system

Abstract

We provide the system. [Solution] A means of providing an interface for a user to initiate a virtual interaction via an electronic device, A means for analyzing received dialogue data and performing natural language processing to evaluate emotional state and stress level, A means for evaluating the risk of psychosis based on the analysis results and generating appropriate follow-up messages or advice, A means of presenting the generated message to the user via an electronic device, If necessary, a means to send notifications to supporters, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] [In recent years, the early detection and prevention of mental health problems have become a social concern. However, many individuals feel resistance to seeking professional care and have difficulty becoming aware of their own mental state. In addition, the shortage of experts and the difficulty of accessing medical institutions are further exacerbating this problem. There is a need for a system that can solve these problems, easily evaluate individual mental health status, and provide appropriate follow-up.]

Means for Solving the Problems

[0005] [This invention features a system that provides an interface for users to engage in virtual dialogue via electronic devices and includes natural language processing means for analyzing the content of that dialogue. The system evaluates emotional state and stress levels and determines the risk of mental illness based on the analysis results. It then presents the user with generated follow-up messages or advice and has a function to notify a third party as necessary. This enables users to manage their own mental health without receiving professional care.]

[0006] A "user" refers to an individual who engages in virtual interaction using the system.

[0007] "Electronic devices" are defined as [devices used by users to access virtual interactive interfaces, including computers and smartphones].

[0008] "Virtual dialogue" refers to [a conversation between a user and a computer-generated character or system, conducted in the form of everyday conversation].

[0009] An "interface" is [a part of a system that provides an operating environment for users to initiate virtual interactions and communicate].

[0010] "Dialogue data" refers to [text or audio information exchanged between the user and the system].

[0011] "Natural language processing" refers to the technology that enables computers to understand and analyze human language, extracting meaning from user text.

[0012] "Emotional state" refers to the emotional and psychological state that can be inferred from the user's dialogue.

[0013] "Stress level" is an indicator that shows the degree of stress a user is experiencing, and is estimated through dialogue analysis.

[0014] "Psychiatric risk" refers to [the degree of possibility that a user has mental health problems, which is judged based on the analysis results].

[0015] "Follow-up message" refers to [the additional guidance and advice provided by the system to the user based on the current situation].

[0016] "Third party" refers to [external people and organizations including supporters and psychiatrists to whom information may be provided with the user's consent].

Brief Explanation of Drawings

[0017] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Embodiments for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the language used in the following description will be explained.

[0020] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0021] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0030] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0037] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0038] This invention is a system that enables users to manage their own mental health by engaging in virtual interactions via electronic devices. The system aims to provide users with mental health checks and advice in a simple and natural way.

[0039] Users initiate virtual conversations using devices such as smartphones or personal computers via a dedicated application. This application features an AI-powered interface that transmits conversation data with the user to a server in real time.

[0040] The server analyzes the received dialogue data using natural language processing techniques to assess the user's emotional state and stress level. The natural language processing techniques used here are designed to understand the dialogue content and recognize emotional expressions and stress indicators within the text. The evaluation results are used by the server to assess risk and identify the risk of mental illness.

[0041] As feedback to the user, the server generates follow-up messages and advice on specific actions. These generated messages are sent to the user's device and displayed automatically. The content of the messages is customized according to the problems the user is likely to be facing and includes specific suggestions for maintaining mental health.

[0042] For example, if a user says something like, "My work has been really tough lately, and I'm exhausted," the system analyzes this information and determines that the user is experiencing a high level of stress. As a result, the server generates and presents advice such as, "Take adequate rest and make time for hobbies to improve your well-being."

[0043] Furthermore, the system incorporates a feature that controls notifications to third parties (psychiatrists and support providers) as needed. This notification feature operates only with the user's consent, ensuring that support is only provided when necessary due to the user's situation.

[0044] Through this configuration, users can assess, manage, and improve their mental health in their daily lives without having to visit a regular medical institution.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] Users log in to the application using electronic devices. The device sends user authentication information to the server, which then authenticates the user by comparing it with information in the database.

[0048] Step 2:

[0049] The user initiates a virtual conversation via a chat interface. The terminal sends user input messages to the server in real time.

[0050] Step 3:

[0051] The server passes the received dialogue data to a natural language processing module. There, the generative AI analyzes the message and identifies the emotional state and stress level.

[0052] Step 4:

[0053] Based on the information analyzed by the generating AI, the server performs a mental illness risk assessment. This assessment uses accumulated data and reference values.

[0054] Step 5:

[0055] The server generates appropriate follow-up messages and advice based on the evaluation results. This generation process is tailored to include personalized information that is relevant to the user's specific situation.

[0056] Step 6:

[0057] The server sends the generated message to the terminal, which then displays advice to the user. The user reviews this information and takes action as needed.

[0058] Step 7:

[0059] If a user requests additional support, the device sends the request to the server. After confirming the user's consent, the server initiates a process to send a notification to a third party (such as a psychiatrist or support provider).

[0060] Step 8:

[0061] After the entire process is complete, the server records the analysis results in the user's profile and updates the database used for future follow-up.

[0062] (Example 1)

[0063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0064] Many current mental health management systems are not easily accessible to individuals in their daily lives, and they struggle to assess mental health status in real time. This makes it difficult for users to receive timely and appropriate support to manage and improve their mental health. Furthermore, their ability to protect privacy and provide personalized support is limited.

[0065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0066] In this invention, the server includes means for providing a user interface for an individual to initiate a virtual dialogue via an information processing device; means for performing automatic language analysis to analyze acquired dialogue information and evaluate psychological state and stress level; and means for transmitting information to a supporter as needed. This makes it possible for individuals to easily evaluate and manage their mental health in their daily lives and to quickly receive necessary support.

[0067] "Individual" refers to a user who uses this system to manage their mental health through virtual dialogue.

[0068] An "information processing device" is a communication terminal capable of electronic interaction, and includes, but is not limited to, smartphones and personal computers.

[0069] A "user interface" refers to the screens and operation modules that allow an individual to initiate a virtual interaction and perform operations through an information processing device.

[0070] "Automated language analysis" refers to the process of analyzing acquired dialogue information using natural language processing technology to evaluate psychological state and level of tension.

[0071] A "generative AI model" is a form of artificial intelligence technology used for analyzing dialogue content and generating advice, and refers to a program model that performs natural language processing.

[0072] A "supporter" refers to a person or organization that provides support and advice to an individual as needed, with the aim of supporting their life.

[0073] "Encryption technology" refers to security technology used to safely transmit acquired data, and is a means of maintaining the confidentiality of communication data.

[0074] "Virtual dialogue" refers to a form of dialogue that takes place via an information processing device and does not require face-to-face interaction in the real world.

[0075] "Psychological state" refers to an individual's mental state and includes various psychological elements such as emotions and stress levels.

[0076] "Stress level" refers to the degree of stress and anxiety an individual experiences and constitutes part of a psychological state assessment.

[0077] A description of the embodiment for carrying out the invention will be provided.

[0078] This system is designed to support the management and improvement of an individual's mental health in their daily life. Users use a smartphone or personal computer as an information processing device and initiate a virtual dialogue through a dedicated application. The application provides an intuitive user interface, allowing users to input their mental state in a natural way.

[0079] The user's device collects the entered conversation content in real time and sends it to the server. The collected data is securely transferred using encryption technology. Specifically, HTTPS is used as the encryption protocol.

[0080] The server analyzes the received data using a generative AI model. This analysis utilizes natural language processing techniques, with typical toolsets including BERT and GPT. Based on this, the server evaluates the user's psychological state and level of tension.

[0081] Based on the analyzed data, the server assesses the user's mental health risks. If necessary, personalized advice and tracking messages are generated and sent to the device. This allows users to receive support in taking appropriate actions in their daily lives.

[0082] For example, if a user enters the prompt "Please tell me about the stress you've been experiencing in your life recently. I'd like some advice on it," the server will analyze this information and evaluate the characteristic stressors. Then, it will provide the user with specific advice such as, "It's important to get adequate rest and make time for your hobbies."

[0083] Furthermore, the system has a function that contacts support providers as needed, based on the user's consent. This ensures that users facing serious mental health challenges can receive prompt professional support.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] The user launches a dedicated application on their device and begins a virtual dialogue. Specifically, they select the "Start Mental Health Check" button using the app's UI. This action initiates user input, and the device prepares to collect dialogue data.

[0087] Step 2:

[0088] The device collects conversational information received from the user in real time. When voice input is used, speech recognition technology converts the speech into text. This input data is saved in text format for later processing.

[0089] Step 3:

[0090] The terminal encrypts the collected conversation information and sends it to the server. The information is securely transmitted over the internet using the HTTPS protocol. Input is user text data, and output is a secure data transmission to the server.

[0091] Step 4:

[0092] The server uses a generative AI model to analyze the received dialogue data. Specifically, it uses natural language processing techniques to analyze the data and evaluate the user's psychological state and level of tension. The input is encrypted dialogue data, and the output is the result of the analyzed psychological state evaluation.

[0093] Step 5:

[0094] The server assesses the user's mental health risks based on the analysis results. Then, if necessary, it generates personalized advice using AI. This advice is tailored to the user's stress and emotions. The input is the assessment results, and the output is the advice message provided to the user.

[0095] Step 6:

[0096] The server sends the generated advice to the user's terminal. The terminal receives this message and presents it to the user through the application's notification function. The input is the advice message, and the output is a visual presentation to the user.

[0097] Step 7:

[0098] If a user is facing certain risks, the system has a function that allows the server to send a notification to a supporter based on the user's consent. The inputs are the user's consent and risk assessment, and the output is the notification to the supporter.

[0099] (Application Example 1)

[0100] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0101] Managing mental health is difficult with conventional methods, as immediate support in daily life is challenging, and personalized advice, especially in online environments, is crucial. This invention aims to provide a way to make shopping and online activities more comfortable by offering immediate and appropriate feedback based on the user's emotional state in virtual stores and online platforms.

[0102] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0103] In this invention, the server includes means for providing an interface for the user to initiate a virtual dialogue via an electronic device; means for analyzing received dialogue data and performing natural language processing to evaluate the emotional state and stress level; and means for suggesting personalized products or activities based on the user's mental state. This enables individualized responses according to the user's emotional state.

[0104] An "interface for users to initiate virtual dialogue via electronic devices" refers to software and hardware settings that enable users to interact with artificial intelligence using smartphones or computers.

[0105] "Natural language processing for analyzing received dialogue data and evaluating emotional state and stress levels" refers to a technology that analyzes text and voice data obtained from users to determine their emotions and mental burden.

[0106] "Assessing the risk of mental illness based on analysis results and generating appropriate follow-up messages or advice" refers to a process that uses natural language processing to detect conditions that may affect mental health and provides users with corresponding information and guidelines.

[0107] "Presenting a generated message to the user via an electronic device" means sending a message automatically generated by the system to the user's terminal and displaying it on a screen or similar device.

[0108] "Sending notifications to supporters as needed" means that, with the user's consent, the system will send warnings or information to experts or support networks when it senses the need for intervention.

[0109] "Suggesting personalized products or activities based on the user's mental state" means providing choices that are more suitable than typical shopping or activities, based on the user's needs inferred from their emotional state.

[0110] To realize this application, the user uses an electronic device such as smart glasses. When the user wears the electronic device, the smart glasses continuously monitor the user's facial expressions and voice using their built-in camera and microphone. The collected data is initially processed on the device and then transmitted to a server via the internet.

[0111] The server analyzes the user's voice and facial expression data using data management software and natural language processing libraries such as TENSORFLOW®. This allows the server to assess the user's emotional state and stress level. Based on the analysis results, the server generates messages through a generative AI model to suggest products and activities that the user might be interested in.

[0112] The generated messages are sent to the user's smart glasses via a cloud service and displayed to the user in real time. These messages include personalized shopping suggestions and online activity suggestions tailored to the user's emotional state.

[0113] For example, if a user says, "I'm tired today," the system analyzes that information and suggests products that have a relaxing effect. An example of a prompt message would be, "Please tell us how you're feeling right now. We have recommended products and activities to help relieve stress."

[0114] This system allows users to receive personalized support in a virtual space.

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The user wears smart glasses and accesses a virtual store. The device uses its built-in camera and microphone to collect the user's facial expressions and voice data in real time. This input data is raw information that reflects the user's emotions and tone.

[0118] Step 2:

[0119] The terminal performs initial processing, compression, and format conversion of the collected audio and facial expression data. The output obtained in this step is data in a format suitable for transmission to the server. This data is transmitted to the server via the internet.

[0120] Step 3:

[0121] The server analyzes the received data by applying a natural language processing engine to audio data and converting it into text data. For facial expression data, it uses an image recognition algorithm to perform emotion analysis. The input is pre-processed data, and the output is an index indicating the user's emotional state and stress level.

[0122] Step 4:

[0123] Based on the analysis results, the server uses a generative AI model to generate recommendation messages for products and activities that the user might be interested in. The output of this step is personalized advice and product recommendation lists for each individual user.

[0124] Step 5:

[0125] The server sends the generated message to the user's terminal via a cloud service. The terminal receives the message and displays it in the user's field of view. The input is the generated text message, and the output is visual information for the user.

[0126] Step 6:

[0127] Users review suggestions displayed on their devices and advance their shopping experience by selecting recommended products and activities. This step leads to product selection and subsequent actions by the user.

[0128] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0129] This invention is a system that allows users to engage in virtual dialogue via electronic devices and analyzes the resulting dialogue data. In particular, by incorporating an emotion engine, it enables a precise understanding of the user's emotional state. The aim of this system is to more accurately assess the user's mental health and provide appropriate advice.

[0130] Users initiate virtual interactions through a specific application using devices such as smartphones or personal computers. This application is equipped with a generative AI and emotion engine, which transmits user input to a server in real time.

[0131] The server uses natural language processing techniques to analyze received dialogue data and recognizes the user's emotions using an emotion engine. The emotion engine extracts emotions from the dialogue content and forms emotion categories such as positive, negative, and neutral. This emotion information is then used to evaluate the emotional state and stress level.

[0132] The server's evaluation results are further analyzed by a generating AI to determine the presence or absence of a risk of mental illness. Based on this, follow-up messages and advice are generated as customized information that takes into account the user's emotional state. This allows users to receive more personalized advice.

[0133] For example, if a user says something like, "I've been feeling down lately," the server recognizes this negative emotion and uses it to generate positive advice such as, "You might be able to cheer yourself up by spending time on your hobbies."

[0134] Furthermore, the emotion engine has the ability to learn the user's emotions over the long term and record emotional trends and changes. This makes it possible to improve the accuracy of risk assessment and follow-up over the long term.

[0135] In the above configuration, the present invention enables users to monitor their mental state on a daily basis and take appropriate action without having to visit a specialized medical institution.

[0136] The following describes the processing flow.

[0137] Step 1:

[0138] The user opens a dedicated application on their device and logs in. The device sends the user's authentication information to the server, which then verifies it against the database to perform authentication.

[0139] Step 2:

[0140] The user initiates a virtual conversation using the application's chat interface. The device sends the user's input messages to the server in real time.

[0141] Step 3:

[0142] The server sends the received dialogue data to a natural language processing module for analysis. This module analyzes the text and extracts keywords and context that indicate emotion.

[0143] Step 4:

[0144] The emotion engine on the server identifies the user's emotions based on the analyzed data. The emotion engine classifies the input message into emotional categories such as positive, negative, and neutral.

[0145] Step 5:

[0146] The server uses emotional information from the emotion engine to assess emotional state and stress levels. This includes a process of comparing it with existing emotional data.

[0147] Step 6:

[0148] Based on the evaluation results, the server determines whether or not there is a risk of mental illness. This determination is made by considering risk criteria and emotional information.

[0149] Step 7:

[0150] The server utilizes AI to generate personalized follow-up messages or advice for each user, taking into account their emotional state.

[0151] Step 8:

[0152] The server sends the generated message to the terminal, which then displays it to the user. The user reviews the advice and follows the instructions as needed.

[0153] Step 9:

[0154] If a user requests additional support or follow-up, the device sends the request to the server. The server verifies the user's consent and, if necessary, configures notifications to third parties.

[0155] Step 10:

[0156] After the process is complete, the server records the user's analysis results in an individual profile, which will be used for future follow-up. This enhances long-term support for the user.

[0157] (Example 2)

[0158] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0159] In modern society, maintaining mental health is becoming increasingly important for users. However, many users find it difficult to monitor their mental state without visiting a medical institution, making it challenging to take appropriate measures early on. To address this challenge, there is a need for a system that allows users to easily manage their mental state on a daily basis.

[0160] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0161] In this invention, the server includes means for providing a user interface for initiating a virtual dialogue via an information processing device; means for analyzing received dialogue data and using language processing techniques to evaluate emotional state and stress indicators; and means for evaluating mental health risks based on the analysis results and generating appropriate follow-up messages or advice. This enables users to monitor their mental state on a daily basis and take appropriate measures quickly as needed.

[0162] An "information processing device" is a digital device that performs functions such as inputting, processing, storing, and outputting information, and includes smartphones, tablets, and laptop computers.

[0163] A "user interface" refers to the screens and operating methods that users use to access and operate information processing equipment, and includes visual input forms and interactive menus.

[0164] "Language processing technology" is a field of computer science that interprets and analyzes human language, and includes techniques such as natural language processing and text mining.

[0165] An "emotion engine" is software that analyzes and classifies emotional states from input data, and includes functions to categorize the user's emotions as positive, negative, neutral, etc.

[0166] A "follow-up message" is a message of advice or warning that is generated based on analysis results and evaluations and presented to the user.

[0167] "Mental health risk" refers to an indicator of an individual's likelihood of experiencing mental health problems, and includes factors such as stress levels and changes in emotional state.

[0168] This invention is a system that allows users to efficiently monitor their own mental state via an information processing device and take appropriate measures as needed. Users launch a specific application using an information processing device such as a smartphone or personal computer and initiate a virtual dialogue. This prepares the system to process user input data in real time, utilizing a generative AI model and an emotion engine.

[0169] The terminal sends the text entered by the user to the server. The server receives this data and analyzes it using language processing technologies such as Python and TensorFlow. In this analysis process, an emotion engine extracts emotions from the text data and classifies them into positive, negative, and neutral categories. This information is used to evaluate the user's emotional state and stress indicators.

[0170] Based on the evaluation results, the server uses a generative AI model to generate follow-up messages or advice. This allows users to receive customized advice tailored to their individual circumstances. The generated messages are presented to the user via their device.

[0171] For example, if a user inputs "I've been feeling down lately," the server recognizes this negative emotion and sends positive advice to the user's device, such as "You might be able to cheer yourself up by spending time on your hobbies." Furthermore, the emotion engine records long-term changes in emotions, enabling continuous monitoring.

[0172] This invention enables users to easily manage their mental state in their daily lives and take necessary actions quickly. By using a generative AI model and prompt text, more accurate support can be provided.

[0173] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0174] Step 1:

[0175] The user uses an information processing device to access a specific application and initiate a virtual interaction. The input here is text data about the user's emotional state and situation, and this data is sent to the server by the terminal as output. The user performs actions such as inputting specific questions and their own emotions as text and sending them.

[0176] Step 2:

[0177] The terminal sends the text entered by the user to the server. The input here is raw text data sent by the user, and the output is text data securely transferred to the server. The terminal uses security protocols to protect the data during transmission.

[0178] Step 3:

[0179] The server analyzes the received text data using natural language processing techniques. The input is text data received from the terminal, and the output is the generated sentiment categories after analysis. The server uses Python and TensorFlow to perform natural language processing and extract sentiments such as positive, negative, and neutral.

[0180] Step 4:

[0181] The server evaluates the user's emotional state and stress indicators based on emotional information extracted by the emotion engine. The input is emotional information based on the analysis results, and the output is an evaluation of the emotional state. The server then performs operations to evaluate indicators such as stress levels as numerical values.

[0182] Step 5:

[0183] The server uses a generative AI model to create appropriate follow-up messages based on the evaluation results. The input is the user's emotional state evaluation result, and the output is a personalized advice message. The server takes a prompt sentence and uses natural language generation technology to generate specific advice.

[0184] Step 6:

[0185] The server sends the generated message to the terminal and presents it to the user. The input is the generated text message, and the output is the message presented to the user. The terminal displays the received message on its screen, allowing the user to confirm it.

[0186] (Application Example 2)

[0187] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0188] In modern society, there is a problem in that it is difficult to manage users' mental health on a daily and accurate basis. Furthermore, in real-world customer interactions, it is difficult to instantly grasp a customer's emotional state and recommend personalized products or services accordingly. Therefore, a new system is needed to solve these problems.

[0189] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0190] In this invention, the server includes means for providing a user interface for a user to initiate a virtual dialogue via an information processing device; means for performing natural language processing to analyze received dialogue information and evaluate emotional state and level of pressure; and means for analyzing the user's emotional state and making personalized product or service recommendations using wearable information devices used in real-world spatial interactions. This makes it possible to understand the user's emotional state and enable personalized responses.

[0191] A "user interface" is a function that provides screen displays and operating methods for users to operate an information processing device.

[0192] "Dialogue information" refers to communication data such as voice and text exchanged between users via information processing devices.

[0193] "Emotional state" refers to information that indicates the user's emotional response and psychological state.

[0194] "Degree of pressure" is a measure that represents the level of stress and burden felt by the user.

[0195] "Natural language processing" is a technology that allows computers to understand and analyze human language.

[0196] "Wearable information devices" refer to information processing devices designed to be carried or worn by users.

[0197] "Personalized products or services" refer to specialized products or support that are tailored to the specific needs and circumstances of the user.

[0198] "Continuing support messages" are advice and encouragement sent regularly to support the mental health of users.

[0199] "Notification" refers to a means of notification or communication to inform a third party of information.

[0200] The system for realizing this invention is based on the user initiating a virtual dialogue using an information processing device, and conducting that dialogue through a wearable information device. The server receives the user's dialogue information acquired through the user interface and performs natural language processing to evaluate the user's emotional state and level of stress. This enables personalized recommendations of products or services.

[0201] The specific technology involves combining speech recognition software with a natural language processing engine for text analysis. In this system, the server analyzes the received dialogue information and uses a generative AI model to generate continuous support messages for the user. Furthermore, by using wearable information devices such as smart glasses and smartwatches, it is possible to grasp the user's emotional state in real time even in the real world and provide personalized advice.

[0202] This system allows, for example, when a customer visits a physical store and says, "I've been feeling tired and down lately because of work," the server to recognize this negative emotional state and generate a specific product suggestion such as, "Why not try some relaxation items?"

[0203] Example of a prompt:

[0204] "Based on the following customer statements, generate appropriate support and suggestions. Consider the customer's emotional state and include suggestions to improve their shopping experience."

[0205] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0206] Step 1:

[0207] While the user is wearing a wearable information device, a virtual dialogue is initiated through the user interface of the information processing device. Voice input from the user is captured by the wearable information device (e.g., smart glasses), and this data is sent to the server. The input is voice data, and the output is a voice data file.

[0208] Step 2:

[0209] The server uses speech recognition software to convert the received audio data into text. The converted text data is then used as input for a natural language processing engine to evaluate the emotional state. The output is the analyzed emotional state and its stress level. Specifically, this involves classifying the emotional state as either positive, negative, or neutral.

[0210] Step 3:

[0211] Based on the analyzed emotional state, the server uses a generative AI model to generate appropriate support messages and product recommendations in response to prompts. The input is the emotional state and user profile, and the output is the generated personalized message. Specifically, the AI ​​model customizes the message using the user's past conversation history.

[0212] Step 4:

[0213] The server presents the generated personalized message to the user via an information processing device. The user receives the output message and reacts as needed. Specifically, this involves displaying the message as text on the user's display.

[0214] Step 5:

[0215] The system collects user feedback and stores it in a database. This feedback is then used to improve follow-up messages and subsequent interactions. In this step, the input is user feedback information, and the output is an updated user profile. Specifically, calculations are performed to predict the next response based on past data and optimize the system.

[0216] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0217] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0218] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0219] [Second Embodiment]

[0220] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0221] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0222] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0223] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0224] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0225] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0226] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0227] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0228] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0229] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0230] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0231] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0232] This invention is a system that enables users to manage their own mental health by engaging in virtual interactions via electronic devices. The system aims to provide users with mental health checks and advice in a simple and natural way.

[0233] Users initiate virtual conversations using devices such as smartphones or personal computers via a dedicated application. This application features an AI-powered interface that transmits conversation data with the user to a server in real time.

[0234] The server analyzes the received dialogue data using natural language processing techniques to assess the user's emotional state and stress level. The natural language processing techniques used here are designed to understand the dialogue content and recognize emotional expressions and stress indicators within the text. The evaluation results are used by the server to assess risk and identify the risk of mental illness.

[0235] As feedback to the user, the server generates follow-up messages and advice on specific actions. These generated messages are sent to the user's device and displayed automatically. The content of the messages is customized according to the problems the user is likely to be facing and includes specific suggestions for maintaining mental health.

[0236] For example, if a user says something like, "My work has been really tough lately, and I'm exhausted," the system analyzes this information and determines that the user is experiencing a high level of stress. As a result, the server generates and presents advice such as, "Take adequate rest and make time for hobbies to improve your well-being."

[0237] Furthermore, the system incorporates a feature that controls notifications to third parties (psychiatrists and support providers) as needed. This notification feature operates only with the user's consent, ensuring that support is only provided when necessary due to the user's situation.

[0238] Through this configuration, users can assess, manage, and improve their mental health in their daily lives without having to visit a regular medical institution.

[0239] The following describes the processing flow.

[0240] Step 1:

[0241] Users log in to the application using electronic devices. The device sends user authentication information to the server, which then authenticates the user by comparing it with information in the database.

[0242] Step 2:

[0243] The user initiates a virtual conversation via a chat interface. The terminal sends user input messages to the server in real time.

[0244] Step 3:

[0245] The server passes the received dialogue data to a natural language processing module. There, the generative AI analyzes the message and identifies the emotional state and stress level.

[0246] Step 4:

[0247] Based on the information analyzed by the generating AI, the server performs a mental illness risk assessment. This assessment uses accumulated data and reference values.

[0248] Step 5:

[0249] The server generates appropriate follow-up messages and advice based on the evaluation results. This generation process is tailored to include personalized information that is relevant to the user's specific situation.

[0250] Step 6:

[0251] The server sends the generated message to the terminal, which then displays advice to the user. The user reviews this information and takes action as needed.

[0252] Step 7:

[0253] If a user requests additional support, the device sends the request to the server. After confirming the user's consent, the server initiates a process to send a notification to a third party (such as a psychiatrist or support provider).

[0254] Step 8:

[0255] After the entire process is complete, the server records the analysis results in the user's profile and updates the database used for future follow-up.

[0256] (Example 1)

[0257] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0258] Many current mental health management systems are not easily accessible to individuals in their daily lives, and they struggle to assess mental health status in real time. This makes it difficult for users to receive timely and appropriate support to manage and improve their mental health. Furthermore, their ability to protect privacy and provide personalized support is limited.

[0259] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0260] In this invention, the server includes means for providing a user interface for an individual to initiate a virtual dialogue via an information processing device; means for performing automatic language analysis to analyze acquired dialogue information and evaluate psychological state and stress level; and means for transmitting information to a supporter as needed. This makes it possible for individuals to easily evaluate and manage their mental health in their daily lives and to quickly receive necessary support.

[0261] "Individual" refers to a user who uses this system to manage their mental health through virtual dialogue.

[0262] An "information processing device" is a communication terminal capable of electronic interaction, and includes, but is not limited to, smartphones and personal computers.

[0263] A "user interface" refers to the screens and operation modules that allow an individual to initiate a virtual interaction and perform operations through an information processing device.

[0264] "Automated language analysis" refers to the process of analyzing acquired dialogue information using natural language processing technology to evaluate psychological state and level of tension.

[0265] A "generative AI model" is a form of artificial intelligence technology used for analyzing dialogue content and generating advice, and refers to a program model that performs natural language processing.

[0266] A "supporter" refers to a person or organization that provides support and advice to an individual as needed, with the aim of supporting their life.

[0267] "Encryption technology" refers to security technology used to safely transmit acquired data, and is a means of maintaining the confidentiality of communication data.

[0268] "Virtual dialogue" refers to a form of dialogue that takes place via an information processing device and does not require face-to-face interaction in the real world.

[0269] "Psychological state" refers to an individual's mental state and includes various psychological elements such as emotions and stress levels.

[0270] "Stress level" refers to the degree of stress and anxiety an individual experiences and constitutes part of a psychological state assessment.

[0271] A description of the embodiment for carrying out the invention will be provided.

[0272] This system is designed to support the management and improvement of an individual's mental health in their daily life. Users use a smartphone or personal computer as an information processing device and initiate a virtual dialogue through a dedicated application. The application provides an intuitive user interface, allowing users to input their mental state in a natural way.

[0273] The user's device collects the entered conversation content in real time and sends it to the server. The collected data is securely transferred using encryption technology. Specifically, HTTPS is used as the encryption protocol.

[0274] The server analyzes the received data using a generative AI model. This analysis utilizes natural language processing techniques, including typical toolsets such as BERT and GPT. Based on this, the server evaluates the user's psychological state and level of tension.

[0275] Based on the analyzed data, the server assesses the user's mental health risks. If necessary, personalized advice and tracking messages are generated and sent to the device. This allows users to receive support in taking appropriate actions in their daily lives.

[0276] For example, if a user enters the prompt "Please tell me about the stress you've been experiencing in your life recently, and I'd like some advice on it," the server will analyze this information and evaluate the characteristic stressors. Then, it will provide the user with specific advice such as, "It's important to get adequate rest and make time for your hobbies."

[0277] Furthermore, the system has a function that contacts support providers as needed, based on the user's consent. This ensures that users facing serious mental health challenges can receive prompt professional support.

[0278] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0279] Step 1:

[0280] The user launches the dedicated application on the terminal and starts a virtual conversation. Specifically, the user selects the "Start Mental Health Check" button using the UI within the application. This action initiates the user's input, and the terminal prepares to collect conversation data.

[0281] Step 2:

[0282] The terminal collects the conversation information received from the user in real time. When using voice input, the voice is converted into text by voice recognition technology. This input data is saved in text format for later processing.

[0283] Step 3:

[0284] The terminal encrypts the collected conversation information and sends it to the server. The information is securely transmitted via the Internet using the HTTPS protocol. The input is the user's text data, and the output is a secure data transmission to the server.

[0285] Step 4:

[0286] The server uses a generated AI model to analyze the received conversation data. Specifically, natural language processing technology is used to analyze the data and evaluate the user's mental state and level of tension. The input is the encrypted conversation data, and the output is the evaluation result of the analyzed mental state.

[0287] Step 5:

[0288] The server evaluates the user's mental health risk based on the analysis results. And in necessary cases, it generates individualized advice by the generated AI. The advice generated here will be according to the stress and emotions the user feels. The input is the evaluation result, and the output is an advice message provided to the user.

[0289] Step 6:

[0290] The server sends the generated advice to the user's terminal. The terminal receives this message and presents it to the user through the application's notification function. The input is the advice message, and the output is a visual presentation to the user.

[0291] Step 7:

[0292] If a user is facing certain risks, the system has a function that allows the server to send a notification to a supporter based on the user's consent. The inputs are the user's consent and risk assessment, and the output is the notification to the supporter.

[0293] (Application Example 1)

[0294] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0295] Managing mental health is difficult with conventional methods, as immediate support in daily life is challenging, and personalized advice, especially in online environments, is crucial. This invention aims to provide a way to make shopping and online activities more comfortable by offering immediate and appropriate feedback based on the user's emotional state in virtual stores and online platforms.

[0296] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0297] In this invention, the server includes means for providing an interface for the user to initiate a virtual dialogue via an electronic device; means for analyzing received dialogue data and performing natural language processing to evaluate the emotional state and stress level; and means for suggesting personalized products or activities based on the user's mental state. This enables individualized responses according to the user's emotional state.

[0298] An "interface for users to initiate virtual dialogue via electronic devices" refers to software and hardware settings that enable users to interact with artificial intelligence using smartphones or computers.

[0299] "Natural language processing for analyzing received dialogue data and evaluating emotional state and stress levels" refers to a technology that analyzes text and voice data obtained from users to determine their emotions and mental burden.

[0300] "Assessing the risk of mental illness based on analysis results and generating appropriate follow-up messages or advice" refers to a process that uses natural language processing to detect conditions that may affect mental health and provides users with corresponding information and guidelines.

[0301] "Presenting a generated message to the user via an electronic device" means sending a message automatically generated by the system to the user's terminal and displaying it on a screen or similar device.

[0302] "Sending notifications to supporters as needed" means that, with the user's consent, the system will send warnings or information to experts or support networks when it senses the need for intervention.

[0303] "Suggesting personalized products or activities based on the user's mental state" means providing choices that are more suitable than typical shopping or activities, based on the user's needs inferred from their emotional state.

[0304] To realize this application, the user uses an electronic device such as smart glasses. When the user wears the electronic device, the smart glasses continuously monitor the user's facial expressions and voice using their built-in camera and microphone. The collected data is initially processed on the device and then transmitted to a server via the internet.

[0305] The server uses data management software and natural language processing libraries such as TensorFlow to analyze the user's voice data and facial expression data. As a result, the user's emotional state and stress level are evaluated. Based on the analysis results, the server generates a message for proposing products and activities that the user may be interested in through a generative AI model.

[0306] The generated message is sent to the user's smart glasses via a cloud service and displayed to the user in real time. This message includes personalized shopping proposals and suggestions for online activities according to the user's emotional state.

[0307] As a specific example, when the user says "I'm tired today", the system analyzes this information and proposes products with a relaxing effect. An example of a prompt sentence is in the form of "Please let me know your current mood. We are preparing recommended products and activities to relieve stress."

[0308] With this system, the user can receive individualized support in the virtual space.

[0309] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0310] Step 1:

[0311] The user wears smart glasses and accesses a virtual store. The terminal uses the built-in camera and microphone to collect the user's facial expression and voice data in real time. This input data is raw information reflecting the user's emotions and tone.

[0312] Step 2:

[0313] The terminal performs initial processing, compression, and format conversion of the collected audio and facial expression data. The output obtained in this step is data in a format suitable for transmission to the server. This data is transmitted to the server via the internet.

[0314] Step 3:

[0315] The server analyzes the received data by applying a natural language processing engine to audio data and converting it into text data. For facial expression data, it uses an image recognition algorithm to perform emotion analysis. The input is pre-processed data, and the output is an index indicating the user's emotional state and stress level.

[0316] Step 4:

[0317] Based on the analysis results, the server uses a generative AI model to generate recommendation messages for products and activities that the user might be interested in. The output of this step is personalized advice and product recommendation lists for each individual user.

[0318] Step 5:

[0319] The server sends the generated message to the user's terminal via a cloud service. The terminal receives the message and displays it in the user's field of view. The input is the generated text message, and the output is visual information for the user.

[0320] Step 6:

[0321] Users review suggestions displayed on their devices and advance their shopping experience by selecting recommended products and activities. This step leads to product selection and subsequent actions by the user.

[0322] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0323] This invention is a system that allows users to engage in virtual dialogue via electronic devices and analyzes the resulting dialogue data. In particular, by incorporating an emotion engine, it enables a precise understanding of the user's emotional state. The aim of this system is to more accurately assess the user's mental health and provide appropriate advice.

[0324] Users initiate virtual interactions through a specific application using devices such as smartphones or personal computers. This application is equipped with a generative AI and emotion engine, which transmits user input to a server in real time.

[0325] The server uses natural language processing techniques to analyze received dialogue data and recognizes the user's emotions using an emotion engine. The emotion engine extracts emotions from the dialogue content and forms emotion categories such as positive, negative, and neutral. This emotion information is then used to evaluate the emotional state and stress level.

[0326] The server's evaluation results are further analyzed by a generating AI to determine the presence or absence of a risk of mental illness. Based on this, follow-up messages and advice are generated as customized information that takes into account the user's emotional state. This allows users to receive more personalized advice.

[0327] For example, if a user says something like, "I've been feeling down lately," the server recognizes this negative emotion and uses it to generate positive advice such as, "You might be able to cheer yourself up by spending time on your hobbies."

[0328] Furthermore, the emotion engine has the ability to learn the user's emotions over the long term and record emotional trends and changes. This makes it possible to improve the accuracy of risk assessment and follow-up over the long term.

[0329] In the above configuration, the present invention enables users to monitor their mental state on a daily basis and take appropriate action without having to visit a specialized medical institution.

[0330] The following describes the processing flow.

[0331] Step 1:

[0332] The user opens a dedicated application on their device and logs in. The device sends the user's authentication information to the server, which then verifies it against the database to perform authentication.

[0333] Step 2:

[0334] The user initiates a virtual conversation using the application's chat interface. The device sends the user's input messages to the server in real time.

[0335] Step 3:

[0336] The server sends the received dialogue data to a natural language processing module for analysis. This module analyzes the text and extracts keywords and context that indicate emotion.

[0337] Step 4:

[0338] The emotion engine on the server identifies the user's emotions based on the analyzed data. The emotion engine classifies the input message into emotional categories such as positive, negative, and neutral.

[0339] Step 5:

[0340] The server uses emotional information from the emotion engine to assess emotional state and stress levels. This includes a process of comparing it with existing emotional data.

[0341] Step 6:

[0342] Based on the evaluation results, the server determines whether or not there is a risk of mental illness. This determination is made by considering risk criteria and emotional information.

[0343] Step 7:

[0344] The server utilizes AI to generate personalized follow-up messages or advice for each user, taking into account their emotional state.

[0345] Step 8:

[0346] The server sends the generated message to the terminal, which then displays it to the user. The user reviews the advice and follows the instructions as needed.

[0347] Step 9:

[0348] If a user requests additional support or follow-up, the device sends the request to the server. The server verifies the user's consent and, if necessary, configures notifications to third parties.

[0349] Step 10:

[0350] After the process is complete, the server records the user's analysis results in an individual profile, which will be used for future follow-up. This enhances long-term support for the user.

[0351] (Example 2)

[0352] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0353] In modern society, maintaining mental health is becoming increasingly important for users. However, many users find it difficult to monitor their mental state without visiting a medical institution, making it challenging to take appropriate measures early on. To address this challenge, there is a need for a system that allows users to easily manage their mental state on a daily basis.

[0354] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0355] In this invention, the server includes means for providing a user interface for initiating a virtual dialogue via an information processing device; means for analyzing received dialogue data and using language processing techniques to evaluate emotional state and stress indicators; and means for evaluating mental health risks based on the analysis results and generating appropriate follow-up messages or advice. This enables users to monitor their mental state on a daily basis and take appropriate measures quickly as needed.

[0356] An "information processing device" is a digital device that performs functions such as inputting, processing, storing, and outputting information, and includes smartphones, tablets, and laptop computers.

[0357] A "user interface" refers to the screens and operating methods that users use to access and operate information processing equipment, and includes visual input forms and interactive menus.

[0358] "Language processing technology" is a field of computer science that interprets and analyzes human language, and includes techniques such as natural language processing and text mining.

[0359] An "emotion engine" is software that analyzes and classifies emotional states from input data, and includes functions to categorize the user's emotions as positive, negative, neutral, etc.

[0360] A "follow-up message" is a message of advice or warning that is generated based on analysis results and evaluations and presented to the user.

[0361] "Mental health risk" refers to an indicator of an individual's likelihood of experiencing mental health problems, and includes factors such as stress levels and changes in emotional state.

[0362] This invention is a system that allows users to efficiently monitor their own mental state via an information processing device and take appropriate measures as needed. Users launch a specific application using an information processing device such as a smartphone or personal computer and initiate a virtual dialogue. This prepares the system to process user input data in real time, utilizing a generative AI model and an emotion engine.

[0363] The terminal sends the text entered by the user to the server. The server receives this data and analyzes it using language processing technologies such as Python and TensorFlow. In this analysis process, an emotion engine extracts emotions from the text data and classifies them into positive, negative, and neutral categories. This information is used to evaluate the user's emotional state and stress indicators.

[0364] Based on the evaluation results, the server uses a generative AI model to generate follow-up messages or advice. This allows users to receive customized advice tailored to their individual circumstances. The generated messages are presented to the user via their device.

[0365] For example, if a user inputs "I've been feeling down lately," the server recognizes this negative emotion and sends positive advice to the user's device, such as "You might be able to cheer yourself up by spending time on your hobbies." Furthermore, the emotion engine records long-term changes in emotions, enabling continuous monitoring.

[0366] This invention enables users to easily manage their mental state in their daily lives and take necessary actions quickly. By using a generative AI model and prompt text, more accurate support can be provided.

[0367] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0368] Step 1:

[0369] The user uses an information processing device to access a specific application and initiate a virtual interaction. The input here is text data about the user's emotional state and situation, and this data is sent to the server by the terminal as output. The user performs actions such as inputting specific questions and their own emotions as text and sending them.

[0370] Step 2:

[0371] The terminal sends the text entered by the user to the server. The input here is raw text data sent by the user, and the output is text data securely transferred to the server. The terminal uses security protocols to protect the data during transmission.

[0372] Step 3:

[0373] The server analyzes the received text data using natural language processing techniques. The input is text data received from the terminal, and the output is the generated sentiment categories after analysis. The server uses Python and TensorFlow to perform natural language processing and extract sentiments such as positive, negative, and neutral.

[0374] Step 4:

[0375] The server evaluates the user's emotional state and stress indicators based on emotional information extracted by the emotion engine. The input is emotional information based on the analysis results, and the output is an evaluation of the emotional state. The server then performs operations to evaluate indicators such as stress levels as numerical values.

[0376] Step 5:

[0377] The server uses a generative AI model to create appropriate follow-up messages based on the evaluation results. The input is the user's emotional state evaluation result, and the output is a personalized advice message. The server takes a prompt sentence and uses natural language generation technology to generate specific advice.

[0378] Step 6:

[0379] The server sends the generated message to the terminal and presents it to the user. The input is the generated text message, and the output is the message presented to the user. The terminal displays the received message on its screen, allowing the user to confirm it.

[0380] (Application Example 2)

[0381] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0382] In modern society, there is a problem in that it is difficult to manage users' mental health on a daily and accurate basis. Furthermore, in real-world customer interactions, it is difficult to instantly grasp a customer's emotional state and recommend personalized products or services accordingly. Therefore, a new system is needed to solve these problems.

[0383] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0384] In this invention, the server includes means for providing a user interface for a user to initiate a virtual dialogue via an information processing device; means for performing natural language processing to analyze received dialogue information and evaluate emotional state and level of pressure; and means for analyzing the user's emotional state and making personalized product or service recommendations using wearable information devices used in real-world spatial interactions. This makes it possible to understand the user's emotional state and enable personalized responses.

[0385] A "user interface" is a function that provides screen displays and operating methods for users to operate an information processing device.

[0386] "Dialogue information" refers to communication data such as voice and text exchanged between users via information processing devices.

[0387] "Emotional state" refers to information that indicates the user's emotional response and psychological state.

[0388] "Degree of pressure" is a measure that represents the level of stress and burden felt by the user.

[0389] "Natural language processing" is a technology that allows computers to understand and analyze human language.

[0390] "Wearable information devices" refer to information processing devices designed to be carried or worn by users.

[0391] "Personalized products or services" refer to specialized products or support that are tailored to the specific needs and circumstances of the user.

[0392] "Continuing support messages" are advice and encouragement sent regularly to support the mental health of users.

[0393] "Notification" refers to a means of notification or communication to inform a third party of information.

[0394] The system for realizing this invention is based on the user initiating a virtual dialogue using an information processing device, and conducting that dialogue through a wearable information device. The server receives the user's dialogue information acquired through the user interface and performs natural language processing to evaluate the user's emotional state and level of stress. This enables personalized recommendations of products or services.

[0395] The specific technology involves combining speech recognition software with a natural language processing engine for text analysis. In this system, the server analyzes the received dialogue information and uses a generative AI model to generate continuous support messages for the user. Furthermore, by using wearable information devices such as smart glasses and smartwatches, it is possible to grasp the user's emotional state in real time even in the real world and provide personalized advice.

[0396] This system allows, for example, when a customer visits a physical store and says, "I've been feeling tired and down lately because of work," the server to recognize this negative emotional state and generate a specific product suggestion such as, "Why not try some relaxation items?"

[0397] Example of a prompt:

[0398] "Based on the following customer statements, generate appropriate support and suggestions. Consider the customer's emotional state and include suggestions to improve their shopping experience."

[0399] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0400] Step 1:

[0401] While the user is wearing a wearable information device, a virtual dialogue is initiated through the user interface of the information processing device. Voice input from the user is captured by the wearable information device (e.g., smart glasses), and this data is sent to the server. The input is voice data, and the output is a voice data file.

[0402] Step 2:

[0403] The server uses speech recognition software to convert the received audio data into text. The converted text data is then used as input for a natural language processing engine to evaluate the emotional state. The output is the analyzed emotional state and its stress level. Specifically, this involves classifying the emotional state as either positive, negative, or neutral.

[0404] Step 3:

[0405] Based on the analyzed emotional state, the server uses a generative AI model to generate appropriate support messages and product recommendations in response to prompts. The input is the emotional state and user profile, and the output is the generated personalized message. Specifically, the AI ​​model customizes the message using the user's past conversation history.

[0406] Step 4:

[0407] The server presents the generated personalized message to the user via an information processing device. The user receives the output message and reacts as needed. Specifically, this involves displaying the message as text on the user's display.

[0408] Step 5:

[0409] The system collects user feedback and stores it in a database. This feedback is then used to improve follow-up messages and subsequent interactions. In this step, the input is user feedback information, and the output is an updated user profile. Specifically, calculations are performed to predict the next response based on past data and optimize the system.

[0410] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0411] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0412] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0413] [Third Embodiment]

[0414] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0415] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0416] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0417] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0418] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0419] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0420] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0421] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0422] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0423] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0424] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0425] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0426] This invention is a system that enables users to manage their own mental health by engaging in virtual interactions via electronic devices. The system aims to provide users with mental health checks and advice in a simple and natural way.

[0427] Users initiate virtual conversations using devices such as smartphones or personal computers via a dedicated application. This application features an AI-powered interface that transmits conversation data with the user to a server in real time.

[0428] The server analyzes the received dialogue data using natural language processing techniques to assess the user's emotional state and stress level. The natural language processing techniques used here are designed to understand the dialogue content and recognize emotional expressions and stress indicators within the text. The evaluation results are used by the server to assess risk and identify the risk of mental illness.

[0429] As feedback to the user, the server generates follow-up messages and advice on specific actions. These generated messages are sent to the user's device and displayed automatically. The content of the messages is customized according to the problems the user is likely to be facing and includes specific suggestions for maintaining mental health.

[0430] For example, if a user says something like, "My work has been really tough lately, and I'm exhausted," the system analyzes this information and determines that the user is experiencing a high level of stress. As a result, the server generates and presents advice such as, "Take adequate rest and make time for hobbies to improve your well-being."

[0431] Furthermore, the system incorporates a feature that controls notifications to third parties (psychiatrists and support providers) as needed. This notification feature operates only with the user's consent, ensuring that support is only provided when necessary due to the user's situation.

[0432] Through this configuration, users can assess, manage, and improve their mental health in their daily lives without having to visit a regular medical institution.

[0433] The following describes the processing flow.

[0434] Step 1:

[0435] Users log in to the application using electronic devices. The device sends user authentication information to the server, which then authenticates the user by comparing it with information in the database.

[0436] Step 2:

[0437] The user initiates a virtual conversation via a chat interface. The terminal sends user input messages to the server in real time.

[0438] Step 3:

[0439] The server passes the received dialogue data to a natural language processing module. There, the generative AI analyzes the message and identifies the emotional state and stress level.

[0440] Step 4:

[0441] Based on the information analyzed by the generating AI, the server performs a mental illness risk assessment. This assessment uses accumulated data and reference values.

[0442] Step 5:

[0443] The server generates appropriate follow-up messages and advice based on the evaluation results. This generation process is tailored to include personalized information that is relevant to the user's specific situation.

[0444] Step 6:

[0445] The server sends the generated message to the terminal, which then displays advice to the user. The user reviews this information and takes action as needed.

[0446] Step 7:

[0447] If a user requests additional support, the device sends the request to the server. After confirming the user's consent, the server initiates a process to send a notification to a third party (such as a psychiatrist or support provider).

[0448] Step 8:

[0449] After the entire process is complete, the server records the analysis results in the user's profile and updates the database used for future follow-up.

[0450] (Example 1)

[0451] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0452] Many current mental health management systems are not easily accessible to individuals in their daily lives, and they struggle to assess mental health status in real time. This makes it difficult for users to receive timely and appropriate support to manage and improve their mental health. Furthermore, their ability to protect privacy and provide personalized support is limited.

[0453] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0454] In this invention, the server includes means for providing a user interface for an individual to initiate a virtual dialogue via an information processing device; means for performing automatic language analysis to analyze acquired dialogue information and evaluate psychological state and stress level; and means for transmitting information to a supporter as needed. This makes it possible for individuals to easily evaluate and manage their mental health in their daily lives and to quickly receive necessary support.

[0455] "Individual" refers to a user who uses this system to manage their mental health through virtual dialogue.

[0456] An "information processing device" is a communication terminal capable of electronic interaction, and includes, but is not limited to, smartphones and personal computers.

[0457] A "user interface" refers to the screens and operation modules that allow an individual to initiate a virtual interaction and perform operations through an information processing device.

[0458] "Automated language analysis" refers to the process of analyzing acquired dialogue information using natural language processing technology to evaluate psychological state and level of tension.

[0459] A "generative AI model" is a form of artificial intelligence technology used for analyzing dialogue content and generating advice, and refers to a program model that performs natural language processing.

[0460] A "supporter" refers to a person or organization that provides support and advice to an individual as needed, with the aim of supporting their life.

[0461] "Encryption technology" refers to security technology used to safely transmit acquired data, and is a means of maintaining the confidentiality of communication data.

[0462] "Virtual dialogue" refers to a form of dialogue that takes place via an information processing device and does not require face-to-face interaction in the real world.

[0463] "Psychological state" refers to an individual's mental state and includes various psychological elements such as emotions and stress levels.

[0464] "Stress level" refers to the degree of stress and anxiety an individual experiences and constitutes part of a psychological state assessment.

[0465] A description of the embodiment for carrying out the invention will be provided.

[0466] This system is designed to support the management and improvement of an individual's mental health in their daily life. Users use a smartphone or personal computer as an information processing device and initiate a virtual dialogue through a dedicated application. The application provides an intuitive user interface, allowing users to input their mental state in a natural way.

[0467] The user's device collects the entered conversation content in real time and sends it to the server. The collected data is securely transferred using encryption technology. Specifically, HTTPS is used as the encryption protocol.

[0468] The server analyzes the received data using a generative AI model. This analysis utilizes natural language processing techniques, with typical toolsets including BERT and GPT. Based on this, the server evaluates the user's psychological state and level of tension.

[0469] Based on the analyzed data, the server assesses the user's mental health risks. If necessary, personalized advice and tracking messages are generated and sent to the device. This allows users to receive support in taking appropriate actions in their daily lives.

[0470] For example, if a user enters the prompt "Please tell me about the stress you've been experiencing in your life recently. I'd like some advice on it," the server will analyze this information and evaluate the characteristic stressors. Then, it will provide the user with specific advice such as, "It's important to get adequate rest and make time for your hobbies."

[0471] Furthermore, the system has a function that contacts support providers as needed, based on the user's consent. This ensures that users facing serious mental health challenges can receive prompt professional support.

[0472] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0473] Step 1:

[0474] The user launches a dedicated application on their device and begins a virtual dialogue. Specifically, they select the "Start Mental Health Check" button using the app's UI. This action initiates user input, and the device prepares to collect dialogue data.

[0475] Step 2:

[0476] The device collects conversational information received from the user in real time. When voice input is used, speech recognition technology converts the speech into text. This input data is saved in text format for later processing.

[0477] Step 3:

[0478] The terminal encrypts the collected conversation information and sends it to the server. The information is securely transmitted over the internet using the HTTPS protocol. Input is user text data, and output is a secure data transmission to the server.

[0479] Step 4:

[0480] The server uses a generative AI model to analyze the received dialogue data. Specifically, it uses natural language processing techniques to analyze the data and evaluate the user's psychological state and level of tension. The input is encrypted dialogue data, and the output is the result of the analyzed psychological state evaluation.

[0481] Step 5:

[0482] The server assesses the user's mental health risks based on the analysis results. Then, if necessary, it generates personalized advice using AI. This advice is tailored to the user's stress and emotions. The input is the assessment results, and the output is the advice message provided to the user.

[0483] Step 6:

[0484] The server sends the generated advice to the user's terminal. The terminal receives this message and presents it to the user through the application's notification function. The input is the advice message, and the output is a visual presentation to the user.

[0485] Step 7:

[0486] If a user is facing certain risks, the system has a function that allows the server to send a notification to a supporter based on the user's consent. The inputs are the user's consent and risk assessment, and the output is the notification to the supporter.

[0487] (Application Example 1)

[0488] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0489] Managing mental health is difficult with conventional methods, as immediate support in daily life is challenging, and personalized advice, especially in online environments, is crucial. This invention aims to provide a way to make shopping and online activities more comfortable by offering immediate and appropriate feedback based on the user's emotional state in virtual stores and online platforms.

[0490] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0491] In this invention, the server includes means for providing an interface for the user to initiate a virtual dialogue via an electronic device; means for analyzing received dialogue data and performing natural language processing to evaluate the emotional state and stress level; and means for suggesting personalized products or activities based on the user's mental state. This enables individualized responses according to the user's emotional state.

[0492] An "interface for users to initiate virtual dialogue via electronic devices" refers to software and hardware settings that enable users to interact with artificial intelligence using smartphones or computers.

[0493] "Natural language processing for analyzing received dialogue data and evaluating emotional state and stress levels" refers to a technology that analyzes text and voice data obtained from users to determine their emotions and mental burden.

[0494] "Assessing the risk of mental illness based on analysis results and generating appropriate follow-up messages or advice" refers to a process that uses natural language processing to detect conditions that may affect mental health and provides users with corresponding information and guidelines.

[0495] "Presenting a generated message to the user via an electronic device" means sending a message automatically generated by the system to the user's terminal and displaying it on a screen or similar device.

[0496] "Sending notifications to supporters as needed" means that, with the user's consent, the system will send warnings or information to experts or support networks when it senses the need for intervention.

[0497] "Suggesting personalized products or activities based on the user's mental state" means providing choices that are more suitable than typical shopping or activities, based on the user's needs inferred from their emotional state.

[0498] To realize this application, the user uses an electronic device such as smart glasses. When the user wears the electronic device, the smart glasses continuously monitor the user's facial expressions and voice using their built-in camera and microphone. The collected data is initially processed on the device and then transmitted to a server via the internet.

[0499] The server analyzes the user's voice and facial expression data using data management software and natural language processing libraries such as TensorFlow. This allows the server to assess the user's emotional state and stress level. Based on the analysis results, the server generates messages through a generative AI model to suggest products and activities that the user might be interested in.

[0500] The generated messages are sent to the user's smart glasses via a cloud service and displayed to the user in real time. These messages include personalized shopping suggestions and online activity suggestions tailored to the user's emotional state.

[0501] For example, if a user says, "I'm tired today," the system analyzes that information and suggests products that have a relaxing effect. An example of a prompt message would be, "Please tell us how you're feeling right now. We have recommended products and activities to help relieve stress."

[0502] This system allows users to receive personalized support in a virtual space.

[0503] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0504] Step 1:

[0505] The user wears smart glasses and accesses a virtual store. The device uses its built-in camera and microphone to collect the user's facial expressions and voice data in real time. This input data is raw information that reflects the user's emotions and tone.

[0506] Step 2:

[0507] The terminal performs initial processing, compression, and format conversion of the collected audio and facial expression data. The output obtained in this step is data in a format suitable for transmission to the server. This data is transmitted to the server via the internet.

[0508] Step 3:

[0509] The server analyzes the received data by applying a natural language processing engine to audio data and converting it into text data. For facial expression data, it uses an image recognition algorithm to perform emotion analysis. The input is pre-processed data, and the output is an index indicating the user's emotional state and stress level.

[0510] Step 4:

[0511] Based on the analysis results, the server uses a generative AI model to generate recommendation messages for products and activities that the user might be interested in. The output of this step is personalized advice and product recommendation lists for each individual user.

[0512] Step 5:

[0513] The server sends the generated message to the user's terminal via a cloud service. The terminal receives the message and displays it in the user's field of view. The input is the generated text message, and the output is visual information for the user.

[0514] Step 6:

[0515] Users review suggestions displayed on their devices and advance their shopping experience by selecting recommended products and activities. This step leads to product selection and subsequent actions by the user.

[0516] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0517] This invention is a system that allows users to engage in virtual dialogue via electronic devices and analyzes the resulting dialogue data. In particular, by incorporating an emotion engine, it enables a precise understanding of the user's emotional state. The aim of this system is to more accurately assess the user's mental health and provide appropriate advice.

[0518] Users initiate virtual interactions through a specific application using devices such as smartphones or personal computers. This application is equipped with a generative AI and emotion engine, which transmits user input to a server in real time.

[0519] The server uses natural language processing techniques to analyze received dialogue data and recognizes the user's emotions using an emotion engine. The emotion engine extracts emotions from the dialogue content and forms emotion categories such as positive, negative, and neutral. This emotion information is then used to evaluate the emotional state and stress level.

[0520] The server's evaluation results are further analyzed by a generating AI to determine the presence or absence of a risk of mental illness. Based on this, follow-up messages and advice are generated as customized information that takes into account the user's emotional state. This allows users to receive more personalized advice.

[0521] For example, if a user says something like, "I've been feeling down lately," the server recognizes this negative emotion and uses it to generate positive advice such as, "You might be able to cheer yourself up by spending time on your hobbies."

[0522] Furthermore, the emotion engine has the ability to learn the user's emotions over the long term and record emotional trends and changes. This makes it possible to improve the accuracy of risk assessment and follow-up over the long term.

[0523] In the above configuration, the present invention enables users to monitor their mental state on a daily basis and take appropriate action without having to visit a specialized medical institution.

[0524] The following describes the processing flow.

[0525] Step 1:

[0526] The user opens a dedicated application on their device and logs in. The device sends the user's authentication information to the server, which then verifies it against the database to perform authentication.

[0527] Step 2:

[0528] The user initiates a virtual conversation using the application's chat interface. The device sends the user's input messages to the server in real time.

[0529] Step 3:

[0530] The server sends the received dialogue data to a natural language processing module for analysis. This module analyzes the text and extracts keywords and context that indicate emotion.

[0531] Step 4:

[0532] The emotion engine on the server identifies the user's emotions based on the analyzed data. The emotion engine classifies the input message into emotional categories such as positive, negative, and neutral.

[0533] Step 5:

[0534] The server uses emotional information from the emotion engine to assess emotional state and stress levels. This includes a process of comparing it with existing emotional data.

[0535] Step 6:

[0536] Based on the evaluation results, the server determines whether or not there is a risk of mental illness. This determination is made by considering risk criteria and emotional information.

[0537] Step 7:

[0538] The server utilizes AI to generate personalized follow-up messages or advice for each user, taking into account their emotional state.

[0539] Step 8:

[0540] The server sends the generated message to the terminal, which then displays it to the user. The user reviews the advice and follows the instructions as needed.

[0541] Step 9:

[0542] If a user requests additional support or follow-up, the device sends the request to the server. The server verifies the user's consent and, if necessary, configures notifications to third parties.

[0543] Step 10:

[0544] After the process is complete, the server records the user's analysis results in an individual profile, which will be used for future follow-up. This enhances long-term support for the user.

[0545] (Example 2)

[0546] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0547] In modern society, maintaining mental health is becoming increasingly important for users. However, many users find it difficult to monitor their mental state without visiting a medical institution, making it challenging to take appropriate measures early on. To address this challenge, there is a need for a system that allows users to easily manage their mental state on a daily basis.

[0548] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0549] In this invention, the server includes means for providing a user interface for initiating a virtual dialogue via an information processing device; means for analyzing received dialogue data and using language processing techniques to evaluate emotional state and stress indicators; and means for evaluating mental health risks based on the analysis results and generating appropriate follow-up messages or advice. This enables users to monitor their mental state on a daily basis and take appropriate measures quickly as needed.

[0550] An "information processing device" is a digital device that performs functions such as inputting, processing, storing, and outputting information, and includes smartphones, tablets, and laptop computers.

[0551] A "user interface" refers to the screens and operating methods that users use to access and operate information processing equipment, and includes visual input forms and interactive menus.

[0552] "Language processing technology" is a field of computer science that interprets and analyzes human language, and includes techniques such as natural language processing and text mining.

[0553] An "emotion engine" is software that analyzes and classifies emotional states from input data, and includes functions to categorize the user's emotions as positive, negative, neutral, etc.

[0554] A "follow-up message" is a message of advice or warning that is generated based on analysis results and evaluations and presented to the user.

[0555] "Mental health risk" refers to an indicator of an individual's likelihood of experiencing mental health problems, and includes factors such as stress levels and changes in emotional state.

[0556] This invention is a system that allows users to efficiently monitor their own mental state via an information processing device and take appropriate measures as needed. Users launch a specific application using an information processing device such as a smartphone or personal computer and initiate a virtual dialogue. This prepares the system to process user input data in real time, utilizing a generative AI model and an emotion engine.

[0557] The terminal sends the text entered by the user to the server. The server receives this data and analyzes it using language processing technologies such as Python and TensorFlow. In this analysis process, an emotion engine extracts emotions from the text data and classifies them into positive, negative, and neutral categories. This information is used to evaluate the user's emotional state and stress indicators.

[0558] Based on the evaluation results, the server uses a generative AI model to generate follow-up messages or advice. This allows users to receive customized advice tailored to their individual circumstances. The generated messages are presented to the user via their device.

[0559] For example, if a user inputs "I've been feeling down lately," the server recognizes this negative emotion and sends positive advice to the user's device, such as "You might be able to cheer yourself up by spending time on your hobbies." Furthermore, the emotion engine records long-term changes in emotions, enabling continuous monitoring.

[0560] This invention enables users to easily manage their mental state in their daily lives and take necessary actions quickly. By using a generative AI model and prompt text, more accurate support can be provided.

[0561] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0562] Step 1:

[0563] The user uses an information processing device to access a specific application and initiate a virtual interaction. The input here is text data about the user's emotional state and situation, and this data is sent to the server by the terminal as output. The user performs actions such as inputting specific questions and their own emotions as text and sending them.

[0564] Step 2:

[0565] The terminal sends the text entered by the user to the server. The input here is raw text data sent by the user, and the output is text data securely transferred to the server. The terminal uses security protocols to protect the data during transmission.

[0566] Step 3:

[0567] The server analyzes the received text data using natural language processing techniques. The input is text data received from the terminal, and the output is the generated sentiment categories after analysis. The server uses Python and TensorFlow to perform natural language processing and extract sentiments such as positive, negative, and neutral.

[0568] Step 4:

[0569] The server evaluates the user's emotional state and stress indicators based on emotional information extracted by the emotion engine. The input is emotional information based on the analysis results, and the output is an evaluation of the emotional state. The server then performs operations to evaluate indicators such as stress levels as numerical values.

[0570] Step 5:

[0571] The server uses a generative AI model to create appropriate follow-up messages based on the evaluation results. The input is the user's emotional state evaluation result, and the output is a personalized advice message. The server takes a prompt sentence and uses natural language generation technology to generate specific advice.

[0572] Step 6:

[0573] The server sends the generated message to the terminal and presents it to the user. The input is the generated text message, and the output is the message presented to the user. The terminal displays the received message on its screen, allowing the user to confirm it.

[0574] (Application Example 2)

[0575] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0576] In modern society, there is a problem in that it is difficult to manage users' mental health on a daily and accurate basis. Furthermore, in real-world customer interactions, it is difficult to instantly grasp a customer's emotional state and recommend personalized products or services accordingly. Therefore, a new system is needed to solve these problems.

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

[0578] In this invention, the server includes means for providing a user interface for a user to initiate a virtual dialogue via an information processing device; means for performing natural language processing to analyze received dialogue information and evaluate emotional state and level of pressure; and means for analyzing the user's emotional state and making personalized product or service recommendations using wearable information devices used in real-world spatial interactions. This makes it possible to understand the user's emotional state and enable personalized responses.

[0579] A "user interface" is a function that provides screen displays and operating methods for users to operate an information processing device.

[0580] "Dialogue information" refers to communication data such as voice and text exchanged between users via information processing devices.

[0581] "Emotional state" refers to information that indicates the user's emotional response and psychological state.

[0582] "Degree of pressure" is a measure that represents the level of stress and burden felt by the user.

[0583] "Natural language processing" is a technology that allows computers to understand and analyze human language.

[0584] "Wearable information devices" refer to information processing devices designed to be carried or worn by users.

[0585] "Personalized products or services" refer to specialized products or support that are tailored to the specific needs and circumstances of the user.

[0586] "Continuing support messages" are advice and encouragement sent regularly to support the mental health of users.

[0587] "Notification" refers to a means of notification or communication to inform a third party of information.

[0588] The system for realizing this invention is based on the user initiating a virtual dialogue using an information processing device, and conducting that dialogue through a wearable information device. The server receives the user's dialogue information acquired through the user interface and performs natural language processing to evaluate the user's emotional state and level of stress. This enables personalized recommendations of products or services.

[0589] The specific technology involves combining speech recognition software with a natural language processing engine for text analysis. In this system, the server analyzes the received dialogue information and uses a generative AI model to generate continuous support messages for the user. Furthermore, by using wearable information devices such as smart glasses and smartwatches, it is possible to grasp the user's emotional state in real time even in the real world and provide personalized advice.

[0590] This system allows, for example, when a customer visits a physical store and says, "I've been feeling tired and down lately because of work," the server to recognize this negative emotional state and generate a specific product suggestion such as, "Why not try some relaxation items?"

[0591] Example of a prompt:

[0592] "Based on the following customer statements, generate appropriate support and suggestions. Consider the customer's emotional state and include suggestions to improve their shopping experience."

[0593] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0594] Step 1:

[0595] While the user is wearing a wearable information device, a virtual dialogue is initiated through the user interface of the information processing device. Voice input from the user is captured by the wearable information device (e.g., smart glasses), and this data is sent to the server. The input is voice data, and the output is a voice data file.

[0596] Step 2:

[0597] The server uses speech recognition software to convert the received audio data into text. The converted text data is then used as input for a natural language processing engine to evaluate the emotional state. The output is the analyzed emotional state and its stress level. Specifically, this involves classifying the emotional state as either positive, negative, or neutral.

[0598] Step 3:

[0599] Based on the analyzed emotional state, the server uses a generative AI model to generate appropriate support messages and product recommendations in response to prompts. The input is the emotional state and user profile, and the output is the generated personalized message. Specifically, the AI ​​model customizes the message using the user's past conversation history.

[0600] Step 4:

[0601] The server presents the generated personalized message to the user via an information processing device. The user receives the output message and reacts as needed. Specifically, this involves displaying the message as text on the user's display.

[0602] Step 5:

[0603] The system collects user feedback and stores it in a database. This feedback is then used to improve follow-up messages and subsequent interactions. In this step, the input is user feedback information, and the output is an updated user profile. Specifically, calculations are performed to predict the next response based on past data and optimize the system.

[0604] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0605] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0606] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0607] [Fourth Embodiment]

[0608] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0609] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0610] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0611] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0612] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0613] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0614] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0615] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0616] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0617] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0618] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0619] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0620] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0621] This invention is a system that enables users to manage their own mental health by engaging in virtual interactions via electronic devices. The system aims to provide users with mental health checks and advice in a simple and natural way.

[0622] Users initiate virtual conversations using devices such as smartphones or personal computers via a dedicated application. This application features an AI-powered interface that transmits conversation data with the user to a server in real time.

[0623] The server analyzes the received dialogue data using natural language processing techniques to assess the user's emotional state and stress level. The natural language processing techniques used here are designed to understand the dialogue content and recognize emotional expressions and stress indicators within the text. The evaluation results are used by the server to assess risk and identify the risk of mental illness.

[0624] As feedback to the user, the server generates follow-up messages and advice on specific actions. These generated messages are sent to the user's device and displayed automatically. The content of the messages is customized according to the problems the user is likely to be facing and includes specific suggestions for maintaining mental health.

[0625] For example, if a user says something like, "My work has been really tough lately, and I'm exhausted," the system analyzes this information and determines that the user is experiencing a high level of stress. As a result, the server generates and presents advice such as, "Take adequate rest and make time for hobbies to improve your well-being."

[0626] Furthermore, the system incorporates a feature that controls notifications to third parties (psychiatrists and support providers) as needed. This notification feature operates only with the user's consent, ensuring that support is only provided when necessary due to the user's situation.

[0627] Through this configuration, users can assess, manage, and improve their mental health in their daily lives without having to visit a regular medical institution.

[0628] The following describes the processing flow.

[0629] Step 1:

[0630] Users log in to the application using electronic devices. The device sends user authentication information to the server, which then authenticates the user by comparing it with information in the database.

[0631] Step 2:

[0632] The user initiates a virtual conversation via a chat interface. The terminal sends user input messages to the server in real time.

[0633] Step 3:

[0634] The server passes the received dialogue data to a natural language processing module. There, the generative AI analyzes the message and identifies the emotional state and stress level.

[0635] Step 4:

[0636] Based on the information analyzed by the generating AI, the server performs a mental illness risk assessment. This assessment uses accumulated data and reference values.

[0637] Step 5:

[0638] The server generates appropriate follow-up messages and advice based on the evaluation results. This generation process is tailored to include personalized information that is relevant to the user's specific situation.

[0639] Step 6:

[0640] The server sends the generated message to the terminal, which then displays advice to the user. The user reviews this information and takes action as needed.

[0641] Step 7:

[0642] If a user requests additional support, the device sends the request to the server. After confirming the user's consent, the server initiates a process to send a notification to a third party (such as a psychiatrist or support provider).

[0643] Step 8:

[0644] After the entire process is complete, the server records the analysis results in the user's profile and updates the database used for future follow-up.

[0645] (Example 1)

[0646] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0647] Many current mental health management systems are not easily accessible to individuals in their daily lives, and they struggle to assess mental health status in real time. This makes it difficult for users to receive timely and appropriate support to manage and improve their mental health. Furthermore, their ability to protect privacy and provide personalized support is limited.

[0648] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0649] In this invention, the server includes means for providing a user interface for an individual to initiate a virtual dialogue via an information processing device; means for performing automatic language analysis to analyze acquired dialogue information and evaluate psychological state and stress level; and means for transmitting information to a supporter as needed. This makes it possible for individuals to easily evaluate and manage their mental health in their daily lives and to quickly receive necessary support.

[0650] "Individual" refers to a user who uses this system to manage their mental health through virtual dialogue.

[0651] An "information processing device" is a communication terminal capable of electronic interaction, and includes, but is not limited to, smartphones and personal computers.

[0652] A "user interface" refers to the screens and operation modules that allow an individual to initiate a virtual interaction and perform operations through an information processing device.

[0653] "Automated language analysis" refers to the process of analyzing acquired dialogue information using natural language processing technology to evaluate psychological state and level of tension.

[0654] A "generative AI model" is a form of artificial intelligence technology used for analyzing dialogue content and generating advice, and refers to a program model that performs natural language processing.

[0655] A "supporter" refers to a person or organization that provides support and advice to an individual as needed, with the aim of supporting their life.

[0656] "Encryption technology" refers to security technology used to safely transmit acquired data, and is a means of maintaining the confidentiality of communication data.

[0657] "Virtual dialogue" refers to a form of dialogue that takes place via an information processing device and does not require face-to-face interaction in the real world.

[0658] "Psychological state" refers to an individual's mental state and includes various psychological elements such as emotions and stress levels.

[0659] "Stress level" refers to the degree of stress and anxiety an individual experiences and constitutes part of a psychological state assessment.

[0660] A description of the embodiment for carrying out the invention will be provided.

[0661] This system is designed to support the management and improvement of an individual's mental health in their daily life. Users use a smartphone or personal computer as an information processing device and initiate a virtual dialogue through a dedicated application. The application provides an intuitive user interface, allowing users to input their mental state in a natural way.

[0662] The user's device collects the entered conversation content in real time and sends it to the server. The collected data is securely transferred using encryption technology. Specifically, HTTPS is used as the encryption protocol.

[0663] The server analyzes the received data using a generative AI model. This analysis utilizes natural language processing techniques, with typical toolsets including BERT and GPT. Based on this, the server evaluates the user's psychological state and level of tension.

[0664] Based on the analyzed data, the server assesses the user's mental health risks. If necessary, personalized advice and tracking messages are generated and sent to the device. This allows users to receive support in taking appropriate actions in their daily lives.

[0665] For example, if a user enters the prompt "Please tell me about the stress you've been experiencing in your life recently. I'd like some advice on it," the server will analyze this information and evaluate the characteristic stressors. Then, it will provide the user with specific advice such as, "It's important to get adequate rest and make time for your hobbies."

[0666] Furthermore, the system has a function that contacts support providers as needed, based on the user's consent. This ensures that users facing serious mental health challenges can receive prompt professional support.

[0667] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0668] Step 1:

[0669] The user launches a dedicated application on their device and begins a virtual dialogue. Specifically, they select the "Start Mental Health Check" button using the app's UI. This action initiates user input, and the device prepares to collect dialogue data.

[0670] Step 2:

[0671] The device collects conversational information received from the user in real time. When voice input is used, speech recognition technology converts the speech into text. This input data is saved in text format for later processing.

[0672] Step 3:

[0673] The terminal encrypts the collected conversation information and sends it to the server. The information is securely transmitted over the internet using the HTTPS protocol. Input is user text data, and output is a secure data transmission to the server.

[0674] Step 4:

[0675] The server uses a generative AI model to analyze the received dialogue data. Specifically, it uses natural language processing techniques to analyze the data and evaluate the user's psychological state and level of tension. The input is encrypted dialogue data, and the output is the result of the analyzed psychological state evaluation.

[0676] Step 5:

[0677] The server assesses the user's mental health risks based on the analysis results. Then, if necessary, it generates personalized advice using AI. This advice is tailored to the user's stress and emotions. The input is the assessment results, and the output is the advice message provided to the user.

[0678] Step 6:

[0679] The server sends the generated advice to the user's terminal. The terminal receives this message and presents it to the user through the application's notification function. The input is the advice message, and the output is a visual presentation to the user.

[0680] Step 7:

[0681] If a user is facing certain risks, the system has a function that allows the server to send a notification to a supporter based on the user's consent. The inputs are the user's consent and risk assessment, and the output is the notification to the supporter.

[0682] (Application Example 1)

[0683] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0684] Managing mental health is difficult with conventional methods, as immediate support in daily life is challenging, and personalized advice, especially in online environments, is crucial. This invention aims to provide a way to make shopping and online activities more comfortable by offering immediate and appropriate feedback based on the user's emotional state in virtual stores and online platforms.

[0685] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0686] In this invention, the server includes means for providing an interface for the user to initiate a virtual dialogue via an electronic device; means for analyzing received dialogue data and performing natural language processing to evaluate the emotional state and stress level; and means for suggesting personalized products or activities based on the user's mental state. This enables individualized responses according to the user's emotional state.

[0687] An "interface for users to initiate virtual dialogue via electronic devices" refers to software and hardware settings that enable users to interact with artificial intelligence using smartphones or computers.

[0688] "Natural language processing for analyzing received dialogue data and evaluating emotional state and stress levels" refers to a technology that analyzes text and voice data obtained from users to determine their emotions and mental burden.

[0689] "Assessing the risk of mental illness based on analysis results and generating appropriate follow-up messages or advice" refers to a process that uses natural language processing to detect conditions that may affect mental health and provides users with corresponding information and guidelines.

[0690] "Presenting a generated message to the user via an electronic device" means sending a message automatically generated by the system to the user's terminal and displaying it on a screen or similar device.

[0691] "Sending notifications to supporters as needed" means that, with the user's consent, the system will send warnings or information to experts or support networks when it senses the need for intervention.

[0692] "Suggesting personalized products or activities based on the user's mental state" means providing choices that are more suitable than typical shopping or activities, based on the user's needs inferred from their emotional state.

[0693] To realize this application, the user uses an electronic device such as smart glasses. When the user wears the electronic device, the smart glasses continuously monitor the user's facial expressions and voice using their built-in camera and microphone. The collected data is initially processed on the device and then transmitted to a server via the internet.

[0694] The server analyzes the user's voice and facial expression data using data management software and natural language processing libraries such as TensorFlow. This allows the server to assess the user's emotional state and stress level. Based on the analysis results, the server generates messages through a generative AI model to suggest products and activities that the user might be interested in.

[0695] The generated messages are sent to the user's smart glasses via a cloud service and displayed to the user in real time. These messages include personalized shopping suggestions and online activity suggestions tailored to the user's emotional state.

[0696] For example, if a user says, "I'm tired today," the system analyzes that information and suggests products that have a relaxing effect. An example of a prompt message would be, "Please tell us how you're feeling right now. We have recommended products and activities to help relieve stress."

[0697] This system allows users to receive personalized support in a virtual space.

[0698] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0699] Step 1:

[0700] The user wears smart glasses and accesses a virtual store. The device uses its built-in camera and microphone to collect the user's facial expressions and voice data in real time. This input data is raw information that reflects the user's emotions and tone.

[0701] Step 2:

[0702] The terminal performs initial processing, compression, and format conversion of the collected audio and facial expression data. The output obtained in this step is data in a format suitable for transmission to the server. This data is transmitted to the server via the internet.

[0703] Step 3:

[0704] The server analyzes the received data by applying a natural language processing engine to audio data and converting it into text data. For facial expression data, it uses an image recognition algorithm to perform emotion analysis. The input is pre-processed data, and the output is an index indicating the user's emotional state and stress level.

[0705] Step 4:

[0706] Based on the analysis results, the server uses a generative AI model to generate recommendation messages for products and activities that the user might be interested in. The output of this step is personalized advice and product recommendation lists for each individual user.

[0707] Step 5:

[0708] The server sends the generated message to the user's terminal via a cloud service. The terminal receives the message and displays it in the user's field of view. The input is the generated text message, and the output is visual information for the user.

[0709] Step 6:

[0710] Users review suggestions displayed on their devices and advance their shopping experience by selecting recommended products and activities. This step leads to product selection and subsequent actions by the user.

[0711] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0712] This invention is a system that allows users to engage in virtual dialogue via electronic devices and analyzes the resulting dialogue data. In particular, by incorporating an emotion engine, it enables a precise understanding of the user's emotional state. The aim of this system is to more accurately assess the user's mental health and provide appropriate advice.

[0713] Users initiate virtual interactions through a specific application using devices such as smartphones or personal computers. This application is equipped with a generative AI and emotion engine, which transmits user input to a server in real time.

[0714] The server uses natural language processing techniques to analyze received dialogue data and recognizes the user's emotions using an emotion engine. The emotion engine extracts emotions from the dialogue content and forms emotion categories such as positive, negative, and neutral. This emotion information is then used to evaluate the emotional state and stress level.

[0715] The server's evaluation results are further analyzed by a generating AI to determine the presence or absence of a risk of mental illness. Based on this, follow-up messages and advice are generated as customized information that takes into account the user's emotional state. This allows users to receive more personalized advice.

[0716] For example, if a user says something like, "I've been feeling down lately," the server recognizes this negative emotion and uses it to generate positive advice such as, "You might be able to cheer yourself up by spending time on your hobbies."

[0717] Furthermore, the emotion engine has the ability to learn the user's emotions over the long term and record emotional trends and changes. This makes it possible to improve the accuracy of risk assessment and follow-up over the long term.

[0718] In the above configuration, the present invention enables users to monitor their mental state on a daily basis and take appropriate action without having to visit a specialized medical institution.

[0719] The following describes the processing flow.

[0720] Step 1:

[0721] The user opens a dedicated application on their device and logs in. The device sends the user's authentication information to the server, which then verifies it against the database to perform authentication.

[0722] Step 2:

[0723] The user initiates a virtual conversation using the application's chat interface. The device sends the user's input messages to the server in real time.

[0724] Step 3:

[0725] The server sends the received dialogue data to a natural language processing module for analysis. This module analyzes the text and extracts keywords and context that indicate emotion.

[0726] Step 4:

[0727] The emotion engine on the server identifies the user's emotions based on the analyzed data. The emotion engine classifies the input message into emotional categories such as positive, negative, and neutral.

[0728] Step 5:

[0729] The server uses emotional information from the emotion engine to assess emotional state and stress levels. This includes a process of comparing it with existing emotional data.

[0730] Step 6:

[0731] Based on the evaluation results, the server determines whether or not there is a risk of mental illness. This determination is made by considering risk criteria and emotional information.

[0732] Step 7:

[0733] The server utilizes AI to generate personalized follow-up messages or advice for each user, taking into account their emotional state.

[0734] Step 8:

[0735] The server sends the generated message to the terminal, which then displays it to the user. The user reviews the advice and follows the instructions as needed.

[0736] Step 9:

[0737] If a user requests additional support or follow-up, the device sends the request to the server. The server verifies the user's consent and, if necessary, configures notifications to third parties.

[0738] Step 10:

[0739] After the process is complete, the server records the user's analysis results in an individual profile, which will be used for future follow-up. This enhances long-term support for the user.

[0740] (Example 2)

[0741] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0742] In modern society, maintaining mental health is becoming increasingly important for users. However, many users find it difficult to monitor their mental state without visiting a medical institution, making it challenging to take appropriate measures early on. To address this challenge, there is a need for a system that allows users to easily manage their mental state on a daily basis.

[0743] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0744] In this invention, the server includes means for providing a user interface for initiating a virtual dialogue via an information processing device; means for analyzing received dialogue data and using language processing techniques to evaluate emotional state and stress indicators; and means for evaluating mental health risks based on the analysis results and generating appropriate follow-up messages or advice. This enables users to monitor their mental state on a daily basis and take appropriate measures quickly as needed.

[0745] An "information processing device" is a digital device that performs functions such as inputting, processing, storing, and outputting information, and includes smartphones, tablets, and laptop computers.

[0746] A "user interface" refers to the screens and operating methods that users use to access and operate information processing equipment, and includes visual input forms and interactive menus.

[0747] "Language processing technology" is a field of computer science that interprets and analyzes human language, and includes techniques such as natural language processing and text mining.

[0748] An "emotion engine" is software that analyzes and classifies emotional states from input data, and includes functions to categorize the user's emotions as positive, negative, neutral, etc.

[0749] A "follow-up message" is a message of advice or warning that is generated based on analysis results and evaluations and presented to the user.

[0750] "Mental health risk" refers to an indicator of an individual's likelihood of experiencing mental health problems, and includes factors such as stress levels and changes in emotional state.

[0751] This invention is a system that allows users to efficiently monitor their own mental state via an information processing device and take appropriate measures as needed. Users launch a specific application using an information processing device such as a smartphone or personal computer and initiate a virtual dialogue. This prepares the system to process user input data in real time, utilizing a generative AI model and an emotion engine.

[0752] The terminal sends the text entered by the user to the server. The server receives this data and analyzes it using language processing technologies such as Python and TensorFlow. In this analysis process, an emotion engine extracts emotions from the text data and classifies them into positive, negative, and neutral categories. This information is used to evaluate the user's emotional state and stress indicators.

[0753] Based on the evaluation results, the server uses a generative AI model to generate follow-up messages or advice. This allows users to receive customized advice tailored to their individual circumstances. The generated messages are presented to the user via their device.

[0754] For example, if a user inputs "I've been feeling down lately," the server recognizes this negative emotion and sends positive advice to the user's device, such as "You might be able to cheer yourself up by spending time on your hobbies." Furthermore, the emotion engine records long-term changes in emotions, enabling continuous monitoring.

[0755] This invention enables users to easily manage their mental state in their daily lives and take necessary actions quickly. By using a generative AI model and prompt text, more accurate support can be provided.

[0756] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0757] Step 1:

[0758] The user uses an information processing device to access a specific application and initiate a virtual interaction. The input here is text data about the user's emotional state and situation, and this data is sent to the server by the terminal as output. The user performs actions such as inputting specific questions and their own emotions as text and sending them.

[0759] Step 2:

[0760] The terminal sends the text entered by the user to the server. The input here is raw text data sent by the user, and the output is text data securely transferred to the server. The terminal uses security protocols to protect the data during transmission.

[0761] Step 3:

[0762] The server analyzes the received text data using natural language processing techniques. The input is text data received from the terminal, and the output is the generated sentiment categories after analysis. The server uses Python and TensorFlow to perform natural language processing and extract sentiments such as positive, negative, and neutral.

[0763] Step 4:

[0764] The server evaluates the user's emotional state and stress indicators based on emotional information extracted by the emotion engine. The input is emotional information based on the analysis results, and the output is an evaluation of the emotional state. The server then performs operations to evaluate indicators such as stress levels as numerical values.

[0765] Step 5:

[0766] The server uses a generative AI model to create appropriate follow-up messages based on the evaluation results. The input is the user's emotional state evaluation result, and the output is a personalized advice message. The server takes a prompt sentence and uses natural language generation technology to generate specific advice.

[0767] Step 6:

[0768] The server sends the generated message to the terminal and presents it to the user. The input is the generated text message, and the output is the message presented to the user. The terminal displays the received message on its screen, allowing the user to confirm it.

[0769] (Application Example 2)

[0770] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0771] In modern society, there is a problem in that it is difficult to manage users' mental health on a daily and accurate basis. Furthermore, in real-world customer interactions, it is difficult to instantly grasp a customer's emotional state and recommend personalized products or services accordingly. Therefore, a new system is needed to solve these problems.

[0772] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0773] In this invention, the server includes means for providing a user interface for a user to initiate a virtual dialogue via an information processing device; means for performing natural language processing to analyze received dialogue information and evaluate emotional state and level of pressure; and means for analyzing the user's emotional state and making personalized product or service recommendations using wearable information devices used in real-world spatial interactions. This makes it possible to understand the user's emotional state and enable personalized responses.

[0774] A "user interface" is a function that provides screen displays and operating methods for users to operate an information processing device.

[0775] "Dialogue information" refers to communication data such as voice and text exchanged between users via information processing devices.

[0776] "Emotional state" refers to information that indicates the user's emotional response and psychological state.

[0777] "Degree of pressure" is a measure that represents the level of stress and burden felt by the user.

[0778] "Natural language processing" is a technology that allows computers to understand and analyze human language.

[0779] "Wearable information devices" refer to information processing devices designed to be carried or worn by users.

[0780] "Personalized products or services" refer to specialized products or support that are tailored to the specific needs and circumstances of the user.

[0781] "Continuing support messages" are advice and encouragement sent regularly to support the mental health of users.

[0782] "Notification" refers to a means of notification or communication to inform a third party of information.

[0783] The system for realizing this invention is based on the user initiating a virtual dialogue using an information processing device, and conducting that dialogue through a wearable information device. The server receives the user's dialogue information acquired through the user interface and performs natural language processing to evaluate the user's emotional state and level of stress. This enables personalized recommendations of products or services.

[0784] The specific technology involves combining speech recognition software with a natural language processing engine for text analysis. In this system, the server analyzes the received dialogue information and uses a generative AI model to generate continuous support messages for the user. Furthermore, by using wearable information devices such as smart glasses and smartwatches, it is possible to grasp the user's emotional state in real time even in the real world and provide personalized advice.

[0785] This system allows, for example, when a customer visits a physical store and says, "I've been feeling tired and down lately because of work," the server to recognize this negative emotional state and generate a specific product suggestion such as, "Why not try some relaxation items?"

[0786] Example of a prompt:

[0787] "Based on the following customer statements, generate appropriate support and suggestions. Consider the customer's emotional state and include suggestions to improve their shopping experience."

[0788] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0789] Step 1:

[0790] While the user is wearing a wearable information device, a virtual dialogue is initiated through the user interface of the information processing device. Voice input from the user is captured by the wearable information device (e.g., smart glasses), and this data is sent to the server. The input is voice data, and the output is a voice data file.

[0791] Step 2:

[0792] The server uses speech recognition software to convert the received audio data into text. The converted text data is then used as input for a natural language processing engine to evaluate the emotional state. The output is the analyzed emotional state and its stress level. Specifically, this involves classifying the emotional state as either positive, negative, or neutral.

[0793] Step 3:

[0794] Based on the analyzed emotional state, the server uses a generative AI model to generate appropriate support messages and product recommendations in response to prompts. The input is the emotional state and user profile, and the output is the generated personalized message. Specifically, the AI ​​model customizes the message using the user's past conversation history.

[0795] Step 4:

[0796] The server presents the generated personalized message to the user via an information processing device. The user receives the output message and reacts as needed. Specifically, this involves displaying the message as text on the user's display.

[0797] Step 5:

[0798] The system collects user feedback and stores it in a database. This feedback is then used to improve follow-up messages and subsequent interactions. In this step, the input is user feedback information, and the output is an updated user profile. Specifically, calculations are performed to predict the next response based on past data and optimize the system.

[0799] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0800] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0801] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0802] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0803] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0804] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0805] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0806] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0807] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0808] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0809] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0810] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0811] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0812] 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.

[0813] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0814] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0815] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0816] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0817] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0818] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0819] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0820] The following is further disclosed regarding the embodiments described above.

[0821] (Claim 1)

[0822] [Means of providing an interface for a user to initiate a virtual interaction via an electronic device,

[0823] [Means for performing natural language processing to analyze received dialogue data and evaluate emotional state and stress level,

[0824] [Means for evaluating the risk of psychosis based on the analysis results and generating appropriate follow-up messages or advice,

[0825] [Means for presenting the generated message to the user via an electronic device,

[0826] [Means of sending notifications to supporters as needed,

[0827] A system that includes this.

[0828] (Claim 2)

[0829] [The system according to claim 1, which controls notifications to third parties based on the user's consent.

[0830] (Claim 3)

[0831] [The system according to claim 1, which records the analysis results for each user as an individual profile and improves the efficiency of follow-up.

[0832] "Example 1"

[0833] (Claim 1)

[0834] [Means for providing a user interface for an individual to initiate a virtual dialogue via an information processing device,

[0835] [Means for performing automated language analysis to analyze acquired dialogue information and evaluate psychological state and tension level,

[0836] [Means for evaluating the risk of mental disorder based on analysis results and generating appropriate follow-up messages or advice,

[0837] [Means of presenting the generated message to an individual via an information processing device,

[0838] [Means of sending information to supporters as needed,

[0839] [Methods that use encryption technology to securely exchange acquired conversation information,

[0840] [Methods for using generative AI models to analyze user emotions,

[0841] A system that includes this.

[0842] (Claim 2)

[0843] [A system according to claim 1 that controls the provision of information to external parties based on the individual's consent.

[0844] (Claim 3)

[0845] [The system according to claim 1, which records the analysis results for each individual as independent information and improves the efficiency of tracking.

[0846] "Application Example 1"

[0847] (Claim 1)

[0848] [Means of providing an interface for a user to initiate a virtual interaction via an electronic device,

[0849] [Means for performing natural language processing to analyze received dialogue data and evaluate emotional state and stress level,

[0850] [Means for evaluating the risk of psychosis based on the analysis results and generating appropriate follow-up messages or advice,

[0851] [Means for presenting the generated message to the user via an electronic device,

[0852] [Means of sending notifications to supporters as needed,

[0853] [Means of suggesting personalized products or activities based on the user's mental state,

[0854] A system that includes this.

[0855] (Claim 2)

[0856] [The system according to claim 1, which controls notifications to third parties based on the user's consent.

[0857] (Claim 3)

[0858] [The system according to claim 1, which records the analysis results for each user as an individual profile and improves the efficiency of follow-up.

[0859] "Example 2 of combining an emotion engine"

[0860] (Claim 1)

[0861] [Means for providing a user interface for initiating a virtual dialogue via an information processing device,

[0862] [Means of using language processing techniques to analyze received dialogue data and evaluate emotional state and stress indicators,

[0863] [Means for evaluating mental health risks based on analysis results and generating appropriate follow-up messages or advice,

[0864] [Means for presenting the generated message to the user via an information processing device,

[0865] [Means of sending notifications to relevant parties as needed,

[0866] [A means of improving the accuracy of analysis by classifying emotions using an emotion engine and recording that information over the long term,

[0867] A system that includes this.

[0868] (Claim 2)

[0869] [The system according to claim 1, which controls the notification of relevant information to third parties based on the user's consent.

[0870] (Claim 3)

[0871] [The system according to claim 1, which records the analysis results for each user as individual data and improves the efficiency of follow-up.

[0872] "Application example 2 when combining with an emotional engine"

[0873] (Claim 1)

[0874] [Means for providing a user interface for a user to initiate a virtual interaction via an information processing device,

[0875] [Means for performing natural language processing to analyze received dialogue information and evaluate emotional state and degree of pressure,

[0876] [Means for evaluating mental health risks based on analysis results and generating appropriate ongoing support messages or guidance,

[0877] [Means for presenting the generated message to the user via an information processing device,

[0878] [Means of sending notifications to supporters as needed,

[0879] [A means of analyzing a user's emotional state and recommending personalized products or services using wearable information devices used in real-world spatial interactions,]

[0880] A system that includes this.

[0881] (Claim 2)

[0882] [The system according to claim 1, which adjusts notification to third parties based on the user's permission.

[0883] (Claim 3)

[0884] [The system according to claim 1, which records the analysis results for each user as individual information and improves the efficiency of follow-up. [Explanation of Symbols]

[0885] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of providing an interface for a user to initiate a virtual interaction via an electronic device, A means for analyzing received dialogue data and performing natural language processing to evaluate emotional state and stress level, A means for evaluating the risk of psychosis based on the analysis results and generating appropriate follow-up messages or advice, A means of presenting the generated message to the user via an electronic device, If necessary, a means to send notifications to supporters, A system that includes this.

2. The system according to claim 1, which controls notifications to third parties based on the user's consent.

3. The system according to claim 1, which records the analysis results for each user as an individual profile and improves the efficiency of follow-up.

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