System

Abstract

A system is provided.SOLUTION: A system comprising: means for providing an interface through which a user can be consulted about emotional depression or anxiety at any time; communication means for transmitting the user's input to a server in real time; an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response; display means for providing the generated response to the user; a matching engine for analyzing the user's consultation history and matching with other users having the same concern; and escalation means for escalating to an expert when the consultation content is serious.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern society, many people suffer from emotional depression and anxiety, and managing and caring for them has become a major issue. However, traditional mental health care services are often difficult to access and offer immediate support. Consulting with a specialist can be particularly difficult during late night or early morning hours, and users may not receive appropriate support. Furthermore, connecting with others who share the same concerns can help people feel empathy and support, but the current system for doing so is insufficient. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention provides a system that includes a means for providing an interface that allows users to consult about depression or anxiety at any time, a communication means for transmitting user input to a server in real time, and an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response. Furthermore, the system includes a display means for providing the generated response to the user and a matching engine for analyzing the user's consultation history and matching the user with other users who have the same concerns, thereby promoting empathy and support. Furthermore, if the consultation content is deemed serious, the system provides appropriate counseling using an escalation means for escalating the consultation to a specialist. When escalating to a specialist, the system includes a means for using a medical record automatically generated based on the consultation content, ensuring an appropriate and prompt response. Furthermore, the system allows users to choose between a free or paid freemium model, and includes a payment means for processing additional fees for paid services, allowing users to receive the advanced care they need.

[0006] 1. An "interface" is a screen or means by which a user interacts with a system.

[0007] 2. "Communication Method" means the data transmission method or technology used to transmit User Input to the Server.

[0008] 3. An "artificial intelligence engine" is an algorithm or software that analyzes data it receives and automatically generates an appropriate response.

[0009] 4. "Display means" means a means for displaying generated responses or information on a screen so that the user can check them.

[0010] 5. A "matching engine" is a system that analyzes a user's consultation history and characteristics to search for and connect with other suitable users.

[0011] 6. "Escalation procedures" are mechanisms for transferring serious problems to experts and encouraging appropriate responses when they are discovered.

[0012] 7. "Medical Record" refers to a detailed record or report that is automatically generated based on the user's consultation.

[0013] 8. "Payment Method" means a system or method for processing payments when a User uses a Paid Service. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The embodiment of the present invention is a comprehensive system that allows users to express their depression and anxiety and receive appropriate support. The system has the following main functions:

[0036] 1. User authentication and login process

[0037] The user starts the application, enters their username and password on the login screen, and clicks the login button. The device sends this authentication information to the server, which then authenticates the user by checking it against a database. If authentication is successful, the user is taken to the main screen and can use the system.

[0038] 2. 24-hour support via AI chatbots

[0039] The user enters their concerns about depression or anxiety on the chat screen and sends them. The device then sends the information to a server, where an artificial intelligence engine analyzes the received information and generates an appropriate response. The generated response is provided to the user in real time, allowing them to express their feelings and receive support through dialogue.

[0040] 3. Empathy and matching process

[0041] The server analyzes the user's consultation history and current consultation content, and searches a database for other users with the same concerns. A matching engine is used to make it easier for users to connect with other users in similar situations, allowing them to receive empathy and support. The matching results are notified to the user via their device, and they can start chatting with other users if necessary.

[0042] 4. Collaboration and response with experts

[0043] If the problem is deemed serious, the server will escalate the issue to a specialist using an automatically generated medical record based on the consultation details. The specialist will then provide appropriate counseling based on the information transferred to them. The device will then display feedback and advice from the specialist to the user in real time, allowing the user to receive the support they need.

[0044] 5. Freemium model vs. paid services

[0045] Users can choose between free and paid services within the application. Users who wish to use paid services enter their payment information on the payment screen and send it to the server via their device. The server then confirms the payment and adds paid service authorization to the user's account. Paid services allow users to receive advanced mental health care.

[0046] The above is an embodiment of the present invention. This system provides users with easily accessible mental health care and provides specific means for regaining emotional composure.

[0047] The processing flow will be explained below.

[0048] Step 1:

[0049] The user launches the application. The user taps the application icon to launch it, and the login screen is displayed.

[0050] Step 2:

[0051] The user enters their login information (username and password) and clicks the Login button.

[0052] Step 3:

[0053] The device sends the login information to the server. The device encrypts the username and password and sends them to the server.

[0054] Step 4:

[0055] The server authenticates the user against a database. The server checks the login information it receives against its database to see if there is a match.

[0056] Step 5:

[0057] The server returns the authentication result to the terminal. If the authentication is successful, the server notifies the terminal of the success, and if the authentication is unsuccessful, it returns an error message.

[0058] Step 6:

[0059] The device notifies the user of the authentication result. If authentication is successful, the device displays the main screen, otherwise it displays an error message.

[0060] Step 7:

[0061] Users access the chat interface from the main screen and enter their concerns about depression or anxiety.

[0062] Step 8:

[0063] The terminal transmits the input consultation content to the server.

[0064] Step 9:

[0065] The server receives the consultation content and passes it to the AI ​​engine, which analyzes the content and generates an appropriate response.

[0066] Step 10:

[0067] The server sends the generated response to the terminal.

[0068] Step 11:

[0069] The device will display the response to the user, who will then be able to see the AI's response in the chat window.

[0070] Step 12:

[0071] The server analyzes the user's consultation history and uses a matching engine to search for other users with the same concerns.

[0072] Step 13:

[0073] The server sends the matching results to the device, which displays them to the user, who can then select the option to chat with other users who share their interests.

[0074] Step 14:

[0075] If the consultation is deemed serious, the server will automatically create a medical record based on the consultation content and escalate the case to a specialist.

[0076] Step 15:

[0077] The expert reviews the chart and sends feedback to the server.

[0078] Step 16:

[0079] The server transfers the feedback from the expert to the device, which then displays it to the user, allowing the user to review the expert's advice and receive the necessary support.

[0080] Step 17:

[0081] If the user selects a paid service, the terminal displays a payment screen and the user enters payment information.

[0082] Step 18:

[0083] The terminal sends the payment information to the server, which verifies the payment via a payment gateway.

[0084] Step 19:

[0085] The server notifies the terminal whether the payment was successful or not, and the terminal displays the result to the user. If successful, the paid service becomes available.

[0086] These are the processing steps of the system, which allows users to vent their feelings and receive support from experts if necessary.

[0087] Example 1

[0088] 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."

[0089] In recent years, mental health problems have been on the rise, creating a need for systems that allow users to easily seek advice about depression and anxiety at any time. However, current systems are inadequate in terms of real-time response, expert response, and empathy matching with other users. In particular, they do not address the needs of users who require smooth escalation to an expert when the issue is serious, or payment for paid services. The present invention aims to solve these problems.

[0090] 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.

[0091] In this invention, the server includes: means for providing an interface that allows users to consult about depression or anxiety at any time; communication means for transmitting user input to the server in real time; an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response; display means for providing the generated response to the user; a matching engine for analyzing the user's consultation history and matching the user with other users who have the same problem; escalation means for escalating the consultation content to a specialist if the consultation content is serious; means for executing user authentication and login process; means for allowing the user to select between a free or paid freemium model; and payment means for processing additional fees for paid services. This allows users to easily consult about their emotions, receive sympathy, and, if necessary, receive professional support.

[0092] "User" refers to any individual or organization that uses this system.

[0093] "Interface" refers to the screen and input means through which a user interacts with a system.

[0094] "Communication means" refers to the devices and protocols that transmit user input to the server in real time.

[0095] "Artificial intelligence engine" refers to software or algorithms that analyze incoming inquiries and generate appropriate responses.

[0096] "Display means" refers to a device or system that provides the generated response to the user visually or audibly.

[0097] A "matching engine" refers to an algorithm or software that analyzes a user's consultation history and connects them with other users who have the same concerns.

[0098] "Escalation mechanisms" refer to mechanisms and processes for transferring serious issues to specialists.

[0099] "User authentication" refers to the process for verifying a user's identity and controlling access to a system.

[0100] "Login process" refers to the authentication steps a user goes through to access a system.

[0101] The "freemium model" refers to a business model that combines free and paid services.

[0102] "Payment Method" means an electronic payment system for processing fees for Paid Services.

[0103] MODE FOR CARRYING OUT THE INVENTION

[0104] The present invention relates to a comprehensive system that allows users to express their depression and anxiety and receive appropriate support, with easy user access and real-time response capabilities.

[0105] User authentication and login process

[0106] A user starts an application and enters their username and password on the login screen. The device sends this authentication information to the server, which then authenticates the user by checking it against a database (e.g., MySQL). If authentication is successful, the server sends the result back to the device, which then redirects the user to the main screen.

[0107] 24-hour support by AI chatbot

[0108] The user enters their concerns about depression or anxiety into the chat screen and sends them. The device then sends the information to the server, which uses an artificial intelligence engine (e.g., OpenAI GPT-3) to analyze the content and generate an appropriate response. The generated response is then sent back to the device, which displays it to the user in real time.

[0109] The empathy and matching process

[0110] The server analyzes the user's consultation history and current consultation content. Using a matching engine (e.g., Elasticsearch), it searches the database for other users with the same concerns and finds users with common interests. The server notifies the device of the matching results, and the device notifies the user. The user receives the notification and can start chatting with other users if necessary.

[0111] Collaboration and response with experts

[0112] The server automatically creates a medical record based on the consultation content that is judged to be a serious problem and escalates it to an expert. The expert then provides counseling based on the medical record. The terminal displays feedback and advice from the expert to the user in real time.

[0113] Freemium model vs. paid services

[0114] Users can choose between free and paid services within the application. Users who wish to use paid services enter their payment information on the payment screen and send it to the server via their device. The server then confirms the payment and adds the paid service authorization to the user's account. By using the paid service, users can receive advanced mental health care.

[0115] Examples of specific examples and prompts

[0116] 1. When a user logs in to the app, they enter "example_user" and "password123" and click the Login button.

[0117] 2. The device sends this information to the server, which then performs authentication.

[0118] 3. The user types, "I've been stressed out lately and can't sleep," into the chat screen and sends it.

[0119] 4. The device sends this information to a server, and the GPT-3 artificial intelligence engine generates a response: "That's tough. Tell me more about what's causing you stress."

[0120] 5. The terminal displays the response to the user.

[0121] 6. The server searches for other users with similar problems and notifies the user via their device, "There is another user with the same problem. Would you like to connect?"

[0122] Example prompt sentence:

[0123] Chatbot prompt: "Generate an appropriate response to the user's message: 'I've been feeling stressed lately and can't sleep.'"

[0124] Matching engine prompt: "Based on the user's complaint 'I'm feeling increasingly stressed,' find other users with similar concerns."

[0125] The above is an embodiment of the present invention. This system allows users to receive prompt and appropriate mental health care and provides specific means for regaining emotional composure.

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Step 1:

[0128] The user starts the application and enters their username and password on the login screen. The entered information is in the form of a username and password. The device sends this authentication information to the server. The server receives it and verifies the username and password against a database to perform authentication. If authentication is successful, the server returns a success message to the device, and the device transitions the user to the main screen.

[0129] Specific behavior:

[0130] The user enters the username "example_user" and password "example_pass" and clicks the Login button.

[0131] The terminal transmits the entered authentication information to the server.

[0132] The server checks the information against the database and sends a message to the terminal indicating successful authentication.

[0133] The device will transition to the main screen.

[0134] Step 2:

[0135] The user moves to the chat screen, enters the content of their consultation, and sends it. The entered content is in text format as the user's consultation content. The device sends this input content to the server. The server receives it and passes it to the artificial intelligence engine. The artificial intelligence engine analyzes the consultation content and generates an appropriate response. The generated response is a response message in text format. The server sends the generated response to the device, which displays it to the user.

[0136] Specific behavior:

[0137] The user types, "I've been feeling stressed lately and can't sleep," and clicks the send button.

[0138] The device sends the input to the server.

[0139] The server requests an analysis from an artificial intelligence engine (e.g., GPT-3) and receives a response message.

[0140] The server sends a response message to the terminal, which displays it to the user.

[0141] Step 3:

[0142] Based on the user's consultation content and past consultation history, the server begins the process of searching for other users who share the same concerns. The input data is text data of the user's current and past consultation content. The server passes this data to a matching engine to search for users with similar consultation content. The matching engine outputs the results and returns them to the server. The output data is a list of users with similar consultation content. The server sends the results to the terminal, which then displays matching suggestions to the user.

[0143] Specific behavior:

[0144] The server analyzes the user's current and past consultations.

[0145] The server passes the data to a matching engine (e.g. Elasticsearch) to search for other users with similar concerns.

[0146] The matching engine generates the results and returns them to the server.

[0147] The server sends the matching results to the device, and the device notifies the user, "There is a user with the same problem. Would you like to connect?"

[0148] Step 4:

[0149] If the consultation is serious, the server starts the process of escalating it to an expert. The input data is text data of the serious consultation content. The server creates an automatically generated medical record and sends it to the expert. The medical record data includes a summary of the consultation content and related information. The expert receives the medical record and provides counseling. The output data is text data of feedback and advice from the expert. The server receives this and sends it to the terminal, which displays it to the user.

[0150] Specific behavior:

[0151] The server analyzes the seriousness of the consultation and creates a medical record using an automatic medical record generation function.

[0152] The server sends the medical record to the specialist.

[0153] The expert provides counseling based on the medical records and returns feedback to the server.

[0154] The server sends feedback to the device, which displays it to the user.

[0155] Step 5:

[0156] If the user wishes to use a paid service, the payment process is initiated. The input data is the user's payment information and the selected paid service. The terminal sends this information to the server. The server confirms the payment via the payment processing service. The output data is a confirmation message that the payment is complete. The server notifies the terminal that the payment is successful, and the terminal adds authorization for the paid service to the user's account.

[0157] Specific behavior:

[0158] The user selects the paid service "High-end Counseling" and enters payment information.

[0159] The terminal sends the payment information to the server.

[0160] The server verifies the payment through a payment processing service (e.g., Stripe).

[0161] The server notifies the terminal that the payment has been completed, and the terminal adds authorization for the paid service to the user account.

[0162] The device notifies the user, "Advanced counseling is available."

[0163] (Application example 1)

[0164] 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."

[0165] In recent years, the number of people experiencing stress and anxiety has increased, making mental health care more important than ever. However, many people are unable to access appropriate support due to time and financial constraints, and are therefore unable to consult with a specialist. Furthermore, existing mental health support tools lack the functionality to provide optimal content tailored to each individual user's emotional state. Therefore, there is a need for a system that allows users to easily seek advice about their depression or anxiety, and that can provide optimal content tailored to their emotional state.

[0166] 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.

[0167] In this invention, the server includes means for providing an interface that allows users to consult about depression or anxiety at any time, communication means for transmitting user input to the server in real time, an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response, display means for providing the generated response to the user, a matching engine for analyzing the user's consultation history and matching with other users who have the same problem, escalation means for escalating the consultation to a specialist if the consultation content is serious, and content recommendation means for recommending optimal content based on the user's emotional state. This allows users to easily receive appropriate mental health care and regain emotional composure through optimal content tailored to their emotional state at the time.

[0168] A "user" is an individual who uses the system to discuss feelings of depression or anxiety.

[0169] An "interface" is a screen or input device through which a user inputs their feelings of depression or anxiety.

[0170] "Communication means" refers to a host device or internet connection for transmitting user input to a server in real time.

[0171] The "artificial intelligence engine" is an algorithm that analyzes the content of the consultation received and generates an appropriate response.

[0172] "Display means" refers to a display or mobile screen for providing the generated response to the user in real time.

[0173] The "matching engine" is an algorithm that analyzes a user's consultation history and connects them with other users who have the same concerns.

[0174] "Escalation means" refers to communication devices or software functions that transfer information to a specialist when the consultation content is serious.

[0175] A "content recommendation method" is an algorithm or system that recommends optimal content based on the user's emotional state.

[0176] To implement this invention, we will build a system that allows users to easily receive mental health care. The main components include a user interface, communication means, an artificial intelligence engine, display means, a matching engine, escalation means, and content recommendation means.

[0177] First, the user interface provides a screen and input device that allows users to input their feelings of depression and anxiety. This interface is implemented as a smartphone application. The data entered by the user is sent to a server in real time via a communication means. An internet connection is required for this communication.

[0178] The server analyzes the received user's inquiry using an AI engine and generates an appropriate response. This AI engine implements a model for sentiment analysis using Hugging Face's Transformers library. The analyzed results are provided to the user via a display means, which can be a smartphone display or a mobile screen.

[0179] The server also has a matching engine that analyzes the user's consultation history and matches them with other users who have the same concerns. This matching engine searches the database for users with similar concerns and helps them support each other.

[0180] Furthermore, if the consultation content is serious, the information is transferred to a specialist using an escalation means, which may include a communication device or a dedicated software function. Once the information is escalated to the specialist, counseling is provided based on the automatically generated medical record.

[0181] Finally, the server has a content recommendation mechanism that recommends optimal content based on the user's emotional state. This content could include relaxing music, guided meditations, videos, etc. This allows users to receive optimal support tailored to their emotional state at any given time. This recommendation algorithm is also implemented using Hugging Face's library.

[0182] For example, if a user types, "I'm feeling really down today," the sentiment analysis model will detect the negative emotion and respond with, "I understand, and I'll provide you with specific support." It will also display links to relaxing music and guided meditations based on the user's emotional state.

[0183] Example prompt sentence:

[0184] "I am feeling very sad today."

[0185] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0186] Step 1:

[0187] Users input their feelings of depression and anxiety through a smartphone interface. This input is in text format, and the input data includes sentences such as "I'm feeling very depressed today."

[0188] Input: Text data showing feelings of depression and anxiety

[0189] Output: Sends input data to the server

[0190] Step 2:

[0191] The device uses a communication means to transmit text data entered by the user to a server in real time, and this communication requires an internet connection.

[0192] Input: Input data (text format)

[0193] Output: Data sent to the server

[0194] Step 3:

[0195] The server then analyzes the received user text data using an artificial intelligence engine, using Hugging Face's Transformers library for sentiment analysis.

[0196] Input: Data sent to the server (text format)

[0197] Data Processing: Sentiment Analysis

[0198] Output: Sentiment analysis result (e.g., negative)

[0199] Step 4:

[0200] The server generates an appropriate response based on the results of the sentiment analysis, and the generated response is provided to the user in real time.

[0201] Input: Sentiment analysis results

[0202] Data calculation: response generation

[0203] Output: Response (e.g. "I understand, I'll provide specific assistance.")

[0204] Step 5:

[0205] The terminal provides the response sent from the server to the user using a display means, such as the display of the smartphone.

[0206] Input: The response sent by the server

[0207] Output: Response displayed on the smartphone display

[0208] Step 6:

[0209] The server analyzes the user's consultation history and matches them with other users who have the same concerns. This process uses a matching engine to search a database for users with similar concerns.

[0210] Input: User's consultation history

[0211] Data processing: consultation history analysis, user matching

[0212] Output: Matching results

[0213] Step 7:

[0214] If the consultation is serious, the server uses an escalation method to transfer the consultation to a specialist, using an automatically generated medical record.

[0215] Input: Serious consultation content

[0216] Data calculation: medical record generation, transfer to specialist

[0217] Output: Specialist notification and medical records

[0218] Step 8:

[0219] The server uses content recommendation tools to recommend optimal content based on the user's emotional state, such as guided meditations or relaxing music.

[0220] Input: Sentiment analysis results

[0221] Data Computing: Content Recommendation

[0222] Output: Recommended content (e.g., a link to a guided meditation)

[0223] Example prompt sentence:

[0224] "I am feeling very sad today."

[0225] 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.

[0226] An embodiment of the present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. This system provides more advanced support by incorporating an emotion engine that recognizes the user's emotions.

[0227] System Configuration

[0228] 1. User authentication and login process

[0229] A user starts the application, enters their username and password on the login screen, and clicks the login button. The device sends the authentication information to the server, which then authenticates the user against the database. If authentication is successful, the user can access the main screen.

[0230] 2. 24-hour support via AI chatbots

[0231] Users input their feelings of depression or anxiety through a chat interface and send them to a server via their device. The server then passes the information to an artificial intelligence engine, which generates an appropriate response.

[0232] 3. Emotion Recognition by Emotion Engine

[0233] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state. Based on the emotional state recognized by the emotion engine, the AI ​​engine adjusts the response and provides more appropriate support.

[0234] 4. Viewing the Response

[0235] The server sends the generated response to the device, which displays it to the user, who can then view the AI's response in a chat window and continue the conversation.

[0236] 5. Empathy and matching process

[0237] The server analyzes the user's consultation history and the emotion recognition results of the emotion engine, and then uses the matching engine to search for other users with the same emotional state or concerns. The matching results are notified to the user via their device, allowing them to receive empathy and support from other users.

[0238] 6. Expert Collaboration and Escalation

[0239] If the consultation is deemed serious, the server automatically creates a medical record based on the user's consultation content and emotion recognition results, and escalates the consultation to an expert. The device receives feedback and advice from the expert and displays it to the user.

[0240] 7. Freemium model vs. paid services

[0241] Users can choose between free and paid services, and if they wish to use the paid service, they enter their payment information on the payment screen. The terminal then sends the payment information to the server, which then confirms the payment and adds paid service authorization to the user's account. Paid services allow users to receive advanced mental health care.

[0242] Specific examples

[0243] For example, if a user is overcome by anxiety at night, they can use this system to receive advice 24 hours a day. When the user types "I've been feeling anxious and can't sleep lately" into the chat interface, the device sends it to the server. The emotion engine in the server analyzes this input and recognizes the user's anxious feelings. At the same time, the artificial intelligence engine generates an appropriate response (e.g., "Can you tell me more about what is causing you anxiety?") and displays it to the user via the device. The emotion engine then analyzes the user's further input, and if it detects serious anxiety, the server automatically escalates the case to a specialist and provides professional support.

[0244] The system allows users to receive appropriate mental health care in real time, helping them regain emotional composure.

[0245] The processing flow will be explained below.

[0246] The embodiment of the present invention is detailed through the following process steps.

[0247] User authentication and login process

[0248] Step 1:

[0249] The user launches the application. The user taps the application icon to launch it, and the login screen is displayed.

[0250] Step 2:

[0251] The user enters their login information (username and password) and clicks the Login button.

[0252] Step 3:

[0253] The device sends the login information to the server. The device encrypts the username and password and sends them to the server.

[0254] Step 4:

[0255] The server authenticates the user against a database. The server checks the login information it receives against its database to see if there is a match.

[0256] Step 5:

[0257] The server returns the authentication result to the terminal. If the authentication is successful, the server notifies the terminal of the success, and if the authentication is unsuccessful, it returns an error message.

[0258] Step 6:

[0259] The device notifies the user of the authentication result. If authentication is successful, the device displays the main screen, otherwise it displays an error message.

[0260] AI chatbot and emotion engine response

[0261] Step 7:

[0262] Users access the chat interface from the main screen and enter their concerns about their depression or anxiety.

[0263] Step 8:

[0264] The terminal transmits the input consultation content to the server.

[0265] Step 9:

[0266] The server receives the consultation content and passes it to the AI ​​engine, which analyzes it and generates an appropriate response.

[0267] Step 10:

[0268] The server sends the generated response to the terminal.

[0269] Step 11:

[0270] The device will display the response to the user, who will then be able to see the AI's response in the chat window.

[0271] Emotion recognition by emotion engine

[0272] Step 12:

[0273] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state.

[0274] Step 13:

[0275] The artificial intelligence engine adjusts the response based on the emotional state recognized by the emotion engine.

[0276] Step 14:

[0277] The server sends the adjusted response to the terminal.

[0278] Step 15:

[0279] The device displays the adjusted response to the user, allowing the user to continue the interaction with better support.

[0280] The empathy and matching process

[0281] Step 16:

[0282] The server analyzes the user's consultation history and emotion recognition results, and uses a matching engine to search for other users with the same emotional state or concerns.

[0283] Step 17:

[0284] The server sends the matching results to the device, which displays them to the user, who can then select the option to chat with other users who share their interests.

[0285] Expert collaboration and escalation

[0286] Step 18:

[0287] If the consultation is deemed serious, the server automatically creates a medical record based on the consultation content and emotion recognition results, and escalates the case to a specialist.

[0288] Step 19:

[0289] The expert reviews the chart and sends feedback to the server.

[0290] Step 20:

[0291] The server transfers the feedback from the expert to the device, which then displays it to the user, allowing the user to review the expert's advice and receive the necessary support.

[0292] Freemium model vs. paid services

[0293] Step 21:

[0294] If the user selects a paid service, the terminal displays a payment screen and the user enters payment information.

[0295] Step 22:

[0296] The terminal sends the payment information to the server.

[0297] Step 23:

[0298] The server verifies the payment via a payment gateway.

[0299] Step 24:

[0300] The server notifies the terminal whether the payment was successful or not, and the terminal displays the result to the user. If successful, the paid service becomes available.

[0301] These are the specific processing steps of the system that combines the emotion engine, which allows users to receive appropriate mental health care in real time and helps them regain emotional composure.

[0302] Example 2

[0303] 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."

[0304] In modern society, the number of people suffering from depression and anxiety is increasing. Systems that provide prompt and appropriate support for these mental health issues are needed. In particular, there is a growing need for systems that respond to users in real time, 24 hours a day, recognize their emotional state, and provide appropriate responses. There is also a need for systems that empathize with and support other users with the same concerns, as well as rapid escalation to professional support. However, current systems have difficulty meeting all of these requirements, necessitating the creation of a more comprehensive mental health care system.

[0305] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for providing an interface that allows users to consult about depression or anxiety at any time, a communication means for transmitting user input to the server in real time, an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response, a display means for providing the generated response to the user, an emotion engine for recognizing the user's emotional state, a means for adjusting the response based on the recognized emotion, a matching engine for analyzing the user's consultation history and matching with other users who have the same concerns, and an escalation means for escalating the consultation content to a specialist if the consultation content is serious. This enables more effective mental health care for users by recognizing emotional fluctuations and providing appropriate responses. It also enables advanced support through empathy and support between users and rapid escalation to a specialist.

[0306] A "user" is someone who uses the system to seek advice about feelings of depression or anxiety.

[0307] The "interface" refers to the screen and operating environment that users use to discuss their feelings of depression and anxiety.

[0308] "Communication means" refers to the process or technology used to transmit user input information to the server in real time.

[0309] A "server" is a computer system that receives input information from a user and performs appropriate processing or responds.

[0310] An "artificial intelligence engine" is software or algorithms that analyze incoming inquiries and generate appropriate responses.

[0311] A "display means" is a screen or device that allows the user to see the generated response.

[0312] An "emotion engine" is software or algorithms that analyze user input and recognize emotional states.

[0313] The "means for adjusting the response based on the recognized emotion" refers to a process or technology for appropriately changing the response of the artificial intelligence engine based on the emotion recognized by the emotion engine.

[0314] "Consultation history" is a record of consultations that a user has previously made through the system.

[0315] A "matching engine" is software or an algorithm that analyzes a user's consultation history and emotions to find other users with the same concerns.

[0316] "Escalation methods" are processes and techniques for notifying a specialist of a serious issue.

[0317] An "expert" is someone who has specialized knowledge and skills in relation to the content of the user's inquiry and who can provide appropriate support and advice.

[0318] A "medical record" is a document or data that organizes information such as consultation details and emotional state and is passed on to a specialist.

[0319] The "freemium model" is a business model that provides basic services for free and offers additional paid services.

[0320] "Payment method" means the process or technology used to process payments when a user uses a paid service.

[0321] The present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. The following describes in detail the modes for carrying out the present invention.

[0322] This system mainly consists of three components: the user terminal, the server, and various engines (artificial intelligence engine, emotion engine, and matching engine).

[0323] User device:

[0324] User devices include PCs, smartphones, tablets, and other devices. Users launch the dedicated application, enter their username and password on the login screen, and click the login button to be authenticated. Once login is successful, they are redirected to the main screen. When users feel depressed or anxious, they can enter their concerns into the application's chat interface and send them.

[0325] server:

[0326] The server is a computer system that receives authentication information and consultation details from the user. The server connects to a database (e.g., MySQL) to authenticate the user. The server then passes the received consultation details to an artificial intelligence engine to generate an appropriate response. For example, OpenAI's GPT-3 is used as the artificial intelligence engine. The generated response is sent to the user's device, which then displays it to the user.

[0327] Emotion Engine:

[0328] The emotion engine is software that analyzes user input and recognizes the user's emotional state. Specifically, it uses tools such as IBM Watson Emotion Analysis. If a user types, "I've been feeling anxious and can't sleep lately," the emotion engine analyzes the content and recognizes the emotion "anxiety." Based on this result, the artificial intelligence engine adjusts the response.

[0329] Matching Engine:

[0330] The matching engine is software that analyzes the user's consultation history and emotion recognition results to find other users with the same concerns. For example, a tool like Elasticsearch is used. This allows users with similar emotional states and concerns to be connected, promoting empathy and support.

[0331] Escalation Methods:

[0332] The escalation method is a process that notifies an expert if the consultation content is judged to be serious. The server creates an automatically generated medical record based on the consultation content along with the analysis results of the emotion engine, and passes it to the expert. The medical record is generated in PDF format or other formats, allowing the expert to quickly evaluate and provide advice. When the expert sends feedback to the server, it is displayed on the user's device.

[0333] Freemium model:

[0334] Users can choose between free and paid services. If they wish to use paid services in addition to the basic free service, they enter their credit card information on the payment screen and complete the payment. The server uses a payment gateway (e.g., Stripe) and, once payment is confirmed, adds permission for the paid service to the user's account. Paid services allow users to receive more advanced mental health care.

[0335] Examples:

[0336] For example, if a user is unable to sleep at night due to anxiety, they can use the system to receive advice 24 hours a day. When the user types "I've been unable to sleep lately due to anxiety" into the chat interface and sends it, the device sends it to the server. The emotion engine in the server analyzes this input and recognizes the "emotion of anxiety," and the artificial intelligence engine generates a response such as "Please tell me more about what is causing your anxiety," and sends it to the device. The response is then displayed to the user. If more serious anxiety is detected, the server automatically escalates the situation to a specialist and provides professional support.

[0337] Example prompts to input to the generative AI model:

[0338] "Please explain how users can use this system to get 24 / 7 support if they feel unsafe at night."

[0339] Thus, the present invention is a system that provides users with comprehensive, real-time, and appropriate mental health care, and is capable of efficiently recognizing emotions, promoting empathy, and escalating professional support.

[0340] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0341] Step 1:

[0342] The user launches the application, enters their username and password on the login screen, and clicks the login button.

[0343] Specific behavior:

[0344] A user launches the application, enters the username "example_user" and password "password123" on the login screen, and clicks the Login button.

[0345] Input: Username and Password

[0346] Output: User credentials are sent from the device to the server.

[0347] Step 2:

[0348] The terminal sends authentication information to the server, which then compares it with a database to authenticate the user.

[0349] Specific behavior:

[0350] The device sends authentication information (username and password) to the server as an HTTP POST request.

[0351] Input: Username and Password

[0352] Data processing: The authentication information is checked against a database on the server (e.g., MySQL).

[0353] Output: If authentication is successful, the server returns the URL of the main page in the HTTP response.

[0354] Step 3:

[0355] If the server succeeds in the authentication, it sends information to the terminal to transition to the main screen.

[0356] Specific behavior:

[0357] The server sends the URL of the main screen to the device in an HTTP response.

[0358] Input: Authentication information match result

[0359] Output: The URL of the main screen is sent to the device.

[0360] Step 4:

[0361] The user types their feelings of depression and anxiety into a chat interface and clicks the send button.

[0362] Specific behavior:

[0363] The user types "I've been feeling anxious and can't sleep lately" into the chat window and presses the send button.

[0364] Input: User's inquiry

[0365] Output: The consultation content is sent from the terminal to the server.

[0366] Step 5:

[0367] The device sends the consultation details to the server, which then passes the details to the artificial intelligence engine.

[0368] Specific behavior:

[0369] The device sends the entered consultation details to the server, which then passes them to an artificial intelligence engine (e.g., OpenAI GPT-3).

[0370] Input: User's inquiry

[0371] Data processing: An artificial intelligence engine analyzes the consultation content and generates an appropriate response.

[0372] Output: The generated response is returned to the server.

[0373] Step 6:

[0374] The server sends the generated response to the terminal.

[0375] Specific behavior:

[0376] The server sends the response obtained from the artificial intelligence engine to the terminal.

[0377] Input: The generated response

[0378] Output: The response is sent to the terminal.

[0379] Step 7:

[0380] The terminal displays the response received from the server to the user.

[0381] Specific behavior:

[0382] The terminal displays the generated response in the chat window.

[0383] Input: Response from the server

[0384] Output: Response displayed in the chat window

[0385] Step 8:

[0386] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state.

[0387] Specific behavior:

[0388] The server sends the user's input information to an emotion engine (e.g., IBM Watson Emotion Analysis) to analyze the user's emotional state.

[0389] Input: User's inquiry

[0390] Data processing: The emotion engine analyzes the input information and recognizes the emotional state.

[0391] Output: Emotional state recognition result

[0392] Step 9:

[0393] The server receives the recognition results from the emotion engine and instructs the artificial intelligence engine to adjust the response.

[0394] Specific behavior:

[0395] The server instructs the artificial intelligence engine to adjust the response based on the recognition results of the emotion engine.

[0396] Input: Emotional state recognition results

[0397] Data processing: Adjusting responses based on recognition results.

[0398] Output: The adjusted response

[0399] Step 10:

[0400] The server sends the adjusted response to the user terminal.

[0401] Specific behavior:

[0402] The server sends the adjusted response to the user's device in an HTTP response.

[0403] Input: Adjusted response

[0404] Output: The adjusted response is sent to the terminal.

[0405] Step 11:

[0406] The user can see the tailored response in the chat window and continue the conversation.

[0407] Specific behavior:

[0408] The user sees the response displayed on the screen.

[0409] Input: Adjusted response

[0410] Output: User confirmation and next input

[0411] Step 12:

[0412] The server analyzes the user's consultation history and the emotion recognition results of the emotion engine, and uses a matching engine to search for other users who have the same emotional state or concerns.

[0413] Specific behavior:

[0414] The server retrieves the user's consultation history and emotion engine data from a database (e.g., MongoDB) and analyzes it.

[0415] Input: Consultation history and emotion recognition results

[0416] Data processing: Analyze using a matching engine (e.g. Elasticsearch).

[0417] Output: Matching results

[0418] Step 13:

[0419] The server notifies the user's device of the matching results, encouraging empathy and support between users.

[0420] Specific behavior:

[0421] The server sends the matching results to the user's device as an HTTP response and displays a notification.

[0422] Input: Matching results

[0423] Output: Notification of sympathy and support between users

[0424] Step 14:

[0425] If the consultation is serious, the server will automatically create a medical record and escalate the case to a specialist.

[0426] Specific behavior:

[0427] If the server detects serious anxiety from the analysis results of the emotion engine, it automatically generates a medical record (e.g., PDF format).

[0428] Input: Emotion recognition results and consultation details

[0429] Data processing: Automatically generate medical records and send them to specialists.

[0430] Output: Sending the medical record to a specialist

[0431] Step 15:

[0432] The expert sends feedback and advice back to the server, which the device displays to the user.

[0433] Specific behavior:

[0434] The expert sends feedback and advice back to the server, which then sends it to the user's device, which displays the advice.

[0435] Input: Expert feedback

[0436] Output: Advice displayed on the user's terminal

[0437] Step 16:

[0438] If the user selects a paid service, they enter payment information on the payment screen, and the terminal sends that information to the server.

[0439] Specific behavior:

[0440] The user clicks the "Upgrade to paid service" button and enters credit card information, etc. The terminal sends the payment information to the server.

[0441] Input: Payment Information

[0442] Output: Payment information is sent to the server.

[0443] Step 17:

[0444] The server verifies the payment information and, if successful, adds authorization for the paid service to the user account.

[0445] Specific behavior:

[0446] Your server verifies the payment with your payment gateway (e.g., Stripe) and, if successful, adds authorization for paid services to the user account.

[0447] Input: Payment Information

[0448] Data Processing: Verify payment information and update account permissions

[0449] Output: The paid service entitlement is added to the user account.

[0450] Step 18:

[0451] The server notifies the user terminal that a paid service has become available, and the terminal displays this to the user.

[0452] Specific behavior:

[0453] The server sends a notification to the user's device saying "Paid service is now available." The device displays it to the user.

[0454] Input: Permission update result for paid service

[0455] Output: A notification to the user about the paid service is displayed.

[0456] (Application example 2)

[0457] 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."

[0458] Conventional mental healthcare systems have difficulty recognizing users' emotional state and stress levels in real time and responding appropriately. Furthermore, in brick-and-mortar stores, if a store clerk is emotionally depressed or stressed, this can affect customer service and reduce customer satisfaction. Furthermore, when escalating serious consultations to specialists, many systems require users to take action themselves, and lack efficient methods such as automated medical record creation. To address these issues, a system with more advanced emotion recognition and stress monitoring capabilities is needed to strengthen mental health support in brick-and-mortar stores.

[0459] 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.

[0460] In this invention, the server includes: means for providing an interface that allows users to consult about depression or anxiety at any time; communication means for transmitting user input to the server in real time; an artificial intelligence engine that analyzes the received consultation content using specific analysis means and generates an appropriate response; display means for providing the generated response to the user; a matching engine that analyzes the user's consultation history and matches them with other users who have the same problem; escalation means for escalating the consultation to a specialist if the consultation content is serious; emotion recognition means for recognizing and analyzing the user's emotions in real time; means for adjusting and providing support according to the emotional state based on the emotion recognition means; means for monitoring the stress level of store staff; and means for providing customer support in a physical store. This enables the emotional states of users and store staff to be recognized in real time, enabling appropriate mental health care and customer support.

[0461] "User" refers to an individual who uses the mental health care system.

[0462] "Interface" refers to the screen and operation methods that provide users with a means to discuss their feelings of depression or anxiety.

[0463] "Communication Method" refers to the technology or protocol used to transmit user input to a server in real time.

[0464] "Artificial intelligence engine" refers to AI technology that analyzes the content of inquiries received and generates appropriate responses.

[0465] "Display means" refers to a display or screen on which the generated response is shown to the user.

[0466] A "matching engine" refers to technology that analyzes a user's consultation history and connects them with other users who have the same concerns.

[0467] "Escalation measures" refer to the means used to convey information to a specialist when the consultation is serious.

[0468] "Emotion recognition means" refers to technology for recognizing and analyzing a user's emotional state in real time.

[0469] "Means for monitoring stress levels" refers to technology for recognizing and monitoring the stress levels of store employees.

[0470] "Means of providing customer service support" refers to the techniques and methods that enable store staff to provide better service to customers in physical stores.

[0471] The present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. Specifically, the system includes an interface, communication means, an artificial intelligence engine, emotion recognition means, display means, a matching engine, and escalation means.

[0472] System Configuration

[0473] 1. Interface

[0474] The system provides a screen and operation method that allows users to consult about their depression or anxiety. Users input their concerns through this interface.

[0475] 2. Means of communication

[0476] User input is sent to the server in real time using HTTP or HTTPS as the communication protocol.

[0477] 3. Artificial Intelligence Engine

[0478] The system analyzes the received consultation content and generates an appropriate response using a generative AI model that uses deep learning technology.

[0479] 4. Emotion recognition means

[0480] It analyzes user input and recognizes their emotional state in real time. The emotion recognition engine uses natural language processing technology to analyze emotions.

[0481] 5. Display means

[0482] It has a display, usually a smartphone or tablet, to show the generated response to the user.

[0483] 6. Matching Engine

[0484] The system analyzes the user's consultation history and matches them with other users who have the same concerns. The matching algorithm uses collaborative filtering technology.

[0485] 7. Escalation Methods

[0486] If the consultation is serious, it will be escalated to a specialist. The server will automatically generate a medical record and send it to the specialist.

[0487] Specific examples

[0488] If a user experiences anxiety at night, they can use this system to receive advice 24 hours a day. When the user types "I've been feeling anxious and can't sleep lately" into the interface, the device sends this to the server. An emotion recognition system within the server analyzes this input and recognizes the user's feelings of anxiety. At the same time, an artificial intelligence engine generates an appropriate response (for example, "Could you tell me more about what is causing you anxiety?") and displays it to the user via the device.

[0489] Furthermore, the emotion recognition means continuously analyzes the user's input, and if it detects a high-stress state, the server automatically escalates to an expert and provides detailed feedback and advice.

[0490] Prompt Sentence Examples

[0491] User: "I've been so stressed lately I can't concentrate on my work."

[0492] AI chatbot: "Tell me what's causing you stress"

[0493] This example allows users to receive prompt and appropriate mental health care.

[0494] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0495] Step 1:

[0496] The user inputs the content of their problem into the interface. The input content is text information such as "I've been feeling anxious lately and can't sleep."

[0497] Step 2:

[0498] The terminal sends user input to the server in real time using HTTP or HTTPS as the communication protocol. The input data is sent to the server in JSON format.

[0499] Step 3:

[0500] The server analyzes the received input data. First, the server's emotion recognition means analyzes the text using natural language processing technology to recognize the user's emotional state in real time. Through this analysis, the emotion contained in the input is labeled as "anxiety."

[0501] Step 4:

[0502] The server generates an appropriate response using a generative AI model based on the emotion recognition results. The AI ​​engine generates a response (e.g., "Tell me more about what causes anxiety") according to the user's emotion label "anxiety."

[0503] Step 5:

[0504] The server sends the generated response to the device, which again encodes the response in JSON format and sends it to the device using the HTTP / S protocol.

[0505] Step 6:

[0506] The terminal provides the response received from the server to the user, specifically, by displaying the generated response message on the display of the terminal.

[0507] Step 7:

[0508] If the user enters the information again, the process is repeated. The emotion recognition means in the server continuously monitors and analyzes the user's emotional state, and if it detects a high stress state, the escalation means is activated. The server then sends the automatically generated medical record to a specialist to provide further support to the user.

[0509] Step 8:

[0510] The matching engine analyzes the user's consultation history. The server uses collaborative filtering technology to search for other users with the same concerns and make appropriate matches. The matching results are sent to the device and displayed on the screen.

[0511] Step 9:

[0512] When the consultation is escalated to an expert by the escalation means, the server receives feedback from the expert and provides it to the user. The terminal displays the feedback and provides the user with professional advice.

[0513] These steps can help users receive prompt and appropriate mental health care and promote emotional stability.

[0514] 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.

[0515] 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.

[0516] 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.

[0517] [Second embodiment]

[0518] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0519] 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.

[0520] 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).

[0521] 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.

[0522] 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.

[0523] 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).

[0524] 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.

[0525] 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.

[0526] 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.

[0527] 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.

[0528] 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.

[0529] 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."

[0530] The embodiment of the present invention is a comprehensive system that allows users to express their depression and anxiety and receive appropriate support. The system has the following main functions:

[0531] 1. User authentication and login process

[0532] The user starts the application, enters their username and password on the login screen, and clicks the login button. The device sends this authentication information to the server, which then authenticates the user by checking it against a database. If authentication is successful, the user is taken to the main screen and can use the system.

[0533] 2. 24-hour support via AI chatbots

[0534] The user enters their concerns about depression or anxiety on the chat screen and sends them. The device then sends the information to a server, where an artificial intelligence engine analyzes the received information and generates an appropriate response. The generated response is provided to the user in real time, allowing them to express their feelings and receive support through dialogue.

[0535] 3. Empathy and matching process

[0536] The server analyzes the user's consultation history and current consultation content, and searches a database for other users with the same concerns. A matching engine is used to make it easier for users to connect with other users in similar situations, allowing them to receive empathy and support. The matching results are notified to the user via their device, and they can start chatting with other users if necessary.

[0537] 4. Collaboration and response with experts

[0538] If the problem is deemed serious, the server will escalate the issue to a specialist using an automatically generated medical record based on the consultation details. The specialist will then provide appropriate counseling based on the information transferred to them. The device will then display feedback and advice from the specialist to the user in real time, allowing the user to receive the support they need.

[0539] 5. Freemium model vs. paid services

[0540] Users can choose between free and paid services within the application. Users who wish to use paid services enter their payment information on the payment screen and send it to the server via their device. The server then confirms the payment and adds paid service authorization to the user's account. Paid services allow users to receive advanced mental health care.

[0541] The above is an embodiment of the present invention. This system provides users with easily accessible mental health care and provides specific means for regaining emotional composure.

[0542] The processing flow will be explained below.

[0543] Step 1:

[0544] The user launches the application. The user taps the application icon to launch it, and the login screen is displayed.

[0545] Step 2:

[0546] The user enters their login information (username and password) and clicks the Login button.

[0547] Step 3:

[0548] The device sends the login information to the server. The device encrypts the username and password and sends them to the server.

[0549] Step 4:

[0550] The server authenticates the user against a database. The server checks the login information it receives against its database to see if there is a match.

[0551] Step 5:

[0552] The server returns the authentication result to the terminal. If the authentication is successful, the server notifies the terminal of the success, and if the authentication is unsuccessful, it returns an error message.

[0553] Step 6:

[0554] The device notifies the user of the authentication result. If authentication is successful, the device displays the main screen, otherwise it displays an error message.

[0555] Step 7:

[0556] Users access the chat interface from the main screen and enter their concerns about depression or anxiety.

[0557] Step 8:

[0558] The terminal transmits the input consultation content to the server.

[0559] Step 9:

[0560] The server receives the consultation content and passes it to the AI ​​engine, which analyzes the content and generates an appropriate response.

[0561] Step 10:

[0562] The server sends the generated response to the terminal.

[0563] Step 11:

[0564] The device will display the response to the user, who will then be able to see the AI's response in the chat window.

[0565] Step 12:

[0566] The server analyzes the user's consultation history and uses a matching engine to search for other users with the same concerns.

[0567] Step 13:

[0568] The server sends the matching results to the device, which displays them to the user, who can then select the option to chat with other users who share their interests.

[0569] Step 14:

[0570] If the consultation is deemed serious, the server will automatically create a medical record based on the consultation content and escalate the case to a specialist.

[0571] Step 15:

[0572] The expert reviews the chart and sends feedback to the server.

[0573] Step 16:

[0574] The server transfers the feedback from the expert to the device, which then displays it to the user, allowing the user to review the expert's advice and receive the necessary support.

[0575] Step 17:

[0576] If the user selects a paid service, the terminal displays a payment screen and the user enters payment information.

[0577] Step 18:

[0578] The terminal sends the payment information to the server, which verifies the payment via a payment gateway.

[0579] Step 19:

[0580] The server notifies the terminal whether the payment was successful or not, and the terminal displays the result to the user. If successful, the paid service becomes available.

[0581] These are the processing steps of the system, which allows users to vent their feelings and receive support from experts if necessary.

[0582] Example 1

[0583] 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."

[0584] In recent years, mental health problems have been on the rise, creating a need for systems that allow users to easily seek advice about depression and anxiety at any time. However, current systems are inadequate in terms of real-time response, expert response, and empathy matching with other users. In particular, they do not address the needs of users who require smooth escalation to an expert when the issue is serious, or payment for paid services. The present invention aims to solve these problems.

[0585] 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.

[0586] In this invention, the server includes: means for providing an interface that allows users to consult about depression or anxiety at any time; communication means for transmitting user input to the server in real time; an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response; display means for providing the generated response to the user; a matching engine for analyzing the user's consultation history and matching the user with other users who have the same problem; escalation means for escalating the consultation content to a specialist if the consultation content is serious; means for executing user authentication and login process; means for allowing the user to select between a free or paid freemium model; and payment means for processing additional fees for paid services. This allows users to easily consult about their emotions, receive sympathy, and, if necessary, receive professional support.

[0587] "User" refers to any individual or organization that uses this system.

[0588] "Interface" refers to the screen and input means through which a user interacts with a system.

[0589] "Communication means" refers to the devices and protocols that transmit user input to the server in real time.

[0590] "Artificial intelligence engine" refers to software or algorithms that analyze incoming inquiries and generate appropriate responses.

[0591] "Display means" refers to a device or system that provides the generated response to the user visually or audibly.

[0592] A "matching engine" refers to an algorithm or software that analyzes a user's consultation history and connects them with other users who have the same concerns.

[0593] "Escalation mechanisms" refer to mechanisms and processes for transferring serious issues to specialists.

[0594] "User authentication" refers to the process for verifying a user's identity and controlling access to a system.

[0595] "Login process" refers to the authentication steps a user goes through to access a system.

[0596] The "freemium model" refers to a business model that combines free and paid services.

[0597] "Payment Method" means an electronic payment system for processing fees for Paid Services.

[0598] MODE FOR CARRYING OUT THE INVENTION

[0599] The present invention relates to a comprehensive system that allows users to express their depression and anxiety and receive appropriate support, with easy user access and real-time response capabilities.

[0600] User authentication and login process

[0601] A user starts an application and enters their username and password on the login screen. The device sends this authentication information to the server, which then authenticates the user by checking it against a database (e.g., MySQL). If authentication is successful, the server sends the result back to the device, which then redirects the user to the main screen.

[0602] 24-hour support by AI chatbot

[0603] The user enters their concerns about depression or anxiety into the chat screen and sends them. The device then sends the information to the server, which uses an artificial intelligence engine (e.g., OpenAI GPT-3) to analyze the content and generate an appropriate response. The generated response is then sent back to the device, which displays it to the user in real time.

[0604] The empathy and matching process

[0605] The server analyzes the user's consultation history and current consultation content. Using a matching engine (e.g., Elasticsearch), it searches the database for other users with the same concerns and finds users with common interests. The server notifies the device of the matching results, and the device notifies the user. The user receives the notification and can start chatting with other users if necessary.

[0606] Collaboration and response with experts

[0607] The server automatically creates a medical record based on the consultation content that is judged to be a serious problem and escalates it to an expert. The expert then provides counseling based on the medical record. The terminal displays feedback and advice from the expert to the user in real time.

[0608] Freemium model vs. paid services

[0609] Users can choose between free and paid services within the application. Users who wish to use paid services enter their payment information on the payment screen and send it to the server via their device. The server then confirms the payment and adds the paid service authorization to the user's account. By using the paid service, users can receive advanced mental health care.

[0610] Examples of specific examples and prompts

[0611] 1. When a user logs in to the app, they enter "example_user" and "password123" and click the Login button.

[0612] 2. The device sends this information to the server, which then performs authentication.

[0613] 3. The user types, "I've been stressed out lately and can't sleep," into the chat screen and sends it.

[0614] 4. The device sends this information to a server, and the GPT-3 artificial intelligence engine generates a response: "That's tough. Tell me more about what's causing you stress."

[0615] 5. The terminal displays the response to the user.

[0616] 6. The server searches for other users with similar problems and notifies the user via their device, "There is another user with the same problem. Would you like to connect?"

[0617] Example prompt sentence:

[0618] Chatbot prompt: "Generate an appropriate response to the user's message: 'I've been feeling stressed lately and can't sleep.'"

[0619] Matching engine prompt: "Based on the user's complaint 'I'm feeling increasingly stressed,' find other users with similar concerns."

[0620] The above is an embodiment of the present invention. This system allows users to receive prompt and appropriate mental health care and provides specific means for regaining emotional composure.

[0621] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0622] Step 1:

[0623] The user starts the application and enters their username and password on the login screen. The entered information is in the form of a username and password. The device sends this authentication information to the server. The server receives it and verifies the username and password against a database to perform authentication. If authentication is successful, the server returns a success message to the device, and the device transitions the user to the main screen.

[0624] Specific behavior:

[0625] The user enters the username "example_user" and password "example_pass" and clicks the Login button.

[0626] The terminal transmits the entered authentication information to the server.

[0627] The server checks the information against the database and sends a message to the terminal indicating successful authentication.

[0628] The device will transition to the main screen.

[0629] Step 2:

[0630] The user moves to the chat screen, enters the content of their consultation, and sends it. The entered content is in text format as the user's consultation content. The device sends this input content to the server. The server receives it and passes it to the artificial intelligence engine. The artificial intelligence engine analyzes the consultation content and generates an appropriate response. The generated response is a response message in text format. The server sends the generated response to the device, which displays it to the user.

[0631] Specific behavior:

[0632] The user types, "I've been feeling stressed lately and can't sleep," and clicks the send button.

[0633] The device sends the input to the server.

[0634] The server requests an analysis from an artificial intelligence engine (e.g., GPT-3) and receives a response message.

[0635] The server sends a response message to the terminal, which displays it to the user.

[0636] Step 3:

[0637] Based on the user's consultation content and past consultation history, the server begins the process of searching for other users who share the same concerns. The input data is text data of the user's current and past consultation content. The server passes this data to a matching engine to search for users with similar consultation content. The matching engine outputs the results and returns them to the server. The output data is a list of users with similar consultation content. The server sends the results to the terminal, which then displays matching suggestions to the user.

[0638] Specific behavior:

[0639] The server analyzes the user's current and past consultations.

[0640] The server passes the data to a matching engine (e.g. Elasticsearch) to search for other users with similar concerns.

[0641] The matching engine generates the results and returns them to the server.

[0642] The server sends the matching results to the device, and the device notifies the user, "There is a user with the same problem. Would you like to connect?"

[0643] Step 4:

[0644] If the consultation is serious, the server starts the process of escalating it to an expert. The input data is text data of the serious consultation content. The server creates an automatically generated medical record and sends it to the expert. The medical record data includes a summary of the consultation content and related information. The expert receives the medical record and provides counseling. The output data is text data of feedback and advice from the expert. The server receives this and sends it to the terminal, which displays it to the user.

[0645] Specific behavior:

[0646] The server analyzes the seriousness of the consultation and creates a medical record using an automatic medical record generation function.

[0647] The server sends the medical record to the specialist.

[0648] The expert provides counseling based on the medical records and returns feedback to the server.

[0649] The server sends feedback to the device, which displays it to the user.

[0650] Step 5:

[0651] If the user wishes to use a paid service, the payment process is initiated. The input data is the user's payment information and the selected paid service. The terminal sends this information to the server. The server confirms the payment via the payment processing service. The output data is a confirmation message that the payment is complete. The server notifies the terminal that the payment is successful, and the terminal adds authorization for the paid service to the user's account.

[0652] Specific behavior:

[0653] The user selects the paid service "High-end Counseling" and enters payment information.

[0654] The terminal sends the payment information to the server.

[0655] The server verifies the payment through a payment processing service (e.g., Stripe).

[0656] The server notifies the terminal that the payment has been completed, and the terminal adds authorization for the paid service to the user account.

[0657] The device notifies the user, "Advanced counseling is available."

[0658] (Application example 1)

[0659] 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."

[0660] In recent years, the number of people experiencing stress and anxiety has increased, making mental health care more important than ever. However, many people are unable to access appropriate support due to time and financial constraints, and are therefore unable to consult with a specialist. Furthermore, existing mental health support tools lack the functionality to provide optimal content tailored to each individual user's emotional state. Therefore, there is a need for a system that allows users to easily seek advice about their depression or anxiety, and that can provide optimal content tailored to their emotional state.

[0661] 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.

[0662] In this invention, the server includes means for providing an interface that allows users to consult about depression or anxiety at any time, communication means for transmitting user input to the server in real time, an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response, display means for providing the generated response to the user, a matching engine for analyzing the user's consultation history and matching with other users who have the same problem, escalation means for escalating the consultation to a specialist if the consultation content is serious, and content recommendation means for recommending optimal content based on the user's emotional state. This allows users to easily receive appropriate mental health care and regain emotional composure through optimal content tailored to their emotional state at the time.

[0663] A "user" is an individual who uses the system to discuss feelings of depression or anxiety.

[0664] An "interface" is a screen or input device through which a user inputs their feelings of depression or anxiety.

[0665] "Communication means" refers to a host device or internet connection for transmitting user input to a server in real time.

[0666] The "artificial intelligence engine" is an algorithm that analyzes the content of the consultation received and generates an appropriate response.

[0667] "Display means" refers to a display or mobile screen for providing the generated response to the user in real time.

[0668] The "matching engine" is an algorithm that analyzes a user's consultation history and connects them with other users who have the same concerns.

[0669] "Escalation means" refers to communication devices or software functions that transfer information to a specialist when the consultation content is serious.

[0670] A "content recommendation method" is an algorithm or system that recommends optimal content based on the user's emotional state.

[0671] To implement this invention, we will build a system that allows users to easily receive mental health care. The main components include a user interface, communication means, an artificial intelligence engine, display means, a matching engine, escalation means, and content recommendation means.

[0672] First, the user interface provides a screen and input device that allows users to input their feelings of depression and anxiety. This interface is implemented as a smartphone application. The data entered by the user is sent to a server in real time via a communication means. An internet connection is required for this communication.

[0673] The server analyzes the received user's inquiry using an AI engine and generates an appropriate response. This AI engine implements a model for sentiment analysis using Hugging Face's Transformers library. The analyzed results are provided to the user via a display means, which can be a smartphone display or a mobile screen.

[0674] The server also has a matching engine that analyzes the user's consultation history and matches them with other users who have the same concerns. This matching engine searches the database for users with similar concerns and helps them support each other.

[0675] Furthermore, if the consultation content is serious, the information is transferred to a specialist using an escalation means. This escalation means includes a communication device and a dedicated software function. Once the information is escalated to the specialist, counseling is provided based on the automatically generated medical record.

[0676] Finally, the server has a content recommendation mechanism that recommends optimal content based on the user's emotional state. This content could include relaxing music, guided meditations, videos, etc. This allows users to receive optimal support tailored to their emotional state at any given time. This recommendation algorithm is also implemented using Hugging Face's library.

[0677] For example, if a user types, "I'm feeling really down today," the sentiment analysis model will detect the negative emotion and respond with, "I understand, and I'll provide you with specific support." It will also display links to relaxing music and guided meditations based on the user's emotional state.

[0678] Example prompt sentence:

[0679] "I am feeling very sad today."

[0680] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0681] Step 1:

[0682] Users input their feelings of depression and anxiety through a smartphone interface. This input is in text format, and the input data includes sentences such as "I'm feeling very depressed today."

[0683] Input: Text data showing feelings of depression and anxiety

[0684] Output: Sends input data to the server

[0685] Step 2:

[0686] The device uses a communication means to transmit text data entered by the user to a server in real time, and this communication requires an internet connection.

[0687] Input: Input data (text format)

[0688] Output: Data sent to the server

[0689] Step 3:

[0690] The server then analyzes the received user text data using an artificial intelligence engine, using Hugging Face's Transformers library for sentiment analysis.

[0691] Input: Data sent to the server (text format)

[0692] Data Processing: Sentiment Analysis

[0693] Output: Sentiment analysis result (e.g., negative)

[0694] Step 4:

[0695] The server generates an appropriate response based on the results of the sentiment analysis, and the generated response is provided to the user in real time.

[0696] Input: Sentiment analysis results

[0697] Data calculation: response generation

[0698] Output: Response (e.g. "I understand, I'll provide specific assistance.")

[0699] Step 5:

[0700] The terminal provides the response sent from the server to the user using a display means, such as the display of the smartphone.

[0701] Input: The response sent by the server

[0702] Output: Response displayed on the smartphone display

[0703] Step 6:

[0704] The server analyzes the user's consultation history and matches them with other users who have the same concerns. This process uses a matching engine to search a database for users with similar concerns.

[0705] Input: User's consultation history

[0706] Data processing: consultation history analysis, user matching

[0707] Output: Matching results

[0708] Step 7:

[0709] If the consultation is serious, the server uses an escalation method to transfer the consultation to a specialist, using an automatically generated medical record.

[0710] Input: Serious consultation content

[0711] Data calculation: medical record generation, transfer to specialist

[0712] Output: Specialist notification and medical records

[0713] Step 8:

[0714] The server uses content recommendation tools to recommend optimal content based on the user's emotional state, such as guided meditations or relaxing music.

[0715] Input: Sentiment analysis results

[0716] Data Computing: Content Recommendation

[0717] Output: Recommended content (e.g., a link to a guided meditation)

[0718] Example prompt sentence:

[0719] "I am feeling very sad today."

[0720] 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.

[0721] An embodiment of the present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. This system provides more advanced support by incorporating an emotion engine that recognizes the user's emotions.

[0722] System Configuration

[0723] 1. User authentication and login process

[0724] A user starts the application, enters their username and password on the login screen, and clicks the login button. The device sends the authentication information to the server, which then authenticates the user against the database. If authentication is successful, the user can access the main screen.

[0725] 2. 24-hour support via AI chatbots

[0726] Users input their feelings of depression or anxiety through a chat interface and send them to a server via their device. The server then passes the information to an artificial intelligence engine, which generates an appropriate response.

[0727] 3. Emotion Recognition by Emotion Engine

[0728] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state. Based on the emotional state recognized by the emotion engine, the AI ​​engine adjusts the response and provides more appropriate support.

[0729] 4. Viewing the Response

[0730] The server sends the generated response to the device, which displays it to the user, who can then view the AI's response in a chat window and continue the conversation.

[0731] 5. Empathy and matching process

[0732] The server analyzes the user's consultation history and the emotion recognition results of the emotion engine, and then uses the matching engine to search for other users with the same emotional state or concerns. The matching results are notified to the user via their device, allowing them to receive empathy and support from other users.

[0733] 6. Expert Collaboration and Escalation

[0734] If the consultation is deemed serious, the server automatically creates a medical record based on the user's consultation content and emotion recognition results, and escalates the consultation to an expert. The device receives feedback and advice from the expert and displays it to the user.

[0735] 7. Freemium model vs. paid services

[0736] Users can choose between free and paid services, and if they wish to use the paid service, they enter their payment information on the payment screen. The terminal then sends the payment information to the server, which then confirms the payment and adds paid service authorization to the user's account. Paid services allow users to receive advanced mental health care.

[0737] Specific examples

[0738] For example, if a user is overcome by anxiety at night, they can use this system to receive advice 24 hours a day. When the user types "I've been feeling anxious and can't sleep lately" into the chat interface, the device sends it to the server. The emotion engine in the server analyzes this input and recognizes the user's anxious feelings. At the same time, the artificial intelligence engine generates an appropriate response (e.g., "Can you tell me more about what is causing you anxiety?") and displays it to the user via the device. The emotion engine then analyzes the user's further input, and if it detects serious anxiety, the server automatically escalates the case to a specialist and provides professional support.

[0739] The system allows users to receive appropriate mental health care in real time, helping them regain emotional composure.

[0740] The processing flow will be explained below.

[0741] The embodiment of the present invention is detailed through the following process steps.

[0742] User authentication and login process

[0743] Step 1:

[0744] The user launches the application. The user taps the application icon to launch it, and the login screen is displayed.

[0745] Step 2:

[0746] The user enters their login information (username and password) and clicks the Login button.

[0747] Step 3:

[0748] The device sends the login information to the server. The device encrypts the username and password and sends them to the server.

[0749] Step 4:

[0750] The server authenticates the user against a database. The server checks the login information it receives against its database to see if there is a match.

[0751] Step 5:

[0752] The server returns the authentication result to the terminal. If the authentication is successful, the server notifies the terminal of the success, and if the authentication is unsuccessful, it returns an error message.

[0753] Step 6:

[0754] The device notifies the user of the authentication result. If authentication is successful, the device displays the main screen, otherwise it displays an error message.

[0755] AI chatbot and emotion engine response

[0756] Step 7:

[0757] Users access the chat interface from the main screen and enter their concerns about their depression or anxiety.

[0758] Step 8:

[0759] The terminal transmits the input consultation content to the server.

[0760] Step 9:

[0761] The server receives the consultation content and passes it to the AI ​​engine, which analyzes it and generates an appropriate response.

[0762] Step 10:

[0763] The server sends the generated response to the terminal.

[0764] Step 11:

[0765] The device will display the response to the user, who will then be able to see the AI's response in the chat window.

[0766] Emotion recognition by emotion engine

[0767] Step 12:

[0768] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state.

[0769] Step 13:

[0770] The artificial intelligence engine adjusts the response based on the emotional state recognized by the emotion engine.

[0771] Step 14:

[0772] The server sends the adjusted response to the terminal.

[0773] Step 15:

[0774] The device displays the adjusted response to the user, allowing the user to continue the interaction with better support.

[0775] The empathy and matching process

[0776] Step 16:

[0777] The server analyzes the user's consultation history and emotion recognition results, and uses a matching engine to search for other users with the same emotional state or concerns.

[0778] Step 17:

[0779] The server sends the matching results to the device, which displays them to the user, who can then select the option to chat with other users who share their interests.

[0780] Expert collaboration and escalation

[0781] Step 18:

[0782] If the consultation is deemed serious, the server automatically creates a medical record based on the consultation content and emotion recognition results, and escalates the case to a specialist.

[0783] Step 19:

[0784] The expert reviews the chart and sends feedback to the server.

[0785] Step 20:

[0786] The server transfers the feedback from the expert to the device, which then displays it to the user, allowing the user to review the expert's advice and receive the necessary support.

[0787] Freemium model vs. paid services

[0788] Step 21:

[0789] If the user selects a paid service, the terminal displays a payment screen and the user enters payment information.

[0790] Step 22:

[0791] The terminal sends the payment information to the server.

[0792] Step 23:

[0793] The server verifies the payment via a payment gateway.

[0794] Step 24:

[0795] The server notifies the terminal whether the payment was successful or not, and the terminal displays the result to the user. If successful, the paid service becomes available.

[0796] These are the specific processing steps of the system that combines the emotion engine, which allows users to receive appropriate mental health care in real time and helps them regain emotional composure.

[0797] Example 2

[0798] 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."

[0799] In modern society, the number of people suffering from depression and anxiety is increasing. Systems that provide prompt and appropriate support for these mental health issues are needed. In particular, there is a growing need for systems that respond to users in real time, 24 hours a day, recognize their emotional state, and provide appropriate responses. There is also a need for systems that empathize with and support other users with the same concerns, as well as rapid escalation to professional support. However, current systems have difficulty meeting all of these requirements, necessitating the creation of a more comprehensive mental health care system.

[0800] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for providing an interface that allows users to consult about depression or anxiety at any time, a communication means for transmitting user input to the server in real time, an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response, a display means for providing the generated response to the user, an emotion engine for recognizing the user's emotional state, a means for adjusting the response based on the recognized emotion, a matching engine for analyzing the user's consultation history and matching with other users who have the same concerns, and an escalation means for escalating the consultation content to a specialist if the consultation content is serious. This enables more effective mental health care for users by recognizing emotional fluctuations and providing appropriate responses. It also enables advanced support through empathy and support between users and rapid escalation to a specialist.

[0801] A "user" is someone who uses the system to seek advice about feelings of depression or anxiety.

[0802] The "interface" refers to the screen and operating environment that users use to discuss their feelings of depression and anxiety.

[0803] "Communication means" refers to the process or technology used to transmit user input information to the server in real time.

[0804] A "server" is a computer system that receives input information from a user and performs appropriate processing or responds.

[0805] An "artificial intelligence engine" is software or algorithms that analyze incoming inquiries and generate appropriate responses.

[0806] A "display means" is a screen or device that allows the user to see the generated response.

[0807] An "emotion engine" is software or algorithms that analyze user input and recognize emotional states.

[0808] The "means for adjusting the response based on the recognized emotion" refers to a process or technology for appropriately changing the response of the artificial intelligence engine based on the emotion recognized by the emotion engine.

[0809] "Consultation history" is a record of consultations that a user has previously made through the system.

[0810] A "matching engine" is software or an algorithm that analyzes a user's consultation history and emotions to find other users with the same concerns.

[0811] "Escalation methods" are processes and techniques for notifying a specialist of a serious issue.

[0812] An "expert" is someone who has specialized knowledge and skills in relation to the content of the user's inquiry and who can provide appropriate support and advice.

[0813] A "medical record" is a document or data that organizes information such as consultation details and emotional state and is passed on to a specialist.

[0814] The "freemium model" is a business model that provides basic services for free and offers additional paid services.

[0815] "Payment method" means the process or technology used to process payments when a user uses a paid service.

[0816] The present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. The following describes in detail the modes for carrying out the present invention.

[0817] This system mainly consists of three components: a user terminal, a server, and various engines (artificial intelligence engine, emotion engine, and matching engine).

[0818] User device:

[0819] User devices include PCs, smartphones, tablets, and other devices. Users launch the dedicated application, enter their username and password on the login screen, and click the login button to be authenticated. Once login is successful, they are redirected to the main screen. When users feel depressed or anxious, they can enter their concerns into the application's chat interface and send them.

[0820] server:

[0821] The server is a computer system that receives authentication information and consultation details from the user. The server connects to a database (e.g., MySQL) to authenticate the user. The server then passes the received consultation details to an artificial intelligence engine to generate an appropriate response. For example, OpenAI's GPT-3 is used as the artificial intelligence engine. The generated response is sent to the user's device, which then displays it to the user.

[0822] Emotion Engine:

[0823] The emotion engine is software that analyzes user input and recognizes the user's emotional state. Specifically, it uses tools such as IBM Watson Emotion Analysis. If a user types, "I've been feeling anxious and can't sleep lately," the emotion engine analyzes the content and recognizes the emotion "anxiety." Based on this result, the artificial intelligence engine adjusts the response.

[0824] Matching Engine:

[0825] The matching engine is software that analyzes the user's consultation history and emotion recognition results to find other users with the same concerns. For example, a tool like Elasticsearch is used. This allows users with similar emotional states and concerns to be connected, promoting empathy and support.

[0826] Escalation Methods:

[0827] The escalation method is a process that notifies an expert if the consultation content is judged to be serious. The server creates an automatically generated medical record based on the consultation content along with the analysis results of the emotion engine, and passes it to the expert. The medical record is generated in PDF format or other formats, allowing the expert to quickly evaluate and provide advice. When the expert sends feedback to the server, it is displayed on the user's device.

[0828] Freemium model:

[0829] Users can choose between free and paid services. If they wish to use paid services in addition to the basic free service, they enter their credit card information on the payment screen and complete the payment. The server uses a payment gateway (e.g., Stripe) and, once payment is confirmed, adds permission for the paid service to the user's account. Paid services allow users to receive more advanced mental health care.

[0830] Examples:

[0831] For example, if a user is unable to sleep at night due to anxiety, they can use the system to receive advice 24 hours a day. When the user types "I've been unable to sleep lately due to anxiety" into the chat interface and sends it, the device sends it to the server. The emotion engine in the server analyzes this input and recognizes the "emotion of anxiety," and the artificial intelligence engine generates a response such as "Please tell me more about what is causing your anxiety," and sends it to the device. The response is then displayed to the user. If more serious anxiety is detected, the server automatically escalates the situation to a specialist and provides professional support.

[0832] Example prompts to input to a generative AI model:

[0833] "Please explain how users can use this system to get 24 / 7 support if they feel unsafe at night."

[0834] Thus, the present invention is a system that provides users with comprehensive, real-time, and appropriate mental health care, and is capable of efficiently recognizing emotions, promoting empathy, and escalating professional support.

[0835] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0836] Step 1:

[0837] The user launches the application, enters their username and password on the login screen, and clicks the login button.

[0838] Specific behavior:

[0839] A user launches the application, enters the username "example_user" and password "password123" on the login screen, and clicks the Login button.

[0840] Input: Username and Password

[0841] Output: User credentials are sent from the device to the server.

[0842] Step 2:

[0843] The terminal sends authentication information to the server, which then compares it with a database to authenticate the user.

[0844] Specific behavior:

[0845] The device sends authentication information (username and password) to the server as an HTTP POST request.

[0846] Input: Username and Password

[0847] Data processing: The authentication information is checked against a database on the server (e.g., MySQL).

[0848] Output: If authentication is successful, the server returns the URL of the main page in the HTTP response.

[0849] Step 3:

[0850] If the server succeeds in the authentication, it sends information to the terminal to transition to the main screen.

[0851] Specific behavior:

[0852] The server sends the URL of the main screen to the device in an HTTP response.

[0853] Input: Authentication information match result

[0854] Output: The URL of the main screen is sent to the device.

[0855] Step 4:

[0856] The user types their feelings of depression and anxiety into a chat interface and clicks the send button.

[0857] Specific behavior:

[0858] The user types "I've been feeling anxious and can't sleep lately" into the chat window and presses the send button.

[0859] Input: User's inquiry

[0860] Output: The consultation content is sent from the terminal to the server.

[0861] Step 5:

[0862] The device sends the consultation details to the server, which then passes the details to the artificial intelligence engine.

[0863] Specific behavior:

[0864] The device sends the entered consultation details to the server, which then passes them to an artificial intelligence engine (e.g., OpenAI GPT-3).

[0865] Input: User's inquiry

[0866] Data processing: An artificial intelligence engine analyzes the consultation content and generates an appropriate response.

[0867] Output: The generated response is returned to the server.

[0868] Step 6:

[0869] The server sends the generated response to the terminal.

[0870] Specific behavior:

[0871] The server sends the response obtained from the artificial intelligence engine to the terminal.

[0872] Input: The generated response

[0873] Output: The response is sent to the terminal.

[0874] Step 7:

[0875] The terminal displays the response received from the server to the user.

[0876] Specific behavior:

[0877] The terminal displays the generated response in the chat window.

[0878] Input: Response from the server

[0879] Output: Response displayed in the chat window

[0880] Step 8:

[0881] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state.

[0882] Specific behavior:

[0883] The server sends the user's input information to an emotion engine (e.g., IBM Watson Emotion Analysis) to analyze the user's emotional state.

[0884] Input: User's inquiry

[0885] Data processing: The emotion engine analyzes the input information and recognizes the emotional state.

[0886] Output: Emotional state recognition result

[0887] Step 9:

[0888] The server receives the recognition results from the emotion engine and instructs the artificial intelligence engine to adjust the response.

[0889] Specific behavior:

[0890] The server instructs the artificial intelligence engine to adjust the response based on the recognition results of the emotion engine.

[0891] Input: Emotional state recognition results

[0892] Data processing: Adjusting responses based on recognition results.

[0893] Output: The adjusted response

[0894] Step 10:

[0895] The server sends the adjusted response to the user terminal.

[0896] Specific behavior:

[0897] The server sends the adjusted response to the user's device in an HTTP response.

[0898] Input: Adjusted response

[0899] Output: The adjusted response is sent to the terminal.

[0900] Step 11:

[0901] The user can see the tailored response in the chat window and continue the conversation.

[0902] Specific behavior:

[0903] The user sees the response displayed on the screen.

[0904] Input: Adjusted response

[0905] Output: User confirmation and next input

[0906] Step 12:

[0907] The server analyzes the user's consultation history and the emotion recognition results of the emotion engine, and uses a matching engine to search for other users who have the same emotional state or concerns.

[0908] Specific behavior:

[0909] The server retrieves the user's consultation history and emotion engine data from a database (e.g., MongoDB) and analyzes it.

[0910] Input: Consultation history and emotion recognition results

[0911] Data processing: Analyze using a matching engine (e.g. Elasticsearch).

[0912] Output: Matching results

[0913] Step 13:

[0914] The server notifies the user's device of the matching results, encouraging empathy and support between users.

[0915] Specific behavior:

[0916] The server sends the matching results to the user's device as an HTTP response and displays a notification.

[0917] Input: Matching results

[0918] Output: Notification of sympathy and support between users

[0919] Step 14:

[0920] If the consultation is serious, the server will automatically create a medical record and escalate the matter to a specialist.

[0921] Specific behavior:

[0922] If the server detects serious anxiety from the analysis results of the emotion engine, it automatically generates a medical record (e.g., PDF format).

[0923] Input: Emotion recognition results and consultation details

[0924] Data processing: Automatically generate medical records and send them to specialists.

[0925] Output: Send medical record to specialist

[0926] Step 15:

[0927] The expert sends feedback and advice back to the server, which the device displays to the user.

[0928] Specific behavior:

[0929] The expert sends feedback and advice back to the server, which then sends it to the user's device, which displays the advice.

[0930] Input: Expert feedback

[0931] Output: Advice displayed on the user's terminal

[0932] Step 16:

[0933] If the user selects a paid service, they enter payment information on the payment screen, and the terminal sends that information to the server.

[0934] Specific behavior:

[0935] The user clicks the "Upgrade to paid service" button and enters credit card information, etc. The terminal sends the payment information to the server.

[0936] Input: Payment Information

[0937] Output: Payment information is sent to the server.

[0938] Step 17:

[0939] The server verifies the payment information and, if successful, adds authorization for the paid service to the user account.

[0940] Specific behavior:

[0941] Your server verifies the payment with a payment gateway (e.g., Stripe) and, if successful, adds authorization for paid services to the user account.

[0942] Input: Payment Information

[0943] Data Processing: Verify payment information and update account permissions

[0944] Output: The paid service entitlement is added to the user account.

[0945] Step 18:

[0946] The server notifies the user terminal that a paid service has become available, and the terminal displays this to the user.

[0947] Specific behavior:

[0948] The server sends a notification to the user's device saying "Paid service is now available." The device displays it to the user.

[0949] Input: Permission update result for paid service

[0950] Output: A notification to the user about the paid service is displayed.

[0951] (Application example 2)

[0952] 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."

[0953] Conventional mental healthcare systems have difficulty recognizing users' emotional state and stress levels in real time and responding appropriately. Furthermore, in brick-and-mortar stores, if a store clerk is emotionally depressed or stressed, this can affect customer service and reduce customer satisfaction. Furthermore, when escalating serious consultations to specialists, many systems require users to take action themselves, and lack efficient methods such as automated medical record creation. To address these issues, a system with more advanced emotion recognition and stress monitoring capabilities is needed to strengthen mental health support in brick-and-mortar stores.

[0954] 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.

[0955] In this invention, the server includes: means for providing an interface that allows users to consult about depression or anxiety at any time; communication means for transmitting user input to the server in real time; an artificial intelligence engine that analyzes the received consultation content using specific analysis means and generates an appropriate response; display means for providing the generated response to the user; a matching engine that analyzes the user's consultation history and matches them with other users who have the same problem; escalation means for escalating the consultation to a specialist if the consultation content is serious; emotion recognition means for recognizing and analyzing the user's emotions in real time; means for adjusting and providing support according to the emotional state based on the emotion recognition means; means for monitoring the stress level of store staff; and means for providing customer support in a physical store. This enables the emotional states of users and store staff to be recognized in real time, enabling appropriate mental health care and customer support.

[0956] "User" refers to an individual who uses the mental health care system.

[0957] "Interface" refers to the screen and operation methods that provide users with a means to discuss their feelings of depression or anxiety.

[0958] "Communication Method" refers to the technology or protocol used to transmit user input to a server in real time.

[0959] "Artificial intelligence engine" refers to AI technology that analyzes the content of inquiries received and generates appropriate responses.

[0960] "Display means" refers to a display or screen on which the generated response is shown to the user.

[0961] A "matching engine" refers to technology that analyzes a user's consultation history and connects them with other users who have the same concerns.

[0962] "Escalation measures" refer to the means of conveying information to a specialist when the consultation matter is serious.

[0963] "Emotion recognition means" refers to technology for recognizing and analyzing a user's emotional state in real time.

[0964] "Means for monitoring stress levels" refers to technology for recognizing and monitoring the stress levels of store employees.

[0965] "Means of providing customer service support" refers to the techniques and methods that enable store staff to provide better service to customers in physical stores.

[0966] The present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. Specifically, the system includes an interface, communication means, an artificial intelligence engine, emotion recognition means, display means, a matching engine, and escalation means.

[0967] System Configuration

[0968] 1. Interface

[0969] The system provides a screen and operation method that allows users to consult about their depression or anxiety. Users input their concerns through this interface.

[0970] 2. Means of communication

[0971] User input is sent to the server in real time using HTTP or HTTPS as the communication protocol.

[0972] 3. Artificial Intelligence Engine

[0973] The system analyzes the received consultation content and generates an appropriate response using a generative AI model that uses deep learning technology.

[0974] 4. Emotion recognition means

[0975] It analyzes user input and recognizes their emotional state in real time. The emotion recognition engine uses natural language processing technology to analyze emotions.

[0976] 5. Display means

[0977] It has a display, usually a smartphone or tablet, to show the generated response to the user.

[0978] 6. Matching Engine

[0979] The system analyzes the user's consultation history and matches them with other users who have the same concerns. The matching algorithm uses collaborative filtering technology.

[0980] 7. Escalation Methods

[0981] If the consultation is serious, it will be escalated to a specialist. The server will automatically generate a medical record and send it to the specialist.

[0982] Specific examples

[0983] If a user experiences anxiety at night, they can use this system to receive advice 24 hours a day. When the user types "I've been feeling anxious and can't sleep lately" into the interface, the device sends this to the server. An emotion recognition system within the server analyzes this input and recognizes the user's feelings of anxiety. At the same time, an artificial intelligence engine generates an appropriate response (for example, "Could you tell me more about what is causing you anxiety?") and displays it to the user via the device.

[0984] Furthermore, the emotion recognition means continuously analyzes the user's input, and if it detects a high-stress state, the server automatically escalates to an expert and provides detailed feedback and advice.

[0985] Prompt Sentence Examples

[0986] User: "I've been so stressed lately I can't concentrate on my work."

[0987] AI chatbot: "Tell me what's causing you stress"

[0988] This example allows users to receive prompt and appropriate mental health care.

[0989] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0990] Step 1:

[0991] The user inputs the content of their problem into the interface. The input content is text information such as "I've been feeling anxious lately and can't sleep."

[0992] Step 2:

[0993] The terminal sends user input to the server in real time using HTTP or HTTPS as the communication protocol. The input data is sent to the server in JSON format.

[0994] Step 3:

[0995] The server analyzes the received input data. First, the server's emotion recognition means analyzes the text using natural language processing technology to recognize the user's emotional state in real time. Through this analysis, the emotion contained in the input is labeled as "anxiety."

[0996] Step 4:

[0997] The server generates an appropriate response using a generative AI model based on the emotion recognition results. The AI ​​engine generates a response (e.g., "Tell me more about what causes anxiety") according to the user's emotion label "anxiety."

[0998] Step 5:

[0999] The server sends the generated response to the device, which again encodes the response in JSON format and sends it to the device using the HTTP / S protocol.

[1000] Step 6:

[1001] The terminal provides the response received from the server to the user, specifically, by displaying the generated response message on the display of the terminal.

[1002] Step 7:

[1003] If the user enters the information again, the process is repeated. The emotion recognition means in the server continuously monitors and analyzes the user's emotional state, and if it detects a high stress state, the escalation means is activated. The server then sends the automatically generated medical record to a specialist to provide further support to the user.

[1004] Step 8:

[1005] The matching engine analyzes the user's consultation history. The server uses collaborative filtering technology to search for other users with the same concerns and make appropriate matches. The matching results are sent to the device and displayed on the screen.

[1006] Step 9:

[1007] When the consultation is escalated to an expert by the escalation means, the server receives feedback from the expert and provides it to the user. The terminal displays the feedback and provides the user with professional advice.

[1008] These steps can help users receive prompt and appropriate mental health care and promote emotional stability.

[1009] 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.

[1010] 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.

[1011] 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.

[1012] [Third embodiment]

[1013] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1014] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1015] 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).

[1016] 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.

[1017] 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.

[1018] 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).

[1019] 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.

[1020] 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.

[1021] 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.

[1022] 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.

[1023] 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.

[1024] 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."

[1025] The embodiment of the present invention is a comprehensive system that allows users to express their depression and anxiety and receive appropriate support. The system has the following main functions:

[1026] 1. User authentication and login process

[1027] The user starts the application, enters their username and password on the login screen, and clicks the login button. The device sends this authentication information to the server, which then authenticates the user by checking it against a database. If authentication is successful, the user is taken to the main screen and can use the system.

[1028] 2. 24-hour support via AI chatbots

[1029] The user enters their concerns about depression or anxiety on the chat screen and sends them. The device then sends the information to a server, where an artificial intelligence engine analyzes the received information and generates an appropriate response. The generated response is provided to the user in real time, allowing them to express their feelings and receive support through dialogue.

[1030] 3. Empathy and matching process

[1031] The server analyzes the user's consultation history and current consultation content, and searches a database for other users with the same concerns. A matching engine is used to make it easier for users to connect with other users in similar situations, allowing them to receive empathy and support. The matching results are notified to the user via their device, and they can start chatting with other users if necessary.

[1032] 4. Collaboration and response with experts

[1033] If the problem is deemed serious, the server will escalate the issue to a specialist using an automatically generated medical record based on the consultation details. The specialist will then provide appropriate counseling based on the information transferred to them. The device will then display feedback and advice from the specialist to the user in real time, allowing the user to receive the support they need.

[1034] 5. Freemium model vs. paid services

[1035] Users can choose between free and paid services within the application. Users who wish to use paid services enter their payment information on the payment screen and send it to the server via their device. The server then confirms the payment and adds paid service authorization to the user's account. Paid services allow users to receive advanced mental health care.

[1036] The above is an embodiment of the present invention. This system provides users with easily accessible mental health care and provides specific means for regaining emotional composure.

[1037] The processing flow will be explained below.

[1038] Step 1:

[1039] The user launches the application. The user taps the application icon to launch it, and the login screen is displayed.

[1040] Step 2:

[1041] The user enters their login information (username and password) and clicks the Login button.

[1042] Step 3:

[1043] The device sends the login information to the server. The device encrypts the username and password and sends them to the server.

[1044] Step 4:

[1045] The server authenticates the user against a database. The server checks the login information it receives against its database to see if there is a match.

[1046] Step 5:

[1047] The server returns the authentication result to the terminal. If the authentication is successful, the server notifies the terminal of the success, and if the authentication is unsuccessful, it returns an error message.

[1048] Step 6:

[1049] The device notifies the user of the authentication result. If authentication is successful, the device displays the main screen, otherwise it displays an error message.

[1050] Step 7:

[1051] Users access the chat interface from the main screen and enter their concerns about depression or anxiety.

[1052] Step 8:

[1053] The terminal transmits the input consultation content to the server.

[1054] Step 9:

[1055] The server receives the consultation content and passes it to the AI ​​engine, which analyzes the content and generates an appropriate response.

[1056] Step 10:

[1057] The server sends the generated response to the terminal.

[1058] Step 11:

[1059] The device will display the response to the user, who will then be able to see the AI's response in the chat window.

[1060] Step 12:

[1061] The server analyzes the user's consultation history and uses a matching engine to search for other users with the same concerns.

[1062] Step 13:

[1063] The server sends the matching results to the device, which displays them to the user, who can then select the option to chat with other users who share their interests.

[1064] Step 14:

[1065] If the consultation is deemed serious, the server will automatically create a medical record based on the consultation content and escalate the case to a specialist.

[1066] Step 15:

[1067] The expert reviews the chart and sends feedback to the server.

[1068] Step 16:

[1069] The server transfers the feedback from the expert to the device, which then displays it to the user, allowing the user to review the expert's advice and receive the necessary support.

[1070] Step 17:

[1071] If the user selects a paid service, the terminal displays a payment screen and the user enters payment information.

[1072] Step 18:

[1073] The terminal sends the payment information to the server, which verifies the payment via a payment gateway.

[1074] Step 19:

[1075] The server notifies the terminal whether the payment was successful or not, and the terminal displays the result to the user. If successful, the paid service becomes available.

[1076] These are the processing steps of the system, which allows users to vent their feelings and receive support from experts if necessary.

[1077] Example 1

[1078] 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."

[1079] In recent years, mental health problems have been on the rise, creating a need for systems that allow users to easily seek advice about depression and anxiety at any time. However, current systems are inadequate in terms of real-time response, expert response, and empathy matching with other users. In particular, they do not address the needs of users who require smooth escalation to an expert when the issue is serious, or payment for paid services. The present invention aims to solve these problems.

[1080] 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.

[1081] In this invention, the server includes: means for providing an interface that allows users to consult about depression or anxiety at any time; communication means for transmitting user input to the server in real time; an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response; display means for providing the generated response to the user; a matching engine for analyzing the user's consultation history and matching the user with other users who have the same problem; escalation means for escalating the consultation content to a specialist if the consultation content is serious; means for executing user authentication and login process; means for allowing the user to select between a free or paid freemium model; and payment means for processing additional fees for paid services. This allows users to easily consult about their emotions, receive sympathy, and, if necessary, receive professional support.

[1082] "User" refers to any individual or organization that uses this system.

[1083] "Interface" refers to the screen and input means through which a user interacts with a system.

[1084] "Communication means" refers to the devices and protocols that transmit user input to the server in real time.

[1085] "Artificial intelligence engine" refers to software or algorithms that analyze incoming inquiries and generate appropriate responses.

[1086] "Display means" refers to a device or system that provides the generated response to the user visually or audibly.

[1087] A "matching engine" refers to an algorithm or software that analyzes a user's consultation history and connects them with other users who have the same concerns.

[1088] "Escalation mechanisms" refer to mechanisms and processes for transferring serious issues to specialists.

[1089] "User authentication" refers to the process for verifying a user's identity and controlling access to a system.

[1090] "Login process" refers to the authentication steps a user goes through to access a system.

[1091] The "freemium model" refers to a business model that combines free and paid services.

[1092] "Payment Method" means an electronic payment system for processing fees for Paid Services.

[1093] MODE FOR CARRYING OUT THE INVENTION

[1094] The present invention relates to a comprehensive system that allows users to express their depression and anxiety and receive appropriate support, with easy user access and real-time response capabilities.

[1095] User authentication and login process

[1096] A user starts an application and enters their username and password on the login screen. The device sends this authentication information to the server, which then authenticates the user by checking it against a database (e.g., MySQL). If authentication is successful, the server sends the result back to the device, which then redirects the user to the main screen.

[1097] 24-hour support by AI chatbot

[1098] The user enters their concerns about depression or anxiety into the chat screen and sends them. The device then sends the information to the server, which uses an artificial intelligence engine (e.g., OpenAI GPT-3) to analyze the content and generate an appropriate response. The generated response is then sent back to the device, which displays it to the user in real time.

[1099] The empathy and matching process

[1100] The server analyzes the user's consultation history and current consultation content. Using a matching engine (e.g., Elasticsearch), it searches the database for other users with the same concerns and finds users with common interests. The server notifies the device of the matching results, and the device notifies the user. The user receives the notification and can start chatting with other users if necessary.

[1101] Collaboration and response with experts

[1102] The server automatically creates a medical record based on the consultation content that is judged to be a serious problem and escalates it to an expert. The expert then provides counseling based on the medical record. The terminal displays feedback and advice from the expert to the user in real time.

[1103] Freemium model vs. paid services

[1104] Users can choose between free and paid services within the application. Users who wish to use paid services enter their payment information on the payment screen and send it to the server via their device. The server then confirms the payment and adds the paid service authorization to the user's account. By using the paid service, users can receive advanced mental health care.

[1105] Examples of specific examples and prompts

[1106] 1. When a user logs in to the app, they enter "example_user" and "password123" and click the Login button.

[1107] 2. The device sends this information to the server, which then performs authentication.

[1108] 3. The user types, "I've been stressed out lately and can't sleep," into the chat screen and sends it.

[1109] 4. The device sends this information to a server, and the GPT-3 artificial intelligence engine generates a response: "That's tough. Tell me more about what's causing you stress."

[1110] 5. The terminal displays the response to the user.

[1111] 6. The server searches for other users with similar problems and notifies the user via their device, "There is another user with the same problem. Would you like to connect?"

[1112] Example prompt sentence:

[1113] Chatbot prompt: "Generate an appropriate response to the user's message: 'I've been feeling stressed lately and can't sleep.'"

[1114] Matching engine prompt: "Based on the user's complaint 'I'm feeling increasingly stressed,' find other users with similar concerns."

[1115] The above is an embodiment of the present invention. This system allows users to receive prompt and appropriate mental health care and provides specific means for regaining emotional composure.

[1116] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1117] Step 1:

[1118] The user starts the application and enters their username and password on the login screen. The entered information is in the form of a username and password. The device sends this authentication information to the server. The server receives it and verifies the username and password against a database to perform authentication. If authentication is successful, the server returns a success message to the device, and the device transitions the user to the main screen.

[1119] Specific behavior:

[1120] The user enters the username "example_user" and password "example_pass" and clicks the Login button.

[1121] The terminal transmits the entered authentication information to the server.

[1122] The server checks the information against the database and sends a message to the terminal indicating successful authentication.

[1123] The device will transition to the main screen.

[1124] Step 2:

[1125] The user moves to the chat screen, enters the content of their consultation, and sends it. The entered content is in text format as the user's consultation content. The device sends this input content to the server. The server receives it and passes it to the artificial intelligence engine. The artificial intelligence engine analyzes the consultation content and generates an appropriate response. The generated response is a response message in text format. The server sends the generated response to the device, which displays it to the user.

[1126] Specific behavior:

[1127] The user types, "I've been feeling stressed lately and can't sleep," and clicks the send button.

[1128] The device sends the input to the server.

[1129] The server requests an analysis from an artificial intelligence engine (e.g., GPT-3) and receives a response message.

[1130] The server sends a response message to the terminal, which displays it to the user.

[1131] Step 3:

[1132] Based on the user's consultation content and past consultation history, the server begins the process of searching for other users who share the same concerns. The input data is text data of the user's current and past consultation content. The server passes this data to a matching engine to search for users with similar consultation content. The matching engine outputs the results and returns them to the server. The output data is a list of users with similar consultation content. The server sends the results to the terminal, which then displays matching suggestions to the user.

[1133] Specific behavior:

[1134] The server analyzes the user's current and past consultations.

[1135] The server passes the data to a matching engine (e.g. Elasticsearch) to search for other users with similar concerns.

[1136] The matching engine generates the results and returns them to the server.

[1137] The server sends the matching results to the device, and the device notifies the user, "There is a user with the same problem. Would you like to connect?"

[1138] Step 4:

[1139] If the consultation is serious, the server starts the process of escalating it to an expert. The input data is text data of the serious consultation content. The server creates an automatically generated medical record and sends it to the expert. The medical record data includes a summary of the consultation content and related information. The expert receives the medical record and provides counseling. The output data is text data of feedback and advice from the expert. The server receives this and sends it to the terminal, which displays it to the user.

[1140] Specific behavior:

[1141] The server analyzes the seriousness of the consultation and creates a medical record using an automatic medical record generation function.

[1142] The server sends the medical record to the specialist.

[1143] The expert provides counseling based on the medical records and returns feedback to the server.

[1144] The server sends feedback to the device, which displays it to the user.

[1145] Step 5:

[1146] If the user wishes to use a paid service, the payment process is initiated. The input data is the user's payment information and the selected paid service. The terminal sends this information to the server. The server confirms the payment via the payment processing service. The output data is a confirmation message that the payment is complete. The server notifies the terminal that the payment is successful, and the terminal adds authorization for the paid service to the user's account.

[1147] Specific behavior:

[1148] The user selects the paid service "High-end Counseling" and enters payment information.

[1149] The terminal sends the payment information to the server.

[1150] The server verifies the payment through a payment processing service (e.g., Stripe).

[1151] The server notifies the terminal that the payment has been completed, and the terminal adds authorization for the paid service to the user account.

[1152] The device notifies the user, "Advanced counseling is available."

[1153] (Application example 1)

[1154] 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."

[1155] In recent years, the number of people experiencing stress and anxiety has increased, making mental health care more important than ever. However, many people are unable to access appropriate support due to time and financial constraints, and are therefore unable to consult with a specialist. Furthermore, existing mental health support tools lack the functionality to provide optimal content tailored to each individual user's emotional state. Therefore, there is a need for a system that allows users to easily seek advice about their depression or anxiety, and that can provide optimal content tailored to their emotional state.

[1156] 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.

[1157] In this invention, the server includes means for providing an interface that allows users to consult about depression or anxiety at any time, communication means for transmitting user input to the server in real time, an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response, display means for providing the generated response to the user, a matching engine for analyzing the user's consultation history and matching with other users who have the same problem, escalation means for escalating the consultation to a specialist if the consultation content is serious, and content recommendation means for recommending optimal content based on the user's emotional state. This allows users to easily receive appropriate mental health care and regain emotional composure through optimal content tailored to their emotional state at the time.

[1158] A "user" is an individual who uses the system to discuss feelings of depression or anxiety.

[1159] An "interface" is a screen or input device through which a user inputs their feelings of depression or anxiety.

[1160] "Communication means" refers to a host device or internet connection for transmitting user input to a server in real time.

[1161] The "artificial intelligence engine" is an algorithm that analyzes the content of the consultation received and generates an appropriate response.

[1162] "Display means" refers to a display or mobile screen for providing the generated response to the user in real time.

[1163] The "matching engine" is an algorithm that analyzes a user's consultation history and connects them with other users who have the same concerns.

[1164] "Escalation means" refers to communication devices or software functions that transfer information to a specialist when the consultation content is serious.

[1165] A "content recommendation method" is an algorithm or system that recommends optimal content based on the user's emotional state.

[1166] To implement this invention, we will build a system that allows users to easily receive mental health care. The main components include a user interface, communication means, an artificial intelligence engine, display means, a matching engine, escalation means, and content recommendation means.

[1167] First, the user interface provides a screen and input device that allows users to input their feelings of depression and anxiety. This interface is implemented as a smartphone application. The data entered by the user is sent to a server in real time via a communication means. An internet connection is required for this communication.

[1168] The server analyzes the received user's inquiry using an AI engine and generates an appropriate response. This AI engine implements a model for sentiment analysis using Hugging Face's Transformers library. The analyzed results are provided to the user via a display means, which can be a smartphone display or a mobile screen.

[1169] The server also has a matching engine that analyzes the user's consultation history and matches them with other users who have the same concerns. This matching engine searches the database for users with similar concerns and helps them support each other.

[1170] Furthermore, if the consultation content is serious, the information is transferred to a specialist using an escalation means. This escalation means includes a communication device and a dedicated software function. Once the information is escalated to the specialist, counseling is provided based on the automatically generated medical record.

[1171] Finally, the server has a content recommendation mechanism that recommends optimal content based on the user's emotional state. This content could include relaxing music, guided meditations, videos, etc. This allows users to receive optimal support tailored to their emotional state at any given time. This recommendation algorithm is also implemented using Hugging Face's library.

[1172] For example, if a user types, "I'm feeling really down today," the sentiment analysis model will detect the negative emotion and respond with, "I understand, and I'll provide you with specific support." It will also display links to relaxing music and guided meditations based on the user's emotional state.

[1173] Example prompt sentence:

[1174] "I am feeling very sad today."

[1175] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1176] Step 1:

[1177] Users input their feelings of depression and anxiety through a smartphone interface. This input is in text format, and the input data includes sentences such as "I'm feeling very depressed today."

[1178] Input: Text data showing feelings of depression and anxiety

[1179] Output: Sends input data to the server

[1180] Step 2:

[1181] The device uses a communication means to transmit text data entered by the user to a server in real time, and this communication requires an internet connection.

[1182] Input: Input data (text format)

[1183] Output: Data sent to the server

[1184] Step 3:

[1185] The server then analyzes the received user text data using an artificial intelligence engine, using Hugging Face's Transformers library for sentiment analysis.

[1186] Input: Data sent to the server (text format)

[1187] Data Processing: Sentiment Analysis

[1188] Output: Sentiment analysis result (e.g., negative)

[1189] Step 4:

[1190] The server generates an appropriate response based on the results of the sentiment analysis, and the generated response is provided to the user in real time.

[1191] Input: Sentiment analysis results

[1192] Data calculation: response generation

[1193] Output: Response (e.g. "I understand, I'll provide specific assistance.")

[1194] Step 5:

[1195] The terminal provides the response sent from the server to the user using a display means, such as the display of the smartphone.

[1196] Input: The response sent by the server

[1197] Output: Response displayed on the smartphone display

[1198] Step 6:

[1199] The server analyzes the user's consultation history and matches them with other users who have the same concerns. This process uses a matching engine to search a database for users with similar concerns.

[1200] Input: User's consultation history

[1201] Data processing: consultation history analysis, user matching

[1202] Output: Matching results

[1203] Step 7:

[1204] If the consultation is serious, the server uses an escalation method to transfer the consultation to a specialist, using an automatically generated medical record.

[1205] Input: Serious consultation content

[1206] Data calculation: medical record generation, transfer to specialist

[1207] Output: Specialist notification and medical records

[1208] Step 8:

[1209] The server uses content recommendation tools to recommend optimal content based on the user's emotional state, such as guided meditations or relaxing music.

[1210] Input: Sentiment analysis results

[1211] Data Computing: Content Recommendation

[1212] Output: Recommended content (e.g., a link to a guided meditation)

[1213] Example prompt sentence:

[1214] "I am feeling very sad today."

[1215] 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.

[1216] An embodiment of the present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. This system provides more advanced support by incorporating an emotion engine that recognizes the user's emotions.

[1217] System Configuration

[1218] 1. User authentication and login process

[1219] A user starts the application, enters their username and password on the login screen, and clicks the login button. The device sends the authentication information to the server, which then authenticates the user against the database. If authentication is successful, the user can access the main screen.

[1220] 2. 24-hour support via AI chatbots

[1221] Users input their feelings of depression or anxiety through a chat interface and send them to a server via their device. The server then passes the information to an artificial intelligence engine, which generates an appropriate response.

[1222] 3. Emotion Recognition by Emotion Engine

[1223] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state. Based on the emotional state recognized by the emotion engine, the AI ​​engine adjusts the response and provides more appropriate support.

[1224] 4. Viewing the Response

[1225] The server sends the generated response to the device, which displays it to the user, who can then view the AI's response in a chat window and continue the conversation.

[1226] 5. Empathy and matching process

[1227] The server analyzes the user's consultation history and the emotion recognition results of the emotion engine, and then uses the matching engine to search for other users with the same emotional state or concerns. The matching results are notified to the user via their device, allowing them to receive empathy and support from other users.

[1228] 6. Expert Collaboration and Escalation

[1229] If the consultation is deemed serious, the server automatically creates a medical record based on the user's consultation content and emotion recognition results, and escalates the consultation to an expert. The device receives feedback and advice from the expert and displays it to the user.

[1230] 7. Freemium model vs. paid services

[1231] Users can choose between free and paid services, and if they wish to use the paid service, they enter their payment information on the payment screen. The terminal then sends the payment information to the server, which then confirms the payment and adds paid service authorization to the user's account. Paid services allow users to receive advanced mental health care.

[1232] Specific examples

[1233] For example, if a user is overcome by anxiety at night, they can use this system to receive advice 24 hours a day. When the user types "I've been feeling anxious and can't sleep lately" into the chat interface, the device sends it to the server. The emotion engine in the server analyzes this input and recognizes the user's anxious feelings. At the same time, the artificial intelligence engine generates an appropriate response (e.g., "Can you tell me more about what is causing you anxiety?") and displays it to the user via the device. The emotion engine then analyzes the user's further input, and if it detects serious anxiety, the server automatically escalates the case to a specialist and provides professional support.

[1234] The system allows users to receive appropriate mental health care in real time, helping them regain emotional composure.

[1235] The processing flow will be explained below.

[1236] The embodiment of the present invention is detailed through the following process steps.

[1237] User authentication and login process

[1238] Step 1:

[1239] The user launches the application. The user taps the application icon to launch it, and the login screen is displayed.

[1240] Step 2:

[1241] The user enters their login information (username and password) and clicks the Login button.

[1242] Step 3:

[1243] The device sends the login information to the server. The device encrypts the username and password and sends them to the server.

[1244] Step 4:

[1245] The server authenticates the user against a database. The server checks the login information it receives against its database to see if there is a match.

[1246] Step 5:

[1247] The server returns the authentication result to the terminal. If the authentication is successful, the server notifies the terminal of the success, and if the authentication is unsuccessful, it returns an error message.

[1248] Step 6:

[1249] The device notifies the user of the authentication result. If authentication is successful, the device displays the main screen, otherwise it displays an error message.

[1250] AI chatbot and emotion engine response

[1251] Step 7:

[1252] Users access the chat interface from the main screen and enter their concerns about their depression or anxiety.

[1253] Step 8:

[1254] The terminal transmits the input consultation content to the server.

[1255] Step 9:

[1256] The server receives the consultation content and passes it to the AI ​​engine, which analyzes it and generates an appropriate response.

[1257] Step 10:

[1258] The server sends the generated response to the terminal.

[1259] Step 11:

[1260] The device will display the response to the user, who will then be able to see the AI's response in the chat window.

[1261] Emotion recognition by emotion engine

[1262] Step 12:

[1263] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state.

[1264] Step 13:

[1265] The artificial intelligence engine adjusts the response based on the emotional state recognized by the emotion engine.

[1266] Step 14:

[1267] The server sends the adjusted response to the terminal.

[1268] Step 15:

[1269] The device displays the adjusted response to the user, allowing the user to continue the interaction with better support.

[1270] The empathy and matching process

[1271] Step 16:

[1272] The server analyzes the user's consultation history and emotion recognition results, and uses a matching engine to search for other users with the same emotional state or concerns.

[1273] Step 17:

[1274] The server sends the matching results to the device, which displays them to the user, who can then select the option to chat with other users who share their interests.

[1275] Expert collaboration and escalation

[1276] Step 18:

[1277] If the consultation is deemed serious, the server automatically creates a medical record based on the consultation content and emotion recognition results, and escalates the case to a specialist.

[1278] Step 19:

[1279] The expert reviews the chart and sends feedback to the server.

[1280] Step 20:

[1281] The server transfers the feedback from the expert to the device, which then displays it to the user, allowing the user to review the expert's advice and receive the necessary support.

[1282] Freemium model vs. paid services

[1283] Step 21:

[1284] If the user selects a paid service, the terminal displays a payment screen and the user enters payment information.

[1285] Step 22:

[1286] The terminal sends the payment information to the server.

[1287] Step 23:

[1288] The server verifies the payment via a payment gateway.

[1289] Step 24:

[1290] The server notifies the terminal whether the payment was successful or not, and the terminal displays the result to the user. If successful, the paid service becomes available.

[1291] These are the specific processing steps of the system that combines the emotion engine, which allows users to receive appropriate mental health care in real time and helps them regain emotional composure.

[1292] Example 2

[1293] 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."

[1294] In modern society, the number of people suffering from depression and anxiety is increasing. Systems that provide prompt and appropriate support for these mental health issues are needed. In particular, there is a growing need for systems that respond to users in real time, 24 hours a day, recognize their emotional state, and provide appropriate responses. There is also a need for systems that empathize with and support other users with the same concerns, as well as rapid escalation to professional support. However, current systems have difficulty meeting all of these requirements, necessitating the creation of a more comprehensive mental health care system.

[1295] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for providing an interface that allows users to consult about depression or anxiety at any time, a communication means for transmitting user input to the server in real time, an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response, a display means for providing the generated response to the user, an emotion engine for recognizing the user's emotional state, a means for adjusting the response based on the recognized emotion, a matching engine for analyzing the user's consultation history and matching with other users who have the same concerns, and an escalation means for escalating the consultation content to a specialist if the consultation content is serious. This enables more effective mental health care for users by recognizing emotional fluctuations and providing appropriate responses. It also enables advanced support through empathy and support between users and rapid escalation to a specialist.

[1296] A "user" is someone who uses the system to seek advice about feelings of depression or anxiety.

[1297] The "interface" refers to the screen and operating environment that users use to discuss their feelings of depression and anxiety.

[1298] "Communication means" refers to the process or technology used to transmit user input information to the server in real time.

[1299] A "server" is a computer system that receives input information from a user and performs appropriate processing or responds.

[1300] An "artificial intelligence engine" is software or algorithms that analyze incoming inquiries and generate appropriate responses.

[1301] A "display means" is a screen or device that allows the user to see the generated response.

[1302] An "emotion engine" is software or algorithms that analyze user input and recognize emotional states.

[1303] The "means for adjusting the response based on the recognized emotion" refers to a process or technology for appropriately changing the response of the artificial intelligence engine based on the emotion recognized by the emotion engine.

[1304] "Consultation history" is a record of consultations that a user has previously made through the system.

[1305] A "matching engine" is software or an algorithm that analyzes a user's consultation history and emotions to find other users with the same concerns.

[1306] "Escalation methods" are processes and techniques for notifying a specialist of a serious issue.

[1307] An "expert" is someone who has specialized knowledge and skills in relation to the content of the user's inquiry and who can provide appropriate support and advice.

[1308] A "medical record" is a document or data that organizes information such as consultation details and emotional state and is passed on to a specialist.

[1309] The "freemium model" is a business model that provides basic services for free and offers additional paid services.

[1310] "Payment method" means the process or technology used to process payments when a user uses a paid service.

[1311] The present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. The following describes in detail the modes for carrying out the present invention.

[1312] This system mainly consists of three components: a user terminal, a server, and various engines (artificial intelligence engine, emotion engine, and matching engine).

[1313] User device:

[1314] User devices include PCs, smartphones, tablets, and other devices. Users launch the dedicated application, enter their username and password on the login screen, and click the login button to be authenticated. Once login is successful, they are redirected to the main screen. When users feel depressed or anxious, they can enter their concerns into the application's chat interface and send them.

[1315] server:

[1316] The server is a computer system that receives authentication information and consultation details from the user. The server connects to a database (e.g., MySQL) to authenticate the user. The server then passes the received consultation details to an artificial intelligence engine to generate an appropriate response. For example, OpenAI's GPT-3 is used as the artificial intelligence engine. The generated response is sent to the user's device, which then displays it to the user.

[1317] Emotion Engine:

[1318] The emotion engine is software that analyzes user input and recognizes the user's emotional state. Specifically, it uses tools such as IBM Watson Emotion Analysis. If a user types, "I've been feeling anxious and can't sleep lately," the emotion engine analyzes the content and recognizes the emotion "anxiety." Based on this result, the artificial intelligence engine adjusts the response.

[1319] Matching Engine:

[1320] The matching engine is software that analyzes the user's consultation history and emotion recognition results to find other users with the same concerns. For example, a tool like Elasticsearch is used. This allows users with similar emotional states and concerns to be connected, promoting empathy and support.

[1321] Escalation Methods:

[1322] The escalation method is a process that notifies an expert if the consultation content is judged to be serious. The server creates an automatically generated medical record based on the consultation content along with the analysis results of the emotion engine, and passes it to the expert. The medical record is generated in PDF format or other formats, allowing the expert to quickly evaluate and provide advice. When the expert sends feedback to the server, it is displayed on the user's device.

[1323] Freemium model:

[1324] Users can choose between free and paid services. If they wish to use paid services in addition to the basic free service, they enter their credit card information on the payment screen and complete the payment. The server uses a payment gateway (e.g., Stripe) and, once payment is confirmed, adds permission for the paid service to the user's account. Paid services allow users to receive more advanced mental health care.

[1325] Examples:

[1326] For example, if a user is unable to sleep at night due to anxiety, they can use the system to receive advice 24 hours a day. When the user types "I've been unable to sleep lately due to anxiety" into the chat interface and sends it, the device sends it to the server. The emotion engine in the server analyzes this input and recognizes the "emotion of anxiety," and the artificial intelligence engine generates a response such as "Please tell me more about what is causing your anxiety," and sends it to the device. The response is then displayed to the user. If more serious anxiety is detected, the server automatically escalates the situation to a specialist and provides professional support.

[1327] Example prompts to input to a generative AI model:

[1328] "Please explain how users can use this system to get 24 / 7 support if they feel unsafe at night."

[1329] Thus, the present invention is a system that provides users with comprehensive, real-time, and appropriate mental health care, and is capable of efficiently recognizing emotions, promoting empathy, and escalating professional support.

[1330] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1331] Step 1:

[1332] The user launches the application, enters their username and password on the login screen, and clicks the login button.

[1333] Specific behavior:

[1334] A user launches the application, enters the username "example_user" and password "password123" on the login screen, and clicks the Login button.

[1335] Input: Username and Password

[1336] Output: User credentials are sent from the device to the server.

[1337] Step 2:

[1338] The terminal sends authentication information to the server, which then compares it with a database to authenticate the user.

[1339] Specific behavior:

[1340] The device sends authentication information (username and password) to the server as an HTTP POST request.

[1341] Input: Username and Password

[1342] Data processing: The authentication information is checked against a database on the server (e.g., MySQL).

[1343] Output: If authentication is successful, the server returns the URL of the main page in the HTTP response.

[1344] Step 3:

[1345] If the server succeeds in the authentication, it sends information to the terminal to transition to the main screen.

[1346] Specific behavior:

[1347] The server sends the URL of the main screen to the device in an HTTP response.

[1348] Input: Authentication information match result

[1349] Output: The URL of the main screen is sent to the device.

[1350] Step 4:

[1351] The user types their feelings of depression and anxiety into a chat interface and clicks the send button.

[1352] Specific behavior:

[1353] The user types "I've been feeling anxious and can't sleep lately" into the chat window and presses the send button.

[1354] Input: User's inquiry

[1355] Output: The consultation content is sent from the terminal to the server.

[1356] Step 5:

[1357] The device sends the consultation details to the server, which then passes the details to the artificial intelligence engine.

[1358] Specific behavior:

[1359] The device sends the entered consultation details to the server, which then passes them to an artificial intelligence engine (e.g., OpenAI GPT-3).

[1360] Input: User's inquiry

[1361] Data processing: An artificial intelligence engine analyzes the consultation content and generates an appropriate response.

[1362] Output: The generated response is returned to the server.

[1363] Step 6:

[1364] The server sends the generated response to the terminal.

[1365] Specific behavior:

[1366] The server sends the response obtained from the artificial intelligence engine to the terminal.

[1367] Input: The generated response

[1368] Output: The response is sent to the terminal.

[1369] Step 7:

[1370] The terminal displays the response received from the server to the user.

[1371] Specific behavior:

[1372] The terminal displays the generated response in the chat window.

[1373] Input: Response from the server

[1374] Output: Response displayed in the chat window

[1375] Step 8:

[1376] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state.

[1377] Specific behavior:

[1378] The server sends the user's input information to an emotion engine (e.g., IBM Watson Emotion Analysis) to analyze the user's emotional state.

[1379] Input: User's inquiry

[1380] Data processing: The emotion engine analyzes the input information and recognizes the emotional state.

[1381] Output: Emotional state recognition result

[1382] Step 9:

[1383] The server receives the recognition results from the emotion engine and instructs the artificial intelligence engine to adjust the response.

[1384] Specific behavior:

[1385] The server instructs the artificial intelligence engine to adjust the response based on the recognition results of the emotion engine.

[1386] Input: Emotional state recognition results

[1387] Data processing: Adjusting responses based on recognition results.

[1388] Output: The adjusted response

[1389] Step 10:

[1390] The server sends the adjusted response to the user terminal.

[1391] Specific behavior:

[1392] The server sends the adjusted response to the user's device in an HTTP response.

[1393] Input: Adjusted response

[1394] Output: The adjusted response is sent to the terminal.

[1395] Step 11:

[1396] The user can see the tailored response in the chat window and continue the conversation.

[1397] Specific behavior:

[1398] The user sees the response displayed on the screen.

[1399] Input: Adjusted response

[1400] Output: User confirmation and next input

[1401] Step 12:

[1402] The server analyzes the user's consultation history and the emotion recognition results of the emotion engine, and uses a matching engine to search for other users who have the same emotional state or concerns.

[1403] Specific behavior:

[1404] The server retrieves the user's consultation history and emotion engine data from a database (e.g., MongoDB) and analyzes it.

[1405] Input: Consultation history and emotion recognition results

[1406] Data processing: Analyze using a matching engine (e.g. Elasticsearch).

[1407] Output: Matching results

[1408] Step 13:

[1409] The server notifies the user's device of the matching results, encouraging empathy and support between users.

[1410] Specific behavior:

[1411] The server sends the matching results to the user's device as an HTTP response and displays a notification.

[1412] Input: Matching results

[1413] Output: Notification of sympathy and support between users

[1414] Step 14:

[1415] If the consultation is serious, the server will automatically create a medical record and escalate the matter to a specialist.

[1416] Specific behavior:

[1417] If the server detects serious anxiety from the analysis results of the emotion engine, it automatically generates a medical record (e.g., PDF format).

[1418] Input: Emotion recognition results and consultation details

[1419] Data processing: Automatically generate medical records and send them to specialists.

[1420] Output: Send medical record to specialist

[1421] Step 15:

[1422] The expert sends feedback and advice back to the server, which the device displays to the user.

[1423] Specific behavior:

[1424] The expert sends feedback and advice back to the server, which then sends it to the user's device, which displays the advice.

[1425] Input: Expert feedback

[1426] Output: Advice displayed on the user's terminal

[1427] Step 16:

[1428] If the user selects a paid service, they enter payment information on the payment screen, and the terminal sends that information to the server.

[1429] Specific behavior:

[1430] The user clicks the "Upgrade to paid service" button and enters credit card information, etc. The terminal sends the payment information to the server.

[1431] Input: Payment Information

[1432] Output: Payment information is sent to the server.

[1433] Step 17:

[1434] The server verifies the payment information and, if successful, adds authorization for the paid service to the user account.

[1435] Specific behavior:

[1436] Your server verifies the payment with a payment gateway (e.g., Stripe) and, if successful, adds authorization for paid services to the user account.

[1437] Input: Payment Information

[1438] Data Processing: Verify payment information and update account permissions

[1439] Output: The paid service entitlement is added to the user account.

[1440] Step 18:

[1441] The server notifies the user terminal that a paid service has become available, and the terminal displays this to the user.

[1442] Specific behavior:

[1443] The server sends a notification to the user's device saying "Paid service is now available." The device displays it to the user.

[1444] Input: Permission update result for paid service

[1445] Output: A notification to the user about the paid service is displayed.

[1446] (Application example 2)

[1447] 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."

[1448] Conventional mental healthcare systems have difficulty recognizing users' emotional state and stress levels in real time and responding appropriately. Furthermore, in brick-and-mortar stores, if a store clerk is emotionally depressed or stressed, this can affect customer service and reduce customer satisfaction. Furthermore, when escalating serious consultations to specialists, many systems require users to take action themselves, and lack efficient methods such as automated medical record creation. To address these issues, a system with more advanced emotion recognition and stress monitoring capabilities is needed to strengthen mental health support in brick-and-mortar stores.

[1449] 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.

[1450] In this invention, the server includes: means for providing an interface that allows users to consult about depression or anxiety at any time; communication means for transmitting user input to the server in real time; an artificial intelligence engine that analyzes the received consultation content using specific analysis means and generates an appropriate response; display means for providing the generated response to the user; a matching engine that analyzes the user's consultation history and matches them with other users who have the same problem; escalation means for escalating the consultation to a specialist if the consultation content is serious; emotion recognition means for recognizing and analyzing the user's emotions in real time; means for adjusting and providing support according to the emotional state based on the emotion recognition means; means for monitoring the stress level of store staff; and means for providing customer support in a physical store. This enables the emotional states of users and store staff to be recognized in real time, enabling appropriate mental health care and customer support.

[1451] "User" refers to an individual who uses the mental health care system.

[1452] "Interface" refers to the screen and operation methods that provide users with a means to discuss their feelings of depression or anxiety.

[1453] "Communication Method" refers to the technology or protocol used to transmit user input to a server in real time.

[1454] "Artificial intelligence engine" refers to AI technology that analyzes the content of inquiries received and generates appropriate responses.

[1455] "Display means" refers to a display or screen on which the generated response is shown to the user.

[1456] A "matching engine" refers to technology that analyzes a user's consultation history and connects them with other users who have the same concerns.

[1457] "Escalation measures" refer to the means of conveying information to a specialist when the consultation matter is serious.

[1458] "Emotion recognition means" refers to technology for recognizing and analyzing a user's emotional state in real time.

[1459] "Means for monitoring stress levels" refers to technology for recognizing and monitoring the stress levels of store employees.

[1460] "Means of providing customer service support" refers to the techniques and methods that enable store staff to provide better service to customers in physical stores.

[1461] The present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. Specifically, the system includes an interface, communication means, an artificial intelligence engine, emotion recognition means, display means, a matching engine, and escalation means.

[1462] System Configuration

[1463] 1. Interface

[1464] The system provides a screen and operation method that allows users to consult about their depression or anxiety. Users input their concerns through this interface.

[1465] 2. Means of communication

[1466] User input is sent to the server in real time using HTTP or HTTPS as the communication protocol.

[1467] 3. Artificial Intelligence Engine

[1468] The system analyzes the received consultation content and generates an appropriate response using a generative AI model that uses deep learning technology.

[1469] 4. Emotion recognition means

[1470] It analyzes user input and recognizes their emotional state in real time. The emotion recognition engine uses natural language processing technology to analyze emotions.

[1471] 5. Display means

[1472] It has a display, usually a smartphone or tablet, to show the generated response to the user.

[1473] 6. Matching Engine

[1474] The system analyzes the user's consultation history and matches them with other users who have the same concerns. The matching algorithm uses collaborative filtering technology.

[1475] 7. Escalation Methods

[1476] If the consultation is serious, it will be escalated to a specialist. The server will automatically generate a medical record and send it to the specialist.

[1477] Specific examples

[1478] If a user experiences anxiety at night, they can use this system to receive advice 24 hours a day. When the user types "I've been feeling anxious and can't sleep lately" into the interface, the device sends this to the server. An emotion recognition system within the server analyzes this input and recognizes the user's feelings of anxiety. At the same time, an artificial intelligence engine generates an appropriate response (for example, "Could you tell me more about what is causing you anxiety?") and displays it to the user via the device.

[1479] Furthermore, the emotion recognition means continuously analyzes the user's input, and if it detects a high-stress state, the server automatically escalates to an expert and provides detailed feedback and advice.

[1480] Prompt Sentence Examples

[1481] User: "I've been so stressed lately I can't concentrate on my work."

[1482] AI chatbot: "Tell me what's causing you stress"

[1483] This example allows users to receive prompt and appropriate mental health care.

[1484] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1485] Step 1:

[1486] The user inputs the content of their problem into the interface. The input content is text information such as "I've been feeling anxious lately and can't sleep."

[1487] Step 2:

[1488] The terminal sends user input to the server in real time using HTTP or HTTPS as the communication protocol. The input data is sent to the server in JSON format.

[1489] Step 3:

[1490] The server analyzes the received input data. First, the server's emotion recognition means analyzes the text using natural language processing technology to recognize the user's emotional state in real time. Through this analysis, the emotion contained in the input is labeled as "anxiety."

[1491] Step 4:

[1492] The server generates an appropriate response using a generative AI model based on the emotion recognition results. The AI ​​engine generates a response (e.g., "Tell me more about what causes anxiety") according to the user's emotion label "anxiety."

[1493] Step 5:

[1494] The server sends the generated response to the device, which again encodes the response in JSON format and sends it to the device using the HTTP / S protocol.

[1495] Step 6:

[1496] The terminal provides the response received from the server to the user, specifically, by displaying the generated response message on the display of the terminal.

[1497] Step 7:

[1498] If the user enters the information again, the process is repeated. The emotion recognition means in the server continuously monitors and analyzes the user's emotional state, and if it detects a high stress state, the escalation means is activated. The server then sends the automatically generated medical record to a specialist to provide further support to the user.

[1499] Step 8:

[1500] The matching engine analyzes the user's consultation history. The server uses collaborative filtering technology to search for other users with the same concerns and make appropriate matches. The matching results are sent to the device and displayed on the screen.

[1501] Step 9:

[1502] When the consultation is escalated to an expert by the escalation means, the server receives feedback from the expert and provides it to the user. The terminal displays the feedback and provides the user with professional advice.

[1503] These steps can help users receive prompt and appropriate mental health care and promote emotional stability.

[1504] 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.

[1505] 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.

[1506] 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.

[1507] [Fourth embodiment]

[1508] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1509] 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.

[1510] 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).

[1511] 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.

[1512] 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.

[1513] 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).

[1514] 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.

[1515] 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.

[1516] 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.

[1517] 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.

[1518] 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.

[1519] 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.

[1520] 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."

[1521] The embodiment of the present invention is a comprehensive system that allows users to express their depression and anxiety and receive appropriate support. The system has the following main functions:

[1522] 1. User authentication and login process

[1523] The user starts the application, enters their username and password on the login screen, and clicks the login button. The device sends this authentication information to the server, which then authenticates the user by checking it against a database. If authentication is successful, the user is taken to the main screen and can use the system.

[1524] 2. 24-hour support via AI chatbots

[1525] The user enters their concerns about depression or anxiety on the chat screen and sends them. The device then sends the information to a server, where an artificial intelligence engine analyzes the received information and generates an appropriate response. The generated response is provided to the user in real time, allowing them to express their feelings and receive support through dialogue.

[1526] 3. Empathy and matching process

[1527] The server analyzes the user's consultation history and current consultation content, and searches a database for other users with the same concerns. A matching engine is used to make it easier for users to connect with other users in similar situations, allowing them to receive empathy and support. The matching results are notified to the user via their device, and they can start chatting with other users if necessary.

[1528] 4. Collaboration and response with experts

[1529] If the problem is deemed serious, the server will escalate the issue to a specialist using an automatically generated medical record based on the consultation details. The specialist will then provide appropriate counseling based on the information transferred to them. The device will then display feedback and advice from the specialist to the user in real time, allowing the user to receive the support they need.

[1530] 5. Freemium model vs. paid services

[1531] Users can choose between free and paid services within the application. Users who wish to use paid services enter their payment information on the payment screen and send it to the server via their device. The server then confirms the payment and adds paid service authorization to the user's account. Paid services allow users to receive advanced mental health care.

[1532] The above is an embodiment of the present invention. This system provides users with easily accessible mental health care and provides specific means for regaining emotional composure.

[1533] The processing flow will be explained below.

[1534] Step 1:

[1535] The user launches the application. The user taps the application icon to launch it, and the login screen is displayed.

[1536] Step 2:

[1537] The user enters their login information (username and password) and clicks the Login button.

[1538] Step 3:

[1539] The device sends the login information to the server. The device encrypts the username and password and sends them to the server.

[1540] Step 4:

[1541] The server authenticates the user against a database. The server checks the login information it receives against its database to see if there is a match.

[1542] Step 5:

[1543] The server returns the authentication result to the terminal. If the authentication is successful, the server notifies the terminal of the success, and if the authentication is unsuccessful, it returns an error message.

[1544] Step 6:

[1545] The device notifies the user of the authentication result. If authentication is successful, the device displays the main screen, otherwise it displays an error message.

[1546] Step 7:

[1547] Users access the chat interface from the main screen and enter their concerns about depression or anxiety.

[1548] Step 8:

[1549] The terminal transmits the input consultation content to the server.

[1550] Step 9:

[1551] The server receives the consultation content and passes it to the AI ​​engine, which analyzes the content and generates an appropriate response.

[1552] Step 10:

[1553] The server sends the generated response to the terminal.

[1554] Step 11:

[1555] The device will display the response to the user, who will then be able to see the AI's response in the chat window.

[1556] Step 12:

[1557] The server analyzes the user's consultation history and uses a matching engine to search for other users with the same concerns.

[1558] Step 13:

[1559] The server sends the matching results to the device, which displays them to the user, who can then select the option to chat with other users who share their interests.

[1560] Step 14:

[1561] If the consultation is deemed serious, the server will automatically create a medical record based on the consultation content and escalate the case to a specialist.

[1562] Step 15:

[1563] The expert reviews the chart and sends feedback to the server.

[1564] Step 16:

[1565] The server transfers the feedback from the expert to the device, which then displays it to the user, allowing the user to review the expert's advice and receive the necessary support.

[1566] Step 17:

[1567] If the user selects a paid service, the terminal displays a payment screen and the user enters payment information.

[1568] Step 18:

[1569] The terminal sends the payment information to the server, which verifies the payment via a payment gateway.

[1570] Step 19:

[1571] The server notifies the terminal whether the payment was successful or not, and the terminal displays the result to the user. If successful, the paid service becomes available.

[1572] These are the processing steps of the system, which allows users to vent their feelings and receive support from experts if necessary.

[1573] Example 1

[1574] 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."

[1575] In recent years, mental health problems have been on the rise, creating a need for systems that allow users to easily seek advice about depression and anxiety at any time. However, current systems are inadequate in terms of real-time response, expert response, and empathy matching with other users. In particular, they do not address the needs of users who require smooth escalation to an expert when the issue is serious, or payment for paid services. The present invention aims to solve these problems.

[1576] 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.

[1577] In this invention, the server includes: means for providing an interface that allows users to consult about depression or anxiety at any time; communication means for transmitting user input to the server in real time; an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response; display means for providing the generated response to the user; a matching engine for analyzing the user's consultation history and matching the user with other users who have the same problem; escalation means for escalating the consultation content to a specialist if the consultation content is serious; means for executing user authentication and login process; means for allowing the user to select between a free or paid freemium model; and payment means for processing additional fees for paid services. This allows users to easily consult about their emotions, receive sympathy, and, if necessary, receive professional support.

[1578] "User" refers to any individual or organization that uses this system.

[1579] "Interface" refers to the screen and input means through which a user interacts with a system.

[1580] "Communication means" refers to the devices and protocols that transmit user input to the server in real time.

[1581] "Artificial intelligence engine" refers to software or algorithms that analyze incoming inquiries and generate appropriate responses.

[1582] "Display means" refers to a device or system that provides the generated response to the user visually or audibly.

[1583] A "matching engine" refers to an algorithm or software that analyzes a user's consultation history and connects them with other users who have the same concerns.

[1584] "Escalation mechanisms" refer to mechanisms and processes for transferring serious issues to specialists.

[1585] "User authentication" refers to the process for verifying a user's identity and controlling access to a system.

[1586] "Login process" refers to the authentication steps a user goes through to access a system.

[1587] The "freemium model" refers to a business model that combines free and paid services.

[1588] "Payment Method" means an electronic payment system for processing fees for Paid Services.

[1589] MODE FOR CARRYING OUT THE INVENTION

[1590] The present invention relates to a comprehensive system that allows users to express their depression and anxiety and receive appropriate support, with easy user access and real-time response capabilities.

[1591] User authentication and login process

[1592] A user starts an application and enters their username and password on the login screen. The device sends this authentication information to the server, which then authenticates the user by checking it against a database (e.g., MySQL). If authentication is successful, the server sends the result back to the device, which then redirects the user to the main screen.

[1593] 24-hour support by AI chatbot

[1594] The user enters their concerns about depression or anxiety into the chat screen and sends them. The device then sends the information to the server, which uses an artificial intelligence engine (e.g., OpenAI GPT-3) to analyze the content and generate an appropriate response. The generated response is then sent back to the device, which displays it to the user in real time.

[1595] The empathy and matching process

[1596] The server analyzes the user's consultation history and current consultation content. Using a matching engine (e.g., Elasticsearch), it searches the database for other users with the same concerns and finds users with common interests. The server notifies the device of the matching results, and the device notifies the user. The user receives the notification and can start chatting with other users if necessary.

[1597] Collaboration and response with experts

[1598] The server automatically creates a medical record based on the consultation content that is judged to be a serious problem and escalates it to an expert. The expert then provides counseling based on the medical record. The terminal displays feedback and advice from the expert to the user in real time.

[1599] Freemium model vs. paid services

[1600] Users can choose between free and paid services within the application. Users who wish to use paid services enter their payment information on the payment screen and send it to the server via their device. The server then confirms the payment and adds the paid service authorization to the user's account. By using the paid service, users can receive advanced mental health care.

[1601] Examples of specific examples and prompts

[1602] 1. When a user logs in to the app, they enter "example_user" and "password123" and click the Login button.

[1603] 2. The device sends this information to the server, which then performs authentication.

[1604] 3. The user types, "I've been stressed out lately and can't sleep," into the chat screen and sends it.

[1605] 4. The device sends this information to a server, and the GPT-3 artificial intelligence engine generates a response: "That's tough. Tell me more about what's causing you stress."

[1606] 5. The terminal displays the response to the user.

[1607] 6. The server searches for other users with similar problems and notifies the user via their device, "There is another user with the same problem. Would you like to connect?"

[1608] Example prompt sentence:

[1609] Chatbot prompt: "Generate an appropriate response to the user's message: 'I've been feeling stressed lately and can't sleep.'"

[1610] Matching engine prompt: "Based on the user's complaint 'I'm feeling increasingly stressed,' find other users with similar concerns."

[1611] The above is an embodiment of the present invention. This system allows users to receive prompt and appropriate mental health care and provides specific means for regaining emotional composure.

[1612] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1613] Step 1:

[1614] The user starts the application and enters their username and password on the login screen. The entered information is in the form of a username and password. The device sends this authentication information to the server. The server receives it and verifies the username and password against a database to perform authentication. If authentication is successful, the server returns a success message to the device, and the device transitions the user to the main screen.

[1615] Specific behavior:

[1616] The user enters the username "example_user" and password "example_pass" and clicks the Login button.

[1617] The terminal transmits the entered authentication information to the server.

[1618] The server checks the information against the database and sends a message to the terminal indicating successful authentication.

[1619] The device will transition to the main screen.

[1620] Step 2:

[1621] The user moves to the chat screen, enters the content of their consultation, and sends it. The entered content is in text format as the user's consultation content. The device sends this input content to the server. The server receives it and passes it to the artificial intelligence engine. The artificial intelligence engine analyzes the consultation content and generates an appropriate response. The generated response is a response message in text format. The server sends the generated response to the device, which displays it to the user.

[1622] Specific behavior:

[1623] The user types, "I've been feeling stressed lately and can't sleep," and clicks the send button.

[1624] The device sends the input to the server.

[1625] The server requests an analysis from an artificial intelligence engine (e.g., GPT-3) and receives a response message.

[1626] The server sends a response message to the terminal, which displays it to the user.

[1627] Step 3:

[1628] Based on the user's consultation content and past consultation history, the server begins the process of searching for other users who share the same concerns. The input data is text data of the user's current and past consultation content. The server passes this data to a matching engine to search for users with similar consultation content. The matching engine outputs the results and returns them to the server. The output data is a list of users with similar consultation content. The server sends the results to the terminal, which then displays matching suggestions to the user.

[1629] Specific behavior:

[1630] The server analyzes the user's current and past consultations.

[1631] The server passes the data to a matching engine (e.g. Elasticsearch) to search for other users with similar concerns.

[1632] The matching engine generates the results and returns them to the server.

[1633] The server sends the matching results to the device, and the device notifies the user, "There is a user with the same problem. Would you like to connect?"

[1634] Step 4:

[1635] If the consultation is serious, the server starts the process of escalating it to an expert. The input data is text data of the serious consultation content. The server creates an automatically generated medical record and sends it to the expert. The medical record data includes a summary of the consultation content and related information. The expert receives the medical record and provides counseling. The output data is text data of feedback and advice from the expert. The server receives this and sends it to the terminal, which displays it to the user.

[1636] Specific behavior:

[1637] The server analyzes the seriousness of the consultation and creates a medical record using an automatic medical record generation function.

[1638] The server sends the medical record to the specialist.

[1639] The expert provides counseling based on the medical records and returns feedback to the server.

[1640] The server sends feedback to the device, which displays it to the user.

[1641] Step 5:

[1642] If the user wishes to use a paid service, the payment process is initiated. The input data is the user's payment information and the selected paid service. The terminal sends this information to the server. The server confirms the payment via the payment processing service. The output data is a confirmation message that the payment is complete. The server notifies the terminal that the payment is successful, and the terminal adds authorization for the paid service to the user's account.

[1643] Specific behavior:

[1644] The user selects the paid service "High-end Counseling" and enters payment information.

[1645] The terminal sends the payment information to the server.

[1646] The server verifies the payment through a payment processing service (e.g., Stripe).

[1647] The server notifies the terminal that the payment has been completed, and the terminal adds authorization for the paid service to the user account.

[1648] The device notifies the user, "Advanced counseling is available."

[1649] (Application example 1)

[1650] 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."

[1651] In recent years, the number of people experiencing stress and anxiety has increased, making mental health care more important than ever. However, many people are unable to access appropriate support due to time and financial constraints, and are therefore unable to consult with a specialist. Furthermore, existing mental health support tools lack the functionality to provide optimal content tailored to each individual user's emotional state. Therefore, there is a need for a system that allows users to easily seek advice about their depression or anxiety, and that can provide optimal content tailored to their emotional state.

[1652] 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.

[1653] In this invention, the server includes means for providing an interface that allows users to consult about depression or anxiety at any time, communication means for transmitting user input to the server in real time, an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response, display means for providing the generated response to the user, a matching engine for analyzing the user's consultation history and matching with other users who have the same problem, escalation means for escalating the consultation to a specialist if the consultation content is serious, and content recommendation means for recommending optimal content based on the user's emotional state. This allows users to easily receive appropriate mental health care and regain emotional composure through optimal content tailored to their emotional state at the time.

[1654] A "user" is an individual who uses the system to discuss feelings of depression or anxiety.

[1655] An "interface" is a screen or input device through which a user inputs their feelings of depression or anxiety.

[1656] "Communication means" refers to a host device or internet connection for transmitting user input to a server in real time.

[1657] The "artificial intelligence engine" is an algorithm that analyzes the content of the consultation received and generates an appropriate response.

[1658] "Display means" refers to a display or mobile screen for providing the generated response to the user in real time.

[1659] The "matching engine" is an algorithm that analyzes a user's consultation history and connects them with other users who have the same concerns.

[1660] "Escalation means" refers to communication devices or software functions that transfer information to a specialist when the consultation content is serious.

[1661] A "content recommendation method" is an algorithm or system that recommends optimal content based on the user's emotional state.

[1662] To implement this invention, we will build a system that allows users to easily receive mental health care. The main components include a user interface, communication means, an artificial intelligence engine, display means, a matching engine, escalation means, and content recommendation means.

[1663] First, the user interface provides a screen and input device that allows users to input their feelings of depression and anxiety. This interface is implemented as a smartphone application. The data entered by the user is sent to a server in real time via a communication means. An internet connection is required for this communication.

[1664] The server analyzes the received user's inquiry using an AI engine and generates an appropriate response. This AI engine implements a model for sentiment analysis using Hugging Face's Transformers library. The analyzed results are provided to the user via a display means, which can be a smartphone display or a mobile screen.

[1665] The server also has a matching engine that analyzes the user's consultation history and matches them with other users who have the same concerns. This matching engine searches the database for users with similar concerns and helps them support each other.

[1666] Furthermore, if the consultation content is serious, the information is transferred to a specialist using an escalation means. This escalation means includes a communication device and a dedicated software function. Once the information is escalated to the specialist, counseling is provided based on the automatically generated medical record.

[1667] Finally, the server has a content recommendation mechanism that recommends optimal content based on the user's emotional state. This content could include relaxing music, guided meditations, videos, etc. This allows users to receive optimal support tailored to their emotional state at any given time. This recommendation algorithm is also implemented using Hugging Face's library.

[1668] For example, if a user types, "I'm feeling really down today," the sentiment analysis model will detect the negative emotion and respond with, "I understand, and I'll provide you with specific support." It will also display links to relaxing music and guided meditations based on the user's emotional state.

[1669] Example prompt sentence:

[1670] "I am feeling very sad today."

[1671] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1672] Step 1:

[1673] Users input their feelings of depression and anxiety through a smartphone interface. This input is in text format, and the input data includes sentences such as "I'm feeling very depressed today."

[1674] Input: Text data showing feelings of depression and anxiety

[1675] Output: Sends input data to the server

[1676] Step 2:

[1677] The device uses a communication means to transmit text data entered by the user to a server in real time, and this communication requires an internet connection.

[1678] Input: Input data (text format)

[1679] Output: Data sent to the server

[1680] Step 3:

[1681] The server then analyzes the received user text data using an artificial intelligence engine, using Hugging Face's Transformers library for sentiment analysis.

[1682] Input: Data sent to the server (text format)

[1683] Data Processing: Sentiment Analysis

[1684] Output: Sentiment analysis result (e.g., negative)

[1685] Step 4:

[1686] The server generates an appropriate response based on the results of the sentiment analysis, and the generated response is provided to the user in real time.

[1687] Input: Sentiment analysis results

[1688] Data calculation: response generation

[1689] Output: Response (e.g. "I understand, I'll provide specific assistance.")

[1690] Step 5:

[1691] The terminal provides the response sent from the server to the user using a display means, such as the display of the smartphone.

[1692] Input: The response sent by the server

[1693] Output: Response displayed on the smartphone display

[1694] Step 6:

[1695] The server analyzes the user's consultation history and matches them with other users who have the same concerns. This process uses a matching engine to search a database for users with similar concerns.

[1696] Input: User's consultation history

[1697] Data processing: consultation history analysis, user matching

[1698] Output: Matching results

[1699] Step 7:

[1700] If the consultation is serious, the server uses an escalation method to transfer the consultation to a specialist, using an automatically generated medical record.

[1701] Input: Serious consultation content

[1702] Data calculation: medical record generation, transfer to specialist

[1703] Output: Specialist notification and medical records

[1704] Step 8:

[1705] The server uses content recommendation tools to recommend optimal content based on the user's emotional state, such as guided meditations or relaxing music.

[1706] Input: Sentiment analysis results

[1707] Data Computing: Content Recommendation

[1708] Output: Recommended content (e.g., a link to a guided meditation)

[1709] Example prompt sentence:

[1710] "I am feeling very sad today."

[1711] 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.

[1712] An embodiment of the present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. This system provides more advanced support by incorporating an emotion engine that recognizes the user's emotions.

[1713] System Configuration

[1714] 1. User authentication and login process

[1715] A user starts the application, enters their username and password on the login screen, and clicks the login button. The device sends the authentication information to the server, which then authenticates the user against the database. If authentication is successful, the user can access the main screen.

[1716] 2. 24-hour support via AI chatbots

[1717] Users input their feelings of depression or anxiety through a chat interface and send them to a server via their device. The server then passes the information to an artificial intelligence engine, which generates an appropriate response.

[1718] 3. Emotion Recognition by Emotion Engine

[1719] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state. Based on the emotional state recognized by the emotion engine, the AI ​​engine adjusts the response and provides more appropriate support.

[1720] 4. Viewing the Response

[1721] The server sends the generated response to the device, which displays it to the user, who can then view the AI's response in a chat window and continue the conversation.

[1722] 5. Empathy and matching process

[1723] The server analyzes the user's consultation history and the emotion recognition results of the emotion engine, and then uses the matching engine to search for other users with the same emotional state or concerns. The matching results are notified to the user via their device, allowing them to receive empathy and support from other users.

[1724] 6. Expert Collaboration and Escalation

[1725] If the consultation is deemed serious, the server automatically creates a medical record based on the user's consultation content and emotion recognition results, and escalates the consultation to an expert. The device receives feedback and advice from the expert and displays it to the user.

[1726] 7. Freemium model vs. paid services

[1727] Users can choose between free and paid services, and if they wish to use the paid service, they enter their payment information on the payment screen. The terminal then sends the payment information to the server, which then confirms the payment and adds paid service authorization to the user's account. Paid services allow users to receive advanced mental health care.

[1728] Specific examples

[1729] For example, if a user is overcome by anxiety at night, they can use this system to receive advice 24 hours a day. When the user types "I've been feeling anxious and can't sleep lately" into the chat interface, the device sends it to the server. The emotion engine in the server analyzes this input and recognizes the user's anxious feelings. At the same time, the artificial intelligence engine generates an appropriate response (e.g., "Can you tell me more about what is causing you anxiety?") and displays it to the user via the device. The emotion engine then analyzes the user's further input, and if it detects serious anxiety, the server automatically escalates the case to a specialist and provides professional support.

[1730] The system allows users to receive appropriate mental health care in real time, helping them regain emotional composure.

[1731] The processing flow will be explained below.

[1732] The embodiment of the present invention is detailed through the following process steps.

[1733] User authentication and login process

[1734] Step 1:

[1735] The user launches the application. The user taps the application icon to launch it, and the login screen is displayed.

[1736] Step 2:

[1737] The user enters their login information (username and password) and clicks the Login button.

[1738] Step 3:

[1739] The device sends the login information to the server. The device encrypts the username and password and sends them to the server.

[1740] Step 4:

[1741] The server authenticates the user against a database. The server checks the login information it receives against its database to see if there is a match.

[1742] Step 5:

[1743] The server returns the authentication result to the terminal. If the authentication is successful, the server notifies the terminal of the success, and if the authentication is unsuccessful, it returns an error message.

[1744] Step 6:

[1745] The device notifies the user of the authentication result. If authentication is successful, the device displays the main screen, otherwise it displays an error message.

[1746] AI chatbot and emotion engine response

[1747] Step 7:

[1748] Users access the chat interface from the main screen and enter their concerns about their depression or anxiety.

[1749] Step 8:

[1750] The terminal transmits the input consultation content to the server.

[1751] Step 9:

[1752] The server receives the consultation content and passes it to the AI ​​engine, which analyzes it and generates an appropriate response.

[1753] Step 10:

[1754] The server sends the generated response to the terminal.

[1755] Step 11:

[1756] The device will display the response to the user, who will then be able to see the AI's response in the chat window.

[1757] Emotion recognition by emotion engine

[1758] Step 12:

[1759] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state.

[1760] Step 13:

[1761] The artificial intelligence engine adjusts the response based on the emotional state recognized by the emotion engine.

[1762] Step 14:

[1763] The server sends the adjusted response to the terminal.

[1764] Step 15:

[1765] The device displays the adjusted response to the user, allowing the user to continue the interaction with better support.

[1766] The empathy and matching process

[1767] Step 16:

[1768] The server analyzes the user's consultation history and emotion recognition results, and uses a matching engine to search for other users with the same emotional state or concerns.

[1769] Step 17:

[1770] The server sends the matching results to the device, which displays them to the user, who can then select the option to chat with other users who share their interests.

[1771] Expert collaboration and escalation

[1772] Step 18:

[1773] If the consultation is deemed serious, the server automatically creates a medical record based on the consultation content and emotion recognition results, and escalates the case to a specialist.

[1774] Step 19:

[1775] The expert reviews the chart and sends feedback to the server.

[1776] Step 20:

[1777] The server transfers the feedback from the expert to the device, which then displays it to the user, allowing the user to review the expert's advice and receive the necessary support.

[1778] Freemium model vs. paid services

[1779] Step 21:

[1780] If the user selects a paid service, the terminal displays a payment screen and the user enters payment information.

[1781] Step 22:

[1782] The terminal sends the payment information to the server.

[1783] Step 23:

[1784] The server verifies the payment via a payment gateway.

[1785] Step 24:

[1786] The server notifies the terminal whether the payment was successful or not, and the terminal displays the result to the user. If successful, the paid service becomes available.

[1787] These are the specific processing steps of the system that combines the emotion engine, which allows users to receive appropriate mental health care in real time and helps them regain emotional composure.

[1788] Example 2

[1789] 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."

[1790] In modern society, the number of people suffering from depression and anxiety is increasing. Systems that provide prompt and appropriate support for these mental health issues are needed. In particular, there is a growing need for systems that respond to users in real time, 24 hours a day, recognize their emotional state, and provide appropriate responses. There is also a need for systems that empathize with and support other users with the same concerns, as well as rapid escalation to professional support. However, current systems have difficulty meeting all of these requirements, necessitating the creation of a more comprehensive mental health care system.

[1791] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for providing an interface that allows users to consult about depression or anxiety at any time, a communication means for transmitting user input to the server in real time, an artificial intelligence engine for analyzing the received consultation content and generating an appropriate response, a display means for providing the generated response to the user, an emotion engine for recognizing the user's emotional state, a means for adjusting the response based on the recognized emotion, a matching engine for analyzing the user's consultation history and matching with other users who have the same concerns, and an escalation means for escalating the consultation content to a specialist if the consultation content is serious. This enables more effective mental health care for users by recognizing emotional fluctuations and providing appropriate responses. It also enables advanced support through empathy and support between users and rapid escalation to a specialist.

[1792] A "user" is someone who uses the system to seek advice about feelings of depression or anxiety.

[1793] The "interface" refers to the screen and operating environment that users use to discuss their feelings of depression and anxiety.

[1794] "Communication means" refers to the process or technology used to transmit user input information to the server in real time.

[1795] A "server" is a computer system that receives input information from a user and performs appropriate processing or responds.

[1796] An "artificial intelligence engine" is software or algorithms that analyze incoming inquiries and generate appropriate responses.

[1797] A "display means" is a screen or device that allows the user to see the generated response.

[1798] An "emotion engine" is software or algorithms that analyze user input and recognize emotional states.

[1799] The "means for adjusting the response based on the recognized emotion" refers to a process or technology for appropriately changing the response of the artificial intelligence engine based on the emotion recognized by the emotion engine.

[1800] "Consultation history" is a record of consultations that a user has previously made through the system.

[1801] A "matching engine" is software or an algorithm that analyzes a user's consultation history and emotions to find other users with the same concerns.

[1802] "Escalation methods" are processes and techniques for notifying a specialist of a serious issue.

[1803] An "expert" is someone who has specialized knowledge and skills in relation to the content of the user's inquiry and who can provide appropriate support and advice.

[1804] A "medical record" is a document or data that organizes information such as consultation details and emotional state and is passed on to a specialist.

[1805] The "freemium model" is a business model that provides basic services for free and offers additional paid services.

[1806] "Payment method" means the process or technology used to process payments when a user uses a paid service.

[1807] The present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. The following describes in detail the modes for carrying out the present invention.

[1808] This system mainly consists of three components: a user terminal, a server, and various engines (artificial intelligence engine, emotion engine, and matching engine).

[1809] User device:

[1810] User devices include PCs, smartphones, tablets, and other devices. Users launch the dedicated application, enter their username and password on the login screen, and click the login button to be authenticated. Once login is successful, they are redirected to the main screen. When users feel depressed or anxious, they can enter their concerns into the application's chat interface and send them.

[1811] server:

[1812] The server is a computer system that receives authentication information and consultation details from the user. The server connects to a database (e.g., MySQL) to authenticate the user. The server then passes the received consultation details to an artificial intelligence engine to generate an appropriate response. For example, OpenAI's GPT-3 is used as the artificial intelligence engine. The generated response is sent to the user's device, which then displays it to the user.

[1813] Emotion Engine:

[1814] The emotion engine is software that analyzes user input and recognizes the user's emotional state. Specifically, it uses tools such as IBM Watson Emotion Analysis. If a user types, "I've been feeling anxious and can't sleep lately," the emotion engine analyzes the content and recognizes the emotion "anxiety." Based on this result, the artificial intelligence engine adjusts the response.

[1815] Matching Engine:

[1816] The matching engine is software that analyzes the user's consultation history and emotion recognition results to find other users with the same concerns. For example, a tool like Elasticsearch is used. This allows users with similar emotional states and concerns to be connected, promoting empathy and support.

[1817] Escalation Methods:

[1818] The escalation method is a process that notifies an expert if the consultation content is judged to be serious. The server creates an automatically generated medical record based on the consultation content along with the analysis results of the emotion engine, and passes it to the expert. The medical record is generated in PDF format or other formats, allowing the expert to quickly evaluate and provide advice. When the expert sends feedback to the server, it is displayed on the user's device.

[1819] Freemium model:

[1820] Users can choose between free and paid services. If they wish to use paid services in addition to the basic free service, they enter their credit card information on the payment screen and complete the payment. The server uses a payment gateway (e.g., Stripe) and, once payment is confirmed, adds permission for the paid service to the user's account. Paid services allow users to receive more advanced mental health care.

[1821] Examples:

[1822] For example, if a user is unable to sleep at night due to anxiety, they can use the system to receive advice 24 hours a day. When the user types "I've been unable to sleep lately due to anxiety" into the chat interface and sends it, the device sends it to the server. The emotion engine in the server analyzes this input and recognizes the "emotion of anxiety," and the artificial intelligence engine generates a response such as "Please tell me more about what is causing your anxiety," and sends it to the device. The response is then displayed to the user. If more serious anxiety is detected, the server automatically escalates the situation to a specialist and provides professional support.

[1823] Example prompts to input to a generative AI model:

[1824] "Please explain how users can use this system to get 24 / 7 support if they feel unsafe at night."

[1825] Thus, the present invention is a system that provides users with comprehensive, real-time, and appropriate mental health care, and is capable of efficiently recognizing emotions, promoting empathy, and escalating professional support.

[1826] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1827] Step 1:

[1828] The user launches the application, enters their username and password on the login screen, and clicks the login button.

[1829] Specific behavior:

[1830] A user launches the application, enters the username "example_user" and password "password123" on the login screen, and clicks the Login button.

[1831] Input: Username and Password

[1832] Output: User credentials are sent from the device to the server.

[1833] Step 2:

[1834] The terminal sends authentication information to the server, which then compares it with a database to authenticate the user.

[1835] Specific behavior:

[1836] The device sends authentication information (username and password) to the server as an HTTP POST request.

[1837] Input: Username and Password

[1838] Data processing: The authentication information is checked against a database on the server (e.g., MySQL).

[1839] Output: If authentication is successful, the server returns the URL of the main page in the HTTP response.

[1840] Step 3:

[1841] If the server succeeds in the authentication, it sends information to the terminal to transition to the main screen.

[1842] Specific behavior:

[1843] The server sends the URL of the main screen to the device in an HTTP response.

[1844] Input: Authentication information match result

[1845] Output: The URL of the main screen is sent to the device.

[1846] Step 4:

[1847] The user types their feelings of depression and anxiety into a chat interface and clicks the send button.

[1848] Specific behavior:

[1849] The user types "I've been feeling anxious and can't sleep lately" into the chat window and presses the send button.

[1850] Input: User's inquiry

[1851] Output: The consultation content is sent from the terminal to the server.

[1852] Step 5:

[1853] The device sends the consultation details to the server, which then passes the details to the artificial intelligence engine.

[1854] Specific behavior:

[1855] The device sends the entered consultation details to the server, which then passes them to an artificial intelligence engine (e.g., OpenAI GPT-3).

[1856] Input: User's inquiry

[1857] Data processing: An artificial intelligence engine analyzes the consultation content and generates an appropriate response.

[1858] Output: The generated response is returned to the server.

[1859] Step 6:

[1860] The server sends the generated response to the terminal.

[1861] Specific behavior:

[1862] The server sends the response obtained from the artificial intelligence engine to the terminal.

[1863] Input: The generated response

[1864] Output: The response is sent to the terminal.

[1865] Step 7:

[1866] The terminal displays the response received from the server to the user.

[1867] Specific behavior:

[1868] The terminal displays the generated response in the chat window.

[1869] Input: Response from the server

[1870] Output: Response displayed in the chat window

[1871] Step 8:

[1872] The emotion engine in the server analyzes the user's input information and recognizes the user's emotional state.

[1873] Specific behavior:

[1874] The server sends the user's input information to an emotion engine (e.g., IBM Watson Emotion Analysis) to analyze the user's emotional state.

[1875] Input: User's inquiry

[1876] Data processing: The emotion engine analyzes the input information and recognizes the emotional state.

[1877] Output: Emotional state recognition result

[1878] Step 9:

[1879] The server receives the recognition results from the emotion engine and instructs the artificial intelligence engine to adjust the response.

[1880] Specific behavior:

[1881] The server instructs the artificial intelligence engine to adjust the response based on the recognition results of the emotion engine.

[1882] Input: Emotional state recognition results

[1883] Data processing: Adjusting responses based on recognition results.

[1884] Output: The adjusted response

[1885] Step 10:

[1886] The server sends the adjusted response to the user terminal.

[1887] Specific behavior:

[1888] The server sends the adjusted response to the user's device in an HTTP response.

[1889] Input: Adjusted response

[1890] Output: The adjusted response is sent to the terminal.

[1891] Step 11:

[1892] The user can see the tailored response in the chat window and continue the conversation.

[1893] Specific behavior:

[1894] The user sees the response displayed on the screen.

[1895] Input: Adjusted response

[1896] Output: User confirmation and next input

[1897] Step 12:

[1898] The server analyzes the user's consultation history and the emotion recognition results of the emotion engine, and uses a matching engine to search for other users who have the same emotional state or concerns.

[1899] Specific behavior:

[1900] The server retrieves the user's consultation history and emotion engine data from a database (e.g., MongoDB) and analyzes it.

[1901] Input: Consultation history and emotion recognition results

[1902] Data processing: Analyze using a matching engine (e.g. Elasticsearch).

[1903] Output: Matching results

[1904] Step 13:

[1905] The server notifies the user's device of the matching results, encouraging empathy and support between users.

[1906] Specific behavior:

[1907] The server sends the matching results to the user's device as an HTTP response and displays a notification.

[1908] Input: Matching results

[1909] Output: Notification of sympathy and support between users

[1910] Step 14:

[1911] If the consultation is serious, the server will automatically create a medical record and escalate the matter to a specialist.

[1912] Specific behavior:

[1913] If the server detects serious anxiety from the analysis results of the emotion engine, it automatically generates a medical record (e.g., PDF format).

[1914] Input: Emotion recognition results and consultation details

[1915] Data processing: Automatically generate medical records and send them to specialists.

[1916] Output: Send medical record to specialist

[1917] Step 15:

[1918] The expert sends feedback and advice back to the server, which the device displays to the user.

[1919] Specific behavior:

[1920] The expert sends feedback and advice back to the server, which then sends it to the user's device, which displays the advice.

[1921] Input: Expert feedback

[1922] Output: Advice displayed on the user's terminal

[1923] Step 16:

[1924] If the user selects a paid service, they enter payment information on the payment screen, and the terminal sends that information to the server.

[1925] Specific behavior:

[1926] The user clicks the "Upgrade to paid service" button and enters credit card information, etc. The terminal sends the payment information to the server.

[1927] Input: Payment Information

[1928] Output: Payment information is sent to the server.

[1929] Step 17:

[1930] The server verifies the payment information and, if successful, adds authorization for the paid service to the user account.

[1931] Specific behavior:

[1932] Your server verifies the payment with a payment gateway (e.g., Stripe) and, if successful, adds authorization for paid services to the user account.

[1933] Input: Payment Information

[1934] Data Processing: Verify payment information and update account permissions

[1935] Output: The paid service entitlement is added to the user account.

[1936] Step 18:

[1937] The server notifies the user terminal that a paid service has become available, and the terminal displays this to the user.

[1938] Specific behavior:

[1939] The server sends a notification to the user's device saying "Paid service is now available." The device displays it to the user.

[1940] Input: Permission update result for paid service

[1941] Output: A notification to the user about the paid service is displayed.

[1942] (Application example 2)

[1943] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1944] Conventional mental healthcare systems have difficulty recognizing users' emotional state and stress levels in real time and responding appropriately. Furthermore, in brick-and-mortar stores, if a store clerk is emotionally depressed or stressed, this can affect customer service and reduce customer satisfaction. Furthermore, when escalating serious consultations to specialists, many systems require users to take action themselves, and lack efficient methods such as automated medical record creation. To address these issues, a system with more advanced emotion recognition and stress monitoring capabilities is needed to strengthen mental health support in brick-and-mortar stores.

[1945] 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.

[1946] In this invention, the server includes: means for providing an interface that allows users to consult about depression or anxiety at any time; communication means for transmitting user input to the server in real time; an artificial intelligence engine that analyzes the received consultation content using specific analysis means and generates an appropriate response; display means for providing the generated response to the user; a matching engine that analyzes the user's consultation history and matches them with other users who have the same problem; escalation means for escalating the consultation to a specialist if the consultation content is serious; emotion recognition means for recognizing and analyzing the user's emotions in real time; means for adjusting and providing support according to the emotional state based on the emotion recognition means; means for monitoring the stress level of store staff; and means for providing customer support in a physical store. This enables the emotional states of users and store staff to be recognized in real time, enabling appropriate mental health care and customer support.

[1947] "User" refers to an individual who uses the mental health care system.

[1948] "Interface" refers to the screen and operation methods that provide users with a means to discuss their feelings of depression or anxiety.

[1949] "Communication Method" refers to the technology or protocol used to transmit user input to a server in real time.

[1950] "Artificial intelligence engine" refers to AI technology that analyzes the content of inquiries received and generates appropriate responses.

[1951] "Display means" refers to a display or screen on which the generated response is shown to the user.

[1952] A "matching engine" refers to technology that analyzes a user's consultation history and connects them with other users who have the same concerns.

[1953] "Escalation measures" refer to the means of conveying information to a specialist when the consultation matter is serious.

[1954] "Emotion recognition means" refers to technology for recognizing and analyzing a user's emotional state in real time.

[1955] "Means for monitoring stress levels" refers to technology for recognizing and monitoring the stress levels of store employees.

[1956] "Means of providing customer service support" refers to the techniques and methods that enable store staff to provide better service to customers in physical stores.

[1957] The present invention is a comprehensive mental health care system that allows users to consult about depression and anxiety and receive appropriate support from AI and experts. Specifically, the system includes an interface, communication means, an artificial intelligence engine, emotion recognition means, display means, a matching engine, and escalation means.

[1958] System Configuration

[1959] 1. Interface

[1960] The system provides a screen and operation method that allows users to consult about their depression or anxiety. Users input their concerns through this interface.

[1961] 2. Means of communication

[1962] User input is sent to the server in real time using HTTP or HTTPS as the communication protocol.

[1963] 3. Artificial Intelligence Engine

[1964] The system analyzes the received consultation content and generates an appropriate response using a generative AI model that uses deep learning technology.

[1965] 4. Emotion recognition means

[1966] It analyzes user input and recognizes their emotional state in real time. The emotion recognition engine uses natural language processing technology to analyze emotions.

[1967] 5. Display means

[1968] It has a display, usually a smartphone or tablet, to show the generated response to the user.

[1969] 6. Matching Engine

[1970] The system analyzes the user's consultation history and matches them with other users who have the same concerns. The matching algorithm uses collaborative filtering technology.

[1971] 7. Escalation Methods

[1972] If the consultation is serious, it will be escalated to a specialist. The server will automatically generate a medical record and send it to the specialist.

[1973] Specific examples

[1974] If a user experiences anxiety at night, they can use this system to receive advice 24 hours a day. When the user types "I've been feeling anxious and can't sleep lately" into the interface, the device sends this to the server. An emotion recognition system within the server analyzes this input and recognizes the user's feelings of anxiety. At the same time, an artificial intelligence engine generates an appropriate response (for example, "Could you tell me more about what is causing you anxiety?") and displays it to the user via the device.

[1975] Furthermore, the emotion recognition means continuously analyzes the user's input, and if it detects a high-stress state, the server automatically escalates to an expert and provides detailed feedback and advice.

[1976] Prompt Sentence Examples

[1977] User: "I've been so stressed lately I can't concentrate on my work."

[1978] AI chatbot: "Tell me what's causing you stress"

[1979] This example allows users to receive prompt and appropriate mental health care.

[1980] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1981] Step 1:

[1982] The user inputs the content of their problem into the interface. The input content is text information such as "I've been feeling anxious lately and can't sleep."

[1983] Step 2:

[1984] The terminal sends user input to the server in real time using HTTP or HTTPS as the communication protocol. The input data is sent to the server in JSON format.

[1985] Step 3:

[1986] The server analyzes the received input data. First, the server's emotion recognition means analyzes the text using natural language processing technology to recognize the user's emotional state in real time. Through this analysis, the emotion contained in the input is labeled as "anxiety."

[1987] Step 4:

[1988] The server generates an appropriate response using a generative AI model based on the emotion recognition results. The AI ​​engine generates a response (e.g., "Tell me more about what causes anxiety") according to the user's emotion label "anxiety."

[1989] Step 5:

[1990] The server sends the generated response to the device, which again encodes the response in JSON format and sends it to the device using the HTTP / S protocol.

[1991] Step 6:

[1992] The terminal provides the response received from the server to the user, specifically, by displaying the generated response message on the display of the terminal.

[1993] Step 7:

[1994] If the user enters the information again, the process is repeated. The emotion recognition means in the server continuously monitors and analyzes the user's emotional state, and if it detects a high stress state, the escalation means is activated. The server then sends the automatically generated medical record to a specialist to provide further support to the user.

[1995] Step 8:

[1996] The matching engine analyzes the user's consultation history. The server uses collaborative filtering technology to search for other users with the same concerns and make appropriate matches. The matching results are sent to the device and displayed on the screen.

[1997] Step 9:

[1998] When the consultation is escalated to an expert by the escalation means, the server receives feedback from the expert and provides it to the user. The terminal displays the feedback and provides the user with professional advice.

[1999] These steps can help users receive prompt and appropriate mental health care and promote emotional stability.

[2000] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2001] 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.

[2002] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2003] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2004] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2005] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2006] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2007] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2008] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2009] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2010] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2011] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2012] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2013] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2014] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2015] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2016] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2017] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2018] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2019] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2020] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2021] The following is further disclosed regarding the above embodiment.

[2022] (Claim 1)

[2023] A means to provide users with an interface where they can consult about their feelings of depression or anxiety at any time,

[2024] A communication means for transmitting user input to a server in real time;

[2025] An artificial intelligence engine that analyzes the received consultation content and generates an appropriate response;

[2026] a display means for presenting the generated response to a user;

[2027] A matching engine that analyzes users' consultation history and matches them with other users who have the same concerns.

[2028] An escalation method to escalate to a specialist if the consultation is serious, and

[2029] A system including:

[2030] (Claim 2)

[2031] 2. The system according to claim 1, further comprising means for using a medical record automatically generated based on the content of the consultation when escalating to a specialist.

[2032] (Claim 3)

[2033] 10. The system of claim 1, wherein the system allows users to choose between free and paid freemium models and includes a payment mechanism for processing additional fees for paid services.

[2034] "Example 1"

[2035] (Claim 1)

[2036] A means to provide users with an interface where they can consult about their feelings of depression or anxiety at any time,

[2037] A communication means for transmitting user input to a server in real time;

[2038] An artificial intelligence engine that analyzes the received consultation content and generates an appropriate response;

[2039] a display means for presenting the generated response to a user;

[2040] A matching engine that analyzes users' consultation history and matches them with other users who have the same concerns.

[2041] An escalation method to escalate to a specialist if the consultation is serious, and

[2042] a means for performing user authentication and login processes;

[2043] A way to let users choose between free and paid freemium models;

[2044] Payment methods to process additional charges for paid services; and

[2045] A system including:

[2046] (Claim 2)

[2047] 2. The system according to claim 1, further comprising means for using a medical record automatically generated based on the content of the consultation when escalating to a specialist.

[2048] (Claim 3)

[2049] 10. The system of claim 1, further comprising means for providing a response generated in real time using an artificial intelligence engine that analyzes the content of the user's inquiry.

[2050] "Application Example 1"

[2051] (Claim 1)

[2052] A means to provide users with an interface where they can consult about their feelings of depression or anxiety at any time,

[2053] A communication means for transmitting user input to a server in real time;

[2054] An artificial intelligence engine that analyzes the received consultation content and generates an appropriate response;

[2055] a display means for presenting the generated response to a user;

[2056] A matching engine that analyzes users' consultation history and matches them with other users who have the same concerns.

[2057] An escalation method to escalate to a specialist if the consultation is serious, and

[2058] a content recommendation means for recommending optimal content based on the emotional state of the user;

[2059] A system including:

[2060] (Claim 2)

[2061] 2. The system according to claim 1, further comprising means for using a medical record automatically generated based on the content of the consultation when escalating to a specialist.

[2062] (Claim 3)

[2063] 10. The system of claim 1, wherein the system allows users to choose between free and paid freemium models and includes a payment mechanism for processing additional fees for paid services.

[2064] "Example 2: Combining Emotion Engines"

[2065] (Claim 1)

[2066] A means to provide users with an interface where they can consult about their feelings of depression or anxiety at any time,

[2067] A communication means for transmitting user input to a server in real time;

[2068] An artificial intelligence engine that analyzes the received consultation content and generates an appropriate response;

[2069] a display means for presenting the generated response to a user;

[2070] an emotion engine that recognizes the user's emotional state;

[2071] a means for adjusting a response based on the perceived emotion;

[2072] A matching engine that analyzes users' consultation history and matches them with other users who have the same concerns.

[2073] An escalation method to escalate to a specialist if the consultation is serious, and

[2074] A system including:

[2075] (Claim 2)

[2076] 2. The system according to claim 1, further comprising means for using a medical record automatically generated based on the content of the consultation when escalating to a specialist.

[2077] (Claim 3)

[2078] 10. The system of claim 1, wherein the system allows users to choose between free and paid freemium models and includes a payment mechanism for processing additional fees for paid services.

[2079] "Application example 2 when combining emotion engines"

[2080] (Claim 1)

[2081] A means to provide users with an interface where they can consult about their feelings of depression or anxiety at any time,

[2082] A communication means for transmitting user input to a server in real time;

[2083] An artificial intelligence engine that analyzes the received consultation content using specific analytical means and generates an appropriate response;

[2084] a display means for presenting the generated response to a user;

[2085] A matching engine that analyzes users' consultation history and matches them with other users who have the same concerns.

[2086] An escalation method to escalate to a specialist if the consultation is serious, and

[2087] an emotion recognition means for recognizing and analyzing the user's emotions in real time;

[2088] means for tailoring and providing support in response to emotional states based on the emotion recognition means;

[2089] A system including:

[2090] (Claim 2)

[2091] The system according to claim 1, further comprising means for using a medical record automatically generated based on the content of the consultation when escalating to an expert, and means for monitoring the stress level of the store clerk.

[2092] (Claim 3)

[2093] The system of claim 1, wherein the system allows users to choose between free and paid freemium models, includes a payment method for processing additional fees for paid services, and further includes a method for providing customer support in a physical store. [Explanation of symbols]

[2094] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means to provide users with an interface where they can consult about their feelings of depression or anxiety at any time, A communication means for transmitting user input to a server in real time; An artificial intelligence engine that analyzes the received consultation content and generates an appropriate response; a display means for presenting the generated response to a user; A matching engine that analyzes users' consultation history and matches them with other users who have the same concerns. An escalation method to escalate to a specialist if the consultation content is serious, and A system including:

2. 2. The system according to claim 1, further comprising means for using a medical record automatically generated based on the content of the consultation when escalating to a specialist.

3. The system of claim 1 , wherein the system allows users to choose between a free and paid freemium model, and includes a payment mechanism for processing additional fees for paid services.

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