0273] Behavior: The analysis results are fed back to the user and displayed as reference information for the next menu suggestion.

[0274] Input: Health status analysis results

[0275] Output: Analysis result screen

[0276] Specific operation:

[0277] 1. Retrieve the analysis results from the server with a GET request.

[0278] 2. Render the UI for displaying the analysis results and display it to the user.

[0279] User

[0280] What it does: Review the feedback and use it to influence your next menu choice.

[0281] Input: Analysis results

[0282] Output: Feedback that influences your next choice

[0283] Specific operation:

[0284] 1. Check the analysis results page and understand the contents.

[0285] (Application example 1)

[0286] 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."

[0287] Currently, elderly people and patients who cannot be hospitalized have difficulty consuming appropriate medical foods at home. There are also issues with the time and effort required to manually select and order medical food menus, and the cumbersome nature of managing feedback. Furthermore, medical food recommendations are not sufficiently personalized, meaning that appropriate menus are not provided that meet the specific needs of users.

[0288] 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.

[0289] In this invention, the server includes means for inputting a user's basic information and medical information, means for receiving the input information and saving it in a database, means for generating a user profile based on the saved information, means for generating an appropriate medical diet menu based on the user profile, means for displaying the generated menu to the user and accepting selections, means for ordering the selected menu from an external delivery service, means for recording the user's selection information, means for periodically checking and notifying the user of the user's progress, means for collecting and saving user feedback, and means for analyzing the collected data and notifying the user of the results. This makes it easy to consume an appropriate medical diet at home, and realizes highly accurate personalized menu suggestions based on feedback.

[0290] "Basic user information" refers to basic information specific to a user, such as name, age, and gender.

[0291] "Medical information" refers to information related to the user's health condition and medical care, such as chronic illnesses, allergies, and medications taken.

[0292] "Input means" refers to the interface and device through which the user inputs basic and medical information into the database.

[0293] "Means for receiving and storing in a database" refers to the system and software for receiving the input information and storing it in a database.

[0294] A "user profile" is data generated based on a user's basic information and medical information, reflecting the user's specific health conditions and dietary preferences.

[0295] "Means for generating" refers to the technical means for creating an appropriate medical diet menu using AI or algorithms based on a user profile.

[0296] The "means for displaying a menu to a user and accepting a selection" is an interface for presenting the generated medical diet menu to a user and allowing the user to select the desired menu from among the menus.

[0297] The "means for ordering the selected menu from an external delivery service" is a system for quickly ordering the medical food menu selected by the user from an external delivery service.

[0298] The "means for recording selection information" refers to a technical means for saving and managing data related to the menu selected by the user.

[0299] The "means for periodically checking and notifying the implementation status" is a system for checking whether the user is properly implementing the menu they selected and notifying them accordingly.

[0300] The "means for collecting and storing feedback" refers to the technical means for collecting data on users' impressions after meals and changes in their physical condition, and storing this data in a database.

[0301] The "means for analyzing collected data and notifying the user of the results" refers to a system and software for analyzing collected feedback data and notifying the user of the results.

[0302] To implement this invention, a system is required that inputs a user's basic information and medical information, generates a user profile based on that information, proposes and allows the user to select a medical diet menu, and manages implementation status and feedback. This system is composed of hardware and software, including a server, a user's terminal, and an external delivery service.

[0303] First, a user installs the smartphone app and enters their basic and medical information. This information is sent from the user's device to a server and stored in a database. The server then generates an individual user profile based on this information. The user profile also includes the user's dietary preferences and lifestyle.

[0304] Based on the generated user profile, an AI engine generates an appropriate medical diet menu. This AI engine uses a generative AI model. The AI ​​model proposes a menu customized according to the user's profile. This menu is displayed on the user's device.

[0305] The user selects the desired item from the proposed menu, and the selected menu item is automatically ordered from an external delivery service via the server. At this time, the order data is sent to an external API using an HTTP request. At the same time, the selection information is recorded in the database.

[0306] The server periodically sends notifications to the user's device regarding the menu implementation status and provides an interface for the user to record the menu items they have actually cooked and consumed. The user inputs feedback after eating and any changes in their physical condition. This information is also sent to the server and stored in a database.

[0307] The server analyzes the collected feedback data and notifies the user of the results. The analysis results are reflected in the next menu proposal, making it possible to provide a more personalized medical meal menu. For example, in the case of a 60-year-old elderly person with diabetes, the AI ​​would suggest a low-carb menu that takes blood sugar levels into consideration.

[0308] This system uses the open source Flask and FastAPI to create API endpoints, and the Python programming language for data processing. Advanced natural language processing models such as GPT-3 can be applied as generative AI models.

[0309] Here, an example of a prompt sentence when generating a medical diet menu based on a user profile is shown.

[0310] Example prompt sentence:

[0311] "Please suggest an appropriate medical diet menu based on the following user profile: Name: Yamada Taro, Age: 65, Gender: Male, Chronic illness: Diabetes, Allergies: Nuts, Favorite foods: Fish, Tofu, Foods to avoid: Sweets."

[0312] As described above, by using this system, elderly people and patients who cannot be hospitalized can easily consume appropriate medical foods at home, thereby maintaining or improving their health.

[0313] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0314] Step 1:

[0315] Users install the smartphone app and enter basic and medical information, including name, age, gender, chronic illnesses, allergies, etc. The device then sends this information to the server.

[0316] input:

[0317] Your basic and medical information

[0318] output:

[0319] User information data sent to the server

[0320] Specific behavior:

[0321] When a user enters information into the application's input form and presses the submit button, the device sends this information to the server via an HTTP POST request.

[0322] Step 2:

[0323] The server stores the received information in a database, which contains detailed profiles for each user.

[0324] input:

[0325] User information data sent from the device

[0326] output:

[0327] User profile information stored in a database

[0328] Specific behavior:

[0329] The server parses the received data and executes SQL queries to store it in a database.

[0330] Step 3:

[0331] The server generates a user profile based on the stored information, and the AI ​​engine uses this profile to create prompts for generating medical meal menus.

[0332] input:

[0333] User information stored in a database

[0334] output:

[0335] User profile used as prompt

[0336] Specific behavior:

[0337] The server reads the data in each field and creates a prompt in text format for the AI ​​engine.

[0338] Step 4:

[0339] The AI ​​engine generates medical meal menus based on user profiles, using generative AI models such as GPT-3.

[0340] input:

[0341] Prompt statement

[0342] output:

[0343] AI-generated customized medical meal menus

[0344] Specific behavior:

[0345] The prompt text is sent to the AI ​​engine as an API request and the generated menu is received.

[0346] Step 5:

[0347] The server displays the generated menu on the user's terminal, and the user selects what they want from the proposed menu.

[0348] input:

[0349] AI-generated medical food menu

[0350] output:

[0351] Menu list displayed on the user's device

[0352] Specific behavior:

[0353] The server sends the menu information to the user terminal, which displays it on the screen.

[0354] Step 6:

[0355] When the user selects the desired menu item, the terminal sends the information to the server, which records the selection information in a database and simultaneously sends the order to an external delivery service.

[0356] input:

[0357] The menu selected by the user

[0358] output:

[0359] Selection information recorded in a database and order information transmitted to delivery services

[0360] Specific behavior:

[0361] When the user presses the selection button, the terminal sends the selection information to the server, which stores it in a database and also sends an order to the delivery service via an HTTP request.

[0362] Step 7:

[0363] The server periodically checks the user's status and sends a notification to the user terminal, and the user records the status based on the notification.

[0364] input:

[0365] Server notifications

[0366] output:

[0367] User implementation records

[0368] Specific behavior:

[0369] The server triggers the notification at the scheduled time and sends the notification content to the user terminal. The user inputs the implementation status according to the notification, and the terminal sends it to the server.

[0370] Step 8:

[0371] After the user performs the task, he / she inputs feedback, and the terminal sends this feedback information to the server, which stores it in the database.

[0372] input:

[0373] User feedback information

[0374] output:

[0375] Feedback information stored in a database

[0376] Specific behavior:

[0377] When a user fills in the feedback form and presses the submit button, the terminal sends the information to the server, which stores it in a database.

[0378] Step 9:

[0379] The server analyzes the collected data and notifies the user of the results, using the user's health status and past feedback data.

[0380] input:

[0381] Various data collected

[0382] output:

[0383] Analysis results notified to the user

[0384] Specific behavior:

[0385] The server runs the data analysis algorithms and generates results, which are sent to the user as notifications and reflected in the next menu suggestion.

[0386] Through the above steps, the system of the present invention can realize a series of processes that allow elderly people and patients who cannot be hospitalized to easily ingest appropriate medical foods at home and maintain or improve their health.

[0387] 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.

[0388] MODE FOR CARRYING OUT THE INVENTION

[0389] This invention adds emotion recognition functionality to a system that helps elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home and maintain and improve their health. This emotion recognition functionality aims to provide personalized dietary advice based on the user's psychological state and improve the overall user experience.

[0390] Program processing

[0391] Initial Setup

[0392] Server: Loads the necessary libraries and datasets when the app starts, including the user interface, database connection module, AI engine, emotion recognition engine, etc.

[0393] Device: When a user installs the app, they are presented with an initial registration screen, which provides an interface for entering basic information such as name, age, and gender.

[0394] User: When launching the app for the first time, users enter basic information such as their name, age, and gender, and then enter medical information such as chronic illnesses and allergies.

[0395] Server: Receives the entered basic information and medical information and stores it in a database. Creates a user profile based on the stored information.

[0396] Creating a User Profile

[0397] Server: Based on the input information, a personalized user profile is generated, taking into account the user's dietary preferences and lifestyle.

[0398] Terminal: Provides an interface that displays customized questions based on the generated user profile, designed to gather information about dietary preferences and specific foods.

[0399] Users: Answer customized questions and enter more detailed information, which further refines their profile.

[0400] Menu suggestions

[0401] Server: Using an AI engine, it generates an appropriate medical meal menu based on the user profile. The generated menu is customized based on the user's health condition and dietary preferences.

[0402] Terminal: Provides an interface that displays the generated menu to the user and accepts selections.

[0403] User: Selects and confirms the desired menu. The selection information is sent to the server and recorded in the user profile.

[0404] emotion recognition

[0405] Device: Monitors the user's facial expressions, voice, etc., and uses an emotion recognition engine to analyze the user's current emotions.

[0406] Server: Receives the analysis results and stores the user's emotional data in a database, allowing the system to modify menu suggestions based on the user's psychological state.

[0407] Feedback and implementation record

[0408] Server: Periodically records the user's menu selection information and execution status, and accumulates feedback and emotion data.

[0409] Device: Provides regular notifications to users and prompts them to input their progress and emotional feedback.

[0410] User: Enters the situation, impressions, changes in physical condition, and emotions regarding the menu that was actually cooked or eaten. For example, reports on physical condition and psychological changes after eating.

[0411] Data storage and analysis

[0412] Server: Analyzes the user's health status trends based on accumulated performance data, feedback data, and emotional data. This can be reflected in future menu suggestions.

[0413] Terminal: The analysis results are notified to the user and displayed as reference information for the next menu suggestion.

[0414] Specific examples

[0415] For example, consider a 65-year-old senior citizen using this system. As an initial setup, the user installs the app and enters basic and medical information. This information is saved by the server and a user profile is generated. The user then answers customized questions to create a detailed profile.

[0416] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile and displays it on the device. The user selects and confirms the desired menu. At the same time, an emotion recognition engine analyzes the user's emotions and customizes the menu suggestions based on that data.

[0417] After eating, the user inputs their emotions and changes in physical condition, and the server analyzes and stores the data. The analysis results are reflected in the next menu suggestion and are notified to the user via their device.

[0418] This system allows users to receive personalized medical diets and feedback at home, enabling them to efficiently manage their health. It also utilizes emotional data to provide support appropriate to the user's psychological state.

[0419] The processing flow will be explained below.

[0420] Step 1:

[0421] When a device launches an app, it loads the necessary libraries and datasets, including the user interface, database connection modules, AI engine, emotion recognition engine, etc.

[0422] Step 2:

[0423] The device displays the initial registration screen to the user, providing an interface for entering basic information such as name, age, and gender.

[0424] Step 3:

[0425] The user enters basic information such as name, age, and gender, which is later used to create a user profile.

[0426] Step 4:

[0427] The server receives the basic information entered and stores it in a database, which is managed in a secure environment.

[0428] Step 5:

[0429] The device then displays a medical information entry screen, which provides an interface for entering detailed medical information such as chronic illnesses, allergies, and current health conditions.

[0430] Step 6:

[0431] The user enters medical information such as chronic illnesses, allergies, and current health conditions.

[0432] Step 7:

[0433] The server receives the entered medical information and stores it in a database, which gathers the information needed to create a user profile.

[0434] Step 8:

[0435] The server uses basic and medical information to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[0436] Step 9:

[0437] The device presents the user with customized questions based on their user profile, including information about dietary preferences and specific foods.

[0438] Step 10:

[0439] Users answer customization questions and enter further details, such as whether they want to avoid certain foods or what foods they prefer.

[0440] Step 11:

[0441] The server receives the user's response and updates the user profile, which is always updated with the latest information.

[0442] Step 12:

[0443] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, and the menu is customized based on the user's health condition and dietary preferences.

[0444] Step 13:

[0445] The terminal displays the generated menu on the user's screen, and the user can select the desired menu from multiple options.

[0446] Step 14:

[0447] The user selects and confirms the desired menu item, and this information is sent to the system.

[0448] Step 15:

[0449] The server receives the user's selection information and records it in a database, which is then used for feedback and analysis.

[0450] Step 16:

[0451] The device monitors the user's facial expressions and voice in real time and uses an emotion recognition engine to analyze their current emotions.

[0452] Step 17:

[0453] The server receives the analysis results from the emotion recognition engine and stores the user's emotion data in a database, which is used to improve menu suggestions.

[0454] Step 18:

[0455] The server periodically checks the user's progress and sends notifications, including reminders and progress checks.

[0456] Step 19:

[0457] The device periodically displays a status confirmation message to the user, allowing the user to enter information accordingly.

[0458] Step 20:

[0459] Users can input the status of the meal they have actually cooked and eaten, their impressions, changes in their physical condition, and their emotions. For example, they can report changes in blood sugar levels and psychological effects after eating.

[0460] Step 21:

[0461] The server receives user feedback and emotion data and stores it in a database. The collected data is reflected in future menu suggestions.

[0462] Step 22:

[0463] The server analyzes the user's health trends based on the collected data, including the effects of the foods consumed and their psychological impact.

[0464] Step 23:

[0465] The device will notify the user of the analysis results and display them as reference information for the next meal plan, allowing the user to plan their next meal based on this information.

[0466] Step 24:

[0467] Users can check the analysis results and use them to help them make better choices for their next meal, leading to better health.

[0468] Example 2

[0469] 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."

[0470] Conventional medical food delivery systems make it difficult for elderly people and patients who cannot be hospitalized to consume appropriate medical food at home and maintain and improve their health. Furthermore, they do not take into account the user's psychological state and do not provide individual dietary advice, which results in a poor overall user experience. Furthermore, they are unable to fully utilize user feedback and emotional data, which means they cannot be reflected in the next menu recommendation.

[0471] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0472] In this invention, the server includes a means for inputting a user's basic information and medical information, a means for receiving the input information and storing it in a database, a means for generating a user profile based on the stored information, a means for analyzing the user's emotions, a means for revising menu suggestions based on the analysis results, a means for periodically checking and notifying the user's progress, a means for collecting and storing user feedback, and a means for analyzing the collected data and notifying the user of the results. This enables personalized dietary advice to be provided based on the user's psychological state, improving the overall user experience. Furthermore, the feedback and emotional data can be reflected in the next menu suggestion, allowing medical diets to be suggested that are appropriate for the user's health and psychological state.

[0473] "Basic user information" refers to basic information such as name, age, and gender that is necessary to identify and individually respond to users.

[0474] "Medical information" refers to medical information necessary for health management and dietary suggestions, such as the user's chronic illnesses, allergies, and medical history.

[0475] "Database" refers to an information storage system for storing and managing a user's basic information, medical information, selection information, and feedback information.

[0476] A "user profile" is a data set generated based on a user's basic information and medical information, and is used to make individually appropriate menu suggestions.

[0477] A "medical meal menu" is a meal plan customized based on a user's health status and dietary preferences.

[0478] "Means for analyzing emotions" refers to technology that analyzes the user's facial expressions, voice, etc., to evaluate their current emotional state.

[0479] "Feedback" is information provided by the user regarding their impressions after eating and changes in their physical condition.

[0480] "Implementation status" is information about whether the user actually ate the suggested menu item.

[0481] The "analysis results" are information about the trends in the user's health and psychological state derived from the collected data.

[0482] This invention adds emotion recognition functionality to a system that helps elderly people and patients who cannot be hospitalized to consume appropriate medical diets at home and maintain and improve their health. The emotion recognition functionality aims to provide personalized dietary advice based on the user's psychological state and improve the overall user experience.

[0483] System configuration and operation

[0484] Initial Setup

[0485] The server loads the necessary libraries and datasets when the application starts, including the user interface, database connection module, AI engine, emotion recognition engine, etc. Specifically, it uses software libraries such as OpenFace, EmotionAPI, and TensorFlow.

[0486] The device displays an initial registration screen to the user who has installed the app. The initial registration screen provides an interface for the user to enter basic information such as name, age, and gender.

[0487] When users launch the app for the first time, they enter their basic information and medical information (such as chronic illnesses and allergies).

[0488] The server receives the basic and medical information entered by the user and stores it in a database, which automatically generates an individual user profile.

[0489] Creating a User Profile

[0490] The server uses the information entered to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[0491] Based on the generated user profile, the device provides an interface displaying customized questions, allowing for more detailed information to be gathered about the user's dietary preferences and specific foods.

[0492] Users answer customized questions and provide additional detailed information, which further refines the user profile.

[0493] Menu suggestions

[0494] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, which is customized according to the user's health condition and dietary preferences.

[0495] The terminal provides an interface for displaying the generated menu to the user and accepting selections.

[0496] The user selects and confirms the desired menu, and the selection is sent to the server and recorded in the user profile.

[0497] emotion recognition

[0498] The device is equipped with an emotion recognition engine that analyzes the user's facial expressions and voice, allowing it to assess the user's current emotional state in real time.

[0499] The server receives the analyzed emotion data and stores it in a database, which can then modify the next menu suggestion to better suit the user's psychological state.

[0500] Feedback and implementation record

[0501] The server periodically records the user's menu selection information and implementation status, accumulates feedback data and emotion data, and periodically notifies the user to prompt input of implementation status and emotion feedback.

[0502] Users input the status of the meal they actually cooked and ate, their impressions, changes in their physical condition, and their emotions. For example, they can provide feedback such as, "I feel better after eating today."

[0503] Data storage and analysis

[0504] The server analyzes the user's health status based on the accumulated data on the user's progress, feedback, and emotions, and can then reflect this in the next menu recommendation.

[0505] The terminal notifies the user of the analysis results and displays them as reference information for suggesting the next menu item.

[0506] Examples and prompts

[0507] For example, if a 65-year-old male uses this system, he or she will follow the steps below: First, he or she installs the app and enters information such as name, age, gender, and chronic illnesses (diabetes, allergies, etc.), which creates an individual user profile.

[0508] Next, a detailed profile is created by answering additional questions about the user's dietary preferences and specific foods. Based on this profile, the server uses an AI engine to generate an appropriate medical meal menu and displays it on the device. The user can then select what they want from the menu.

[0509] After eating, the emotion recognition engine analyzes the user's current emotional state, and the data is sent to the server. The user also enters their thoughts about the meal and any changes in their physical condition, and this data is stored for analysis.

[0510] The analysis results are reflected in the next menu suggestion and notified to the user, allowing for more personalized and healthy meal suggestions.

[0511] Example prompt for generative AI model:

[0512] "A 65-year-old man with chronic conditions of diabetes and high blood pressure. His favorite foods are chicken and broccoli. Please suggest a daily meal menu."

[0513] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0514] Step 1:

[0515] The server loads the necessary libraries and datasets when the application starts, including software libraries such as OpenFace, EmotionAPI, and TensorFlow. Loading these prepares the entire system for operation.

[0516] Input: Application launch event

[0517] Output: Library and dataset loading completion status

[0518] Step 2:

[0519] The device displays an initial registration screen to users who have installed the app. This screen provides an interface for entering basic information such as name, age, and gender. The user interface is created using HTML or React Native.

[0520] Input: User's first launch of the app

[0521] Output: Display of initial registration screen

[0522] Step 3:

[0523] On the initial registration screen, users enter basic information such as name, age, and gender, as well as medical information such as chronic illnesses and allergies.

[0524] Input: Initial registration screen (basic information and medical information)

[0525] Output: Basic and medical information entered

[0526] Step 4:

[0527] The server receives the basic and medical information entered by the user and stores it in a database, which creates an individual user profile. The database used for storage is SQLite.

[0528] Input: Basic and medical information entered by the user

[0529] Output: User information stored in the database and generated profile

[0530] Step 5:

[0531] The server uses the information entered to create a personalized user profile, which includes information about the user's medical conditions, allergies, and dietary preferences.

[0532] Input: Basic and medical information stored in the database

[0533] Output: Generated user profile

[0534] Step 6:

[0535] Based on the generated user profile, the device provides an interface that displays additional customized questions to gather information about the user's dietary preferences and specific foods.

[0536] Input: Generated user profile

[0537] Output: Display of customization questions

[0538] Step 7:

[0539] Users answer customized questions and enter detailed information, which refines their profile.

[0540] Input: Customization Question

[0541] Output: Detailed information of the answer

[0542] Step 8:

[0543] The server uses an AI engine based on the user profile to generate an appropriate medical meal menu. The menu is customized according to the user's health condition and dietary preferences. The AI ​​engine uses TensorFlow and other technologies.

[0544] Input: Detailed user profile

[0545] Output: Generated medical food menu

[0546] Step 9:

[0547] The terminal provides an interface for displaying the generated menu to the user and accepting selections.

[0548] Input: Generated medical food menu

[0549] Output: Show menu

[0550] Step 10:

[0551] The user selects and confirms the desired menu item, and the selection is sent to the server and recorded in the user profile.

[0552] Enter:

[0553] Output: Selected menu and confirmation information

[0554] Step 11:

[0555] The device uses an emotion recognition engine that analyzes the user's facial expressions and voice to determine their current emotional state in real time, using OpenFace and EmotionAPI.

[0556] Input: User's facial expressions and voice

[0557] Output: Parsed emotion data

[0558] Step 12:

[0559] The server receives the analyzed emotion data and stores it in a database, which allows it to tailor the next menu suggestion to suit the user's emotional state.

[0560] Input: Parsed emotion data

[0561] Output: Emotion data stored in a database

[0562] Step 13:

[0563] The server periodically records the user's menu selection information and execution status, accumulates feedback and emotion data, and sends notifications to prompt the user to input execution status and emotion feedback via the terminal.

[0564] Input: User performance and feedback

[0565] Output: Recorded performance and feedback data

[0566] Step 14:

[0567] Users input the status of the meal they actually cooked and ate, their impressions, changes in their physical condition, and their emotions. For example, they can provide feedback such as, "I feel better after eating today."

[0568] Input: Implementation status and impressions, changes in physical condition

[0569] Output: Providing feedback data

[0570] Step 15:

[0571] The server analyzes the user's health trends based on the accumulated data and reflects this in its next menu suggestions. It also notifies the user of the analysis results via their device, allowing for more personalized and healthy meal suggestions.

[0572] Input: Accumulated implementation status data, feedback data, emotion data

[0573] Output: Analysis results and next menu suggestions

[0574] (Application example 2)

[0575] 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."

[0576] Conventional systems are insufficient to support elderly people and patients with chronic illnesses in maintaining and improving their health by consuming appropriate medical foods at home. Furthermore, they do not provide personalized dietary advice that takes into account the user's emotional state, which hinders the overall user experience.

[0577] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0578] a means for inputting basic information and medical information of the user;

[0579] means for receiving the input information and storing it in a database;

[0580] means for generating a user profile based on the stored information;

[0581] A means for generating an appropriate medical diet menu based on a user profile;

[0582] means for displaying the generated menu to a user and accepting a selection;

[0583] means for recording user selection information;

[0584] A means for periodically checking and notifying the user of their implementation status;

[0585] a means for collecting and storing user feedback;

[0586] means for analyzing the collected data and notifying the user of the results;

[0587] A means for monitoring the user's facial expressions and voice and analyzing emotions;

[0588] A means for customizing medical food menus based on emotional data;

[0589] This makes it possible to propose individual medical diets that take into account the user's health and psychological state.

[0590] "Basic user information" refers to information for identifying an individual, such as name, age, sex, and address.

[0591] "Medical information" refers to information necessary for health management, such as the user's chronic illnesses, allergies, and medication usage.

[0592] A "user profile" is an individual data set that is constructed based on a user's basic information and medical information.

[0593] A "medical diet menu" is a meal suggestion created based on the user's health condition and dietary preferences.

[0594] "Emotion data" is information about the psychological state obtained by analyzing the user's facial expressions, voice, etc.

[0595] "Customization" means adjusting or modifying something to suit your individual needs and preferences.

[0596] "Feedback" refers to reactions such as opinions and impressions provided by users.

[0597] "Generation" means creating new data or suggestions based on algorithms and rules.

[0598] "Selection information" refers to the specific content selected by the user from the options provided.

[0599] The "implementation status" refers to the extent to which the user has implemented the suggested menu or instruction.

[0600] "Notification" is the act of the system providing information to the user.

[0601] MODE FOR CARRYING OUT THE INVENTION

[0602] The system for implementing this invention operates in cooperation with three parties: a server, a terminal, and a user. The following describes the processes of each party and the hardware and software used.

[0603] server

[0604] Initial Setup and Profile Creation

[0605] The server receives the user's basic information and medical information and stores it in a database. Basic information includes name, age, gender, etc., while medical information includes chronic illnesses, allergies, and medication usage. A user profile is generated based on this information. The server uses a database and an AI engine (e.g., TensorFlow or Django).

[0606] Menu suggestions and emotion recognition

[0607] The server generates an appropriate medical meal menu based on the generated user profile and emotional data. Emotional data is information about the user's psychological state obtained by analyzing the user's facial expressions and voice. The server analyzes the emotional data using an emotion recognition engine (e.g., OpenCV) and passes the results to an AI engine to generate a customized menu.

[0608] Feedback and Data Analysis

[0609] The system collects feedback provided by users and stores it in a database. Based on the collected data, the system evaluates the user's health status and reflects it in menu suggestions for future visits. The server analyzes the feedback data and notifies the user of the results.

[0610] Terminal

[0611] User Interface and Data Entry

[0612] The device (such as a smartphone or smart glasses) provides an interface for users to input basic and medical information, and displays and accepts answers to questions customized based on the user profile.

[0613] Collecting Emotional Data

[0614] The device uses a built-in camera and microphone to monitor the user's facial expressions and voice in real time, and sends the data to an emotion recognition engine. This data is then transferred to a server and used to make menu suggestions.

[0615] Menu Selection and Notifications

[0616] The terminal displays the generated menu to the user and provides an interface for menu selection. When the user selects the desired menu, the selection information is sent to the server and recorded in the user profile. In addition, the user's implementation status is periodically checked and notified.

[0617] User

[0618] Entering information and selecting menus

[0619] Users enter basic and medical information on first launch, then answer questions to create a detailed profile, choose from a menu of suggestions, and provide feedback to improve the overall accuracy and user experience of the system.

[0620] Feedback Input

[0621] Users enter their emotions and changes in physical condition after a meal into the app, and the server analyzes the data and reflects it in menu suggestions for the next meal.

[0622] Specific examples

[0623] For example, if a 65-year-old senior citizen needs a medical diet based on their physical condition and emotions, the user installs the app and enters their basic and medical information. The app uses the smartphone camera to recognize emotions and analyze the user's current emotional state (e.g., increased stress). Based on the analysis results, the AI ​​engine generates a stress relief menu appropriate for the user and displays it on the device.

[0624] Example prompts for generative AI models

[0625] Prompt: A 65-year-old male needs blood pressure management and is currently under a lot of stress. Please suggest a medical diet for this user that is appropriate for his health and emotional state.

[0626] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0627] Program processing flow

[0628] Step 1:

[0629] The user installs the app and registers for the first time. The information entered includes basic information such as name, age, gender, chronic illnesses, and allergies, as well as medical information. The device acquires this information and sends it to the server. The input for this step is the basic information and medical information provided by the user, and the output is that this information is sent to the server.

[0630] Step 2:

[0631] The server stores the received basic and medical information in a database. The server then generates a user profile based on that information, including the user's preferences and lifestyle habits. The input to this step is the user information sent from the device, and the output is the generated user profile.

[0632] Step 3:

[0633] The terminal displays customized questions based on the user profile. The user answers the questions and provides further detailed information. The terminal sends this information back to the server. The input to this step is the generated user profile and customized questions, and the output is detailed user information.

[0634] Step 4:

[0635] The server stores the received detailed information in a database and uses an AI engine to generate an appropriate medical diet menu. This generated menu is customized based on the user's health condition and emotions. The input of this step is detailed user information, and the output is the generated medical diet menu.

[0636] Step 5:

[0637] The terminal displays the generated menu to the user and accepts the menu selection. The user selects the desired menu and the selection information is sent to the server. The input of this step is the generated medical diet menu, and the output is the user's selection information.

[0638] Step 6:

[0639] The device monitors the user's facial expressions and voice and analyzes the emotional data using an emotion recognition engine. The emotional data is sent to the server and stored in the user profile. The input of this step is the user's facial expressions and voice, and the output is the analyzed emotional data.

[0640] Step 7:

[0641] The server receives the analyzed emotion data and modifies the menu suggestions based on it. For example, a menu using ingredients that relieve stress may be suggested to a user who is under stress. The input of this step is emotion data, and the output is a modified medical food menu.

[0642] Step 8:

[0643] The user provides feedback after eating. The device collects this feedback and sends it to the server. The server stores the feedback data and reflects it in the next menu suggestion. The input of this step is the user feedback, and the output is an updated database and an improved suggestion for the next time.

[0644] Step 9:

[0645] The server periodically checks the user's status and sends a notification to the terminal. The user inputs the status in response to the notification, and the data is sent to the server. The input of this step is the periodic confirmation notification, and the output is the user's status data.

[0646] Step 10:

[0647] The server analyzes the collected data and notifies the user of the results, making it easier for users to understand their own health status. The input to this step is the various collected data, and the output is a notification of the analysis results.

[0648] 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.

[0649] 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.

[0650] 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.

[0651] [Second embodiment]

[0652] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0653] 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.

[0654] 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).

[0655] 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.

[0656] 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.

[0657] 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).

[0658] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0659] 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.

[0660] 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.

[0661] 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.

[0662] 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.

[0663] 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."

[0664] MODE FOR CARRYING OUT THE INVENTION

[0665] This invention is a system that aims to enable elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home and maintain or improve their health. The system creates a user profile based on the user's basic information and medical information, and proposes medical food menus generated by AI. It also collects the user's progress and feedback, and proposes further customized menus based on the analysis results.

[0666] Program processing

[0667] Initial Setup

[0668] Server: Loads the necessary libraries and datasets when the app starts, including the AI ​​engine, database connection module, notification service, etc.

[0669] On the device: After the user installs the app, the app displays a screen for entering basic and medical information when the user launches it for the first time. This provides an interface that makes it easy for users to enter their information.

[0670] User: When launching the app for the first time, users enter basic information such as their name, age, and gender, and then enter medical information such as chronic illnesses and allergies.

[0671] Creating a User Profile

[0672] Server: Receives the basic and medical information entered and stores it in a database. It generates an individual user profile based on the information entered. This profile also takes into account the user's dietary preferences and lifestyle.

[0673] On the device: It displays customized questions based on the user's profile information and provides an interface to gather further information.

[0674] User: Answers customization questions and enters additional information, such as whether the user likes certain foods or whether there are foods they want to avoid.

[0675] Menu suggestions

[0676] Server: Based on the user profile, the AI ​​engine generates an appropriate medical meal menu, which is customized based on the user's health condition and dietary preferences.

[0677] Terminal: Provides an interface that displays the proposed menus on the user's screen and allows the user to select the desired menu.

[0678] User: Selects from the menu of options and confirms. This information is sent to the server and reflected in the user profile.

[0679] Recording implementation and feedback

[0680] Server: Periodically records the menu selections made by the user and their implementation status. Also, accumulates feedback and reflects it in the next menu proposal.

[0681] Terminal: Periodically notify the user and display a screen to check the status of the menu, helping the user remember to enter information.

[0682] User: Records the meals they have actually cooked and eaten, and inputs their impressions and changes in their physical condition. For example, they report changes in blood sugar levels after meals and whether their physical condition is good or bad.

[0683] Data storage and analysis

[0684] Server: Based on the accumulated data, the server analyzes the user's health trends and reflects them in future menu suggestions, enabling more effective medical diet suggestions.

[0685] Device: The analysis results are fed back to the user and displayed as reference information when suggesting menu items next time.

[0686] Users: Review the feedback and use it to make better menu choices next time, leading to healthier choices.

[0687] Specific examples

[0688] For example, consider the case where a 60-year-old person uses this system.

[0689] Initial Setup

[0690] When a user installs the app and launches it for the first time, they enter their basic and medical information. The server stores this information in a database and creates a user profile.

[0691] Creating a User Profile

[0692] The device displays customized questions and the user enters details, which the server uses to update the profile and suggest a personalized medical diet menu.

[0693] Menu suggestions

[0694] The server uses an AI engine to generate an appropriate menu based on the user profile and displays it on the device. The user then selects and confirms the desired menu.

[0695] Recording implementation and feedback

[0696] The server periodically records the user's menu selection and the progress of the meal, and collects feedback. The device periodically notifies the user, allowing them to input their impressions after the meal and any changes in their physical condition.

[0697] Data storage and analysis

[0698] The server analyzes the collected data and reflects it in the next menu suggestion, while the device notifies the user of the analysis results and helps them use them to make their next selection.

[0699] The system allows users to easily consume the right medical diet to maintain and improve their health at home.

[0700] The processing flow will be explained below.

[0701] Step 1:

[0702] When a device launches an app, it loads the necessary libraries and datasets, including the user interface, database connection modules, and AI engine.

[0703] Step 2:

[0704] The device displays the initial registration screen to the user, providing an interface for entering basic information such as name, age, and gender.

[0705] Step 3:

[0706] The user enters basic information such as name, age, and gender, which is later used to create a user profile.

[0707] Step 4:

[0708] The server receives the basic information entered and stores it in a database, which is managed in a secure environment.

[0709] Step 5:

[0710] The device then displays a medical information entry screen, which provides an interface for entering detailed medical information such as chronic illnesses, allergies, and current health conditions.

[0711] Step 6:

[0712] The user enters medical information such as chronic illnesses, allergies, and current health conditions.

[0713] Step 7:

[0714] The server receives the entered medical information and stores it in a database, which gathers the information needed to create a user profile.

[0715] Step 8:

[0716] The server uses basic and medical information to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[0717] Step 9:

[0718] The device presents the user with customized questions based on their user profile, including information about dietary preferences and specific foods.

[0719] Step 10:

[0720] Users answer customization questions and enter further details, such as whether they want to avoid certain foods or what foods they prefer.

[0721] Step 11:

[0722] The server receives the user's response and updates the user profile, which is always updated with the latest information.

[0723] Step 12:

[0724] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, which reflects the user's health condition and dietary preferences.

[0725] Step 13:

[0726] The terminal displays the generated menu on the user's screen, and the user can select the desired menu from multiple options.

[0727] Step 14:

[0728] The user selects and confirms the desired menu item, and this information is sent to the system.

[0729] Step 15:

[0730] The server receives the user's selection information and records it in a database, which is then used for feedback and analysis.

[0731] Step 16:

[0732] The server periodically checks and notifies the user about their progress, including reminders and progress checks.

[0733] Step 17:

[0734] The device periodically displays a status confirmation message to the user, allowing the user to enter information accordingly.

[0735] Step 18:

[0736] Users can input the status of the meal they have actually cooked and eaten, their impressions, and any changes in their physical condition. For example, they can report changes in blood sugar levels and their physical condition after eating.

[0737] Step 19:

[0738] The server receives user feedback and stores it in a database. The collected data is used to suggest new menu items for future visits.

[0739] Step 20:

[0740] The server analyzes the user's health trends based on the collected data, including the effects of foods consumed and changes in physical condition.

[0741] Step 21:

[0742] The device will notify the user of the analysis results and display them as reference information for the next meal plan, allowing the user to plan their next meal based on this information.

[0743] Step 22:

[0744] Users can check the analysis results and use them as a reference for their next menu selection, allowing them to make appropriate choices that lead to better health.

[0745] Example 1

[0746] 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."

[0747] It is important for elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home to maintain or improve their health. However, it is difficult to easily obtain medical foods tailored to individual health conditions and dietary preferences at home. Furthermore, there is a lack of systems for ensuring that meals are consumed at the appropriate time and for continuously monitoring their effects. As a result, many patients are unable to consume appropriate medical foods, which can lead to a deterioration in their health.

[0748] 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.

[0749] In this invention, the server includes means for inputting a user's basic information and medical information, means for receiving the input information and saving it in a database, means for generating a user profile based on the saved information, means for generating an appropriate medical diet menu based on the generated user profile, means for displaying the generated medical diet menu to the user and accepting selections, means for recording the user's selection information and reflecting it in the user profile, means for periodically checking and notifying the user's progress, means for collecting and saving user feedback, and means for analyzing the user's health condition based on the collected data and notifying the user of the results. This allows users to easily consume a medical diet appropriate for them at home and continuously monitor its effects.

[0750] "Basic user information" refers to information for identifying an individual, such as the user's name, age, and gender.

[0751] "Medical information" refers to information related to a user's health condition and treatment, such as chronic illnesses, allergies, and medications currently being taken.

[0752] A "database" is a system that centrally manages and stores information, allowing it to be quickly searched and retrieved as needed.

[0753] A "user profile" is a detailed data structure about an individual user that is generated based on the user's basic information and medical information.

[0754] A "medical diet menu" is a meal plan customized to the user's health condition and dietary preferences.

[0755] The "AI engine" is a software module that uses artificial intelligence technology to generate appropriate medical diet menus based on user profiles.

[0756] A "notification service" is a mechanism for notifying users of specific information or actions.

[0757] A "prompt sentence" is an input sentence that causes the AI ​​engine to perform tasks such as generating a menu.

[0758] "Feedback" refers to information provided by users after a meal, such as their impressions and changes in their physical condition, and is reflected in future menu suggestions.

[0759] "Analysis results" are the results of analysis performed by the AI ​​engine based on collected data, and are data that indicate the user's health condition and the effects of their diet.

[0760] "Health trends" are information about fluctuations and patterns in health status obtained through analysis of a user's ongoing health data.

[0761] "Customized questions" are questions that are used to obtain more detailed information about the lifestyle and dietary preferences of individual users in order to create a user profile.

[0762] "Periodic notification" is a notification that prompts the user to input information and check the meal status at regular intervals.

[0763] This invention is a system that aims to enable elderly people and patients who cannot be hospitalized to ingest appropriate medical foods at home and maintain or improve their health. Specific embodiments for carrying out this invention are described below.

[0764] Initial Setup

[0765] Server: When the app starts, it first imports the AI ​​engine (e.g., TensorFlow, PyTorch), database connection module (e.g., MySQL connection library), and notification service library to load the necessary libraries and datasets. This ensures that the necessary data and models are immediately available.

[0766] Device: After installing the app, the user will be prompted to enter basic and medical information when they first launch it. This screen provides a UI (user interface) for entering information such as name, age, gender, chronic illnesses, and allergies.

[0767] User: When launching the app for the first time, the user enters basic information such as name, age, and gender, followed by medical information such as chronic illnesses and allergies. This information is sent to the server.

[0768] Creating a User Profile

[0769] Server: Receives the basic and medical information entered and stores it in a database (e.g., MySQL, PostgreSQL). Based on the stored information, a user profile is generated for each individual user, including the user's dietary preferences and lifestyle.

[0770] On the device: Based on the user's profile information, the device will ask customized questions (e.g., whether they like certain foods or avoid certain foods) and provide an interface to gather more detailed information.

[0771] Users: Answer customization questions and enter additional information, such as details about specific food preferences or foods they avoid.

[0772] Menu suggestions

[0773] Server: Generates appropriate medical meal menus using a generative AI model (e.g., GPT-4) based on the user profile. The generated menus are customized based on the user's health condition and dietary preferences.

[0774] Terminal: Provides an interface that displays the proposed menus on the user's screen and allows the user to select the desired menu.

[0775] User: Selects desired option from the menu of suggestions and confirms. This information is sent to the server and reflected in the user profile.

[0776] Recording implementation and feedback

[0777] Server: Periodically records the menu selections and their implementation status, and collects feedback to be reflected in the next menu suggestions.

[0778] Terminal: Periodically notify the user and display a screen to check the status of the menu, helping the user remember to enter information.

[0779] User: Records the meals they have actually cooked and eaten, and inputs their impressions and changes in their physical condition. For example, they report changes in blood sugar levels after meals and whether their physical condition is good or bad.

[0780] Data storage and analysis

[0781] Server: Based on the accumulated data, the server analyzes the user's health trends and reflects them in future menu suggestions, enabling more effective medical diet suggestions.

[0782] Device: The analysis results are fed back to the user and displayed as reference information when suggesting menu items next time.

[0783] Users: Review the feedback and use it to make better menu choices next time, leading to healthier choices.

[0784] Specific examples

[0785] For example, consider the case where a 60-year-old person uses this system.

[0786] Initial Setup

[0787] When a user installs the app and launches it for the first time, they enter their basic and medical information. The server stores this information in a database and creates a user profile.

[0788] Creating a User Profile

[0789] The device displays customized questions and the user enters further details, which the server uses to update the profile and suggest a personalized medical diet menu.

[0790] Menu suggestions

[0791] The server uses a generative AI model based on the user profile to generate an appropriate menu and displays it on the device. The user then selects and confirms the desired menu.

[0792] Recording implementation and feedback

[0793] The server records the user's menu selection and the progress of the meal, and collects feedback. The device periodically sends notifications, allowing the user to input their impressions after the meal and any changes in their physical condition.

[0794] Data storage and analysis

[0795] The server analyzes the collected data and reflects it in the next menu suggestion, while the device notifies the user of the analysis results and helps them use them to make their next selection.

[0796] Example of input prompt for generative AI model

[0797] "Please suggest an appropriate medical diet menu for a 60-year-old male user with diabetes. His preference is fish dishes, and he wants to avoid fried foods."

[0798] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0799] Processing Steps

[0800] Step 1: Initial Setup

[0801] server

[0802] What it does: Loads required libraries and datasets when the app starts.

[0803] Input: N / A

[0804] Output: Loaded libraries and datasets

[0805] Specific operation:

[0806] 1. Import the AI ​​engine (e.g. TensorFlow or PyTorch) library.

[0807] 2. Import the database connection module (for example, the MySQL connection library).

[0808] 3. Load the initial dataset for menu generation (e.g., a CSV file of a medical food database) into memory.

[0809] Terminal

[0810] How it works: After the user installs the app, the first time they launch it, they are prompted to enter their basic and medical information.

[0811] Input: N / A

[0812] Output: User information input screen

[0813] Specific operation:

[0814] 1. Check the first boot flag.

[0815] 2. If this is your first time, you will be prompted to enter your name, age, gender, medical conditions, and allergies.

[0816] User

[0817] How it works: When you first launch the app, you enter basic information such as your name, age, and gender, and then enter medical information such as any chronic illnesses or allergies.

[0818] Input: Name, age, gender, chronic illness, allergy information

[0819] Output: User information entered

[0820] Specific operation:

[0821] 1. Enter the information in each input field.

[0822] 2. Press the send button.

[0823] Step 2: Create a user profile

[0824] server

[0825] How it works: Receives basic and medical information entered and stores it in a database. Creates a user profile based on the stored information.

[0826] Input: User's basic and medical information

[0827] Output: User profile data

[0828] Specific operation:

[0829] 1. Parse the user information received in the HTTP request.

[0830] 2. Execute an INSERT query to the database to save the user information.

[0831] 3. Run the profile generation logic based on the stored information.

[0832] Terminal

[0833] What it does: Shows users customized questions based on their profile information.

[0834] Input: User profile data

[0835] Output: Custom question input screen

[0836] Specific operation:

[0837] 1. Retrieve profile data from the server with a GET request.

[0838] 2. Generate customized questions based on your profile.

[0839] 3. The question input screen will be displayed.

[0840] User

[0841] What it does: Answer customization questions and enter additional information.

[0842] Input: Answer to customization question

[0843] Output: Added user information

[0844] Specific operation:

[0845] 1. Enter text and options for the question.

[0846] 2. Press the send button.

[0847] Step 3: Menu proposal

[0848] server

[0849] How it works: Generates appropriate medical meal menus using a generative AI model based on a user profile.

[0850] Input: User profile data

[0851] Output: Suggested menu list

[0852] Specific operation:

[0853] 1. Query the user profile from the database.

[0854] 2. Generate a prompt sentence and input it into the generative AI model.

[0855] 3. Convert the results received from the AI ​​engine into a menu list.

[0856] Terminal

[0857] Behavior: Displays the suggested menu on the user's screen.

[0858] Input: Suggestion menu list

[0859] Output: Suggestion menu screen

[0860] Specific operation:

[0861] 1. Get the suggested menu list from the server with a GET request.

[0862] 2. Render the menu UI and display the list.

[0863] User

[0864] Action: Select the desired option from the menu of suggestions and confirm.

[0865] Enter: Selected menu

[0866] Output: Confirmed menu information

[0867] Specific operation:

[0868] 1. Scroll through the menu list and select the desired menu.

[0869] 2. Press the Confirm button.

[0870] Step 4: Recording progress and feedback

[0871] server

[0872] Behavior: Periodically records the user's menu selections and their implementation status, and collects feedback to be reflected in the next menu suggestions.

[0873] Input: User selection data and feedback

[0874] Output: Recorded data and analysis results

[0875] Specific operation:

[0876] 1. Save the selection data received in the HTTP request to the database.

[0877] 2. Periodically send feedback data to the analysis logic and accumulate the results.

[0878] Terminal

[0879] Behavior: Sends periodic notifications and displays a screen to the user to check the status of the menu.

[0880] Input: Implementation status confirmation request

[0881] Output: Implementation status input screen

[0882] Specific operation:

[0883] 1. Set up local notifications and schedule them to run.

[0884] 2. A pop-up screen will appear asking you to confirm the implementation status.

[0885] User

[0886] Operation: Record the meals you have actually cooked and eaten, and enter your impressions and changes in your physical condition.

[0887] Input: Impressions and changes in physical condition

[0888] Output: Feedback data

[0889] Specific operation:

[0890] 1. Enter your thoughts in the text area and select the changes in your physical condition using the check boxes.

[0891] 2. Press the send button.

[0892] Step 5: Store and analyze data

[0893] server

[0894] How it works: Analyzes the user's health trends based on accumulated data.

[0895] Input: Collected feedback data

[0896] Output: Health status analysis results

[0897] Specific operation:

[0898] 1. Run data analysis algorithms to visualize health trends.

[0899] 2. The analysis results are saved in a database and used to generate the next menu.

[0900] Terminal

[0901] Behavior: The analysis results are fed back to the user and displayed as reference information for the next menu suggestion.

[0902] Input: Health status analysis results

[0903] Output: Analysis result screen

[0904] Specific operation:

[0905] 1. Retrieve the analysis results from the server with a GET request.

[0906] 2. Render the UI for displaying the analysis results and display it to the user.

[0907] User

[0908] What it does: Review the feedback and use it to influence your next menu choice.

[0909] Input: Analysis results

[0910] Output: Feedback that influences your next choice

[0911] Specific operation:

[0912] 1. Check the analysis results page and understand the contents.

[0913] (Application example 1)

[0914] 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."

[0915] Currently, elderly people and patients who cannot be hospitalized have difficulty consuming appropriate medical foods at home. There are also issues with the time and effort required to manually select and order medical food menus, and the cumbersome nature of managing feedback. Furthermore, medical food recommendations are not sufficiently personalized, meaning that appropriate menus are not provided that meet the specific needs of users.

[0916] 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.

[0917] In this invention, the server includes means for inputting a user's basic information and medical information, means for receiving the input information and saving it in a database, means for generating a user profile based on the saved information, means for generating an appropriate medical diet menu based on the user profile, means for displaying the generated menu to the user and accepting selections, means for ordering the selected menu from an external delivery service, means for recording the user's selection information, means for periodically checking and notifying the user of the user's progress, means for collecting and saving user feedback, and means for analyzing the collected data and notifying the user of the results. This makes it easy to consume an appropriate medical diet at home, and realizes highly accurate personalized menu suggestions based on feedback.

[0918] "Basic user information" refers to basic information specific to a user, such as name, age, and gender.

[0919] "Medical information" refers to information related to the user's health condition and medical care, such as chronic illnesses, allergies, and medications taken.

[0920] "Input means" refers to the interface and device through which the user inputs basic and medical information into the database.

[0921] "Means for receiving and storing in a database" refers to the system and software for receiving the input information and storing it in a database.

[0922] A "user profile" is data generated based on a user's basic information and medical information, reflecting the user's specific health conditions and dietary preferences.

[0923] "Means for generating" refers to the technical means for creating an appropriate medical diet menu using AI or algorithms based on a user profile.

[0924] The "means for displaying a menu to a user and accepting a selection" is an interface for presenting the generated medical diet menu to a user and allowing the user to select the desired menu from among the menus.

[0925] The "means for ordering the selected menu from an external delivery service" is a system for quickly ordering the medical food menu selected by the user from an external delivery service.

[0926] The "means for recording selection information" refers to a technical means for saving and managing data related to the menu selected by the user.

[0927] The "means for periodically checking and notifying the implementation status" is a system for checking whether the user is properly implementing the menu they selected and notifying them accordingly.

[0928] The "means for collecting and storing feedback" refers to the technical means for collecting data on users' impressions after meals and changes in their physical condition, and storing this data in a database.

[0929] The "means for analyzing collected data and notifying the user of the results" refers to a system and software for analyzing collected feedback data and notifying the user of the results.

[0930] To implement this invention, a system is required that inputs a user's basic information and medical information, generates a user profile based on that information, proposes and allows the user to select a medical diet menu, and manages implementation status and feedback. This system is composed of hardware and software, including a server, a user's terminal, and an external delivery service.

[0931] First, a user installs the smartphone app and enters their basic and medical information. This information is sent from the user's device to a server and stored in a database. The server then generates an individual user profile based on this information. The user profile also includes the user's dietary preferences and lifestyle.

[0932] Based on the generated user profile, an AI engine generates an appropriate medical diet menu. This AI engine uses a generative AI model. The AI ​​model proposes a menu customized according to the user's profile. This menu is displayed on the user's device.

[0933] The user selects the desired item from the proposed menu, and the selected menu item is automatically ordered from an external delivery service via the server. At this time, the order data is sent to an external API using an HTTP request. At the same time, the selection information is recorded in the database.

[0934] The server periodically sends notifications to the user's device regarding the menu implementation status and provides an interface for the user to record the menu items they have actually cooked and consumed. The user inputs feedback after eating and any changes in their physical condition. This information is also sent to the server and stored in a database.

[0935] The server analyzes the collected feedback data and notifies the user of the results. The analysis results are reflected in the next menu proposal, making it possible to provide a more personalized medical meal menu. For example, in the case of a 60-year-old elderly person with diabetes, the AI ​​would suggest a low-carb menu that takes blood sugar levels into consideration.

[0936] This system uses the open source Flask and FastAPI to create API endpoints, and the Python programming language for data processing. Advanced natural language processing models such as GPT-3 can be applied as generative AI models.

[0937] Here, an example of a prompt sentence when generating a medical diet menu based on a user profile is shown.

[0938] Example prompt sentence:

[0939] "Please suggest an appropriate medical diet menu based on the following user profile: Name: Yamada Taro, Age: 65, Gender: Male, Chronic illness: Diabetes, Allergies: Nuts, Favorite foods: Fish, Tofu, Foods to avoid: Sweets."

[0940] As described above, by using this system, elderly people and patients who cannot be hospitalized can easily consume appropriate medical foods at home, thereby maintaining or improving their health.

[0941] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0942] Step 1:

[0943] Users install the smartphone app and enter basic and medical information, including name, age, gender, chronic illnesses, allergies, etc. The device then sends this information to the server.

[0944] input:

[0945] Your basic and medical information

[0946] output:

[0947] User information data sent to the server

[0948] Specific behavior:

[0949] When a user enters information into the application's input form and presses the submit button, the device sends this information to the server via an HTTP POST request.

[0950] Step 2:

[0951] The server stores the received information in a database, which contains detailed profiles for each user.

[0952] input:

[0953] User information data sent from the device

[0954] output:

[0955] User profile information stored in a database

[0956] Specific behavior:

[0957] The server parses the received data and executes SQL queries to store it in a database.

[0958] Step 3:

[0959] The server generates a user profile based on the stored information, and the AI ​​engine uses this profile to create prompts for generating medical meal menus.

[0960] input:

[0961] User information stored in a database

[0962] output:

[0963] User profile used as prompt

[0964] Specific behavior:

[0965] The server reads the data in each field and creates a prompt in text format for the AI ​​engine.

[0966] Step 4:

[0967] The AI ​​engine generates medical meal menus based on user profiles, using generative AI models such as GPT-3.

[0968] input:

[0969] Prompt statement

[0970] output:

[0971] AI-generated customized medical meal menus

[0972] Specific behavior:

[0973] The prompt text is sent to the AI ​​engine as an API request and the generated menu is received.

[0974] Step 5:

[0975] The server displays the generated menu on the user's terminal, and the user selects what they want from the proposed menu.

[0976] input:

[0977] AI-generated medical food menu

[0978] output:

[0979] Menu list displayed on the user's device

[0980] Specific behavior:

[0981] The server sends the menu information to the user terminal, which displays it on the screen.

[0982] Step 6:

[0983] When the user selects the desired menu item, the terminal sends the information to the server, which records the selection information in a database and simultaneously sends the order to an external delivery service.

[0984] input:

[0985] The menu selected by the user

[0986] output:

[0987] Selection information recorded in a database and order information transmitted to delivery services

[0988] Specific behavior:

[0989] When the user presses the selection button, the terminal sends the selection information to the server, which stores it in a database and also sends an order to the delivery service via an HTTP request.

[0990] Step 7:

[0991] The server periodically checks the user's status and sends a notification to the user terminal, and the user records the status based on the notification.

[0992] input:

[0993] Server notifications

[0994] output:

[0995] User implementation records

[0996] Specific behavior:

[0997] The server triggers the notification at the scheduled time and sends the notification content to the user terminal. The user inputs the implementation status according to the notification, and the terminal sends it to the server.

[0998] Step 8:

[0999] After the user performs the task, he / she inputs feedback, and the terminal sends this feedback information to the server, which stores it in the database.

[1000] input:

[1001] User feedback information

[1002] output:

[1003] Feedback information stored in a database

[1004] Specific behavior:

[1005] When a user fills in the feedback form and presses the submit button, the terminal sends the information to the server, which stores it in a database.

[1006] Step 9:

[1007] The server analyzes the collected data and notifies the user of the results, using the user's health status and past feedback data.

[1008] input:

[1009] Various data collected

[1010] output:

[1011] Analysis results notified to the user

[1012] Specific behavior:

[1013] The server runs the data analysis algorithms and generates results, which are sent to the user as notifications and reflected in the next menu suggestion.

[1014] Through the above steps, the system of the present invention can realize a series of processes that allow elderly people and patients who cannot be hospitalized to easily ingest appropriate medical foods at home and maintain or improve their health.

[1015] 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.

[1016] MODE FOR CARRYING OUT THE INVENTION

[1017] This invention adds emotion recognition functionality to a system that helps elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home and maintain and improve their health. This emotion recognition functionality aims to provide personalized dietary advice based on the user's psychological state and improve the overall user experience.

[1018] Program processing

[1019] Initial Setup

[1020] Server: Loads the necessary libraries and datasets when the app starts, including the user interface, database connection module, AI engine, emotion recognition engine, etc.

[1021] Device: When a user installs the app, they are presented with an initial registration screen, which provides an interface for entering basic information such as name, age, and gender.

[1022] User: When launching the app for the first time, users enter basic information such as their name, age, and gender, and then enter medical information such as chronic illnesses and allergies.

[1023] Server: Receives the entered basic information and medical information and stores it in a database. Creates a user profile based on the stored information.

[1024] Creating a User Profile

[1025] Server: Based on the input information, a personalized user profile is generated, taking into account the user's dietary preferences and lifestyle.

[1026] Terminal: Provides an interface that displays customized questions based on the generated user profile, designed to gather information about dietary preferences and specific foods.

[1027] Users: Answer customized questions and enter more detailed information, which further refines their profile.

[1028] Menu suggestions

[1029] Server: Using an AI engine, it generates an appropriate medical meal menu based on the user profile. The generated menu is customized based on the user's health condition and dietary preferences.

[1030] Terminal: Provides an interface that displays the generated menu to the user and accepts selections.

[1031] User: Selects and confirms the desired menu. The selection information is sent to the server and recorded in the user profile.

[1032] emotion recognition

[1033] Device: Monitors the user's facial expressions, voice, etc., and uses an emotion recognition engine to analyze the user's current emotions.

[1034] Server: Receives the analysis results and stores the user's emotional data in a database, allowing the system to modify menu suggestions based on the user's psychological state.

[1035] Feedback and implementation record

[1036] Server: Periodically records the user's menu selection information and execution status, and accumulates feedback and emotion data.

[1037] Device: Provides regular notifications to users and prompts them to input their progress and emotional feedback.

[1038] User: Enters the situation, impressions, changes in physical condition, and emotions regarding the menu that was actually cooked or eaten. For example, reports on physical condition and psychological changes after eating.

[1039] Data storage and analysis

[1040] Server: Analyzes the user's health status trends based on accumulated performance data, feedback data, and emotional data. This can be reflected in future menu suggestions.

[1041] Terminal: The analysis results are notified to the user and displayed as reference information for the next menu suggestion.

[1042] Specific examples

[1043] For example, consider a 65-year-old senior citizen using this system. As an initial setup, the user installs the app and enters basic and medical information. This information is saved by the server and a user profile is generated. The user then answers customized questions to create a detailed profile.

[1044] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile and displays it on the device. The user selects and confirms the desired menu. At the same time, an emotion recognition engine analyzes the user's emotions and customizes the menu suggestions based on that data.

[1045] After eating, the user inputs their emotions and changes in physical condition, and the server analyzes and stores the data. The analysis results are reflected in the next menu suggestion and are notified to the user via their device.

[1046] This system allows users to receive personalized medical diets and feedback at home, enabling them to efficiently manage their health. It also utilizes emotional data to provide support appropriate to the user's psychological state.

[1047] The processing flow will be explained below.

[1048] Step 1:

[1049] When a device launches an app, it loads the necessary libraries and datasets, including the user interface, database connection modules, AI engine, emotion recognition engine, etc.

[1050] Step 2:

[1051] The device displays the initial registration screen to the user, providing an interface for entering basic information such as name, age, and gender.

[1052] Step 3:

[1053] The user enters basic information such as name, age, and gender, which is later used to create a user profile.

[1054] Step 4:

[1055] The server receives the basic information entered and stores it in a database, which is managed in a secure environment.

[1056] Step 5:

[1057] The device then displays a medical information entry screen, which provides an interface for entering detailed medical information such as chronic illnesses, allergies, and current health conditions.

[1058] Step 6:

[1059] The user enters medical information such as chronic illnesses, allergies, and current health conditions.

[1060] Step 7:

[1061] The server receives the entered medical information and stores it in a database, which gathers the information needed to create a user profile.

[1062] Step 8:

[1063] The server uses basic and medical information to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[1064] Step 9:

[1065] The device presents the user with customized questions based on their user profile, including information about dietary preferences and specific foods.

[1066] Step 10:

[1067] Users answer customization questions and enter further details, such as whether they want to avoid certain foods or what foods they prefer.

[1068] Step 11:

[1069] The server receives the user's response and updates the user profile, which is always updated with the latest information.

[1070] Step 12:

[1071] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, and the menu is customized based on the user's health condition and dietary preferences.

[1072] Step 13:

[1073] The terminal displays the generated menu on the user's screen, and the user can select the desired menu from multiple options.

[1074] Step 14:

[1075] The user selects and confirms the desired menu item, and this information is sent to the system.

[1076] Step 15:

[1077] The server receives the user's selection information and records it in a database, which is then used for feedback and analysis.

[1078] Step 16:

[1079] The device monitors the user's facial expressions and voice in real time and uses an emotion recognition engine to analyze their current emotions.

[1080] Step 17:

[1081] The server receives the analysis results from the emotion recognition engine and stores the user's emotion data in a database, which is used to improve menu suggestions.

[1082] Step 18:

[1083] The server periodically checks the user's progress and sends notifications, including reminders and progress checks.

[1084] Step 19:

[1085] The device periodically displays a status confirmation message to the user, allowing the user to enter information accordingly.

[1086] Step 20:

[1087] Users can input the status of the meal they have actually cooked and eaten, their impressions, changes in their physical condition, and their emotions. For example, they can report changes in blood sugar levels and psychological effects after eating.

[1088] Step 21:

[1089] The server receives user feedback and emotion data and stores it in a database. The collected data is reflected in future menu suggestions.

[1090] Step 22:

[1091] The server analyzes the user's health trends based on the collected data, including the effects of the foods consumed and their psychological impact.

[1092] Step 23:

[1093] The device will notify the user of the analysis results and display them as reference information for the next meal plan, allowing the user to plan their next meal based on this information.

[1094] Step 24:

[1095] Users can check the analysis results and use them to help them make better choices for their next meal, leading to better health.

[1096] Example 2

[1097] 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."

[1098] Conventional medical food delivery systems make it difficult for elderly people and patients who cannot be hospitalized to consume appropriate medical food at home and maintain and improve their health. Furthermore, they do not take into account the user's psychological state and do not provide individual dietary advice, which results in a poor overall user experience. Furthermore, they are unable to fully utilize user feedback and emotional data, which means they cannot be reflected in the next menu recommendation.

[1099] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1100] In this invention, the server includes a means for inputting a user's basic information and medical information, a means for receiving the input information and storing it in a database, a means for generating a user profile based on the stored information, a means for analyzing the user's emotions, a means for revising menu suggestions based on the analysis results, a means for periodically checking and notifying the user's progress, a means for collecting and storing user feedback, and a means for analyzing the collected data and notifying the user of the results. This enables personalized dietary advice to be provided based on the user's psychological state, improving the overall user experience. Furthermore, the feedback and emotional data can be reflected in the next menu suggestion, allowing medical diets to be suggested that are appropriate for the user's health and psychological state.

[1101] "Basic user information" refers to basic information such as name, age, and gender that is necessary to identify and individually respond to users.

[1102] "Medical information" refers to medical information necessary for health management and dietary suggestions, such as the user's chronic illnesses, allergies, and medical history.

[1103] "Database" refers to an information storage system for storing and managing a user's basic information, medical information, selection information, and feedback information.

[1104] A "user profile" is a data set generated based on a user's basic information and medical information, and is used to make individually appropriate menu suggestions.

[1105] A "medical meal menu" is a meal plan customized based on a user's health status and dietary preferences.

[1106] "Means for analyzing emotions" refers to technology that analyzes the user's facial expressions, voice, etc., to evaluate their current emotional state.

[1107] "Feedback" is information provided by the user regarding their impressions after eating and changes in their physical condition.

[1108] "Implementation status" is information about whether the user actually ate the suggested menu item.

[1109] The "analysis results" are information about the trends in the user's health and psychological state derived from the collected data.

[1110] This invention adds emotion recognition functionality to a system that helps elderly people and patients who cannot be hospitalized to consume appropriate medical diets at home and maintain and improve their health. The emotion recognition functionality aims to provide personalized dietary advice based on the user's psychological state and improve the overall user experience.

[1111] System configuration and operation

[1112] Initial Setup

[1113] The server loads the necessary libraries and datasets when the application starts, including the user interface, database connection module, AI engine, emotion recognition engine, etc. Specifically, it uses software libraries such as OpenFace, EmotionAPI, and TensorFlow.

[1114] The device displays an initial registration screen to the user who has installed the app. The initial registration screen provides an interface for the user to enter basic information such as name, age, and gender.

[1115] When users launch the app for the first time, they enter their basic information and medical information (such as chronic illnesses and allergies).

[1116] The server receives the basic and medical information entered by the user and stores it in a database, which automatically generates an individual user profile.

[1117] Creating a User Profile

[1118] The server uses the information entered to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[1119] Based on the generated user profile, the device provides an interface displaying customized questions, allowing for more detailed information to be gathered about the user's dietary preferences and specific foods.

[1120] Users answer customized questions and provide additional detailed information, which further refines the user profile.

[1121] Menu suggestions

[1122] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, which is customized according to the user's health condition and dietary preferences.

[1123] The terminal provides an interface for displaying the generated menu to the user and accepting selections.

[1124] The user selects and confirms the desired menu, and the selection is sent to the server and recorded in the user profile.

[1125] emotion recognition

[1126] The device is equipped with an emotion recognition engine that analyzes the user's facial expressions and voice, allowing it to assess the user's current emotional state in real time.

[1127] The server receives the analyzed emotion data and stores it in a database, which can then modify the next menu suggestion to better suit the user's psychological state.

[1128] Feedback and implementation record

[1129] The server periodically records the user's menu selection information and implementation status, accumulates feedback data and emotion data, and periodically notifies the user to prompt input of implementation status and emotion feedback.

[1130] Users input the status of the meal they actually cooked and ate, their impressions, changes in their physical condition, and their emotions. For example, they can provide feedback such as, "I feel better after eating today."

[1131] Data storage and analysis

[1132] The server analyzes the user's health status based on the accumulated data on the user's progress, feedback, and emotions, and can then reflect this in the next menu recommendation.

[1133] The terminal notifies the user of the analysis results and displays them as reference information for suggesting the next menu item.

[1134] Examples and prompts

[1135] For example, if a 65-year-old male uses this system, he or she will follow the steps below: First, he or she installs the app and enters information such as name, age, gender, and chronic illnesses (diabetes, allergies, etc.), which creates an individual user profile.

[1136] Next, a detailed profile is created by answering additional questions about the user's dietary preferences and specific foods. Based on this profile, the server uses an AI engine to generate an appropriate medical meal menu and displays it on the device. The user can then select what they want from the menu.

[1137] After eating, the emotion recognition engine analyzes the user's current emotional state, and the data is sent to the server. The user also enters their thoughts about the meal and any changes in their physical condition, and this data is stored for analysis.

[1138] The analysis results are reflected in the next menu suggestion and notified to the user, allowing for more personalized and healthy meal suggestions.

[1139] Example prompt for generative AI model:

[1140] "A 65-year-old man with chronic conditions of diabetes and high blood pressure. His favorite foods are chicken and broccoli. Please suggest a daily meal menu."

[1141] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1142] Step 1:

[1143] The server loads the necessary libraries and datasets when the application starts, including software libraries such as OpenFace, EmotionAPI, and TensorFlow. Loading these prepares the entire system for operation.

[1144] Input: Application launch event

[1145] Output: Library and dataset loading completion status

[1146] Step 2:

[1147] The device displays an initial registration screen to users who have installed the app. This screen provides an interface for entering basic information such as name, age, and gender. The user interface is created using HTML or React Native.

[1148] Input: User's first launch of the app

[1149] Output: Display of initial registration screen

[1150] Step 3:

[1151] On the initial registration screen, users enter basic information such as name, age, and gender, as well as medical information such as chronic illnesses and allergies.

[1152] Input: Initial registration screen (basic information and medical information)

[1153] Output: Basic and medical information entered

[1154] Step 4:

[1155] The server receives the basic and medical information entered by the user and stores it in a database, which creates an individual user profile. The database used for storage is SQLite.

[1156] Input: Basic and medical information entered by the user

[1157] Output: User information stored in the database and generated profile

[1158] Step 5:

[1159] The server uses the information entered to create a personalized user profile, which includes information about the user's medical conditions, allergies, and dietary preferences.

[1160] Input: Basic and medical information stored in the database

[1161] Output: Generated user profile

[1162] Step 6:

[1163] Based on the generated user profile, the device provides an interface that displays additional customized questions to gather information about the user's dietary preferences and specific foods.

[1164] Input: Generated user profile

[1165] Output: Display of customization questions

[1166] Step 7:

[1167] Users answer customized questions and enter detailed information, which refines their profile.

[1168] Input: Customization Question

[1169] Output: Detailed information of the answer

[1170] Step 8:

[1171] The server uses an AI engine based on the user profile to generate an appropriate medical meal menu. The menu is customized according to the user's health condition and dietary preferences. The AI ​​engine uses TensorFlow and other technologies.

[1172] Input: Detailed user profile

[1173] Output: Generated medical food menu

[1174] Step 9:

[1175] The terminal provides an interface for displaying the generated menu to the user and accepting selections.

[1176] Input: Generated medical food menu

[1177] Output: Show menu

[1178] Step 10:

[1179] The user selects and confirms the desired menu item, and the selection is sent to the server and recorded in the user profile.

[1180] Enter:

[1181] Output: Selected menu and confirmation information

[1182] Step 11:

[1183] The device uses an emotion recognition engine that analyzes the user's facial expressions and voice to determine their current emotional state in real time, using OpenFace and EmotionAPI.

[1184] Input: User's facial expressions and voice

[1185] Output: Parsed emotion data

[1186] Step 12:

[1187] The server receives the analyzed emotion data and stores it in a database, which allows it to tailor the next menu suggestion to suit the user's emotional state.

[1188] Input: Parsed emotion data

[1189] Output: Emotion data stored in a database

[1190] Step 13:

[1191] The server periodically records the user's menu selection information and execution status, accumulates feedback and emotion data, and sends notifications to prompt the user to input execution status and emotion feedback via the terminal.

[1192] Input: User performance and feedback

[1193] Output: Recorded performance and feedback data

[1194] Step 14:

[1195] Users input the status of the meal they actually cooked and ate, their impressions, changes in their physical condition, and their emotions. For example, they can provide feedback such as, "I feel better after eating today."

[1196] Input: Implementation status and impressions, changes in physical condition

[1197] Output: Providing feedback data

[1198] Step 15:

[1199] The server analyzes the user's health trends based on the accumulated data and reflects this in its next menu suggestions. It also notifies the user of the analysis results via their device, allowing for more personalized and healthy meal suggestions.

[1200] Input: Accumulated implementation status data, feedback data, emotion data

[1201] Output: Analysis results and next menu suggestions

[1202] (Application example 2)

[1203] 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."

[1204] Conventional systems are insufficient to support elderly people and patients with chronic illnesses in maintaining and improving their health by consuming appropriate medical foods at home. Furthermore, they do not provide personalized dietary advice that takes into account the user's emotional state, which hinders the overall user experience.

[1205] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1206] a means for inputting basic information and medical information of the user;

[1207] means for receiving the input information and storing it in a database;

[1208] means for generating a user profile based on the stored information;

[1209] A means for generating an appropriate medical diet menu based on a user profile;

[1210] means for displaying the generated menu to a user and accepting a selection;

[1211] means for recording user selection information;

[1212] A means for periodically checking and notifying the user of their implementation status;

[1213] a means for collecting and storing user feedback;

[1214] means for analyzing the collected data and notifying the user of the results;

[1215] A means for monitoring the user's facial expressions and voice and analyzing emotions;

[1216] A means for customizing medical food menus based on emotional data;

[1217] This makes it possible to propose individual medical diets that take into account the user's health and psychological state.

[1218] "Basic user information" refers to information for identifying an individual, such as name, age, sex, and address.

[1219] "Medical information" refers to information necessary for health management, such as the user's chronic illnesses, allergies, and medication usage.

[1220] A "user profile" is an individual data set that is constructed based on a user's basic information and medical information.

[1221] A "medical diet menu" is a meal suggestion created based on the user's health condition and dietary preferences.

[1222] "Emotion data" is information about the psychological state obtained by analyzing the user's facial expressions, voice, etc.

[1223] "Customization" means adjusting or modifying something to suit your individual needs and preferences.

[1224] "Feedback" refers to reactions such as opinions and impressions provided by users.

[1225] "Generation" means creating new data or suggestions based on algorithms and rules.

[1226] "Selection information" refers to the specific content selected by the user from the options provided.

[1227] The "implementation status" refers to the extent to which the user has implemented the suggested menu or instruction.

[1228] "Notification" is the act of the system providing information to the user.

[1229] MODE FOR CARRYING OUT THE INVENTION

[1230] The system for implementing this invention operates in cooperation with three parties: a server, a terminal, and a user. The following describes the processes of each party and the hardware and software used.

[1231] server

[1232] Initial Setup and Profile Creation

[1233] The server receives the user's basic information and medical information and stores it in a database. Basic information includes name, age, gender, etc., while medical information includes chronic illnesses, allergies, and medication usage. A user profile is generated based on this information. The server uses a database and an AI engine (e.g., TensorFlow or Django).

[1234] Menu suggestions and emotion recognition

[1235] The server generates an appropriate medical meal menu based on the generated user profile and emotional data. Emotional data is information about the user's psychological state obtained by analyzing the user's facial expressions and voice. The server analyzes the emotional data using an emotion recognition engine (e.g., OpenCV) and passes the results to an AI engine to generate a customized menu.

[1236] Feedback and Data Analysis

[1237] The system collects feedback provided by users and stores it in a database. Based on the collected data, the system evaluates the user's health status and reflects it in menu suggestions for future visits. The server analyzes the feedback data and notifies the user of the results.

[1238] Terminal

[1239] User Interface and Data Entry

[1240] The device (such as a smartphone or smart glasses) provides an interface for users to input basic and medical information, and displays and accepts answers to questions customized based on the user profile.

[1241] Collecting Emotional Data

[1242] The device uses a built-in camera and microphone to monitor the user's facial expressions and voice in real time, and sends the data to an emotion recognition engine. This data is then transferred to a server and used to make menu suggestions.

[1243] Menu Selection and Notifications

[1244] The terminal displays the generated menu to the user and provides an interface for menu selection. When the user selects the desired menu, the selection information is sent to the server and recorded in the user profile. In addition, the user's implementation status is periodically checked and notified.

[1245] User

[1246] Entering information and selecting menus

[1247] Users enter basic and medical information on first launch, then answer questions to create a detailed profile, choose from a menu of suggestions, and provide feedback to improve the overall accuracy and user experience of the system.

[1248] Feedback Input

[1249] Users enter their emotions and changes in physical condition after a meal into the app, and the server analyzes the data and reflects it in menu suggestions for the next meal.

[1250] Specific examples

[1251] For example, if a 65-year-old senior citizen needs a medical diet based on their physical condition and emotions, the user installs the app and enters their basic and medical information. The app uses the smartphone camera to recognize emotions and analyze the user's current emotional state (e.g., increased stress). Based on the analysis results, the AI ​​engine generates a stress relief menu appropriate for the user and displays it on the device.

[1252] Example prompts for generative AI models

[1253] Prompt: A 65-year-old male needs blood pressure management and is currently under a lot of stress. Please suggest a medical diet for this user that is appropriate for his health and emotional state.

[1254] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1255] Program processing flow

[1256] Step 1:

[1257] The user installs the app and registers for the first time. The information entered includes basic information such as name, age, gender, chronic illnesses, and allergies, as well as medical information. The device acquires this information and sends it to the server. The input for this step is the basic information and medical information provided by the user, and the output is that this information is sent to the server.

[1258] Step 2:

[1259] The server stores the received basic and medical information in a database. The server then generates a user profile based on that information, including the user's preferences and lifestyle habits. The input to this step is the user information sent from the device, and the output is the generated user profile.

[1260] Step 3:

[1261] The terminal displays customized questions based on the user profile. The user answers the questions and provides further detailed information. The terminal sends this information back to the server. The input to this step is the generated user profile and customized questions, and the output is detailed user information.

[1262] Step 4:

[1263] The server stores the received detailed information in a database and uses an AI engine to generate an appropriate medical diet menu. This generated menu is customized based on the user's health condition and emotions. The input of this step is detailed user information, and the output is the generated medical diet menu.

[1264] Step 5:

[1265] The terminal displays the generated menu to the user and accepts the menu selection. The user selects the desired menu and the selection information is sent to the server. The input of this step is the generated medical diet menu, and the output is the user's selection information.

[1266] Step 6:

[1267] The device monitors the user's facial expressions and voice and analyzes the emotional data using an emotion recognition engine. The emotional data is sent to the server and stored in the user profile. The input of this step is the user's facial expressions and voice, and the output is the analyzed emotional data.

[1268] Step 7:

[1269] The server receives the analyzed emotion data and modifies the menu suggestions based on it. For example, a menu using ingredients that relieve stress may be suggested to a user who is under stress. The input of this step is emotion data, and the output is a modified medical food menu.

[1270] Step 8:

[1271] The user provides feedback after eating. The device collects this feedback and sends it to the server. The server stores the feedback data and reflects it in the next menu suggestion. The input of this step is the user feedback, and the output is an updated database and an improved suggestion for the next time.

[1272] Step 9:

[1273] The server periodically checks the user's status and sends a notification to the terminal. The user inputs the status in response to the notification, and the data is sent to the server. The input of this step is the periodic confirmation notification, and the output is the user's status data.

[1274] Step 10:

[1275] The server analyzes the collected data and notifies the user of the results, making it easier for users to understand their own health status. The input to this step is the various collected data, and the output is a notification of the analysis results.

[1276] 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.

[1277] 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.

[1278] 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.

[1279] [Third embodiment]

[1280] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1281] 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.

[1282] 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).

[1283] 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.

[1284] 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.

[1285] 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).

[1286] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1287] 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.

[1288] 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.

[1289] 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.

[1290] 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.

[1291] 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."

[1292] MODE FOR CARRYING OUT THE INVENTION

[1293] This invention is a system that aims to enable elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home and maintain or improve their health. The system creates a user profile based on the user's basic information and medical information, and proposes medical food menus generated by AI. It also collects the user's progress and feedback, and proposes further customized menus based on the analysis results.

[1294] Program processing

[1295] Initial Setup

[1296] Server: Loads the necessary libraries and datasets when the app starts, including the AI ​​engine, database connection module, notification service, etc.

[1297] On the device: After the user installs the app, the app displays a screen for entering basic and medical information when the user launches it for the first time. This provides an interface that makes it easy for users to enter their information.

[1298] User: When launching the app for the first time, users enter basic information such as their name, age, and gender, and then enter medical information such as chronic illnesses and allergies.

[1299] Creating a User Profile

[1300] Server: Receives the basic and medical information entered and stores it in a database. It generates an individual user profile based on the information entered. This profile also takes into account the user's dietary preferences and lifestyle.

[1301] On the device: It displays customized questions based on the user's profile information and provides an interface to gather further information.

[1302] User: Answers customization questions and enters additional information, such as whether the user likes certain foods or whether there are foods they want to avoid.

[1303] Menu suggestions

[1304] Server: Based on the user profile, the AI ​​engine generates an appropriate medical meal menu, which is customized based on the user's health condition and dietary preferences.

[1305] Terminal: Provides an interface that displays the proposed menus on the user's screen and allows the user to select the desired menu.

[1306] User: Selects from the menu of options and confirms. This information is sent to the server and reflected in the user profile.

[1307] Recording implementation and feedback

[1308] Server: Periodically records the menu selections made by the user and their implementation status. Also, accumulates feedback and reflects it in the next menu proposal.

[1309] Terminal: Periodically notify the user and display a screen to check the status of the menu, helping the user remember to enter information.

[1310] User: Records the meals they have actually cooked and eaten, and inputs their impressions and changes in their physical condition. For example, they report changes in blood sugar levels after meals and whether their physical condition is good or bad.

[1311] Data storage and analysis

[1312] Server: Based on the accumulated data, the server analyzes the user's health trends and reflects them in future menu suggestions, enabling more effective medical diet suggestions.

[1313] Device: The analysis results are fed back to the user and displayed as reference information when suggesting menu items next time.

[1314] Users: Review the feedback and use it to make better menu choices next time, leading to healthier choices.

[1315] Specific examples

[1316] For example, consider the case where a 60-year-old person uses this system.

[1317] Initial Setup

[1318] When a user installs the app and launches it for the first time, they enter their basic and medical information. The server stores this information in a database and creates a user profile.

[1319] Creating a User Profile

[1320] The device displays customized questions and the user enters details, which the server uses to update the profile and suggest a personalized medical diet menu.

[1321] Menu suggestions

[1322] The server uses an AI engine to generate an appropriate menu based on the user profile and displays it on the device. The user then selects and confirms the desired menu.

[1323] Recording implementation and feedback

[1324] The server periodically records the user's menu selection and the progress of the meal, and collects feedback. The device periodically notifies the user, allowing them to input their impressions after the meal and any changes in their physical condition.

[1325] Data storage and analysis

[1326] The server analyzes the collected data and reflects it in the next menu suggestion, while the device notifies the user of the analysis results and helps them use them to make their next selection.

[1327] The system allows users to easily consume the right medical diet to maintain and improve their health at home.

[1328] The processing flow will be explained below.

[1329] Step 1:

[1330] When a device launches an app, it loads the necessary libraries and datasets, including the user interface, database connection modules, and AI engine.

[1331] Step 2:

[1332] The device displays the initial registration screen to the user, providing an interface for entering basic information such as name, age, and gender.

[1333] Step 3:

[1334] The user enters basic information such as name, age, and gender, which is later used to create a user profile.

[1335] Step 4:

[1336] The server receives the basic information entered and stores it in a database, which is managed in a secure environment.

[1337] Step 5:

[1338] The device then displays a medical information entry screen, which provides an interface for entering detailed medical information such as chronic illnesses, allergies, and current health conditions.

[1339] Step 6:

[1340] The user enters medical information such as chronic illnesses, allergies, and current health conditions.

[1341] Step 7:

[1342] The server receives the entered medical information and stores it in a database, which gathers the information needed to create a user profile.

[1343] Step 8:

[1344] The server uses basic and medical information to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[1345] Step 9:

[1346] The device presents the user with customized questions based on their user profile, including information about dietary preferences and specific foods.

[1347] Step 10:

[1348] Users answer customization questions and enter further details, such as whether they want to avoid certain foods or what foods they prefer.

[1349] Step 11:

[1350] The server receives the user's response and updates the user profile, which is always updated with the latest information.

[1351] Step 12:

[1352] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, which reflects the user's health condition and dietary preferences.

[1353] Step 13:

[1354] The terminal displays the generated menu on the user's screen, and the user can select the desired menu from multiple options.

[1355] Step 14:

[1356] The user selects and confirms the desired menu item, and this information is sent to the system.

[1357] Step 15:

[1358] The server receives the user's selection information and records it in a database, which is then used for feedback and analysis.

[1359] Step 16:

[1360] The server periodically checks and notifies the user about their progress, including reminders and progress checks.

[1361] Step 17:

[1362] The device periodically displays a status confirmation message to the user, allowing the user to enter information accordingly.

[1363] Step 18:

[1364] Users can input the status of the meal they have actually cooked and eaten, their impressions, and any changes in their physical condition. For example, they can report changes in blood sugar levels and their physical condition after eating.

[1365] Step 19:

[1366] The server receives user feedback and stores it in a database. The collected data is used to suggest new menu items for future visits.

[1367] Step 20:

[1368] The server analyzes the user's health trends based on the collected data, including the effects of foods consumed and changes in physical condition.

[1369] Step 21:

[1370] The device will notify the user of the analysis results and display them as reference information for the next meal plan, allowing the user to plan their next meal based on this information.

[1371] Step 22:

[1372] Users can check the analysis results and use them as a reference for their next menu selection, allowing them to make appropriate choices that lead to better health.

[1373] Example 1

[1374] 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."

[1375] It is important for elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home to maintain or improve their health. However, it is difficult to easily obtain medical foods tailored to individual health conditions and dietary preferences at home. Furthermore, there is a lack of systems for ensuring that meals are consumed at the appropriate time and for continuously monitoring their effects. As a result, many patients are unable to consume appropriate medical foods, which can lead to a deterioration in their health.

[1376] 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.

[1377] In this invention, the server includes means for inputting a user's basic information and medical information, means for receiving the input information and saving it in a database, means for generating a user profile based on the saved information, means for generating an appropriate medical diet menu based on the generated user profile, means for displaying the generated medical diet menu to the user and accepting selections, means for recording the user's selection information and reflecting it in the user profile, means for periodically checking and notifying the user's progress, means for collecting and saving user feedback, and means for analyzing the user's health condition based on the collected data and notifying the user of the results. This allows users to easily consume a medical diet appropriate for them at home and continuously monitor its effects.

[1378] "Basic user information" refers to information for identifying an individual, such as the user's name, age, and gender.

[1379] "Medical information" refers to information related to a user's health condition and treatment, such as chronic illnesses, allergies, and medications currently being taken.

[1380] A "database" is a system that centrally manages and stores information, allowing it to be quickly searched and retrieved as needed.

[1381] A "user profile" is a detailed data structure about an individual user that is generated based on the user's basic information and medical information.

[1382] A "medical diet menu" is a meal plan customized to the user's health condition and dietary preferences.

[1383] The "AI engine" is a software module that uses artificial intelligence technology to generate appropriate medical diet menus based on user profiles.

[1384] A "notification service" is a mechanism for notifying users of specific information or actions.

[1385] A "prompt sentence" is an input sentence that causes the AI ​​engine to perform tasks such as generating a menu.

[1386] "Feedback" refers to information provided by users after a meal, such as their impressions and changes in their physical condition, and is reflected in future menu suggestions.

[1387] "Analysis results" are the results of analysis performed by the AI ​​engine based on collected data, and are data that indicate the user's health condition and the effects of their diet.

[1388] "Health trends" are information about fluctuations and patterns in health status obtained through analysis of a user's ongoing health data.

[1389] "Customized questions" are questions that are used to obtain more detailed information about the lifestyle and dietary preferences of individual users in order to create a user profile.

[1390] "Periodic notification" is a notification that prompts the user to input information and check the meal status at regular intervals.

[1391] This invention is a system that aims to enable elderly people and patients who cannot be hospitalized to ingest appropriate medical foods at home and maintain or improve their health. Specific embodiments for carrying out this invention are described below.

[1392] Initial Setup

[1393] Server: When the app starts, it first imports the AI ​​engine (e.g., TensorFlow, PyTorch), database connection module (e.g., MySQL connection library), and notification service library to load the necessary libraries and datasets. This ensures that the necessary data and models are immediately available.

[1394] Device: After installing the app, the user will be prompted to enter basic and medical information when they first launch it. This screen provides a UI (user interface) for entering information such as name, age, gender, chronic illnesses, and allergies.

[1395] User: When launching the app for the first time, the user enters basic information such as name, age, and gender, followed by medical information such as chronic illnesses and allergies. This information is sent to the server.

[1396] Creating a User Profile

[1397] Server: Receives the basic and medical information entered and stores it in a database (e.g., MySQL, PostgreSQL). Based on the stored information, a user profile is generated for each individual user, including the user's dietary preferences and lifestyle.

[1398] On the device: Based on the user's profile information, the device will ask customized questions (e.g., whether they like certain foods or avoid certain foods) and provide an interface to gather more detailed information.

[1399] Users: Answer customization questions and enter additional information, such as details about specific food preferences or foods they avoid.

[1400] Menu suggestions

[1401] Server: Generates appropriate medical meal menus using a generative AI model (e.g., GPT-4) based on the user profile. The generated menus are customized based on the user's health condition and dietary preferences.

[1402] Terminal: Provides an interface that displays the proposed menus on the user's screen and allows the user to select the desired menu.

[1403] User: Selects desired option from the menu of suggestions and confirms. This information is sent to the server and reflected in the user profile.

[1404] Recording implementation and feedback

[1405] Server: Periodically records the menu selections and their implementation status, and collects feedback to be reflected in the next menu suggestions.

[1406] Terminal: Periodically notify the user and display a screen to check the status of the menu, helping the user remember to enter information.

[1407] User: Records the meals they have actually cooked and eaten, and inputs their impressions and changes in their physical condition. For example, they report changes in blood sugar levels after meals and whether their physical condition is good or bad.

[1408] Data storage and analysis

[1409] Server: Based on the accumulated data, the server analyzes the user's health trends and reflects them in future menu suggestions, enabling more effective medical diet suggestions.

[1410] Device: The analysis results are fed back to the user and displayed as reference information when suggesting menu items next time.

[1411] Users: Review the feedback and use it to make better menu choices next time, leading to healthier choices.

[1412] Specific examples

[1413] For example, consider the case where a 60-year-old person uses this system.

[1414] Initial Setup

[1415] When a user installs the app and launches it for the first time, they enter their basic and medical information. The server stores this information in a database and creates a user profile.

[1416] Creating a User Profile

[1417] The device displays customized questions and the user enters further details, which the server uses to update the profile and suggest a personalized medical diet menu.

[1418] Menu suggestions

[1419] The server uses a generative AI model based on the user profile to generate an appropriate menu and displays it on the device. The user then selects and confirms the desired menu.

[1420] Recording implementation and feedback

[1421] The server records the user's menu selection and the progress of the meal, and collects feedback. The device periodically sends notifications, allowing the user to input their impressions after the meal and any changes in their physical condition.

[1422] Data storage and analysis

[1423] The server analyzes the collected data and reflects it in the next menu suggestion, while the device notifies the user of the analysis results and helps them use them to make their next selection.

[1424] Example of input prompt for generative AI model

[1425] "Please suggest an appropriate medical diet menu for a 60-year-old male user with diabetes. His preference is fish dishes, and he wants to avoid fried foods."

[1426] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1427] Processing Steps

[1428] Step 1: Initial Setup

[1429] server

[1430] What it does: Loads required libraries and datasets when the app starts.

[1431] Input: N / A

[1432] Output: Loaded libraries and datasets

[1433] Specific operation:

[1434] 1. Import the AI ​​engine (e.g. TensorFlow or PyTorch) library.

[1435] 2. Import the database connection module (for example, the MySQL connection library).

[1436] 3. Load the initial dataset for menu generation (e.g., a CSV file of a medical food database) into memory.

[1437] Terminal

[1438] How it works: After the user installs the app, the first time they launch it, they are prompted to enter their basic and medical information.

[1439] Input: N / A

[1440] Output: User information input screen

[1441] Specific operation:

[1442] 1. Check the first boot flag.

[1443] 2. If this is your first time, you will be prompted to enter your name, age, gender, medical conditions, and allergies.

[1444] User

[1445] How it works: When you first launch the app, you enter basic information such as your name, age, and gender, and then enter medical information such as any chronic illnesses or allergies.

[1446] Input: Name, age, gender, chronic illness, allergy information

[1447] Output: User information entered

[1448] Specific operation:

[1449] 1. Enter the information in each input field.

[1450] 2. Press the send button.

[1451] Step 2: Create a user profile

[1452] server

[1453] How it works: Receives basic and medical information entered and stores it in a database. Creates a user profile based on the stored information.

[1454] Input: User's basic and medical information

[1455] Output: User profile data

[1456] Specific operation:

[1457] 1. Parse the user information received in the HTTP request.

[1458] 2. Execute an INSERT query to the database to save the user information.

[1459] 3. Run the profile generation logic based on the stored information.

[1460] Terminal

[1461] What it does: Shows users customized questions based on their profile information.

[1462] Input: User profile data

[1463] Output: Custom question input screen

[1464] Specific operation:

[1465] 1. Retrieve profile data from the server with a GET request.

[1466] 2. Generate customized questions based on your profile.

[1467] 3. The question input screen will be displayed.

[1468] User

[1469] What it does: Answer customization questions and enter additional information.

[1470] Input: Answer to customization question

[1471] Output: Added user information

[1472] Specific operation:

[1473] 1. Enter text and options for the question.

[1474] 2. Press the send button.

[1475] Step 3: Menu proposal

[1476] server

[1477] How it works: Generates appropriate medical meal menus using a generative AI model based on a user profile.

[1478] Input: User profile data

[1479] Output: Suggested menu list

[1480] Specific operation:

[1481] 1. Query the user profile from the database.

[1482] 2. Generate a prompt sentence and input it into the generative AI model.

[1483] 3. Convert the results received from the AI ​​engine into a menu list.

[1484] Terminal

[1485] Behavior: Displays the suggested menu on the user's screen.

[1486] Input: Suggestion menu list

[1487] Output: Suggestion menu screen

[1488] Specific operation:

[1489] 1. Get the suggested menu list from the server with a GET request.

[1490] 2. Render the menu UI and display the list.

[1491] User

[1492] Action: Select the desired option from the menu of suggestions and confirm.

[1493] Enter: Selected menu

[1494] Output: Confirmed menu information

[1495] Specific operation:

[1496] 1. Scroll through the menu list and select the desired menu.

[1497] 2. Press the Confirm button.

[1498] Step 4: Recording progress and feedback

[1499] server

[1500] Behavior: Periodically records the user's menu selections and their implementation status, and collects feedback to be reflected in the next menu suggestions.

[1501] Input: User selection data and feedback

[1502] Output: Recorded data and analysis results

[1503] Specific operation:

[1504] 1. Save the selection data received in the HTTP request to the database.

[1505] 2. Periodically send feedback data to the analysis logic and accumulate the results.

[1506] Terminal

[1507] Behavior: Sends periodic notifications and displays a screen to the user to check the status of the menu.

[1508] Input: Implementation status confirmation request

[1509] Output: Implementation status input screen

[1510] Specific operation:

[1511] 1. Set up local notifications and schedule them to run.

[1512] 2. A pop-up screen will appear asking you to confirm the implementation status.

[1513] User

[1514] Operation: Record the meals you have actually cooked and eaten, and enter your impressions and changes in your physical condition.

[1515] Input: Impressions and changes in physical condition

[1516] Output: Feedback data

[1517] Specific operation:

[1518] 1. Enter your thoughts in the text area and select the changes in your physical condition using the check boxes.

[1519] 2. Press the send button.

[1520] Step 5: Store and analyze data

[1521] server

[1522] How it works: Analyzes the user's health trends based on accumulated data.

[1523] Input: Collected feedback data

[1524] Output: Health status analysis results

[1525] Specific operation:

[1526] 1. Run data analysis algorithms to visualize health trends.

[1527] 2. The analysis results are saved in a database and used to generate the next menu.

[1528] Terminal

[1529] Behavior: The analysis results are fed back to the user and displayed as reference information for the next menu suggestion.

[1530] Input: Health status analysis results

[1531] Output: Analysis result screen

[1532] Specific operation:

[1533] 1. Retrieve the analysis results from the server with a GET request.

[1534] 2. Render the UI for displaying the analysis results and display it to the user.

[1535] User

[1536] What it does: Review the feedback and use it to influence your next menu choice.

[1537] Input: Analysis results

[1538] Output: Feedback that influences your next choice

[1539] Specific operation:

[1540] 1. Check the analysis results page and understand the contents.

[1541] (Application example 1)

[1542] 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."

[1543] Currently, elderly people and patients who cannot be hospitalized have difficulty consuming appropriate medical foods at home. There are also issues with the time and effort required to manually select and order medical food menus, and the cumbersome nature of managing feedback. Furthermore, medical food recommendations are not sufficiently personalized, meaning that appropriate menus are not provided that meet the specific needs of users.

[1544] 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.

[1545] In this invention, the server includes means for inputting a user's basic information and medical information, means for receiving the input information and saving it in a database, means for generating a user profile based on the saved information, means for generating an appropriate medical diet menu based on the user profile, means for displaying the generated menu to the user and accepting selections, means for ordering the selected menu from an external delivery service, means for recording the user's selection information, means for periodically checking and notifying the user of the user's progress, means for collecting and saving user feedback, and means for analyzing the collected data and notifying the user of the results. This makes it easy to consume an appropriate medical diet at home, and realizes highly accurate personalized menu suggestions based on feedback.

[1546] "Basic user information" refers to basic information specific to a user, such as name, age, and gender.

[1547] "Medical information" refers to information related to the user's health condition and medical care, such as chronic illnesses, allergies, and medications taken.

[1548] "Input means" refers to the interface and device through which the user inputs basic and medical information into the database.

[1549] "Means for receiving and storing in a database" refers to the system and software for receiving the input information and storing it in a database.

[1550] A "user profile" is data generated based on a user's basic information and medical information, reflecting the user's specific health conditions and dietary preferences.

[1551] "Means for generating" refers to the technical means for creating an appropriate medical diet menu using AI or algorithms based on a user profile.

[1552] The "means for displaying a menu to a user and accepting a selection" is an interface for presenting the generated medical diet menu to a user and allowing the user to select the desired menu from among the menus.

[1553] The "means for ordering the selected menu from an external delivery service" is a system for quickly ordering the medical food menu selected by the user from an external delivery service.

[1554] The "means for recording selection information" refers to a technical means for saving and managing data related to the menu selected by the user.

[1555] The "means for periodically checking and notifying the implementation status" is a system for checking whether the user is properly implementing the menu they selected and notifying them accordingly.

[1556] The "means for collecting and storing feedback" refers to the technical means for collecting data on users' impressions after meals and changes in their physical condition, and storing this data in a database.

[1557] The "means for analyzing collected data and notifying the user of the results" refers to a system and software for analyzing collected feedback data and notifying the user of the results.

[1558] To implement this invention, a system is required that inputs a user's basic information and medical information, generates a user profile based on that information, proposes and allows the user to select a medical diet menu, and manages implementation status and feedback. This system is composed of hardware and software, including a server, a user's terminal, and an external delivery service.

[1559] First, a user installs the smartphone app and enters their basic and medical information. This information is sent from the user's device to a server and stored in a database. The server then generates an individual user profile based on this information. The user profile also includes the user's dietary preferences and lifestyle.

[1560] Based on the generated user profile, an AI engine generates an appropriate medical diet menu. This AI engine uses a generative AI model. The AI ​​model proposes a menu customized according to the user's profile. This menu is displayed on the user's device.

[1561] The user selects the desired item from the proposed menu, and the selected menu item is automatically ordered from an external delivery service via the server. At this time, the order data is sent to an external API using an HTTP request. At the same time, the selection information is recorded in the database.

[1562] The server periodically sends notifications to the user's device regarding the menu implementation status and provides an interface for the user to record the menu items they have actually cooked and consumed. The user inputs feedback after eating and any changes in their physical condition. This information is also sent to the server and stored in a database.

[1563] The server analyzes the collected feedback data and notifies the user of the results. The analysis results are reflected in the next menu proposal, making it possible to provide a more personalized medical meal menu. For example, in the case of a 60-year-old elderly person with diabetes, the AI ​​would suggest a low-carb menu that takes blood sugar levels into consideration.

[1564] This system uses the open source Flask and FastAPI to create API endpoints, and the Python programming language for data processing. Advanced natural language processing models such as GPT-3 can be applied as generative AI models.

[1565] Here, an example of a prompt sentence when generating a medical diet menu based on a user profile is shown.

[1566] Example prompt sentence:

[1567] "Please suggest an appropriate medical diet menu based on the following user profile: Name: Yamada Taro, Age: 65, Gender: Male, Chronic illness: Diabetes, Allergies: Nuts, Favorite foods: Fish, Tofu, Foods to avoid: Sweets."

[1568] As described above, by using this system, elderly people and patients who cannot be hospitalized can easily consume appropriate medical foods at home, thereby maintaining or improving their health.

[1569] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1570] Step 1:

[1571] Users install the smartphone app and enter basic and medical information, including name, age, gender, chronic illnesses, allergies, etc. The device then sends this information to the server.

[1572] input:

[1573] Your basic and medical information

[1574] output:

[1575] User information data sent to the server

[1576] Specific behavior:

[1577] When a user enters information into the application's input form and presses the submit button, the device sends this information to the server via an HTTP POST request.

[1578] Step 2:

[1579] The server stores the received information in a database, which contains detailed profiles for each user.

[1580] input:

[1581] User information data sent from the device

[1582] output:

[1583] User profile information stored in a database

[1584] Specific behavior:

[1585] The server parses the received data and executes SQL queries to store it in a database.

[1586] Step 3:

[1587] The server generates a user profile based on the stored information, and the AI ​​engine uses this profile to create prompts for generating medical meal menus.

[1588] input:

[1589] User information stored in a database

[1590] output:

[1591] User profile used as prompt

[1592] Specific behavior:

[1593] The server reads the data in each field and creates a prompt in text format for the AI ​​engine.

[1594] Step 4:

[1595] The AI ​​engine generates medical meal menus based on user profiles, using generative AI models such as GPT-3.

[1596] input:

[1597] Prompt statement

[1598] output:

[1599] AI-generated customized medical meal menus

[1600] Specific behavior:

[1601] The prompt text is sent to the AI ​​engine as an API request and the generated menu is received.

[1602] Step 5:

[1603] The server displays the generated menu on the user's terminal, and the user selects what they want from the proposed menu.

[1604] input:

[1605] AI-generated medical food menu

[1606] output:

[1607] Menu list displayed on the user's device

[1608] Specific behavior:

[1609] The server sends the menu information to the user terminal, which displays it on the screen.

[1610] Step 6:

[1611] When the user selects the desired menu item, the terminal sends the information to the server, which records the selection information in a database and simultaneously sends the order to an external delivery service.

[1612] input:

[1613] The menu selected by the user

[1614] output:

[1615] Selection information recorded in a database and order information transmitted to delivery services

[1616] Specific behavior:

[1617] When the user presses the selection button, the terminal sends the selection information to the server, which stores it in a database and also sends an order to the delivery service via an HTTP request.

[1618] Step 7:

[1619] The server periodically checks the user's status and sends a notification to the user terminal, and the user records the status based on the notification.

[1620] input:

[1621] Server notifications

[1622] output:

[1623] User implementation records

[1624] Specific behavior:

[1625] The server triggers the notification at the scheduled time and sends the notification content to the user terminal. The user inputs the implementation status according to the notification, and the terminal sends it to the server.

[1626] Step 8:

[1627] After the user performs the task, he / she inputs feedback, and the terminal sends this feedback information to the server, which stores it in the database.

[1628] input:

[1629] User feedback information

[1630] output:

[1631] Feedback information stored in a database

[1632] Specific behavior:

[1633] When a user fills in the feedback form and presses the submit button, the terminal sends the information to the server, which stores it in a database.

[1634] Step 9:

[1635] The server analyzes the collected data and notifies the user of the results, using the user's health status and past feedback data.

[1636] input:

[1637] Various data collected

[1638] output:

[1639] Analysis results notified to the user

[1640] Specific behavior:

[1641] The server runs the data analysis algorithms and generates results, which are sent to the user as notifications and reflected in the next menu suggestion.

[1642] Through the above steps, the system of the present invention can realize a series of processes that allow elderly people and patients who cannot be hospitalized to easily ingest appropriate medical foods at home and maintain or improve their health.

[1643] 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.

[1644] MODE FOR CARRYING OUT THE INVENTION

[1645] This invention adds emotion recognition functionality to a system that helps elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home and maintain and improve their health. This emotion recognition functionality aims to provide personalized dietary advice based on the user's psychological state and improve the overall user experience.

[1646] Program processing

[1647] Initial Setup

[1648] Server: Loads the necessary libraries and datasets when the app starts, including the user interface, database connection module, AI engine, emotion recognition engine, etc.

[1649] Device: When a user installs the app, they are presented with an initial registration screen, which provides an interface for entering basic information such as name, age, and gender.

[1650] User: When launching the app for the first time, users enter basic information such as their name, age, and gender, and then enter medical information such as chronic illnesses and allergies.

[1651] Server: Receives the entered basic information and medical information and stores it in a database. Creates a user profile based on the stored information.

[1652] Creating a User Profile

[1653] Server: Based on the input information, a personalized user profile is generated, taking into account the user's dietary preferences and lifestyle.

[1654] Terminal: Provides an interface that displays customized questions based on the generated user profile, designed to gather information about dietary preferences and specific foods.

[1655] Users: Answer customized questions and enter more detailed information, which further refines their profile.

[1656] Menu suggestions

[1657] Server: Using an AI engine, it generates an appropriate medical meal menu based on the user profile. The generated menu is customized based on the user's health condition and dietary preferences.

[1658] Terminal: Provides an interface that displays the generated menu to the user and accepts selections.

[1659] User: Selects and confirms the desired menu. The selection information is sent to the server and recorded in the user profile.

[1660] emotion recognition

[1661] Device: Monitors the user's facial expressions, voice, etc., and uses an emotion recognition engine to analyze the user's current emotions.

[1662] Server: Receives the analysis results and stores the user's emotional data in a database, allowing the system to modify menu suggestions based on the user's psychological state.

[1663] Feedback and implementation record

[1664] Server: Periodically records the user's menu selection information and execution status, and accumulates feedback and emotion data.

[1665] Device: Provides regular notifications to users and prompts them to input their progress and emotional feedback.

[1666] User: Enters the situation, impressions, changes in physical condition, and emotions regarding the menu that was actually cooked or eaten. For example, reports on physical condition and psychological changes after eating.

[1667] Data storage and analysis

[1668] Server: Analyzes the user's health status trends based on accumulated performance data, feedback data, and emotional data. This can be reflected in future menu suggestions.

[1669] Terminal: The analysis results are notified to the user and displayed as reference information for the next menu suggestion.

[1670] Specific examples

[1671] For example, consider a 65-year-old senior citizen using this system. As an initial setup, the user installs the app and enters basic and medical information. This information is saved by the server and a user profile is generated. The user then answers customized questions to create a detailed profile.

[1672] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile and displays it on the device. The user selects and confirms the desired menu. At the same time, an emotion recognition engine analyzes the user's emotions and customizes the menu suggestions based on that data.

[1673] After eating, the user inputs their emotions and changes in physical condition, and the server analyzes and stores the data. The analysis results are reflected in the next menu suggestion and are notified to the user via their device.

[1674] This system allows users to receive personalized medical diets and feedback at home, enabling them to efficiently manage their health. It also utilizes emotional data to provide support appropriate to the user's psychological state.

[1675] The processing flow will be explained below.

[1676] Step 1:

[1677] When a device launches an app, it loads the necessary libraries and datasets, including the user interface, database connection modules, AI engine, emotion recognition engine, etc.

[1678] Step 2:

[1679] The device displays the initial registration screen to the user, providing an interface for entering basic information such as name, age, and gender.

[1680] Step 3:

[1681] The user enters basic information such as name, age, and gender, which is later used to create a user profile.

[1682] Step 4:

[1683] The server receives the basic information entered and stores it in a database, which is managed in a secure environment.

[1684] Step 5:

[1685] The device then displays a medical information entry screen, which provides an interface for entering detailed medical information such as chronic illnesses, allergies, and current health conditions.

[1686] Step 6:

[1687] The user enters medical information such as chronic illnesses, allergies, and current health conditions.

[1688] Step 7:

[1689] The server receives the entered medical information and stores it in a database, which gathers the information needed to create a user profile.

[1690] Step 8:

[1691] The server uses basic and medical information to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[1692] Step 9:

[1693] The device presents the user with customized questions based on their user profile, including information about dietary preferences and specific foods.

[1694] Step 10:

[1695] Users answer customization questions and enter further details, such as whether they want to avoid certain foods or what foods they prefer.

[1696] Step 11:

[1697] The server receives the user's response and updates the user profile, which is always updated with the latest information.

[1698] Step 12:

[1699] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, and the menu is customized based on the user's health condition and dietary preferences.

[1700] Step 13:

[1701] The terminal displays the generated menu on the user's screen, and the user can select the desired menu from multiple options.

[1702] Step 14:

[1703] The user selects and confirms the desired menu item, and this information is sent to the system.

[1704] Step 15:

[1705] The server receives the user's selection information and records it in a database, which is then used for feedback and analysis.

[1706] Step 16:

[1707] The device monitors the user's facial expressions and voice in real time and uses an emotion recognition engine to analyze their current emotions.

[1708] Step 17:

[1709] The server receives the analysis results from the emotion recognition engine and stores the user's emotion data in a database, which is used to improve menu suggestions.

[1710] Step 18:

[1711] The server periodically checks the user's progress and sends notifications, including reminders and progress checks.

[1712] Step 19:

[1713] The device periodically displays a status confirmation message to the user, allowing the user to enter information accordingly.

[1714] Step 20:

[1715] Users can input the status of the meal they have actually cooked and eaten, their impressions, changes in their physical condition, and their emotions. For example, they can report changes in blood sugar levels and psychological effects after eating.

[1716] Step 21:

[1717] The server receives user feedback and emotion data and stores it in a database. The collected data is reflected in future menu suggestions.

[1718] Step 22:

[1719] The server analyzes the user's health trends based on the collected data, including the effects of the foods consumed and their psychological impact.

[1720] Step 23:

[1721] The device will notify the user of the analysis results and display them as reference information for the next meal plan, allowing the user to plan their next meal based on this information.

[1722] Step 24:

[1723] Users can check the analysis results and use them to help them make better choices for their next meal, leading to better health.

[1724] Example 2

[1725] 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."

[1726] Conventional medical food delivery systems make it difficult for elderly people and patients who cannot be hospitalized to consume appropriate medical food at home and maintain and improve their health. Furthermore, they do not take into account the user's psychological state and do not provide individual dietary advice, which results in a poor overall user experience. Furthermore, they are unable to fully utilize user feedback and emotional data, which means they cannot be reflected in the next menu recommendation.

[1727] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1728] In this invention, the server includes a means for inputting a user's basic information and medical information, a means for receiving the input information and storing it in a database, a means for generating a user profile based on the stored information, a means for analyzing the user's emotions, a means for revising menu suggestions based on the analysis results, a means for periodically checking and notifying the user's progress, a means for collecting and storing user feedback, and a means for analyzing the collected data and notifying the user of the results. This enables personalized dietary advice to be provided based on the user's psychological state, improving the overall user experience. Furthermore, the feedback and emotional data can be reflected in the next menu suggestion, allowing medical diets to be suggested that are appropriate for the user's health and psychological state.

[1729] "Basic user information" refers to basic information such as name, age, and gender that is necessary to identify and individually respond to users.

[1730] "Medical information" refers to medical information necessary for health management and dietary suggestions, such as the user's chronic illnesses, allergies, and medical history.

[1731] "Database" refers to an information storage system for storing and managing a user's basic information, medical information, selection information, and feedback information.

[1732] A "user profile" is a data set generated based on a user's basic information and medical information, and is used to make individually appropriate menu suggestions.

[1733] A "medical meal menu" is a meal plan customized based on a user's health status and dietary preferences.

[1734] "Means for analyzing emotions" refers to technology that analyzes the user's facial expressions, voice, etc., to evaluate their current emotional state.

[1735] "Feedback" is information provided by the user regarding their impressions after eating and changes in their physical condition.

[1736] "Implementation status" is information about whether the user actually ate the suggested menu item.

[1737] The "analysis results" are information about the trends in the user's health and psychological state derived from the collected data.

[1738] This invention adds emotion recognition functionality to a system that helps elderly people and patients who cannot be hospitalized to consume appropriate medical diets at home and maintain and improve their health. The emotion recognition functionality aims to provide personalized dietary advice based on the user's psychological state and improve the overall user experience.

[1739] System configuration and operation

[1740] Initial Setup

[1741] The server loads the necessary libraries and datasets when the application starts, including the user interface, database connection module, AI engine, emotion recognition engine, etc. Specifically, it uses software libraries such as OpenFace, EmotionAPI, and TensorFlow.

[1742] The device displays an initial registration screen to the user who has installed the app. The initial registration screen provides an interface for the user to enter basic information such as name, age, and gender.

[1743] When users launch the app for the first time, they enter their basic information and medical information (such as chronic illnesses and allergies).

[1744] The server receives the basic and medical information entered by the user and stores it in a database, which automatically generates an individual user profile.

[1745] Creating a User Profile

[1746] The server uses the information entered to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[1747] Based on the generated user profile, the device provides an interface displaying customized questions, allowing for more detailed information to be gathered about the user's dietary preferences and specific foods.

[1748] Users answer customized questions and provide additional detailed information, which further refines the user profile.

[1749] Menu suggestions

[1750] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, which is customized according to the user's health condition and dietary preferences.

[1751] The terminal provides an interface for displaying the generated menu to the user and accepting selections.

[1752] The user selects and confirms the desired menu, and the selection is sent to the server and recorded in the user profile.

[1753] emotion recognition

[1754] The device is equipped with an emotion recognition engine that analyzes the user's facial expressions and voice, allowing it to assess the user's current emotional state in real time.

[1755] The server receives the analyzed emotion data and stores it in a database, which can then modify the next menu suggestion to better suit the user's psychological state.

[1756] Feedback and implementation record

[1757] The server periodically records the user's menu selection information and implementation status, accumulates feedback data and emotion data, and periodically notifies the user to prompt input of implementation status and emotion feedback.

[1758] Users input the status of the meal they actually cooked and ate, their impressions, changes in their physical condition, and their emotions. For example, they can provide feedback such as, "I feel better after eating today."

[1759] Data storage and analysis

[1760] The server analyzes the user's health status based on the accumulated data on the user's progress, feedback, and emotions, and can then reflect this in the next menu recommendation.

[1761] The terminal notifies the user of the analysis results and displays them as reference information for suggesting the next menu item.

[1762] Examples and prompts

[1763] For example, if a 65-year-old male uses this system, he or she will follow the steps below: First, he or she installs the app and enters information such as name, age, gender, and chronic illnesses (diabetes, allergies, etc.), which creates an individual user profile.

[1764] Next, a detailed profile is created by answering additional questions about the user's dietary preferences and specific foods. Based on this profile, the server uses an AI engine to generate an appropriate medical meal menu and displays it on the device. The user can then select what they want from the menu.

[1765] After eating, the emotion recognition engine analyzes the user's current emotional state, and the data is sent to the server. The user also enters their thoughts about the meal and any changes in their physical condition, and this data is stored for analysis.

[1766] The analysis results are reflected in the next menu suggestion and notified to the user, allowing for more personalized and healthy meal suggestions.

[1767] Example prompt for generative AI model:

[1768] "A 65-year-old man with chronic conditions of diabetes and high blood pressure. His favorite foods are chicken and broccoli. Please suggest a daily meal menu."

[1769] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1770] Step 1:

[1771] The server loads the necessary libraries and datasets when the application starts, including software libraries such as OpenFace, EmotionAPI, and TensorFlow. Loading these prepares the entire system for operation.

[1772] Input: Application launch event

[1773] Output: Library and dataset loading completion status

[1774] Step 2:

[1775] The device displays an initial registration screen to users who have installed the app. This screen provides an interface for entering basic information such as name, age, and gender. The user interface is created using HTML or React Native.

[1776] Input: User's first launch of the app

[1777] Output: Display of initial registration screen

[1778] Step 3:

[1779] On the initial registration screen, users enter basic information such as name, age, and gender, as well as medical information such as chronic illnesses and allergies.

[1780] Input: Initial registration screen (basic information and medical information)

[1781] Output: Basic and medical information entered

[1782] Step 4:

[1783] The server receives the basic and medical information entered by the user and stores it in a database, which creates an individual user profile. The database used for storage is SQLite.

[1784] Input: Basic and medical information entered by the user

[1785] Output: User information stored in the database and generated profile

[1786] Step 5:

[1787] The server uses the information entered to create a personalized user profile, which includes information about the user's medical conditions, allergies, and dietary preferences.

[1788] Input: Basic and medical information stored in the database

[1789] Output: Generated user profile

[1790] Step 6:

[1791] Based on the generated user profile, the device provides an interface that displays additional customized questions to gather information about the user's dietary preferences and specific foods.

[1792] Input: Generated user profile

[1793] Output: Display of customization questions

[1794] Step 7:

[1795] Users answer customized questions and enter detailed information, which refines their profile.

[1796] Input: Customization Question

[1797] Output: Detailed information of the answer

[1798] Step 8:

[1799] The server uses an AI engine based on the user profile to generate an appropriate medical meal menu. The menu is customized according to the user's health condition and dietary preferences. The AI ​​engine uses TensorFlow and other technologies.

[1800] Input: Detailed user profile

[1801] Output: Generated medical food menu

[1802] Step 9:

[1803] The terminal provides an interface for displaying the generated menu to the user and accepting selections.

[1804] Input: Generated medical food menu

[1805] Output: Show menu

[1806] Step 10:

[1807] The user selects and confirms the desired menu item, and the selection is sent to the server and recorded in the user profile.

[1808] Enter:

[1809] Output: Selected menu and confirmation information

[1810] Step 11:

[1811] The device uses an emotion recognition engine that analyzes the user's facial expressions and voice to determine their current emotional state in real time, using OpenFace and EmotionAPI.

[1812] Input: User's facial expressions and voice

[1813] Output: Parsed emotion data

[1814] Step 12:

[1815] The server receives the analyzed emotion data and stores it in a database, which allows it to tailor the next menu suggestion to suit the user's emotional state.

[1816] Input: Parsed emotion data

[1817] Output: Emotion data stored in a database

[1818] Step 13:

[1819] The server periodically records the user's menu selection information and execution status, accumulates feedback and emotion data, and sends notifications to prompt the user to input execution status and emotion feedback via the terminal.

[1820] Input: User performance and feedback

[1821] Output: Recorded performance and feedback data

[1822] Step 14:

[1823] Users input the status of the meal they actually cooked and ate, their impressions, changes in their physical condition, and their emotions. For example, they can provide feedback such as, "I feel better after eating today."

[1824] Input: Implementation status and impressions, changes in physical condition

[1825] Output: Providing feedback data

[1826] Step 15:

[1827] The server analyzes the user's health trends based on the accumulated data and reflects this in its next menu suggestions. It also notifies the user of the analysis results via their device, allowing for more personalized and healthy meal suggestions.

[1828] Input: Accumulated implementation status data, feedback data, emotion data

[1829] Output: Analysis results and next menu suggestions

[1830] (Application example 2)

[1831] 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."

[1832] Conventional systems are insufficient to support elderly people and patients with chronic illnesses in maintaining and improving their health by consuming appropriate medical foods at home. Furthermore, they do not provide personalized dietary advice that takes into account the user's emotional state, which hinders the overall user experience.

[1833] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1834] a means for inputting basic information and medical information of the user;

[1835] means for receiving the input information and storing it in a database;

[1836] means for generating a user profile based on the stored information;

[1837] A means for generating an appropriate medical diet menu based on a user profile;

[1838] means for displaying the generated menu to a user and accepting a selection;

[1839] means for recording user selection information;

[1840] A means for periodically checking and notifying the user of their implementation status;

[1841] a means for collecting and storing user feedback;

[1842] means for analyzing the collected data and notifying the user of the results;

[1843] A means for monitoring the user's facial expressions and voice and analyzing emotions;

[1844] A means for customizing medical food menus based on emotional data;

[1845] This makes it possible to propose individual medical diets that take into account the user's health and psychological state.

[1846] "Basic user information" refers to information for identifying an individual, such as name, age, sex, and address.

[1847] "Medical information" refers to information necessary for health management, such as the user's chronic illnesses, allergies, and medication usage.

[1848] A "user profile" is an individual data set that is constructed based on a user's basic information and medical information.

[1849] A "medical diet menu" is a meal suggestion created based on the user's health condition and dietary preferences.

[1850] "Emotion data" is information about the psychological state obtained by analyzing the user's facial expressions, voice, etc.

[1851] "Customization" means adjusting or modifying something to suit your individual needs and preferences.

[1852] "Feedback" refers to reactions such as opinions and impressions provided by users.

[1853] "Generation" means creating new data or suggestions based on algorithms and rules.

[1854] "Selection information" refers to the specific content selected by the user from the options provided.

[1855] The "implementation status" refers to the extent to which the user has implemented the suggested menu or instruction.

[1856] "Notification" is the act of the system providing information to the user.

[1857] MODE FOR CARRYING OUT THE INVENTION

[1858] The system for implementing this invention operates in cooperation with three parties: a server, a terminal, and a user. The following describes the processes of each party and the hardware and software used.

[1859] server

[1860] Initial Setup and Profile Creation

[1861] The server receives the user's basic information and medical information and stores it in a database. Basic information includes name, age, gender, etc., while medical information includes chronic illnesses, allergies, and medication usage. A user profile is generated based on this information. The server uses a database and an AI engine (e.g., TensorFlow or Django).

[1862] Menu suggestions and emotion recognition

[1863] The server generates an appropriate medical meal menu based on the generated user profile and emotional data. Emotional data is information about the user's psychological state obtained by analyzing the user's facial expressions and voice. The server analyzes the emotional data using an emotion recognition engine (e.g., OpenCV) and passes the results to an AI engine to generate a customized menu.

[1864] Feedback and Data Analysis

[1865] The system collects feedback provided by users and stores it in a database. Based on the collected data, the system evaluates the user's health status and reflects it in menu suggestions for future visits. The server analyzes the feedback data and notifies the user of the results.

[1866] Terminal

[1867] User Interface and Data Entry

[1868] The device (such as a smartphone or smart glasses) provides an interface for users to input basic and medical information, and displays and accepts answers to questions customized based on the user profile.

[1869] Collecting Emotional Data

[1870] The device uses a built-in camera and microphone to monitor the user's facial expressions and voice in real time, and sends the data to an emotion recognition engine. This data is then transferred to a server and used to make menu suggestions.

[1871] Menu Selection and Notifications

[1872] The terminal displays the generated menu to the user and provides an interface for menu selection. When the user selects the desired menu, the selection information is sent to the server and recorded in the user profile. In addition, the user's implementation status is periodically checked and notified.

[1873] User

[1874] Entering information and selecting menus

[1875] Users enter basic and medical information on first launch, then answer questions to create a detailed profile, choose from a menu of suggestions, and provide feedback to improve the overall accuracy and user experience of the system.

[1876] Feedback Input

[1877] Users enter their emotions and changes in physical condition after a meal into the app, and the server analyzes the data and reflects it in menu suggestions for the next meal.

[1878] Specific examples

[1879] For example, if a 65-year-old senior citizen needs a medical diet based on their physical condition and emotions, the user installs the app and enters their basic and medical information. The app uses the smartphone camera to recognize emotions and analyze the user's current emotional state (e.g., increased stress). Based on the analysis results, the AI ​​engine generates a stress relief menu appropriate for the user and displays it on the device.

[1880] Example prompts for generative AI models

[1881] Prompt: A 65-year-old male needs blood pressure management and is currently under a lot of stress. Please suggest a medical diet for this user that is appropriate for his health and emotional state.

[1882] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1883] Program processing flow

[1884] Step 1:

[1885] The user installs the app and registers for the first time. The information entered includes basic information such as name, age, gender, chronic illnesses, and allergies, as well as medical information. The device acquires this information and sends it to the server. The input for this step is the basic information and medical information provided by the user, and the output is that this information is sent to the server.

[1886] Step 2:

[1887] The server stores the received basic and medical information in a database. The server then generates a user profile based on that information, including the user's preferences and lifestyle habits. The input to this step is the user information sent from the device, and the output is the generated user profile.

[1888] Step 3:

[1889] The terminal displays customized questions based on the user profile. The user answers the questions and provides further detailed information. The terminal sends this information back to the server. The input to this step is the generated user profile and customized questions, and the output is detailed user information.

[1890] Step 4:

[1891] The server stores the received detailed information in a database and uses an AI engine to generate an appropriate medical diet menu. This generated menu is customized based on the user's health condition and emotions. The input of this step is detailed user information, and the output is the generated medical diet menu.

[1892] Step 5:

[1893] The terminal displays the generated menu to the user and accepts the menu selection. The user selects the desired menu and the selection information is sent to the server. The input of this step is the generated medical diet menu, and the output is the user's selection information.

[1894] Step 6:

[1895] The device monitors the user's facial expressions and voice and analyzes the emotional data using an emotion recognition engine. The emotional data is sent to the server and stored in the user profile. The input of this step is the user's facial expressions and voice, and the output is the analyzed emotional data.

[1896] Step 7:

[1897] The server receives the analyzed emotion data and modifies the menu suggestions based on it. For example, a menu using ingredients that relieve stress may be suggested to a user who is under stress. The input of this step is emotion data, and the output is a modified medical food menu.

[1898] Step 8:

[1899] The user provides feedback after eating. The device collects this feedback and sends it to the server. The server stores the feedback data and reflects it in the next menu suggestion. The input of this step is the user feedback, and the output is an updated database and an improved suggestion for the next time.

[1900] Step 9:

[1901] The server periodically checks the user's status and sends a notification to the terminal. The user inputs the status in response to the notification, and the data is sent to the server. The input of this step is the periodic confirmation notification, and the output is the user's status data.

[1902] Step 10:

[1903] The server analyzes the collected data and notifies the user of the results, making it easier for users to understand their own health status. The input to this step is the various collected data, and the output is a notification of the analysis results.

[1904] 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.

[1905] 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.

[1906] 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.

[1907] [Fourth embodiment]

[1908] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1909] 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.

[1910] 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).

[1911] 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.

[1912] 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.

[1913] 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).

[1914] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1915] 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.

[1916] 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.

[1917] 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.

[1918] 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.

[1919] 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.

[1920] 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."

[1921] MODE FOR CARRYING OUT THE INVENTION

[1922] This invention is a system that aims to enable elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home and maintain or improve their health. The system creates a user profile based on the user's basic information and medical information, and proposes medical food menus generated by AI. It also collects the user's progress and feedback, and proposes further customized menus based on the analysis results.

[1923] Program processing

[1924] Initial Setup

[1925] Server: Loads the necessary libraries and datasets when the app starts, including the AI ​​engine, database connection module, notification service, etc.

[1926] On the device: After the user installs the app, the app displays a screen for entering basic and medical information when the user launches it for the first time. This provides an interface that makes it easy for users to enter their information.

[1927] User: When launching the app for the first time, users enter basic information such as their name, age, and gender, and then enter medical information such as chronic illnesses and allergies.

[1928] Creating a User Profile

[1929] Server: Receives the basic and medical information entered and stores it in a database. It generates an individual user profile based on the information entered. This profile also takes into account the user's dietary preferences and lifestyle.

[1930] On the device: It displays customized questions based on the user's profile information and provides an interface to gather further information.

[1931] User: Answers customization questions and enters additional information, such as whether the user likes certain foods or whether there are foods they want to avoid.

[1932] Menu suggestions

[1933] Server: Based on the user profile, the AI ​​engine generates an appropriate medical meal menu, which is customized based on the user's health condition and dietary preferences.

[1934] Terminal: Provides an interface that displays the proposed menus on the user's screen and allows the user to select the desired menu.

[1935] User: Selects from the menu of options and confirms. This information is sent to the server and reflected in the user profile.

[1936] Recording implementation and feedback

[1937] Server: Periodically records the menu selections made by the user and their implementation status. Also, accumulates feedback and reflects it in the next menu proposal.

[1938] Terminal: Periodically notify the user and display a screen to check the status of the menu, helping the user remember to enter information.

[1939] User: Records the meals they have actually cooked and eaten, and inputs their impressions and changes in their physical condition. For example, they report changes in blood sugar levels after meals and whether their physical condition is good or bad.

[1940] Data storage and analysis

[1941] Server: Based on the accumulated data, the server analyzes the user's health trends and reflects them in future menu suggestions, enabling more effective medical diet suggestions.

[1942] Device: The analysis results are fed back to the user and displayed as reference information when suggesting menu items next time.

[1943] Users: Review the feedback and use it to make better menu choices next time, leading to healthier choices.

[1944] Specific examples

[1945] For example, consider the case where a 60-year-old person uses this system.

[1946] Initial Setup

[1947] When a user installs the app and launches it for the first time, they enter their basic and medical information. The server stores this information in a database and creates a user profile.

[1948] Creating a User Profile

[1949] The device displays customized questions and the user enters details, which the server uses to update the profile and suggest a personalized medical diet menu.

[1950] Menu suggestions

[1951] The server uses an AI engine to generate an appropriate menu based on the user profile and displays it on the device. The user then selects and confirms the desired menu.

[1952] Recording implementation and feedback

[1953] The server periodically records the user's menu selection and the progress of the meal, and collects feedback. The device periodically notifies the user, allowing them to input their impressions after the meal and any changes in their physical condition.

[1954] Data storage and analysis

[1955] The server analyzes the collected data and reflects it in the next menu suggestion, while the device notifies the user of the analysis results and helps them use them to make their next selection.

[1956] The system allows users to easily consume the right medical diet to maintain and improve their health at home.

[1957] The processing flow will be explained below.

[1958] Step 1:

[1959] When a device launches an app, it loads the necessary libraries and datasets, including the user interface, database connection modules, and AI engine.

[1960] Step 2:

[1961] The device displays the initial registration screen to the user, providing an interface for entering basic information such as name, age, and gender.

[1962] Step 3:

[1963] The user enters basic information such as name, age, and gender, which is later used to create a user profile.

[1964] Step 4:

[1965] The server receives the basic information entered and stores it in a database, which is managed in a secure environment.

[1966] Step 5:

[1967] The device then displays a medical information entry screen, which provides an interface for entering detailed medical information such as chronic illnesses, allergies, and current health conditions.

[1968] Step 6:

[1969] The user enters medical information such as chronic illnesses, allergies, and current health conditions.

[1970] Step 7:

[1971] The server receives the entered medical information and stores it in a database, which gathers the information needed to create a user profile.

[1972] Step 8:

[1973] The server uses basic and medical information to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[1974] Step 9:

[1975] The device presents the user with customized questions based on their user profile, including information about dietary preferences and specific foods.

[1976] Step 10:

[1977] Users answer customization questions and enter further details, such as whether they want to avoid certain foods or what foods they prefer.

[1978] Step 11:

[1979] The server receives the user's response and updates the user profile, which is always updated with the latest information.

[1980] Step 12:

[1981] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, which reflects the user's health condition and dietary preferences.

[1982] Step 13:

[1983] The terminal displays the generated menu on the user's screen, and the user can select the desired menu from multiple options.

[1984] Step 14:

[1985] The user selects and confirms the desired menu item, and this information is sent to the system.

[1986] Step 15:

[1987] The server receives the user's selection information and records it in a database, which is then used for feedback and analysis.

[1988] Step 16:

[1989] The server periodically checks and notifies the user about their progress, including reminders and progress checks.

[1990] Step 17:

[1991] The device periodically displays a status confirmation message to the user, allowing the user to enter information accordingly.

[1992] Step 18:

[1993] Users can input the status of the meal they have actually cooked and eaten, their impressions, and any changes in their physical condition. For example, they can report changes in blood sugar levels and their physical condition after eating.

[1994] Step 19:

[1995] The server receives user feedback and stores it in a database. The collected data is used to suggest new menu items for future visits.

[1996] Step 20:

[1997] The server analyzes the user's health trends based on the collected data, including the effects of foods consumed and changes in physical condition.

[1998] Step 21:

[1999] The device will notify the user of the analysis results and display them as reference information for the next meal plan, allowing the user to plan their next meal based on this information.

[2000] Step 22:

[2001] Users can check the analysis results and use them as a reference for their next menu selection, allowing them to make appropriate choices that lead to better health.

[2002] Example 1

[2003] 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."

[2004] It is important for elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home to maintain or improve their health. However, it is difficult to easily obtain medical foods tailored to individual health conditions and dietary preferences at home. Furthermore, there is a lack of systems for ensuring that meals are consumed at the appropriate time and for continuously monitoring their effects. As a result, many patients are unable to consume appropriate medical foods, which can lead to a deterioration in their health.

[2005] 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.

[2006] In this invention, the server includes means for inputting a user's basic information and medical information, means for receiving the input information and saving it in a database, means for generating a user profile based on the saved information, means for generating an appropriate medical diet menu based on the generated user profile, means for displaying the generated medical diet menu to the user and accepting selections, means for recording the user's selection information and reflecting it in the user profile, means for periodically checking and notifying the user's progress, means for collecting and saving user feedback, and means for analyzing the user's health condition based on the collected data and notifying the user of the results. This allows users to easily consume a medical diet appropriate for them at home and continuously monitor its effects.

[2007] "Basic user information" refers to information for identifying an individual, such as the user's name, age, and gender.

[2008] "Medical information" refers to information related to a user's health condition and treatment, such as chronic illnesses, allergies, and medications currently being taken.

[2009] A "database" is a system that centrally manages and stores information, allowing it to be quickly searched and retrieved as needed.

[2010] A "user profile" is a detailed data structure about an individual user that is generated based on the user's basic information and medical information.

[2011] A "medical diet menu" is a meal plan customized to the user's health condition and dietary preferences.

[2012] The "AI engine" is a software module that uses artificial intelligence technology to generate appropriate medical diet menus based on user profiles.

[2013] A "notification service" is a mechanism for notifying users of specific information or actions.

[2014] A "prompt sentence" is an input sentence that causes the AI ​​engine to perform tasks such as generating a menu.

[2015] "Feedback" refers to information provided by users after a meal, such as their impressions and changes in their physical condition, and is reflected in future menu suggestions.

[2016] "Analysis results" are the results of analysis performed by the AI ​​engine based on collected data, and are data that indicate the user's health condition and the effects of their diet.

[2017] "Health trends" are information about fluctuations and patterns in health status obtained through analysis of a user's ongoing health data.

[2018] "Customized questions" are questions that are used to obtain more detailed information about the lifestyle and dietary preferences of individual users in order to create a user profile.

[2019] "Periodic notification" is a notification that prompts the user to input information and check the meal status at regular intervals.

[2020] This invention is a system that aims to enable elderly people and patients who cannot be hospitalized to ingest appropriate medical foods at home and maintain or improve their health. Specific embodiments for carrying out this invention are described below.

[2021] Initial Setup

[2022] Server: When the app starts, it first imports the AI ​​engine (e.g., TensorFlow, PyTorch), database connection module (e.g., MySQL connection library), and notification service library to load the necessary libraries and datasets. This ensures that the necessary data and models are immediately available.

[2023] Device: After installing the app, the user will be prompted to enter basic and medical information when they first launch it. This screen provides a UI (user interface) for entering information such as name, age, gender, chronic illnesses, and allergies.

[2024] User: When launching the app for the first time, the user enters basic information such as name, age, and gender, followed by medical information such as chronic illnesses and allergies. This information is sent to the server.

[2025] Creating a User Profile

[2026] Server: Receives the basic and medical information entered and stores it in a database (e.g., MySQL, PostgreSQL). Based on the stored information, a user profile is generated for each individual user, including the user's dietary preferences and lifestyle.

[2027] On the device: Based on the user's profile information, the device will ask customized questions (e.g., whether they like certain foods or avoid certain foods) and provide an interface to gather more detailed information.

[2028] Users: Answer customization questions and enter additional information, such as details about specific food preferences or foods they avoid.

[2029] Menu suggestions

[2030] Server: Generates appropriate medical meal menus using a generative AI model (e.g., GPT-4) based on the user profile. The generated menus are customized based on the user's health condition and dietary preferences.

[2031] Terminal: Provides an interface that displays the proposed menus on the user's screen and allows the user to select the desired menu.

[2032] User: Selects desired option from the menu of suggestions and confirms. This information is sent to the server and reflected in the user profile.

[2033] Recording implementation and feedback

[2034] Server: Periodically records the menu selections and their implementation status, and collects feedback to be reflected in the next menu suggestions.

[2035] Terminal: Periodically notify the user and display a screen to check the status of the menu, helping the user remember to enter information.

[2036] User: Records the meals they have actually cooked and eaten, and inputs their impressions and changes in their physical condition. For example, they report changes in blood sugar levels after meals and whether their physical condition is good or bad.

[2037] Data storage and analysis

[2038] Server: Based on the accumulated data, the server analyzes the user's health trends and reflects them in future menu suggestions, enabling more effective medical diet suggestions.

[2039] Device: The analysis results are fed back to the user and displayed as reference information when suggesting menu items next time.

[2040] Users: Review the feedback and use it to make better menu choices next time, leading to healthier choices.

[2041] Specific examples

[2042] For example, consider the case where a 60-year-old person uses this system.

[2043] Initial Setup

[2044] When a user installs the app and launches it for the first time, they enter their basic and medical information. The server stores this information in a database and creates a user profile.

[2045] Creating a User Profile

[2046] The device displays customized questions and the user enters further details, which the server uses to update the profile and suggest a personalized medical diet menu.

[2047] Menu suggestions

[2048] The server uses a generative AI model based on the user profile to generate an appropriate menu and displays it on the device. The user then selects and confirms the desired menu.

[2049] Recording implementation and feedback

[2050] The server records the user's menu selection and the progress of the meal, and collects feedback. The device periodically sends notifications, allowing the user to input their impressions after the meal and any changes in their physical condition.

[2051] Data storage and analysis

[2052] The server analyzes the collected data and reflects it in the next menu suggestion, while the device notifies the user of the analysis results and helps them use them to make their next selection.

[2053] Example of input prompt for generative AI model

[2054] "Please suggest an appropriate medical diet menu for a 60-year-old male user with diabetes. His preference is fish dishes, and he wants to avoid fried foods."

[2055] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2056] Processing Steps

[2057] Step 1: Initial Setup

[2058] server

[2059] What it does: Loads required libraries and datasets when the app starts.

[2060] Input: N / A

[2061] Output: Loaded libraries and datasets

[2062] Specific operation:

[2063] 1. Import the AI ​​engine (e.g. TensorFlow or PyTorch) library.

[2064] 2. Import the database connection module (for example, the MySQL connection library).

[2065] 3. Load the initial dataset for menu generation (e.g., a CSV file of a medical food database) into memory.

[2066] Terminal

[2067] How it works: After the user installs the app, the first time they launch it, they are prompted to enter their basic and medical information.

[2068] Input: N / A

[2069] Output: User information input screen

[2070] Specific operation:

[2071] 1. Check the first boot flag.

[2072] 2. If this is your first time, you will be prompted to enter your name, age, gender, medical conditions, and allergies.

[2073] User

[2074] How it works: When you first launch the app, you enter basic information such as your name, age, and gender, and then enter medical information such as any chronic illnesses or allergies.

[2075] Input: Name, age, gender, chronic illness, allergy information

[2076] Output: User information entered

[2077] Specific operation:

[2078] 1. Enter the information in each input field.

[2079] 2. Press the send button.

[2080] Step 2: Create a user profile

[2081] server

[2082] How it works: Receives basic and medical information entered and stores it in a database. Creates a user profile based on the stored information.

[2083] Input: User's basic and medical information

[2084] Output: User profile data

[2085] Specific operation:

[2086] 1. Parse the user information received in the HTTP request.

[2087] 2. Execute an INSERT query to the database to save the user information.

[2088] 3. Run the profile generation logic based on the stored information.

[2089] Terminal

[2090] What it does: Shows users customized questions based on their profile information.

[2091] Input: User profile data

[2092] Output: Custom question input screen

[2093] Specific operation:

[2094] 1. Retrieve profile data from the server with a GET request.

[2095] 2. Generate customized questions based on your profile.

[2096] 3. The question input screen will be displayed.

[2097] User

[2098] What it does: Answer customization questions and enter additional information.

[2099] Input: Answer to customization question

[2100] Output: Added user information

[2101] Specific operation:

[2102] 1. Enter text and options for the question.

[2103] 2. Press the send button.

[2104] Step 3: Menu proposal

[2105] server

[2106] How it works: Generates appropriate medical meal menus using a generative AI model based on a user profile.

[2107] Input: User profile data

[2108] Output: Suggested menu list

[2109] Specific operation:

[2110] 1. Query the user profile from the database.

[2111] 2. Generate a prompt sentence and input it into the generative AI model.

[2112] 3. Convert the results received from the AI ​​engine into a menu list.

[2113] Terminal

[2114] Behavior: Displays the suggested menu on the user's screen.

[2115] Input: Suggestion menu list

[2116] Output: Suggestion menu screen

[2117] Specific operation:

[2118] 1. Get the suggested menu list from the server with a GET request.

[2119] 2. Render the menu UI and display the list.

[2120] User

[2121] Action: Select the desired option from the menu of suggestions and confirm.

[2122] Enter: Selected menu

[2123] Output: Confirmed menu information

[2124] Specific operation:

[2125] 1. Scroll through the menu list and select the desired menu.

[2126] 2. Press the Confirm button.

[2127] Step 4: Recording progress and feedback

[2128] server

[2129] Behavior: Periodically records the user's menu selections and their implementation status, and collects feedback to be reflected in the next menu suggestions.

[2130] Input: User selection data and feedback

[2131] Output: Recorded data and analysis results

[2132] Specific operation:

[2133] 1. Save the selection data received in the HTTP request to the database.

[2134] 2. Periodically send feedback data to the analysis logic and accumulate the results.

[2135] Terminal

[2136] Behavior: Sends periodic notifications and displays a screen to the user to check the status of the menu.

[2137] Input: Implementation status confirmation request

[2138] Output: Implementation status input screen

[2139] Specific operation:

[2140] 1. Set up local notifications and schedule them to run.

[2141] 2. A pop-up screen will appear asking you to confirm the implementation status.

[2142] User

[2143] Operation: Record the meals you have actually cooked and eaten, and enter your impressions and changes in your physical condition.

[2144] Input: Impressions and changes in physical condition

[2145] Output: Feedback data

[2146] Specific operation:

[2147] 1. Enter your thoughts in the text area and select the changes in your physical condition using the check boxes.

[2148] 2. Press the send button.

[2149] Step 5: Store and analyze data

[2150] server

[2151] How it works: Analyzes the user's health trends based on accumulated data.

[2152] Input: Collected feedback data

[2153] Output: Health status analysis results

[2154] Specific operation:

[2155] 1. Run data analysis algorithms to visualize health trends.

[2156] 2. The analysis results are saved in a database and used to generate the next menu.

[2157] Terminal

[2158] Behavior: The analysis results are fed back to the user and displayed as reference information for the next menu suggestion.

[2159] Input: Health status analysis results

[2160] Output: Analysis result screen

[2161] Specific operation:

[2162] 1. Retrieve the analysis results from the server with a GET request.

[2163] 2. Render the UI for displaying the analysis results and display it to the user.

[2164] User

[2165] What it does: Review the feedback and use it to influence your next menu choice.

[2166] Input: Analysis results

[2167] Output: Feedback that influences your next choice

[2168] Specific operation:

[2169] 1. Check the analysis results page and understand the contents.

[2170] (Application example 1)

[2171] 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."

[2172] Currently, elderly people and patients who cannot be hospitalized have difficulty consuming appropriate medical foods at home. There are also issues with the time and effort required to manually select and order medical food menus, and the cumbersome nature of managing feedback. Furthermore, medical food recommendations are not sufficiently personalized, meaning that appropriate menus are not provided that meet the specific needs of users.

[2173] 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.

[2174] In this invention, the server includes means for inputting a user's basic information and medical information, means for receiving the input information and saving it in a database, means for generating a user profile based on the saved information, means for generating an appropriate medical diet menu based on the user profile, means for displaying the generated menu to the user and accepting selections, means for ordering the selected menu from an external delivery service, means for recording the user's selection information, means for periodically checking and notifying the user of the user's progress, means for collecting and saving user feedback, and means for analyzing the collected data and notifying the user of the results. This makes it easy to consume an appropriate medical diet at home, and realizes highly accurate personalized menu suggestions based on feedback.

[2175] "Basic user information" refers to basic information specific to a user, such as name, age, and gender.

[2176] "Medical information" refers to information related to the user's health condition and medical care, such as chronic illnesses, allergies, and medications taken.

[2177] "Input means" refers to the interface and device through which the user inputs basic and medical information into the database.

[2178] "Means for receiving and storing in a database" refers to the system and software for receiving the input information and storing it in a database.

[2179] A "user profile" is data generated based on a user's basic information and medical information, reflecting the user's specific health conditions and dietary preferences.

[2180] "Means for generating" refers to the technical means for creating an appropriate medical diet menu using AI or algorithms based on a user profile.

[2181] The "means for displaying a menu to a user and accepting a selection" is an interface for presenting the generated medical diet menu to a user and allowing the user to select the desired menu from among the menus.

[2182] The "means for ordering the selected menu from an external delivery service" is a system for quickly ordering the medical food menu selected by the user from an external delivery service.

[2183] The "means for recording selection information" refers to a technical means for saving and managing data related to the menu selected by the user.

[2184] The "means for periodically checking and notifying the implementation status" is a system for checking whether the user is properly implementing the menu they selected and notifying them accordingly.

[2185] The "means for collecting and storing feedback" refers to the technical means for collecting data on users' impressions after meals and changes in their physical condition, and storing this data in a database.

[2186] The "means for analyzing collected data and notifying the user of the results" refers to a system and software for analyzing collected feedback data and notifying the user of the results.

[2187] To implement this invention, a system is required that inputs a user's basic information and medical information, generates a user profile based on that information, proposes and allows the user to select a medical diet menu, and manages implementation status and feedback. This system is composed of hardware and software, including a server, a user's terminal, and an external delivery service.

[2188] First, a user installs the smartphone app and enters their basic and medical information. This information is sent from the user's device to a server and stored in a database. The server then generates an individual user profile based on this information. The user profile also includes the user's dietary preferences and lifestyle.

[2189] Based on the generated user profile, an AI engine generates an appropriate medical diet menu. This AI engine uses a generative AI model. The AI ​​model proposes a menu customized according to the user's profile. This menu is displayed on the user's device.

[2190] The user selects the desired item from the proposed menu, and the selected menu item is automatically ordered from an external delivery service via the server. At this time, the order data is sent to an external API using an HTTP request. At the same time, the selection information is recorded in the database.

[2191] The server periodically sends notifications to the user's device regarding the menu implementation status and provides an interface for the user to record the menu items they have actually cooked and consumed. The user inputs feedback after eating and any changes in their physical condition. This information is also sent to the server and stored in a database.

[2192] The server analyzes the collected feedback data and notifies the user of the results. The analysis results are reflected in the next menu proposal, making it possible to provide a more personalized medical meal menu. For example, in the case of a 60-year-old elderly person with diabetes, the AI ​​would suggest a low-carb menu that takes blood sugar levels into consideration.

[2193] This system uses the open source Flask and FastAPI to create API endpoints, and the Python programming language for data processing. Advanced natural language processing models such as GPT-3 can be applied as generative AI models.

[2194] Here, an example of a prompt sentence when generating a medical diet menu based on a user profile is shown.

[2195] Example prompt sentence:

[2196] "Please suggest an appropriate medical diet menu based on the following user profile: Name: Yamada Taro, Age: 65, Gender: Male, Chronic illness: Diabetes, Allergies: Nuts, Favorite foods: Fish, Tofu, Foods to avoid: Sweets."

[2197] As described above, by using this system, elderly people and patients who cannot be hospitalized can easily consume appropriate medical foods at home, thereby maintaining or improving their health.

[2198] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2199] Step 1:

[2200] Users install the smartphone app and enter basic and medical information, including name, age, gender, chronic illnesses, allergies, etc. The device then sends this information to the server.

[2201] input:

[2202] Your basic and medical information

[2203] output:

[2204] User information data sent to the server

[2205] Specific behavior:

[2206] When a user enters information into the application's input form and presses the submit button, the device sends this information to the server via an HTTP POST request.

[2207] Step 2:

[2208] The server stores the received information in a database, which contains detailed profiles for each user.

[2209] input:

[2210] User information data sent from the device

[2211] output:

[2212] User profile information stored in a database

[2213] Specific behavior:

[2214] The server parses the received data and executes SQL queries to store it in a database.

[2215] Step 3:

[2216] The server generates a user profile based on the stored information, and the AI ​​engine uses this profile to create prompts for generating medical meal menus.

[2217] input:

[2218] User information stored in a database

[2219] output:

[2220] User profile used as prompt

[2221] Specific behavior:

[2222] The server reads the data in each field and creates a prompt in text format for the AI ​​engine.

[2223] Step 4:

[2224] The AI ​​engine generates medical meal menus based on user profiles, using generative AI models such as GPT-3.

[2225] input:

[2226] Prompt statement

[2227] output:

[2228] AI-generated customized medical meal menus

[2229] Specific behavior:

[2230] The prompt text is sent to the AI ​​engine as an API request and the generated menu is received.

[2231] Step 5:

[2232] The server displays the generated menu on the user's terminal, and the user selects what they want from the proposed menu.

[2233] input:

[2234] AI-generated medical food menu

[2235] output:

[2236] Menu list displayed on the user's device

[2237] Specific behavior:

[2238] The server sends the menu information to the user terminal, which displays it on the screen.

[2239] Step 6:

[2240] When the user selects the desired menu item, the terminal sends the information to the server, which records the selection information in a database and simultaneously sends the order to an external delivery service.

[2241] input:

[2242] The menu selected by the user

[2243] output:

[2244] Selection information recorded in a database and order information transmitted to delivery services

[2245] Specific behavior:

[2246] When the user presses the selection button, the terminal sends the selection information to the server, which stores it in a database and also sends an order to the delivery service via an HTTP request.

[2247] Step 7:

[2248] The server periodically checks the user's status and sends a notification to the user terminal, and the user records the status based on the notification.

[2249] input:

[2250] Server notifications

[2251] output:

[2252] User implementation records

[2253] Specific behavior:

[2254] The server triggers the notification at the scheduled time and sends the notification content to the user terminal. The user inputs the implementation status according to the notification, and the terminal sends it to the server.

[2255] Step 8:

[2256] After the user performs the task, he / she inputs feedback, and the terminal sends this feedback information to the server, which stores it in the database.

[2257] input:

[2258] User feedback information

[2259] output:

[2260] Feedback information stored in a database

[2261] Specific behavior:

[2262] When a user fills in the feedback form and presses the submit button, the terminal sends the information to the server, which stores it in a database.

[2263] Step 9:

[2264] The server analyzes the collected data and notifies the user of the results, using the user's health status and past feedback data.

[2265] input:

[2266] Various data collected

[2267] output:

[2268] Analysis results notified to the user

[2269] Specific behavior:

[2270] The server runs the data analysis algorithms and generates results, which are sent to the user as notifications and reflected in the next menu suggestion.

[2271] Through the above steps, the system of the present invention can realize a series of processes that allow elderly people and patients who cannot be hospitalized to easily ingest appropriate medical foods at home and maintain or improve their health.

[2272] 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.

[2273] MODE FOR CARRYING OUT THE INVENTION

[2274] This invention adds emotion recognition functionality to a system that helps elderly people and patients who cannot be hospitalized to consume appropriate medical foods at home and maintain and improve their health. This emotion recognition functionality aims to provide personalized dietary advice based on the user's psychological state and improve the overall user experience.

[2275] Program processing

[2276] Initial Setup

[2277] Server: Loads the necessary libraries and datasets when the app starts, including the user interface, database connection module, AI engine, emotion recognition engine, etc.

[2278] Device: When a user installs the app, they are presented with an initial registration screen, which provides an interface for entering basic information such as name, age, and gender.

[2279] User: When launching the app for the first time, users enter basic information such as their name, age, and gender, and then enter medical information such as chronic illnesses and allergies.

[2280] Server: Receives the entered basic information and medical information and stores it in a database. Creates a user profile based on the stored information.

[2281] Creating a User Profile

[2282] Server: Based on the input information, a personalized user profile is generated, taking into account the user's dietary preferences and lifestyle.

[2283] Terminal: Provides an interface that displays customized questions based on the generated user profile, designed to gather information about dietary preferences and specific foods.

[2284] Users: Answer customized questions and enter more detailed information, which further refines their profile.

[2285] Menu suggestions

[2286] Server: Using an AI engine, it generates an appropriate medical meal menu based on the user profile. The generated menu is customized based on the user's health condition and dietary preferences.

[2287] Terminal: Provides an interface that displays the generated menu to the user and accepts selections.

[2288] User: Selects and confirms the desired menu. The selection information is sent to the server and recorded in the user profile.

[2289] emotion recognition

[2290] Device: Monitors the user's facial expressions, voice, etc., and uses an emotion recognition engine to analyze the user's current emotions.

[2291] Server: Receives the analysis results and stores the user's emotional data in a database, allowing the system to modify menu suggestions based on the user's psychological state.

[2292] Feedback and implementation record

[2293] Server: Periodically records the user's menu selection information and execution status, and accumulates feedback and emotion data.

[2294] Device: Provides regular notifications to users and prompts them to input their progress and emotional feedback.

[2295] User: Enters the situation, impressions, changes in physical condition, and emotions regarding the menu that was actually cooked or eaten. For example, reports on physical condition and psychological changes after eating.

[2296] Data storage and analysis

[2297] Server: Analyzes the user's health status trends based on accumulated performance data, feedback data, and emotional data. This can be reflected in future menu suggestions.

[2298] Terminal: The analysis results are notified to the user and displayed as reference information for the next menu suggestion.

[2299] Specific examples

[2300] For example, consider a 65-year-old senior citizen using this system. As an initial setup, the user installs the app and enters basic and medical information. This information is saved by the server and a user profile is generated. The user then answers customized questions to create a detailed profile.

[2301] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile and displays it on the device. The user selects and confirms the desired menu. At the same time, an emotion recognition engine analyzes the user's emotions and customizes the menu suggestions based on that data.

[2302] After eating, the user inputs their emotions and changes in physical condition, and the server analyzes and stores the data. The analysis results are reflected in the next menu suggestion and are notified to the user via their device.

[2303] This system allows users to receive personalized medical diets and feedback at home, enabling them to efficiently manage their health. It also utilizes emotional data to provide support appropriate to the user's psychological state.

[2304] The processing flow will be explained below.

[2305] Step 1:

[2306] When a device launches an app, it loads the necessary libraries and datasets, including the user interface, database connection modules, AI engine, emotion recognition engine, etc.

[2307] Step 2:

[2308] The device displays the initial registration screen to the user, providing an interface for entering basic information such as name, age, and gender.

[2309] Step 3:

[2310] The user enters basic information such as name, age, and gender, which is later used to create a user profile.

[2311] Step 4:

[2312] The server receives the basic information entered and stores it in a database, which is managed in a secure environment.

[2313] Step 5:

[2314] The device then displays a medical information entry screen, which provides an interface for entering detailed medical information such as chronic illnesses, allergies, and current health conditions.

[2315] Step 6:

[2316] The user enters medical information such as chronic illnesses, allergies, and current health conditions.

[2317] Step 7:

[2318] The server receives the entered medical information and stores it in a database, which gathers the information needed to create a user profile.

[2319] Step 8:

[2320] The server uses basic and medical information to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[2321] Step 9:

[2322] The device presents the user with customized questions based on their user profile, including information about dietary preferences and specific foods.

[2323] Step 10:

[2324] Users answer customization questions and enter further details, such as whether they want to avoid certain foods or what foods they prefer.

[2325] Step 11:

[2326] The server receives the user's response and updates the user profile, which is always updated with the latest information.

[2327] Step 12:

[2328] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, and the menu is customized based on the user's health condition and dietary preferences.

[2329] Step 13:

[2330] The terminal displays the generated menu on the user's screen, and the user can select the desired menu from multiple options.

[2331] Step 14:

[2332] The user selects and confirms the desired menu item, and this information is sent to the system.

[2333] Step 15:

[2334] The server receives the user's selection information and records it in a database, which is then used for feedback and analysis.

[2335] Step 16:

[2336] The device monitors the user's facial expressions and voice in real time and uses an emotion recognition engine to analyze their current emotions.

[2337] Step 17:

[2338] The server receives the analysis results from the emotion recognition engine and stores the user's emotion data in a database, which is used to improve menu suggestions.

[2339] Step 18:

[2340] The server periodically checks the user's progress and sends notifications, including reminders and progress checks.

[2341] Step 19:

[2342] The device periodically displays a status confirmation message to the user, allowing the user to enter information accordingly.

[2343] Step 20:

[2344] Users can input the status of the meal they have actually cooked and eaten, their impressions, changes in their physical condition, and their emotions. For example, they can report changes in blood sugar levels and psychological effects after eating.

[2345] Step 21:

[2346] The server receives user feedback and emotion data and stores it in a database. The collected data is reflected in future menu suggestions.

[2347] Step 22:

[2348] The server analyzes the user's health trends based on the collected data, including the effects of the foods consumed and their psychological impact.

[2349] Step 23:

[2350] The device will notify the user of the analysis results and display them as reference information for the next meal plan, allowing the user to plan their next meal based on this information.

[2351] Step 24:

[2352] Users can check the analysis results and use them to help them make better choices for their next meal, leading to better health.

[2353] Example 2

[2354] 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."

[2355] Conventional medical food delivery systems make it difficult for elderly people and patients who cannot be hospitalized to consume appropriate medical food at home and maintain and improve their health. Furthermore, they do not take into account the user's psychological state and do not provide individual dietary advice, which results in a poor overall user experience. Furthermore, they are unable to fully utilize user feedback and emotional data, which means they cannot be reflected in the next menu recommendation.

[2356] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2357] In this invention, the server includes a means for inputting a user's basic information and medical information, a means for receiving the input information and storing it in a database, a means for generating a user profile based on the stored information, a means for analyzing the user's emotions, a means for revising menu suggestions based on the analysis results, a means for periodically checking and notifying the user's progress, a means for collecting and storing user feedback, and a means for analyzing the collected data and notifying the user of the results. This enables personalized dietary advice to be provided based on the user's psychological state, improving the overall user experience. Furthermore, the feedback and emotional data can be reflected in the next menu suggestion, allowing medical diets to be suggested that are appropriate for the user's health and psychological state.

[2358] "Basic user information" refers to basic information such as name, age, and gender that is necessary to identify and individually respond to users.

[2359] "Medical information" refers to medical information necessary for health management and dietary suggestions, such as the user's chronic illnesses, allergies, and medical history.

[2360] "Database" refers to an information storage system for storing and managing a user's basic information, medical information, selection information, and feedback information.

[2361] A "user profile" is a data set generated based on a user's basic information and medical information, and is used to make individually appropriate menu suggestions.

[2362] A "medical meal menu" is a meal plan customized based on a user's health status and dietary preferences.

[2363] "Means for analyzing emotions" refers to technology that analyzes the user's facial expressions, voice, etc., to evaluate their current emotional state.

[2364] "Feedback" is information provided by the user regarding their impressions after eating and changes in their physical condition.

[2365] "Implementation status" is information about whether the user actually ate the suggested menu item.

[2366] The "analysis results" are information about the trends in the user's health and psychological state derived from the collected data.

[2367] This invention adds emotion recognition functionality to a system that helps elderly people and patients who cannot be hospitalized to consume appropriate medical diets at home and maintain and improve their health. The emotion recognition functionality aims to provide personalized dietary advice based on the user's psychological state and improve the overall user experience.

[2368] System configuration and operation

[2369] Initial Setup

[2370] The server loads the necessary libraries and datasets when the application starts, including the user interface, database connection module, AI engine, emotion recognition engine, etc. Specifically, it uses software libraries such as OpenFace, EmotionAPI, and TensorFlow.

[2371] The device displays an initial registration screen to the user who has installed the app. The initial registration screen provides an interface for the user to enter basic information such as name, age, and gender.

[2372] When users launch the app for the first time, they enter their basic information and medical information (such as chronic illnesses and allergies).

[2373] The server receives the basic and medical information entered by the user and stores it in a database, which automatically generates an individual user profile.

[2374] Creating a User Profile

[2375] The server uses the information entered to create a personalized user profile, which also takes into account the user's dietary preferences and lifestyle.

[2376] Based on the generated user profile, the device provides an interface displaying customized questions, allowing for more detailed information to be gathered about the user's dietary preferences and specific foods.

[2377] Users answer customized questions and provide additional detailed information, which further refines the user profile.

[2378] Menu suggestions

[2379] The server uses an AI engine to generate an appropriate medical meal menu based on the user profile, which is customized according to the user's health condition and dietary preferences.

[2380] The terminal provides an interface for displaying the generated menu to the user and accepting selections.

[2381] The user selects and confirms the desired menu, and the selection is sent to the server and recorded in the user profile.

[2382] emotion recognition

[2383] The device is equipped with an emotion recognition engine that analyzes the user's facial expressions and voice, allowing it to assess the user's current emotional state in real time.

[2384] The server receives the analyzed emotion data and stores it in a database, which can then modify the next menu suggestion to better suit the user's psychological state.

[2385] Feedback and implementation record

[2386] The server periodically records the user's menu selection information and implementation status, accumulates feedback data and emotion data, and periodically notifies the user to prompt input of implementation status and emotion feedback.

[2387] Users input the status of the meal they actually cooked and ate, their impressions, changes in their physical condition, and their emotions. For example, they can provide feedback such as, "I feel better after eating today."

[2388] Data storage and analysis

[2389] The server analyzes the user's health status based on the accumulated data on the user's progress, feedback, and emotions, and can then reflect this in the next menu recommendation.

[2390] The terminal notifies the user of the analysis results and displays them as reference information for suggesting the next menu item.

[2391] Examples and prompts

[2392] For example, if a 65-year-old male uses this system, he or she will follow the steps below: First, he or she installs the app and enters information such as name, age, gender, and chronic illnesses (diabetes, allergies, etc.), which creates an individual user profile.

[2393] Next, a detailed profile is created by answering additional questions about the user's dietary preferences and specific foods. Based on this profile, the server uses an AI engine to generate an appropriate medical meal menu and displays it on the device. The user can then select what they want from the menu.

[2394] After eating, the emotion recognition engine analyzes the user's current emotional state, and the data is sent to the server. The user also enters their thoughts about the meal and any changes in their physical condition, and this data is stored for analysis.

[2395] The analysis results are reflected in the next menu suggestion and notified to the user, allowing for more personalized and healthy meal suggestions.

[2396] Example prompt for generative AI model:

[2397] "A 65-year-old man with chronic conditions of diabetes and high blood pressure. His favorite foods are chicken and broccoli. Please suggest a daily meal menu."

[2398] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2399] Step 1:

[2400] The server loads the necessary libraries and datasets when the application starts, including software libraries such as OpenFace, EmotionAPI, and TensorFlow. Loading these prepares the entire system for operation.

[2401] Input: Application launch event

[2402] Output: Library and dataset loading completion status

[2403] Step 2:

[2404] The device displays an initial registration screen to users who have installed the app. This screen provides an interface for entering basic information such as name, age, and gender. The user interface is created using HTML or React Native.

[2405] Input: User's first launch of the app

[2406] Output: Display of initial registration screen ...

Claims

1. a means for inputting basic information and medical information of the user; means for receiving the input information and storing it in a database; means for generating a user profile based on the stored information; A means for generating an appropriate medical diet menu based on a user profile; means for displaying the generated menu to a user and accepting a selection; means for recording user selection information; A means for periodically checking and notifying the user of their implementation status; a means for collecting and storing user feedback; means for analyzing the collected data and notifying the user of the results; A system including:

2. 10. The system of claim 1, further comprising means for modifying subsequent menu suggestions based on user feedback.

3. The system of claim 1 further comprising means for assessing and reporting a user's health status based on the collected data.

Images