System

Abstract

A system is provided.SOLUTION: A system, comprising: a device for collecting biometric information; a device comprising a generative model for analyzing the biometric information and determining an emotional state of a user; a device for providing a relaxation environment to the user based on the emotional state; a device for entering and analyzing an emotional diary for responding to changes in the emotional state; and a device for connecting the user to a social support group.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] The present invention aims to address challenges faced by patients with depression and other mental health conditions, particularly the difficulty of seeking psychological counseling and delays in receiving support. Patients with depression can wait long periods of time before seeking a follow-up consultation, putting them at high risk of their symptoms worsening during that time. Therefore, there is a need for a means to provide prompt, personalized support by collecting and analyzing patients' biometric data in real time. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention provides the following solutions. First, a device is provided for collecting biometric information such as a user's heart rate, eye movements, and facial expressions. Next, a device is provided for analyzing the collected biometric information using a generative model to determine the user's emotional state. If the user's emotional state is low, a device is provided for providing a relaxation environment to the user, displaying virtual landscapes and fantastical places using AR or VR technology. Furthermore, a device is provided for the user to enter and analyze an emotional diary, thereby understanding and managing fluctuations in the emotional state. Furthermore, a device is provided for connecting the user to a social support group in real time, supporting communication with other users. In this way, the present invention realizes a system that provides the rapid and personalized support needed by patients with depression and other mental health conditions.

[0006] "Biometric information" refers to data obtained from the user's body, such as heart rate, eye movement, and facial expressions.

[0007] "Apparatus" means a machine or digital device designed for a specific purpose.

[0008] "Emotional state" refers to the user's current psychological and mental state as determined when analyzed by a generative model.

[0009] A "generative model" refers to an algorithm or program that uses machine learning or artificial intelligence techniques to analyze data and generate a specific result.

[0010] "Relaxation environment" refers to providing a virtual or real environment for the purpose of mental relaxation and stress reduction for users.

[0011] "Virtual landscape" refers to a virtual natural landscape or fantastical place generated by a computer.

[0012] "AR" stands for augmented reality, a technology that overlays digital information onto real-world scenery.

[0013] "VR" stands for virtual reality, a technology that provides users with an immersive virtual environment.

[0014] An "emotion diary" refers to a digital or physical notebook that allows users to record their daily emotions and moods.

[0015] A "social support group" refers to a group of users who share the same goals and interests and who come together to support and exchange information with each other.

[0016] "Real-time" refers to data collection, communication, analysis, and display occurring immediately. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

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

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

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

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0032] 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.

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

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The present invention provides a system for providing rapid, personalized support to patients with depression and other mental health conditions. The system uses devices such as smart glasses to collect biometric information in real time and analyzes it with a generative model to determine the user's emotional state. Specific embodiments are described below.

[0039] Biometric data collection

[0040] The user wears smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, allowing the glasses to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[0041] Data transmission and analysis

[0042] The biometric information collected by the smart glasses is transmitted to a server via network communication. The server preprocesses the received data, removing noise and normalizing it. The preprocessed data is then input into a generative model to analyze the user's emotional state.

[0043] Emotional state assessment and relaxation environment provision

[0044] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[0045] Emotional diary entry and analysis

[0046] Users can use the smart glasses' voice input function to write down their emotions in a diary, which is then sent to a server and analyzed using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[0047] Connecting to social support groups

[0048] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[0049] Specific examples

[0050] For example, when a user puts on smart glasses in the morning, their heart rate is measured to be higher than normal, their eye movements are erratic, and their facial expression is sad. This data is sent to the server, where it is analyzed by a generative model and determined to be stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters in their emotion diary by voice, "This morning was stressful, but I was able to relax on the virtual beach." This diary entry is then analyzed by the server and recorded as emotional fluctuations.

[0051] This allows the present invention to manage the user's emotional state in real time and provide appropriate support.

[0052] The processing flow will be explained below.

[0053] Step 1:

[0054] The user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial recognition camera, so once they are put on, they are ready to go.

[0055] Step 2:

[0056] The smart glasses measure heart rate data by using a heart rate sensor to measure the user's heart rate in real time and temporarily store this data in an internal buffer.

[0057] Step 3:

[0058] Smart glasses collect eye movement data. A built-in tracking camera captures the user's eye movements, analyzes them, and stores them as data.

[0059] Step 4:

[0060] The smart glasses analyze facial expression data. Using a facial recognition camera, they analyze the user's facial muscle movements and convert their current facial expression into digital data and store it.

[0061] Step 5:

[0062] The smart glasses transmit biometric information (heart rate data, eye movement data, facial expression data) to a server. The data is transferred to the server via a network using a secure communication protocol (e.g., HTTPS).

[0063] Step 6:

[0064] The server preprocesses the received biometric information, including noise removal and data normalization, to make it suitable for analysis.

[0065] Step 7:

[0066] The server inputs the preprocessed data into a generative model to analyze the user's emotional state. The generative AI model evaluates the data and determines the user's emotional state (e.g., stressed, relaxed, tired, etc.).

[0067] Step 8:

[0068] The server determines the user's emotional state and sends an alert to encourage them to take a break if necessary. If the user's emotional state falls below a defined threshold, the server sends the user an alert message telling them to take a break.

[0069] Step 9:

[0070] The server prepares relaxation environment data for AR / VR and sends it to the smart glasses, providing relaxation data such as virtual beach scenes or forest scenes to the smart glasses.

[0071] Step 10:

[0072] The smart glasses display the received virtual landscape data, utilizing AR / VR technology to provide virtual landscapes and fantastical places for users to relax.

[0073] Step 11:

[0074] Users write their emotional diary using voice input. Using the voice input function of the smart glasses, they record their emotions and experiences for the day.

[0075] Step 12:

[0076] The smart glasses convert the voice-input emotion diary into digital data and send it to the server, where it is transferred as text data.

[0077] Step 13:

[0078] The server analyzes the emotion diary data and uses natural language processing (NLP) technology to understand and record the user's emotional fluctuations.

[0079] Step 14:

[0080] Users connect to a social support group through a smartphone app. The user sends a join request within the app, which is received by the server.

[0081] Step 15:

[0082] The server processes your join request and establishes a connection with your social support group, allowing you to communicate in real time.

[0083] Step 16:

[0084] Users can communicate with other users in real time and receive information and support within social support groups.

[0085] Example 1

[0086] 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."

[0087] In recent years, there has been a demand for rapid and personalized support for patients with depression and other mental health conditions. However, conventional mental health care systems have had difficulty accurately grasping users' emotional states in real time and providing immediate, appropriate support. In addition, the utilization of emotional diaries and social support groups has not been fully realized, resulting in delays in providing measures tailored to each user's individual situation.

[0088] 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.

[0089] In this invention, the server includes a means for transmitting biometric information via a network, a means for preprocessing and noise reduction of the received biometric information, and a means for analyzing the preprocessed biometric information using a generative AI model to determine the user's emotional state. This allows for accurate understanding of the user's emotional state in real time, enabling the immediate provision of an appropriate relaxation environment and analysis of an emotional diary entry. Furthermore, by connecting the user to a social support group, psychological support is enhanced.

[0090] "Biometric information" is data obtained from the user's body, and includes heart rate, eye movement, facial expression data, and the like.

[0091] "Network communications" refers to internet connections and wireless communication technologies (such as Wi-Fi and Bluetooth) for sending and receiving data.

[0092] "Preprocessing" refers to the process of removing noise from the received biometric information and normalizing the data to make it analyzable.

[0093] "Noise removal" is a process of removing unnecessary data and errors from collected biometric information.

[0094] A "generative AI model" is a model that uses deep learning or machine learning algorithms to analyze data and is used to determine a user's emotional state.

[0095] An "emotional state" is a psychological state that a user is feeling, and may include stress, happiness, sadness, etc.

[0096] A "relaxation environment" is a virtual landscape or fantasy place that promotes mental relaxation for users, and is provided using augmented reality (AR) and virtual reality (VR) technologies.

[0097] An "emotion diary" is a diary in which users record their emotional fluctuations and state. It is written using voice input and analyzed using natural language processing technology.

[0098] "Natural language processing technology" is a technology that converts voice data into text information and analyzes its content.

[0099] A "social support group" is a group in which users can participate and communicate with other users to receive emotional support and exchange information.

[0100] The present invention is a system for providing prompt and personalized support to patients with depression and other mental health conditions. An embodiment of the system will be described in detail below.

[0101] First, the user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Using these sensors and cameras, the smart glasses collect biometric information such as the user's heart rate, eye movement, and facial expressions in real time.

[0102] Once biometric information is collected, the smart glasses send it to a server via network communication (Wi-Fi or Bluetooth). The biometric information received by the server is first preprocessed. Preprocessing includes noise reduction and data normalization. Noise reduction removes unnecessary data, and data normalization standardizes the scale of the data.

[0103] The preprocessed data is input into a generative AI model. The server uses this generative AI model to analyze the user's emotional state. Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, virtual scenery data for relaxation is also sent to the smart glasses.

[0104] Based on the virtual landscape data received by the smart glasses, the glasses use augmented reality (AR) and virtual reality (VR) technology to display a relaxing virtual environment for the user, such as a beach or mountain landscape, allowing the user to refresh in a virtual relaxation environment.

[0105] Furthermore, users can use the smart glasses' voice input function to write an emotional diary, which is then sent to a server where it is analyzed using natural language processing (NLP) technology to analyze emotional fluctuations in detail.

[0106] Finally, users can join social support groups through a smartphone app. The server receives the join request and establishes a connection. This connection allows users to communicate with other users in real time and provide emotional support.

[0107] Specific examples

[0108] For example, suppose a user wears smart glasses in the morning, and the heart rate sensor measures a heart rate of 90 beats per minute, the eye movement tracking camera detects frequent eye movements, and the facial expression recognition camera analyzes sad facial expressions. This data is sent to the server, where noise removal and data normalization are performed. The data is then input into a generative AI model to determine that the user is in a stressed state. The server then sends the user an alert saying, "Take a short break," and displays a virtual beach scene on the smart glasses. After relaxing on the virtual beach, the user writes in their emotion diary by voice input, "I was stressed this morning, but I was able to relax on the virtual beach." This diary is analyzed by the server and recorded as emotional fluctuations.

[0109] Prompt Sentence Examples

[0110] "Please explain how a system where a user wears smart glasses collects biometric information (heart rate, eye movements, facial expressions) and sends it to a server for analysis to determine the user's emotional state and provide appropriate support."

[0111] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0112] Step 1:

[0113] The user wears smart glasses, which use built-in heart rate sensors, eye movement tracking cameras, and facial expression recognition cameras to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[0114] Input: User's biometric information (heart rate, eye movement, facial expression)

[0115] Output: Collected biometric data

[0116] Step 2:

[0117] The biometric information collected by the smart glasses is sent to a server via a network, specifically using Wi-Fi or Bluetooth.

[0118] Input: Collected biometric data

[0119] Output: Biometric data sent to the server

[0120] Step 3:

[0121] The server preprocesses the received biometric data, which includes noise removal and data normalization to improve data quality and make it suitable for analysis.

[0122] Input: Biometric data sent to the server

[0123] Output: Preprocessed biometric data

[0124] Step 4:

[0125] The preprocessed biometric data is input into a generative AI model. The server uses the generative AI model to analyze the data and determine the user's emotional state. A deep learning algorithm is used as the generative AI model.

[0126] Input: Preprocessed biometric data

[0127] Output: Parsed emotional state

[0128] Step 5:

[0129] The server determines the user's emotional state based on the analyzed emotional state, such as "high stress," "happiness," or "sadness."

[0130] Input: Parsed emotional state

[0131] Output: Determined emotional state

[0132] Step 6:

[0133] If the emotional state is judged to be low, for example "sadness," the server sends an alert to the user saying "Take a short break." At the same time, virtual scenery data for relaxation is sent to the smart glasses.

[0134] Input: Determined emotional state

[0135] Output: Break alert and virtual landscape data

[0136] Step 7:

[0137] Based on the virtual landscape data received by the smart glasses, augmented reality (AR) and virtual reality (VR) technologies are used to display a relaxation environment for the user, such as a beach or mountain landscape.

[0138] Input: Virtual landscape data

[0139] Output: The virtual relaxation environment seen by the user

[0140] Step 8:

[0141] The user uses the voice input function of the smart glasses to write an emotional diary.

[0142] Input: User voice input

[0143] Output: Emotion diary entries

[0144] Step 9:

[0145] The emotion diary entries are sent to a server and analyzed using natural language processing (NLP) technology. Specifically, the voice data is converted into text information, and the emotion diary is analyzed in detail.

[0146] Input: Emotional diary entry

[0147] Output: Parsed emotion diary

[0148] Step 10:

[0149] A user sends a request to join a social support group via a smartphone app.

[0150] Input: Join request

[0151] Output: Support group join request

[0152] Step 11:

[0153] The server receives the user's request and establishes a connection, allowing users to communicate with other users in real time.

[0154] Input: Join request

[0155] Output: Social support group connections

[0156] (Application example 1)

[0157] 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."

[0158] In modern society, people engaged in high-stress jobs, such as police officers and security guards, have difficulty understanding their rapidly fluctuating mental state in real time and receiving appropriate support. Furthermore, if stress and anxiety that arise during work cannot be properly managed, it can lead to serious accidents and reduced work efficiency. Concrete measures to resolve these issues and improve work safety and efficiency are needed.

[0159] 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.

[0160] In this invention, the server includes a device for collecting biometric information, a device with a generative model for analyzing the biometric information and determining the user's emotional state, a device for providing a relaxation environment to the user based on the emotional state, a device for entering and analyzing an emotion diary to respond to fluctuations in the emotional state, a device for connecting the user to a social support group, a device and processing means for monitoring the user's mental state while performing work and providing appropriate alerts, and a rendering means for providing the relaxation environment using VR technology.This allows the user's mental state to be understood in real time and an appropriate relaxation environment to be provided, enabling the user to safely and efficiently handle even high-stress work.

[0161] "Biometric information" refers to data related to the user's vital activities, such as heart rate, eye movement, and facial expression data.

[0162] A "generative model" refers to an algorithmic model that uses machine learning and artificial intelligence techniques to determine a user's emotional state.

[0163] A "relaxation environment" refers to an environment that provides virtual landscapes and fantastical places to promote mental stability for users.

[0164] An "emotion diary" refers to a system that records a user's emotional fluctuations and collects data for analysis.

[0165] A "social support group" refers to a group where multiple users communicate with each other, provide emotional support, and exchange information.

[0166] "Monitoring mental state during work performance" refers to monitoring the mental state of a user in real time while they are performing their work.

[0167] "Alert" refers to a system that provides important notifications to users, such as encouraging them to take a break.

[0168] "VR technology" refers to technology that uses virtual reality technology to allow users to experience an immersive virtual environment.

[0169] "Rendering means" refers to devices or software that generate virtual landscapes or fantasy locations using computer graphics techniques to visually represent virtual environments.

[0170] This invention is a system that collects biometric information and monitors the user's mental state in real time, supporting job performance in high-stress environments. Specifically, the system includes smart glasses, a server, network communications, a generative model, and a VR rendering means.

[0171] Biometric data collection

[0172] The device (here, smart glasses) is worn by the user. The smart glasses are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Each of these sensors collects biometric information such as the user's heart rate, eye movement, and facial expressions in real time.

[0173] Data transmission and analysis

[0174] The biometric information collected by the smart glasses is transmitted to a server via network communication. The server preprocesses the received data, removes noise, and normalizes the data. The preprocessed data is then input into a generative model to analyze the user's emotional state.

[0175] Emotional state assessment and relaxation environment provision

[0176] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[0177] Emotional diary entry and analysis

[0178] Users can use the smart glasses' voice input function to write down their emotions in a diary, which is then sent to a server and analyzed using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[0179] Connecting to social support groups

[0180] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[0181] Specific examples of programs

[0182] As a pre-processing step for biometric information, a Butterworth filter is applied to the heart rate data to remove noise. Data is transmitted via network communication (HTTP request), and the server uses a generative AI model to analyze the data. Additionally, a relaxation environment is provided when the emotional state is low, and is rendered using VR technology. As a specific example, the server analyzes the user's data using the following prompt:

[0183] Example prompt sentence:

[0184] "Analyze heart rate data: {heart rate data}, eye movement data: {eye movement data}, and facial expressions: {facial expressions} to determine the user's emotional state."

[0185] This system allows users to grasp their mental state in real time and provide an appropriate relaxation environment, enabling them to respond safely and efficiently to even high-stress work.

[0186] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0187] Step 1: Collecting biometric information

[0188] The user puts on the smart glasses. The smart glasses' heart rate sensor, eye movement tracking camera, and facial expression recognition camera are activated, collecting the user's heart rate, eye movement, and facial expression data in real time. This biometric information is temporarily stored in the recording media inside the smart glasses.

[0189] Input: User's heart rate, eye movement, and facial expression data

[0190] Output: Collected biometric information

[0191] Step 2: Sending data

[0192] The device (smart glasses) sends the collected biometric information to the server via network communication. Specifically, it uses an HTTP request to package the biometric information in JSON format and send it to a specified endpoint.

[0193] Input: Collected biometric information

[0194] Output: Data sent to the server

[0195] Step 3: Preprocessing the data

[0196] The server preprocesses the received biometric data. At this stage, noise removal and data normalization are performed. For example, a Butterworth filter is applied to heart rate data to remove noise. Eye movement data and facial expression data are also preprocessed in a similar way to prepare them for analysis.

[0197] Input: Data sent to the server

[0198] Output: Preprocessed biometric information

[0199] Step 4: Analyze emotional state

[0200] The server inputs the preprocessed biometric information into a generative model to analyze the user's emotional state. The generative AI model then comprehensively analyzes heart rate, eye movement, and facial expression data to determine the user's emotional state.

[0201] Input: Preprocessed biometric information

[0202] Output: User's emotional state

[0203] Step 5: Provide a Relaxation Environment

[0204] If the server analyzes the user's emotional state and determines that the user's mental state is low, it will send an alert urging the user to take a break. It also sends virtual landscape data for relaxation to the smart glasses, which then use augmented reality (AR) and virtual reality (VR) technology to display a relaxing environment.

[0205] Input: User's emotional state

[0206] Output: Alert and relaxation environment

[0207] Step 6: Emotional Diary

[0208] The user uses the voice input function of the smart glasses to write down their emotions in a diary, which is then sent to a server, where it analyzes the diary using natural language processing (NLP) technology to understand the user's emotional fluctuations.

[0209] Input: Emotion diary based on user voice input

[0210] Output: Analyzed emotion diary data

[0211] Step 7: Connect to social support groups

[0212] A user sends a request to join a social support group through a smartphone app. The server receives the request and establishes a connection, allowing users to communicate with other users in real time and exchange support and information.

[0213] Input: User's join request

[0214] Output: Connected social support groups

[0215] In this way, the system manages the user's mental state in real time and provides an appropriate relaxation environment and support, enabling them to cope with high-stress work safely and efficiently.

[0216] 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.

[0217] The present invention is a system that provides rapid, personalized support for patients with depression and other mental health conditions. The system uses devices such as smart glasses to collect biometric information in real time and analyzes it with a generative model combined with an emotion engine to determine the user's emotional state. Specific embodiments are described below.

[0218] Biometric data collection

[0219] The user wears smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, allowing the glasses to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[0220] Data transmission and analysis

[0221] The biometric information collected by the smart glasses is sent to a server via network communication. The server preprocesses the received data, removing noise and normalizing it. The preprocessed data is then input into a generative model combined with an emotion engine to analyze the user's emotional state.

[0222] Emotional state assessment and feedback

[0223] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[0224] Emotional diary entry and analysis

[0225] Users can use the smart glasses' voice input function to write down their emotions in a diary. The diary entries are sent to a server where an emotion engine analyzes them using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[0226] Connecting to social support groups

[0227] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[0228] Specific examples

[0229] For example, when a user puts on smart glasses in the morning, it is measured that their heart rate is higher than normal, their eye movements are erratic, and their facial expression is sad. This data is sent to the server, where it is analyzed using a generative model combined with an emotion engine, and it is determined that the user is feeling stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters in their emotion diary by voice, "I was stressed this morning, but I was able to relax on the virtual beach." This diary entry is then analyzed by the server and recorded as emotional fluctuations.

[0230] This allows the present invention to manage the user's emotional state in real time and provide appropriate support. Furthermore, the use of an emotion engine enables more accurate emotion recognition and feedback, thereby effectively supporting the user's mental health.

[0231] The processing flow will be explained below.

[0232] Step 1:

[0233] The user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial recognition camera, so once they are put on, they are ready to go.

[0234] Step 2:

[0235] The smart glasses measure heart rate data by using a heart rate sensor to measure the user's heart rate in real time and temporarily store this data in an internal buffer.

[0236] Step 3:

[0237] Smart glasses collect eye movement data. A built-in tracking camera captures the user's eye movements, analyzes them, and stores them as data.

[0238] Step 4:

[0239] The smart glasses analyze facial expression data. Using a facial recognition camera, they analyze the user's facial muscle movements and convert their current facial expression into digital data and store it.

[0240] Step 5:

[0241] The smart glasses transmit biometric information (heart rate data, eye movement data, facial expression data) to a server. The data is transferred to the server via a network using a secure communication protocol (e.g., HTTPS).

[0242] Step 6:

[0243] The server preprocesses the received biometric information, including noise removal and data normalization, to make it suitable for analysis.

[0244] Step 7:

[0245] The server inputs the preprocessed data into a generative model to analyze the user's emotional state. The generative AI model evaluates the data and determines the user's emotional state (e.g., stressed, relaxed, tired, etc.).

[0246] Step 8:

[0247] The server checks the analysis results with the emotion engine and updates the emotional state in real time. The emotion engine performs additional data analysis and provides immediate feedback on the user's emotional state.

[0248] Step 9:

[0249] The server determines the user's emotional state and sends an alert to encourage them to take a break if necessary. If the user's emotional state falls below a defined threshold, the server sends the user an alert message telling them to take a break.

[0250] Step 10:

[0251] The server prepares relaxation environment data for AR / VR and sends it to the smart glasses, providing relaxation data such as virtual beach scenes or forest scenes to the smart glasses.

[0252] Step 11:

[0253] The smart glasses display the received virtual landscape data, utilizing AR / VR technology to provide virtual landscapes and fantastical places for users to relax.

[0254] Step 12:

[0255] Users write their emotional diary using voice input. Using the voice input function of the smart glasses, they record their emotions and experiences for the day.

[0256] Step 13:

[0257] The smart glasses convert the voice-input emotion diary into digital data and send it to the server, where it is transferred as text data.

[0258] Step 14:

[0259] The server analyzes the emotion diary data, and the emotion engine uses natural language processing (NLP) technology to analyze it and understand the user's emotional fluctuations.

[0260] Step 15:

[0261] Users connect to a social support group through a smartphone app. The user sends a request to join within the app, which is received by the server.

[0262] Step 16:

[0263] The server processes your join request and establishes a connection with your social support group, allowing you to communicate in real time.

[0264] Step 17:

[0265] Users can communicate with other users in real time and receive information and support within social support groups.

[0266] Example 2

[0267] 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."

[0268] Existing technologies include systems that collect and analyze biometric data to determine a user's emotional state, but these systems often lack the ability to collect and provide feedback in real time. Furthermore, they lack detailed analysis of the user's emotional fluctuations and integration with social support, limiting their ability to effectively support the user's mental health. This invention aims to provide comprehensive mental health care by continuously monitoring a user's emotional state in real time, providing an appropriate relaxation environment, analyzing emotional records, and facilitating connection to social support groups.

[0269] 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.

[0270] In this invention, the server includes a means for collecting biometric data, a means for providing a generative artificial intelligence model for analyzing the biometric data and determining the user's emotional state, a means for providing a relaxation environment to the user based on the emotional state, a means for recording and analyzing an emotional log to respond to fluctuations in the emotional state, and a means for connecting the user to a social support group, thereby enabling real-time monitoring and analysis of the emotional state and providing appropriate feedback and comprehensive mental health support.

[0271] "Biometric data" refers to data that indicates the user's physical condition, including heart rate, eye movement data, and facial expression data.

[0272] "Generative AI models" refer to algorithms or machine learning models that analyze a user's biometric data and determine their emotional state.

[0273] A "relaxation environment" refers to an environment in which users can relax by providing virtual landscapes and fantastical places using augmented reality and virtual reality technologies.

[0274] "Emotion records" record fluctuations in a user's emotional state and refer to data collected through voice and text input.

[0275] A "social support group" refers to a group of other users and supporters with whom a user can receive emotional support through real-time communication.

[0276] The present invention relates to a system for collecting a user's biological data in real time, analyzing the user's emotional state based on the collected data, providing an appropriate relaxation environment, and analyzing the emotional record.

[0277] Biometric data collection

[0278] The user wears a device called smart glasses, which collects biometric data. The smart glasses are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, and these sensors are used to collect biometric data such as heart rate, eye movement, and facial expressions in real time. The collected data is temporarily stored in the smart glasses and is sent to a server once it is ready.

[0279] Data transmission and analysis

[0280] The biometric data collected by the smart glasses is sent to a server via network communication. The server first preprocesses the received data, removing noise and normalizing it. After preprocessing is complete, the data is input into a generative AI model (such as OpenAI's GPT-3) that combines an emotion engine to analyze the user's emotional state.

[0281] Providing a relaxing environment

[0282] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. It also sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[0283] Emotional record entry and analysis

[0284] Users can record their emotions using the smart glasses' voice input function. The recorded emotion record is then sent to a server via the network. The server receives the record and an emotion engine analyzes it using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[0285] Connecting to social support groups

[0286] Users can join social support groups through a smartphone app. The server receives the join request and establishes a connection with the group, allowing users to communicate with other users in real time and receive social support.

[0287] Specific examples

[0288] For example, when a user puts on smart glasses in the morning, it detects that their heart rate is higher than normal, their eye movements are erratic, and their facial expression looks sad. This data is sent to the server, where it is analyzed by a generative AI model combined with an emotion engine, and it is determined that the user is feeling stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters the following in their emotion log by voice: "The morning was stressful, but I was able to relax on the virtual beach." These records are then analyzed by the server and recorded as emotional fluctuations.

[0289] Example prompts for generative AI models

[0290] Prompt: "Please describe in detail how you would analyze the user's emotional state and provide appropriate feedback."

[0291] This allows the present invention to manage the user's emotional state in real time and provide appropriate support. Furthermore, the use of an emotion engine enables more accurate emotion recognition and feedback, thereby effectively supporting the user's mental health.

[0292] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0293] Step 1:

[0294] The user wears the smart glasses, which collect biometric data (heart rate, eye movement data, facial expression data) in real time. The input is various biometric signals from the smart glasses' sensors, and the output is biometric data that is temporarily stored in the smart glasses. Specifically, the heart rate sensor detects the heart rate, the tracking camera captures eye movement, and the facial expression recognition camera analyzes facial expressions.

[0295] Step 2:

[0296] The biometric data collected by the smart glasses is sent to a server via network communication. The input is the biometric data stored in the smart glasses, and the output is the data sent to the server. Specifically, the smart glasses upload the data to the server in real time using Wi-Fi or Bluetooth.

[0297] Step 3:

[0298] The server preprocesses the received biometric data. The input is the received biometric data, and the output is preprocessed data that has been subjected to noise removal and normalization. Specifically, the server uses a filtering algorithm to remove noise and normalize the scale of the data, converting the data into a format suitable for the analysis model.

[0299] Step 4:

[0300] The server inputs the preprocessed data into a generative AI model combined with an emotion engine to analyze the user's emotional state. The input is the preprocessed data, and the output is the analyzed emotional state. Specifically, a generative AI model (e.g., GPT-3) is used to analyze the user's emotions from the data, and the results are returned to the server.

[0301] Step 5:

[0302] The server determines the user's emotional state based on the analysis results. If the emotional state is determined to be low, the server sends an alert encouraging the user to take a break. The input is the emotion analysis result from the generative AI model, and the output is an alert sent to the user and virtual scenery data necessary for relaxation. Specifically, the server determines that the user is "high stress" and sends scenery data of a virtual beach to the smart glasses along with a message such as "take a break."

[0303] Step 6:

[0304] Based on the virtual landscape data received by the smart glasses, a relaxing environment is displayed using augmented reality (AR) and virtual reality (VR) technology. The input is the virtual landscape data sent from the server, and the output is the display of the relaxing environment. Specifically, the smart glasses display the virtual landscape on a visual display, encouraging the user to relax.

[0305] Step 7:

[0306] The user uses the voice input function of the smart glasses to record their emotions. The input is the user's voice command, and the output is sent to the server as voice data. Specifically, the user might say, "I had a stressful morning, but I was able to relax on the virtual beach," and the smart glasses would analyze this as voice data and send it to the server.

[0307] Step 8:

[0308] The server receives the transmitted emotion record, and the emotion engine analyzes the record using natural language processing (NLP) technology. The input is voice data, and the output is analyzed emotion fluctuation data. Specifically, the server converts the voice data into text, analyzes the emotion record using NLP technology, and records the user's emotional fluctuations.

[0309] Step 9:

[0310] A user joins a social support group through a smartphone app. The input is the user's join request, and the output is permission to connect to the group. Specifically, the server accepts the join request and provides group connection information to the user's smartphone app, allowing the user to communicate with other group members in real time.

[0311] (Application example 2)

[0312] 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."

[0313] Delivery workers, including food delivery workers, are often exposed to long working hours and stress, which can have a negative impact on their work efficiency and health. Currently, there is a lack of a system that monitors worker stress and fatigue in real time and provides appropriate support, so quick and effective measures are needed.

[0314] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0315] In this invention, the server includes means for collecting biometric information, means for providing a generative model for analyzing emotional states, means for providing a relaxation environment to a user, means for recording and analyzing an emotional diary, means for connecting the user to a social support group, and means for use by delivery workers to monitor the fatigue and stress of the worker in real time and provide a rest and relaxation environment as needed, thereby managing the stress and fatigue of the worker and improving their work efficiency and health.

[0316] "Biometric information" refers to information for understanding the user's physical condition, such as the user's heart rate, eye movement, and facial expression data.

[0317] A "generative model" is a model for analyzing collected biometric information and determining the user's emotional state.

[0318] A "relaxation environment" is an environment that uses AR and VR technology to provide virtual landscapes and fantastical places to help users relax.

[0319] An "emotion diary" is a tool that allows users to record fluctuations in their emotional state.

[0320] A "social support group" is a group where users can communicate with other users in real time and receive emotional support.

[0321] "Delivery work" refers to the work that a user does to deliver a product to a recipient.

[0322] A "worker" is a user who is engaged in delivery work.

[0323] "Real-time" refers to processing or responding with minimal delay.

[0324] "Monitoring" is the act of continuously observing and recording specific information or conditions.

[0325] A "break" refers to a temporary interruption of work by a user to restore physical or mental strength.

[0326] The present invention provides a system for managing stress and fatigue of delivery workers, thereby improving their work efficiency and health. Specific embodiments for carrying out the present invention will be described below.

[0327] Biometric data collection

[0328] The device (smart glasses) is equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Using these sensors, the device collects biometric information such as heart rate, eye movement, and facial expressions in real time. This collected data is sent to a server via network communication.

[0329] Data preprocessing and analysis

[0330] On the server side, after receiving the biometric information, preprocessing such as noise removal and data normalization is performed. The preprocessed data is then input into a generative model equipped with an emotion engine to analyze the user's emotional state. This generative model combines the diverse data collected to accurately determine the user's stress and fatigue state.

[0331] Emotional state assessment and feedback

[0332] The server uses an emotion engine to analyze the user's emotional state, and if it determines that the user is experiencing high levels of stress or fatigue, it sends an alert to the device urging them to take a break. At the same time, relaxing virtual landscape data (e.g., a beach scene) is sent to the device, providing the user with a relaxation environment using AR and VR technology.

[0333] Emotional diary entry and analysis

[0334] Users can use the smart glasses to write their emotional diary using voice input, and this diary data is also sent to a server where it is analyzed using natural language processing (NLP) technology, allowing continuous fluctuations in the user's emotional state to be understood.

[0335] Connecting to social support groups

[0336] Users can join social support groups through a smartphone app, where they can communicate with other workers in real time, offering mutual comfort and information exchange, thereby enhancing psychological support.

[0337] Specific examples

[0338] For example, if a delivery person exhibits biometric information such as a high heart rate, unstable eye movements, and a stern expression while making a delivery, the server will analyze this with its emotion engine and determine that the delivery person is experiencing high stress. The server will immediately send an alert to the device urging them to take a break, and at the same time display a relaxing virtual beach scene on the device. The delivery person will enter an emotion diary entry by saying, "Today was busy and stressful, but I was able to relax on the beach," and the diary data will be analyzed and recorded on the server.

[0339] Example prompt for a generative AI model:

[0340] "Analyze the following text to determine the user's emotional state: 'Today was busy, but I was able to relax on the beach during my break.'"

[0341] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0342] Step 1:

[0343] The terminal collects the user's biometric information.

[0344] Specifically, the device's built-in heart rate sensor, eye movement tracking camera, and facial expression recognition camera measure and collect heart rate, eye movement, and facial expression data in real time, respectively.

[0345] Input: User's biometric information (heart rate, eye movement, facial expression data)

[0346] Output: Collected biometric data

[0347] Step 2:

[0348] The terminal transmits the collected biometric information to the server.

[0349] Specifically, the terminal transmits the collected biometric information data to a server via network communication.

[0350] Input: Collected biometric data

[0351] Output: Biometric data sent to the server

[0352] Step 3:

[0353] The server preprocesses the received biometric data.

[0354] Specifically, we perform preprocessing to improve the accuracy of the analysis by removing noise and normalizing the data. We use a median filter for noise removal and an appropriate scaling method for data normalization.

[0355] Input: Biometric data sent to the server

[0356] Output: Preprocessed biometric data

[0357] Step 4:

[0358] The server inputs the preprocessed biometric data into a generative model to analyze the user's emotional state.

[0359] Specifically, a generative AI model combined with an emotion engine is used to determine the user's stress level and fatigue level from biometric data.

[0360] Input: Preprocessed biometric data

[0361] Output: User's emotional state (e.g., stress level, high / low)

[0362] Step 5:

[0363] The server generates feedback based on the analysis results.

[0364] Specifically, if the user shows signs of high stress or fatigue, an alert is generated to encourage them to take a break, and virtual scenery data (e.g., a beach scene) is also provided.

[0365] Input: User's emotional state (stress level)

[0366] Output: Break alert, virtual landscape data

[0367] Step 6:

[0368] The terminal receives the feedback from the server and displays it to the user.

[0369] Specifically, the system will notify users with an alert encouraging them to take a break, and will use virtual landscape data to display a relaxation environment using AR and VR technology.

[0370] Input: Break alerts, virtual landscape data

[0371] Output: Alert to user, display of relaxation environment

[0372] Step 7:

[0373] The user writes an emotion diary using voice input.

[0374] Specifically, users use the voice input function of the smart glasses to record their emotional state and the events of the day.

[0375] Input: Audio data of the user's emotion diary

[0376] Output: Emotion diary written by voice

[0377] Step 8:

[0378] The emotion diary data is sent to a server, which analyzes it using natural language processing (NLP) technology.

[0379] Specifically, text data is generated from voice data, and this is analyzed using an NLP model to record fluctuations in the user's emotions.

[0380] Input: Emotional diary written by voice

[0381] Output: Analyzed emotional state data and its fluctuations

[0382] Step 9:

[0383] Users connect to social support groups.

[0384] Specifically, users join support groups through a smartphone app and communicate with other users in real time. The server receives connection requests and establishes the connections.

[0385] Input: A user's connection request

[0386] Output: Connection established to a social support group

[0387] 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.

[0388] 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.

[0389] 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.

[0390] [Second embodiment]

[0391] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0392] 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.

[0393] 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).

[0394] 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.

[0395] 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.

[0396] 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).

[0397] 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.

[0398] 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.

[0399] 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.

[0400] 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.

[0401] 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.

[0402] 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."

[0403] The present invention provides a system for providing rapid, personalized support to patients with depression and other mental health conditions. The system uses devices such as smart glasses to collect biometric information in real time and analyzes it with a generative model to determine the user's emotional state. Specific embodiments are described below.

[0404] Biometric data collection

[0405] The user wears smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, allowing the glasses to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[0406] Data transmission and analysis

[0407] The biometric information collected by the smart glasses is transmitted to a server via network communication. The server preprocesses the received data, removing noise and normalizing it. The preprocessed data is then input into a generative model to analyze the user's emotional state.

[0408] Emotional state assessment and relaxation environment provision

[0409] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[0410] Emotional diary entry and analysis

[0411] Users can use the smart glasses' voice input function to write down their emotions in a diary, which is then sent to a server and analyzed using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[0412] Connecting to social support groups

[0413] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[0414] Specific examples

[0415] For example, when a user puts on smart glasses in the morning, their heart rate is measured to be higher than normal, their eye movements are erratic, and their facial expression is sad. This data is sent to the server, where it is analyzed by a generative model and determined to be stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters in their emotion diary by voice, "This morning was stressful, but I was able to relax on the virtual beach." This diary entry is then analyzed by the server and recorded as emotional fluctuations.

[0416] This allows the present invention to manage the user's emotional state in real time and provide appropriate support.

[0417] The processing flow will be explained below.

[0418] Step 1:

[0419] The user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial recognition camera, so once they are put on, they are ready to go.

[0420] Step 2:

[0421] The smart glasses measure heart rate data by using a heart rate sensor to measure the user's heart rate in real time and temporarily store this data in an internal buffer.

[0422] Step 3:

[0423] Smart glasses collect eye movement data. A built-in tracking camera captures the user's eye movements, analyzes them, and stores them as data.

[0424] Step 4:

[0425] The smart glasses analyze facial expression data. Using a facial recognition camera, they analyze the user's facial muscle movements and convert their current facial expression into digital data and store it.

[0426] Step 5:

[0427] The smart glasses transmit biometric information (heart rate data, eye movement data, facial expression data) to a server. The data is transferred to the server via a network using a secure communication protocol (e.g., HTTPS).

[0428] Step 6:

[0429] The server preprocesses the received biometric information, including noise removal and data normalization, to make it suitable for analysis.

[0430] Step 7:

[0431] The server inputs the preprocessed data into a generative model to analyze the user's emotional state. The generative AI model evaluates the data and determines the user's emotional state (e.g., stressed, relaxed, tired, etc.).

[0432] Step 8:

[0433] The server determines the user's emotional state and sends an alert to encourage them to take a break if necessary. If the user's emotional state falls below a defined threshold, the server sends the user an alert message telling them to take a break.

[0434] Step 9:

[0435] The server prepares relaxation environment data for AR / VR and sends it to the smart glasses, providing relaxation data such as virtual beach scenes or forest scenes to the smart glasses.

[0436] Step 10:

[0437] The smart glasses display the received virtual landscape data, utilizing AR / VR technology to provide virtual landscapes and fantastical places for users to relax.

[0438] Step 11:

[0439] Users write their emotional diary using voice input. Using the voice input function of the smart glasses, they record their emotions and experiences for the day.

[0440] Step 12:

[0441] The smart glasses convert the voice-input emotion diary into digital data and send it to the server, where it is transferred as text data.

[0442] Step 13:

[0443] The server analyzes the emotion diary data and uses natural language processing (NLP) technology to understand and record the user's emotional fluctuations.

[0444] Step 14:

[0445] Users connect to a social support group through a smartphone app. The user sends a request to join within the app, which is received by the server.

[0446] Step 15:

[0447] The server processes your join request and establishes a connection with your social support group, allowing you to communicate in real time.

[0448] Step 16:

[0449] Users can communicate with other users in real time and receive information and support within social support groups.

[0450] Example 1

[0451] 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."

[0452] In recent years, there has been a demand for rapid and personalized support for patients with depression and other mental health conditions. However, conventional mental health care systems have had difficulty accurately grasping users' emotional states in real time and providing immediate, appropriate support. In addition, the utilization of emotional diaries and social support groups has not been fully realized, resulting in delays in providing measures tailored to each user's individual situation.

[0453] 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.

[0454] In this invention, the server includes a means for transmitting biometric information via a network, a means for preprocessing and noise reduction of the received biometric information, and a means for analyzing the preprocessed biometric information using a generative AI model to determine the user's emotional state. This allows for accurate understanding of the user's emotional state in real time, enabling the immediate provision of an appropriate relaxation environment and analysis of an emotional diary entry. Furthermore, by connecting the user to a social support group, psychological support is enhanced.

[0455] "Biometric information" is data obtained from the user's body, and includes heart rate, eye movement, facial expression data, and the like.

[0456] "Network communications" refers to internet connections and wireless communication technologies (such as Wi-Fi and Bluetooth) for sending and receiving data.

[0457] "Preprocessing" refers to the process of removing noise from the received biometric information and normalizing the data to make it analyzable.

[0458] "Noise removal" is a process of removing unnecessary data and errors from collected biometric information.

[0459] A "generative AI model" is a model that uses deep learning or machine learning algorithms to analyze data and is used to determine a user's emotional state.

[0460] An "emotional state" is a psychological state that a user is feeling, and may include stress, happiness, sadness, etc.

[0461] A "relaxation environment" is a virtual landscape or fantasy place that promotes mental relaxation for users, and is provided using augmented reality (AR) and virtual reality (VR) technologies.

[0462] An "emotion diary" is a diary in which users record their emotional fluctuations and state. It is written using voice input and analyzed using natural language processing technology.

[0463] "Natural language processing technology" is a technology that converts voice data into text information and analyzes its content.

[0464] A "social support group" is a group in which users can participate and communicate with other users to receive emotional support and exchange information.

[0465] The present invention is a system for providing prompt and personalized support to patients with depression and other mental health conditions. An embodiment of the system will be described in detail below.

[0466] First, the user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Using these sensors and cameras, the smart glasses collect biometric information such as the user's heart rate, eye movement, and facial expressions in real time.

[0467] Once biometric information is collected, the smart glasses send it to a server via network communication (Wi-Fi or Bluetooth). The biometric information received by the server is first preprocessed. Preprocessing includes noise reduction and data normalization. Noise reduction removes unnecessary data, and data normalization standardizes the scale of the data.

[0468] The preprocessed data is input into a generative AI model. The server uses this generative AI model to analyze the user's emotional state. Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, virtual scenery data for relaxation is also sent to the smart glasses.

[0469] Based on the virtual landscape data received by the smart glasses, the glasses use augmented reality (AR) and virtual reality (VR) technology to display a relaxing virtual environment for the user, such as a beach or mountain landscape, allowing the user to refresh in a virtual relaxation environment.

[0470] Furthermore, users can use the smart glasses' voice input function to write an emotional diary, which is then sent to a server where it is analyzed using natural language processing (NLP) technology to analyze emotional fluctuations in detail.

[0471] Finally, users can join social support groups through a smartphone app. The server receives the join request and establishes a connection. This connection allows users to communicate with other users in real time and provide emotional support.

[0472] Specific examples

[0473] For example, suppose a user wears smart glasses in the morning, and the heart rate sensor measures a heart rate of 90 beats per minute, the eye movement tracking camera detects frequent eye movements, and the facial expression recognition camera analyzes sad facial expressions. This data is sent to the server, where noise removal and data normalization are performed. The data is then input into a generative AI model to determine that the user is in a stressed state. The server then sends the user an alert saying, "Take a short break," and displays a virtual beach scene on the smart glasses. After relaxing on the virtual beach, the user writes in their emotion diary by voice input, "I was stressed this morning, but I was able to relax on the virtual beach." This diary is analyzed by the server and recorded as emotional fluctuations.

[0474] Prompt Sentence Examples

[0475] "Please explain how a system where a user wears smart glasses collects biometric information (heart rate, eye movements, facial expressions) and sends it to a server for analysis to determine the user's emotional state and provide appropriate support."

[0476] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0477] Step 1:

[0478] The user wears smart glasses, which use built-in heart rate sensors, eye movement tracking cameras, and facial expression recognition cameras to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[0479] Input: User's biometric information (heart rate, eye movement, facial expression)

[0480] Output: Collected biometric data

[0481] Step 2:

[0482] The biometric information collected by the smart glasses is sent to a server via a network, specifically using Wi-Fi or Bluetooth.

[0483] Input: Collected biometric data

[0484] Output: Biometric data sent to the server

[0485] Step 3:

[0486] The server preprocesses the received biometric data, which includes noise removal and data normalization to improve data quality and make it suitable for analysis.

[0487] Input: Biometric data sent to the server

[0488] Output: Preprocessed biometric data

[0489] Step 4:

[0490] The preprocessed biometric data is input into a generative AI model. The server uses the generative AI model to analyze the data and determine the user's emotional state. A deep learning algorithm is used as the generative AI model.

[0491] Input: Preprocessed biometric data

[0492] Output: Parsed emotional state

[0493] Step 5:

[0494] The server determines the user's emotional state based on the analyzed emotional state, such as "high stress," "happiness," or "sadness."

[0495] Input: Parsed emotional state

[0496] Output: Determined emotional state

[0497] Step 6:

[0498] If the user's emotional state is judged to be low, such as "sadness," the server sends an alert to the user saying, "Take a short break." At the same time, virtual scenery data for relaxation is sent to the smart glasses.

[0499] Input: Determined emotional state

[0500] Output: Break alert and virtual landscape data

[0501] Step 7:

[0502] Based on the virtual landscape data received by the smart glasses, augmented reality (AR) and virtual reality (VR) technologies are used to display a relaxation environment for the user, such as a beach or mountain landscape.

[0503] Input: Virtual landscape data

[0504] Output: The virtual relaxation environment seen by the user

[0505] Step 8:

[0506] The user uses the voice input function of the smart glasses to write an emotional diary.

[0507] Input: User voice input

[0508] Output: Emotion diary entries

[0509] Step 9:

[0510] The emotion diary entries are sent to a server and analyzed using natural language processing (NLP) technology. Specifically, the voice data is converted into text information, and the emotion diary is analyzed in detail.

[0511] Input: Emotional diary entry

[0512] Output: Parsed emotion diary

[0513] Step 10:

[0514] A user sends a request to join a social support group via a smartphone app.

[0515] Input: Join request

[0516] Output: Support group join request

[0517] Step 11:

[0518] The server receives the user's request and establishes a connection, allowing users to communicate with other users in real time.

[0519] Input: Join request

[0520] Output: Social support group connections

[0521] (Application example 1)

[0522] 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."

[0523] In modern society, people engaged in high-stress jobs, such as police officers and security guards, have difficulty understanding their rapidly fluctuating mental state in real time and receiving appropriate support. Furthermore, if stress and anxiety that arise during work cannot be properly managed, it can lead to serious accidents and reduced work efficiency. Concrete measures to resolve these issues and improve work safety and efficiency are needed.

[0524] 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.

[0525] In this invention, the server includes a device for collecting biometric information, a device with a generative model for analyzing the biometric information and determining the user's emotional state, a device for providing a relaxation environment to the user based on the emotional state, a device for entering and analyzing an emotion diary to respond to fluctuations in the emotional state, a device for connecting the user to a social support group, a device and processing means for monitoring the user's mental state while performing work and providing appropriate alerts, and a rendering means for providing the relaxation environment using VR technology.This allows the user's mental state to be understood in real time and an appropriate relaxation environment to be provided, enabling the user to safely and efficiently handle even high-stress work.

[0526] "Biometric information" refers to data related to the user's vital activities, such as heart rate, eye movement, and facial expression data.

[0527] A "generative model" refers to an algorithmic model that uses machine learning and artificial intelligence techniques to determine a user's emotional state.

[0528] A "relaxation environment" refers to an environment that provides virtual landscapes and fantastical places to promote mental stability for users.

[0529] An "emotion diary" refers to a system that records a user's emotional fluctuations and collects data for analysis.

[0530] A "social support group" refers to a group where multiple users communicate with each other, provide emotional support, and exchange information.

[0531] "Monitoring mental state during work performance" refers to monitoring the mental state of a user in real time while they are performing their work.

[0532] "Alert" refers to a system that provides important notifications to users, such as encouraging them to take a break.

[0533] "VR technology" refers to technology that uses virtual reality technology to allow users to experience an immersive virtual environment.

[0534] "Rendering means" refers to devices or software that generate virtual landscapes or fantasy locations using computer graphics techniques to visually represent virtual environments.

[0535] This invention is a system that collects biometric information and monitors the user's mental state in real time, supporting job performance in high-stress environments. Specifically, the system includes smart glasses, a server, network communications, a generative model, and a VR rendering means.

[0536] Biometric data collection

[0537] The device (here, smart glasses) is worn by the user. The smart glasses are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Each of these sensors collects biometric information such as the user's heart rate, eye movement, and facial expressions in real time.

[0538] Data transmission and analysis

[0539] The biometric information collected by the smart glasses is transmitted to a server via network communication. The server preprocesses the received data, removes noise, and normalizes the data. The preprocessed data is then input into a generative model to analyze the user's emotional state.

[0540] Emotional state assessment and relaxation environment provision

[0541] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[0542] Emotional diary entry and analysis

[0543] Users can use the smart glasses' voice input function to write down their emotions in a diary, which is then sent to a server and analyzed using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[0544] Connecting to social support groups

[0545] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[0546] Specific examples of programs

[0547] As a pre-processing step for biometric information, a Butterworth filter is applied to the heart rate data to remove noise. Data is transmitted via network communication (HTTP request), and the server uses a generative AI model to analyze the data. Additionally, a relaxation environment is provided when the emotional state is low, and is rendered using VR technology. As a specific example, the server analyzes the user's data using the following prompt:

[0548] Example prompt sentence:

[0549] "Analyze heart rate data: {heart rate data}, eye movement data: {eye movement data}, and facial expressions: {facial expressions} to determine the user's emotional state."

[0550] This system allows users to grasp their mental state in real time and provide an appropriate relaxation environment, enabling them to respond safely and efficiently to even high-stress work.

[0551] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0552] Step 1: Collecting biometric information

[0553] The user puts on the smart glasses. The smart glasses' heart rate sensor, eye movement tracking camera, and facial expression recognition camera are activated, collecting the user's heart rate, eye movement, and facial expression data in real time. This biometric information is temporarily stored in the recording media inside the smart glasses.

[0554] Input: User's heart rate, eye movement, and facial expression data

[0555] Output: Collected biometric information

[0556] Step 2: Sending data

[0557] The device (smart glasses) sends the collected biometric information to the server via network communication. Specifically, it uses an HTTP request to package the biometric information in JSON format and send it to a specified endpoint.

[0558] Input: Collected biometric information

[0559] Output: Data sent to the server

[0560] Step 3: Preprocessing the data

[0561] The server preprocesses the received biometric data. At this stage, noise removal and data normalization are performed. For example, a Butterworth filter is applied to heart rate data to remove noise. Eye movement data and facial expression data are also preprocessed in a similar way to prepare them for analysis.

[0562] Input: Data sent to the server

[0563] Output: Preprocessed biometric information

[0564] Step 4: Analyze emotional state

[0565] The server inputs the preprocessed biometric information into a generative model to analyze the user's emotional state. The generative AI model then comprehensively analyzes heart rate, eye movement, and facial expression data to determine the user's emotional state.

[0566] Input: Preprocessed biometric information

[0567] Output: User's emotional state

[0568] Step 5: Provide a Relaxation Environment

[0569] If the server analyzes the user's emotional state and determines that the user's mental state is low, it will send an alert urging the user to take a break. It also sends virtual landscape data for relaxation to the smart glasses, which then use augmented reality (AR) and virtual reality (VR) technology to display a relaxing environment.

[0570] Input: User's emotional state

[0571] Output: Alert and relaxation environment

[0572] Step 6: Emotional Diary

[0573] The user uses the voice input function of the smart glasses to write down their emotions in a diary, which is then sent to a server, where it analyzes the diary using natural language processing (NLP) technology to understand the user's emotional fluctuations.

[0574] Input: Emotion diary based on user voice input

[0575] Output: Analyzed emotion diary data

[0576] Step 7: Connect to social support groups

[0577] A user sends a request to join a social support group through a smartphone app. The server receives the request and establishes a connection, allowing users to communicate with other users in real time and exchange support and information.

[0578] Input: User's join request

[0579] Output: Connected social support groups

[0580] In this way, the system manages the user's mental state in real time and provides an appropriate relaxation environment and support, enabling them to cope with high-stress work safely and efficiently.

[0581] 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.

[0582] The present invention is a system that provides rapid, personalized support for patients with depression and other mental health conditions. The system uses devices such as smart glasses to collect biometric information in real time and analyzes it with a generative model combined with an emotion engine to determine the user's emotional state. Specific embodiments are described below.

[0583] Biometric data collection

[0584] The user wears smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, allowing the glasses to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[0585] Data transmission and analysis

[0586] The biometric information collected by the smart glasses is sent to a server via network communication. The server preprocesses the received data, removing noise and normalizing it. The preprocessed data is then input into a generative model combined with an emotion engine to analyze the user's emotional state.

[0587] Emotional state assessment and feedback

[0588] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[0589] Emotional diary entry and analysis

[0590] Users can use the smart glasses' voice input function to write down their emotions in a diary. The diary entries are sent to a server where an emotion engine analyzes them using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[0591] Connecting to social support groups

[0592] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[0593] Specific examples

[0594] For example, when a user puts on smart glasses in the morning, it is measured that their heart rate is higher than normal, their eye movements are erratic, and their facial expression is sad. This data is sent to the server, where it is analyzed using a generative model combined with an emotion engine, and it is determined that the user is feeling stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters in their emotion diary by voice, "I was stressed this morning, but I was able to relax on the virtual beach." This diary entry is then analyzed by the server and recorded as emotional fluctuations.

[0595] This allows the present invention to manage the user's emotional state in real time and provide appropriate support. Furthermore, the use of an emotion engine enables more accurate emotion recognition and feedback, thereby effectively supporting the user's mental health.

[0596] The processing flow will be explained below.

[0597] Step 1:

[0598] The user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial recognition camera, so once they are put on, they are ready to go.

[0599] Step 2:

[0600] The smart glasses measure heart rate data by using a heart rate sensor to measure the user's heart rate in real time and temporarily store this data in an internal buffer.

[0601] Step 3:

[0602] Smart glasses collect eye movement data. A built-in tracking camera captures the user's eye movements, analyzes them, and stores them as data.

[0603] Step 4:

[0604] The smart glasses analyze facial expression data. Using a facial recognition camera, they analyze the user's facial muscle movements and convert their current facial expression into digital data and store it.

[0605] Step 5:

[0606] The smart glasses transmit biometric information (heart rate data, eye movement data, facial expression data) to a server. The data is transferred to the server via a network using a secure communication protocol (e.g., HTTPS).

[0607] Step 6:

[0608] The server preprocesses the received biometric information, including noise removal and data normalization, to make it suitable for analysis.

[0609] Step 7:

[0610] The server inputs the preprocessed data into a generative model to analyze the user's emotional state. The generative AI model evaluates the data and determines the user's emotional state (e.g., stressed, relaxed, tired, etc.).

[0611] Step 8:

[0612] The server checks the analysis results with the emotion engine and updates the emotional state in real time. The emotion engine performs additional data analysis and provides immediate feedback on the user's emotional state.

[0613] Step 9:

[0614] The server determines the user's emotional state and sends an alert to encourage them to take a break if necessary. If the user's emotional state falls below a defined threshold, the server sends the user an alert message telling them to take a break.

[0615] Step 10:

[0616] The server prepares relaxation environment data for AR / VR and sends it to the smart glasses, providing relaxation data such as virtual beach scenes or forest scenes to the smart glasses.

[0617] Step 11:

[0618] The smart glasses display the received virtual landscape data, utilizing AR / VR technology to provide virtual landscapes and fantastical places for users to relax.

[0619] Step 12:

[0620] Users write their emotional diary using voice input. Using the voice input function of the smart glasses, they record their emotions and experiences for the day.

[0621] Step 13:

[0622] The smart glasses convert the voice-input emotion diary into digital data and send it to the server, where it is transferred as text data.

[0623] Step 14:

[0624] The server analyzes the emotion diary data, and the emotion engine uses natural language processing (NLP) technology to analyze it and understand the user's emotional fluctuations.

[0625] Step 15:

[0626] Users connect to a social support group through a smartphone app. The user sends a request to join within the app, which is received by the server.

[0627] Step 16:

[0628] The server processes your join request and establishes a connection with your social support group, allowing you to communicate in real time.

[0629] Step 17:

[0630] Users can communicate with other users in real time and receive information and support within social support groups.

[0631] Example 2

[0632] 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."

[0633] Existing technologies include systems that collect and analyze biometric data to determine a user's emotional state, but these systems often lack the ability to collect and provide feedback in real time. Furthermore, they lack detailed analysis of the user's emotional fluctuations and integration with social support, limiting their ability to effectively support the user's mental health. This invention aims to provide comprehensive mental health care by continuously monitoring a user's emotional state in real time, providing an appropriate relaxation environment, analyzing emotional records, and facilitating connection to social support groups.

[0634] 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.

[0635] In this invention, the server includes a means for collecting biometric data, a means for providing a generative artificial intelligence model for analyzing the biometric data and determining the user's emotional state, a means for providing a relaxation environment to the user based on the emotional state, a means for recording and analyzing an emotional log to respond to fluctuations in the emotional state, and a means for connecting the user to a social support group, thereby enabling real-time monitoring and analysis of the emotional state and providing appropriate feedback and comprehensive mental health support.

[0636] "Biometric data" refers to data that indicates the user's physical condition, including heart rate, eye movement data, and facial expression data.

[0637] "Generative AI models" refer to algorithms or machine learning models that analyze a user's biometric data and determine their emotional state.

[0638] A "relaxation environment" refers to an environment in which users can relax by providing virtual landscapes and fantastical places using augmented reality and virtual reality technologies.

[0639] "Emotion records" record fluctuations in a user's emotional state and refer to data collected through voice and text input.

[0640] A "social support group" refers to a group of other users and supporters with whom a user can receive emotional support through real-time communication.

[0641] The present invention relates to a system for collecting a user's biological data in real time, analyzing the user's emotional state based on the collected data, providing an appropriate relaxation environment, and analyzing the emotional record.

[0642] Biometric data collection

[0643] The user wears a device called smart glasses, which collects biometric data. The smart glasses are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, and these sensors are used to collect biometric data such as heart rate, eye movement, and facial expressions in real time. The collected data is temporarily stored in the smart glasses and is sent to a server once it is ready.

[0644] Data transmission and analysis

[0645] The biometric data collected by the smart glasses is sent to a server via network communication. The server first preprocesses the received data, removing noise and normalizing it. After preprocessing is complete, the data is input into a generative AI model (such as OpenAI's GPT-3) that combines an emotion engine to analyze the user's emotional state.

[0646] Providing a relaxing environment

[0647] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. It also sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[0648] Emotional record entry and analysis

[0649] Users can record their emotions using the smart glasses' voice input function. The recorded emotion record is then sent to a server via the network. The server receives the record and an emotion engine analyzes it using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[0650] Connecting to social support groups

[0651] Users can join social support groups through a smartphone app. The server receives the join request and establishes a connection with the group, allowing users to communicate with other users in real time and receive social support.

[0652] Specific examples

[0653] For example, when a user puts on smart glasses in the morning, it detects that their heart rate is higher than normal, their eye movements are erratic, and their facial expression looks sad. This data is sent to the server, where it is analyzed by a generative AI model combined with an emotion engine, and it is determined that the user is feeling stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters the following in their emotion log by voice: "The morning was stressful, but I was able to relax on the virtual beach." These records are then analyzed by the server and recorded as emotional fluctuations.

[0654] Example prompts for generative AI models

[0655] Prompt: "Please describe in detail how you would analyze the user's emotional state and provide appropriate feedback."

[0656] This allows the present invention to manage the user's emotional state in real time and provide appropriate support. Furthermore, the use of an emotion engine enables more accurate emotion recognition and feedback, thereby effectively supporting the user's mental health.

[0657] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0658] Step 1:

[0659] The user wears the smart glasses, which collect biometric data (heart rate, eye movement data, facial expression data) in real time. The input is various biometric signals from the smart glasses' sensors, and the output is biometric data that is temporarily stored in the smart glasses. Specifically, the heart rate sensor detects the heart rate, the tracking camera captures eye movement, and the facial expression recognition camera analyzes facial expressions.

[0660] Step 2:

[0661] The biometric data collected by the smart glasses is sent to a server via network communication. The input is the biometric data stored in the smart glasses, and the output is the data sent to the server. Specifically, the smart glasses upload the data to the server in real time using Wi-Fi or Bluetooth.

[0662] Step 3:

[0663] The server preprocesses the received biometric data. The input is the received biometric data, and the output is preprocessed data that has been subjected to noise removal and normalization. Specifically, the server uses a filtering algorithm to remove noise and normalize the scale of the data, converting the data into a format suitable for the analysis model.

[0664] Step 4:

[0665] The server inputs the preprocessed data into a generative AI model combined with an emotion engine to analyze the user's emotional state. The input is the preprocessed data, and the output is the analyzed emotional state. Specifically, a generative AI model (e.g., GPT-3) is used to analyze the user's emotions from the data, and the results are returned to the server.

[0666] Step 5:

[0667] The server determines the user's emotional state based on the analysis results. If the emotional state is determined to be low, the server sends an alert encouraging the user to take a break. The input is the emotion analysis result from the generative AI model, and the output is an alert sent to the user and virtual scenery data necessary for relaxation. Specifically, the server determines that the user is "high stress" and sends scenery data of a virtual beach to the smart glasses along with a message such as "take a break."

[0668] Step 6:

[0669] Based on the virtual landscape data received by the smart glasses, a relaxing environment is displayed using augmented reality (AR) and virtual reality (VR) technology. The input is the virtual landscape data sent from the server, and the output is the display of the relaxing environment. Specifically, the smart glasses display the virtual landscape on a visual display, encouraging the user to relax.

[0670] Step 7:

[0671] The user uses the voice input function of the smart glasses to record their emotions. The input is the user's voice command, and the output is sent to the server as voice data. Specifically, the user might say, "I had a stressful morning, but I was able to relax on the virtual beach," and the smart glasses would analyze this as voice data and send it to the server.

[0672] Step 8:

[0673] The server receives the transmitted emotion record, and the emotion engine analyzes the record using natural language processing (NLP) technology. The input is voice data, and the output is analyzed emotion fluctuation data. Specifically, the server converts the voice data into text, analyzes the emotion record using NLP technology, and records the user's emotional fluctuations.

[0674] Step 9:

[0675] A user joins a social support group through a smartphone app. The input is the user's join request, and the output is permission to connect to the group. Specifically, the server accepts the join request and provides group connection information to the user's smartphone app, allowing the user to communicate with other group members in real time.

[0676] (Application example 2)

[0677] 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."

[0678] Delivery workers, including food delivery workers, are often exposed to long working hours and stress, which can have a negative impact on their work efficiency and health. Currently, there is a lack of a system that monitors worker stress and fatigue in real time and provides appropriate support, so quick and effective measures are needed.

[0679] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0680] In this invention, the server includes means for collecting biometric information, means for providing a generative model for analyzing emotional states, means for providing a relaxation environment to a user, means for recording and analyzing an emotional diary, means for connecting the user to a social support group, and means for use by delivery workers to monitor the fatigue and stress of the worker in real time and provide a rest and relaxation environment as needed, thereby managing the stress and fatigue of the worker and improving their work efficiency and health.

[0681] "Biometric information" refers to information for understanding the user's physical condition, such as the user's heart rate, eye movement, and facial expression data.

[0682] A "generative model" is a model for analyzing collected biometric information and determining the user's emotional state.

[0683] A "relaxation environment" is an environment that uses AR and VR technology to provide virtual landscapes and fantastical places to help users relax.

[0684] An "emotion diary" is a tool that allows users to record fluctuations in their emotional state.

[0685] A "social support group" is a group where users can communicate with other users in real time and receive emotional support.

[0686] "Delivery work" refers to the work that a user does to deliver a product to a recipient.

[0687] A "worker" is a user who is engaged in delivery work.

[0688] "Real-time" refers to processing or responding with minimal delay.

[0689] "Monitoring" is the act of continuously observing and recording specific information or conditions.

[0690] A "break" refers to a temporary interruption of work by a user to restore physical or mental strength.

[0691] The present invention provides a system for managing stress and fatigue of delivery workers, thereby improving their work efficiency and health. Specific embodiments for carrying out the present invention will be described below.

[0692] Biometric data collection

[0693] The device (smart glasses) is equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Using these sensors, the device collects biometric information such as heart rate, eye movement, and facial expressions in real time. This collected data is sent to a server via network communication.

[0694] Data preprocessing and analysis

[0695] On the server side, after receiving the biometric information, preprocessing such as noise removal and data normalization is performed. The preprocessed data is then input into a generative model equipped with an emotion engine to analyze the user's emotional state. This generative model combines the diverse data collected to accurately determine the user's stress and fatigue state.

[0696] Emotional state assessment and feedback

[0697] The server uses an emotion engine to analyze the user's emotional state, and if it determines that the user is experiencing high levels of stress or fatigue, it sends an alert to the device urging them to take a break. At the same time, relaxing virtual landscape data (e.g., a beach scene) is sent to the device, providing the user with a relaxation environment using AR and VR technology.

[0698] Emotional diary entry and analysis

[0699] Users can use the smart glasses to write their emotional diary using voice input, and this diary data is also sent to a server where it is analyzed using natural language processing (NLP) technology, allowing continuous fluctuations in the user's emotional state to be understood.

[0700] Connecting to social support groups

[0701] Users can join social support groups through a smartphone app, where they can communicate with other workers in real time, offering mutual comfort and information exchange, thereby enhancing psychological support.

[0702] Specific examples

[0703] For example, if a delivery person exhibits biometric information such as a high heart rate, unstable eye movements, and a stern expression while making a delivery, the server will analyze this with its emotion engine and determine that the delivery person is experiencing high stress. The server will immediately send an alert to the device urging them to take a break, and at the same time display a relaxing virtual beach scene on the device. The delivery person will enter an emotion diary entry by saying, "Today was busy and stressful, but I was able to relax on the beach," and the diary data will be analyzed and recorded on the server.

[0704] Example prompt for a generative AI model:

[0705] "Analyze the following text to determine the user's emotional state: 'Today was busy, but I was able to relax on the beach during my break.'"

[0706] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0707] Step 1:

[0708] The terminal collects the user's biometric information.

[0709] Specifically, the device's built-in heart rate sensor, eye movement tracking camera, and facial expression recognition camera measure and collect heart rate, eye movement, and facial expression data in real time, respectively.

[0710] Input: User's biometric information (heart rate, eye movement, facial expression data)

[0711] Output: Collected biometric data

[0712] Step 2:

[0713] The terminal transmits the collected biometric information to the server.

[0714] Specifically, the terminal transmits the collected biometric information data to a server via network communication.

[0715] Input: Collected biometric data

[0716] Output: Biometric data sent to the server

[0717] Step 3:

[0718] The server preprocesses the received biometric data.

[0719] Specifically, we perform preprocessing to improve the accuracy of the analysis by removing noise and normalizing the data. We use a median filter for noise removal and an appropriate scaling method for data normalization.

[0720] Input: Biometric data sent to the server

[0721] Output: Preprocessed biometric data

[0722] Step 4:

[0723] The server inputs the preprocessed biometric data into a generative model to analyze the user's emotional state.

[0724] Specifically, a generative AI model combined with an emotion engine is used to determine the user's stress level and fatigue level from biometric data.

[0725] Input: Preprocessed biometric data

[0726] Output: User's emotional state (e.g., stress level, high / low)

[0727] Step 5:

[0728] The server generates feedback based on the analysis results.

[0729] Specifically, if the user shows signs of high stress or fatigue, an alert is generated to encourage them to take a break, and virtual scenery data (e.g., a beach scene) is also provided.

[0730] Input: User's emotional state (stress level)

[0731] Output: Break alert, virtual landscape data

[0732] Step 6:

[0733] The terminal receives the feedback from the server and displays it to the user.

[0734] Specifically, the system will notify users with an alert encouraging them to take a break, and will use virtual landscape data to display a relaxation environment using AR and VR technology.

[0735] Input: Break alerts, virtual landscape data

[0736] Output: Alert to user, display of relaxation environment

[0737] Step 7:

[0738] The user writes an emotion diary using voice input.

[0739] Specifically, users use the voice input function of the smart glasses to record their emotional state and the events of the day.

[0740] Input: Audio data of the user's emotion diary

[0741] Output: Emotion diary written by voice

[0742] Step 8:

[0743] The emotion diary data is sent to a server, which analyzes it using natural language processing (NLP) technology.

[0744] Specifically, text data is generated from voice data, and this is analyzed using an NLP model to record fluctuations in the user's emotions.

[0745] Input: Emotional diary written by voice

[0746] Output: Analyzed emotional state data and its fluctuations

[0747] Step 9:

[0748] Users connect to social support groups.

[0749] Specifically, users join support groups through a smartphone app and communicate with other users in real time. The server receives connection requests and establishes the connections.

[0750] Input: A user's connection request

[0751] Output: Connection established to a social support group

[0752] 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.

[0753] 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.

[0754] 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.

[0755] [Third embodiment]

[0756] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0757] 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.

[0758] 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).

[0759] 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.

[0760] 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.

[0761] 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).

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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."

[0768] The present invention provides a system for providing rapid, personalized support to patients with depression and other mental health conditions. The system uses devices such as smart glasses to collect biometric information in real time and analyzes it with a generative model to determine the user's emotional state. Specific embodiments are described below.

[0769] Biometric data collection

[0770] The user wears smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, allowing the glasses to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[0771] Data transmission and analysis

[0772] The biometric information collected by the smart glasses is transmitted to a server via network communication. The server preprocesses the received data, removing noise and normalizing it. The preprocessed data is then input into a generative model to analyze the user's emotional state.

[0773] Emotional state assessment and relaxation environment provision

[0774] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[0775] Emotional diary entry and analysis

[0776] Users can use the smart glasses' voice input function to write down their emotions in a diary, which is then sent to a server and analyzed using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[0777] Connecting to social support groups

[0778] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[0779] Specific examples

[0780] For example, when a user puts on smart glasses in the morning, their heart rate is measured to be higher than normal, their eye movements are erratic, and their facial expression is sad. This data is sent to the server, where it is analyzed by a generative model and determined to be stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters in their emotion diary by voice, "This morning was stressful, but I was able to relax on the virtual beach." This diary entry is then analyzed by the server and recorded as emotional fluctuations.

[0781] This allows the present invention to manage the user's emotional state in real time and provide appropriate support.

[0782] The processing flow will be explained below.

[0783] Step 1:

[0784] The user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial recognition camera, so once they are put on, they are ready to go.

[0785] Step 2:

[0786] The smart glasses measure heart rate data by using a heart rate sensor to measure the user's heart rate in real time and temporarily store this data in an internal buffer.

[0787] Step 3:

[0788] Smart glasses collect eye movement data. A built-in tracking camera captures the user's eye movements, analyzes them, and stores them as data.

[0789] Step 4:

[0790] The smart glasses analyze facial expression data. Using a facial recognition camera, they analyze the user's facial muscle movements and convert their current facial expression into digital data and store it.

[0791] Step 5:

[0792] The smart glasses transmit biometric information (heart rate data, eye movement data, facial expression data) to a server. The data is transferred to the server via a network using a secure communication protocol (e.g., HTTPS).

[0793] Step 6:

[0794] The server preprocesses the received biometric information, including noise removal and data normalization, to make it suitable for analysis.

[0795] Step 7:

[0796] The server inputs the preprocessed data into a generative model to analyze the user's emotional state. The generative AI model evaluates the data and determines the user's emotional state (e.g., stressed, relaxed, tired, etc.).

[0797] Step 8:

[0798] The server determines the user's emotional state and sends an alert to encourage them to take a break if necessary. If the user's emotional state falls below a defined threshold, the server sends the user an alert message telling them to take a break.

[0799] Step 9:

[0800] The server prepares relaxation environment data for AR / VR and sends it to the smart glasses, providing relaxation data such as virtual beach scenes or forest scenes to the smart glasses.

[0801] Step 10:

[0802] The smart glasses display the received virtual landscape data, utilizing AR / VR technology to provide virtual landscapes and fantastical places for users to relax.

[0803] Step 11:

[0804] Users write their emotional diary using voice input. Using the voice input function of the smart glasses, they record their emotions and experiences for the day.

[0805] Step 12:

[0806] The smart glasses convert the voice-input emotion diary into digital data and send it to the server, where it is transferred as text data.

[0807] Step 13:

[0808] The server analyzes the emotion diary data and uses natural language processing (NLP) technology to understand and record the user's emotional fluctuations.

[0809] Step 14:

[0810] Users connect to a social support group through a smartphone app. The user sends a request to join within the app, which is received by the server.

[0811] Step 15:

[0812] The server processes your join request and establishes a connection with your social support group, allowing you to communicate in real time.

[0813] Step 16:

[0814] Users can communicate with other users in real time and receive information and support within social support groups.

[0815] Example 1

[0816] 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."

[0817] In recent years, there has been a demand for rapid and personalized support for patients with depression and other mental health conditions. However, conventional mental health care systems have had difficulty accurately grasping users' emotional states in real time and providing immediate, appropriate support. In addition, the utilization of emotional diaries and social support groups has not been fully realized, resulting in delays in providing measures tailored to each user's individual situation.

[0818] 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.

[0819] In this invention, the server includes a means for transmitting biometric information via a network, a means for preprocessing and noise reduction of the received biometric information, and a means for analyzing the preprocessed biometric information using a generative AI model to determine the user's emotional state. This allows for accurate understanding of the user's emotional state in real time, enabling the immediate provision of an appropriate relaxation environment and analysis of an emotional diary entry. Furthermore, by connecting the user to a social support group, psychological support is enhanced.

[0820] "Biometric information" is data obtained from the user's body, and includes heart rate, eye movement, facial expression data, and the like.

[0821] "Network communications" refers to internet connections and wireless communication technologies (such as Wi-Fi and Bluetooth) for sending and receiving data.

[0822] "Preprocessing" refers to the process of removing noise from the received biometric information and normalizing the data to make it analyzable.

[0823] "Noise removal" is a process of removing unnecessary data and errors from collected biometric information.

[0824] A "generative AI model" is a model that uses deep learning or machine learning algorithms to analyze data and is used to determine a user's emotional state.

[0825] An "emotional state" is a psychological state that a user is feeling, and may include stress, happiness, sadness, etc.

[0826] A "relaxation environment" is a virtual landscape or fantasy place that promotes mental relaxation for users, and is provided using augmented reality (AR) and virtual reality (VR) technologies.

[0827] An "emotion diary" is a diary in which users record their emotional fluctuations and state. It is written using voice input and analyzed using natural language processing technology.

[0828] "Natural language processing technology" is a technology that converts voice data into text information and analyzes its content.

[0829] A "social support group" is a group in which users can participate and communicate with other users to receive emotional support and exchange information.

[0830] The present invention is a system for providing prompt and personalized support to patients with depression and other mental health conditions. An embodiment of the system will be described in detail below.

[0831] First, the user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Using these sensors and cameras, the smart glasses collect biometric information such as the user's heart rate, eye movement, and facial expressions in real time.

[0832] Once biometric information is collected, the smart glasses send it to a server via network communication (Wi-Fi or Bluetooth). The biometric information received by the server is first preprocessed. Preprocessing includes noise reduction and data normalization. Noise reduction removes unnecessary data, and data normalization standardizes the scale of the data.

[0833] The preprocessed data is input into a generative AI model. The server uses this generative AI model to analyze the user's emotional state. Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, virtual scenery data for relaxation is also sent to the smart glasses.

[0834] Based on the virtual landscape data received by the smart glasses, the glasses use augmented reality (AR) and virtual reality (VR) technology to display a relaxing virtual environment for the user, such as a beach or mountain landscape, allowing the user to refresh in a virtual relaxation environment.

[0835] Furthermore, users can use the smart glasses' voice input function to write an emotional diary, which is then sent to a server where it is analyzed using natural language processing (NLP) technology to analyze emotional fluctuations in detail.

[0836] Finally, users can join social support groups through a smartphone app. The server receives the join request and establishes a connection. This connection allows users to communicate with other users in real time and provide emotional support.

[0837] Specific examples

[0838] For example, suppose a user wears smart glasses in the morning, and the heart rate sensor measures a heart rate of 90 beats per minute, the eye movement tracking camera detects frequent eye movements, and the facial expression recognition camera analyzes sad facial expressions. This data is sent to the server, where noise removal and data normalization are performed. The data is then input into a generative AI model to determine that the user is in a stressed state. The server then sends the user an alert saying, "Take a short break," and displays a virtual beach scene on the smart glasses. After relaxing on the virtual beach, the user writes in their emotion diary by voice input, "I was stressed this morning, but I was able to relax on the virtual beach." This diary is analyzed by the server and recorded as emotional fluctuations.

[0839] Prompt Sentence Examples

[0840] "Please explain how a system where a user wears smart glasses collects biometric information (heart rate, eye movements, facial expressions) and sends it to a server for analysis to determine the user's emotional state and provide appropriate support."

[0841] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0842] Step 1:

[0843] The user wears smart glasses, which use built-in heart rate sensors, eye movement tracking cameras, and facial expression recognition cameras to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[0844] Input: User's biometric information (heart rate, eye movement, facial expression)

[0845] Output: Collected biometric data

[0846] Step 2:

[0847] The biometric information collected by the smart glasses is sent to a server via a network, specifically using Wi-Fi or Bluetooth.

[0848] Input: Collected biometric data

[0849] Output: Biometric data sent to the server

[0850] Step 3:

[0851] The server preprocesses the received biometric data, which includes noise removal and data normalization to improve data quality and make it suitable for analysis.

[0852] Input: Biometric data sent to the server

[0853] Output: Preprocessed biometric data

[0854] Step 4:

[0855] The preprocessed biometric data is input into a generative AI model. The server uses the generative AI model to analyze the data and determine the user's emotional state. A deep learning algorithm is used as the generative AI model.

[0856] Input: Preprocessed biometric data

[0857] Output: Parsed emotional state

[0858] Step 5:

[0859] The server determines the user's emotional state based on the analyzed emotional state, such as "high stress," "happiness," or "sadness."

[0860] Input: Parsed emotional state

[0861] Output: Determined emotional state

[0862] Step 6:

[0863] If the user's emotional state is judged to be low, such as "sadness," the server sends an alert to the user saying, "Take a short break." At the same time, virtual scenery data for relaxation is sent to the smart glasses.

[0864] Input: Determined emotional state

[0865] Output: Break alert and virtual landscape data

[0866] Step 7:

[0867] Based on the virtual landscape data received by the smart glasses, augmented reality (AR) and virtual reality (VR) technologies are used to display a relaxation environment for the user, such as a beach or mountain landscape.

[0868] Input: Virtual landscape data

[0869] Output: The virtual relaxation environment seen by the user

[0870] Step 8:

[0871] The user uses the voice input function of the smart glasses to write an emotional diary.

[0872] Input: User voice input

[0873] Output: Emotion diary entries

[0874] Step 9:

[0875] The emotion diary entries are sent to a server and analyzed using natural language processing (NLP) technology. Specifically, the voice data is converted into text information, and the emotion diary is analyzed in detail.

[0876] Input: Emotional diary entry

[0877] Output: Parsed emotion diary

[0878] Step 10:

[0879] A user sends a request to join a social support group via a smartphone app.

[0880] Input: Join request

[0881] Output: Support group join request

[0882] Step 11:

[0883] The server receives the user's request and establishes a connection, allowing users to communicate with other users in real time.

[0884] Input: Join request

[0885] Output: Social support group connections

[0886] (Application example 1)

[0887] 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."

[0888] In modern society, people engaged in high-stress jobs, such as police officers and security guards, have difficulty understanding their rapidly fluctuating mental state in real time and receiving appropriate support. Furthermore, if stress and anxiety that arise during work cannot be properly managed, it can lead to serious accidents and reduced work efficiency. Concrete measures to resolve these issues and improve work safety and efficiency are needed.

[0889] 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.

[0890] In this invention, the server includes a device for collecting biometric information, a device with a generative model for analyzing the biometric information and determining the user's emotional state, a device for providing a relaxation environment to the user based on the emotional state, a device for entering and analyzing an emotion diary to respond to fluctuations in the emotional state, a device for connecting the user to a social support group, a device and processing means for monitoring the user's mental state while performing work and providing appropriate alerts, and a rendering means for providing the relaxation environment using VR technology.This allows the user's mental state to be understood in real time and an appropriate relaxation environment to be provided, enabling the user to safely and efficiently handle even high-stress work.

[0891] "Biometric information" refers to data related to the user's vital activities, such as heart rate, eye movement, and facial expression data.

[0892] A "generative model" refers to an algorithmic model that uses machine learning and artificial intelligence techniques to determine a user's emotional state.

[0893] A "relaxation environment" refers to an environment that provides virtual landscapes and fantastical places to promote mental stability for users.

[0894] An "emotion diary" refers to a system that records a user's emotional fluctuations and collects data for analysis.

[0895] A "social support group" refers to a group where multiple users communicate with each other, provide emotional support, and exchange information.

[0896] "Monitoring mental state during work performance" refers to monitoring the mental state of a user in real time while they are performing their work.

[0897] "Alert" refers to a system that provides important notifications to users, such as encouraging them to take a break.

[0898] "VR technology" refers to technology that uses virtual reality technology to allow users to experience an immersive virtual environment.

[0899] "Rendering means" refers to devices or software that generate virtual landscapes or fantasy locations using computer graphics techniques to visually represent virtual environments.

[0900] This invention is a system that collects biometric information and monitors the user's mental state in real time, supporting job performance in high-stress environments. Specifically, the system includes smart glasses, a server, network communications, a generative model, and a VR rendering means.

[0901] Biometric data collection

[0902] The device (here, smart glasses) is worn by the user. The smart glasses are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Each of these sensors collects biometric information such as the user's heart rate, eye movement, and facial expressions in real time.

[0903] Data transmission and analysis

[0904] The biometric information collected by the smart glasses is transmitted to a server via network communication. The server preprocesses the received data, removes noise, and normalizes the data. The preprocessed data is then input into a generative model to analyze the user's emotional state.

[0905] Emotional state assessment and relaxation environment provision

[0906] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[0907] Emotional diary entry and analysis

[0908] Users can use the smart glasses' voice input function to write down their emotions in a diary, which is then sent to a server and analyzed using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[0909] Connecting to social support groups

[0910] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[0911] Specific examples of programs

[0912] As a pre-processing step for biometric information, a Butterworth filter is applied to the heart rate data to remove noise. Data is transmitted via network communication (HTTP request), and the server uses a generative AI model to analyze the data. Additionally, a relaxation environment is provided when the emotional state is low, and is rendered using VR technology. As a specific example, the server analyzes the user's data using the following prompt:

[0913] Example prompt sentence:

[0914] "Analyze heart rate data: {heart rate data}, eye movement data: {eye movement data}, and facial expressions: {facial expressions} to determine the user's emotional state."

[0915] This system allows users to grasp their mental state in real time and provide an appropriate relaxation environment, enabling them to respond safely and efficiently to even high-stress work.

[0916] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0917] Step 1: Collecting biometric information

[0918] The user puts on the smart glasses. The smart glasses' heart rate sensor, eye movement tracking camera, and facial expression recognition camera are activated, collecting the user's heart rate, eye movement, and facial expression data in real time. This biometric information is temporarily stored in the recording media inside the smart glasses.

[0919] Input: User's heart rate, eye movement, and facial expression data

[0920] Output: Collected biometric information

[0921] Step 2: Sending data

[0922] The device (smart glasses) sends the collected biometric information to the server via network communication. Specifically, it uses an HTTP request to package the biometric information in JSON format and send it to a specified endpoint.

[0923] Input: Collected biometric information

[0924] Output: Data sent to the server

[0925] Step 3: Preprocessing the data

[0926] The server preprocesses the received biometric data. At this stage, noise removal and data normalization are performed. For example, a Butterworth filter is applied to heart rate data to remove noise. Eye movement data and facial expression data are also preprocessed in a similar way to prepare them for analysis.

[0927] Input: Data sent to the server

[0928] Output: Preprocessed biometric information

[0929] Step 4: Analyze emotional state

[0930] The server inputs the preprocessed biometric information into a generative model to analyze the user's emotional state. The generative AI model then comprehensively analyzes heart rate, eye movement, and facial expression data to determine the user's emotional state.

[0931] Input: Preprocessed biometric information

[0932] Output: User's emotional state

[0933] Step 5: Provide a Relaxation Environment

[0934] If the server analyzes the user's emotional state and determines that the user's mental state is low, it will send an alert urging the user to take a break. It also sends virtual landscape data for relaxation to the smart glasses, which then use augmented reality (AR) and virtual reality (VR) technology to display a relaxing environment.

[0935] Input: User's emotional state

[0936] Output: Alert and relaxation environment

[0937] Step 6: Emotional Diary

[0938] The user uses the voice input function of the smart glasses to write down their emotions in a diary, which is then sent to a server, where it analyzes the diary using natural language processing (NLP) technology to understand the user's emotional fluctuations.

[0939] Input: Emotion diary based on user voice input

[0940] Output: Analyzed emotion diary data

[0941] Step 7: Connect to social support groups

[0942] A user sends a request to join a social support group through a smartphone app. The server receives the request and establishes a connection, allowing users to communicate with other users in real time and exchange support and information.

[0943] Input: User's join request

[0944] Output: Connected social support groups

[0945] In this way, the system manages the user's mental state in real time and provides an appropriate relaxation environment and support, enabling them to cope with high-stress work safely and efficiently.

[0946] 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.

[0947] The present invention is a system that provides rapid, personalized support for patients with depression and other mental health conditions. The system uses devices such as smart glasses to collect biometric information in real time and analyzes it with a generative model combined with an emotion engine to determine the user's emotional state. Specific embodiments are described below.

[0948] Biometric data collection

[0949] The user wears smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, allowing the glasses to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[0950] Data transmission and analysis

[0951] The biometric information collected by the smart glasses is sent to a server via network communication. The server preprocesses the received data, removing noise and normalizing it. The preprocessed data is then input into a generative model combined with an emotion engine to analyze the user's emotional state.

[0952] Emotional state assessment and feedback

[0953] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[0954] Emotional diary entry and analysis

[0955] Users can use the smart glasses' voice input function to write down their emotions in a diary. The diary entries are sent to a server where an emotion engine analyzes them using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[0956] Connecting to social support groups

[0957] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[0958] Specific examples

[0959] For example, when a user puts on smart glasses in the morning, it is measured that their heart rate is higher than normal, their eye movements are erratic, and their facial expression is sad. This data is sent to the server, where it is analyzed using a generative model combined with an emotion engine, and it is determined that the user is feeling stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters in their emotion diary by voice, "I was stressed this morning, but I was able to relax on the virtual beach." This diary entry is then analyzed by the server and recorded as emotional fluctuations.

[0960] This allows the present invention to manage the user's emotional state in real time and provide appropriate support. Furthermore, the use of an emotion engine enables more accurate emotion recognition and feedback, thereby effectively supporting the user's mental health.

[0961] The processing flow will be explained below.

[0962] Step 1:

[0963] The user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial recognition camera, so once they are put on, they are ready to go.

[0964] Step 2:

[0965] The smart glasses measure heart rate data by using a heart rate sensor to measure the user's heart rate in real time and temporarily store this data in an internal buffer.

[0966] Step 3:

[0967] Smart glasses collect eye movement data. A built-in tracking camera captures the user's eye movements, analyzes them, and stores them as data.

[0968] Step 4:

[0969] The smart glasses analyze facial expression data. Using a facial recognition camera, they analyze the user's facial muscle movements and convert their current facial expression into digital data and store it.

[0970] Step 5:

[0971] The smart glasses transmit biometric information (heart rate data, eye movement data, facial expression data) to a server. The data is transferred to the server via a network using a secure communication protocol (e.g., HTTPS).

[0972] Step 6:

[0973] The server preprocesses the received biometric information, including noise removal and data normalization, to make it suitable for analysis.

[0974] Step 7:

[0975] The server inputs the preprocessed data into a generative model to analyze the user's emotional state. The generative AI model evaluates the data and determines the user's emotional state (e.g., stressed, relaxed, tired, etc.).

[0976] Step 8:

[0977] The server checks the analysis results with the emotion engine and updates the emotional state in real time. The emotion engine performs additional data analysis and provides immediate feedback on the user's emotional state.

[0978] Step 9:

[0979] The server determines the user's emotional state and sends an alert to encourage them to take a break if necessary. If the user's emotional state falls below a defined threshold, the server sends the user an alert message telling them to take a break.

[0980] Step 10:

[0981] The server prepares relaxation environment data for AR / VR and sends it to the smart glasses, providing relaxation data such as virtual beach scenes or forest scenes to the smart glasses.

[0982] Step 11:

[0983] The smart glasses display the received virtual landscape data, utilizing AR / VR technology to provide virtual landscapes and fantastical places for users to relax.

[0984] Step 12:

[0985] Users write their emotional diary using voice input. Using the voice input function of the smart glasses, they record their emotions and experiences for the day.

[0986] Step 13:

[0987] The smart glasses convert the voice-input emotion diary into digital data and send it to the server, where it is transferred as text data.

[0988] Step 14:

[0989] The server analyzes the emotion diary data, and the emotion engine uses natural language processing (NLP) technology to analyze it and understand the user's emotional fluctuations.

[0990] Step 15:

[0991] Users connect to a social support group through a smartphone app. The user sends a request to join within the app, which is received by the server.

[0992] Step 16:

[0993] The server processes your join request and establishes a connection with your social support group, allowing you to communicate in real time.

[0994] Step 17:

[0995] Users can communicate with other users in real time and receive information and support within social support groups.

[0996] Example 2

[0997] 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."

[0998] Existing technologies include systems that collect and analyze biometric data to determine a user's emotional state, but these systems often lack the ability to collect and provide feedback in real time. Furthermore, they lack detailed analysis of the user's emotional fluctuations and integration with social support, limiting their ability to effectively support the user's mental health. This invention aims to provide comprehensive mental health care by continuously monitoring a user's emotional state in real time, providing an appropriate relaxation environment, analyzing emotional records, and facilitating connection to social support groups.

[0999] 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.

[1000] In this invention, the server includes a means for collecting biometric data, a means for providing a generative artificial intelligence model for analyzing the biometric data and determining the user's emotional state, a means for providing a relaxation environment to the user based on the emotional state, a means for recording and analyzing an emotional log to respond to fluctuations in the emotional state, and a means for connecting the user to a social support group, thereby enabling real-time monitoring and analysis of the emotional state and providing appropriate feedback and comprehensive mental health support.

[1001] "Biometric data" refers to data that indicates the user's physical condition, including heart rate, eye movement data, and facial expression data.

[1002] "Generative AI models" refer to algorithms or machine learning models that analyze a user's biometric data and determine their emotional state.

[1003] A "relaxation environment" refers to an environment in which users can relax by providing virtual landscapes and fantastical places using augmented reality and virtual reality technologies.

[1004] "Emotion records" record fluctuations in a user's emotional state and refer to data collected through voice and text input.

[1005] A "social support group" refers to a group of other users and supporters with whom a user can receive emotional support through real-time communication.

[1006] The present invention relates to a system for collecting a user's biological data in real time, analyzing the user's emotional state based on the collected data, providing an appropriate relaxation environment, and analyzing the emotional record.

[1007] Biometric data collection

[1008] The user wears a device called smart glasses, which collects biometric data. The smart glasses are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, and these sensors are used to collect biometric data such as heart rate, eye movement, and facial expressions in real time. The collected data is temporarily stored in the smart glasses and is sent to a server once it is ready.

[1009] Data transmission and analysis

[1010] The biometric data collected by the smart glasses is sent to a server via network communication. The server first preprocesses the received data, removing noise and normalizing it. After preprocessing is complete, the data is input into a generative AI model (such as OpenAI's GPT-3) that combines an emotion engine to analyze the user's emotional state.

[1011] Providing a relaxing environment

[1012] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. It also sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[1013] Emotional record entry and analysis

[1014] Users can record their emotions using the smart glasses' voice input function. The recorded emotion record is then sent to a server via the network. The server receives the record and an emotion engine analyzes it using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[1015] Connecting to social support groups

[1016] Users can join social support groups through a smartphone app. The server receives the join request and establishes a connection with the group, allowing users to communicate with other users in real time and receive social support.

[1017] Specific examples

[1018] For example, when a user puts on smart glasses in the morning, it detects that their heart rate is higher than normal, their eye movements are erratic, and their facial expression looks sad. This data is sent to the server, where it is analyzed by a generative AI model combined with an emotion engine, and it is determined that the user is feeling stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters the following in their emotion log by voice: "The morning was stressful, but I was able to relax on the virtual beach." These records are then analyzed by the server and recorded as emotional fluctuations.

[1019] Example prompts for generative AI models

[1020] Prompt: "Please describe in detail how you would analyze the user's emotional state and provide appropriate feedback."

[1021] This allows the present invention to manage the user's emotional state in real time and provide appropriate support. Furthermore, the use of an emotion engine enables more accurate emotion recognition and feedback, thereby effectively supporting the user's mental health.

[1022] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1023] Step 1:

[1024] The user wears the smart glasses, which collect biometric data (heart rate, eye movement data, facial expression data) in real time. The input is various biometric signals from the smart glasses' sensors, and the output is biometric data that is temporarily stored in the smart glasses. Specifically, the heart rate sensor detects the heart rate, the tracking camera captures eye movement, and the facial expression recognition camera analyzes facial expressions.

[1025] Step 2:

[1026] The biometric data collected by the smart glasses is sent to a server via network communication. The input is the biometric data stored in the smart glasses, and the output is the data sent to the server. Specifically, the smart glasses upload the data to the server in real time using Wi-Fi or Bluetooth.

[1027] Step 3:

[1028] The server preprocesses the received biometric data. The input is the received biometric data, and the output is preprocessed data that has been subjected to noise removal and normalization. Specifically, the server uses a filtering algorithm to remove noise and normalize the scale of the data, converting the data into a format suitable for the analysis model.

[1029] Step 4:

[1030] The server inputs the preprocessed data into a generative AI model combined with an emotion engine to analyze the user's emotional state. The input is the preprocessed data, and the output is the analyzed emotional state. Specifically, a generative AI model (e.g., GPT-3) is used to analyze the user's emotions from the data, and the results are returned to the server.

[1031] Step 5:

[1032] The server determines the user's emotional state based on the analysis results. If the emotional state is determined to be low, the server sends an alert encouraging the user to take a break. The input is the emotion analysis result from the generative AI model, and the output is an alert sent to the user and virtual scenery data necessary for relaxation. Specifically, the server determines that the user is "high stress" and sends scenery data of a virtual beach to the smart glasses along with a message such as "take a break."

[1033] Step 6:

[1034] Based on the virtual landscape data received by the smart glasses, a relaxing environment is displayed using augmented reality (AR) and virtual reality (VR) technology. The input is the virtual landscape data sent from the server, and the output is the display of the relaxing environment. Specifically, the smart glasses display the virtual landscape on a visual display, encouraging the user to relax.

[1035] Step 7:

[1036] The user uses the voice input function of the smart glasses to record their emotions. The input is the user's voice command, and the output is sent to the server as voice data. Specifically, the user might say, "I had a stressful morning, but I was able to relax on the virtual beach," and the smart glasses would analyze this as voice data and send it to the server.

[1037] Step 8:

[1038] The server receives the transmitted emotion record, and the emotion engine analyzes the record using natural language processing (NLP) technology. The input is voice data, and the output is analyzed emotion fluctuation data. Specifically, the server converts the voice data into text, analyzes the emotion record using NLP technology, and records the user's emotional fluctuations.

[1039] Step 9:

[1040] A user joins a social support group through a smartphone app. The input is the user's join request, and the output is permission to connect to the group. Specifically, the server accepts the join request and provides group connection information to the user's smartphone app, allowing the user to communicate with other group members in real time.

[1041] (Application example 2)

[1042] 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."

[1043] Delivery workers, including food delivery workers, are often exposed to long working hours and stress, which can have a negative impact on their work efficiency and health. Currently, there is a lack of a system that monitors worker stress and fatigue in real time and provides appropriate support, so quick and effective measures are needed.

[1044] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1045] In this invention, the server includes means for collecting biometric information, means for providing a generative model for analyzing emotional states, means for providing a relaxation environment to a user, means for recording and analyzing an emotional diary, means for connecting the user to a social support group, and means for use by delivery workers to monitor the fatigue and stress of the worker in real time and provide a rest and relaxation environment as needed, thereby managing the stress and fatigue of the worker and improving their work efficiency and health.

[1046] "Biometric information" refers to information for understanding the user's physical condition, such as the user's heart rate, eye movement, and facial expression data.

[1047] A "generative model" is a model for analyzing collected biometric information and determining the user's emotional state.

[1048] A "relaxation environment" is an environment that uses AR and VR technology to provide virtual landscapes and fantastical places to help users relax.

[1049] An "emotion diary" is a tool that allows users to record fluctuations in their emotional state.

[1050] A "social support group" is a group where users can communicate with other users in real time and receive emotional support.

[1051] "Delivery work" refers to the work that a user does to deliver a product to a recipient.

[1052] A "worker" is a user who is engaged in delivery work.

[1053] "Real-time" refers to processing or responding with minimal delay.

[1054] "Monitoring" is the act of continuously observing and recording specific information or conditions.

[1055] A "break" refers to a temporary interruption of work by a user to restore physical or mental strength.

[1056] The present invention provides a system for managing stress and fatigue of delivery workers, thereby improving their work efficiency and health. Specific embodiments for carrying out the present invention will be described below.

[1057] Biometric data collection

[1058] The device (smart glasses) is equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Using these sensors, the device collects biometric information such as heart rate, eye movement, and facial expressions in real time. This collected data is sent to a server via network communication.

[1059] Data preprocessing and analysis

[1060] On the server side, after receiving the biometric information, preprocessing such as noise removal and data normalization is performed. The preprocessed data is then input into a generative model equipped with an emotion engine to analyze the user's emotional state. This generative model combines the diverse data collected to accurately determine the user's stress and fatigue state.

[1061] Emotional state assessment and feedback

[1062] The server uses an emotion engine to analyze the user's emotional state, and if it determines that the user is experiencing high levels of stress or fatigue, it sends an alert to the device urging them to take a break. At the same time, relaxing virtual landscape data (e.g., a beach scene) is sent to the device, providing the user with a relaxation environment using AR and VR technology.

[1063] Emotional diary entry and analysis

[1064] Users can use the smart glasses to write their emotional diary using voice input, and this diary data is also sent to a server where it is analyzed using natural language processing (NLP) technology, allowing continuous fluctuations in the user's emotional state to be understood.

[1065] Connecting to social support groups

[1066] Users can join social support groups through a smartphone app, where they can communicate with other workers in real time, offering mutual comfort and information exchange, thereby enhancing psychological support.

[1067] Specific examples

[1068] For example, if a delivery person exhibits biometric information such as a high heart rate, unstable eye movements, and a stern expression while making a delivery, the server will analyze this with its emotion engine and determine that the delivery person is experiencing high stress. The server will immediately send an alert to the device urging them to take a break, and at the same time display a relaxing virtual beach scene on the device. The delivery person will enter an emotion diary entry by saying, "Today was busy and stressful, but I was able to relax on the beach," and the diary data will be analyzed and recorded on the server.

[1069] Example prompt for a generative AI model:

[1070] "Analyze the following text to determine the user's emotional state: 'Today was busy, but I was able to relax on the beach during my break.'"

[1071] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1072] Step 1:

[1073] The terminal collects the user's biometric information.

[1074] Specifically, the device's built-in heart rate sensor, eye movement tracking camera, and facial expression recognition camera measure and collect heart rate, eye movement, and facial expression data in real time, respectively.

[1075] Input: User's biometric information (heart rate, eye movement, facial expression data)

[1076] Output: Collected biometric data

[1077] Step 2:

[1078] The terminal transmits the collected biometric information to the server.

[1079] Specifically, the terminal transmits the collected biometric information data to a server via network communication.

[1080] Input: Collected biometric data

[1081] Output: Biometric data sent to the server

[1082] Step 3:

[1083] The server preprocesses the received biometric data.

[1084] Specifically, we perform preprocessing to improve the accuracy of the analysis by removing noise and normalizing the data. We use a median filter for noise removal and an appropriate scaling method for data normalization.

[1085] Input: Biometric data sent to the server

[1086] Output: Preprocessed biometric data

[1087] Step 4:

[1088] The server inputs the preprocessed biometric data into a generative model to analyze the user's emotional state.

[1089] Specifically, a generative AI model combined with an emotion engine is used to determine the user's stress level and fatigue level from biometric data.

[1090] Input: Preprocessed biometric data

[1091] Output: User's emotional state (e.g., stress level, high / low)

[1092] Step 5:

[1093] The server generates feedback based on the analysis results.

[1094] Specifically, if the user shows signs of high stress or fatigue, an alert is generated encouraging them to take a break, and virtual scenery data (e.g., a beach scene) is also provided.

[1095] Input: User's emotional state (stress level)

[1096] Output: Break alert, virtual landscape data

[1097] Step 6:

[1098] The terminal receives the feedback from the server and displays it to the user.

[1099] Specifically, the system will notify users with an alert encouraging them to take a break, and will use virtual landscape data to display a relaxation environment using AR and VR technology.

[1100] Input: Break alerts, virtual landscape data

[1101] Output: Alert to user, display of relaxation environment

[1102] Step 7:

[1103] The user writes an emotion diary using voice input.

[1104] Specifically, users use the voice input function of the smart glasses to record their emotional state and the events of the day.

[1105] Input: Audio data of the user's emotion diary

[1106] Output: Emotion diary written by voice

[1107] Step 8:

[1108] The emotion diary data is sent to a server, which analyzes it using natural language processing (NLP) technology.

[1109] Specifically, text data is generated from voice data, and this is analyzed using an NLP model to record fluctuations in the user's emotions.

[1110] Input: Emotional diary written by voice

[1111] Output: Analyzed emotional state data and its fluctuations

[1112] Step 9:

[1113] Users connect to social support groups.

[1114] Specifically, users join support groups through a smartphone app and communicate with other users in real time. The server receives connection requests and establishes the connections.

[1115] Input: A user's connection request

[1116] Output: Connection established to a social support group

[1117] 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.

[1118] 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.

[1119] 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.

[1120] [Fourth embodiment]

[1121] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1122] 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.

[1123] 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).

[1124] 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.

[1125] 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.

[1126] 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).

[1127] 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.

[1128] 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.

[1129] 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.

[1130] 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.

[1131] 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.

[1132] 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.

[1133] 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."

[1134] The present invention provides a system for providing rapid, personalized support to patients with depression and other mental health conditions. The system uses devices such as smart glasses to collect biometric information in real time and analyzes it with a generative model to determine the user's emotional state. Specific embodiments are described below.

[1135] Biometric data collection

[1136] The user wears smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, allowing the glasses to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[1137] Data transmission and analysis

[1138] The biometric information collected by the smart glasses is transmitted to a server via network communication. The server preprocesses the received data, removing noise and normalizing it. The preprocessed data is then input into a generative model to analyze the user's emotional state.

[1139] Emotional state assessment and relaxation environment provision

[1140] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[1141] Emotional diary entry and analysis

[1142] Users can use the smart glasses' voice input function to write down their emotions in a diary, which is then sent to a server and analyzed using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[1143] Connecting to social support groups

[1144] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[1145] Specific examples

[1146] For example, when a user puts on smart glasses in the morning, their heart rate is measured to be higher than normal, their eye movements are erratic, and their facial expression is sad. This data is sent to the server, where it is analyzed by a generative model and determined to be stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters in their emotion diary by voice, "This morning was stressful, but I was able to relax on the virtual beach." This diary entry is then analyzed by the server and recorded as emotional fluctuations.

[1147] This allows the present invention to manage the user's emotional state in real time and provide appropriate support.

[1148] The processing flow will be explained below.

[1149] Step 1:

[1150] The user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial recognition camera, so once they are put on, they are ready to go.

[1151] Step 2:

[1152] The smart glasses measure heart rate data by using a heart rate sensor to measure the user's heart rate in real time and temporarily store this data in an internal buffer.

[1153] Step 3:

[1154] Smart glasses collect eye movement data. A built-in tracking camera captures the user's eye movements, analyzes them, and stores them as data.

[1155] Step 4:

[1156] The smart glasses analyze facial expression data. Using a facial recognition camera, they analyze the user's facial muscle movements and convert their current facial expression into digital data and store it.

[1157] Step 5:

[1158] The smart glasses transmit biometric information (heart rate data, eye movement data, facial expression data) to a server. The data is transferred to the server via a network using a secure communication protocol (e.g., HTTPS).

[1159] Step 6:

[1160] The server preprocesses the received biometric information, including noise removal and data normalization, to make it suitable for analysis.

[1161] Step 7:

[1162] The server inputs the preprocessed data into a generative model to analyze the user's emotional state. The generative AI model evaluates the data and determines the user's emotional state (e.g., stressed, relaxed, tired, etc.).

[1163] Step 8:

[1164] The server determines the user's emotional state and sends an alert to encourage them to take a break if necessary. If the user's emotional state falls below a defined threshold, the server sends the user an alert message telling them to take a break.

[1165] Step 9:

[1166] The server prepares relaxation environment data for AR / VR and sends it to the smart glasses, providing relaxation data such as virtual beach scenes or forest scenes to the smart glasses.

[1167] Step 10:

[1168] The smart glasses display the received virtual landscape data, utilizing AR / VR technology to provide virtual landscapes and fantastical places for users to relax.

[1169] Step 11:

[1170] Users write their emotional diary using voice input. Using the voice input function of the smart glasses, they record their emotions and experiences for the day.

[1171] Step 12:

[1172] The smart glasses convert the voice-input emotion diary into digital data and send it to the server, where it is transferred as text data.

[1173] Step 13:

[1174] The server analyzes the emotion diary data and uses natural language processing (NLP) technology to understand and record the user's emotional fluctuations.

[1175] Step 14:

[1176] Users connect to a social support group through a smartphone app. The user sends a join request within the app, which is received by the server.

[1177] Step 15:

[1178] The server processes your join request and establishes a connection with your social support group, allowing you to communicate in real time.

[1179] Step 16:

[1180] Users can communicate with other users in real time and receive information and support within social support groups.

[1181] Example 1

[1182] 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."

[1183] In recent years, there has been a demand for rapid and personalized support for patients with depression and other mental health conditions. However, conventional mental health care systems have had difficulty accurately grasping users' emotional states in real time and providing immediate, appropriate support. In addition, the utilization of emotional diaries and social support groups has not been fully realized, resulting in delays in providing measures tailored to each user's individual situation.

[1184] 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.

[1185] In this invention, the server includes a means for transmitting biometric information via a network, a means for preprocessing and noise reduction of the received biometric information, and a means for analyzing the preprocessed biometric information using a generative AI model to determine the user's emotional state. This allows for accurate understanding of the user's emotional state in real time, enabling the immediate provision of an appropriate relaxation environment and analysis of an emotional diary entry. Furthermore, by connecting the user to a social support group, psychological support is enhanced.

[1186] "Biometric information" is data obtained from the user's body, and includes heart rate, eye movement, facial expression data, and the like.

[1187] "Network communications" refers to internet connections and wireless communication technologies (such as Wi-Fi and Bluetooth) for sending and receiving data.

[1188] "Preprocessing" refers to the process of removing noise from the received biometric information and normalizing the data to make it analyzable.

[1189] "Noise removal" is a process of removing unnecessary data and errors from collected biometric information.

[1190] A "generative AI model" is a model that uses deep learning or machine learning algorithms to analyze data and is used to determine a user's emotional state.

[1191] An "emotional state" is a psychological state that a user is feeling, and may include stress, happiness, sadness, etc.

[1192] A "relaxation environment" is a virtual landscape or fantasy place that promotes mental relaxation for users, and is provided using augmented reality (AR) and virtual reality (VR) technologies.

[1193] An "emotion diary" is a diary in which users record their emotional fluctuations and state. It is written using voice input and analyzed using natural language processing technology.

[1194] "Natural language processing technology" is a technology that converts voice data into text information and analyzes its content.

[1195] A "social support group" is a group in which users can participate and communicate with other users to receive emotional support and exchange information.

[1196] The present invention is a system for providing prompt and personalized support to patients with depression and other mental health conditions. An embodiment of the system will be described in detail below.

[1197] First, the user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Using these sensors and cameras, the smart glasses collect biometric information such as the user's heart rate, eye movement, and facial expressions in real time.

[1198] Once biometric information is collected, the smart glasses send it to a server via network communication (Wi-Fi or Bluetooth). The biometric information received by the server is first preprocessed. Preprocessing includes noise reduction and data normalization. Noise reduction removes unnecessary data, and data normalization standardizes the scale of the data.

[1199] The preprocessed data is input into a generative AI model. The server uses this generative AI model to analyze the user's emotional state. Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, virtual scenery data for relaxation is also sent to the smart glasses.

[1200] Based on the virtual landscape data received by the smart glasses, the glasses use augmented reality (AR) and virtual reality (VR) technology to display a relaxing virtual environment for the user, such as a beach or mountain landscape, allowing the user to refresh in a virtual relaxation environment.

[1201] Furthermore, users can use the smart glasses' voice input function to write an emotional diary, which is then sent to a server where it is analyzed using natural language processing (NLP) technology to analyze emotional fluctuations in detail.

[1202] Finally, users can join social support groups through a smartphone app. The server receives the join request and establishes a connection. This connection allows users to communicate with other users in real time and provide emotional support.

[1203] Specific examples

[1204] For example, suppose a user wears smart glasses in the morning, and the heart rate sensor measures a heart rate of 90 beats per minute, the eye movement tracking camera detects frequent eye movements, and the facial expression recognition camera analyzes sad facial expressions. This data is sent to the server, where noise removal and data normalization are performed. The data is then input into a generative AI model to determine that the user is in a stressed state. The server then sends the user an alert saying, "Take a short break," and displays a virtual beach scene on the smart glasses. After relaxing on the virtual beach, the user writes in their emotion diary by voice input, "I was stressed this morning, but I was able to relax on the virtual beach." This diary is analyzed by the server and recorded as emotional fluctuations.

[1205] Prompt Sentence Examples

[1206] "Please explain how a system where a user wears smart glasses collects biometric information (heart rate, eye movements, facial expressions) and sends it to a server for analysis to determine the user's emotional state and provide appropriate support."

[1207] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1208] Step 1:

[1209] The user wears smart glasses, which use built-in heart rate sensors, eye movement tracking cameras, and facial expression recognition cameras to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[1210] Input: User's biometric information (heart rate, eye movement, facial expression)

[1211] Output: Collected biometric data

[1212] Step 2:

[1213] The biometric information collected by the smart glasses is sent to a server via a network, specifically using Wi-Fi or Bluetooth.

[1214] Input: Collected biometric data

[1215] Output: Biometric data sent to the server

[1216] Step 3:

[1217] The server preprocesses the received biometric data, which includes noise removal and data normalization to improve data quality and make it suitable for analysis.

[1218] Input: Biometric data sent to the server

[1219] Output: Preprocessed biometric data

[1220] Step 4:

[1221] The preprocessed biometric data is input into a generative AI model. The server uses the generative AI model to analyze the data and determine the user's emotional state. A deep learning algorithm is used as the generative AI model.

[1222] Input: Preprocessed biometric data

[1223] Output: Parsed emotional state

[1224] Step 5:

[1225] The server determines the user's emotional state based on the analyzed emotional state, such as "high stress," "happiness," or "sadness."

[1226] Input: Parsed emotional state

[1227] Output: Determined emotional state

[1228] Step 6:

[1229] If the user's emotional state is judged to be low, such as "sadness," the server sends an alert to the user saying, "Take a short break." At the same time, virtual scenery data for relaxation is sent to the smart glasses.

[1230] Input: Determined emotional state

[1231] Output: Break alert and virtual landscape data

[1232] Step 7:

[1233] Based on the virtual landscape data received by the smart glasses, augmented reality (AR) and virtual reality (VR) technologies are used to display a relaxation environment for the user, such as a beach or mountain landscape.

[1234] Input: Virtual landscape data

[1235] Output: The virtual relaxation environment seen by the user

[1236] Step 8:

[1237] The user uses the voice input function of the smart glasses to write an emotional diary.

[1238] Input: User voice input

[1239] Output: Emotion diary entries

[1240] Step 9:

[1241] The emotion diary entries are sent to a server and analyzed using natural language processing (NLP) technology. Specifically, the voice data is converted into text information, and the emotion diary is analyzed in detail.

[1242] Input: Emotional diary entry

[1243] Output: Parsed emotion diary

[1244] Step 10:

[1245] A user sends a request to join a social support group via a smartphone app.

[1246] Input: Join request

[1247] Output: Support group join request

[1248] Step 11:

[1249] The server receives the user's request and establishes a connection, allowing users to communicate with other users in real time.

[1250] Input: Join request

[1251] Output: Social support group connections

[1252] (Application example 1)

[1253] 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."

[1254] In modern society, people engaged in high-stress jobs, such as police officers and security guards, have difficulty understanding their rapidly fluctuating mental state in real time and receiving appropriate support. Furthermore, if stress and anxiety that arise during work cannot be properly managed, it can lead to serious accidents and reduced work efficiency. Concrete measures to resolve these issues and improve work safety and efficiency are needed.

[1255] 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.

[1256] In this invention, the server includes a device for collecting biometric information, a device with a generative model for analyzing the biometric information and determining the user's emotional state, a device for providing a relaxation environment to the user based on the emotional state, a device for entering and analyzing an emotion diary to respond to fluctuations in the emotional state, a device for connecting the user to a social support group, a device and processing means for monitoring the user's mental state while performing work and providing appropriate alerts, and a rendering means for providing the relaxation environment using VR technology.This allows the user's mental state to be understood in real time and an appropriate relaxation environment to be provided, enabling the user to safely and efficiently handle even high-stress work.

[1257] "Biometric information" refers to data related to the user's vital activities, such as heart rate, eye movement, and facial expression data.

[1258] A "generative model" refers to an algorithmic model that uses machine learning and artificial intelligence techniques to determine a user's emotional state.

[1259] A "relaxation environment" refers to an environment that provides virtual landscapes and fantastical places to promote mental stability for users.

[1260] An "emotion diary" refers to a system that records a user's emotional fluctuations and collects data for analysis.

[1261] A "social support group" refers to a group where multiple users communicate with each other, provide emotional support, and exchange information.

[1262] "Monitoring mental state during work performance" refers to monitoring the mental state of a user in real time while they are performing their work.

[1263] "Alert" refers to a system that provides important notifications to users, such as encouraging them to take a break.

[1264] "VR technology" refers to technology that uses virtual reality technology to allow users to experience an immersive virtual environment.

[1265] "Rendering means" refers to devices or software that generate virtual landscapes or fantasy locations using computer graphics techniques to visually represent virtual environments.

[1266] This invention is a system that collects biometric information and monitors the user's mental state in real time, supporting job performance in high-stress environments. Specifically, the system includes smart glasses, a server, network communications, a generative model, and a VR rendering means.

[1267] Biometric data collection

[1268] The device (here, smart glasses) is worn by the user. The smart glasses are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Each of these sensors collects biometric information such as the user's heart rate, eye movement, and facial expressions in real time.

[1269] Data transmission and analysis

[1270] The biometric information collected by the smart glasses is transmitted to a server via network communication. The server preprocesses the received data, removes noise, and normalizes the data. The preprocessed data is then input into a generative model to analyze the user's emotional state.

[1271] Emotional state assessment and relaxation environment provision

[1272] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[1273] Emotional diary entry and analysis

[1274] Users can use the smart glasses' voice input function to write down their emotions in a diary, which is then sent to a server and analyzed using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[1275] Connecting to social support groups

[1276] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[1277] Specific examples of programs

[1278] As a pre-processing step for biometric information, a Butterworth filter is applied to the heart rate data to remove noise. Data is transmitted via network communication (HTTP request), and the server uses a generative AI model to analyze the data. Additionally, a relaxation environment is provided when the emotional state is low, and is rendered using VR technology. As a specific example, the server analyzes the user's data using the following prompt:

[1279] Example prompt sentence:

[1280] "Analyze heart rate data: {heart rate data}, eye movement data: {eye movement data}, and facial expressions: {facial expressions} to determine the user's emotional state."

[1281] This system allows users to grasp their mental state in real time and provide an appropriate relaxation environment, enabling them to respond safely and efficiently to even high-stress work.

[1282] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1283] Step 1: Collecting biometric information

[1284] The user puts on the smart glasses. The smart glasses' heart rate sensor, eye movement tracking camera, and facial expression recognition camera are activated, collecting the user's heart rate, eye movement, and facial expression data in real time. This biometric information is temporarily stored in the recording media inside the smart glasses.

[1285] Input: User's heart rate, eye movement, and facial expression data

[1286] Output: Collected biometric information

[1287] Step 2: Sending data

[1288] The device (smart glasses) sends the collected biometric information to the server via network communication. Specifically, it uses an HTTP request to package the biometric information in JSON format and send it to a specified endpoint.

[1289] Input: Collected biometric information

[1290] Output: Data sent to the server

[1291] Step 3: Preprocessing the data

[1292] The server preprocesses the received biometric data. At this stage, noise removal and data normalization are performed. For example, a Butterworth filter is applied to heart rate data to remove noise. Eye movement data and facial expression data are also preprocessed in a similar way to prepare them for analysis.

[1293] Input: Data sent to the server

[1294] Output: Preprocessed biometric information

[1295] Step 4: Analyze emotional state

[1296] The server inputs the preprocessed biometric information into a generative model to analyze the user's emotional state. The generative AI model then comprehensively analyzes heart rate, eye movement, and facial expression data to determine the user's emotional state.

[1297] Input: Preprocessed biometric information

[1298] Output: User's emotional state

[1299] Step 5: Provide a Relaxation Environment

[1300] If the server analyzes the user's emotional state and determines that the user's mental state is low, it will send an alert urging the user to take a break. It also sends virtual landscape data for relaxation to the smart glasses, which then use augmented reality (AR) and virtual reality (VR) technology to display a relaxing environment.

[1301] Input: User's emotional state

[1302] Output: Alert and relaxation environment

[1303] Step 6: Emotional Diary

[1304] The user uses the voice input function of the smart glasses to write down their emotions in a diary, which is then sent to a server, where it analyzes the diary using natural language processing (NLP) technology to understand the user's emotional fluctuations.

[1305] Input: Emotion diary based on user voice input

[1306] Output: Analyzed emotion diary data

[1307] Step 7: Connect to social support groups

[1308] A user sends a request to join a social support group through a smartphone app. The server receives the request and establishes a connection, allowing users to communicate with other users in real time and exchange support and information.

[1309] Input: User's join request

[1310] Output: Connected social support groups

[1311] In this way, the system manages the user's mental state in real time and provides an appropriate relaxation environment and support, enabling them to cope with high-stress work safely and efficiently.

[1312] 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.

[1313] The present invention is a system that provides rapid, personalized support for patients with depression and other mental health conditions. The system uses devices such as smart glasses to collect biometric information in real time and analyzes it with a generative model combined with an emotion engine to determine the user's emotional state. Specific embodiments are described below.

[1314] Biometric data collection

[1315] The user wears smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, allowing the glasses to collect biometric information such as heart rate, eye movement, and facial expressions in real time.

[1316] Data transmission and analysis

[1317] The biometric information collected by the smart glasses is sent to a server via network communication. The server preprocesses the received data, removing noise and normalizing it. The preprocessed data is then input into a generative model combined with an emotion engine to analyze the user's emotional state.

[1318] Emotional state assessment and feedback

[1319] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. At the same time, the server sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[1320] Emotional diary entry and analysis

[1321] Users can use the smart glasses' voice input function to write down their emotions in a diary. The diary entries are sent to a server where an emotion engine analyzes them using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[1322] Connecting to social support groups

[1323] Users can join social support groups through a smartphone app. The server receives the joining request and establishes a connection. This allows users to communicate with other users in real time. In social support groups, users can exchange support and information with each other, strengthening their emotional support.

[1324] Specific examples

[1325] For example, when a user puts on smart glasses in the morning, it is measured that their heart rate is higher than normal, their eye movements are erratic, and their facial expression is sad. This data is sent to the server, where it is analyzed using a generative model combined with an emotion engine, and it is determined that the user is feeling stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters in their emotion diary by voice, "I was stressed this morning, but I was able to relax on the virtual beach." This diary entry is then analyzed by the server and recorded as emotional fluctuations.

[1326] This allows the present invention to manage the user's emotional state in real time and provide appropriate support. Furthermore, the use of an emotion engine enables more accurate emotion recognition and feedback, thereby effectively supporting the user's mental health.

[1327] The processing flow will be explained below.

[1328] Step 1:

[1329] The user puts on the smart glasses, which are equipped with a heart rate sensor, an eye movement tracking camera, and a facial recognition camera, so once they are put on, they are ready to go.

[1330] Step 2:

[1331] The smart glasses measure heart rate data by using a heart rate sensor to measure the user's heart rate in real time and temporarily store this data in an internal buffer.

[1332] Step 3:

[1333] Smart glasses collect eye movement data. A built-in tracking camera captures the user's eye movements, analyzes them, and stores them as data.

[1334] Step 4:

[1335] The smart glasses analyze facial expression data. Using a facial recognition camera, they analyze the user's facial muscle movements and convert their current facial expression into digital data and store it.

[1336] Step 5:

[1337] The smart glasses transmit biometric information (heart rate data, eye movement data, facial expression data) to a server. The data is transferred to the server via a network using a secure communication protocol (e.g., HTTPS).

[1338] Step 6:

[1339] The server preprocesses the received biometric information, including noise removal and data normalization, to make it suitable for analysis.

[1340] Step 7:

[1341] The server inputs the preprocessed data into a generative model to analyze the user's emotional state. The generative AI model evaluates the data and determines the user's emotional state (e.g., stressed, relaxed, tired, etc.).

[1342] Step 8:

[1343] The server checks the analysis results with the emotion engine and updates the emotional state in real time. The emotion engine performs additional data analysis and provides immediate feedback on the user's emotional state.

[1344] Step 9:

[1345] The server determines the user's emotional state and sends an alert to encourage them to take a break if necessary. If the user's emotional state falls below a defined threshold, the server sends the user an alert message telling them to take a break.

[1346] Step 10:

[1347] The server prepares relaxation environment data for AR / VR and sends it to the smart glasses, providing relaxation data such as virtual beach scenes or forest scenes to the smart glasses.

[1348] Step 11:

[1349] The smart glasses display the received virtual landscape data, utilizing AR / VR technology to provide virtual landscapes and fantastical places for users to relax.

[1350] Step 12:

[1351] Users write their emotional diary using voice input. Using the voice input function of the smart glasses, they record their emotions and experiences for the day.

[1352] Step 13:

[1353] The smart glasses convert the voice-input emotion diary into digital data and send it to the server, where it is transferred as text data.

[1354] Step 14:

[1355] The server analyzes the emotion diary data, and the emotion engine uses natural language processing (NLP) technology to analyze it and understand the user's emotional fluctuations.

[1356] Step 15:

[1357] Users connect to a social support group through a smartphone app. The user sends a request to join within the app, which is received by the server.

[1358] Step 16:

[1359] The server processes your join request and establishes a connection with your social support group, allowing you to communicate in real time.

[1360] Step 17:

[1361] Users can communicate with other users in real time and receive information and support within social support groups.

[1362] Example 2

[1363] 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."

[1364] Existing technologies include systems that collect and analyze biometric data to determine a user's emotional state, but these systems often lack the ability to collect and provide feedback in real time. Furthermore, they lack detailed analysis of the user's emotional fluctuations and integration with social support, limiting their ability to effectively support the user's mental health. This invention aims to provide comprehensive mental health care by continuously monitoring a user's emotional state in real time, providing an appropriate relaxation environment, analyzing emotional records, and facilitating connection to social support groups.

[1365] 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.

[1366] In this invention, the server includes a means for collecting biometric data, a means for providing a generative artificial intelligence model for analyzing the biometric data and determining the user's emotional state, a means for providing a relaxation environment to the user based on the emotional state, a means for recording and analyzing an emotional log to respond to fluctuations in the emotional state, and a means for connecting the user to a social support group, thereby enabling real-time monitoring and analysis of the emotional state and providing appropriate feedback and comprehensive mental health support.

[1367] "Biometric data" refers to data that indicates the user's physical condition, including heart rate, eye movement data, and facial expression data.

[1368] "Generative AI models" refer to algorithms or machine learning models that analyze a user's biometric data and determine their emotional state.

[1369] A "relaxation environment" refers to an environment in which users can relax by providing virtual landscapes and fantastical places using augmented reality and virtual reality technologies.

[1370] "Emotion records" record fluctuations in a user's emotional state and refer to data collected through voice and text input.

[1371] A "social support group" refers to a group of other users and supporters with whom a user can receive emotional support through real-time communication.

[1372] The present invention relates to a system for collecting a user's biological data in real time, analyzing the user's emotional state based on the collected data, providing an appropriate relaxation environment, and analyzing the emotional record.

[1373] Biometric data collection

[1374] The user wears a device called smart glasses, which collects biometric data. The smart glasses are equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera, and these sensors are used to collect biometric data such as heart rate, eye movement, and facial expressions in real time. The collected data is temporarily stored in the smart glasses and is sent to a server once it is ready.

[1375] Data transmission and analysis

[1376] The biometric data collected by the smart glasses is sent to a server via network communication. The server first preprocesses the received data, removing noise and normalizing it. After preprocessing is complete, the data is input into a generative AI model (such as OpenAI's GPT-3) that combines an emotion engine to analyze the user's emotional state.

[1377] Providing a relaxing environment

[1378] Based on the analysis results, the server determines the user's emotional state. If the emotional state is determined to be low, the server sends an alert urging the user to take a break. It also sends virtual landscape data for relaxation to the smart glasses. The smart glasses receive this data and display a relaxing environment for the user using augmented reality (AR) and virtual reality (VR) technology.

[1379] Emotional record entry and analysis

[1380] Users can record their emotions using the smart glasses' voice input function. The recorded emotion record is then sent to a server via the network. The server receives the record and an emotion engine analyzes it using natural language processing (NLP) technology. This allows the system to understand the user's emotional fluctuations and provide appropriate support.

[1381] Connecting to social support groups

[1382] Users can join social support groups through a smartphone app. The server receives the join request and establishes a connection with the group, allowing users to communicate with other users in real time and receive social support.

[1383] Specific examples

[1384] For example, when a user puts on smart glasses in the morning, it detects that their heart rate is higher than normal, their eye movements are erratic, and their facial expression looks sad. This data is sent to the server, where it is analyzed by a generative AI model combined with an emotion engine, and it is determined that the user is feeling stressed. The server then sends the user an alert saying, "Take a short break," and simultaneously displays a virtual beach scene on the smart glasses to encourage relaxation. The user then enters the following in their emotion log by voice: "The morning was stressful, but I was able to relax on the virtual beach." These records are then analyzed by the server and recorded as emotional fluctuations.

[1385] Example prompts for generative AI models

[1386] Prompt: "Please describe in detail how you would analyze the user's emotional state and provide appropriate feedback."

[1387] This allows the present invention to manage the user's emotional state in real time and provide appropriate support. Furthermore, the use of an emotion engine enables more accurate emotion recognition and feedback, thereby effectively supporting the user's mental health.

[1388] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1389] Step 1:

[1390] The user wears the smart glasses, which collect biometric data (heart rate, eye movement data, facial expression data) in real time. The input is various biometric signals from the smart glasses' sensors, and the output is biometric data that is temporarily stored in the smart glasses. Specifically, the heart rate sensor detects the heart rate, the tracking camera captures eye movement, and the facial expression recognition camera analyzes facial expressions.

[1391] Step 2:

[1392] The biometric data collected by the smart glasses is sent to a server via network communication. The input is the biometric data stored in the smart glasses, and the output is the data sent to the server. Specifically, the smart glasses upload the data to the server in real time using Wi-Fi or Bluetooth.

[1393] Step 3:

[1394] The server preprocesses the received biometric data. The input is the received biometric data, and the output is preprocessed data that has been subjected to noise removal and normalization. Specifically, the server uses a filtering algorithm to remove noise and normalize the scale of the data, converting the data into a format suitable for the analysis model.

[1395] Step 4:

[1396] The server inputs the preprocessed data into a generative AI model combined with an emotion engine to analyze the user's emotional state. The input is the preprocessed data, and the output is the analyzed emotional state. Specifically, a generative AI model (e.g., GPT-3) is used to analyze the user's emotions from the data, and the results are returned to the server.

[1397] Step 5:

[1398] The server determines the user's emotional state based on the analysis results. If the emotional state is determined to be low, the server sends an alert encouraging the user to take a break. The input is the emotion analysis result from the generative AI model, and the output is an alert sent to the user and virtual scenery data necessary for relaxation. Specifically, the server determines that the user is "high stress" and sends scenery data of a virtual beach to the smart glasses along with a message such as "take a break."

[1399] Step 6:

[1400] Based on the virtual landscape data received by the smart glasses, a relaxing environment is displayed using augmented reality (AR) and virtual reality (VR) technology. The input is the virtual landscape data sent from the server, and the output is the display of the relaxing environment. Specifically, the smart glasses display the virtual landscape on a visual display, encouraging the user to relax.

[1401] Step 7:

[1402] The user uses the voice input function of the smart glasses to record their emotions. The input is the user's voice command, and the output is sent to the server as voice data. Specifically, the user might say, "I had a stressful morning, but I was able to relax on the virtual beach," and the smart glasses would analyze this as voice data and send it to the server.

[1403] Step 8:

[1404] The server receives the transmitted emotion record, and the emotion engine analyzes the record using natural language processing (NLP) technology. The input is voice data, and the output is analyzed emotion fluctuation data. Specifically, the server converts the voice data into text, analyzes the emotion record using NLP technology, and records the user's emotional fluctuations.

[1405] Step 9:

[1406] A user joins a social support group through a smartphone app. The input is the user's join request, and the output is permission to connect to the group. Specifically, the server accepts the join request and provides group connection information to the user's smartphone app, allowing the user to communicate with other group members in real time.

[1407] (Application example 2)

[1408] 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."

[1409] Delivery workers, including food delivery workers, are often exposed to long working hours and stress, which can have a negative impact on their work efficiency and health. Currently, there is a lack of a system that monitors worker stress and fatigue in real time and provides appropriate support, so quick and effective measures are needed.

[1410] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1411] In this invention, the server includes means for collecting biometric information, means for providing a generative model for analyzing emotional states, means for providing a relaxation environment to a user, means for recording and analyzing an emotional diary, means for connecting the user to a social support group, and means for use by delivery workers to monitor the fatigue and stress of the worker in real time and provide a rest and relaxation environment as needed, thereby managing the stress and fatigue of the worker and improving their work efficiency and health.

[1412] "Biometric information" refers to information for understanding the user's physical condition, such as the user's heart rate, eye movement, and facial expression data.

[1413] A "generative model" is a model for analyzing collected biometric information and determining the user's emotional state.

[1414] A "relaxation environment" is an environment that uses AR and VR technology to provide virtual landscapes and fantastical places to help users relax.

[1415] An "emotion diary" is a tool that allows users to record fluctuations in their emotional state.

[1416] A "social support group" is a group where users can communicate with other users in real time and receive emotional support.

[1417] "Delivery work" refers to the work that a user does to deliver a product to a recipient.

[1418] A "worker" is a user who is engaged in delivery work.

[1419] "Real-time" refers to processing or responding with minimal delay.

[1420] "Monitoring" is the act of continuously observing and recording specific information or conditions.

[1421] A "break" refers to a temporary interruption of work by a user to restore physical or mental strength.

[1422] The present invention provides a system for managing stress and fatigue of delivery workers, thereby improving their work efficiency and health. Specific embodiments for carrying out the present invention will be described below.

[1423] Biometric data collection

[1424] The device (smart glasses) is equipped with a heart rate sensor, an eye movement tracking camera, and a facial expression recognition camera. Using these sensors, the device collects biometric information such as heart rate, eye movement, and facial expressions in real time. This collected data is sent to a server via network communication.

[1425] Data preprocessing and analysis

[1426] On the server side, after receiving the biometric information, preprocessing such as noise removal and data normalization is performed. The preprocessed data is then input into a generative model equipped with an emotion engine to analyze the user's emotional state. This generative model combines the diverse data collected to accurately determine the user's stress and fatigue state.

[1427] Emotional state assessment and feedback

[1428] The server uses an emotion engine to analyze the user's emotional state, and if it determines that the user is experiencing high levels of stress or fatigue, it sends an alert to the device urging them to take a break. At the same time, relaxing virtual landscape data (e.g., a beach scene) is sent to the device, providing the user with a relaxation environment using AR and VR technology.

[1429] Emotional diary entry and analysis

[1430] Users can use the smart glasses to write their emotional diary using voice input, and this diary data is also sent to a server where it is analyzed using natural language processing (NLP) technology, allowing continuous fluctuations in the user's emotional state to be understood.

[1431] Connecting to social support groups

[1432] Users can join social support groups through a smartphone app, where they can communicate with other workers in real time, offering mutual comfort and information exchange, thereby enhancing psychological support.

[1433] Specific examples

[1434] For example, if a delivery person exhibits biometric information such as a high heart rate, unstable eye movements, and a stern expression while making a delivery, the server will analyze this with its emotion engine and determine that the delivery person is experiencing high stress. The server will immediately send an alert to the device urging them to take a break, and at the same time display a relaxing virtual beach scene on the device. The delivery person will enter an emotion diary entry by saying, "Today was busy and stressful, but I was able to relax on the beach," and the diary data will be analyzed and recorded on the server.

[1435] Example prompt for a generative AI model:

[1436] "Analyze the following text to determine the user's emotional state: 'Today was busy, but I was able to relax on the beach during my break.'"

[1437] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1438] Step 1:

[1439] The terminal collects the user's biometric information.

[1440] Specifically, the device's built-in heart rate sensor, eye movement tracking camera, and facial expression recognition camera measure and collect heart rate, eye movement, and facial expression data in real time, respectively.

[1441] Input: User's biometric information (heart rate, eye movement, facial expression data)

[1442] Output: Collected biometric data

[1443] Step 2:

[1444] The terminal transmits the collected biometric information to the server.

[1445] Specifically, the terminal transmits the collected biometric information data to a server via network communication.

[1446] Input: Collected biometric data

[1447] Output: Biometric data sent to the server

[1448] Step 3:

[1449] The server preprocesses the received biometric data.

[1450] Specifically, we perform preprocessing to improve the accuracy of the analysis by removing noise and normalizing the data. We use a median filter for noise removal and an appropriate scaling method for data normalization.

[1451] Input: Biometric data sent to the server

[1452] Output: Preprocessed biometric data

[1453] Step 4:

[1454] The server inputs the preprocessed biometric data into a generative model to analyze the user's emotional state.

[1455] Specifically, a generative AI model combined with an emotion engine is used to determine the user's stress level and fatigue level from biometric data.

[1456] Input: Preprocessed biometric data

[1457] Output: User's emotional state (e.g., stress level, high / low)

[1458] Step 5:

[1459] The server generates feedback based on the analysis results.

[1460] Specifically, if the user shows signs of high stress or fatigue, an alert is generated encouraging them to take a break, and virtual scenery data (e.g., a beach scene) is also provided.

[1461] Input: User's emotional state (stress level)

[1462] Output: Break alert, virtual landscape data

[1463] Step 6:

[1464] The terminal receives the feedback from the server and displays it to the user.

[1465] Specifically, the system will notify users with an alert encouraging them to take a break, and will use virtual landscape data to display a relaxation environment using AR and VR technology.

[1466] Input: Break alerts, virtual landscape data

[1467] Output: Alert to user, display of relaxation environment

[1468] Step 7:

[1469] The user writes an emotion diary using voice input.

[1470] Specifically, users use the voice input function of the smart glasses to record their emotional state and the events of the day.

[1471] Input: Audio data of the user's emotion diary

[1472] Output: Emotion diary written by voice

[1473] Step 8:

[1474] The emotion diary data is sent to a server, which analyzes it using natural language processing (NLP) technology.

[1475] Specifically, text data is generated from voice data, and this is analyzed using an NLP model to record fluctuations in the user's emotions.

[1476] Input: Emotional diary written by voice

[1477] Output: Analyzed emotional state data and its fluctuations

[1478] Step 9:

[1479] Users connect to social support groups.

[1480] Specifically, users join support groups through a smartphone app and communicate with other users in real time. The server receives connection requests and establishes the connections.

[1481] Input: A user's connection request

[1482] Output: Connection established to a social support group

[1483] 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.

[1484] 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.

[1485] 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.

[1486] 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.

[1487] 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.

[1488] 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.

[1489] 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).

[1490] 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.

[1491] 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."

[1492] 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.

[1493] 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).

[1494] 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.

[1495] 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.

[1496] 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.

[1497] 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.

[1498] 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.

[1499] 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.

[1500] 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.

[1501] 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.

[1502] 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.

[1503] 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.

[1504] The following is further disclosed regarding the above embodiment.

[1505] (Claim 1)

[1506] a device for collecting biometric information;

[1507] a device comprising a generative model for analyzing the biometric information and determining the emotional state of a user;

[1508] an apparatus for providing a relaxation environment to a user based on said emotional state;

[1509] a device for writing and analyzing an emotion diary to respond to fluctuations in the emotional state;

[1510] Apparatus for connecting said user to a social support group

[1511] A system including:

[1512] (Claim 2)

[1513] 2. The system according to claim 1, wherein the biological information includes at least one of heart rate, eye movement, and facial expression data.

[1514] (Claim 3)

[1515] The system according to claim 1, characterized in that the relaxation environment provides virtual landscapes and fantastical places using AR or VR technology.

[1516] "Example 1"

[1517] (Claim 1)

[1518] a device for collecting biometric information;

[1519] means for transmitting the biometric information via network communication;

[1520] means for pre-processing and denoising the received biometric information;

[1521] means for analyzing the preprocessed biometric information with a generative AI model to determine the emotional state of the user;

[1522] an apparatus for providing a relaxation environment to a user based on said emotional state;

[1523] a means for entering an emotion diary by voice input to respond to the fluctuation of the emotional state and analyzing the diary by natural language processing technology;

[1524] means for connecting said user to a social support group;

[1525] A system including:

[1526] (Claim 2)

[1527] 2. The system according to claim 1, wherein the biological information includes at least one of heart rate, eye movement, and facial expression data.

[1528] (Claim 3)

[1529] 2. The system according to claim 1, wherein the relaxation environment provides virtual landscapes and fantastical places using augmented reality (AR) and virtual reality (VR) technology.

[1530] "Application Example 1"

[1531] (Claim 1)

[1532] a device for collecting biometric information;

[1533] a device comprising a generative model for analyzing the biometric information and determining the emotional state of a user;

[1534] an apparatus for providing a relaxation environment to a user based on said emotional state;

[1535] a device for writing and analyzing an emotion diary to respond to fluctuations in the emotional state;

[1536] a device for connecting the user to a social support group;

[1537] an apparatus and processing means for monitoring the user's mental state during work performance and providing appropriate alerts;

[1538] Rendering means for providing the relaxation environment by VR technology

[1539] A system including:

[1540] (Claim 2)

[1541] 2. The system according to claim 1, wherein the biological information includes at least one of heart rate, eye movement, and facial expression data.

[1542] (Claim 3)

[1543] The system according to claim 1, characterized in that the relaxation environment provides virtual landscapes and fantastical places using AR or VR technology.

[1544] "Example 2: Combining Emotion Engines"

[1545] (Claim 1)

[1546] means for collecting biometric data;

[1547] means for analyzing the biometric data and providing a generative artificial intelligence model for determining the user's emotional state;

[1548] means for providing a relaxation environment to a user based on said emotional state;

[1549] means for recording and analyzing an emotional record to respond to fluctuations in said emotional state;

[1550] means for connecting said user to a social support group;

[1551] A system including:

[1552] (Claim 2)

[1553] 2. The system according to claim 1, wherein the biometric data includes at least one of heart rate, eye movement data, and facial expression data.

[1554] (Claim 3)

[1555] 2. The system according to claim 1, wherein the relaxation environment provides virtual landscapes and fantastical locations using augmented reality and virtual reality technologies.

[1556] "Application example 2 when combining emotion engines"

[1557] (Claim 1)

[1558] a device for collecting biometric information;

[1559] a device comprising a generative model for analyzing the biometric information and determining the emotional state of a user;

[1560] an apparatus for providing a relaxation environment to a user based on said emotional state;

[1561] a device for writing and analyzing an emotion diary to respond to fluctuations in the emotional state;

[1562] a device for connecting the user to a social support group;

[1563] The system is intended for use by workers engaged in delivery work, and includes a means for monitoring the fatigue and stress of the workers in real time and providing a rest and relaxation environment as needed;

[1564] A system including:

[1565] (Claim 2)

[1566] 2. The system according to claim 1, wherein the biological information includes at least one of heart rate, eye movement, and facial expression data.

[1567] (Claim 3)

[1568] The system according to claim 1, characterized in that the relaxation environment provides virtual landscapes and fantastical places using AR or VR technology. [Explanation of symbols]

[1569] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a device for collecting biometric information; a device comprising a generative model for analyzing the biometric information and determining the emotional state of a user; an apparatus for providing a relaxation environment to a user based on said emotional state; a device for writing and analyzing an emotion diary to respond to fluctuations in the emotional state; Apparatus for connecting said user to a social support group A system including:

2. 2. The system according to claim 1, wherein the biological information includes at least one of heart rate, eye movement, and facial expression data.

3. The system according to claim 1, characterized in that the relaxation environment provides virtual landscapes and fantastical places using AR or VR technology.

Images