System

Abstract

A system is provided.SOLUTION: A system comprising: an information processing apparatus; a sensing device connected to the information processing apparatus; means for receiving data collected from the sensing device and analyzing an emotion and a stress level of a user; means for providing customized mental health support to the user based on a result of the analysis; and means for notifying the user of the customized mental health support.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] People in litigation have to contend with prolonged stress and anxiety, placing a heavy burden on both their mind and body. This burden often leads to mental exhaustion, making it difficult for them to properly navigate the legal process. Appropriate technological solutions are needed to address this issue. [Means for solving the problem]

[0005] The present invention relates to a system that analyzes a user's emotions and stress level using an information processing device and a sensing device connected to the device. Specifically, the system includes: (1) means for receiving data collected from the sensing device and analyzing the user's emotions and stress level; (2) means for providing the user with customized mental health support based on the analysis results; and (3) means for notifying the user of the customized mental health support. The system further includes means for providing the mental health support in the form of guided meditation, psychological counseling sessions, or relaxation exercises. It also includes means for providing access to legal advice and counseling services. This configuration reduces the mental burden during litigation, enabling users to proceed through the legal process more healthily.

[0006] An "information processing device" is a computer system or server that performs a series of operations such as data collection, analysis, and notification.

[0007] A "sensing device" is a hardware device used to collect a user's biometric and behavioral data, including, for example, a smartwatch or smartphone.

[0008] "Data" refers to biometric and behavioral data collected from sensing devices, including, for example, heart rate, body temperature, and keystroke rhythm.

[0009] "Emotion" refers to information that indicates the user's psychological state, specifically states such as stress, fatigue, and anxiety.

[0010] "Stress level" is an indicator of the degree of mental stress obtained as a result of analyzing the user's emotional data.

[0011] "Means of analysis" refers to algorithms and AI models that assess emotions and stress levels based on the collected data.

[0012] "Customized mental health support" refers to the provision of mental support that is individually designed to address a user's specific emotional state and stress level.

[0013] "Guided Meditation" means audio or video content that guides users through a relaxing meditation session.

[0014] A "psychological counseling session" is a session in which you receive psychological advice and support from a professional counselor.

[0015] "Relaxation exercises" are specific activities, such as exercises or breathing techniques, that are designed to reduce stress and promote relaxation in users.

[0016] "Legal Advice" means providing initial answers or guidance regarding a legal issue.

[0017] "Counseling services" are services that allow users to receive professional support to reduce anxiety and mental stress during litigation. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6]FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] Introduction

[0040] The present invention relates to a method for managing a user's emotions and stress levels and providing customized mental health support using information processing devices, sensing devices, data analysis and notification systems.

[0041] System Configuration

[0042] Information processing device

[0043] The server is responsible for the system's primary data analysis and information management. It receives data from the sensing devices, performs calculations for analysis, and sends notifications regarding mental health support to users.

[0044] Sensing Device

[0045] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[0046] Program and Processing Overview

[0047] Data collection and analysis

[0048] 1. Data Collection

[0049] Device: A smartwatch or smartphone collects the user's biometric data (heart rate, body temperature, etc.), which is then sent to a server in real time.

[0050] 2. Data Reception and Analysis

[0051] Server: Receives data sent from the device and analyzes it using an AI model. As a result of the analysis, the user's emotional state (e.g., stress, fatigue, anxiety) and stress level are determined.

[0052] Providing mental health support

[0053] 1. Generate customized support

[0054] Server: Generates a mental health support plan tailored to the user based on the data analysis results. For example, if stress levels are high, it provides a meditation guide.

[0055] 2. Support Notifications

[0056] Device: Notifies the user of the generated mental health support plan and provides specific instructions on how to implement it (e.g., starting a guided meditation).

[0057] Integrated legal support

[0058] 1. Receiving and analyzing legal questions

[0059] User: If you have any legal questions or concerns, you can send them to the server from your device.

[0060] Server: Receives the question and generates preliminary legal advice using AI.

[0061] 2. Providing counseling services

[0062] Server: Provides an option to book legal consultations if needed, allowing users to speak to a legal professional directly.

[0063] Specific examples

[0064] Specific examples of mental health care

[0065] 1. Data Collection

[0066] Device: The smartwatch continuously measures the user's heart rate and sends the data to the server every two minutes.

[0067] 2. Data analysis and customization support

[0068] Server: After analyzing the heart rate data, the server determines that the user's stress level is "high." Based on this, the server generates a support plan that suggests a five-minute guided meditation.

[0069] 3. Notice and Enforcement

[0070] Device: Notifies the user of the guided meditation video and instructs them to play it.

[0071] User: Follow the guided meditation for 5 minutes.

[0072] Examples of legal support

[0073] 1. Accepting questions

[0074] User: Submit legal questions regarding ongoing litigation proceedings from the device.

[0075] 2. Legal Answers and Counseling Appointments

[0076] Server: Analyzes the question and generates relevant legal advice. It also provides the user with a link to schedule a legal consultation.

[0077] Device: Informs users of legal advice and options for booking counseling appointments.

[0078] Users: Book a consultation and speak to a specialist if necessary.

[0079] This allows users to receive real-time assistance in managing emotions and stress, reducing the mental burden during litigation.

[0080] The processing flow will be explained below.

[0081] Step 1:

[0082] Data collection

[0083] Device: A smartwatch or smartphone collects biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmits this data to a server at regular intervals.

[0084] Step 2:

[0085] Data reception

[0086] Server: Receives data sent from the device. The received data is stored in a database and prepared for analysis.

[0087] Step 3:

[0088] Data analysis

[0089] Server: Uses AI models to analyze stored biometric data, assessing emotions and stress levels to determine the user's emotional state (e.g., stress, fatigue, anxiety).

[0090] Step 4:

[0091] Generate customization support

[0092] Server: Based on the analysis results, the server automatically generates a mental health support plan appropriate for the user's emotional state. For example, it suggests a guided meditation plan if the user's stress level is high.

[0093] Step 5:

[0094] Submit a Support Plan

[0095] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[0096] Step 6:

[0097] Support Plan Notifications

[0098] Device: Notify the user of the received support plan and show them how to implement it. For example, a notification saying "Start a 5-minute guided meditation" will be displayed on the device screen.

[0099] Step 7:

[0100] Support Execution

[0101] User: Follow the notifications from the device to play a guided meditation video or perform deep breathing exercises, while the device continues to record their progress.

[0102] Step 8:

[0103] Recording progress

[0104] Device: Records the status of support execution (for example, meditation time and exercise completion status) and sends it to the server.

[0105] Step 9:

[0106] Progress data analysis

[0107] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user responses and effectiveness, more effective support can be provided.

[0108] Step 10:

[0109] Providing legal support

[0110] User: If there is a legal consultation or question, the user makes an inquiry to the server via the terminal.

[0111] Server: Analyzes the user's question and uses AI to automatically generate initial legal advice. If necessary, it provides a link to book a legal consultation.

[0112] Step 11:

[0113] Sending legal advice

[0114] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[0115] Device: Displays legal advice to the user and notifies them when counseling appointments are available.

[0116] Step 12:

[0117] Counseling appointment

[0118] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[0119] This is the detailed program flow of LegalEase MindGuard. This system allows users to receive appropriate mental health support and legal advice in real time, significantly reducing the mental burden during litigation.

[0120] Example 1

[0121] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0122] In modern society, there is a need to effectively manage users' emotions and stress levels and provide appropriate mental health support. However, existing systems do not properly collect and analyze biometric data, making it difficult to provide users with prompt, customized support. Furthermore, there are no systems that can respond to legal questions or provide counseling services. This makes it difficult for users to receive mental and legal support at the appropriate time.

[0123] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0124] In this invention, the server includes a data analysis means, a determination means, a mental health support plan generation means, a notification means, a legal question analysis means, and a legal counseling appointment provision means. This makes it possible to analyze a user's biometric data in real time and provide a customized mental health support plan. It also makes it possible to quickly provide comprehensive support to users through initial responses to legal questions and appointments for counseling services.

[0125] An "information processing device" is a computer device that receives, analyzes, and manages data.

[0126] "Sensing devices" are devices that collect biometric data from users, including smartwatches and smartphones.

[0127] "Biometric data" refers to physical data such as a user's heart rate, body temperature, and keystroke rhythm.

[0128] "Data analysis means" refers to the means for analyzing collected biometric data, utilizing technologies such as AI models to extract meaningful information from the data.

[0129] The "determination means" is a means for determining the user's emotional state and stress level based on the analyzed data.

[0130] The "mental health support plan generation means" is a means for generating a mental health support plan tailored to the user based on the assessment results.

[0131] "Notification means" refers to a means for notifying the user of the generated mental health support plan.

[0132] "Legal question analysis means" means for receiving a legal question from a user and generating initial legal advice in response thereto.

[0133] A "Legal Counseling Appointment Offering" is a means for providing Users with the option to book legal counseling services.

[0134] The present invention relates to a system that uses information processing devices, sensing devices, data analysis means, and notification systems to manage a user's emotions and stress levels and provide customized mental health support and legal support.

[0135] System Configuration

[0136] Information processing device

[0137] The server is responsible for the system's primary data analysis and information management. Specifically, it receives data from the sensing devices and performs calculations for analysis. The server also sends notifications to users regarding mental health support. The server's processing uses AI models such as TensorFlow.

[0138] Sensing Device

[0139] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server in real time. With the user's consent, the devices monitor the data continuously.

[0140] Data Analysis Methods

[0141] The server receives the biometric data sent from the device and stores it in a database. The stored data is analyzed using AI models such as TensorFlow. As a result of the analysis, the user's emotional state (stress, fatigue, anxiety) and stress level are identified.

[0142] Mental Health Support Plan Generation Tool

[0143] Based on the analysis results, the server generates a personalized mental health support plan for each user, suggesting guided meditations and relaxing music for users with high stress levels, for example.

[0144] Notification means

[0145] The device will then notify the user of the customized mental health support plan sent from the server, which will be displayed as a push notification or in-app notification, prompting the user to take specific action.

[0146] legal question analysis tool

[0147] Users submit legal questions from their devices, which are then received by a server that uses natural language processing models such as GPT-3 to generate initial legal advice.

[0148] Legal counseling appointment delivery methods

[0149] Depending on the legal question, the server generates and notifies the user of a legal counseling appointment option, which includes a link to meet with an expert.

[0150] Specific examples

[0151] Specific examples of mental health care

[0152] 1. Data Collection

[0153] Device: The smartwatch continuously measures the user's heart rate and sends the data to the server every 30 seconds.

[0154] 2. Data analysis and generation of customized support

[0155] Server: Analyzes heart rate data using an AI model, and if stress levels are determined to be high, generates a support plan suggesting a five-minute guided meditation.

[0156] 3. Notification

[0157] On device: The user is notified of the support plan and is shown the message, "Your stress level seems high. Try a 5-minute guided meditation." The user taps the notification to begin the guided meditation.

[0158] Examples of legal support

[0159] 1. Accepting questions

[0160] User: Sends questions about the lawsuit from their smartphone to the server.

[0161] 2. Legal Answers and Counseling Appointments

[0162] Server: Analyzes the question using GPT-3 and generates an initial advice such as "When collecting evidence in litigation, it is important to verify its reliability and legality." It also sends a notification with a link to schedule a legal consultation.

[0163] 3. Counseling appointment

[0164] Users: Receive notifications and, if necessary, book counseling appointments and meetings with specialists.

[0165] Example prompts for generative AI models

[0166] "Please explain the specific process flow for collecting heart rate data in real time while the user is wearing the smartwatch, analyzing stress levels using TensorFlow, and providing customized mental health support based on the results. Also, please include a process flow for using GPT-3 to provide initial response to legal questions."

[0167] As can be seen, this invention can improve a user's overall well-being by using their biometric data to manage their emotions and stress levels in real time and provide mental health and legal support.

[0168] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0169] Step 1:

[0170] Data collection

[0171] Device: Smartwatches and smartphones continuously collect users' biometric data (heart rate, body temperature, keystroke rhythm).

[0172] Input: User biometric data. For example, a smartwatch measures heart rate and temperature every 30 seconds, and a smartphone captures keystroke rhythm.

[0173] Output: The collected biometric data is temporarily stored on the device. The smartwatch transmits the data via Bluetooth to the smartphone, which prepares it to be sent to the server via Wi-Fi or mobile data.

[0174] Step 2:

[0175] Data reception

[0176] Server: Receives biometric data sent from the terminal.

[0177] Input: Biometric data sent from the device.

[0178] Output: The received biometric data is stored in the server's database. Specifically, the server's receiving module captures the data and stores it in the database.

[0179] Step 3:

[0180] Data analysis

[0181] Server: Analyzes the received biometric data using an AI model (such as TensorFlow).

[0182] Input: Biometric data stored on the server.

[0183] Processing: The AI ​​model analyzes the data and determines the user's emotional state and stress level.

[0184] Output: The analysis results in the user's emotional state (e.g., stress level is high, medium, low, etc.) and a stress index.

[0185] Step 4:

[0186] Customized Support Plan Generation

[0187] Server: Generates a personalized mental health support plan for each user based on the results of data analysis.

[0188] Input: Analysis results (user's emotional state and stress level).

[0189] Processing: The server creates a support plan based on the analysis results. For example, it suggests a five-minute guided meditation for a user with a high stress level.

[0190] Output: A customized support plan is generated, which may include guided meditation, relaxation exercises, or psychological counseling sessions.

[0191] Step 5:

[0192] Support Notifications

[0193] On the device: Notifies the user of the support plan sent from the server.

[0194] Input: The customized support plan sent by the server.

[0195] Action: Your device will display your support plan as a push or in-app notification.

[0196] Output: The user is notified with a message such as "Your stress level seems high. Try a 5-minute guided meditation." When the user taps the notification, a guided meditation app or similar will launch.

[0197] Step 6:

[0198] Accepting legal questions

[0199] Users: If they have legal questions or concerns, they can send them to the server using their smartphone or PC.

[0200] Input: Legal question submitted by user.

[0201] Output: The question is sent to the server. Specifically, this includes the user entering "I would like to ask about evidence collection in litigation" into the app's question form and submitting it.

[0202] Step 7:

[0203] Legal Advice Generation and Notification

[0204] Server: Generates initial legal advice in response to legal questions received from users using an AI model that performs natural language processing (e.g., GPT-3).

[0205] Input: Legal question received from user.

[0206] Processing: The AI ​​model analyzes the question and generates legal advice such as, "When collecting evidence during litigation, it is important to verify the reliability and legality of the evidence."

[0207] Output: The generated legal advice is communicated to the user.

[0208] Step 8:

[0209] Legal counseling appointments available

[0210] Server: Generates and notifies users of legal advice, along with options to book legal counseling.

[0211] Input: Description of legal issue and generated legal advice.

[0212] Processing: The server generates a link that provides counseling appointment options and notifies the user.

[0213] Output: The notification will contain a link such as "Schedule a legal consultation here" that the user can click to complete the booking process.

[0214] In this way, the overall processing flow of the system is to collect the user's biometric data, perform analysis based on that data, and provide customized mental health support and legal support based on the analysis results.

[0215] (Application example 1)

[0216] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0217] Until now, there have been no adequate methods established for managing the mental health of workers in industrial environments. As a result, workers' accumulated stress and fatigue have had a negative impact on productivity and safety, ultimately causing a decline in the quality of the overall working environment. There is a need for a system that can solve these problems, monitor workers' mental health status in real time, and provide appropriate support.

[0218] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0219] In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing a user's emotions and stress level, means for providing customized mental health support to the user based on the analysis results, means for notifying the user of the customized mental health support, and means for collecting biometric data of workers in an industrial environment and suggesting relaxation support and breaks based on the analysis results. This makes it possible to monitor the mental health status of workers in real time and suggest support and breaks that are appropriate for each individual, thereby improving the working environment and increasing productivity.

[0220] An "information processing device" is a device that analyzes collected data and provides various types of support and notifications to users.

[0221] A "sensing device" is a device used to collect a user's biometric data, and examples include smartwatches and smartphones.

[0222] The "means for receiving data and analyzing the user's emotions and stress level" refers to a means for receiving data transmitted from a sensing device and analyzing the data to determine the user's emotional state and level of stress.

[0223] "Means for providing customized mental health support" refers to means for selecting and providing a mental health support method suitable for the user based on the analysis results.

[0224] "Means for notifying users of customized mental health support" refers to means for notifying users of the generated support plan, thereby enabling users to receive actual support.

[0225] An "industrial environment" refers to an industrial site or workplace where manufacturing or processing takes place, and is an environment where managing the mental health of workers is particularly important.

[0226] "Means for collecting workers' biometric data and suggesting relaxation support and rest based on the analysis results" refers to means for collecting biometric data such as heart rate and body temperature of workers in industrial environments and suggesting appropriate relaxation methods and rest based on the results of analyzing this data.

[0227] "Guided Meditation" means a means of providing users with guided meditation sessions for the purposes of stress reduction and relaxation.

[0228] "Psychological Counseling Session" refers to a counseling session to provide psychological support to a User.

[0229] "Relaxation exercise" is a method of providing users with physical activity or exercise aimed at relieving muscle tension or mental refreshment.

[0230] "Means for providing access to legal advice and counseling services" means means for accepting legal questions from users and providing appropriate advice and, if necessary, counseling appointments with professionals.

[0231] Overall structure

[0232] The present invention is a system that uses information processing devices, sensing devices, data analysis and notification systems to manage a user's emotions and stress levels and provide customized mental health support.

[0233] Hardware Configuration

[0234] Server: An important device that analyzes data and manages information. Commercial high-performance servers or cloud servers are often used.

[0235] Sensing devices: Specifically, smartwatches and smartphones. These devices collect biometric data such as heart rate and body temperature from users and transmit it to a server.

[0236] Devices specialized for industrial environments: Devices designed to collect biometric data from workers in industrial environments in real time, enabling highly accurate data analysis.

[0237] Data collection and analysis

[0238] Data collection: Sensing devices collect biometric data such as the user's heart rate and body temperature. This data is sent to a server in real time. In industrial environments, workers wear smartwatches or head-mounted displays to collect this data as needed.

[0239] Data analysis: The server receives the collected biometric data and analyzes it using an AI model. This determines the user's emotional state and stress level. For example, if the heart rate or body temperature exceeds a certain threshold, the stress level is classified into three levels: "low," "medium," or "high."

[0240] Providing mental health support

[0241] Generate customized support: The server generates a mental health support plan tailored to the user based on the analysis results. For example, if the stress level is determined to be high, it generates relaxation support that suggests a five-minute break.

[0242] Support notification: The generated mental health support plan will be sent to the user's smartwatch or smartphone, and the user can follow the instructions to receive actual support.

[0243] Specific examples

[0244] Example of data collection: A smartwatch continuously measures the user's heart rate and transmits the data to a server every two minutes, enabling real-time data monitoring.

[0245] Example of data analysis: If the server performs an analysis and User A's heart rate exceeds 90 bpm and his body temperature is 37.2 degrees, it will be determined that his "stress level is high."

[0246] Example of support notification: Based on the analysis results, the server generates a message suggesting a break and notifies the user through the smartwatch, such as "Your stress level is high. Please take a 5-minute break."

[0247] Prompt Sentence Examples

[0248] For example, you might input a prompt like this for a generative AI model:

[0249] "If the heart rate is above 90, determine that the worker's stress level is high and generate a notification message in the application suggesting a break."

[0250] This makes it possible to monitor the user's mental health status in real time and provide appropriate support immediately.

[0251] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0252] Step 1:

[0253] Data collection:

[0254] The device, a smartwatch or smartphone, continuously measures the user's biometric data, such as heart rate and body temperature. The measured data is sent to the server in real time. The input at this stage is the user's heart rate and body temperature data, which are sent to the server in an appropriate format. The output is the completion of sending the biometric data to the server.

[0255] Step 2:

[0256] Data reception:

[0257] The server receives the biometric data sent from the terminal. The received data is stored in a database in the server. The input at this stage is the biometric data sent from the terminal. The output is the biometric data stored in the server.

[0258] Step 3:

[0259] Data Analysis:

[0260] The server analyzes the collected biometric data using an AI model. Here, the user's emotional state and stress level are determined based on heart rate and body temperature data. Specifically, a heart rate above 90 or a body temperature above 37.0 degrees is determined to be a "high stress state." The input at this stage is the biometric data stored on the server, and the output is the emotional state and stress level as the analytical results.

[0261] Step 4:

[0262] Customized support generation:

[0263] Based on the analysis results, the server generates an optimal mental health support plan for the user. In this case, if the stress level is determined to be high, it will generate suggestions such as "5 minutes of meditation" or "taking a break." The input is the emotional state and stress level resulting from the analysis, and the output is the generated mental health support plan.

[0264] Step 5:

[0265] Support Notice:

[0266] The generated mental health support plan is notified to the device. A message such as "Please take a break" is displayed on the user's smartwatch or smartphone. The input at this stage is the generated mental health support plan, and the output is the message to notify the user.

[0267] Step 6:

[0268] User Response:

[0269] The user follows the mental health support plan, specifically by taking prescribed relaxation and rest breaks as per the notification. At this stage, the user's biometric data is reset again and the next data collection cycle begins.

[0270] This allows users' mental health status to be monitored in real time, and measures such as relaxation and rest can be provided at appropriate times.

[0271] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0272] Introduction

[0273] The present invention relates to a system that uses an information processing device, a sensing device, and an emotion engine to manage a user's emotions and stress levels and provide customized mental health support. In particular, the present invention incorporates an emotion engine that analyzes voice data, text data, and image data to recognize a user's emotions.

[0274] System Configuration

[0275] Information processing device

[0276] The server is responsible for data analysis and information management for the entire system. It receives and analyzes data from the sensing devices and emotion engine, and sends notifications about mental health support to users.

[0277] Sensing Device

[0278] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[0279] Emotion Engine

[0280] The emotion engine recognizes the user's emotions by analyzing voice data, text data, and image data. For example, it analyzes the tone and speed of the voice from the voice data, the choice of words from the text data, and facial expressions from the image data.

[0281] Program and Processing Overview

[0282] Data collection and analysis

[0283] 1. Data Collection

[0284] Device: A smartwatch or smartphone collects the user's biometric data, which is then sent to a server in real time.

[0285] Emotion engine: Receives voice, text, and image data sent from the device and analyzes the user's emotional state.

[0286] 2. Data Reception and Analysis

[0287] Server: Receives data sent from the device and emotion engine and stores it in a database.

[0288] Server: Uses AI models to analyze the stored data. The AI ​​models evaluate emotions and stress levels to determine the user's emotional state (e.g., stress, fatigue, anxiety).

[0289] Providing mental health support

[0290] 1. Generate customization support

[0291] Server: Based on the results of data analysis and the emotion engine's analysis, the server automatically generates a mental health support plan appropriate for the user's emotional state. For example, if the stress level is high, the server suggests a guided meditation.

[0292] 2. Submit your support plan

[0293] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[0294] 3. Support Plan Notification

[0295] Device: Notify the user of the support plan they received and provide instructions on how to implement it. For example, display a notification saying, "Start a 5-minute guided meditation."

[0296] 4. Support Execution

[0297] User: Follow the notifications from your device to play a guided meditation video or do a deep breathing exercise, while your device records your progress.

[0298] 5. Track your progress

[0299] Device: Records the status of support execution (e.g., meditation time and exercise completion status) and sends it to the server.

[0300] 6. Analysis of progress data

[0301] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user reactions and effectiveness, more effective support can be provided.

[0302] Integrated legal support

[0303] 1. Receiving and analyzing legal questions

[0304] User: Sends legal questions or concerns to the server via their device.

[0305] Server: Receives the question and uses AI models to generate preliminary legal advice. In some cases, it offers the option to schedule a legal consultation.

[0306] 2. Sending legal advice

[0307] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[0308] Device: Providing legal advice and the option to book a consultation appointment if needed.

[0309] 3. Make a counseling appointment

[0310] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[0311] This is a specific implementation of LegalEase MindGuard, which combines an emotion engine, allowing users to manage their emotions and stress levels in real time and receive appropriate mental health care and legal support.

[0312] The processing flow will be explained below.

[0313] Step 1:

[0314] Data collection

[0315] Device: A smartwatch or smartphone collects the user's biometric data (heart rate, body temperature, keystroke rhythm, etc.), and also acquires audio data through the device's microphone and image data through the camera.

[0316] Terminal: Sends collected data to the server in real time.

[0317] Step 2:

[0318] Data reception

[0319] Server: Receives biometric data, voice data, and image data sent from the terminal and stores them in a database.

[0320] Step 3:

[0321] Analysis of audio and text data

[0322] Emotion engine: Analyzes audio data to analyze the user's tone, speed, and pitch. It also analyzes text data obtained from the device to evaluate word choice and context.

[0323] Server: Receives the results of the emotion engine and stores them in a database.

[0324] Step 4:

[0325] Image data analysis

[0326] Emotion engine: Using image recognition technology, the engine analyzes the user's facial expressions, such as facial contours, eye opening, and mouth curve, to determine emotions.

[0327] Server: Receives the results of the emotion engine and stores them in a database.

[0328] Step 5:

[0329] Comprehensive Data Analysis

[0330] Server: An AI model is used to comprehensively analyze all collected data (biometric data, voice data, text data, image data). The AI ​​model integrates multiple data sources to assess the user's emotional state (e.g., stress, fatigue, anxiety) and stress level.

[0331] Step 6:

[0332] Generate customization support

[0333] Server: Based on the analysis results, automatically generate a mental health support plan (e.g., meditation guide, psychological counseling session, relaxation exercise) appropriate for the user.

[0334] Step 7:

[0335] Submit a Support Plan

[0336] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[0337] Step 8:

[0338] Support Plan Notifications

[0339] Device: Notify the user of the received support plan and provide instructions on how to implement it. For example, display a notification on the device screen saying, "Start a 5-minute guided meditation."

[0340] Step 9:

[0341] Support Execution

[0342] User: Follow the notifications from your device to play a guided meditation video or do a deep breathing exercise, while your device records your progress.

[0343] Step 10:

[0344] Recording progress

[0345] Device: Records the status of support execution (e.g., meditation time and exercise completion status) and sends it to the server.

[0346] Step 11:

[0347] Progress data analysis

[0348] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user reactions and effectiveness, more effective support can be provided.

[0349] Step 12:

[0350] Providing legal support

[0351] User: If you have any legal questions or concerns, send them to the server via your device.

[0352] Server: Receives the question and uses AI models to generate initial legal advice. If necessary, it provides the option to schedule a legal consultation.

[0353] Step 13:

[0354] Sending legal advice

[0355] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[0356] Device: Providing legal advice and the option to book a consultation appointment if needed.

[0357] Step 14:

[0358] Counseling appointment

[0359] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[0360] This is the detailed program flow of LegalEase MindGuard, which combines an emotion engine. This system allows users to manage their emotions and stress levels in real time and receive appropriate mental health care and legal support.

[0361] Example 2

[0362] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0363] The current mental health care system struggles to properly assess users' emotions and stress levels and provide customized support. It also lacks real-time feedback, ongoing support, and legal advice integration, preventing users from receiving the comprehensive support they truly need.

[0364] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0365] In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing the user's emotions and stress level, means for notifying the user of a mental health support plan generated based on the analysis results and recording the implementation status, means for analyzing the recorded implementation status and using it to improve the future mental health support plan, and means for receiving legal questions from the user, generating initial legal advice, and providing an option to reserve legal counseling as needed. This enables the user to manage their emotions and stress level in real time and receive personalized mental health care and legal support.

[0366] An "information processing device" is a device such as a computer or server that collects, analyzes, and stores data.

[0367] A "sensing device" is a device that acquires biometric and environmental data from a user in real time and transmits it to an information processing device. Examples include smartwatches and smartphones.

[0368] "Means for analyzing emotions and stress levels" refers to algorithms or AI models that assess a user's emotional state and stress level based on the collected data.

[0369] The "Mental Health Support Plan" is a personalized mental health care plan provided to users based on the analysis results, which may include, for example, guided meditation and relaxation exercises.

[0370] A "means for recording implementation status" is a device or application that allows a user to record the progress of the user when actually implementing the mental health support plan.

[0371] "Means for receiving legal questions and generating initial legal advice" refers to an algorithm or AI model that receives legal questions or concerns from users, analyzes them, and provides initial legal advice.

[0372] A "means for providing legal counseling appointment options" is a system that allows a user to make an appointment for legal counseling if they wish to receive additional assistance.

[0373] Introduction

[0374] This invention relates to a system that uses an information processing device, a sensing device, and an emotion engine to manage a user's emotions and stress level and provide customized mental health support. In particular, this invention incorporates an emotion engine that analyzes voice data, text data, and image data to recognize the user's emotions.

[0375] System Configuration

[0376] Information processing device

[0377] The server is responsible for data analysis and information management for the entire system. It receives and analyzes data from the sensing devices and emotion engine, and sends notifications about mental health support to users.

[0378] Sensing Device

[0379] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[0380] Emotion Engine

[0381] The emotion engine recognizes the user's emotions by analyzing voice data, text data, and image data. For example, it analyzes the tone and speed of the voice from the voice data, the choice of words from the text data, and facial expressions from the image data.

[0382] Program and Processing Overview

[0383] Data collection and analysis

[0384] The device captures biometric data and transmits it in real time to a server, which receives it and stores it in a database. The emotion engine analyzes the voice, text, and image data to assess the user's emotional state. The server then uses an AI model to analyze emotions and stress levels.

[0385] Providing mental health support

[0386] The server generates a mental health support plan appropriate for the user based on the analysis results. The plan is then sent to the device, which notifies the user. The user then follows the instructions and implements the plan, and their progress is recorded.

[0387] For example, if a device sends heart rate data to a server, and the server analyzes the data and recognizes a high stress state, it will send a notification suggesting a five-minute guided meditation to the user, who can then begin the meditation and track their progress.

[0388] Integrated legal support

[0389] When a user sends a legal question to the server via their device, the server uses an AI model to generate initial legal advice and, if necessary, provides the option to book a legal consultation. The generated legal advice and booking information are sent to the device, where the user can view and interact with it.

[0390] Examples and prompts

[0391] Specific examples include the following:

[0392] Device: The smartwatch measures the heart rate and sends it to the server.

[0393] Server: Analyzes the received heart rate data and determines that the user is in a state of stress.

[0394] Server: Sends a message to the user's device saying, "Please start the 5-minute guided meditation."

[0395] User: Receive a notification from the device and play a guided meditation video.

[0396] (Example of a prompt)

[0397] "Receive and analyze the user's heart rate data, and generate a program that suggests appropriate guided meditations if stress levels are detected."

[0398] The above is a natural language description of the program process of the system of the present invention, which allows users to manage their emotions and stress levels in real time and receive personalized mental health care and legal support.

[0399] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0400] Step 1: Data collection

[0401] Input: Biometric data from sensors (heart rate, body temperature, keystroke rhythm, etc.)

[0402] Device: A smartwatch or smartphone collects the user's biometric data through sensors, which are then sent to a server in real time.

[0403] Output: The collected biometric data is sent to the server.

[0404] Specifically, the smartwatch measures the user's heart rate every second, sends the data to the smartphone via Bluetooth, and then the smartphone sends it to a server via Wi-Fi.

[0405] Step 2: Receiving and storing data

[0406] Input: Biometric data sent from the device

[0407] Server: Receives biometric data sent from the device in real time and stores it in a database.

[0408] Output: Biometric data stored in a database

[0409] Specifically, the server receives the data through a dedicated API and stores it in a database in the form of "user ID, measurement time, heart rate, body temperature, etc."

[0410] Step 3: Data analysis

[0411] Input: Biometric data stored in a database

[0412] Server: The stored data is fed into an AI model to assess the user's emotions and stress levels. The emotion engine also analyzes voice, text, and image data.

[0413] Output: Analysis results (e.g. high stress, fatigue, relaxed)

[0414] Specifically, the server processes batches of data weekly and feeds them into an AI model to estimate emotions and stress levels. For example, an elevated heart rate and a drop in voice tone might be assessed as "high stress."

[0415] Step 4: Generate a Mental Health Support Plan

[0416] Input: Analysis results

[0417] Server: Based on the analysis results, automatically generate a mental health support plan appropriate for the user.

[0418] Output: Generated mental health support plan (e.g., guided meditation, relaxation exercises)

[0419] Specifically, if the server detects that the user is in a high-stress state based on the analysis results, it generates a support plan suggesting a "5-minute meditation guide."

[0420] Step 5: Submit your support plan

[0421] Input: Generated Mental Health Support Plan

[0422] Server: Sends the generated support plan to the device.

[0423] Output: Notification message sent to the user's device (e.g., notification that a guided meditation has started)

[0424] Specifically, the server uses the SMTP protocol to send a notification to the user's smartphone saying, "Please start the meditation guide."

[0425] Step 6: Support Execution Notification

[0426] Input: Support plan notification

[0427] Device: Receives notifications and displays them to the user.

[0428] Output: A notification message that will be displayed on the user's terminal.

[0429] Specifically, it uses the smartphone's notification function to display a pop-up message on the user's screen saying, "Please start a 5-minute guided meditation."

[0430] Step 7: Performing and recording support

[0431] Input: Support plan execution instructions

[0432] User: Follows notifications from the device and provides mental health support. The device records the execution status.

[0433] Output: Performance data (e.g., meditation time, exercise completion status)

[0434] Specifically, the user follows the notification to play the guided meditation video, while the smartphone records the playback time. The smartphone also records the progress of the exercise by pressing the completion button.

[0435] Step 8: Analyze support progress

[0436] Input: Recorded execution status data

[0437] Server: Receives and analyzes progress data and uses it to improve the next mental health support plan.

[0438] Output: Improved support plan

[0439] Specifically, the server retrains the AI ​​model based on the performance data and generates personalized feedback such as "suggesting 10 minutes of meditation next time."

[0440] Step 9: Legal Questions Reception and Analysis

[0441] Input: Legal Question from User

[0442] User: Type and submit legal questions via the device.

[0443] Server: Receives the question and uses AI models to generate preliminary legal advice.

[0444] Output: Generated legal advice

[0445] Specifically, the user types "Please tell me about property division in divorce" into their device, which is then sent to the server, which uses an AI model to respond with the appropriate legal information.

[0446] Step 10: Submit legal advice and book a consultation

[0447] Input: Generated legal advice and counseling appointment information

[0448] Server: Sends legal advice and counseling appointment information to the terminal.

[0449] Device: Displays legal advice to the user and offers the option to book a consultation if necessary.

[0450] Output: Legal advice and counseling booking options displayed to the user

[0451] Specifically, the device will display a message saying, "Details on how to divide assets are provided. Click 'Book' to schedule a consultation."

[0452] (Application example 2)

[0453] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0454] In modern society, mental health has become a significant issue due to increased stress and anxiety. However, conventional mental health care systems have difficulty providing accurate support adapted to each user's individual emotional state and stress level. Furthermore, there has been a lack of efficient means to provide continuous mental health support in remote environments or to deliver content appropriate for each user. This has led to problems such as users not receiving appropriate support, limiting the effectiveness of mental health care.

[0455] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing the user's emotions and stress level, means for providing customized mental health support to the user based on the analysis results, means for notifying the user of the customized mental health support, means for delivering appropriate content based on the analysis results, means for recording content consumption status and generating feedback data, and means for improving future mental health support based on the feedback data. This makes it possible to provide highly accurate mental health care and appropriate content according to the user's individual emotional state and stress level.

[0456] "Information processing device" is a general term for hardware and software for receiving, storing, and analyzing data.

[0457] A "sensing device" is a device that collects a user's biometric and environmental data in real time, and is a general term for smartwatches, smartphones, etc.

[0458] "Emotion and stress level analysis means" is a general term for algorithms and technologies for analyzing collected voice data, text data, and image data to estimate a user's emotional state and stress level.

[0459] "Means for providing customized mental health support" is a general term for technologies and processes that automatically generate and provide mental health care adapted to a user's specific emotions and stress state based on analysis results.

[0460] "Mental health support notification means" is a general term for technologies and devices that notify users of customized mental health support plans and encourage them to take action.

[0461] "Content delivery method" is a general term for the technologies and processes that deliver digital content such as music, videos, and podcasts appropriate to a user's emotions and stress levels to a user's device via a network.

[0462] "Means for recording consumption status" is a general term for technologies that record how users consume provided content (for example, playback time and number of times) and store this information in a database.

[0463] "Feedback data generation means" is a general term for the processes and technologies that generate new analytical data based on recorded content consumption status and user feedback, and use it to improve future mental health support.

[0464] In this invention, we combine an information processing device, a sensing device, and an emotion engine to build a system that manages a user's emotions and stress level and provides customized mental health support. Each component of the system and its function are described in detail below.

[0465] System Configuration

[0466] Information processing device

[0467] The server is responsible for data analysis and information management for the entire system. It also functions as an "information processing device," analyzing data collected from the sensing devices and emotion engine to provide mental health support tailored to the user.

[0468] Sensing Device

[0469] The devices include smartwatches and smartphones. These devices act as "sensing devices" that continuously collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm. This data is then transmitted to a server in real time.

[0470] Emotion Engine

[0471] The emotion engine, which functions as an "emotion and stress level analyzer," analyzes voice, text, and image data to identify the user's emotional state. Specifically, it analyzes the tone and speed of voice from the voice data, selected words from the text data, and facial expressions from the image data.

[0472] Programs and their processing

[0473] The server receives biometric data from the sensing device and analysis results from the emotion engine, stores them in a database, analyzes the stored data to determine the user's emotions and stress level, and then generates a customized mental health support plan based on the analysis results and notifies the user.

[0474] Customized Mental Health Support

[0475] As a "means of providing customized mental health support," the server provides users with appropriate mental health support based on the analysis results. This support can include guided meditations, relaxation music, podcasts, etc. For example, if stress levels are high, relaxation music or guided meditations will be provided.

[0476] Content distribution and feedback

[0477] The server will then use the "content delivery means" to deliver content appropriate to the user based on the analysis results. The device will also record consumption status as a "consumption status recording means" and send this to the server. This will allow the "feedback data generation means" to analyze the user's progress and effectiveness, allowing for further customization of support from the next time onwards.

[0478] Hardware and software used

[0479] Hardware:

[0480] Smartphones, smartwatches (sensing devices)

[0481] Server (information processing device)

[0482] software:

[0483] TensorFlow, Keras (emotion engine, AI model)

[0484] OpenCV (image analysis)

[0485] Librosa (audio analysis)

[0486] Examples and how to use generative AI models

[0487] For example, if a user is feeling stressed, they can use prompts like the following to feed data into a generative AI model:

[0488] Example prompt sentence:

[0489] The user's biometric data indicates a heart rate of 90 and a body temperature of 37.5°C. Voice data analysis indicates the voice tone is unstable and fast. Image data analysis indicates the facial expression indicates sadness. Based on this data, diagnose the user's current emotional state and suggest appropriate mental health support content.

[0490] This system allows users to manage their emotions and stress levels in real time and receive appropriate mental health care, which is expected to improve their mental health and quality of life.

[0491] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0492] Step 1:

[0493] The device collects the user's biometric data. It uses a smartwatch or smartphone to measure heart rate, body temperature, and keystroke rhythm in real time and transmits the data to a server. The input is various biometric data, and the output is the biometric data sent to the server.

[0494] Step 2:

[0495] The server uses an emotion engine to analyze the user's voice data, text data, and image data. The voice data sent from the device is used to extract MFCCs using Librosa, and the image data is used to analyze facial expressions using OpenCV. The text data is analyzed using natural language processing technology. The input is voice, text, and image data, and the output is the analysis of the user's emotional state and stress level.

[0496] Step 3:

[0497] The server integrates data from the sensing device and the emotion engine, and uses an AI model (using TensorFlow and Keras) to determine the user's current emotional state and stress level. The input is biometric data and the analysis results of the emotion engine, and the output is the determined emotional state and stress level.

[0498] Step 4:

[0499] The server generates a customized mental health support plan. Based on the determined emotional state and stress level, it selects appropriate content from relaxation music, guided meditations, podcasts, etc. The input is the determined emotional state and stress level, and the output is a customized mental health support plan.

[0500] Step 5:

[0501] The server sends the customized mental health support plan to the terminal, and the terminal displays specific implementation methods (video links and text instructions) to the user based on the received notification. The input is the customized mental health support plan, and the output is the notification to the user.

[0502] Step 6:

[0503] The user performs mental health support based on notifications from the device. For example, the user performs specific actions such as playing relaxation music or watching a guided meditation video. The input is the notification to the user, and the output is the execution of mental health support.

[0504] Step 7:

[0505] The device records the user's mental health support activities, collecting data on the type and time of activities performed and sending it to the server. The input is the mental health support activity data, and the output is the recorded data sent to the server.

[0506] Step 8:

[0507] The server analyzes the feedback data and uses it to improve future mental health support plans. It analyzes user responses and effects and adjusts the AI ​​model. The input is the recorded data and response data, and the output is an updated mental health support plan.

[0508] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0509] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0510] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0511] [Second embodiment]

[0512] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0513] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0514] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0515] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0516] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0517] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0518] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0519] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0520] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0521] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0522] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0523] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0524] Introduction

[0525] The present invention relates to a method for managing a user's emotions and stress levels and providing customized mental health support using information processing devices, sensing devices, data analysis and notification systems.

[0526] System Configuration

[0527] Information processing device

[0528] The server is responsible for the system's primary data analysis and information management. It receives data from the sensing devices, performs calculations for analysis, and sends notifications regarding mental health support to users.

[0529] Sensing Device

[0530] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[0531] Program and Processing Overview

[0532] Data collection and analysis

[0533] 1. Data Collection

[0534] Device: A smartwatch or smartphone collects the user's biometric data (heart rate, body temperature, etc.), which is then sent to a server in real time.

[0535] 2. Data Reception and Analysis

[0536] Server: Receives data sent from the device and analyzes it using an AI model. As a result of the analysis, the user's emotional state (e.g., stress, fatigue, anxiety) and stress level are determined.

[0537] Providing mental health support

[0538] 1. Generate customized support

[0539] Server: Generates a mental health support plan tailored to the user based on the data analysis results. For example, if stress levels are high, it provides a meditation guide.

[0540] 2. Support Notifications

[0541] Device: Notifies the user of the generated mental health support plan and provides specific instructions on how to implement it (e.g., starting a guided meditation).

[0542] Integrated legal support

[0543] 1. Receiving and analyzing legal questions

[0544] User: If you have any legal questions or concerns, you can send them to the server from your device.

[0545] Server: Receives the question and generates preliminary legal advice using AI.

[0546] 2. Providing counseling services

[0547] Server: Provides an option to book legal consultations if needed, allowing users to speak to a legal professional directly.

[0548] Specific examples

[0549] Specific examples of mental health care

[0550] 1. Data Collection

[0551] Device: The smartwatch continuously measures the user's heart rate and sends the data to the server every two minutes.

[0552] 2. Data analysis and customization support

[0553] Server: After analyzing the heart rate data, the server determines that the user's stress level is "high." Based on this, the server generates a support plan that suggests a five-minute guided meditation.

[0554] 3. Notice and Enforcement

[0555] Device: Notifies the user of the guided meditation video and instructs them to play it.

[0556] User: Follow the guided meditation for 5 minutes.

[0557] Examples of legal support

[0558] 1. Accepting questions

[0559] User: Submit legal questions regarding ongoing litigation proceedings from the device.

[0560] 2. Legal Answers and Counseling Appointments

[0561] Server: Analyzes the question and generates relevant legal advice. It also provides the user with a link to schedule a legal consultation.

[0562] Device: Informs users of legal advice and options for booking counseling appointments.

[0563] Users: Book a consultation and speak to a specialist if necessary.

[0564] This allows users to receive real-time assistance in managing emotions and stress, reducing the mental burden during litigation.

[0565] The processing flow will be explained below.

[0566] Step 1:

[0567] Data collection

[0568] Device: A smartwatch or smartphone collects biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmits this data to a server at regular intervals.

[0569] Step 2:

[0570] Data reception

[0571] Server: Receives data sent from the device. The received data is stored in a database and prepared for analysis.

[0572] Step 3:

[0573] Data analysis

[0574] Server: Uses AI models to analyze stored biometric data, assessing emotions and stress levels to determine the user's emotional state (e.g., stress, fatigue, anxiety).

[0575] Step 4:

[0576] Generate customization support

[0577] Server: Based on the analysis results, the server automatically generates a mental health support plan appropriate for the user's emotional state. For example, it suggests a guided meditation if the user's stress level is high.

[0578] Step 5:

[0579] Submit a Support Plan

[0580] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[0581] Step 6:

[0582] Support Plan Notifications

[0583] Device: Notify the user of the received support plan and show them how to implement it. For example, a notification saying "Start a 5-minute guided meditation" will be displayed on the device screen.

[0584] Step 7:

[0585] Support Execution

[0586] User: Follow the notifications from the device to play a guided meditation video or perform deep breathing exercises, while the device continues to record their progress.

[0587] Step 8:

[0588] Recording progress

[0589] Device: Records the status of support execution (for example, meditation time and exercise completion status) and sends it to the server.

[0590] Step 9:

[0591] Progress data analysis

[0592] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user responses and effectiveness, more effective support can be provided.

[0593] Step 10:

[0594] Providing legal support

[0595] User: If there is a legal consultation or question, the user makes an inquiry to the server via the terminal.

[0596] Server: Analyzes the user's question and uses AI to automatically generate initial legal advice. If necessary, it provides a link to book a legal consultation.

[0597] Step 11:

[0598] Sending legal advice

[0599] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[0600] Device: Displays legal advice to the user and notifies them when counseling appointments are available.

[0601] Step 12:

[0602] Counseling appointment

[0603] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[0604] This is the detailed program flow of LegalEase MindGuard. This system allows users to receive appropriate mental health support and legal advice in real time, significantly reducing the mental burden during litigation.

[0605] Example 1

[0606] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0607] In modern society, there is a need to effectively manage users' emotions and stress levels and provide appropriate mental health support. However, existing systems do not properly collect and analyze biometric data, making it difficult to provide users with prompt, customized support. Furthermore, there are no systems that can respond to legal questions or provide counseling services. This makes it difficult for users to receive mental and legal support at the appropriate time.

[0608] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0609] In this invention, the server includes a data analysis means, a determination means, a mental health support plan generation means, a notification means, a legal question analysis means, and a legal counseling appointment provision means. This makes it possible to analyze a user's biometric data in real time and provide a customized mental health support plan. It also makes it possible to quickly provide comprehensive support to users through initial responses to legal questions and appointments for counseling services.

[0610] An "information processing device" is a computer device that receives, analyzes, and manages data.

[0611] "Sensing devices" are devices that collect biometric data from users, including smartwatches and smartphones.

[0612] "Biometric data" refers to physical data such as a user's heart rate, body temperature, and keystroke rhythm.

[0613] "Data analysis means" refers to the means for analyzing collected biometric data, utilizing technologies such as AI models to extract meaningful information from the data.

[0614] The "determination means" is a means for determining the user's emotional state and stress level based on the analyzed data.

[0615] The "mental health support plan generation means" is a means for generating a mental health support plan tailored to the user based on the assessment results.

[0616] "Notification means" refers to a means for notifying a user of the generated mental health support plan.

[0617] "Legal question analysis means" means for receiving a legal question from a user and generating initial legal advice in response thereto.

[0618] A "Legal Counseling Appointment Offering" is a means for providing Users with the option to book legal counseling services.

[0619] The present invention relates to a system that uses information processing devices, sensing devices, data analysis means, and notification systems to manage a user's emotions and stress levels and provide customized mental health support and legal support.

[0620] System Configuration

[0621] Information processing device

[0622] The server is responsible for the system's primary data analysis and information management. Specifically, it receives data from the sensing devices and performs calculations for analysis. The server also sends notifications to users regarding mental health support. The server's processing uses AI models such as TensorFlow.

[0623] Sensing Device

[0624] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server in real time. With the user's consent, the devices monitor the data continuously.

[0625] Data Analysis Methods

[0626] The server receives the biometric data sent from the device and stores it in a database. The stored data is analyzed using AI models such as TensorFlow. As a result of the analysis, the user's emotional state (stress, fatigue, anxiety) and stress level are identified.

[0627] Mental Health Support Plan Generation Tool

[0628] Based on the analysis results, the server generates a personalized mental health support plan for each user, suggesting guided meditations and relaxing music for users with high stress levels, for example.

[0629] Notification means

[0630] The device will then notify the user of the customized mental health support plan sent from the server, which will be displayed as a push notification or in-app notification, prompting the user to take specific action.

[0631] legal question analysis tool

[0632] Users submit legal questions from their devices, which are then received by a server that uses natural language processing models such as GPT-3 to generate initial legal advice.

[0633] Legal counseling appointment delivery methods

[0634] Depending on the legal question, the server generates and notifies the user of a legal counseling appointment option, which includes a link to meet with an expert.

[0635] Specific examples

[0636] Specific examples of mental health care

[0637] 1. Data Collection

[0638] Device: The smartwatch continuously measures the user's heart rate and sends the data to the server every 30 seconds.

[0639] 2. Data analysis and generation of customized support

[0640] Server: Analyzes heart rate data using an AI model, and if stress levels are determined to be high, generates a support plan suggesting a five-minute guided meditation.

[0641] 3. Notification

[0642] On device: The user is notified of the support plan and is shown the message, "Your stress level seems high. Try a 5-minute guided meditation." The user taps the notification to begin the guided meditation.

[0643] Examples of legal support

[0644] 1. Accepting questions

[0645] User: Sends questions about the lawsuit from their smartphone to the server.

[0646] 2. Legal Answers and Counseling Appointments

[0647] Server: Analyzes the question using GPT-3 and generates an initial advice such as "When collecting evidence during litigation, it is important to verify its reliability and legality." It also sends a notification with a link to schedule a legal consultation.

[0648] 3. Counseling appointment

[0649] Users: Receive notifications and, if necessary, book counseling appointments and meetings with specialists.

[0650] Example prompts for generative AI models

[0651] "Please explain the specific process flow for collecting heart rate data in real time while the user is wearing the smartwatch, analyzing stress levels using TensorFlow, and providing customized mental health support based on the results. Also, please include a process flow for using GPT-3 to provide initial response to legal questions."

[0652] As can be seen, this invention can improve a user's overall well-being by using their biometric data to manage their emotions and stress levels in real time and provide mental health and legal support.

[0653] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0654] Step 1:

[0655] Data collection

[0656] Device: Smartwatches and smartphones continuously collect users' biometric data (heart rate, body temperature, keystroke rhythm).

[0657] Input: User biometric data. For example, a smartwatch measures heart rate and temperature every 30 seconds, and a smartphone captures keystroke rhythm.

[0658] Output: The collected biometric data is temporarily stored on the device. The smartwatch transmits the data via Bluetooth to the smartphone, which prepares it to be sent to the server via Wi-Fi or mobile data.

[0659] Step 2:

[0660] Data reception

[0661] Server: Receives biometric data sent from the terminal.

[0662] Input: Biometric data sent from the device.

[0663] Output: The received biometric data is stored in the server's database. Specifically, the server's receiving module captures the data and stores it in the database.

[0664] Step 3:

[0665] Data analysis

[0666] Server: Analyzes the received biometric data using an AI model (such as TensorFlow).

[0667] Input: Biometric data stored on the server.

[0668] Processing: The AI ​​model analyzes the data and determines the user's emotional state and stress level.

[0669] Output: The analysis results in the user's emotional state (e.g., stress level is high, medium, low, etc.) and a stress index.

[0670] Step 4:

[0671] Customized Support Plan Generation

[0672] Server: Generates a personalized mental health support plan for each user based on the results of data analysis.

[0673] Input: Analysis results (user's emotional state and stress level).

[0674] Processing: The server creates a support plan based on the analysis results. For example, it suggests a five-minute guided meditation for a user with a high stress level.

[0675] Output: A customized support plan is generated, which may include guided meditation, relaxation exercises, or psychological counseling sessions.

[0676] Step 5:

[0677] Support Notifications

[0678] On the device: Notifies the user of the support plan sent from the server.

[0679] Input: The customized support plan sent by the server.

[0680] Action: Your device will display your support plan as a push or in-app notification.

[0681] Output: The user is notified with a message such as "Your stress level seems high. Try a 5-minute guided meditation." When the user taps the notification, a guided meditation app or similar will launch.

[0682] Step 6:

[0683] Accepting legal questions

[0684] Users: If they have legal questions or concerns, they can send them to the server using their smartphone or PC.

[0685] Input: Legal question submitted by user.

[0686] Output: The question is sent to the server. Specifically, this includes the user entering "I would like to ask about evidence collection in litigation" into the app's question form and submitting it.

[0687] Step 7:

[0688] Legal advice generation and notification

[0689] Server: Generates initial legal advice in response to legal questions received from users using an AI model that performs natural language processing (e.g., GPT-3).

[0690] Input: Legal question received from user.

[0691] Processing: The AI ​​model analyzes the question and generates legal advice such as, "When collecting evidence during litigation, it is important to verify the reliability and legality of the evidence."

[0692] Output: The generated legal advice is communicated to the user.

[0693] Step 8:

[0694] Legal counseling appointments available

[0695] Server: Generates and notifies users of legal advice, along with options to book legal counseling.

[0696] Input: Description of legal issue and generated legal advice.

[0697] Processing: The server generates a link that provides counseling appointment options and notifies the user.

[0698] Output: The notification will contain a link such as "Schedule a legal consultation here" that the user can click to complete the booking process.

[0699] In this way, the overall processing flow of the system is to collect the user's biometric data, perform analysis based on that data, and provide customized mental health support and legal support based on the analysis results.

[0700] (Application example 1)

[0701] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0702] Until now, there have been no adequate methods established for managing the mental health of workers in industrial environments. As a result, workers' accumulated stress and fatigue have had a negative impact on productivity and safety, ultimately causing a decline in the quality of the overall working environment. There is a need for a system that can solve these problems, monitor workers' mental health status in real time, and provide appropriate support.

[0703] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0704] In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing a user's emotions and stress level, means for providing customized mental health support to the user based on the analysis results, means for notifying the user of the customized mental health support, and means for collecting biometric data of workers in an industrial environment and suggesting relaxation support and breaks based on the analysis results. This makes it possible to monitor the mental health status of workers in real time and suggest support and breaks that are appropriate for each individual, thereby improving the working environment and increasing productivity.

[0705] An "information processing device" is a device that analyzes collected data and provides various types of support and notifications to users.

[0706] A "sensing device" is a device used to collect a user's biometric data, and examples include smartwatches and smartphones.

[0707] The "means for receiving data and analyzing the user's emotions and stress level" refers to a means for receiving data transmitted from a sensing device and analyzing the data to determine the user's emotional state and level of stress.

[0708] "Means for providing customized mental health support" refers to means for selecting and providing a mental health support method suitable for the user based on the analysis results.

[0709] "Means for notifying users of customized mental health support" refers to means for notifying users of the generated support plan, thereby enabling users to receive actual support.

[0710] An "industrial environment" refers to an industrial site or workplace where manufacturing or processing takes place, and is an environment where managing the mental health of workers is particularly important.

[0711] "Means for collecting workers' biometric data and suggesting relaxation support and rest based on the analysis results" refers to means for collecting biometric data such as heart rate and body temperature of workers in industrial environments and suggesting appropriate relaxation methods and rest based on the results of analyzing this data.

[0712] "Guided Meditation" means a means of providing users with guided meditation sessions for the purposes of stress reduction and relaxation.

[0713] "Psychological Counseling Session" refers to a counseling session to provide psychological support to a User.

[0714] "Relaxation exercise" is a method of providing users with physical activity or exercise aimed at relieving muscle tension or mental refreshment.

[0715] "Means for providing access to legal advice and counseling services" means means for accepting legal questions from users and providing appropriate advice and, if necessary, counseling appointments with professionals.

[0716] Overall structure

[0717] The present invention is a system that uses information processing devices, sensing devices, data analysis and notification systems to manage a user's emotions and stress levels and provide customized mental health support.

[0718] Hardware Configuration

[0719] Server: An important device that analyzes data and manages information. Commercial high-performance servers or cloud servers are often used.

[0720] Sensing devices: Specifically, smartwatches and smartphones. These devices collect biometric data such as heart rate and body temperature from users and transmit it to a server.

[0721] Devices specialized for industrial environments: Devices designed to collect biometric data from workers in industrial environments in real time, enabling highly accurate data analysis.

[0722] Data collection and analysis

[0723] Data collection: Sensing devices collect biometric data such as the user's heart rate and body temperature. This data is sent to a server in real time. In industrial environments, workers wear smartwatches or head-mounted displays to collect this data as needed.

[0724] Data analysis: The server receives the collected biometric data and analyzes it using an AI model. This determines the user's emotional state and stress level. For example, if the heart rate or body temperature exceeds a certain threshold, the stress level is classified into three levels: "low," "medium," or "high."

[0725] Providing mental health support

[0726] Generate customized support: The server generates a mental health support plan tailored to the user based on the analysis results. For example, if the stress level is determined to be high, it generates relaxation support that suggests a five-minute break.

[0727] Support notification: The generated mental health support plan will be sent to the user's smartwatch or smartphone, and the user can follow the instructions to receive actual support.

[0728] Specific examples

[0729] Example of data collection: A smartwatch continuously measures the user's heart rate and transmits the data to a server every two minutes, enabling real-time data monitoring.

[0730] Example of data analysis: If the server performs an analysis and User A's heart rate exceeds 90 bpm and his body temperature is 37.2 degrees, it will be determined that his "stress level is high."

[0731] Example of support notification: Based on the analysis results, the server generates a message suggesting a break and notifies the user through the smartwatch, such as "Your stress level is high. Please take a 5-minute break."

[0732] Prompt Sentence Examples

[0733] For example, you might input a prompt like this for a generative AI model:

[0734] "If the heart rate is above 90, determine that the worker's stress level is high and generate a notification message in the application suggesting a break."

[0735] This makes it possible to monitor the user's mental health status in real time and provide appropriate support immediately.

[0736] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0737] Step 1:

[0738] Data collection:

[0739] The device, a smartwatch or smartphone, continuously measures the user's biometric data, such as heart rate and body temperature. The measured data is sent to the server in real time. The input at this stage is the user's heart rate and body temperature data, which are sent to the server in an appropriate format. The output is the completion of sending the biometric data to the server.

[0740] Step 2:

[0741] Data reception:

[0742] The server receives the biometric data sent from the terminal. The received data is stored in a database in the server. The input at this stage is the biometric data sent from the terminal. The output is the biometric data stored in the server.

[0743] Step 3:

[0744] Data Analysis:

[0745] The server analyzes the collected biometric data using an AI model. Here, the user's emotional state and stress level are determined based on heart rate and body temperature data. Specifically, a heart rate above 90 or a body temperature above 37.0 degrees is determined to be a "high stress state." The input at this stage is the biometric data stored on the server, and the output is the emotional state and stress level as the analytical results.

[0746] Step 4:

[0747] Customized support generation:

[0748] Based on the analysis results, the server generates an optimal mental health support plan for the user. In this case, if the stress level is determined to be high, it will generate suggestions such as "5 minutes of meditation" or "taking a break." The input is the emotional state and stress level resulting from the analysis, and the output is the generated mental health support plan.

[0749] Step 5:

[0750] Support Notice:

[0751] The generated mental health support plan is notified to the device. A message such as "Please take a break" is displayed on the user's smartwatch or smartphone. The input at this stage is the generated mental health support plan, and the output is the message to notify the user.

[0752] Step 6:

[0753] User Response:

[0754] The user follows the mental health support plan, specifically by taking prescribed relaxation and rest breaks as per the notification. At this stage, the user's biometric data is reset again and the next data collection cycle begins.

[0755] This allows users' mental health status to be monitored in real time, and measures such as relaxation and rest can be provided at appropriate times.

[0756] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0757] Introduction

[0758] The present invention relates to a system that uses an information processing device, a sensing device, and an emotion engine to manage a user's emotions and stress levels and provide customized mental health support. In particular, the present invention incorporates an emotion engine that analyzes voice data, text data, and image data to recognize a user's emotions.

[0759] System Configuration

[0760] Information processing device

[0761] The server is responsible for data analysis and information management for the entire system. It receives and analyzes data from the sensing devices and emotion engine, and sends notifications about mental health support to users.

[0762] Sensing Device

[0763] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[0764] Emotion Engine

[0765] The emotion engine recognizes the user's emotions by analyzing voice data, text data, and image data. For example, it analyzes the tone and speed of the voice from the voice data, the choice of words from the text data, and facial expressions from the image data.

[0766] Program and Processing Overview

[0767] Data collection and analysis

[0768] 1. Data Collection

[0769] Device: A smartwatch or smartphone collects the user's biometric data, which is then sent to a server in real time.

[0770] Emotion engine: Receives voice, text, and image data sent from the device and analyzes the user's emotional state.

[0771] 2. Data Reception and Analysis

[0772] Server: Receives data sent from the device and emotion engine and stores it in a database.

[0773] Server: Uses AI models to analyze the stored data. The AI ​​models evaluate emotions and stress levels to determine the user's emotional state (e.g., stress, fatigue, anxiety).

[0774] Providing mental health support

[0775] 1. Generate customization support

[0776] Server: Based on the results of data analysis and the emotion engine's analysis, the server automatically generates a mental health support plan appropriate for the user's emotional state. For example, if the stress level is high, the server suggests a guided meditation.

[0777] 2. Submit your support plan

[0778] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[0779] 3. Support Plan Notification

[0780] Device: Notify the user of the support plan they received and provide instructions on how to implement it. For example, display a notification saying, "Start a 5-minute guided meditation."

[0781] 4. Support Execution

[0782] User: Follow the notifications from your device to play a guided meditation video or do a deep breathing exercise, while your device records your progress.

[0783] 5. Track your progress

[0784] Device: Records the status of support execution (e.g., meditation time and exercise completion status) and sends it to the server.

[0785] 6. Analysis of progress data

[0786] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user responses and effectiveness, more effective support can be provided.

[0787] Integrated legal support

[0788] 1. Receiving and analyzing legal questions

[0789] User: Sends legal questions or concerns to the server via their device.

[0790] Server: Receives the question and uses AI models to generate preliminary legal advice. In some cases, it offers the option to schedule a legal consultation.

[0791] 2. Sending legal advice

[0792] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[0793] Device: Providing legal advice and the option to book a consultation appointment if needed.

[0794] 3. Make a counseling appointment

[0795] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[0796] This is a specific implementation of LegalEase MindGuard, which combines an emotion engine, allowing users to manage their emotions and stress levels in real time and receive appropriate mental health care and legal support.

[0797] The processing flow will be explained below.

[0798] Step 1:

[0799] Data collection

[0800] Device: A smartwatch or smartphone collects the user's biometric data (heart rate, body temperature, keystroke rhythm, etc.), and also acquires audio data through the device's microphone and image data through the camera.

[0801] Terminal: Sends collected data to the server in real time.

[0802] Step 2:

[0803] Data reception

[0804] Server: Receives biometric data, voice data, and image data sent from the terminal and stores them in a database.

[0805] Step 3:

[0806] Analysis of audio and text data

[0807] Emotion engine: Analyzes audio data to analyze the user's tone, speed, and pitch. It also analyzes text data obtained from the device to evaluate word choice and context.

[0808] Server: Receives the results of the emotion engine and stores them in a database.

[0809] Step 4:

[0810] Image data analysis

[0811] Emotion engine: Using image recognition technology, the system analyzes the user's facial expressions, such as facial contours, eye opening, and mouth curve, to determine emotions.

[0812] Server: Receives the results of the emotion engine and stores them in a database.

[0813] Step 5:

[0814] Comprehensive Data Analysis

[0815] Server: An AI model is used to comprehensively analyze all collected data (biometric data, voice data, text data, image data). The AI ​​model integrates multiple data sources to assess the user's emotional state (e.g., stress, fatigue, anxiety) and stress level.

[0816] Step 6:

[0817] Generate customization support

[0818] Server: Based on the analysis results, automatically generate a mental health support plan (e.g., meditation guide, psychological counseling session, relaxation exercise) appropriate for the user.

[0819] Step 7:

[0820] Submit a Support Plan

[0821] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[0822] Step 8:

[0823] Support Plan Notifications

[0824] Device: Notify the user of the received support plan and provide instructions on how to implement it. For example, display a notification on the device screen saying, "Start a 5-minute guided meditation."

[0825] Step 9:

[0826] Support Execution

[0827] User: Follow the notifications from your device to play a guided meditation video or do a deep breathing exercise, while your device records your progress.

[0828] Step 10:

[0829] Recording progress

[0830] Device: Records the status of support execution (e.g., meditation time and exercise completion status) and sends it to the server.

[0831] Step 11:

[0832] Progress data analysis

[0833] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user responses and effectiveness, more effective support can be provided.

[0834] Step 12:

[0835] Providing legal support

[0836] User: If you have any legal questions or concerns, send them to the server via your device.

[0837] Server: Receives the question and uses AI models to generate initial legal advice. If necessary, it provides the option to schedule a legal consultation.

[0838] Step 13:

[0839] Sending legal advice

[0840] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[0841] Device: Providing legal advice and the option to book a consultation appointment if needed.

[0842] Step 14:

[0843] Counseling appointment

[0844] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[0845] This is the detailed program flow of LegalEase MindGuard, which combines an emotion engine. This system allows users to manage their emotions and stress levels in real time and receive appropriate mental health care and legal support.

[0846] Example 2

[0847] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0848] The current mental health care system struggles to properly assess users' emotions and stress levels and provide customized support. It also lacks real-time feedback, ongoing support, and legal advice integration, preventing users from receiving the comprehensive support they truly need.

[0849] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0850] In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing the user's emotions and stress level, means for notifying the user of a mental health support plan generated based on the analysis results and recording the implementation status, means for analyzing the recorded implementation status and using it to improve the future mental health support plan, and means for receiving legal questions from the user, generating initial legal advice, and providing an option to reserve legal counseling as needed. This enables the user to manage their emotions and stress level in real time and receive personalized mental health care and legal support.

[0851] An "information processing device" is a device such as a computer or server that collects, analyzes, and stores data.

[0852] A "sensing device" is a device that acquires biometric and environmental data from a user in real time and transmits it to an information processing device. Examples include smartwatches and smartphones.

[0853] "Means for analyzing emotions and stress levels" refers to algorithms or AI models that assess a user's emotional state and stress level based on the collected data.

[0854] The "Mental Health Support Plan" is a personalized mental health care plan provided to users based on the analysis results, which may include, for example, guided meditation and relaxation exercises.

[0855] A "means for recording implementation status" is a device or application that allows a user to record the progress of the user when actually implementing the mental health support plan.

[0856] "Means for receiving legal questions and generating initial legal advice" refers to an algorithm or AI model that receives legal questions or concerns from users, analyzes them, and provides initial legal advice.

[0857] A "means for providing legal counseling appointment options" is a system that allows a user to make an appointment for legal counseling if they wish to receive additional assistance.

[0858] Introduction

[0859] This invention relates to a system that uses an information processing device, a sensing device, and an emotion engine to manage a user's emotions and stress level and provide customized mental health support. In particular, this invention incorporates an emotion engine that analyzes voice data, text data, and image data to recognize the user's emotions.

[0860] System Configuration

[0861] Information processing device

[0862] The server is responsible for data analysis and information management for the entire system. It receives and analyzes data from the sensing devices and emotion engine, and sends notifications about mental health support to users.

[0863] Sensing Device

[0864] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[0865] Emotion Engine

[0866] The emotion engine recognizes the user's emotions by analyzing voice data, text data, and image data. For example, it analyzes the tone and speed of the voice from the voice data, the choice of words from the text data, and facial expressions from the image data.

[0867] Program and Processing Overview

[0868] Data collection and analysis

[0869] The device captures biometric data and transmits it in real time to a server, which receives it and stores it in a database. The emotion engine analyzes the voice, text, and image data to assess the user's emotional state. The server then uses an AI model to analyze emotions and stress levels.

[0870] Providing mental health support

[0871] The server generates a mental health support plan appropriate for the user based on the analysis results. The plan is then sent to the device, which notifies the user. The user then follows the instructions and implements the plan, and their progress is recorded.

[0872] For example, if a device sends heart rate data to a server, and the server analyzes the data and recognizes a high stress state, it will send a notification suggesting a five-minute guided meditation to the user, who can then begin the meditation and track their progress.

[0873] Integrated legal support

[0874] When a user sends a legal question to the server via their device, the server uses an AI model to generate initial legal advice and, if necessary, provides the option to book a legal consultation. The generated legal advice and booking information are sent to the device, where the user can view and interact with it.

[0875] Examples and prompts

[0876] Specific examples include the following:

[0877] Device: The smartwatch measures the heart rate and sends it to the server.

[0878] Server: Analyzes the received heart rate data and determines that the user is in a state of stress.

[0879] Server: Sends a message to the user's device saying, "Please start the 5-minute guided meditation."

[0880] User: Receive a notification from the device and play a guided meditation video.

[0881] (Example of a prompt)

[0882] "Receive and analyze the user's heart rate data, and generate a program that suggests appropriate guided meditations if stress levels are detected."

[0883] The above is a natural language description of the program process of the system of the present invention, which allows users to manage their emotions and stress levels in real time and receive personalized mental health care and legal support.

[0884] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0885] Step 1: Data collection

[0886] Input: Biometric data from sensors (heart rate, body temperature, keystroke rhythm, etc.)

[0887] Device: A smartwatch or smartphone collects the user's biometric data through sensors, which are then sent to a server in real time.

[0888] Output: The collected biometric data is sent to the server.

[0889] Specifically, the smartwatch measures the user's heart rate every second, sends the data to the smartphone via Bluetooth, and then the smartphone sends it to a server via Wi-Fi.

[0890] Step 2: Receiving and storing data

[0891] Input: Biometric data sent from the device

[0892] Server: Receives biometric data sent from the device in real time and stores it in a database.

[0893] Output: Biometric data stored in a database

[0894] Specifically, the server receives the data through a dedicated API and stores it in a database in the form of "user ID, measurement time, heart rate, body temperature, etc."

[0895] Step 3: Data analysis

[0896] Input: Biometric data stored in a database

[0897] Server: The stored data is fed into an AI model to assess the user's emotions and stress levels. The emotion engine also analyzes voice, text, and image data.

[0898] Output: Analysis results (e.g. high stress, fatigue, relaxed)

[0899] Specifically, the server processes batches of data weekly and feeds them into an AI model to estimate emotions and stress levels. For example, an elevated heart rate and a drop in voice tone might be assessed as "high stress."

[0900] Step 4: Generate a Mental Health Support Plan

[0901] Input: Analysis results

[0902] Server: Based on the analysis results, automatically generate a mental health support plan appropriate for the user.

[0903] Output: Generated mental health support plan (e.g., guided meditation, relaxation exercises)

[0904] Specifically, if the server detects that the user is in a high-stress state based on the analysis results, it generates a support plan suggesting a "5-minute meditation guide."

[0905] Step 5: Submit your support plan

[0906] Input: Generated Mental Health Support Plan

[0907] Server: Sends the generated support plan to the device.

[0908] Output: Notification message sent to the user's device (e.g., notification that a guided meditation has started)

[0909] Specifically, the server uses the SMTP protocol to send a notification to the user's smartphone saying, "Please start the meditation guide."

[0910] Step 6: Support Execution Notification

[0911] Input: Support plan notification

[0912] Device: Receives notifications and displays them to the user.

[0913] Output: A notification message that will be displayed on the user's terminal.

[0914] Specifically, it uses the smartphone's notification function to display a pop-up message on the user's screen saying, "Please start a 5-minute guided meditation."

[0915] Step 7: Performing and recording support

[0916] Input: Support plan execution instructions

[0917] User: Follows notifications from the device and provides mental health support. The device records the execution status.

[0918] Output: Performance data (e.g., meditation time, exercise completion status)

[0919] Specifically, the user follows the notification to play the guided meditation video, while the smartphone records the playback time. The smartphone also records the progress of the exercise by pressing the completion button.

[0920] Step 8: Analyze support progress

[0921] Input: Recorded execution status data

[0922] Server: Receives and analyzes progress data and uses it to improve the next mental health support plan.

[0923] Output: Improved support plan

[0924] Specifically, the server retrains the AI ​​model based on the performance data and generates personalized feedback such as "suggesting 10 minutes of meditation next time."

[0925] Step 9: Legal Questions Reception and Analysis

[0926] Input: Legal Question from User

[0927] User: Type and submit legal questions via the device.

[0928] Server: Receives the question and uses AI models to generate preliminary legal advice.

[0929] Output: Generated legal advice

[0930] Specifically, the user types "Please tell me about property division in divorce" into their device, which is then sent to the server, which uses an AI model to respond with the appropriate legal information.

[0931] Step 10: Submit legal advice and book a consultation

[0932] Input: Generated legal advice and counseling appointment information

[0933] Server: Sends legal advice and counseling appointment information to the terminal.

[0934] Device: Displays legal advice to the user and offers the option to book a consultation if necessary.

[0935] Output: Legal advice and counseling booking options displayed to the user

[0936] Specifically, the device will display a message saying, "Details on how to divide assets are provided. Click 'Book' to schedule a consultation."

[0937] (Application example 2)

[0938] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0939] In modern society, mental health has become a significant issue due to increased stress and anxiety. However, conventional mental health care systems have difficulty providing accurate support adapted to each user's individual emotional state and stress level. Furthermore, there has been a lack of efficient means to provide continuous mental health support in remote environments or to deliver content appropriate for each user. This has led to problems such as users not receiving appropriate support, limiting the effectiveness of mental health care.

[0940] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing the user's emotions and stress level, means for providing customized mental health support to the user based on the analysis results, means for notifying the user of the customized mental health support, means for delivering appropriate content based on the analysis results, means for recording content consumption status and generating feedback data, and means for improving future mental health support based on the feedback data. This makes it possible to provide highly accurate mental health care and appropriate content according to the user's individual emotional state and stress level.

[0941] "Information processing device" is a general term for hardware and software for receiving, storing, and analyzing data.

[0942] A "sensing device" is a device that collects a user's biometric and environmental data in real time, and is a general term for smartwatches, smartphones, etc.

[0943] "Emotion and stress level analysis means" is a general term for algorithms and technologies for analyzing collected voice data, text data, and image data to estimate a user's emotional state and stress level.

[0944] "Means for providing customized mental health support" is a general term for technologies and processes that automatically generate and provide mental health care adapted to a user's specific emotions and stress state based on analysis results.

[0945] "Mental health support notification means" is a general term for technologies and devices that notify users of customized mental health support plans and encourage them to take action.

[0946] "Content delivery method" is a general term for the technologies and processes that deliver digital content such as music, videos, and podcasts appropriate to a user's emotions and stress levels to a user's device via a network.

[0947] "Means for recording consumption status" is a general term for technologies that record how users consume provided content (for example, playback time and number of times) and store this information in a database.

[0948] "Feedback data generation means" is a general term for the processes and technologies that generate new analytical data based on recorded content consumption status and user feedback, and use it to improve future mental health support.

[0949] In this invention, we combine an information processing device, a sensing device, and an emotion engine to build a system that manages a user's emotions and stress level and provides customized mental health support. Each component of the system and its function are described in detail below.

[0950] System Configuration

[0951] Information processing device

[0952] The server is responsible for data analysis and information management for the entire system. It also functions as an "information processing device," analyzing data collected from the sensing devices and emotion engine to provide mental health support tailored to the user.

[0953] Sensing Device

[0954] The devices include smartwatches and smartphones. These devices act as "sensing devices" that continuously collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm. This data is then transmitted to a server in real time.

[0955] Emotion Engine

[0956] The emotion engine, which functions as an "emotion and stress level analyzer," analyzes voice, text, and image data to identify the user's emotional state. Specifically, it analyzes the tone and speed of voice from the voice data, selected words from the text data, and facial expressions from the image data.

[0957] Programs and their processing

[0958] The server receives biometric data from the sensing device and analysis results from the emotion engine, stores them in a database, analyzes the stored data to determine the user's emotions and stress level, and then generates a customized mental health support plan based on the analysis results and notifies the user.

[0959] Customized Mental Health Support

[0960] As a "means of providing customized mental health support," the server provides users with appropriate mental health support based on the analysis results. This support can include guided meditations, relaxation music, podcasts, etc. For example, if stress levels are high, relaxation music or guided meditations will be provided.

[0961] Content distribution and feedback

[0962] The server will then use the "content delivery means" to deliver content appropriate to the user based on the analysis results. The device will also record consumption status as a "consumption status recording means" and send this to the server. This will allow the "feedback data generation means" to analyze the user's progress and effectiveness, allowing for further customization of support from the next time onwards.

[0963] Hardware and software used

[0964] Hardware:

[0965] Smartphones, smartwatches (sensing devices)

[0966] Server (information processing device)

[0967] software:

[0968] TensorFlow, Keras (emotion engine, AI model)

[0969] OpenCV (image analysis)

[0970] Librosa (audio analysis)

[0971] Examples and how to use generative AI models

[0972] For example, if a user is feeling stressed, they can use prompts like the following to feed data into a generative AI model:

[0973] Example prompt sentence:

[0974] The user's biometric data indicates a heart rate of 90 and a body temperature of 37.5°C. Voice data analysis indicates the voice tone is unstable and fast. Image data analysis indicates the facial expression indicates sadness. Based on this data, diagnose the user's current emotional state and suggest appropriate mental health support content.

[0975] This system allows users to manage their emotions and stress levels in real time and receive appropriate mental health care, which is expected to improve their mental health and quality of life.

[0976] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0977] Step 1:

[0978] The device collects the user's biometric data. It uses a smartwatch or smartphone to measure heart rate, body temperature, and keystroke rhythm in real time and transmits the data to a server. The input is various biometric data, and the output is the biometric data sent to the server.

[0979] Step 2:

[0980] The server uses an emotion engine to analyze the user's voice data, text data, and image data. The voice data sent from the device is used to extract MFCCs using Librosa, and the image data is used to analyze facial expressions using OpenCV. The text data is analyzed using natural language processing technology. The input is voice, text, and image data, and the output is the analysis of the user's emotional state and stress level.

[0981] Step 3:

[0982] The server integrates data from the sensing device and the emotion engine, and uses an AI model (using TensorFlow and Keras) to determine the user's current emotional state and stress level. The input is biometric data and the analysis results of the emotion engine, and the output is the determined emotional state and stress level.

[0983] Step 4:

[0984] The server generates a customized mental health support plan. Based on the determined emotional state and stress level, it selects appropriate content from relaxation music, guided meditations, podcasts, etc. The input is the determined emotional state and stress level, and the output is a customized mental health support plan.

[0985] Step 5:

[0986] The server sends the customized mental health support plan to the terminal, and the terminal displays specific implementation methods (video links and text instructions) to the user based on the received notification. The input is the customized mental health support plan, and the output is the notification to the user.

[0987] Step 6:

[0988] The user performs mental health support based on notifications from the device. For example, the user performs specific actions such as playing relaxation music or watching a guided meditation video. The input is the notification to the user, and the output is the execution of mental health support.

[0989] Step 7:

[0990] The device records the user's mental health support activities, collecting data on the type and time of activities performed and sending it to the server. The input is the mental health support activity data, and the output is the recorded data sent to the server.

[0991] Step 8:

[0992] The server analyzes the feedback data and uses it to improve future mental health support plans. It analyzes user responses and effects and adjusts the AI ​​model. The input is the recorded data and response data, and the output is an updated mental health support plan.

[0993] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0994] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0995] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0996] [Third embodiment]

[0997] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0998] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0999] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1000] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1001] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1002] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1003] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1004] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1005] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1006] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1007] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1008] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1009] Introduction

[1010] The present invention relates to a method for managing a user's emotions and stress levels and providing customized mental health support using information processing devices, sensing devices, data analysis and notification systems.

[1011] System Configuration

[1012] Information processing device

[1013] The server is responsible for the system's primary data analysis and information management. It receives data from the sensing devices, performs calculations for analysis, and sends notifications regarding mental health support to users.

[1014] Sensing Device

[1015] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[1016] Program and Processing Overview

[1017] Data collection and analysis

[1018] 1. Data Collection

[1019] Device: A smartwatch or smartphone collects the user's biometric data (heart rate, body temperature, etc.), which is then sent to a server in real time.

[1020] 2. Data Reception and Analysis

[1021] Server: Receives data sent from the device and analyzes it using an AI model. As a result of the analysis, the user's emotional state (e.g., stress, fatigue, anxiety) and stress level are determined.

[1022] Providing mental health support

[1023] 1. Generate customized support

[1024] Server: Generates a mental health support plan tailored to the user based on the data analysis results. For example, if stress levels are high, it provides a meditation guide.

[1025] 2. Support Notifications

[1026] Device: Notifies the user of the generated mental health support plan and provides specific instructions on how to implement it (e.g., starting a guided meditation).

[1027] Integrated legal support

[1028] 1. Receiving and analyzing legal questions

[1029] User: If you have any legal questions or concerns, you can send them to the server from your device.

[1030] Server: Receives the question and generates preliminary legal advice using AI.

[1031] 2. Providing counseling services

[1032] Server: Provides an option to book legal consultations if needed, allowing users to speak to a legal professional directly.

[1033] Specific examples

[1034] Specific examples of mental health care

[1035] 1. Data Collection

[1036] Device: The smartwatch continuously measures the user's heart rate and sends the data to the server every two minutes.

[1037] 2. Data analysis and customization support

[1038] Server: After analyzing the heart rate data, the server determines that the user's stress level is "high." Based on this, the server generates a support plan that suggests a five-minute guided meditation.

[1039] 3. Notice and Enforcement

[1040] Device: Notifies the user of the guided meditation video and instructs them to play it.

[1041] User: Follow the guided meditation for 5 minutes.

[1042] Examples of legal support

[1043] 1. Accepting questions

[1044] User: Submit legal questions regarding ongoing litigation proceedings from the device.

[1045] 2. Legal Answers and Counseling Appointments

[1046] Server: Analyzes the question and generates relevant legal advice. It also provides the user with a link to schedule a legal consultation.

[1047] Device: Informs users of legal advice and options for booking counseling appointments.

[1048] Users: Book a consultation and speak to a specialist if necessary.

[1049] This allows users to receive real-time assistance in managing emotions and stress, reducing the mental burden during litigation.

[1050] The processing flow will be explained below.

[1051] Step 1:

[1052] Data collection

[1053] Device: A smartwatch or smartphone collects biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmits this data to a server at regular intervals.

[1054] Step 2:

[1055] Data reception

[1056] Server: Receives data sent from the device. The received data is stored in a database and prepared for analysis.

[1057] Step 3:

[1058] Data analysis

[1059] Server: Uses AI models to analyze stored biometric data, assessing emotions and stress levels to determine the user's emotional state (e.g., stress, fatigue, anxiety).

[1060] Step 4:

[1061] Generate customization support

[1062] Server: Based on the analysis results, the server automatically generates a mental health support plan appropriate for the user's emotional state. For example, it suggests a guided meditation if the user's stress level is high.

[1063] Step 5:

[1064] Submit a Support Plan

[1065] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[1066] Step 6:

[1067] Support Plan Notifications

[1068] Device: Notify the user of the received support plan and show them how to implement it. For example, a notification saying "Start a 5-minute guided meditation" will be displayed on the device screen.

[1069] Step 7:

[1070] Support Execution

[1071] User: Follow the notifications from the device to play a guided meditation video or perform deep breathing exercises, while the device continues to record their progress.

[1072] Step 8:

[1073] Recording progress

[1074] Device: Records the status of support execution (for example, meditation time and exercise completion status) and sends it to the server.

[1075] Step 9:

[1076] Progress data analysis

[1077] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user responses and effectiveness, more effective support can be provided.

[1078] Step 10:

[1079] Providing legal support

[1080] User: If there is a legal consultation or question, the user makes an inquiry to the server via the terminal.

[1081] Server: Analyzes the user's question and uses AI to automatically generate initial legal advice. If necessary, it provides a link to book a legal consultation.

[1082] Step 11:

[1083] Sending legal advice

[1084] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[1085] Device: Displays legal advice to the user and notifies them when counseling appointments are available.

[1086] Step 12:

[1087] Counseling appointment

[1088] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[1089] This is the detailed program flow of LegalEase MindGuard. This system allows users to receive appropriate mental health support and legal advice in real time, significantly reducing the mental burden during litigation.

[1090] Example 1

[1091] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1092] In modern society, there is a need to effectively manage users' emotions and stress levels and provide appropriate mental health support. However, existing systems do not properly collect and analyze biometric data, making it difficult to provide users with prompt, customized support. Furthermore, there are no systems that can respond to legal questions or provide counseling services. This makes it difficult for users to receive mental and legal support at the appropriate time.

[1093] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1094] In this invention, the server includes a data analysis means, a determination means, a mental health support plan generation means, a notification means, a legal question analysis means, and a legal counseling appointment provision means. This makes it possible to analyze a user's biometric data in real time and provide a customized mental health support plan. It also makes it possible to quickly provide comprehensive support to users through initial responses to legal questions and appointments for counseling services.

[1095] An "information processing device" is a computer device that receives, analyzes, and manages data.

[1096] "Sensing devices" are devices that collect biometric data from users, including smartwatches and smartphones.

[1097] "Biometric data" refers to physical data such as a user's heart rate, body temperature, and keystroke rhythm.

[1098] "Data analysis means" refers to the means for analyzing the collected biometric data, using technologies such as AI models to extract meaningful information from the data.

[1099] The "determination means" is a means for determining the user's emotional state and stress level based on the analyzed data.

[1100] The "mental health support plan generation means" is a means for generating a mental health support plan tailored to the user based on the assessment results.

[1101] "Notification means" refers to a means for notifying a user of the generated mental health support plan.

[1102] "Legal question analysis means" means for receiving a legal question from a user and generating initial legal advice in response thereto.

[1103] A "Legal Counseling Appointment Offering" is a means for providing Users with the option to book legal counseling services.

[1104] The present invention relates to a system that uses information processing devices, sensing devices, data analysis means, and notification systems to manage a user's emotions and stress levels and provide customized mental health support and legal support.

[1105] System Configuration

[1106] Information processing device

[1107] The server is responsible for the system's primary data analysis and information management. Specifically, it receives data from the sensing devices and performs calculations for analysis. The server also sends notifications to users regarding mental health support. The server's processing uses AI models such as TensorFlow.

[1108] Sensing Device

[1109] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server in real time. With the user's consent, the devices monitor the data continuously.

[1110] Data Analysis Methods

[1111] The server receives the biometric data sent from the device and stores it in a database. The stored data is analyzed using AI models such as TensorFlow. As a result of the analysis, the user's emotional state (stress, fatigue, anxiety) and stress level are identified.

[1112] Mental Health Support Plan Generation Tool

[1113] Based on the analysis results, the server generates a personalized mental health support plan for each user, suggesting guided meditations and relaxing music for users with high stress levels, for example.

[1114] Notification means

[1115] The device will then notify the user of the customized mental health support plan sent from the server, which will be displayed as a push notification or in-app notification, prompting the user to take specific action.

[1116] legal question analysis tool

[1117] Users submit legal questions from their devices, which are then received by a server that uses natural language processing models such as GPT-3 to generate initial legal advice.

[1118] Legal counseling appointment delivery methods

[1119] Depending on the legal question, the server generates and notifies the user of a legal counseling appointment option, which includes a link to meet with an expert.

[1120] Specific examples

[1121] Specific examples of mental health care

[1122] 1. Data Collection

[1123] Device: The smartwatch continuously measures the user's heart rate and sends the data to the server every 30 seconds.

[1124] 2. Data analysis and generation of customized support

[1125] Server: Analyzes heart rate data using an AI model, and if stress levels are determined to be high, generates a support plan suggesting a five-minute guided meditation.

[1126] 3. Notification

[1127] On device: The user is notified of the support plan and is shown the message, "Your stress level seems high. Try a 5-minute guided meditation." The user taps the notification to begin the guided meditation.

[1128] Examples of legal support

[1129] 1. Accepting questions

[1130] User: Sends questions about the lawsuit from their smartphone to the server.

[1131] 2. Legal Answers and Counseling Appointments

[1132] Server: Analyzes the question using GPT-3 and generates an initial advice such as "When collecting evidence during litigation, it is important to verify its reliability and legality." It also sends a notification with a link to schedule a legal consultation.

[1133] 3. Counseling appointment

[1134] Users: Receive notifications and, if necessary, book counseling appointments and meetings with specialists.

[1135] Example prompts for generative AI models

[1136] "Please explain the specific process flow for collecting heart rate data in real time while the user is wearing the smartwatch, analyzing stress levels using TensorFlow, and providing customized mental health support based on the results. Also, please include a process flow for using GPT-3 to provide initial response to legal questions."

[1137] As can be seen, this invention can improve a user's overall well-being by using their biometric data to manage their emotions and stress levels in real time and provide mental health and legal support.

[1138] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1139] Step 1:

[1140] Data collection

[1141] Device: Smartwatches and smartphones continuously collect users' biometric data (heart rate, body temperature, keystroke rhythm).

[1142] Input: User biometric data. For example, a smartwatch measures heart rate and temperature every 30 seconds, and a smartphone captures keystroke rhythm.

[1143] Output: The collected biometric data is temporarily stored on the device. The smartwatch transmits the data via Bluetooth to the smartphone, which prepares it to be sent to the server via Wi-Fi or mobile data.

[1144] Step 2:

[1145] Data reception

[1146] Server: Receives biometric data sent from the terminal.

[1147] Input: Biometric data sent from the device.

[1148] Output: The received biometric data is stored in the server's database. Specifically, the server's receiving module captures the data and stores it in the database.

[1149] Step 3:

[1150] Data analysis

[1151] Server: Analyzes the received biometric data using an AI model (such as TensorFlow).

[1152] Input: Biometric data stored on the server.

[1153] Processing: The AI ​​model analyzes the data and determines the user's emotional state and stress level.

[1154] Output: The analysis results in the user's emotional state (e.g., stress level is high, medium, low, etc.) and a stress index.

[1155] Step 4:

[1156] Customized Support Plan Generation

[1157] Server: Generates a personalized mental health support plan for each user based on the results of data analysis.

[1158] Input: Analysis results (user's emotional state and stress level).

[1159] Processing: The server creates a support plan based on the analysis results. For example, it suggests a five-minute guided meditation for a user with a high stress level.

[1160] Output: A customized support plan is generated, which may include guided meditation, relaxation exercises, or psychological counseling sessions.

[1161] Step 5:

[1162] Support Notifications

[1163] On the device: Notifies the user of the support plan sent from the server.

[1164] Input: The customized support plan sent by the server.

[1165] Action: Your device will display your support plan as a push or in-app notification.

[1166] Output: The user is notified with a message such as "Your stress level seems high. Try a 5-minute guided meditation." When the user taps the notification, a guided meditation app or similar will launch.

[1167] Step 6:

[1168] Accepting legal questions

[1169] Users: If they have legal questions or concerns, they can send them to the server using their smartphone or PC.

[1170] Input: Legal question submitted by user.

[1171] Output: The question is sent to the server. Specifically, this includes the user entering "I would like to ask about evidence collection in litigation" into the app's question form and submitting it.

[1172] Step 7:

[1173] Legal Advice Generation and Notification

[1174] Server: Generates initial legal advice in response to legal questions received from users using an AI model that performs natural language processing (e.g., GPT-3).

[1175] Input: Legal question received from user.

[1176] Processing: The AI ​​model analyzes the question and generates legal advice such as, "When collecting evidence during litigation, it is important to verify the reliability and legality of the evidence."

[1177] Output: The generated legal advice is communicated to the user.

[1178] Step 8:

[1179] Legal counseling appointments available

[1180] Server: Generates and notifies users of legal advice, along with options to book legal counseling.

[1181] Input: Description of legal issue and generated legal advice.

[1182] Processing: The server generates a link that provides counseling appointment options and notifies the user.

[1183] Output: The notification will contain a link such as "Schedule a legal consultation here" that the user can click to complete the booking process.

[1184] In this way, the overall processing flow of the system is to collect the user's biometric data, perform analysis based on that data, and provide customized mental health support and legal support based on the analysis results.

[1185] (Application example 1)

[1186] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1187] Until now, there have been no adequate methods established for managing the mental health of workers in industrial environments. As a result, workers' accumulated stress and fatigue have had a negative impact on productivity and safety, ultimately causing a decline in the quality of the overall working environment. There is a need for a system that can solve these problems, monitor workers' mental health status in real time, and provide appropriate support.

[1188] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1189] In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing a user's emotions and stress level, means for providing customized mental health support to the user based on the analysis results, means for notifying the user of the customized mental health support, and means for collecting biometric data of workers in an industrial environment and suggesting relaxation support and breaks based on the analysis results. This makes it possible to monitor the mental health status of workers in real time and suggest support and breaks that are appropriate for each individual, thereby improving the working environment and increasing productivity.

[1190] An "information processing device" is a device that analyzes collected data and provides various types of support and notifications to users.

[1191] A "sensing device" is a device used to collect a user's biometric data, and examples include smartwatches and smartphones.

[1192] The "means for receiving data and analyzing the user's emotions and stress level" refers to a means for receiving data transmitted from a sensing device and analyzing the data to determine the user's emotional state and level of stress.

[1193] "Means for providing customized mental health support" refers to means for selecting and providing a mental health support method suitable for the user based on the analysis results.

[1194] "Means for notifying users of customized mental health support" refers to means for notifying users of the generated support plan, thereby enabling users to receive actual support.

[1195] An "industrial environment" refers to an industrial site or workplace where manufacturing or processing takes place, and is an environment where managing the mental health of workers is particularly important.

[1196] "Means for collecting workers' biometric data and suggesting relaxation support and rest based on the analysis results" refers to means for collecting biometric data such as heart rate and body temperature of workers in industrial environments and suggesting appropriate relaxation methods and rest based on the results of analyzing this data.

[1197] "Guided Meditation" means a means of providing users with guided meditation sessions for the purposes of stress reduction and relaxation.

[1198] "Psychological Counseling Session" refers to a counseling session to provide psychological support to a User.

[1199] "Relaxation exercise" is a method of providing users with physical activity or exercise aimed at relieving muscle tension or mental refreshment.

[1200] "Means for providing access to legal advice and counseling services" means means for accepting legal questions from users and providing appropriate advice and, if necessary, counseling appointments with professionals.

[1201] Overall structure

[1202] The present invention is a system that uses information processing devices, sensing devices, data analysis and notification systems to manage a user's emotions and stress levels and provide customized mental health support.

[1203] Hardware Configuration

[1204] Server: An important device that analyzes data and manages information. Commercial high-performance servers or cloud servers are often used.

[1205] Sensing devices: Specifically, smartwatches and smartphones. These devices collect biometric data such as heart rate and body temperature from users and transmit it to a server.

[1206] Devices specialized for industrial environments: Devices designed to collect biometric data from workers in industrial environments in real time, enabling highly accurate data analysis.

[1207] Data collection and analysis

[1208] Data collection: Sensing devices collect biometric data such as the user's heart rate and body temperature. This data is sent to a server in real time. In industrial environments, workers wear smartwatches or head-mounted displays to collect this data as needed.

[1209] Data analysis: The server receives the collected biometric data and analyzes it using an AI model. This determines the user's emotional state and stress level. For example, if the heart rate or body temperature exceeds a certain threshold, the stress level is classified into three levels: "low," "medium," or "high."

[1210] Providing mental health support

[1211] Generate customized support: The server generates a mental health support plan tailored to the user based on the analysis results. For example, if the stress level is determined to be high, it generates relaxation support that suggests a five-minute break.

[1212] Support notification: The generated mental health support plan will be sent to the user's smartwatch or smartphone, and the user can follow the instructions to receive actual support.

[1213] Specific examples

[1214] Example of data collection: A smartwatch continuously measures the user's heart rate and transmits the data to a server every two minutes, enabling real-time data monitoring.

[1215] Example of data analysis: If the server performs an analysis and User A's heart rate exceeds 90 bpm and his body temperature is 37.2 degrees, it will be determined that his "stress level is high."

[1216] Example of support notification: Based on the analysis results, the server generates a message suggesting a break and notifies the user through the smartwatch, such as "Your stress level is high. Please take a 5-minute break."

[1217] Prompt Sentence Examples

[1218] For example, you might input a prompt like this for a generative AI model:

[1219] "If the heart rate is above 90, determine that the worker's stress level is high and generate a notification message in the application suggesting a break."

[1220] This makes it possible to monitor the user's mental health status in real time and provide appropriate support immediately.

[1221] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1222] Step 1:

[1223] Data collection:

[1224] The device, a smartwatch or smartphone, continuously measures the user's biometric data, such as heart rate and body temperature. The measured data is sent to the server in real time. The input at this stage is the user's heart rate and body temperature data, which are sent to the server in an appropriate format. The output is the completion of sending the biometric data to the server.

[1225] Step 2:

[1226] Data reception:

[1227] The server receives the biometric data sent from the terminal. The received data is stored in a database in the server. The input at this stage is the biometric data sent from the terminal. The output is the biometric data stored in the server.

[1228] Step 3:

[1229] Data Analysis:

[1230] The server analyzes the collected biometric data using an AI model. Here, the user's emotional state and stress level are determined based on heart rate and body temperature data. Specifically, a heart rate above 90 or a body temperature above 37.0 degrees is determined to be a "high stress state." The input at this stage is the biometric data stored on the server, and the output is the emotional state and stress level as the analytical results.

[1231] Step 4:

[1232] Customized support generation:

[1233] Based on the analysis results, the server generates an optimal mental health support plan for the user. In this case, if the stress level is determined to be high, it will generate suggestions such as "5 minutes of meditation" or "taking a break." The input is the emotional state and stress level resulting from the analysis, and the output is the generated mental health support plan.

[1234] Step 5:

[1235] Support Notice:

[1236] The generated mental health support plan is notified to the device. A message such as "Please take a break" is displayed on the user's smartwatch or smartphone. The input at this stage is the generated mental health support plan, and the output is the message to notify the user.

[1237] Step 6:

[1238] User Response:

[1239] The user follows the mental health support plan, specifically by taking prescribed relaxation and rest breaks as per the notification. At this stage, the user's biometric data is reset again and the next data collection cycle begins.

[1240] This allows users' mental health status to be monitored in real time, and measures such as relaxation and rest can be provided at appropriate times.

[1241] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1242] Introduction

[1243] The present invention relates to a system that uses an information processing device, a sensing device, and an emotion engine to manage a user's emotions and stress levels and provide customized mental health support. In particular, the present invention incorporates an emotion engine that analyzes voice data, text data, and image data to recognize a user's emotions.

[1244] System Configuration

[1245] Information processing device

[1246] The server is responsible for data analysis and information management for the entire system. It receives and analyzes data from the sensing devices and emotion engine, and sends notifications about mental health support to users.

[1247] Sensing Device

[1248] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[1249] Emotion Engine

[1250] The emotion engine recognizes the user's emotions by analyzing voice data, text data, and image data. For example, it analyzes the tone and speed of the voice from the voice data, the choice of words from the text data, and facial expressions from the image data.

[1251] Program and Processing Overview

[1252] Data collection and analysis

[1253] 1. Data Collection

[1254] Device: A smartwatch or smartphone collects the user's biometric data, which is then sent to a server in real time.

[1255] Emotion engine: Receives voice, text, and image data sent from the device and analyzes the user's emotional state.

[1256] 2. Data Reception and Analysis

[1257] Server: Receives data sent from the device and emotion engine and stores it in a database.

[1258] Server: Uses AI models to analyze the stored data. The AI ​​models evaluate emotions and stress levels to determine the user's emotional state (e.g., stress, fatigue, anxiety).

[1259] Providing mental health support

[1260] 1. Generate customization support

[1261] Server: Based on the results of data analysis and the emotion engine's analysis, the server automatically generates a mental health support plan appropriate for the user's emotional state. For example, if the stress level is high, the server suggests a guided meditation.

[1262] 2. Submit your support plan

[1263] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[1264] 3. Support Plan Notification

[1265] Device: Notify the user of the support plan received and provide instructions on how to implement it. For example, display a notification saying, "Start a 5-minute guided meditation."

[1266] 4. Support Execution

[1267] User: Follow the notifications from your device to play a guided meditation video or do a deep breathing exercise, while your device records your progress.

[1268] 5. Track your progress

[1269] Device: Records the status of support execution (e.g., meditation time and exercise completion status) and sends it to the server.

[1270] 6. Analysis of progress data

[1271] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user responses and effectiveness, more effective support can be provided.

[1272] Integrated legal support

[1273] 1. Receiving and analyzing legal questions

[1274] User: Sends legal questions or concerns to the server via their device.

[1275] Server: Receives the question and uses AI models to generate preliminary legal advice. In some cases, it offers the option to schedule a legal consultation.

[1276] 2. Sending legal advice

[1277] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[1278] Device: Providing legal advice and the option to book a consultation appointment if needed.

[1279] 3. Make a counseling appointment

[1280] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[1281] The above is a specific implementation of LegalEase MindGuard, which combines an emotion engine, allowing users to manage their emotions and stress levels in real time and receive appropriate mental health care and legal support.

[1282] The processing flow will be explained below.

[1283] Step 1:

[1284] Data collection

[1285] Device: A smartwatch or smartphone collects the user's biometric data (heart rate, body temperature, keystroke rhythm, etc.), and also acquires audio data through the device's microphone and image data through the camera.

[1286] Terminal: Sends collected data to the server in real time.

[1287] Step 2:

[1288] Data reception

[1289] Server: Receives biometric data, voice data, and image data sent from the terminal and stores them in a database.

[1290] Step 3:

[1291] Analysis of audio and text data

[1292] Emotion engine: Analyzes audio data to analyze the user's tone, speed, and pitch. It also analyzes text data obtained from the device to evaluate word choice and context.

[1293] Server: Receives the results of the emotion engine and stores them in a database.

[1294] Step 4:

[1295] Image data analysis

[1296] Emotion engine: Using image recognition technology, the system analyzes the user's facial expressions, such as facial contours, eye opening, and mouth curve, to determine emotions.

[1297] Server: Receives the results of the emotion engine and stores them in a database.

[1298] Step 5:

[1299] Comprehensive Data Analysis

[1300] Server: An AI model is used to comprehensively analyze all collected data (biometric data, voice data, text data, image data). The AI ​​model integrates multiple data sources to assess the user's emotional state (e.g., stress, fatigue, anxiety) and stress level.

[1301] Step 6:

[1302] Generate customization support

[1303] Server: Based on the analysis results, automatically generate a mental health support plan (e.g., meditation guide, psychological counseling session, relaxation exercise) appropriate for the user.

[1304] Step 7:

[1305] Submit a Support Plan

[1306] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[1307] Step 8:

[1308] Support Plan Notifications

[1309] Device: Notify the user of the received support plan and provide instructions on how to implement it. For example, display a notification on the device screen saying, "Start a 5-minute guided meditation."

[1310] Step 9:

[1311] Support Execution

[1312] User: Follow the notifications from your device to play a guided meditation video or do a deep breathing exercise, while your device records your progress.

[1313] Step 10:

[1314] Recording progress

[1315] Device: Records the status of support execution (e.g., meditation time and exercise completion status) and sends it to the server.

[1316] Step 11:

[1317] Progress data analysis

[1318] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user responses and effectiveness, more effective support can be provided.

[1319] Step 12:

[1320] Providing legal support

[1321] User: If you have any legal questions or concerns, send them to the server via your device.

[1322] Server: Receives the question and uses AI models to generate initial legal advice. If necessary, it provides the option to schedule a legal consultation.

[1323] Step 13:

[1324] Sending legal advice

[1325] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[1326] Device: Providing legal advice and the option to book a consultation appointment if needed.

[1327] Step 14:

[1328] Counseling appointment

[1329] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[1330] This is the detailed program flow of LegalEase MindGuard, which combines an emotion engine. This system allows users to manage their emotions and stress levels in real time and receive appropriate mental health care and legal support.

[1331] Example 2

[1332] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1333] The current mental health care system struggles to properly assess users' emotions and stress levels and provide customized support. It also lacks real-time feedback, ongoing support, and legal advice integration, preventing users from receiving the comprehensive support they truly need.

[1334] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1335] In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing the user's emotions and stress level, means for notifying the user of a mental health support plan generated based on the analysis results and recording the implementation status, means for analyzing the recorded implementation status and using it to improve the future mental health support plan, and means for receiving legal questions from the user, generating initial legal advice, and providing an option to reserve legal counseling as needed. This enables the user to manage their emotions and stress level in real time and receive personalized mental health care and legal support.

[1336] An "information processing device" is a device such as a computer or server that collects, analyzes, and stores data.

[1337] A "sensing device" is a device that acquires biometric and environmental data from a user in real time and transmits the data to an information processing device. Examples include smartwatches and smartphones.

[1338] "Means for analyzing emotions and stress levels" refers to algorithms or AI models that assess a user's emotional state and stress levels based on the collected data.

[1339] The "Mental Health Support Plan" is a personalized mental health care plan provided to users based on the analysis results, which may include, for example, guided meditation and relaxation exercises.

[1340] A "means for recording implementation status" is a device or application that allows a user to record the progress of the user when actually implementing the mental health support plan.

[1341] "Means for receiving legal questions and generating initial legal advice" refers to an algorithm or AI model that receives legal questions or concerns from users, analyzes them, and provides initial legal advice.

[1342] A "means for providing legal counseling appointment options" is a system that allows a user to make an appointment for legal counseling if they wish to receive additional assistance.

[1343] Introduction

[1344] This invention relates to a system that uses an information processing device, a sensing device, and an emotion engine to manage a user's emotions and stress level and provide customized mental health support. In particular, this invention incorporates an emotion engine that analyzes voice data, text data, and image data to recognize the user's emotions.

[1345] System Configuration

[1346] Information processing device

[1347] The server is responsible for data analysis and information management for the entire system. It receives and analyzes data from the sensing devices and emotion engine, and sends notifications about mental health support to users.

[1348] Sensing Device

[1349] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[1350] Emotion Engine

[1351] The emotion engine recognizes the user's emotions by analyzing voice data, text data, and image data. For example, it analyzes the tone and speed of the voice from the voice data, the choice of words from the text data, and facial expressions from the image data.

[1352] Program and Processing Overview

[1353] Data collection and analysis

[1354] The device captures biometric data and transmits it in real time to a server, which receives it and stores it in a database. The emotion engine analyzes the voice, text, and image data to assess the user's emotional state. The server then uses an AI model to analyze emotions and stress levels.

[1355] Providing mental health support

[1356] The server generates a mental health support plan appropriate for the user based on the analysis results. The plan is then sent to the device, which notifies the user. The user then follows the instructions and implements the plan, and their progress is recorded.

[1357] For example, if a device sends heart rate data to a server, and the server analyzes the data and recognizes a high stress state, it will send a notification suggesting a five-minute guided meditation to the user, who can then begin the meditation and track their progress.

[1358] Integrated legal support

[1359] When a user sends a legal question to the server via their device, the server uses an AI model to generate initial legal advice and, if necessary, provides the option to book a legal consultation. The generated legal advice and booking information are sent to the device, where the user can view and interact with it.

[1360] Examples and prompts

[1361] Specific examples include the following:

[1362] Device: The smartwatch measures the heart rate and sends it to the server.

[1363] Server: Analyzes the received heart rate data and determines that the user is in a state of stress.

[1364] Server: Sends a message to the user's device saying, "Please start the 5-minute guided meditation."

[1365] User: Receive a notification from the device and play a guided meditation video.

[1366] (Example of a prompt)

[1367] "Receive and analyze the user's heart rate data, and generate a program that suggests appropriate guided meditations if stress levels are detected."

[1368] The above is a natural language description of the program process of the system of the present invention, which allows users to manage their emotions and stress levels in real time and receive personalized mental health care and legal support.

[1369] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1370] Step 1: Data collection

[1371] Input: Biometric data from sensors (heart rate, body temperature, keystroke rhythm, etc.)

[1372] Device: A smartwatch or smartphone collects the user's biometric data through sensors, which are then sent to a server in real time.

[1373] Output: The collected biometric data is sent to the server.

[1374] Specifically, the smartwatch measures the user's heart rate every second, sends the data to the smartphone via Bluetooth, and then the smartphone sends it to a server via Wi-Fi.

[1375] Step 2: Receiving and storing data

[1376] Input: Biometric data sent from the device

[1377] Server: Receives biometric data sent from the device in real time and stores it in a database.

[1378] Output: Biometric data stored in a database

[1379] Specifically, the server receives the data through a dedicated API and stores it in a database in the form of "user ID, measurement time, heart rate, body temperature, etc."

[1380] Step 3: Data analysis

[1381] Input: Biometric data stored in a database

[1382] Server: The stored data is fed into an AI model to assess the user's emotions and stress levels. The emotion engine also analyzes voice, text, and image data.

[1383] Output: Analysis results (e.g. high stress, fatigue, relaxed)

[1384] Specifically, the server processes a batch of data on a weekly basis and feeds it into an AI model to estimate emotions and stress levels. For example, an elevated heart rate and a drop in voice tone might be assessed as "high stress."

[1385] Step 4: Generate a Mental Health Support Plan

[1386] Input: Analysis results

[1387] Server: Based on the analysis results, automatically generate a mental health support plan appropriate for the user.

[1388] Output: Generated mental health support plan (e.g., guided meditation, relaxation exercises)

[1389] Specifically, if the server detects that the user is in a state of high stress based on the analysis results, it generates a support plan suggesting a "5-minute meditation guide."

[1390] Step 5: Submit your support plan

[1391] Input: Generated Mental Health Support Plan

[1392] Server: Sends the generated support plan to the device.

[1393] Output: Notification message sent to the user's device (e.g., notification that a guided meditation has started)

[1394] Specifically, the server uses the SMTP protocol to send a notification to the user's smartphone saying, "Please start the meditation guide."

[1395] Step 6: Support Execution Notification

[1396] Input: Support plan notification

[1397] Device: Receives notifications and displays them to the user.

[1398] Output: A notification message that will be displayed on the user's terminal.

[1399] Specifically, it uses the smartphone's notification function to display a pop-up message on the user's screen saying, "Please start a 5-minute guided meditation."

[1400] Step 7: Performing and recording support

[1401] Input: Support plan execution instructions

[1402] User: Follows notifications from the device and provides mental health support. The device records the execution status.

[1403] Output: Performance data (e.g., meditation time, exercise completion status)

[1404] Specifically, the user follows the notification to play the guided meditation video, while the smartphone records the playback time. The smartphone also records the progress of the exercise by pressing the completion button.

[1405] Step 8: Analyze support progress

[1406] Input: Recorded execution status data

[1407] Server: Receives and analyzes progress data and uses it to improve the next mental health support plan.

[1408] Output: Improved support plan

[1409] Specifically, the server retrains the AI ​​model based on the performance data and generates personalized feedback such as "suggesting a 10-minute meditation session next time."

[1410] Step 9: Legal Questions Reception and Analysis

[1411] Input: Legal Question from User

[1412] User: Type and submit legal questions via the device.

[1413] Server: Receives the question and uses AI models to generate preliminary legal advice.

[1414] Output: Generated legal advice

[1415] Specifically, the user types "Please tell me about property division in divorce" into their device, which is then sent to the server, which uses an AI model to respond with the appropriate legal information.

[1416] Step 10: Submit legal advice and book a consultation

[1417] Input: Generated legal advice and counseling appointment information

[1418] Server: Sends legal advice and counseling appointment information to the terminal.

[1419] Device: Displays legal advice to the user and offers the option to book a consultation if necessary.

[1420] Output: Legal advice and counseling booking options displayed to the user

[1421] Specifically, the device will display a message saying, "Details on how to divide assets are provided. Click 'Book' to schedule a consultation."

[1422] (Application example 2)

[1423] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1424] In modern society, mental health has become a significant issue due to increased stress and anxiety. However, conventional mental health care systems have difficulty providing accurate support adapted to each user's individual emotional state and stress level. Furthermore, there has been a lack of efficient means to provide continuous mental health support in remote environments or to deliver content appropriate for each user. This has led to problems such as users not receiving appropriate support, limiting the effectiveness of mental health care.

[1425] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing the user's emotions and stress level, means for providing customized mental health support to the user based on the analysis results, means for notifying the user of the customized mental health support, means for delivering appropriate content based on the analysis results, means for recording content consumption status and generating feedback data, and means for improving future mental health support based on the feedback data. This makes it possible to provide highly accurate mental health care and appropriate content according to the user's individual emotional state and stress level.

[1426] "Information processing device" is a general term for hardware and software for receiving, storing, and analyzing data.

[1427] A "sensing device" is a device that collects a user's biometric and environmental data in real time, and is a general term for smartwatches, smartphones, etc.

[1428] "Emotion and stress level analysis means" is a general term for algorithms and technologies for analyzing collected voice data, text data, and image data to estimate a user's emotional state and stress level.

[1429] "Means for providing customized mental health support" is a general term for technologies and processes that automatically generate and provide mental health care adapted to a user's specific emotions and stress state based on analysis results.

[1430] "Mental health support notification means" is a general term for technologies and devices that notify users of customized mental health support plans and encourage them to take action.

[1431] "Content delivery method" is a general term for the technologies and processes that deliver digital content such as music, videos, and podcasts that are appropriate for a user's emotions and stress levels to a user's device via a network.

[1432] "Means for recording consumption status" is a general term for technologies that record how users consume provided content (for example, playback time and number of times) and store this information in a database.

[1433] "Feedback data generation means" is a general term for the processes and technologies that generate new analytical data based on recorded content consumption status and user feedback, and use it to improve future mental health support.

[1434] In this invention, we combine an information processing device, a sensing device, and an emotion engine to build a system that manages a user's emotions and stress level and provides customized mental health support. Each component of the system and its function are described in detail below.

[1435] System Configuration

[1436] Information processing device

[1437] The server is responsible for data analysis and information management for the entire system. It also functions as an "information processing device," analyzing data collected from the sensing devices and emotion engine to provide mental health support tailored to the user.

[1438] Sensing Device

[1439] The devices include smartwatches and smartphones. These devices act as "sensing devices" that continuously collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm. This data is then transmitted to a server in real time.

[1440] Emotion Engine

[1441] The emotion engine, which functions as an "emotion and stress level analyzer," analyzes voice, text, and image data to identify the user's emotional state. Specifically, it analyzes the tone and speed of voice from the voice data, selected words from the text data, and facial expressions from the image data.

[1442] Programs and their processing

[1443] The server receives biometric data from the sensing device and analysis results from the emotion engine, stores them in a database, analyzes the stored data to determine the user's emotions and stress level, and then generates a customized mental health support plan based on the analysis results and notifies the user.

[1444] Customized Mental Health Support

[1445] As a "means of providing customized mental health support," the server provides users with appropriate mental health support based on the analysis results. This support can include guided meditations, relaxation music, podcasts, etc. For example, if stress levels are high, relaxation music or guided meditations will be provided.

[1446] Content distribution and feedback

[1447] The server will then use the "content delivery means" to deliver content appropriate to the user based on the analysis results. The device will also record consumption status as a "consumption status recording means" and send this to the server. This will allow the "feedback data generation means" to analyze the user's progress and effectiveness, allowing for further customization of support from the next time onwards.

[1448] Hardware and software used

[1449] Hardware:

[1450] Smartphones, smartwatches (sensing devices)

[1451] Server (information processing device)

[1452] software:

[1453] TensorFlow, Keras (emotion engine, AI model)

[1454] OpenCV (image analysis)

[1455] Librosa (voice analysis)

[1456] Examples and how to use generative AI models

[1457] For example, if a user is feeling stressed, they can use prompts like the following to feed data into a generative AI model:

[1458] Example prompt sentence:

[1459] The user's biometric data indicates a heart rate of 90 and a body temperature of 37.5°C. Voice data analysis indicates the voice tone is unstable and fast. Image data analysis indicates the facial expression indicates sadness. Based on this data, diagnose the user's current emotional state and suggest appropriate mental health support content.

[1460] This system allows users to manage their emotions and stress levels in real time and receive appropriate mental health care, which is expected to result in improved mental health and a better quality of life.

[1461] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1462] Step 1:

[1463] The device collects the user's biometric data. It uses a smartwatch or smartphone to measure heart rate, body temperature, and keystroke rhythm in real time and transmits the data to a server. The input is various biometric data, and the output is the biometric data sent to the server.

[1464] Step 2:

[1465] The server uses an emotion engine to analyze the user's voice data, text data, and image data. The voice data sent from the device is used to extract MFCCs using Librosa, and the image data is used to analyze facial expressions using OpenCV. The text data is analyzed using natural language processing technology. The input is voice, text, and image data, and the output is the analysis of the user's emotional state and stress level.

[1466] Step 3:

[1467] The server integrates data from the sensing device and the emotion engine, and uses an AI model (using TensorFlow and Keras) to determine the user's current emotional state and stress level. The input is biometric data and the analysis results of the emotion engine, and the output is the determined emotional state and stress level.

[1468] Step 4:

[1469] The server generates a customized mental health support plan. Based on the determined emotional state and stress level, it selects appropriate content from relaxation music, guided meditations, podcasts, etc. The input is the determined emotional state and stress level, and the output is a customized mental health support plan.

[1470] Step 5:

[1471] The server sends the customized mental health support plan to the terminal, and the terminal displays specific implementation methods (video links and text instructions) to the user based on the received notification. The input is the customized mental health support plan, and the output is the notification to the user.

[1472] Step 6:

[1473] The user performs mental health support based on notifications from the device. For example, the user performs specific actions such as playing relaxation music or watching a guided meditation video. The input is the notification to the user, and the output is the execution of mental health support.

[1474] Step 7:

[1475] The device records the user's mental health support activities, collecting data on the type and time of activities performed and sending it to the server. The input is the mental health support activity data, and the output is the recorded data sent to the server.

[1476] Step 8:

[1477] The server analyzes the feedback data and uses it to improve future mental health support plans. It analyzes user reactions and effects and adjusts the AI ​​model. The input is the recorded data and reaction data, and the output is an updated mental health support plan.

[1478] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1479] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1480] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1481] [Fourth embodiment]

[1482] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1483] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1484] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1485] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1486] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1487] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1488] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1489] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1490] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1491] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1492] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1493] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1494] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1495] Introduction

[1496] The present invention relates to a method for managing a user's emotions and stress levels and providing customized mental health support using information processing devices, sensing devices, data analysis and notification systems.

[1497] System Configuration

[1498] Information processing device

[1499] The server is responsible for the system's primary data analysis and information management. It receives data from the sensing devices, performs calculations for analysis, and sends notifications regarding mental health support to users.

[1500] Sensing Device

[1501] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[1502] Program and Processing Overview

[1503] Data collection and analysis

[1504] 1. Data Collection

[1505] Device: A smartwatch or smartphone collects the user's biometric data (heart rate, body temperature, etc.), which is then sent to a server in real time.

[1506] 2. Data Reception and Analysis

[1507] Server: Receives data sent from the device and analyzes it using an AI model. As a result of the analysis, the user's emotional state (e.g., stress, fatigue, anxiety) and stress level are determined.

[1508] Providing mental health support

[1509] 1. Generate customized support

[1510] Server: Generates a mental health support plan tailored to the user based on the data analysis results. For example, if stress levels are high, it provides a meditation guide.

[1511] 2. Support Notifications

[1512] Device: Notifies the user of the generated mental health support plan and provides specific instructions on how to implement it (e.g., starting a guided meditation).

[1513] Integrated legal support

[1514] 1. Receiving and analyzing legal questions

[1515] User: If you have any legal questions or concerns, you can send them to the server from your device.

[1516] Server: Receives the question and generates preliminary legal advice using AI.

[1517] 2. Providing counseling services

[1518] Server: Provides an option to book legal consultations if needed, allowing users to speak to a legal professional directly.

[1519] Specific examples

[1520] Specific examples of mental health care

[1521] 1. Data Collection

[1522] Device: The smartwatch continuously measures the user's heart rate and sends the data to the server every two minutes.

[1523] 2. Data analysis and customization support

[1524] Server: After analyzing the heart rate data, the server determines that the user's stress level is "high." Based on this, the server generates a support plan that suggests a five-minute guided meditation.

[1525] 3. Notice and Enforcement

[1526] Device: Notifies the user of the guided meditation video and instructs them to play it.

[1527] User: Follow the guided meditation for 5 minutes.

[1528] Examples of legal support

[1529] 1. Accepting questions

[1530] User: Submit legal questions regarding ongoing litigation proceedings from the device.

[1531] 2. Legal Answers and Counseling Appointments

[1532] Server: Analyzes the question and generates relevant legal advice. It also provides the user with a link to schedule a legal consultation.

[1533] Device: Informs users of legal advice and options for booking counseling appointments.

[1534] Users: Book a consultation and speak to a specialist if necessary.

[1535] This allows users to receive real-time assistance in managing emotions and stress, reducing the mental burden during litigation.

[1536] The processing flow will be explained below.

[1537] Step 1:

[1538] Data collection

[1539] Device: A smartwatch or smartphone collects biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmits this data to a server at regular intervals.

[1540] Step 2:

[1541] Data reception

[1542] Server: Receives data sent from the device. The received data is stored in a database and prepared for analysis.

[1543] Step 3:

[1544] Data analysis

[1545] Server: Uses AI models to analyze stored biometric data, assessing emotions and stress levels to determine the user's emotional state (e.g., stress, fatigue, anxiety).

[1546] Step 4:

[1547] Generate customization support

[1548] Server: Based on the analysis results, the server automatically generates a mental health support plan appropriate for the user's emotional state. For example, it suggests a guided meditation if the user's stress level is high.

[1549] Step 5:

[1550] Submit a Support Plan

[1551] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[1552] Step 6:

[1553] Support Plan Notifications

[1554] Device: Notify the user of the received support plan and show them how to implement it. For example, a notification saying "Start a 5-minute guided meditation" will be displayed on the device screen.

[1555] Step 7:

[1556] Support Execution

[1557] User: Follow the notifications from the device to play a guided meditation video or perform deep breathing exercises, while the device continues to record their progress.

[1558] Step 8:

[1559] Recording progress

[1560] Device: Records the status of support execution (for example, meditation time and exercise completion status) and sends it to the server.

[1561] Step 9:

[1562] Progress data analysis

[1563] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user responses and effectiveness, more effective support can be provided.

[1564] Step 10:

[1565] Providing legal support

[1566] User: If there is a legal consultation or question, the user makes an inquiry to the server via the terminal.

[1567] Server: Analyzes the user's question and uses AI to automatically generate initial legal advice. If necessary, it provides a link to book a legal consultation.

[1568] Step 11:

[1569] Sending legal advice

[1570] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[1571] Device: Displays legal advice to the user and notifies them when counseling appointments are available.

[1572] Step 12:

[1573] Counseling appointment

[1574] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[1575] This is the detailed program flow of LegalEase MindGuard. This system allows users to receive appropriate mental health support and legal advice in real time, significantly reducing the mental burden during litigation.

[1576] Example 1

[1577] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1578] In modern society, there is a need to effectively manage users' emotions and stress levels and provide appropriate mental health support. However, existing systems do not properly collect and analyze biometric data, making it difficult to provide users with prompt, customized support. Furthermore, there are no systems that can respond to legal questions or provide counseling services. This makes it difficult for users to receive mental and legal support at the appropriate time.

[1579] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1580] In this invention, the server includes a data analysis means, a determination means, a mental health support plan generation means, a notification means, a legal question analysis means, and a legal counseling appointment provision means. This makes it possible to analyze a user's biometric data in real time and provide a customized mental health support plan. It also makes it possible to quickly provide comprehensive support to users through initial responses to legal questions and appointments for counseling services.

[1581] An "information processing device" is a computer device that receives, analyzes, and manages data.

[1582] "Sensing devices" are devices that collect biometric data from users, including smartwatches and smartphones.

[1583] "Biometric data" refers to physical data such as a user's heart rate, body temperature, and keystroke rhythm.

[1584] "Data analysis means" refers to the means for analyzing collected biometric data, utilizing technologies such as AI models to extract meaningful information from the data.

[1585] The "determination means" is a means for determining the user's emotional state and stress level based on the analyzed data.

[1586] The "mental health support plan generation means" is a means for generating a mental health support plan tailored to the user based on the assessment results.

[1587] "Notification means" refers to a means for notifying a user of the generated mental health support plan.

[1588] "Legal question analysis means" means for receiving a legal question from a user and generating initial legal advice in response thereto.

[1589] A "Legal Counseling Appointment Offering" is a means for providing Users with the option to book legal counseling services.

[1590] The present invention relates to a system that uses information processing devices, sensing devices, data analysis means, and notification systems to manage a user's emotions and stress levels and provide customized mental health support and legal support.

[1591] System Configuration

[1592] Information processing device

[1593] The server is responsible for the system's primary data analysis and information management. Specifically, it receives data from the sensing devices and performs calculations for analysis. The server also sends notifications to users regarding mental health support. The server's processing uses AI models such as TensorFlow.

[1594] Sensing Device

[1595] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server in real time. With the user's consent, the devices monitor the data continuously.

[1596] Data Analysis Methods

[1597] The server receives the biometric data sent from the device and stores it in a database. The stored data is analyzed using AI models such as TensorFlow. As a result of the analysis, the user's emotional state (stress, fatigue, anxiety) and stress level are identified.

[1598] Mental Health Support Plan Generation Tool

[1599] Based on the analysis results, the server generates a personalized mental health support plan for each user, suggesting guided meditations and relaxing music for users with high stress levels, for example.

[1600] Notification means

[1601] The device will then notify the user of the customized mental health support plan sent from the server, which will be displayed as a push notification or in-app notification, prompting the user to take specific action.

[1602] legal question analysis tool

[1603] Users submit legal questions from their devices, which are then received by a server that uses natural language processing models such as GPT-3 to generate initial legal advice.

[1604] Legal counseling appointment delivery methods

[1605] Depending on the legal question, the server generates and notifies the user of a legal counseling appointment option, which includes a link to meet with an expert.

[1606] Specific examples

[1607] Specific examples of mental health care

[1608] 1. Data Collection

[1609] Device: The smartwatch continuously measures the user's heart rate and sends the data to the server every 30 seconds.

[1610] 2. Data analysis and generation of customized support

[1611] Server: Analyzes heart rate data using an AI model, and if stress levels are determined to be high, generates a support plan suggesting a five-minute guided meditation.

[1612] 3. Notification

[1613] On device: The user is notified of the support plan and is shown the message, "Your stress level seems high. Try a 5-minute guided meditation." The user taps the notification to begin the guided meditation.

[1614] Examples of legal support

[1615] 1. Accepting questions

[1616] User: Sends questions about the lawsuit from their smartphone to the server.

[1617] 2. Legal Answers and Counseling Appointments

[1618] Server: Analyzes the question using GPT-3 and generates an initial advice such as "When collecting evidence during litigation, it is important to verify its reliability and legality." It also sends a notification with a link to schedule a legal consultation.

[1619] 3. Counseling appointment

[1620] Users: Receive notifications and, if necessary, book counseling appointments and meetings with specialists.

[1621] Example prompts for generative AI models

[1622] "Please explain the specific process flow for collecting heart rate data in real time while the user is wearing the smartwatch, analyzing stress levels using TensorFlow, and providing customized mental health support based on the results. Also, please include a process flow for using GPT-3 to provide initial response to legal questions."

[1623] As can be seen, this invention can improve a user's overall well-being by using their biometric data to manage their emotions and stress levels in real time and provide mental health and legal support.

[1624] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1625] Step 1:

[1626] Data collection

[1627] Device: Smartwatches and smartphones continuously collect users' biometric data (heart rate, body temperature, keystroke rhythm).

[1628] Input: User biometric data. For example, a smartwatch measures heart rate and temperature every 30 seconds, and a smartphone captures keystroke rhythm.

[1629] Output: The collected biometric data is temporarily stored on the device. The smartwatch transmits the data via Bluetooth to the smartphone, which prepares it to be sent to the server via Wi-Fi or mobile data.

[1630] Step 2:

[1631] Data reception

[1632] Server: Receives biometric data sent from the terminal.

[1633] Input: Biometric data sent from the device.

[1634] Output: The received biometric data is stored in the server's database. Specifically, the server's receiving module captures the data and stores it in the database.

[1635] Step 3:

[1636] Data analysis

[1637] Server: Analyzes the received biometric data using an AI model (such as TensorFlow).

[1638] Input: Biometric data stored on the server.

[1639] Processing: The AI ​​model analyzes the data and determines the user's emotional state and stress level.

[1640] Output: The analysis results in the user's emotional state (e.g., stress level is high, medium, low, etc.) and a stress index.

[1641] Step 4:

[1642] Customized Support Plan Generation

[1643] Server: Generates a personalized mental health support plan for each user based on the results of data analysis.

[1644] Input: Analysis results (user's emotional state and stress level).

[1645] Processing: The server creates a support plan based on the analysis results. For example, it suggests a five-minute guided meditation for a user with a high stress level.

[1646] Output: A customized support plan is generated, which may include guided meditation, relaxation exercises, or psychological counseling sessions.

[1647] Step 5:

[1648] Support Notifications

[1649] On the device: Notifies the user of the support plan sent from the server.

[1650] Input: The customized support plan sent by the server.

[1651] Action: Your device will display your support plan as a push or in-app notification.

[1652] Output: The user is notified with a message such as "Your stress level seems high. Try a 5-minute guided meditation." When the user taps the notification, a guided meditation app or similar will launch.

[1653] Step 6:

[1654] Accepting legal questions

[1655] Users: If they have legal questions or concerns, they can send them to the server using their smartphone or PC.

[1656] Input: Legal question submitted by user.

[1657] Output: The question is sent to the server. Specifically, this includes the user entering "I would like to ask about evidence collection in litigation" into the app's question form and submitting it.

[1658] Step 7:

[1659] Legal Advice Generation and Notification

[1660] Server: Generates initial legal advice in response to legal questions received from users using an AI model that performs natural language processing (e.g., GPT-3).

[1661] Input: Legal question received from user.

[1662] Processing: The AI ​​model analyzes the question and generates legal advice such as, "When collecting evidence during litigation, it is important to verify the reliability and legality of the evidence."

[1663] Output: The generated legal advice is communicated to the user.

[1664] Step 8:

[1665] Legal counseling appointments available

[1666] Server: Generates and notifies users of legal advice, along with options to book legal counseling.

[1667] Input: Description of legal issue and generated legal advice.

[1668] Processing: The server generates a link that provides counseling appointment options and notifies the user.

[1669] Output: The notification will contain a link such as "Schedule a legal consultation here" that the user can click to complete the booking process.

[1670] In this way, the overall processing flow of the system is to collect the user's biometric data, perform analysis based on that data, and provide customized mental health support and legal support based on the analysis results.

[1671] (Application example 1)

[1672] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1673] Until now, there have been no adequate methods established for managing the mental health of workers in industrial environments. As a result, workers' accumulated stress and fatigue have had a negative impact on productivity and safety, ultimately causing a decline in the quality of the overall working environment. There is a need for a system that can solve these problems, monitor workers' mental health status in real time, and provide appropriate support.

[1674] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1675] In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing a user's emotions and stress level, means for providing customized mental health support to the user based on the analysis results, means for notifying the user of the customized mental health support, and means for collecting biometric data of workers in an industrial environment and suggesting relaxation support and breaks based on the analysis results. This makes it possible to monitor the mental health status of workers in real time and suggest support and breaks that are appropriate for each individual, thereby improving the working environment and increasing productivity.

[1676] An "information processing device" is a device that analyzes collected data and provides various types of support and notifications to users.

[1677] A "sensing device" is a device used to collect a user's biometric data, and examples include smartwatches and smartphones.

[1678] The "means for receiving data and analyzing the user's emotions and stress level" refers to a means for receiving data transmitted from a sensing device and analyzing the data to determine the user's emotional state and level of stress.

[1679] "Means for providing customized mental health support" refers to means for selecting and providing a mental health support method suitable for the user based on the analysis results.

[1680] "Means for notifying users of customized mental health support" refers to means for notifying users of the generated support plan, thereby enabling users to receive actual support.

[1681] An "industrial environment" refers to an industrial site or workplace where manufacturing or processing takes place, and is an environment where managing the mental health of workers is particularly important.

[1682] "Means for collecting workers' biometric data and suggesting relaxation support and rest based on the analysis results" refers to means for collecting biometric data such as heart rate and body temperature of workers in industrial environments and suggesting appropriate relaxation methods and rest based on the results of analyzing this data.

[1683] "Guided Meditation" means a means of providing users with guided meditation sessions for the purposes of stress reduction and relaxation.

[1684] "Psychological Counseling Session" refers to a counseling session to provide psychological support to a User.

[1685] "Relaxation exercise" is a method of providing users with physical activity or exercise aimed at relieving muscle tension or mental refreshment.

[1686] "Means for providing access to legal advice and counseling services" means means for accepting legal questions from users and providing appropriate advice and, if necessary, counseling appointments with professionals.

[1687] Overall structure

[1688] The present invention is a system that uses information processing devices, sensing devices, data analysis and notification systems to manage a user's emotions and stress levels and provide customized mental health support.

[1689] Hardware Configuration

[1690] Server: An important device that analyzes data and manages information. Commercial high-performance servers or cloud servers are often used.

[1691] Sensing devices: Specifically, smartwatches and smartphones. These devices collect biometric data such as heart rate and body temperature from users and transmit it to a server.

[1692] Devices specialized for industrial environments: Devices designed to collect biometric data from workers in industrial environments in real time, enabling highly accurate data analysis.

[1693] Data collection and analysis

[1694] Data collection: Sensing devices collect biometric data such as the user's heart rate and body temperature. This data is sent to a server in real time. In industrial environments, workers wear smartwatches or head-mounted displays to collect this data as needed.

[1695] Data analysis: The server receives the collected biometric data and analyzes it using an AI model. This determines the user's emotional state and stress level. For example, if the heart rate or body temperature exceeds a certain threshold, the stress level is classified into three levels: "low," "medium," or "high."

[1696] Providing mental health support

[1697] Generate customized support: The server generates a mental health support plan tailored to the user based on the analysis results. For example, if the stress level is determined to be high, it generates relaxation support that suggests a five-minute break.

[1698] Support notification: The generated mental health support plan will be sent to the user's smartwatch or smartphone, and the user can follow the instructions to receive actual support.

[1699] Specific examples

[1700] Example of data collection: A smartwatch continuously measures the user's heart rate and transmits the data to a server every two minutes, enabling real-time data monitoring.

[1701] Example of data analysis: If the server performs an analysis and User A's heart rate exceeds 90 bpm and his body temperature is 37.2 degrees, it will be determined that his "stress level is high."

[1702] Example of support notification: Based on the analysis results, the server generates a message suggesting a break and notifies the user through the smartwatch, such as "Your stress level is high. Please take a 5-minute break."

[1703] Prompt Sentence Examples

[1704] For example, you might input a prompt like this for a generative AI model:

[1705] "If the heart rate is above 90, determine that the worker's stress level is high and generate a notification message in the application suggesting a break."

[1706] This makes it possible to monitor the user's mental health status in real time and provide appropriate support immediately.

[1707] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1708] Step 1:

[1709] Data collection:

[1710] The device, a smartwatch or smartphone, continuously measures the user's biometric data, such as heart rate and body temperature. The measured data is sent to the server in real time. The input at this stage is the user's heart rate and body temperature data, which are sent to the server in an appropriate format. The output is the completion of sending the biometric data to the server.

[1711] Step 2:

[1712] Data reception:

[1713] The server receives the biometric data sent from the terminal. The received data is stored in a database in the server. The input at this stage is the biometric data sent from the terminal. The output is the biometric data stored in the server.

[1714] Step 3:

[1715] Data Analysis:

[1716] The server analyzes the collected biometric data using an AI model. Here, the user's emotional state and stress level are determined based on heart rate and body temperature data. Specifically, a heart rate above 90 or a body temperature above 37.0 degrees is determined to be a "high stress state." The input at this stage is the biometric data stored on the server, and the output is the emotional state and stress level as the analytical results.

[1717] Step 4:

[1718] Customized support generation:

[1719] Based on the analysis results, the server generates an optimal mental health support plan for the user. In this case, if the stress level is determined to be high, it will generate suggestions such as "5 minutes of meditation" or "taking a break." The input is the emotional state and stress level resulting from the analysis, and the output is the generated mental health support plan.

[1720] Step 5:

[1721] Support Notice:

[1722] The generated mental health support plan is notified to the device. A message such as "Please take a break" is displayed on the user's smartwatch or smartphone. The input at this stage is the generated mental health support plan, and the output is the message to notify the user.

[1723] Step 6:

[1724] User Response:

[1725] The user follows the mental health support plan, specifically by taking prescribed relaxation and rest breaks as per the notification. At this stage, the user's biometric data is reset again and the next data collection cycle begins.

[1726] This allows users' mental health status to be monitored in real time, and measures such as relaxation and rest can be provided at appropriate times.

[1727] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1728] Introduction

[1729] The present invention relates to a system that uses an information processing device, a sensing device, and an emotion engine to manage a user's emotions and stress levels and provide customized mental health support. In particular, the present invention incorporates an emotion engine that analyzes voice data, text data, and image data to recognize a user's emotions.

[1730] System Configuration

[1731] Information processing device

[1732] The server is responsible for data analysis and information management for the entire system. It receives and analyzes data from the sensing devices and emotion engine, and sends notifications about mental health support to users.

[1733] Sensing Device

[1734] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[1735] Emotion Engine

[1736] The emotion engine recognizes the user's emotions by analyzing voice data, text data, and image data. For example, it analyzes the tone and speed of the voice from the voice data, the choice of words from the text data, and facial expressions from the image data.

[1737] Program and Processing Overview

[1738] Data collection and analysis

[1739] 1. Data Collection

[1740] Device: A smartwatch or smartphone collects the user's biometric data, which is then sent to a server in real time.

[1741] Emotion engine: Receives voice, text, and image data sent from the device and analyzes the user's emotional state.

[1742] 2. Data Reception and Analysis

[1743] Server: Receives data sent from the device and emotion engine and stores it in a database.

[1744] Server: Uses AI models to analyze the stored data. The AI ​​models evaluate emotions and stress levels to determine the user's emotional state (e.g., stress, fatigue, anxiety).

[1745] Providing mental health support

[1746] 1. Generate customization support

[1747] Server: Based on the results of data analysis and the emotion engine's analysis, the server automatically generates a mental health support plan appropriate for the user's emotional state. For example, if the stress level is high, the server suggests a guided meditation.

[1748] 2. Submit your support plan

[1749] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[1750] 3. Support Plan Notification

[1751] Device: Notify the user of the support plan received and provide instructions on how to implement it. For example, display a notification saying, "Start a 5-minute guided meditation."

[1752] 4. Support Execution

[1753] User: Follow the notifications from your device to play a guided meditation video or do a deep breathing exercise, while your device records your progress.

[1754] 5. Track your progress

[1755] Device: Records the status of support execution (e.g., meditation time and exercise completion status) and sends it to the server.

[1756] 6. Analysis of progress data

[1757] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user responses and effectiveness, more effective support can be provided.

[1758] Integrated legal support

[1759] 1. Receiving and analyzing legal questions

[1760] User: Sends legal questions or concerns to the server via their device.

[1761] Server: Receives the question and uses AI models to generate preliminary legal advice. In some cases, it offers the option to schedule a legal consultation.

[1762] 2. Sending legal advice

[1763] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[1764] Device: Providing legal advice and the option to book a consultation appointment if needed.

[1765] 3. Make a counseling appointment

[1766] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[1767] The above is a specific implementation of LegalEase MindGuard, which combines an emotion engine, allowing users to manage their emotions and stress levels in real time and receive appropriate mental health care and legal support.

[1768] The processing flow will be explained below.

[1769] Step 1:

[1770] Data collection

[1771] Device: A smartwatch or smartphone collects the user's biometric data (heart rate, body temperature, keystroke rhythm, etc.), and also acquires audio data through the device's microphone and image data through the camera.

[1772] Terminal: Sends collected data to the server in real time.

[1773] Step 2:

[1774] Data reception

[1775] Server: Receives biometric data, voice data, and image data sent from the terminal and stores them in a database.

[1776] Step 3:

[1777] Analysis of audio and text data

[1778] Emotion engine: Analyzes audio data to analyze the user's tone, speed, and pitch. It also analyzes text data obtained from the device to evaluate word choice and context.

[1779] Server: Receives the results of the emotion engine and stores them in a database.

[1780] Step 4:

[1781] Image data analysis

[1782] Emotion engine: Using image recognition technology, the system analyzes the user's facial expressions, such as facial contours, eye opening, and mouth curve, to determine emotions.

[1783] Server: Receives the results of the emotion engine and stores them in a database.

[1784] Step 5:

[1785] Comprehensive Data Analysis

[1786] Server: An AI model is used to comprehensively analyze all collected data (biometric data, voice data, text data, image data). The AI ​​model integrates multiple data sources to assess the user's emotional state (e.g., stress, fatigue, anxiety) and stress level.

[1787] Step 6:

[1788] Generate customization support

[1789] Server: Based on the analysis results, automatically generate a mental health support plan (e.g., meditation guide, psychological counseling session, relaxation exercise) appropriate for the user.

[1790] Step 7:

[1791] Submit a Support Plan

[1792] Server: Sends the generated mental health support plan to the device. The support plan includes specific implementation methods (e.g., links to guided meditation videos and text instructions).

[1793] Step 8:

[1794] Support Plan Notifications

[1795] Device: Notify the user of the received support plan and provide instructions on how to implement it. For example, display a notification on the device screen saying, "Start a 5-minute guided meditation."

[1796] Step 9:

[1797] Support Execution

[1798] User: Follow the notifications from your device to play a guided meditation video or do a deep breathing exercise, while your device records your progress.

[1799] Step 10:

[1800] Recording progress

[1801] Device: Records the status of support execution (e.g., meditation time and exercise completion status) and sends it to the server.

[1802] Step 11:

[1803] Progress data analysis

[1804] Server: Analyzes the progress data sent and uses it to improve future mental health support plans. By analyzing user responses and effectiveness, more effective support can be provided.

[1805] Step 12:

[1806] Providing legal support

[1807] User: If you have any legal questions or concerns, send them to the server via your device.

[1808] Server: Receives the question and uses AI models to generate initial legal advice. If necessary, it provides the option to schedule a legal consultation.

[1809] Step 13:

[1810] Sending legal advice

[1811] Server: Sends the generated legal advice and counseling appointment information to the terminal.

[1812] Device: Providing legal advice and the option to book a consultation appointment if needed.

[1813] Step 14:

[1814] Counseling appointment

[1815] User: Uses the device to make an appointment for legal counseling. The appointment information is sent to the specialist via the server.

[1816] This is the detailed program flow of LegalEase MindGuard, which combines an emotion engine. This system allows users to manage their emotions and stress levels in real time and receive appropriate mental health care and legal support.

[1817] Example 2

[1818] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1819] The current mental health care system struggles to properly assess users' emotions and stress levels and provide customized support. It also lacks real-time feedback, ongoing support, and legal advice integration, preventing users from receiving the comprehensive support they truly need.

[1820] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1821] In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing the user's emotions and stress level, means for notifying the user of a mental health support plan generated based on the analysis results and recording the implementation status, means for analyzing the recorded implementation status and using it to improve the future mental health support plan, and means for receiving legal questions from the user, generating initial legal advice, and providing an option to reserve legal counseling as needed. This enables the user to manage their emotions and stress level in real time and receive personalized mental health care and legal support.

[1822] An "information processing device" is a device such as a computer or server that collects, analyzes, and stores data.

[1823] A "sensing device" is a device that acquires biometric and environmental data from a user in real time and transmits the data to an information processing device. Examples include smartwatches and smartphones.

[1824] "Means for analyzing emotions and stress levels" refers to algorithms or AI models that assess a user's emotional state and stress levels based on the collected data.

[1825] The "Mental Health Support Plan" is a personalized mental health care plan provided to users based on the analysis results, which may include, for example, guided meditation and relaxation exercises.

[1826] A "means for recording implementation status" is a device or application that allows a user to record the progress of the user when actually implementing the mental health support plan.

[1827] "Means for receiving legal questions and generating initial legal advice" refers to an algorithm or AI model that receives legal questions or concerns from users, analyzes them, and provides initial legal advice.

[1828] A "means for providing legal counseling appointment options" is a system that allows a user to make an appointment for legal counseling if they wish to receive additional assistance.

[1829] Introduction

[1830] This invention relates to a system that uses an information processing device, a sensing device, and an emotion engine to manage a user's emotions and stress level and provide customized mental health support. In particular, this invention incorporates an emotion engine that analyzes voice data, text data, and image data to recognize the user's emotions.

[1831] System Configuration

[1832] Information processing device

[1833] The server is responsible for data analysis and information management for the entire system. It receives and analyzes data from the sensing devices and emotion engine, and sends notifications about mental health support to users.

[1834] Sensing Device

[1835] The devices include smartwatches and smartphones. These devices collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm, and transmit it to a server. With the user's consent, the devices continuously monitor the data.

[1836] Emotion Engine

[1837] The emotion engine recognizes the user's emotions by analyzing voice data, text data, and image data. For example, it analyzes the tone and speed of the voice from the voice data, the choice of words from the text data, and facial expressions from the image data.

[1838] Program and Processing Overview

[1839] Data collection and analysis

[1840] The device captures biometric data and transmits it in real time to a server, which receives it and stores it in a database. The emotion engine analyzes the voice, text, and image data to assess the user's emotional state. The server then uses an AI model to analyze emotions and stress levels.

[1841] Providing mental health support

[1842] The server generates a mental health support plan appropriate for the user based on the analysis results. The plan is then sent to the device, which notifies the user. The user then follows the instructions and implements the plan, and their progress is recorded.

[1843] For example, if a device sends heart rate data to a server, and the server analyzes the data and recognizes a high stress state, it will send a notification suggesting a five-minute guided meditation to the user, who can then begin the meditation and track their progress.

[1844] Integrated legal support

[1845] When a user sends a legal question to the server via their device, the server uses an AI model to generate initial legal advice and, if necessary, provides the option to book a legal consultation. The generated legal advice and booking information are sent to the device, where the user can view and interact with it.

[1846] Examples and prompts

[1847] Specific examples include the following:

[1848] Device: The smartwatch measures the heart rate and sends it to the server.

[1849] Server: Analyzes the received heart rate data and determines that the user is in a state of stress.

[1850] Server: Sends a message to the user's device saying, "Please start the 5-minute guided meditation."

[1851] User: Receive a notification from the device and play a guided meditation video.

[1852] (Example of a prompt)

[1853] "Receive and analyze the user's heart rate data, and generate a program that suggests appropriate guided meditations if stress levels are detected."

[1854] The above is a natural language description of the program process of the system of the present invention, which allows users to manage their emotions and stress levels in real time and receive personalized mental health care and legal support.

[1855] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1856] Step 1: Data collection

[1857] Input: Biometric data from sensors (heart rate, body temperature, keystroke rhythm, etc.)

[1858] Device: A smartwatch or smartphone collects the user's biometric data through sensors, which are then sent to a server in real time.

[1859] Output: The collected biometric data is sent to the server.

[1860] Specifically, the smartwatch measures the user's heart rate every second, sends the data to the smartphone via Bluetooth, and then the smartphone sends it to a server via Wi-Fi.

[1861] Step 2: Receiving and storing data

[1862] Input: Biometric data sent from the device

[1863] Server: Receives biometric data sent from the device in real time and stores it in a database.

[1864] Output: Biometric data stored in a database

[1865] Specifically, the server receives the data through a dedicated API and stores it in a database in the form of "user ID, measurement time, heart rate, body temperature, etc."

[1866] Step 3: Data analysis

[1867] Input: Biometric data stored in a database

[1868] Server: The stored data is fed into an AI model to assess the user's emotions and stress levels. The emotion engine also analyzes voice, text, and image data.

[1869] Output: Analysis results (e.g. high stress, fatigue, relaxed)

[1870] Specifically, the server processes a batch of data on a weekly basis and feeds it into an AI model to estimate emotions and stress levels. For example, an elevated heart rate and a drop in voice tone might be assessed as "high stress."

[1871] Step 4: Generate a Mental Health Support Plan

[1872] Input: Analysis results

[1873] Server: Based on the analysis results, automatically generate a mental health support plan appropriate for the user.

[1874] Output: Generated mental health support plan (e.g., guided meditation, relaxation exercises)

[1875] Specifically, if the server detects that the user is in a state of high stress based on the analysis results, it generates a support plan suggesting a "5-minute meditation guide."

[1876] Step 5: Submit your support plan

[1877] Input: Generated Mental Health Support Plan

[1878] Server: Sends the generated support plan to the device.

[1879] Output: Notification message sent to the user's device (e.g., notification that a guided meditation has started)

[1880] Specifically, the server uses the SMTP protocol to send a notification to the user's smartphone saying, "Please start the meditation guide."

[1881] Step 6: Support Execution Notification

[1882] Input: Support plan notification

[1883] Device: Receives notifications and displays them to the user.

[1884] Output: A notification message that will be displayed on the user's terminal.

[1885] Specifically, it uses the smartphone's notification function to display a pop-up message on the user's screen saying, "Please start a 5-minute guided meditation."

[1886] Step 7: Performing and recording support

[1887] Input: Support plan execution instructions

[1888] User: Follows notifications from the device and provides mental health support. The device records the execution status.

[1889] Output: Performance data (e.g., meditation time, exercise completion status)

[1890] Specifically, the user follows the notification to play the guided meditation video, while the smartphone records the playback time. The smartphone also records the progress of the exercise by pressing the completion button.

[1891] Step 8: Analyze support progress

[1892] Input: Recorded execution status data

[1893] Server: Receives and analyzes progress data and uses it to improve the next mental health support plan.

[1894] Output: Improved support plan

[1895] Specifically, the server retrains the AI ​​model based on the performance data and generates personalized feedback such as "suggesting a 10-minute meditation session next time."

[1896] Step 9: Legal Questions Reception and Analysis

[1897] Input: Legal Question from User

[1898] User: Type and submit legal questions via the device.

[1899] Server: Receives the question and uses AI models to generate preliminary legal advice.

[1900] Output: Generated legal advice

[1901] Specifically, the user types "Please tell me about property division in divorce" into their device, which is then sent to the server, which uses an AI model to respond with the appropriate legal information.

[1902] Step 10: Submit legal advice and book a consultation

[1903] Input: Generated legal advice and counseling appointment information

[1904] Server: Sends legal advice and counseling appointment information to the terminal.

[1905] Device: Displays legal advice to the user and offers the option to book a consultation if necessary.

[1906] Output: Legal advice and counseling booking options displayed to the user

[1907] Specifically, the device will display a message saying, "Details on how to divide assets are provided. Click 'Book' to schedule a consultation."

[1908] (Application example 2)

[1909] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1910] In modern society, mental health has become a significant issue due to increased stress and anxiety. However, conventional mental health care systems have difficulty providing accurate support adapted to each user's individual emotional state and stress level. Furthermore, there has been a lack of efficient means to provide continuous mental health support in remote environments or to deliver content appropriate for each user. This has led to problems such as users not receiving appropriate support, limiting the effectiveness of mental health care.

[1911] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information processing device, a sensing device connected to the information processing device, means for receiving data collected from the sensing device and analyzing the user's emotions and stress level, means for providing customized mental health support to the user based on the analysis results, means for notifying the user of the customized mental health support, means for delivering appropriate content based on the analysis results, means for recording content consumption status and generating feedback data, and means for improving future mental health support based on the feedback data. This makes it possible to provide highly accurate mental health care and appropriate content according to the user's individual emotional state and stress level.

[1912] "Information processing device" is a general term for hardware and software for receiving, storing, and analyzing data.

[1913] A "sensing device" is a device that collects a user's biometric and environmental data in real time, and is a general term for smartwatches, smartphones, etc.

[1914] "Emotion and stress level analysis means" is a general term for algorithms and technologies for analyzing collected voice data, text data, and image data to estimate a user's emotional state and stress level.

[1915] "Means for providing customized mental health support" is a general term for technologies and processes that automatically generate and provide mental health care adapted to a user's specific emotions and stress state based on analysis results.

[1916] "Mental health support notification means" is a general term for technologies and devices that notify users of customized mental health support plans and encourage them to take action.

[1917] "Content delivery method" is a general term for the technologies and processes that deliver digital content such as music, videos, and podcasts that are appropriate for a user's emotions and stress levels to a user's device via a network.

[1918] "Means for recording consumption status" is a general term for technologies that record how users consume provided content (for example, playback time and number of times) and store this information in a database.

[1919] "Feedback data generation means" is a general term for the processes and technologies that generate new analytical data based on recorded content consumption status and user feedback, and use it to improve future mental health support.

[1920] In this invention, we combine an information processing device, a sensing device, and an emotion engine to build a system that manages a user's emotions and stress level and provides customized mental health support. Each component of the system and its function are described in detail below.

[1921] System Configuration

[1922] Information processing device

[1923] The server is responsible for data analysis and information management for the entire system. It also functions as an "information processing device," analyzing data collected from the sensing devices and emotion engine to provide mental health support tailored to the user.

[1924] Sensing Device

[1925] The devices include smartwatches and smartphones. These devices act as "sensing devices" that continuously collect biometric data such as the user's heart rate, body temperature, and keystroke rhythm. This data is then transmitted to a server in real time.

[1926] Emotion Engine

[1927] The emotion engine, which functions as an "emotion and stress level analyzer," analyzes voice, text, and image data to identify the user's emotional state. Specifically, it analyzes the tone and speed of voice from the voice data, selected words from the text data, and facial expressions from the image data.

[1928] Programs and their processing

[1929] The server receives biometric data from the sensing device and analysis results from the emotion engine, stores them in a database, analyzes the stored data to determine the user's emotions and stress level, and then generates a customized mental health support plan based on the analysis results and notifies the user.

[1930] Customized Mental Health Support

[1931] As a "means of providing customized mental health support," the server provides users with appropriate mental health support based on the analysis results. This support can include guided meditations, relaxation music, podcasts, etc. For example, if stress levels are high, relaxation music or guided meditations will be provided.

[1932] Content distribution and feedback

[1933] The server will then use the "content delivery means" to deliver content appropriate to the user based on the analysis results. The device will also record consumption status as a "consumption status recording means" and send this to the server. This will allow the "feedback data generation means" to analyze the user's progress and effectiveness, allowing for further customization of support from the next time onwards.

[1934] Hardware and software used

[1935] Hardware:

[1936] Smartphones, smartwatches (sensing devices)

[1937] Server (information processing device)

[1938] software:

[1939] TensorFlow, Keras (emotion engine, AI model)

[1940] OpenCV (image analysis)

[1941] Librosa (voice analysis)

[1942] Examples and how to use generative AI models

[1943] For example, if a user is feeling stressed, they can use prompts like the following to feed data into a generative AI model:

[1944] Example prompt sentence:

[1945] The user's biometric data indicates a heart rate of 90 and a body temperature of 37.5°C. Voice data analysis indicates the voice tone is unstable and fast. Image data analysis indicates the facial expression indicates sadness. Based on this data, diagnose the user's current emotional state and suggest appropriate mental health support content.

[1946] This system allows users to manage their emotions and stress levels in real time and receive appropriate mental health care, which is expected to result in improved mental health and a better quality of life.

[1947] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1948] Step 1:

[1949] The device collects the user's biometric data. It uses a smartwatch or smartphone to measure heart rate, body temperature, and keystroke rhythm in real time and transmits the data to a server. The input is various biometric data, and the output is the biometric data sent to the server.

[1950] Step 2:

[1951] The server uses an emotion engine to analyze the user's voice data, text data, and image data. The voice data sent from the device is used to extract MFCCs using Librosa, and the image data is used to analyze facial expressions using OpenCV. The text data is analyzed using natural language processing technology. The input is voice, text, and image data, and the output is the analysis of the user's emotional state and stress level.

[1952] Step 3:

[1953] The server integrates data from the sensing device and the emotion engine, and uses an AI model (using TensorFlow and Keras) to determine the user's current emotional state and stress level. The input is biometric data and the analysis results of the emotion engine, and the output is the determined emotional state and stress level.

[1954] Step 4:

[1955] The server generates a customized mental health support plan. Based on the determined emotional state and stress level, it selects appropriate content from relaxation music, guided meditations, podcasts, etc. The input is the determined emotional state and stress level, and the output is a customized mental health support plan.

[1956] Step 5:

[1957] The server sends the customized mental health support plan to the terminal, and the terminal displays specific implementation methods (video links and text instructions) to the user based on the received notification. The input is the customized mental health support plan, and the output is the notification to the user.

[1958] Step 6:

[1959] The user performs mental health support based on notifications from the device. For example, the user performs specific actions such as playing relaxation music or watching a guided meditation video. The input is the notification to the user, and the output is the execution of mental health support.

[1960] Step 7:

[1961] The device records the user's mental health support activities, collecting data on the type and time of activities performed and sending it to the server. The input is the mental health support activity data, and the output is the recorded data sent to the server.

[1962] Step 8:

[1963] The server analyzes the feedback data and uses it to improve future mental health support plans. It analyzes user reactions and effects and adjusts the AI ​​model. The input is the recorded data and reaction data, and the output is an updated mental health support plan.

[1964] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1965] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1966] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1967] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1968] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1969] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1970] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1971] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1972] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1973] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1974] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1975] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1976] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1977] 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.

[1978] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1979] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1980] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1981] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1982] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1983] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1984] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1985] The following is further disclosed regarding the above embodiment.

[1986] (Claim 1)

[1987] an information processing device;

[1988] a sensing device connected to the information processing device;

[1989] means for receiving the data collected from the sensing device and analyzing the user's emotions and stress levels;

[1990] A means for providing customized mental health support to the user based on the analysis results;

[1991] means for notifying a user of the customized mental health support;

[1992] A system including:

[1993] (Claim 2)

[1994] 10. The system of claim 1, wherein the mental health support includes providing one of a guided meditation, a psychological counseling session, and relaxation exercises.

[1995] (Claim 3)

[1996] 10. The system of claim 1, further comprising means for providing access to legal advice or counseling services based on the analysis results.

[1997] "Example 1"

[1998] (Claim 1)

[1999] an information processing device;

[2000] a sensing device connected to the information processing device;

[2001] data analysis means for receiving and analyzing the biometric data collected from the sensing device;

[2002] a determination means for determining the user's emotions and stress level by the data analysis means;

[2003] A means for generating a user-specific mental health support plan based on the determination result;

[2004] notification means for notifying a user of the mental health support plan;

[2005] a legal question parser for receiving a legal question and generating initial legal advice;

[2006] A means of providing appointment options for legal counseling services;

[2007] A system including:

[2008] (Claim 2)

[2009] 10. The system of claim 1, wherein the mental health support includes providing one of a guided meditation, a psychological counseling session, and relaxation exercises.

[2010] (Claim 3)

[2011] 10. The system of claim 1, further comprising means for providing access to legal advice or counseling services based on the analysis results.

[2012] "Application Example 1"

[2013] (Claim 1)

[2014] an information processing device;

[2015] a sensing device connected to the information processing device;

[2016] means for receiving the data collected from the sensing device and analyzing the user's emotions and stress levels;

[2017] A means for providing customized mental health support to the user based on the analysis results;

[2018] means for notifying a user of the customized mental health support;

[2019] A method for collecting biometric data of workers in an industrial environment and proposing relaxation support and breaks based on the analysis results;

[2020] A system including:

[2021] (Claim 2)

[2022] 2. The system of claim 1, wherein the mental health support includes a means for providing any one of a meditation guide, a psychological counseling session, and relaxation exercises, and a means for suggesting breaks and deep breathing depending on the worker's stress level.

[2023] (Claim 3)

[2024] 10. The system of claim 1, further comprising means for providing access to legal advice and counseling services based on the analysis, and further providing mental health support specific to industrial environments.

[2025] "Example 2: Combining Emotion Engines"

[2026] (Claim 1)

[2027] an information processing device;

[2028] a sensing device connected to the information processing device;

[2029] means for receiving the data collected from the sensing device and analyzing the user's emotions and stress levels;

[2030] a means for notifying a user of a mental health support plan generated based on the analysis results and recording the implementation status;

[2031] A means for analyzing the recorded execution status and using it to improve future mental health support plans;

[2032] means for receiving legal questions from said user, generating initial legal advice, and providing an option to schedule legal counseling if necessary;

[2033] A system including:

[2034] (Claim 2)

[2035] 10. The system of claim 1, wherein the mental health support plan includes a means for providing any one of guided meditation, psychological counseling sessions, and relaxation exercises.

[2036] (Claim 3)

[2037] 10. The system of claim 1, further comprising means for providing access to legal advice or counseling services based on the analysis results.

[2038] "Application example 2 when combining emotion engines"

[2039] (Claim 1)

[2040] an information processing device;

[2041] a sensing device connected to the information processing device;

[2042] means for receiving the data collected from the sensing device and analyzing the user's emotions and stress levels;

[2043] A means for providing customized mental health support to the user based on the analysis results;

[2044] means for notifying a user of the customized mental health support;

[2045] means for delivering appropriate content based on the analysis results;

[2046] a means for recording the consumption status of the content and generating feedback data;

[2047] a means for improving future mental health support based on said feedback data; and

[2048] A system including:

[2049] (Claim 2)

[2050] 10. The system of claim 1, wherein the mental health support includes providing one of a guided meditation, a psychological counseling session, and relaxation exercises.

[2051] (Claim 3)

[2052] 10. The system of claim 1, further comprising means for providing music, videos, and podcasts as appropriate content based on the analysis results and feedback data. [Explanation of symbols]

[2053] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. an information processing device; a sensing device connected to the information processing device; means for receiving the data collected from the sensing device and analyzing the user's emotions and stress levels; A means for providing customized mental health support to the user based on the analysis results; means for notifying a user of the customized mental health support; A system including:

2. The system of claim 1 , wherein the mental health support includes providing any one of guided meditation, psychological counseling sessions, and relaxation exercises.

3. The system of claim 1 , further comprising means for providing access to legal advice and counseling services based on the analysis results.

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