system

Abstract

We provide the system. [Solution] A means of acquiring and analyzing users' biometric data, A means for generating a virtual environment for relaxation based on acquired biometric data, A means of providing the generated virtual environment to the user, A means of collecting user feedback and optimizing the next experience, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, the increase in stress and lack of sleep have become major health problems. To address such situations, means for users to easily relax are in demand. However, the current relaxation methods cannot adequately respond to the individual states and preferences of users, and there is a problem that it is difficult to maximize stress reduction and relaxation effects.

Means for Solving the Problems

[0005] This invention provides a technology that acquires a user's biometric data in real time and automatically generates an optimal virtual environment for relaxation based on that data. Furthermore, it improves stress reduction by analyzing the user's past usage data and feedback and providing a personalized experience based on that analysis. It also includes a mechanism to continuously improve the quality of the experience by utilizing data accumulated through monitoring of the virtual environment being provided.

[0006] A "user" refers to an individual who enjoys a relaxation experience through a virtual environment.

[0007] "Biometric data" refers to information that indicates the user's physical condition, such as heart rate, brain waves, and stress levels.

[0008] "Analysis" refers to the process of identifying trends and patterns based on acquired data to support decision-making.

[0009] A "virtual environment" refers to a digitally generated space or landscape that is different from the real world.

[0010] "Generation" refers to the process of creating new content or data based on specific conditions.

[0011] "Providing" refers to the act of giving a user the opportunity to use a specific experience or service.

[0012] "Feedback" refers to the reactions and evaluations that users provide to the system.

[0013] "Optimization" refers to the process of improving something to maximize the results for a specific purpose.

[0014] "Monitoring" refers to the process of monitoring data in real time and understanding trends.

[0015] "Accumulation" refers to the act of organizing the collected data and storing it for later analysis.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] The present invention provides a means for users to enjoy a relaxation experience in a virtual reality environment. This system mainly consists of three elements: a server, a terminal, and a user.

[0038] First, when a user logs into the system, the device retrieves past usage data and feedback from the server. This collects data about the user's past experiences and preferences.

[0039] Subsequently, the terminal selects the optimal relaxation scenario based on this data and presents it to the user. Once the user selects their desired scenario, the server utilizes generative AI to optimize the selected scenario and automatically generates a virtual environment tailored to the individual user.

[0040] The generated virtual environment is provided to the user through the device. The user uses a VR device to immerse themselves in this environment and obtain a visually and aurally relaxing experience.

[0041] Simultaneously, the device monitors the user's biometric data in real time. Specifically, data such as heart rate and brain waves are acquired by sensors and transmitted to a server. The server aggregates this data, analyzes stress levels, and evaluates the effectiveness of the experience.

[0042] For example, if a user selects "Healing Forest," the server automatically generates a forest landscape with soothing sounds of wind and birdsong, taking into account sound frequencies and volumes that stabilize the heart rate. This allows the user to fully relax in that environment.

[0043] Once a session ends, the device provides the user with feedback based on their biometric data from that session. This includes fluctuations in stress levels and the degree of relaxation during the session, which can be used to improve future experiences.

[0044] Thus, the system of the present invention makes it possible to efficiently provide a virtual reality relaxation experience tailored to the user's characteristics and state.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user logs into the VR device. The device sends the user's authentication information to the server for authentication. If authentication is successful, the server sends the user's past usage history and feedback data to the device.

[0048] Step 2:

[0049] The device presents the user with potential relaxation scenarios based on data received from the server. These scenarios include a variety of natural environments and relaxing situations.

[0050] Step 3:

[0051] The user selects their preferred scenario from the presented options. The device then sends the selected scenario information to the server.

[0052] Step 4:

[0053] The server retrieves detailed data for the selected scenario and uses generative AI to automatically generate a customized virtual environment for the user. This includes optimizations based on the user's past usage data and feedback.

[0054] Step 5:

[0055] The generated virtual environment data is sent to the terminal. The terminal uses this data to provide the virtual environment to the user through a VR device.

[0056] Step 6:

[0057] While the user experiences relaxation in the VR environment, the device monitors biometric data such as heart rate and brainwaves in real time. The monitored data is transmitted from the device to the server.

[0058] Step 7:

[0059] The server analyzes the acquired biometric data and evaluates changes in stress levels. This evaluation result is used as feedback for future optimization.

[0060] Step 8:

[0061] After the session ends, the device displays feedback to the user based on their biometric data from the session. This allows the user to confirm the stress-reducing effect and use it to help them choose their next session.

[0062] (Example 1)

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

[0064] Conventional relaxation systems often lack the precision to assess stress levels using individual user biometric data, and fail to provide personalized support based on users' past usage patterns. This makes it difficult to offer users the optimal relaxation environment.

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

[0066] In this invention, the server includes means for collecting the user's biometric data, means for evaluating the stress level based on the acquired biometric data, and means for acquiring and analyzing the user's past usage data. This makes it possible to provide the user with an optimized relaxation experience.

[0067] "User" refers to an individual user who accesses the virtual environment and enjoys a relaxation experience.

[0068] "Biometric data" refers to data that indicates the user's physical condition, including measurements such as heart rate and brain waves.

[0069] "Stress level" is an indicator that shows the degree of mental and physical burden on a user, calculated based on biometric data.

[0070] "Usage data" refers to information about how users have used the system in the past, including specific usage history and feedback.

[0071] A "relaxation scenario" refers to a virtual environment experience plan built based on user data to maximize relaxation effects.

[0072] A "generative AI model" refers to an artificial intelligence program or algorithm used to automatically generate a virtual environment based on a user and their data.

[0073] A "virtual environment" refers to a computer-generated environment or space that a user experiences visually and aurally through a VR device.

[0074] "Feedback" refers to the evaluations and impressions that users provide after using a system, and includes information that is used to optimize the system.

[0075] The present invention automatically generates a virtual reality environment in which users can enjoy a relaxation experience optimized for their individual needs. This system operates based on three elements: a server, a terminal, and a user.

[0076] The server manages users' past usage data and feedback stored in a database and uses data analysis software to analyze it. Specifically, it utilizes the Python library Pandas. When a user accesses the system through a terminal and logs in, the server provides this data.

[0077] The terminal uses biosensors to transmit biometric data acquired from the user in real time to the server. These include devices such as heart rate sensors and electroencephalographs (EEGs). The server then uses this biometric data to assess the user's stress level and provides a customized virtual environment tailored to the user's condition.

[0078] Based on the relaxation scenario selected by the user, the server constructs a virtual environment using a generative AI model. This AI model is executed using machine learning platforms such as TENSORFLOW® and PyTorch. The final generated virtual environment is provided to the user via a terminal, and the user wears a VR device (e.g., Oculus Quest 2) and immerses themselves in this virtual space.

[0079] For example, if a user requests to relax in a "healing forest," the server generates a forest acoustic environment that considers frequencies that help stabilize the heart rate. This environment is presented through the device, allowing the user to relax comfortably.

[0080] Examples of prompt messages include the following:

[0081] "Create a relaxing virtual forest environment based on the user's heart rate data."

[0082] Thus, the present invention realizes a detailed relaxation experience tailored to the user's characteristics and condition.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] A user logs into the system using their terminal. The user enters their login information, which is then sent to the server via the terminal. The input is the user's login information, and the output is an authentication request. The server performs authentication based on this information. If authentication is successful, it retrieves the user's past usage data from the database and sends it to the terminal. The data analysis software used here is Pandas.

[0086] Step 2:

[0087] The terminal selects the optimal relaxation scenario using past usage data received from the server. The input is past usage data, and the output is the proposed scenario. The terminal performs data analysis calculations and analyzes the user's past preferences to present a individually customized relaxation scenario.

[0088] Step 3:

[0089] The user selects their desired relaxation scenario. Based on this selection, the terminal sends a prompt to the server. The input is the scenario selected by the user, and the output is a prompt to run the generative AI model. The server uses this prompt to begin generating a virtual environment using the generative AI model. The model uses TensorFlow.

[0090] Step 4:

[0091] The server uses a generative AI model to generate a virtual environment based on the user's biometric data and selected scenario. Inputs are biometric data and prompt messages, while output is data from the virtual environment. The server creates a individually customized virtual space and sends that data to the terminal.

[0092] Step 5:

[0093] The terminal provides the user with received virtual environment data through a VR device. The input is the virtual environment data, and the output is the visual and auditory information experienced by the user. The user puts on the device and begins a relaxation experience in the virtual environment.

[0094] Step 6:

[0095] The device monitors the user's biometric data in real time via biosensors and transmits the obtained data to a server. The input is biometric data, and the output is data transmission to the server. The server uses this data to analyze stress levels and evaluate the effectiveness of the experience.

[0096] Step 7:

[0097] Once the session ends, the terminal provides feedback to the user based on the analysis results from the server. The input is the analysis results from the server, and the output is feedback information for the user to refer to. This feedback will be used to optimize the experience for the next time.

[0098] (Application Example 1)

[0099] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0100] In modern society, providing effective relaxation to individual users amidst busy lifestyles and stressful environments is challenging. Furthermore, conventional relaxation methods lack sufficient optimization based on users' biometric information and individual preferences. Therefore, there is a need for systems that provide a more personalized relaxation experience.

[0101] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0102] In this invention, the server includes means for acquiring and analyzing the user's biometric information, means for generating a virtual environment for relaxation based on the acquired biometric information, and means for providing the generated virtual environment to the user. This makes it possible to provide a personalized relaxation experience tailored to the user's state and preferences.

[0103] "User biometric information" refers to biological data such as heart rate and brainwaves obtained from individual users.

[0104] "Means for generating a virtual environment" refers to a method for creating a digital environment for user relaxation based on the user's biometric information and past usage data.

[0105] "Methods for collecting and optimizing feedback" refers to the process of analyzing user feedback data and making improvements so that the next experience is more appropriate.

[0106] "Consumer-use machinery and devices" refer to devices such as robots that are used for personal purposes within the home and assist in daily life through various functions.

[0107] "A means of monitoring stress levels in real time" refers to technology that continuously monitors the user's stress level and adjusts the virtual environment as needed.

[0108] To implement this invention, a household robot as a consumer-grade mechanical device is used. This robot is equipped with a heart rate sensor and an electroencephalogram (EEG) sensor to acquire the user's biometric information. The biometric information obtained from the sensors is biological data such as the user's heart rate and brain waves, which is useful for personalizing relaxation.

[0109] The server generates a virtual environment for relaxation based on the user's biometric information and past usage data. Specifically, it utilizes a generative AI model to automatically generate scenarios optimized for the user's preferences using prompt messages. For example, a prompt message such as, "Based on the user's recent experience data and current heart rate, please suggest the optimal relaxation scenario and generate an effective combination of sound and visuals," might be used.

[0110] The generated virtual environment is delivered to the user via a robot. The robot is equipped with a display and speakers, enabling it to provide a visual and auditory relaxation experience. The robot also collects user feedback to optimize future experiences.

[0111] For example, after a user returns home, the robot might suggest a "calm seaside experience for relaxation," monitoring the user's heart rate while displaying the sounds of gentle waves and a beautiful sunset from a secluded spot. This system allows users to easily enjoy relaxing experiences in their daily lives.

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] The server receives the user's past usage data and biometric information. This includes real-time data such as heart rate and brainwaves, as well as past usage history. This information is stored in a database and prepared for the next processing step.

[0115] Step 2:

[0116] The server analyzes the acquired data. Specifically, it extracts elements that are presumed to have a high relaxation effect based on the user's current heart rate and past usage patterns. It uses a generative AI model to generate prompt messages. It creates a prompt message in the form of, "Please suggest the optimal relaxation scenario based on the user's recent experience data and current heart rate," and inputs it into the AI.

[0117] Step 3:

[0118] A generative AI model generates relaxation scenarios based on prompt text. This creates visual and auditory scenarios, and the data is returned to the server. The scenarios include elements such as scenery and music tailored to the user's preferences.

[0119] Step 4:

[0120] The device (a home robot) receives relaxation scenarios provided by the server. The device then uses its built-in display and speaker to deliver these scenarios to the user. Visual information is displayed on the screen, and auditory information is played through the speaker.

[0121] Step 5:

[0122] While the user is experiencing relaxation, the device continuously monitors their biometric information. Heart rate and brain waves are acquired in real time and transmitted to the server. The server receives this data and analyzes fluctuations in tension levels.

[0123] Step 6:

[0124] At the end of a relaxation session, the server provides feedback to the user based on the collected data. This feedback, displayed via the user's device, includes suggestions for improvement for the next session, such as changes in the user's tension level and which elements had the most relaxing effect.

[0125] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0126] This invention combines a system for users to enjoy a relaxation experience in a virtual reality environment with an emotion engine that recognizes emotions in real time. The system mainly consists of a server, a terminal, and a device including the emotion engine.

[0127] First, when a user logs into the VR terminal, the terminal collects past usage history and feedback data and sends it to the server. This data is used to generate relaxation scenarios. Furthermore, the emotion engine recognizes the user's emotions in real time from their facial expressions and speech. This emotion data is integrated with biometric data and sent to the server.

[0128] The server analyzes biometric and emotional data to assess the user's current psychological state. Based on this analysis, it uses generative AI to automatically generate an optimal virtual environment for the user. The generated virtual environment is then provided to the user via their terminal.

[0129] For example, if a user indicates an intention to "relax," the emotion engine might detect the user's tension. Based on this information, the server generates an environment that includes calming natural scenery and soft music, and provides it to the user. Through such dynamic environmental adjustments, the user can experience deeper relaxation.

[0130] Furthermore, all data during the virtual environment is monitored by the terminal, and the emotion engine makes additional adjustments in real time as needed. Once the session ends, the user receives feedback via the terminal, evaluating the experience. This feedback is used to optimize future experiences.

[0131] This system enables real-time environmental adjustment using an emotion engine, providing a high-quality relaxation experience that surpasses conventional relaxation methods.

[0132] The following describes the processing flow.

[0133] Step 1:

[0134] The user activates the VR device and logs in. The device sends the user's authentication information to the server, completing the authentication. After authentication, the server provides the device with the user's past usage history and feedback data.

[0135] Step 2:

[0136] The device analyzes past data received from the server and presents the user with suggested relaxation scenarios. The user then selects their preferred scenario from the presented options.

[0137] Step 3:

[0138] Scenario information selected by the user is sent to the server via the terminal. Simultaneously, the emotion engine recognizes the user's emotional state in real time from their facial expressions, voice, and gestures, and sends that data to the server.

[0139] Step 4:

[0140] The server aggregates all information, including biometric and emotional data, and begins processing to generate a virtual environment tailored to the user's psychological and physical state. The generation AI automatically creates the optimal environment.

[0141] Step 5:

[0142] The generated virtual environment data is sent to the terminal. The terminal provides this data to the user using a VR device, and the user begins the experience.

[0143] Step 6:

[0144] During the experience, the device works in conjunction with the emotion engine to continuously monitor the user's emotions and biometric data in real time. This allows the server to dynamically adjust the virtual environment as needed.

[0145] Step 7:

[0146] Once the session ends, the device displays detailed feedback to the user based on their emotions and biometric data from the session. The user can then see how their experience was optimized based on the displayed feedback.

[0147] Step 8:

[0148] The device sends feedback data to the server, which is used to optimize subsequent sessions. This is expected to further improve the user's relaxation experience.

[0149] (Example 2)

[0150] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0151] The relaxation experience needs to be optimized according to each user's instantaneous emotional and biological state, but conventional systems have not adequately performed this real-time adjustment. As a result, the relaxation effect was limited, and this did not lead to increased user satisfaction.

[0152] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0153] In this invention, the server includes means for collecting the user's biometric and emotional information in real time, means for generating an optimal virtual environment according to the user's state using a generative AI model, and means for receiving feedback from the user and optimizing the next relaxation scenario. This makes it possible to provide a relaxation experience that is immediately responsive to the user's emotional state, enabling more effective stress reduction and improved satisfaction.

[0154] "Biometric information" refers to data related to the user's physical condition, including physical data such as heart rate, skin temperature, and brain waves.

[0155] "Emotional information" refers to data that indicates the psychological state of a user, estimated from their facial expressions and voice analysis.

[0156] A "generative AI model" is an artificial intelligence program that processes a user's biometric and emotional information to automatically design the optimal virtual environment.

[0157] A "virtual environment" is a simulated space that combines digitized visual and auditory content experienced by the user.

[0158] "Feedback" refers to the evaluation and comments a user provides about a relaxation session after it has ended, and is used to improve future experiences.

[0159] A "user terminal" is a device that a user uses to access a virtual environment or relaxation experience and to send and receive data.

[0160] "Real-time" refers to a time frame in which data collection and processing are performed immediately, and the results are reflected quickly.

[0161] This system consists of a server, a terminal, and a device including an emotion engine. When a user logs into the VR terminal, the terminal collects the user's past usage history and feedback data and sends it to the server. This procedure allows the server to obtain the basic data needed to prepare a personalized relaxation scenario for the user. The emotion engine analyzes the user's emotions in real time from their facial expressions and voice, and sends this emotional information along with biometric data to the server.

[0162] The server utilizes a generative AI model implemented in Python or similar languages ​​to analyze biometric and emotional information. Based on the analysis results, it generates a virtual environment optimized for the user's psychological state. This virtual environment appeals to the user's visual and auditory senses, promoting relaxation. For example, if the user is feeling anxious, the server generates a calming environment including natural sounds and scenery, and provides it to the user through the terminal. The generative AI model is given a prompt such as, "Generate a relaxing environment to alleviate the user's anxiety."

[0163] Furthermore, the device continuously monitors the user in real time while they experience the virtual environment, and the emotion engine adjusts the environment as needed. If the user's state changes, the relaxation scenario can be dynamically modified accordingly. After the session ends, the user evaluates the experience, and this feedback is used to optimize the next relaxation scenario. This allows users to enjoy a more effective and personalized relaxation experience.

[0164] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0165] Step 1:

[0166] The user logs into the VR terminal. After login authentication, the terminal retrieves the user's past usage history and feedback data from its internal database. This data is then formatted and sent to the server. The input is the user's identification information, and the output is a set of usage history and feedback data.

[0167] Step 2:

[0168] The server analyzes usage history and feedback data received from the terminal. Using a data analysis algorithm, it extracts patterns of relaxation environments that users have previously preferred. The output is a standard for relaxation scenarios based on these patterns. This standard serves as a reference for generating the next environment.

[0169] Step 3:

[0170] An emotion engine runs on the device, capturing the user's facial expressions and voice data in real time. This emotional information is collected via the device's built-in sensors and microphone. The input is the user's facial expressions and voice, and the output is emotional data generated based on them. This data is sent to a server.

[0171] Step 4:

[0172] The server uses a generative AI model to comprehensively analyze biometric and emotional information. The AI ​​model receives this data along with the prompt "Generate a healing environment to alleviate the user's tension" and generates an optimal virtual environment tailored to the user's current psychological state. The output consists of virtual environment parameters, including visual and auditory information.

[0173] Step 5:

[0174] The server transmits the generated virtual environment to the terminal. The terminal renders that environment on the VR device and provides it to the user. This allows the user to experience a digitally displayed relaxation environment. The input is the virtual environment data from the server, and the output is the user's visual and auditory experience.

[0175] Step 6:

[0176] The terminal continuously monitors user responses in real time and analyzes newly collected data using an emotion engine. When a change in the user's state is detected, it sends that information to the server, which then dynamically adjusts the virtual environment. The output is the parameters of the adjusted virtual environment.

[0177] Step 7:

[0178] When a user ends their virtual environment session, the terminal displays a survey requesting feedback. The user's evaluation information is sent from the terminal to the server. This feedback is used as reference when generating future relaxation scenarios. The input is the user's evaluation information, and the output is an update to the feedback database.

[0179] (Application Example 2)

[0180] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0181] In modern society, stress and mental fatigue are significant problems faced by many people. Traditional relaxation methods lack the means to appropriately adjust the environment based on the user's real-time emotional state, and there is a need for more personalized relaxation experiences. Furthermore, support for relaxation in the home environment needs to be both convenient and effective. However, a systematic solution to make this possible has not existed.

[0182] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0183] In this invention, the server includes means for acquiring and analyzing the user's biometric information, means for generating a virtual environment for comfort based on the acquired biometric information, and means for recognizing the user's emotional state in real time and dynamically adjusting the virtual environment based on that information. This makes it possible to automatically generate an optimal relaxation environment according to the user's emotions and state, and to easily provide a high-quality relaxation experience in a home environment.

[0184] "Biometric information" refers to physiological data obtained from the user's body, such as heart rate, body temperature, and respiratory rate.

[0185] "Comfort optimization" is the process of adjusting the environment and services according to the user's psychological and physiological state.

[0186] A "virtual environment" is an artificial space created by a computer that a user can experience through sight and other senses.

[0187] "Real-time" refers to the process of information being processed instantly and without delay in response to actual ongoing events.

[0188] "Emotional state" refers to the psychological situation or mood a user is experiencing at a particular point in time.

[0189] The system for implementing this invention acquires the user's biometric information and emotional state, and generates an optimized virtual environment to provide the user with a real-time, personalized relaxation experience.

[0190] The system's main components are a server, a terminal, an emotion engine, and a display device. The terminal has the function of transmitting the user's biometric information to the emotion engine. This biometric information consists of physical data such as heart rate and body temperature. The emotion engine also analyzes the user's voice and facial expressions to recognize their emotional state in real time.

[0191] The server receives this data and uses a generative AI model to generate a virtual environment optimized for the user. This generative AI model dynamically adjusts the environment according to the user's current emotional state, while also considering the user's past usage history and feedback data.

[0192] For example, if a user tells their device via voice, "I want to relax today," the server generates a quiet forest scene based on data received from the emotion engine. This virtual environment is then presented to the user through the display device.

[0193] An example of a prompt would be, "If the user says 'I'm tired today,' what kind of virtual environment should be generated?" This question is used by the generative AI model to select an appropriate virtual environment.

[0194] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0195] Step 1:

[0196] The user logs into the device. In this step, the device receives the user's login information and sends past usage history and feedback data to the server. The input is the user's login information, and the output is the past usage data sent to the server. The device collects this data and uses it to create an optimal relaxation environment.

[0197] Step 2:

[0198] The device collects the user's biometric information and transmits it to the emotion engine. The input here is physiological data such as heart rate and body temperature obtained from sensors, while the output is analysis data passed to the emotion engine. The device acquires this data in real time and prepares to evaluate the user's state.

[0199] Step 3:

[0200] The emotion engine analyzes the user's biometric information, voice, and facial expressions to recognize their emotional state in real time. Input is biometric information transmitted from the device and the user's real-time voice and facial expression data; output is the analyzed emotional state. The emotion engine uses an emotion recognition algorithm to analyze the data and evaluate the type and intensity of the emotion.

[0201] Step 4:

[0202] The server uses emotional states from the emotion engine and past usage data to generate an appropriate virtual environment using a generative AI model. The input is the user's emotional state and usage history data, and the output is the virtual environment provided to the user. The server runs the generative AI model and constructs a dynamic virtual environment based on this input data.

[0203] Step 5:

[0204] The generated virtual environment is provided to the user through the terminal. The input here is the virtual environment data sent from the server, and the output is the virtual environment experienced by the user. The terminal sends this data to a display device, showing the user a relaxing environment in real time.

[0205] Step 6:

[0206] The user experiences a virtual environment and provides feedback to the terminal. The input is the user's feedback, and the output is data for optimizing the next session. The terminal records the user's feedback and sends it to the server for use in generating the next environment.

[0207] Step 7:

[0208] The server generates prompts to improve the next relaxation environment based on user feedback data, and uses them to train the generation AI model. At this point, the input is user-provided feedback, and the output is prompts that contribute to improving the generation AI model. The server analyzes the feedback and creates specific and effective prompts.

[0209] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0210] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0211] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0212] [Second Embodiment]

[0213] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0214] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0215] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0216] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0217] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0218] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0219] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0220] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0221] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0222] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0223] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0224] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0225] The present invention provides a means for users to enjoy a relaxation experience in a virtual reality environment. This system mainly consists of three elements: a server, a terminal, and a user.

[0226] First, when a user logs into the system, the device retrieves past usage data and feedback from the server. This collects data about the user's past experiences and preferences.

[0227] Subsequently, the terminal selects the optimal relaxation scenario based on this data and presents it to the user. Once the user selects their desired scenario, the server utilizes generative AI to optimize the selected scenario and automatically generates a virtual environment tailored to the individual user.

[0228] The generated virtual environment is provided to the user through the device. The user uses a VR device to immerse themselves in this environment and obtain a visually and aurally relaxing experience.

[0229] Simultaneously, the device monitors the user's biometric data in real time. Specifically, data such as heart rate and brain waves are acquired by sensors and transmitted to a server. The server aggregates this data, analyzes stress levels, and evaluates the effectiveness of the experience.

[0230] For example, if a user selects "Healing Forest," the server automatically generates a forest landscape with soothing sounds of wind and birdsong, taking into account sound frequencies and volumes that stabilize the heart rate. This allows the user to fully relax in that environment.

[0231] Once a session ends, the device provides the user with feedback based on their biometric data from that session. This includes fluctuations in stress levels and the degree of relaxation during the session, which can be used to improve future experiences.

[0232] Thus, the system of the present invention makes it possible to efficiently provide a virtual reality relaxation experience tailored to the user's characteristics and state.

[0233] The following describes the processing flow.

[0234] Step 1:

[0235] The user logs into the VR device. The device sends the user's authentication information to the server for authentication. If authentication is successful, the server sends the user's past usage history and feedback data to the device.

[0236] Step 2:

[0237] The device presents the user with potential relaxation scenarios based on data received from the server. These scenarios include a variety of natural environments and relaxing situations.

[0238] Step 3:

[0239] The user selects their preferred scenario from the presented options. The device then sends the selected scenario information to the server.

[0240] Step 4:

[0241] The server retrieves detailed data for the selected scenario and uses generative AI to automatically generate a customized virtual environment for the user. This includes optimizations based on the user's past usage data and feedback.

[0242] Step 5:

[0243] The generated virtual environment data is sent to the terminal. The terminal uses this data to provide the virtual environment to the user through a VR device.

[0244] Step 6:

[0245] While the user experiences relaxation in the VR environment, the device monitors biometric data such as heart rate and brainwaves in real time. The monitored data is transmitted from the device to the server.

[0246] Step 7:

[0247] The server analyzes the acquired biometric data and evaluates changes in stress levels. This evaluation result is used as feedback for future optimization.

[0248] Step 8:

[0249] After the session ends, the device displays feedback to the user based on their biometric data from the session. This allows the user to confirm the stress-reducing effect and use it to help them choose their next session.

[0250] (Example 1)

[0251] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0252] Conventional relaxation systems often lack the precision to assess stress levels using individual user biometric data, and fail to provide personalized support based on users' past usage patterns. This makes it difficult to offer users the optimal relaxation environment.

[0253] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0254] In this invention, the server includes means for collecting the user's biometric data, means for evaluating the stress level based on the acquired biometric data, and means for acquiring and analyzing the user's past usage data. This makes it possible to provide the user with an optimized relaxation experience.

[0255] "User" refers to an individual user who accesses the virtual environment and enjoys a relaxation experience.

[0256] "Biometric data" refers to data that indicates the user's physical condition, including measurements such as heart rate and brain waves.

[0257] "Stress level" is an indicator that shows the degree of mental and physical burden on a user, calculated based on biometric data.

[0258] "Usage data" refers to information about how users have used the system in the past, including specific usage history and feedback.

[0259] A "relaxation scenario" refers to a virtual environment experience plan built based on user data to maximize relaxation effects.

[0260] A "generative AI model" refers to an artificial intelligence program or algorithm used to automatically generate a virtual environment based on a user and their data.

[0261] A "virtual environment" refers to a computer-generated environment or space that a user experiences visually and aurally through a VR device.

[0262] "Feedback" refers to the evaluations and impressions that users provide after using a system, and includes information that is used to optimize the system.

[0263] The present invention automatically generates a virtual reality environment in which users can enjoy a relaxation experience optimized for their individual needs. This system operates based on three elements: a server, a terminal, and a user.

[0264] The server manages users' past usage data and feedback stored in a database and uses data analysis software to analyze it. Specifically, it utilizes the Python library Pandas. When a user accesses the system through a terminal and logs in, the server provides this data.

[0265] The terminal uses biosensors to transmit biometric data acquired from the user in real time to the server. These include devices such as heart rate sensors and electroencephalographs (EEGs). The server then uses this biometric data to assess the user's stress level and provides a customized virtual environment tailored to the user's condition.

[0266] Based on the relaxation scenario selected by the user, the server constructs a virtual environment using a generative AI model. This AI model is executed using machine learning platforms such as TensorFlow and PyTorch. The final generated virtual environment is provided to the user via a terminal, and the user puts on a VR device (e.g., Oculus Quest 2) and immerses themselves in this virtual space.

[0267] For example, if a user requests to relax in a "healing forest," the server generates a forest acoustic environment that considers frequencies that help stabilize the heart rate. This environment is presented through the device, allowing the user to relax comfortably.

[0268] Examples of prompt messages include the following:

[0269] "Create a relaxing virtual forest environment based on the user's heart rate data."

[0270] Thus, the present invention realizes a detailed relaxation experience tailored to the user's characteristics and condition.

[0271] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0272] Step 1:

[0273] A user logs into the system using their terminal. The user enters their login information, which is then sent to the server via the terminal. The input is the user's login information, and the output is an authentication request. The server performs authentication based on this information. If authentication is successful, it retrieves the user's past usage data from the database and sends it to the terminal. The data analysis software used here is Pandas.

[0274] Step 2:

[0275] The terminal selects the optimal relaxation scenario using past usage data received from the server. The input is past usage data, and the output is the proposed scenario. The terminal performs data analysis calculations and analyzes the user's past preferences to present a individually customized relaxation scenario.

[0276] Step 3:

[0277] The user selects their desired relaxation scenario. Based on this selection, the terminal sends a prompt to the server. The input is the scenario selected by the user, and the output is a prompt to run the generative AI model. The server uses this prompt to begin generating a virtual environment using the generative AI model. The model uses TensorFlow.

[0278] Step 4:

[0279] The server uses a generative AI model to generate a virtual environment based on the user's biometric data and selected scenario. Inputs are biometric data and prompt messages, while output is data from the virtual environment. The server creates a individually customized virtual space and sends that data to the terminal.

[0280] Step 5:

[0281] The terminal provides the received virtual environment data to the user through a VR device. The input is the data of the virtual environment, and the output is the visual and auditory information experienced by the user. The user wears the device and starts a relaxation experience in the virtual environment.

[0282] Step 6:

[0283] The terminal monitors the user's biological data in real time through a biosensor and transmits the obtained data to the server. The input is the biological data, and the output is the data transmission to the server. The server uses this to analyze the stress level and evaluate the effect of the experience.

[0284] Step 7:

[0285] When the session ends, the terminal provides feedback to the user based on the analysis result from the server. The input is the analysis result from the server, and the output is the feedback information for the user to refer to. This feedback is utilized for optimization during the next experience.

[0286] (Application Example 1)

[0287] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0288] In modern society, it is difficult to effectively provide relaxation for individual users in a busy life and a stressful environment. Also, there is a problem that conventional relaxation means do not sufficiently perform optimization based on the biological information and individual preferences of users. For this reason, a system for providing a more personalized relaxation experience is required.

[0289] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0290] In this invention, the server includes means for acquiring and analyzing the user's biometric information, means for generating a virtual environment for relaxation based on the acquired biometric information, and means for providing the generated virtual environment to the user. This makes it possible to provide a personalized relaxation experience tailored to the user's state and preferences.

[0291] "User biometric information" refers to biological data such as heart rate and brainwaves obtained from individual users.

[0292] "Means for generating a virtual environment" refers to a method for creating a digital environment for user relaxation based on the user's biometric information and past usage data.

[0293] "Methods for collecting and optimizing feedback" refers to the process of analyzing user feedback data and making improvements so that the next experience is more appropriate.

[0294] "Consumer-use machinery and devices" refer to devices such as robots that are used for personal purposes within the home and assist in daily life through various functions.

[0295] "A means of monitoring stress levels in real time" refers to technology that continuously monitors the user's stress level and adjusts the virtual environment as needed.

[0296] To implement this invention, a household robot as a consumer-grade mechanical device is used. This robot is equipped with a heart rate sensor and an electroencephalogram (EEG) sensor to acquire the user's biometric information. The biometric information obtained from the sensors is biological data such as the user's heart rate and brain waves, which is useful for personalizing relaxation.

[0297] The server generates a virtual environment for relaxation based on the user's biometric information and past usage data. Specifically, it utilizes a generative AI model to automatically generate scenarios optimized for the user's preferences using prompt messages. For example, a prompt message such as, "Based on the user's recent experience data and current heart rate, please suggest the optimal relaxation scenario and generate an effective combination of sound and visuals," might be used.

[0298] The generated virtual environment is delivered to the user via a robot. The robot is equipped with a display and speakers, enabling it to provide a visual and auditory relaxation experience. The robot also collects user feedback to optimize future experiences.

[0299] For example, after a user returns home, the robot might suggest a "calm seaside experience for relaxation," monitoring the user's heart rate while displaying the sounds of gentle waves and a beautiful sunset from a secluded spot. This system allows users to easily enjoy relaxing experiences in their daily lives.

[0300] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0301] Step 1:

[0302] The server receives the user's past usage data and biometric information. This includes real-time data such as heart rate and brainwaves, as well as past usage history. This information is stored in a database and prepared for the next processing step.

[0303] Step 2:

[0304] The server analyzes the acquired data. Specifically, based on the user's current heart rate and past usage patterns, it extracts elements that are presumed to have a high relaxation effect. It utilizes a generative AI model to generate a prompt sentence. A prompt sentence in the form of "Please propose an optimal relaxation scenario based on the user's recent experience data and current heart rate" is created and input into the AI.

[0305] Step 3:

[0306] The generative AI model generates a relaxation scenario based on the prompt sentence. As a result, visual and auditory scenarios are generated, and the data is returned to the server. The scenarios include elements such as landscapes and music that match the user's preferences.

[0307] Step 4:

[0308] The terminal (home robot) receives the relaxation scenario provided by the server. The terminal uses its built-in display and speaker to provide this scenario to the user. The visual information is displayed on the display, and the auditory information is played from the speaker.

[0309] Step 5:

[0310] During the user's relaxation experience, the terminal continuously monitors biometric information. Heart rate and brain waves are acquired in real-time and transmitted to the server. The server receives these data and analyzes the fluctuations in the stress level.

[0311] Step 6:

[0312] At the end of the relaxation session, the server provides feedback to the user based on the collected data. Feedback incorporating suggestions for improvement for the next time, such as changes in the user's stress level and which elements were most relaxing, is shown to the user through the terminal.

[0313] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0314] This invention combines a system for users to enjoy a relaxation experience in a virtual reality environment with an emotion engine that recognizes emotions in real time. The system mainly consists of a server, a terminal, and a device including the emotion engine.

[0315] First, when a user logs into the VR terminal, the terminal collects past usage history and feedback data and sends it to the server. This data is used to generate relaxation scenarios. Furthermore, the emotion engine recognizes the user's emotions in real time from their facial expressions and speech. This emotion data is integrated with biometric data and sent to the server.

[0316] The server analyzes biometric and emotional data to assess the user's current psychological state. Based on this analysis, it uses generative AI to automatically generate an optimal virtual environment for the user. The generated virtual environment is then provided to the user via their terminal.

[0317] For example, if a user indicates an intention to "relax," the emotion engine might detect the user's tension. Based on this information, the server generates an environment that includes calming natural scenery and soft music, and provides it to the user. Through such dynamic environmental adjustments, the user can experience deeper relaxation.

[0318] Furthermore, all data during the virtual environment is monitored by the terminal, and the emotion engine makes additional adjustments in real time as needed. Once the session ends, the user receives feedback via the terminal, evaluating the experience. This feedback is used to optimize future experiences.

[0319] This system enables real-time environmental adjustment using an emotion engine, providing a high-quality relaxation experience that surpasses conventional relaxation methods.

[0320] The following describes the processing flow.

[0321] Step 1:

[0322] The user activates the VR device and logs in. The device sends the user's authentication information to the server, completing the authentication. After authentication, the server provides the device with the user's past usage history and feedback data.

[0323] Step 2:

[0324] The device analyzes past data received from the server and presents the user with suggested relaxation scenarios. The user then selects their preferred scenario from the presented options.

[0325] Step 3:

[0326] Scenario information selected by the user is sent to the server via the terminal. Simultaneously, the emotion engine recognizes the user's emotional state in real time from their facial expressions, voice, and gestures, and sends that data to the server.

[0327] Step 4:

[0328] The server aggregates all information, including biometric and emotional data, and begins processing to generate a virtual environment tailored to the user's psychological and physical state. The generation AI automatically creates the optimal environment.

[0329] Step 5:

[0330] The generated virtual environment data is sent to the terminal. The terminal provides this data to the user using a VR device, and the user begins the experience.

[0331] Step 6:

[0332] During the experience, the device works in conjunction with the emotion engine to continuously monitor the user's emotions and biometric data in real time. This allows the server to dynamically adjust the virtual environment as needed.

[0333] Step 7:

[0334] Once the session ends, the device displays detailed feedback to the user based on their emotions and biometric data from the session. The user can then see how their experience was optimized based on the displayed feedback.

[0335] Step 8:

[0336] The device sends feedback data to the server, which is used to optimize subsequent sessions. This is expected to further improve the user's relaxation experience.

[0337] (Example 2)

[0338] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0339] The relaxation experience needs to be optimized according to each user's instantaneous emotional and biological state, but conventional systems have not adequately performed this real-time adjustment. As a result, the relaxation effect was limited, and this did not lead to increased user satisfaction.

[0340] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0341] In this invention, the server includes means for collecting the user's biometric and emotional information in real time, means for generating an optimal virtual environment according to the user's state using a generative AI model, and means for receiving feedback from the user and optimizing the next relaxation scenario. This makes it possible to provide a relaxation experience that is immediately responsive to the user's emotional state, enabling more effective stress reduction and improved satisfaction.

[0342] "Biometric information" refers to data related to the user's physical condition, including physical data such as heart rate, skin temperature, and brain waves.

[0343] "Emotional information" refers to data that indicates the psychological state of a user, estimated from their facial expressions and voice analysis.

[0344] A "generative AI model" is an artificial intelligence program that processes a user's biometric and emotional information to automatically design the optimal virtual environment.

[0345] A "virtual environment" is a simulated space that combines digitized visual and auditory content experienced by the user.

[0346] "Feedback" refers to the evaluation and comments a user provides about a relaxation session after it has ended, and is used to improve future experiences.

[0347] A "user terminal" is a device that a user uses to access a virtual environment or relaxation experience and to send and receive data.

[0348] "Real-time" refers to a time frame in which data collection and processing are performed immediately, and the results are reflected quickly.

[0349] This system consists of a server, a terminal, and a device including an emotion engine. When a user logs into the VR terminal, the terminal collects the user's past usage history and feedback data and sends it to the server. This procedure allows the server to obtain the basic data needed to prepare a personalized relaxation scenario for the user. The emotion engine analyzes the user's emotions in real time from their facial expressions and voice, and sends this emotional information along with biometric data to the server.

[0350] The server utilizes a generative AI model implemented in Python or similar languages ​​to analyze biometric and emotional information. Based on the analysis results, it generates a virtual environment optimized for the user's psychological state. This virtual environment appeals to the user's visual and auditory senses, promoting relaxation. For example, if the user is feeling anxious, the server generates a calming environment including natural sounds and scenery, and provides it to the user through the terminal. The generative AI model is given a prompt such as, "Generate a relaxing environment to alleviate the user's anxiety."

[0351] Furthermore, the device continuously monitors the user in real time while they experience the virtual environment, and the emotion engine adjusts the environment as needed. If the user's state changes, the relaxation scenario can be dynamically modified accordingly. After the session ends, the user evaluates the experience, and this feedback is used to optimize the next relaxation scenario. This allows users to enjoy a more effective and personalized relaxation experience.

[0352] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0353] Step 1:

[0354] The user logs into the VR terminal. After login authentication, the terminal retrieves the user's past usage history and feedback data from its internal database. This data is then formatted and sent to the server. The input is the user's identification information, and the output is a set of usage history and feedback data.

[0355] Step 2:

[0356] The server analyzes usage history and feedback data received from the terminal. Using a data analysis algorithm, it extracts patterns of relaxation environments that users have previously preferred. The output is a standard for relaxation scenarios based on these patterns. This standard serves as a reference for generating the next environment.

[0357] Step 3:

[0358] An emotion engine runs on the device, capturing the user's facial expressions and voice data in real time. This emotional information is collected via the device's built-in sensors and microphone. The input is the user's facial expressions and voice, and the output is emotional data generated based on them. This data is sent to a server.

[0359] Step 4:

[0360] The server uses a generative AI model to comprehensively analyze biometric and emotional information. The AI ​​model receives this data along with the prompt "Generate a healing environment to alleviate the user's tension" and generates an optimal virtual environment tailored to the user's current psychological state. The output consists of virtual environment parameters, including visual and auditory information.

[0361] Step 5:

[0362] The server transmits the generated virtual environment to the terminal. The terminal renders that environment on the VR device and provides it to the user. This allows the user to experience a digitally displayed relaxation environment. The input is the virtual environment data from the server, and the output is the user's visual and auditory experience.

[0363] Step 6:

[0364] The terminal continuously monitors user responses in real time and analyzes newly collected data using an emotion engine. When a change in the user's state is detected, it sends that information to the server, which then dynamically adjusts the virtual environment. The output is the parameters of the adjusted virtual environment.

[0365] Step 7:

[0366] When a user ends their virtual environment session, the terminal displays a survey requesting feedback. The user's evaluation information is sent from the terminal to the server. This feedback is used as reference when generating future relaxation scenarios. The input is the user's evaluation information, and the output is an update to the feedback database.

[0367] (Application Example 2)

[0368] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0369] In modern society, stress and mental fatigue are significant problems faced by many people. Traditional relaxation methods lack the means to appropriately adjust the environment based on the user's real-time emotional state, and there is a need for more personalized relaxation experiences. Furthermore, support for relaxation in the home environment needs to be both convenient and effective. However, a systematic solution to make this possible has not existed.

[0370] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0371] In this invention, the server includes means for acquiring and analyzing the user's biometric information, means for generating a virtual environment for comfort based on the acquired biometric information, and means for recognizing the user's emotional state in real time and dynamically adjusting the virtual environment based on that information. This makes it possible to automatically generate an optimal relaxation environment according to the user's emotions and state, and to easily provide a high-quality relaxation experience in a home environment.

[0372] "Biometric information" refers to physiological data obtained from the user's body, such as heart rate, body temperature, and respiratory rate.

[0373] "Comfort optimization" is the process of adjusting the environment and services according to the user's psychological and physiological state.

[0374] A "virtual environment" is an artificial space created by a computer that a user can experience through sight and other senses.

[0375] "Real-time" refers to the process of information being processed instantly and without delay in response to actual ongoing events.

[0376] "Emotional state" refers to the psychological situation or mood a user is experiencing at a particular point in time.

[0377] The system for implementing this invention acquires the user's biometric information and emotional state, and generates an optimized virtual environment to provide the user with a real-time, personalized relaxation experience.

[0378] The system's main components are a server, a terminal, an emotion engine, and a display device. The terminal has the function of transmitting the user's biometric information to the emotion engine. This biometric information consists of physical data such as heart rate and body temperature. The emotion engine also analyzes the user's voice and facial expressions to recognize their emotional state in real time.

[0379] The server receives this data and uses a generative AI model to generate a virtual environment optimized for the user. This generative AI model dynamically adjusts the environment according to the user's current emotional state, while also considering the user's past usage history and feedback data.

[0380] For example, if a user tells their device via voice, "I want to relax today," the server generates a quiet forest scene based on data received from the emotion engine. This virtual environment is then presented to the user through the display device.

[0381] An example of a prompt would be, "If the user says 'I'm tired today,' what kind of virtual environment should be generated?" This question is used by the generative AI model to select an appropriate virtual environment.

[0382] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0383] Step 1:

[0384] The user logs into the device. In this step, the device receives the user's login information and sends past usage history and feedback data to the server. The input is the user's login information, and the output is the past usage data sent to the server. The device collects this data and uses it to create an optimal relaxation environment.

[0385] Step 2:

[0386] The device collects the user's biometric information and transmits it to the emotion engine. The input here is physiological data such as heart rate and body temperature obtained from sensors, while the output is analysis data passed to the emotion engine. The device acquires this data in real time and prepares to evaluate the user's state.

[0387] Step 3:

[0388] The emotion engine analyzes the user's biometric information, voice, and facial expressions to recognize their emotional state in real time. Input is biometric information transmitted from the device and the user's real-time voice and facial expression data; output is the analyzed emotional state. The emotion engine uses an emotion recognition algorithm to analyze the data and evaluate the type and intensity of the emotion.

[0389] Step 4:

[0390] The server uses emotional states from the emotion engine and past usage data to generate an appropriate virtual environment using a generative AI model. The input is the user's emotional state and usage history data, and the output is the virtual environment provided to the user. The server runs the generative AI model and constructs a dynamic virtual environment based on this input data.

[0391] Step 5:

[0392] The generated virtual environment is provided to the user through the terminal. The input here is the virtual environment data sent from the server, and the output is the virtual environment experienced by the user. The terminal sends this data to a display device, showing the user a relaxing environment in real time.

[0393] Step 6:

[0394] The user experiences a virtual environment and provides feedback to the terminal. The input is the user's feedback, and the output is data for optimizing the next session. The terminal records the user's feedback and sends it to the server for use in generating the next environment.

[0395] Step 7:

[0396] The server generates prompts to improve the next relaxation environment based on user feedback data, and uses them to train the generation AI model. At this point, the input is user-provided feedback, and the output is prompts that contribute to improving the generation AI model. The server analyzes the feedback and creates specific and effective prompts.

[0397] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0398] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0399] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0400] [Third Embodiment]

[0401] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0402] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0403] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0404] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0405] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0406] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0407] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0408] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0409] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0410] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0411] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0412] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0413] The present invention provides a means for users to enjoy a relaxation experience in a virtual reality environment. This system mainly consists of three elements: a server, a terminal, and a user.

[0414] First, when a user logs into the system, the device retrieves past usage data and feedback from the server. This collects data about the user's past experiences and preferences.

[0415] Subsequently, the terminal selects the optimal relaxation scenario based on this data and presents it to the user. Once the user selects their desired scenario, the server utilizes generative AI to optimize the selected scenario and automatically generates a virtual environment tailored to the individual user.

[0416] The generated virtual environment is provided to the user through the device. The user uses a VR device to immerse themselves in this environment and obtain a visually and aurally relaxing experience.

[0417] Simultaneously, the device monitors the user's biometric data in real time. Specifically, data such as heart rate and brain waves are acquired by sensors and transmitted to a server. The server aggregates this data, analyzes stress levels, and evaluates the effectiveness of the experience.

[0418] For example, if a user selects "Healing Forest," the server automatically generates a forest landscape with soothing sounds of wind and birdsong, taking into account sound frequencies and volumes that stabilize the heart rate. This allows the user to fully relax in that environment.

[0419] Once a session ends, the device provides the user with feedback based on their biometric data from that session. This includes fluctuations in stress levels and the degree of relaxation during the session, which can be used to improve future experiences.

[0420] Thus, the system of the present invention makes it possible to efficiently provide a virtual reality relaxation experience tailored to the user's characteristics and state.

[0421] The following describes the processing flow.

[0422] Step 1:

[0423] The user logs into the VR device. The device sends the user's authentication information to the server for authentication. If authentication is successful, the server sends the user's past usage history and feedback data to the device.

[0424] Step 2:

[0425] The device presents the user with potential relaxation scenarios based on data received from the server. These scenarios include a variety of natural environments and relaxing situations.

[0426] Step 3:

[0427] The user selects their preferred scenario from the presented options. The device then sends the selected scenario information to the server.

[0428] Step 4:

[0429] The server retrieves detailed data for the selected scenario and uses generative AI to automatically generate a customized virtual environment for the user. This includes optimizations based on the user's past usage data and feedback.

[0430] Step 5:

[0431] The generated virtual environment data is sent to the terminal. The terminal uses this data to provide the virtual environment to the user through a VR device.

[0432] Step 6:

[0433] While the user experiences relaxation in the VR environment, the device monitors biometric data such as heart rate and brainwaves in real time. The monitored data is transmitted from the device to the server.

[0434] Step 7:

[0435] The server analyzes the acquired biometric data and evaluates changes in stress levels. This evaluation result is used as feedback for future optimization.

[0436] Step 8:

[0437] After the session ends, the device displays feedback to the user based on their biometric data from the session. This allows the user to confirm the stress-reducing effect and use it to help them choose their next session.

[0438] (Example 1)

[0439] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0440] Conventional relaxation systems often lack the precision to assess stress levels using individual user biometric data, and fail to provide personalized support based on users' past usage patterns. This makes it difficult to offer users the optimal relaxation environment.

[0441] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0442] In this invention, the server includes means for collecting the user's biometric data, means for evaluating the stress level based on the acquired biometric data, and means for acquiring and analyzing the user's past usage data. This makes it possible to provide the user with an optimized relaxation experience.

[0443] "User" refers to an individual user who accesses the virtual environment and enjoys a relaxation experience.

[0444] "Biometric data" refers to data that indicates the user's physical condition, including measurements such as heart rate and brain waves.

[0445] "Stress level" is an indicator that shows the degree of mental and physical burden on a user, calculated based on biometric data.

[0446] "Usage data" refers to information about how users have used the system in the past, including specific usage history and feedback.

[0447] A "relaxation scenario" refers to a virtual environment experience plan built based on user data to maximize relaxation effects.

[0448] A "generative AI model" refers to an artificial intelligence program or algorithm used to automatically generate a virtual environment based on a user and their data.

[0449] A "virtual environment" refers to a computer-generated environment or space that a user experiences visually and aurally through a VR device.

[0450] "Feedback" refers to the evaluations and impressions that users provide after using a system, and includes information that is used to optimize the system.

[0451] The present invention automatically generates a virtual reality environment in which users can enjoy a relaxation experience optimized for their individual needs. This system operates based on three elements: a server, a terminal, and a user.

[0452] The server manages users' past usage data and feedback stored in a database and uses data analysis software to analyze it. Specifically, it utilizes the Python library Pandas. When a user accesses the system through a terminal and logs in, the server provides this data.

[0453] The terminal uses biosensors to transmit biometric data acquired from the user in real time to the server. These include devices such as heart rate sensors and electroencephalographs (EEGs). The server then uses this biometric data to assess the user's stress level and provides a customized virtual environment tailored to the user's condition.

[0454] Based on the relaxation scenario selected by the user, the server constructs a virtual environment using a generative AI model. This AI model is executed using machine learning platforms such as TensorFlow and PyTorch. The final generated virtual environment is provided to the user via a terminal, and the user puts on a VR device (e.g., Oculus Quest 2) and immerses themselves in this virtual space.

[0455] For example, if a user requests to relax in a "healing forest," the server generates a forest acoustic environment that considers frequencies that help stabilize the heart rate. This environment is presented through the device, allowing the user to relax comfortably.

[0456] Examples of prompt messages include the following:

[0457] "Create a relaxing virtual forest environment based on the user's heart rate data."

[0458] Thus, the present invention realizes a detailed relaxation experience tailored to the user's characteristics and condition.

[0459] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0460] Step 1:

[0461] A user logs into the system using their terminal. The user enters their login information, which is then sent to the server via the terminal. The input is the user's login information, and the output is an authentication request. The server performs authentication based on this information. If authentication is successful, it retrieves the user's past usage data from the database and sends it to the terminal. The data analysis software used here is Pandas.

[0462] Step 2:

[0463] The terminal selects the optimal relaxation scenario using past usage data received from the server. The input is past usage data, and the output is the proposed scenario. The terminal performs data analysis calculations and analyzes the user's past preferences to present a individually customized relaxation scenario.

[0464] Step 3:

[0465] The user selects their desired relaxation scenario. Based on this selection, the terminal sends a prompt to the server. The input is the scenario selected by the user, and the output is a prompt to run the generative AI model. The server uses this prompt to begin generating a virtual environment using the generative AI model. The model uses TensorFlow.

[0466] Step 4:

[0467] The server uses a generative AI model to generate a virtual environment based on the user's biometric data and selected scenario. Inputs are biometric data and prompt messages, while output is data from the virtual environment. The server creates a individually customized virtual space and sends that data to the terminal.

[0468] Step 5:

[0469] The terminal provides the user with received virtual environment data through a VR device. The input is the virtual environment data, and the output is the visual and auditory information experienced by the user. The user puts on the device and begins a relaxation experience in the virtual environment.

[0470] Step 6:

[0471] The device monitors the user's biometric data in real time via biosensors and transmits the obtained data to a server. The input is biometric data, and the output is data transmission to the server. The server uses this data to analyze stress levels and evaluate the effectiveness of the experience.

[0472] Step 7:

[0473] Once the session ends, the terminal provides feedback to the user based on the analysis results from the server. The input is the analysis results from the server, and the output is feedback information for the user to refer to. This feedback will be used to optimize the experience for the next time.

[0474] (Application Example 1)

[0475] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0476] In modern society, providing effective relaxation to individual users amidst busy lifestyles and stressful environments is challenging. Furthermore, conventional relaxation methods lack sufficient optimization based on users' biometric information and individual preferences. Therefore, there is a need for systems that provide a more personalized relaxation experience.

[0477] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0478] In this invention, the server includes means for acquiring and analyzing the user's biometric information, means for generating a virtual environment for relaxation based on the acquired biometric information, and means for providing the generated virtual environment to the user. This makes it possible to provide a personalized relaxation experience tailored to the user's state and preferences.

[0479] "User biometric information" refers to biological data such as heart rate and brainwaves obtained from individual users.

[0480] "Means for generating a virtual environment" refers to a method for creating a digital environment for user relaxation based on the user's biometric information and past usage data.

[0481] "Methods for collecting and optimizing feedback" refers to the process of analyzing user feedback data and making improvements so that the next experience is more appropriate.

[0482] "Consumer-use machinery and devices" refer to devices such as robots that are used for personal purposes within the home and assist in daily life through various functions.

[0483] "A means of monitoring stress levels in real time" refers to technology that continuously monitors the user's stress level and adjusts the virtual environment as needed.

[0484] To implement this invention, a household robot as a consumer-grade mechanical device is used. This robot is equipped with a heart rate sensor and an electroencephalogram (EEG) sensor to acquire the user's biometric information. The biometric information obtained from the sensors is biological data such as the user's heart rate and brain waves, which is useful for personalizing relaxation.

[0485] The server generates a virtual environment for relaxation based on the user's biometric information and past usage data. Specifically, it utilizes a generative AI model to automatically generate scenarios optimized for the user's preferences using prompt messages. For example, a prompt message such as, "Based on the user's recent experience data and current heart rate, please suggest the optimal relaxation scenario and generate an effective combination of sound and visuals," might be used.

[0486] The generated virtual environment is delivered to the user via a robot. The robot is equipped with a display and speakers, enabling it to provide a visual and auditory relaxation experience. The robot also collects user feedback to optimize future experiences.

[0487] For example, after a user returns home, the robot might suggest a "calm seaside experience for relaxation," monitoring the user's heart rate while displaying the sounds of gentle waves and a beautiful sunset from a secluded spot. This system allows users to easily enjoy relaxing experiences in their daily lives.

[0488] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0489] Step 1:

[0490] The server receives the user's past usage data and biometric information. This includes real-time data such as heart rate and brainwaves, as well as past usage history. This information is stored in a database and prepared for the next processing step.

[0491] Step 2:

[0492] The server analyzes the acquired data. Specifically, it extracts elements that are presumed to have a high relaxation effect based on the user's current heart rate and past usage patterns. It uses a generative AI model to generate prompt messages. It creates a prompt message in the form of, "Please suggest the optimal relaxation scenario based on the user's recent experience data and current heart rate," and inputs it into the AI.

[0493] Step 3:

[0494] A generative AI model generates relaxation scenarios based on prompt text. This creates visual and auditory scenarios, and the data is returned to the server. The scenarios include elements such as scenery and music tailored to the user's preferences.

[0495] Step 4:

[0496] The device (a home robot) receives relaxation scenarios provided by the server. The device then uses its built-in display and speaker to deliver these scenarios to the user. Visual information is displayed on the screen, and auditory information is played through the speaker.

[0497] Step 5:

[0498] While the user is experiencing relaxation, the device continuously monitors their biometric information. Heart rate and brain waves are acquired in real time and transmitted to the server. The server receives this data and analyzes fluctuations in tension levels.

[0499] Step 6:

[0500] At the end of a relaxation session, the server provides feedback to the user based on the collected data. This feedback, displayed via the user's device, includes suggestions for improvement for the next session, such as changes in the user's tension level and which elements had the most relaxing effect.

[0501] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0502] This invention combines a system for users to enjoy a relaxation experience in a virtual reality environment with an emotion engine that recognizes emotions in real time. The system mainly consists of a server, a terminal, and a device including the emotion engine.

[0503] First, when a user logs into the VR terminal, the terminal collects past usage history and feedback data and sends it to the server. This data is used to generate relaxation scenarios. Furthermore, the emotion engine recognizes the user's emotions in real time from their facial expressions and speech. This emotion data is integrated with biometric data and sent to the server.

[0504] The server analyzes biometric and emotional data to assess the user's current psychological state. Based on this analysis, it uses generative AI to automatically generate an optimal virtual environment for the user. The generated virtual environment is then provided to the user via their terminal.

[0505] For example, if a user indicates an intention to "relax," the emotion engine might detect the user's tension. Based on this information, the server generates an environment that includes calming natural scenery and soft music, and provides it to the user. Through such dynamic environmental adjustments, the user can experience deeper relaxation.

[0506] Furthermore, all data during the virtual environment is monitored by the terminal, and the emotion engine makes additional adjustments in real time as needed. Once the session ends, the user receives feedback via the terminal, evaluating the experience. This feedback is used to optimize future experiences.

[0507] This system enables real-time environmental adjustment using an emotion engine, providing a high-quality relaxation experience that surpasses conventional relaxation methods.

[0508] The following describes the processing flow.

[0509] Step 1:

[0510] The user activates the VR device and logs in. The device sends the user's authentication information to the server, completing the authentication. After authentication, the server provides the device with the user's past usage history and feedback data.

[0511] Step 2:

[0512] The device analyzes past data received from the server and presents the user with suggested relaxation scenarios. The user then selects their preferred scenario from the presented options.

[0513] Step 3:

[0514] Scenario information selected by the user is sent to the server via the terminal. Simultaneously, the emotion engine recognizes the user's emotional state in real time from their facial expressions, voice, and gestures, and sends that data to the server.

[0515] Step 4:

[0516] The server aggregates all information, including biometric and emotional data, and begins processing to generate a virtual environment tailored to the user's psychological and physical state. The generation AI automatically creates the optimal environment.

[0517] Step 5:

[0518] The generated virtual environment data is sent to the terminal. The terminal provides this data to the user using a VR device, and the user begins the experience.

[0519] Step 6:

[0520] During the experience, the device works in conjunction with the emotion engine to continuously monitor the user's emotions and biometric data in real time. This allows the server to dynamically adjust the virtual environment as needed.

[0521] Step 7:

[0522] Once the session ends, the device displays detailed feedback to the user based on their emotions and biometric data from the session. The user can then see how their experience was optimized based on the displayed feedback.

[0523] Step 8:

[0524] The device sends feedback data to the server, which is used to optimize subsequent sessions. This is expected to further improve the user's relaxation experience.

[0525] (Example 2)

[0526] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0527] The relaxation experience needs to be optimized according to each user's instantaneous emotional and biological state, but conventional systems have not adequately performed this real-time adjustment. As a result, the relaxation effect was limited, and this did not lead to increased user satisfaction.

[0528] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0529] In this invention, the server includes means for collecting the user's biometric and emotional information in real time, means for generating an optimal virtual environment according to the user's state using a generative AI model, and means for receiving feedback from the user and optimizing the next relaxation scenario. This makes it possible to provide a relaxation experience that is immediately responsive to the user's emotional state, enabling more effective stress reduction and improved satisfaction.

[0530] "Biometric information" refers to data related to the user's physical condition, including physical data such as heart rate, skin temperature, and brain waves.

[0531] "Emotional information" refers to data that indicates the psychological state of a user, estimated from their facial expressions and voice analysis.

[0532] A "generative AI model" is an artificial intelligence program that processes a user's biometric and emotional information to automatically design the optimal virtual environment.

[0533] A "virtual environment" is a simulated space that combines digitized visual and auditory content experienced by the user.

[0534] "Feedback" refers to the evaluation and comments a user provides about a relaxation session after it has ended, and is used to improve future experiences.

[0535] A "user terminal" is a device that a user uses to access a virtual environment or relaxation experience and to send and receive data.

[0536] "Real-time" refers to a time frame in which data collection and processing are performed immediately, and the results are reflected quickly.

[0537] This system consists of a server, a terminal, and a device including an emotion engine. When a user logs into the VR terminal, the terminal collects the user's past usage history and feedback data and sends it to the server. This procedure allows the server to obtain the basic data needed to prepare a personalized relaxation scenario for the user. The emotion engine analyzes the user's emotions in real time from their facial expressions and voice, and sends this emotional information along with biometric data to the server.

[0538] The server utilizes a generative AI model implemented in Python or similar languages ​​to analyze biometric and emotional information. Based on the analysis results, it generates a virtual environment optimized for the user's psychological state. This virtual environment appeals to the user's visual and auditory senses, promoting relaxation. For example, if the user is feeling anxious, the server generates a calming environment including natural sounds and scenery, and provides it to the user through the terminal. The generative AI model is given a prompt such as, "Generate a relaxing environment to alleviate the user's anxiety."

[0539] Furthermore, the device continuously monitors the user in real time while they experience the virtual environment, and the emotion engine adjusts the environment as needed. If the user's state changes, the relaxation scenario can be dynamically modified accordingly. After the session ends, the user evaluates the experience, and this feedback is used to optimize the next relaxation scenario. This allows users to enjoy a more effective and personalized relaxation experience.

[0540] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0541] Step 1:

[0542] The user logs into the VR terminal. After login authentication, the terminal retrieves the user's past usage history and feedback data from its internal database. This data is then formatted and sent to the server. The input is the user's identification information, and the output is a set of usage history and feedback data.

[0543] Step 2:

[0544] The server analyzes usage history and feedback data received from the terminal. Using a data analysis algorithm, it extracts patterns of relaxation environments that users have previously preferred. The output is a standard for relaxation scenarios based on these patterns. This standard serves as a reference for generating the next environment.

[0545] Step 3:

[0546] An emotion engine runs on the device, capturing the user's facial expressions and voice data in real time. This emotional information is collected via the device's built-in sensors and microphone. The input is the user's facial expressions and voice, and the output is emotional data generated based on them. This data is sent to a server.

[0547] Step 4:

[0548] The server uses a generative AI model to comprehensively analyze biometric and emotional information. The AI ​​model receives this data along with the prompt "Generate a healing environment to alleviate the user's tension" and generates an optimal virtual environment tailored to the user's current psychological state. The output consists of virtual environment parameters, including visual and auditory information.

[0549] Step 5:

[0550] The server transmits the generated virtual environment to the terminal. The terminal renders that environment on the VR device and provides it to the user. This allows the user to experience a digitally displayed relaxation environment. The input is the virtual environment data from the server, and the output is the user's visual and auditory experience.

[0551] Step 6:

[0552] The terminal continuously monitors user responses in real time and analyzes newly collected data using an emotion engine. When a change in the user's state is detected, it sends that information to the server, which then dynamically adjusts the virtual environment. The output is the parameters of the adjusted virtual environment.

[0553] Step 7:

[0554] When a user ends their virtual environment session, the terminal displays a survey requesting feedback. The user's evaluation information is sent from the terminal to the server. This feedback is used as reference when generating future relaxation scenarios. The input is the user's evaluation information, and the output is an update to the feedback database.

[0555] (Application Example 2)

[0556] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0557] In modern society, stress and mental fatigue are significant problems faced by many people. Traditional relaxation methods lack the means to appropriately adjust the environment based on the user's real-time emotional state, and there is a need for more personalized relaxation experiences. Furthermore, support for relaxation in the home environment needs to be both convenient and effective. However, a systematic solution to make this possible has not existed.

[0558] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0559] In this invention, the server includes means for acquiring and analyzing the user's biometric information, means for generating a virtual environment for comfort based on the acquired biometric information, and means for recognizing the user's emotional state in real time and dynamically adjusting the virtual environment based on that information. This makes it possible to automatically generate an optimal relaxation environment according to the user's emotions and state, and to easily provide a high-quality relaxation experience in a home environment.

[0560] "Biometric information" refers to physiological data obtained from the user's body, such as heart rate, body temperature, and respiratory rate.

[0561] "Comfort optimization" is the process of adjusting the environment and services according to the user's psychological and physiological state.

[0562] A "virtual environment" is an artificial space created by a computer that a user can experience through sight and other senses.

[0563] "Real-time" refers to the process of information being processed instantly and without delay in response to actual ongoing events.

[0564] "Emotional state" refers to the psychological situation or mood a user is experiencing at a particular point in time.

[0565] The system for implementing this invention acquires the user's biometric information and emotional state, and generates an optimized virtual environment to provide the user with a real-time, personalized relaxation experience.

[0566] The system's main components are a server, a terminal, an emotion engine, and a display device. The terminal has the function of transmitting the user's biometric information to the emotion engine. This biometric information consists of physical data such as heart rate and body temperature. The emotion engine also analyzes the user's voice and facial expressions to recognize their emotional state in real time.

[0567] The server receives this data and uses a generative AI model to generate a virtual environment optimized for the user. This generative AI model dynamically adjusts the environment according to the user's current emotional state, while also considering the user's past usage history and feedback data.

[0568] For example, if a user tells their device via voice, "I want to relax today," the server generates a quiet forest scene based on data received from the emotion engine. This virtual environment is then presented to the user through the display device.

[0569] An example of a prompt would be, "If the user says 'I'm tired today,' what kind of virtual environment should be generated?" This question is used by the generative AI model to select an appropriate virtual environment.

[0570] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0571] Step 1:

[0572] The user logs into the device. In this step, the device receives the user's login information and sends past usage history and feedback data to the server. The input is the user's login information, and the output is the past usage data sent to the server. The device collects this data and uses it to create an optimal relaxation environment.

[0573] Step 2:

[0574] The device collects the user's biometric information and transmits it to the emotion engine. The input here is physiological data such as heart rate and body temperature obtained from sensors, while the output is analysis data passed to the emotion engine. The device acquires this data in real time and prepares to evaluate the user's state.

[0575] Step 3:

[0576] The emotion engine analyzes the user's biometric information, voice, and facial expressions to recognize their emotional state in real time. Input is biometric information transmitted from the device and the user's real-time voice and facial expression data; output is the analyzed emotional state. The emotion engine uses an emotion recognition algorithm to analyze the data and evaluate the type and intensity of the emotion.

[0577] Step 4:

[0578] The server uses emotional states from the emotion engine and past usage data to generate an appropriate virtual environment using a generative AI model. The input is the user's emotional state and usage history data, and the output is the virtual environment provided to the user. The server runs the generative AI model and constructs a dynamic virtual environment based on this input data.

[0579] Step 5:

[0580] The generated virtual environment is provided to the user through the terminal. The input here is the virtual environment data sent from the server, and the output is the virtual environment experienced by the user. The terminal sends this data to a display device, showing the user a relaxing environment in real time.

[0581] Step 6:

[0582] The user experiences a virtual environment and provides feedback to the terminal. The input is the user's feedback, and the output is data for optimizing the next session. The terminal records the user's feedback and sends it to the server for use in generating the next environment.

[0583] Step 7:

[0584] The server generates prompts to improve the next relaxation environment based on user feedback data, and uses them to train the generation AI model. At this point, the input is user-provided feedback, and the output is prompts that contribute to improving the generation AI model. The server analyzes the feedback and creates specific and effective prompts.

[0585] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0586] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0587] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0588] [Fourth Embodiment]

[0589] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0590] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0591] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0592] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0593] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0594] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0595] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0596] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0597] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0598] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0599] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0600] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0601] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0602] The present invention provides a means for users to enjoy a relaxation experience in a virtual reality environment. This system mainly consists of three elements: a server, a terminal, and a user.

[0603] First, when a user logs into the system, the device retrieves past usage data and feedback from the server. This collects data about the user's past experiences and preferences.

[0604] Subsequently, the terminal selects the optimal relaxation scenario based on this data and presents it to the user. Once the user selects their desired scenario, the server utilizes generative AI to optimize the selected scenario and automatically generates a virtual environment tailored to the individual user.

[0605] The generated virtual environment is provided to the user through the device. The user uses a VR device to immerse themselves in this environment and obtain a visually and aurally relaxing experience.

[0606] Simultaneously, the device monitors the user's biometric data in real time. Specifically, data such as heart rate and brain waves are acquired by sensors and transmitted to a server. The server aggregates this data, analyzes stress levels, and evaluates the effectiveness of the experience.

[0607] For example, if a user selects "Healing Forest," the server automatically generates a forest landscape with soothing sounds of wind and birdsong, taking into account sound frequencies and volumes that stabilize the heart rate. This allows the user to fully relax in that environment.

[0608] Once a session ends, the device provides the user with feedback based on their biometric data from that session. This includes fluctuations in stress levels and the degree of relaxation during the session, which can be used to improve future experiences.

[0609] Thus, the system of the present invention makes it possible to efficiently provide a virtual reality relaxation experience tailored to the user's characteristics and state.

[0610] The following describes the processing flow.

[0611] Step 1:

[0612] The user logs into the VR device. The device sends the user's authentication information to the server for authentication. If authentication is successful, the server sends the user's past usage history and feedback data to the device.

[0613] Step 2:

[0614] The device presents the user with potential relaxation scenarios based on data received from the server. These scenarios include a variety of natural environments and relaxing situations.

[0615] Step 3:

[0616] The user selects their preferred scenario from the presented options. The device then sends the selected scenario information to the server.

[0617] Step 4:

[0618] The server retrieves detailed data for the selected scenario and uses generative AI to automatically generate a customized virtual environment for the user. This includes optimizations based on the user's past usage data and feedback.

[0619] Step 5:

[0620] The generated virtual environment data is sent to the terminal. The terminal uses this data to provide the virtual environment to the user through a VR device.

[0621] Step 6:

[0622] While the user experiences relaxation in the VR environment, the device monitors biometric data such as heart rate and brainwaves in real time. The monitored data is transmitted from the device to the server.

[0623] Step 7:

[0624] The server analyzes the acquired biometric data and evaluates changes in stress levels. This evaluation result is used as feedback for future optimization.

[0625] Step 8:

[0626] After the session ends, the device displays feedback to the user based on their biometric data from the session. This allows the user to confirm the stress-reducing effect and use it to help them choose their next session.

[0627] (Example 1)

[0628] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0629] Conventional relaxation systems often lack the precision to assess stress levels using individual user biometric data, and fail to provide personalized support based on users' past usage patterns. This makes it difficult to offer users the optimal relaxation environment.

[0630] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0631] In this invention, the server includes means for collecting the user's biometric data, means for evaluating the stress level based on the acquired biometric data, and means for acquiring and analyzing the user's past usage data. This makes it possible to provide the user with an optimized relaxation experience.

[0632] "User" refers to an individual user who accesses the virtual environment and enjoys a relaxation experience.

[0633] "Biometric data" refers to data that indicates the user's physical condition, including measurements such as heart rate and brain waves.

[0634] "Stress level" is an indicator that shows the degree of mental and physical burden on a user, calculated based on biometric data.

[0635] "Usage data" refers to information about how users have used the system in the past, including specific usage history and feedback.

[0636] A "relaxation scenario" refers to a virtual environment experience plan built based on user data to maximize relaxation effects.

[0637] A "generative AI model" refers to an artificial intelligence program or algorithm used to automatically generate a virtual environment based on a user and their data.

[0638] A "virtual environment" refers to a computer-generated environment or space that a user experiences visually and aurally through a VR device.

[0639] "Feedback" refers to the evaluations and impressions that users provide after using a system, and includes information that is used to optimize the system.

[0640] The present invention automatically generates a virtual reality environment in which users can enjoy a relaxation experience optimized for their individual needs. This system operates based on three elements: a server, a terminal, and a user.

[0641] The server manages users' past usage data and feedback stored in a database and uses data analysis software to analyze it. Specifically, it utilizes the Python library Pandas. When a user accesses the system through a terminal and logs in, the server provides this data.

[0642] The terminal uses biosensors to transmit biometric data acquired from the user in real time to the server. These include devices such as heart rate sensors and electroencephalographs (EEGs). The server then uses this biometric data to assess the user's stress level and provides a customized virtual environment tailored to the user's condition.

[0643] Based on the relaxation scenario selected by the user, the server constructs a virtual environment using a generative AI model. This AI model is executed using machine learning platforms such as TensorFlow and PyTorch. The final generated virtual environment is provided to the user via a terminal, and the user puts on a VR device (e.g., Oculus Quest 2) and immerses themselves in this virtual space.

[0644] For example, if a user requests to relax in a "healing forest," the server generates a forest acoustic environment that considers frequencies that help stabilize the heart rate. This environment is presented through the device, allowing the user to relax comfortably.

[0645] Examples of prompt messages include the following:

[0646] "Create a relaxing virtual forest environment based on the user's heart rate data."

[0647] Thus, the present invention realizes a detailed relaxation experience tailored to the user's characteristics and condition.

[0648] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0649] Step 1:

[0650] A user logs into the system using their terminal. The user enters their login information, which is then sent to the server via the terminal. The input is the user's login information, and the output is an authentication request. The server performs authentication based on this information. If authentication is successful, it retrieves the user's past usage data from the database and sends it to the terminal. The data analysis software used here is Pandas.

[0651] Step 2:

[0652] The terminal selects the optimal relaxation scenario using past usage data received from the server. The input is past usage data, and the output is the proposed scenario. The terminal performs data analysis calculations and analyzes the user's past preferences to present a individually customized relaxation scenario.

[0653] Step 3:

[0654] The user selects their desired relaxation scenario. Based on this selection, the terminal sends a prompt to the server. The input is the scenario selected by the user, and the output is a prompt to run the generative AI model. The server uses this prompt to begin generating a virtual environment using the generative AI model. The model uses TensorFlow.

[0655] Step 4:

[0656] The server uses a generative AI model to generate a virtual environment based on the user's biometric data and selected scenario. Inputs are biometric data and prompt messages, while output is data from the virtual environment. The server creates a individually customized virtual space and sends that data to the terminal.

[0657] Step 5:

[0658] The terminal provides the user with received virtual environment data through a VR device. The input is the virtual environment data, and the output is the visual and auditory information experienced by the user. The user puts on the device and begins a relaxation experience in the virtual environment.

[0659] Step 6:

[0660] The device monitors the user's biometric data in real time via biosensors and transmits the obtained data to a server. The input is biometric data, and the output is data transmission to the server. The server uses this data to analyze stress levels and evaluate the effectiveness of the experience.

[0661] Step 7:

[0662] Once the session ends, the terminal provides feedback to the user based on the analysis results from the server. The input is the analysis results from the server, and the output is feedback information for the user to refer to. This feedback will be used to optimize the experience for the next time.

[0663] (Application Example 1)

[0664] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0665] In modern society, providing effective relaxation to individual users amidst busy lifestyles and stressful environments is challenging. Furthermore, conventional relaxation methods lack sufficient optimization based on users' biometric information and individual preferences. Therefore, there is a need for systems that provide a more personalized relaxation experience.

[0666] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0667] In this invention, the server includes means for acquiring and analyzing the user's biometric information, means for generating a virtual environment for relaxation based on the acquired biometric information, and means for providing the generated virtual environment to the user. This makes it possible to provide a personalized relaxation experience tailored to the user's state and preferences.

[0668] "User biometric information" refers to biological data such as heart rate and brainwaves obtained from individual users.

[0669] "Means for generating a virtual environment" refers to a method for creating a digital environment for user relaxation based on the user's biometric information and past usage data.

[0670] "Methods for collecting and optimizing feedback" refers to the process of analyzing user feedback data and making improvements so that the next experience is more appropriate.

[0671] "Consumer-use machinery and devices" refer to devices such as robots that are used for personal purposes within the home and assist in daily life through various functions.

[0672] "A means of monitoring stress levels in real time" refers to technology that continuously monitors the user's stress level and adjusts the virtual environment as needed.

[0673] To implement this invention, a household robot as a consumer-grade mechanical device is used. This robot is equipped with a heart rate sensor and an electroencephalogram (EEG) sensor to acquire the user's biometric information. The biometric information obtained from the sensors is biological data such as the user's heart rate and brain waves, which is useful for personalizing relaxation.

[0674] The server generates a virtual environment for relaxation based on the user's biometric information and past usage data. Specifically, it utilizes a generative AI model to automatically generate scenarios optimized for the user's preferences using prompt messages. For example, a prompt message such as, "Based on the user's recent experience data and current heart rate, please suggest the optimal relaxation scenario and generate an effective combination of sound and visuals," might be used.

[0675] The generated virtual environment is delivered to the user via a robot. The robot is equipped with a display and speakers, enabling it to provide a visual and auditory relaxation experience. The robot also collects user feedback to optimize future experiences.

[0676] For example, after a user returns home, the robot might suggest a "calm seaside experience for relaxation," monitoring the user's heart rate while displaying the sounds of gentle waves and a beautiful sunset from a secluded spot. This system allows users to easily enjoy relaxing experiences in their daily lives.

[0677] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0678] Step 1:

[0679] The server receives the user's past usage data and biometric information. This includes real-time data such as heart rate and brainwaves, as well as past usage history. This information is stored in a database and prepared for the next processing step.

[0680] Step 2:

[0681] The server analyzes the acquired data. Specifically, it extracts elements that are presumed to have a high relaxation effect based on the user's current heart rate and past usage patterns. It uses a generative AI model to generate prompt messages. It creates a prompt message in the form of, "Please suggest the optimal relaxation scenario based on the user's recent experience data and current heart rate," and inputs it into the AI.

[0682] Step 3:

[0683] A generative AI model generates relaxation scenarios based on prompt text. This creates visual and auditory scenarios, and the data is returned to the server. The scenarios include elements such as scenery and music tailored to the user's preferences.

[0684] Step 4:

[0685] The device (a home robot) receives relaxation scenarios provided by the server. The device then uses its built-in display and speaker to deliver these scenarios to the user. Visual information is displayed on the screen, and auditory information is played through the speaker.

[0686] Step 5:

[0687] While the user is experiencing relaxation, the device continuously monitors their biometric information. Heart rate and brain waves are acquired in real time and transmitted to the server. The server receives this data and analyzes fluctuations in tension levels.

[0688] Step 6:

[0689] At the end of a relaxation session, the server provides feedback to the user based on the collected data. This feedback, displayed via the user's device, includes suggestions for improvement for the next session, such as changes in the user's tension level and which elements had the most relaxing effect.

[0690] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0691] This invention combines a system for users to enjoy a relaxation experience in a virtual reality environment with an emotion engine that recognizes emotions in real time. The system mainly consists of a server, a terminal, and a device including the emotion engine.

[0692] First, when a user logs into the VR terminal, the terminal collects past usage history and feedback data and sends it to the server. This data is used to generate relaxation scenarios. Furthermore, the emotion engine recognizes the user's emotions in real time from their facial expressions and speech. This emotion data is integrated with biometric data and sent to the server.

[0693] The server analyzes biometric and emotional data to assess the user's current psychological state. Based on this analysis, it uses generative AI to automatically generate an optimal virtual environment for the user. The generated virtual environment is then provided to the user via their terminal.

[0694] For example, if a user indicates an intention to "relax," the emotion engine might detect the user's tension. Based on this information, the server generates an environment that includes calming natural scenery and soft music, and provides it to the user. Through such dynamic environmental adjustments, the user can experience deeper relaxation.

[0695] Furthermore, all data during the virtual environment is monitored by the terminal, and the emotion engine makes additional adjustments in real time as needed. Once the session ends, the user receives feedback via the terminal, evaluating the experience. This feedback is used to optimize future experiences.

[0696] This system enables real-time environmental adjustment using an emotion engine, providing a high-quality relaxation experience that surpasses conventional relaxation methods.

[0697] The following describes the processing flow.

[0698] Step 1:

[0699] The user activates the VR device and logs in. The device sends the user's authentication information to the server, completing the authentication. After authentication, the server provides the device with the user's past usage history and feedback data.

[0700] Step 2:

[0701] The device analyzes past data received from the server and presents the user with suggested relaxation scenarios. The user then selects their preferred scenario from the presented options.

[0702] Step 3:

[0703] Scenario information selected by the user is sent to the server via the terminal. Simultaneously, the emotion engine recognizes the user's emotional state in real time from their facial expressions, voice, and gestures, and sends that data to the server.

[0704] Step 4:

[0705] The server aggregates all information, including biometric and emotional data, and begins processing to generate a virtual environment tailored to the user's psychological and physical state. The generation AI automatically creates the optimal environment.

[0706] Step 5:

[0707] The generated virtual environment data is sent to the terminal. The terminal provides this data to the user using a VR device, and the user begins the experience.

[0708] Step 6:

[0709] During the experience, the device works in conjunction with the emotion engine to continuously monitor the user's emotions and biometric data in real time. This allows the server to dynamically adjust the virtual environment as needed.

[0710] Step 7:

[0711] Once the session ends, the device displays detailed feedback to the user based on their emotions and biometric data from the session. The user can then see how their experience was optimized based on the displayed feedback.

[0712] Step 8:

[0713] The device sends feedback data to the server, which is used to optimize subsequent sessions. This is expected to further improve the user's relaxation experience.

[0714] (Example 2)

[0715] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0716] The relaxation experience needs to be optimized according to each user's instantaneous emotional and biological state, but conventional systems have not adequately performed this real-time adjustment. As a result, the relaxation effect was limited, and this did not lead to increased user satisfaction.

[0717] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0718] In this invention, the server includes means for collecting the user's biometric and emotional information in real time, means for generating an optimal virtual environment according to the user's state using a generative AI model, and means for receiving feedback from the user and optimizing the next relaxation scenario. This makes it possible to provide a relaxation experience that is immediately responsive to the user's emotional state, enabling more effective stress reduction and improved satisfaction.

[0719] "Biometric information" refers to data related to the user's physical condition, including physical data such as heart rate, skin temperature, and brain waves.

[0720] "Emotional information" refers to data that indicates the psychological state of a user, estimated from their facial expressions and voice analysis.

[0721] A "generative AI model" is an artificial intelligence program that processes a user's biometric and emotional information to automatically design the optimal virtual environment.

[0722] A "virtual environment" is a simulated space that combines digitized visual and auditory content experienced by the user.

[0723] "Feedback" refers to the evaluation and comments a user provides about a relaxation session after it has ended, and is used to improve future experiences.

[0724] A "user terminal" is a device that a user uses to access a virtual environment or relaxation experience and to send and receive data.

[0725] "Real-time" refers to a time frame in which data collection and processing are performed immediately, and the results are reflected quickly.

[0726] This system consists of a server, a terminal, and a device including an emotion engine. When a user logs into the VR terminal, the terminal collects the user's past usage history and feedback data and sends it to the server. This procedure allows the server to obtain the basic data needed to prepare a personalized relaxation scenario for the user. The emotion engine analyzes the user's emotions in real time from their facial expressions and voice, and sends this emotional information along with biometric data to the server.

[0727] The server utilizes a generative AI model implemented in Python or similar languages ​​to analyze biometric and emotional information. Based on the analysis results, it generates a virtual environment optimized for the user's psychological state. This virtual environment appeals to the user's visual and auditory senses, promoting relaxation. For example, if the user is feeling anxious, the server generates a calming environment including natural sounds and scenery, and provides it to the user through the terminal. The generative AI model is given a prompt such as, "Generate a relaxing environment to alleviate the user's anxiety."

[0728] Furthermore, the device continuously monitors the user in real time while they experience the virtual environment, and the emotion engine adjusts the environment as needed. If the user's state changes, the relaxation scenario can be dynamically modified accordingly. After the session ends, the user evaluates the experience, and this feedback is used to optimize the next relaxation scenario. This allows users to enjoy a more effective and personalized relaxation experience.

[0729] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0730] Step 1:

[0731] The user logs into the VR terminal. After login authentication, the terminal retrieves the user's past usage history and feedback data from its internal database. This data is then formatted and sent to the server. The input is the user's identification information, and the output is a set of usage history and feedback data.

[0732] Step 2:

[0733] The server analyzes usage history and feedback data received from the terminal. Using a data analysis algorithm, it extracts patterns of relaxation environments that users have previously preferred. The output is a standard for relaxation scenarios based on these patterns. This standard serves as a reference for generating the next environment.

[0734] Step 3:

[0735] An emotion engine runs on the device, capturing the user's facial expressions and voice data in real time. This emotional information is collected via the device's built-in sensors and microphone. The input is the user's facial expressions and voice, and the output is emotional data generated based on them. This data is sent to a server.

[0736] Step 4:

[0737] The server uses a generative AI model to comprehensively analyze biometric and emotional information. The AI ​​model receives this data along with the prompt "Generate a healing environment to alleviate the user's tension" and generates an optimal virtual environment tailored to the user's current psychological state. The output consists of virtual environment parameters, including visual and auditory information.

[0738] Step 5:

[0739] The server transmits the generated virtual environment to the terminal. The terminal renders that environment on the VR device and provides it to the user. This allows the user to experience a digitally displayed relaxation environment. The input is the virtual environment data from the server, and the output is the user's visual and auditory experience.

[0740] Step 6:

[0741] The terminal continuously monitors user responses in real time and analyzes newly collected data using an emotion engine. When a change in the user's state is detected, it sends that information to the server, which then dynamically adjusts the virtual environment. The output is the parameters of the adjusted virtual environment.

[0742] Step 7:

[0743] When a user ends their virtual environment session, the terminal displays a survey requesting feedback. The user's evaluation information is sent from the terminal to the server. This feedback is used as reference when generating future relaxation scenarios. The input is the user's evaluation information, and the output is an update to the feedback database.

[0744] (Application Example 2)

[0745] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0746] In modern society, stress and mental fatigue are significant problems faced by many people. Traditional relaxation methods lack the means to appropriately adjust the environment based on the user's real-time emotional state, and there is a need for more personalized relaxation experiences. Furthermore, support for relaxation in the home environment needs to be both convenient and effective. However, a systematic solution to make this possible has not existed.

[0747] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0748] In this invention, the server includes means for acquiring and analyzing the user's biometric information, means for generating a virtual environment for comfort based on the acquired biometric information, and means for recognizing the user's emotional state in real time and dynamically adjusting the virtual environment based on that information. This makes it possible to automatically generate an optimal relaxation environment according to the user's emotions and state, and to easily provide a high-quality relaxation experience in a home environment.

[0749] "Biometric information" refers to physiological data obtained from the user's body, such as heart rate, body temperature, and respiratory rate.

[0750] "Comfort optimization" is the process of adjusting the environment and services according to the user's psychological and physiological state.

[0751] A "virtual environment" is an artificial space created by a computer that a user can experience through sight and other senses.

[0752] "Real-time" refers to the process of information being processed instantly and without delay in response to actual ongoing events.

[0753] "Emotional state" refers to the psychological situation or mood a user is experiencing at a particular point in time.

[0754] The system for implementing this invention acquires the user's biometric information and emotional state, and generates an optimized virtual environment to provide the user with a real-time, personalized relaxation experience.

[0755] The system's main components are a server, a terminal, an emotion engine, and a display device. The terminal has the function of transmitting the user's biometric information to the emotion engine. This biometric information consists of physical data such as heart rate and body temperature. The emotion engine also analyzes the user's voice and facial expressions to recognize their emotional state in real time.

[0756] The server receives this data and uses a generative AI model to generate a virtual environment optimized for the user. This generative AI model dynamically adjusts the environment according to the user's current emotional state, while also considering the user's past usage history and feedback data.

[0757] For example, if a user tells their device via voice, "I want to relax today," the server generates a quiet forest scene based on data received from the emotion engine. This virtual environment is then presented to the user through the display device.

[0758] An example of a prompt would be, "If the user says 'I'm tired today,' what kind of virtual environment should be generated?" This question is used by the generative AI model to select an appropriate virtual environment.

[0759] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0760] Step 1:

[0761] The user logs into the device. In this step, the device receives the user's login information and sends past usage history and feedback data to the server. The input is the user's login information, and the output is the past usage data sent to the server. The device collects this data and uses it to create an optimal relaxation environment.

[0762] Step 2:

[0763] The device collects the user's biometric information and transmits it to the emotion engine. The input here is physiological data such as heart rate and body temperature obtained from sensors, while the output is analysis data passed to the emotion engine. The device acquires this data in real time and prepares to evaluate the user's state.

[0764] Step 3:

[0765] The emotion engine analyzes the user's biometric information, voice, and facial expressions to recognize their emotional state in real time. Input is biometric information transmitted from the device and the user's real-time voice and facial expression data; output is the analyzed emotional state. The emotion engine uses an emotion recognition algorithm to analyze the data and evaluate the type and intensity of the emotion.

[0766] Step 4:

[0767] The server uses emotional states from the emotion engine and past usage data to generate an appropriate virtual environment using a generative AI model. The input is the user's emotional state and usage history data, and the output is the virtual environment provided to the user. The server runs the generative AI model and constructs a dynamic virtual environment based on this input data.

[0768] Step 5:

[0769] The generated virtual environment is provided to the user through the terminal. The input here is the virtual environment data sent from the server, and the output is the virtual environment experienced by the user. The terminal sends this data to a display device, showing the user a relaxing environment in real time.

[0770] Step 6:

[0771] The user experiences a virtual environment and provides feedback to the terminal. The input is the user's feedback, and the output is data for optimizing the next session. The terminal records the user's feedback and sends it to the server for use in generating the next environment.

[0772] Step 7:

[0773] The server generates prompts to improve the next relaxation environment based on user feedback data, and uses them to train the generation AI model. At this point, the input is user-provided feedback, and the output is prompts that contribute to improving the generation AI model. The server analyzes the feedback and creates specific and effective prompts.

[0774] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0775] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0776] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0777] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0778] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0779] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0780] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0781] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0782] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0783] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0784] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0785] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0786] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0787] 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.

[0788] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0789] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0790] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0791] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0792] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0793] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0794] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0795] The following is further disclosed regarding the embodiments described above.

[0796] (Claim 1)

[0797] A means of acquiring and analyzing users' biometric data,

[0798] A means for generating a virtual environment for relaxation based on acquired biometric data,

[0799] A means of providing the generated virtual environment to the user,

[0800] A means of collecting user feedback and optimizing the next experience,

[0801] A system that includes this.

[0802] (Claim 2)

[0803] The system according to claim 1, comprising means for generating a relaxation scenario optimized for the user by acquiring and analyzing the user's past usage data.

[0804] (Claim 3)

[0805] The system according to claim 1, comprising means for monitoring the user's stress level in real time and accumulating the data while providing a virtual environment.

[0806] "Example 1"

[0807] (Claim 1)

[0808] Means for collecting users' biometric data,

[0809] A means of evaluating stress levels based on acquired biometric data,

[0810] A means of acquiring and analyzing users' past usage data,

[0811] A means for generating relaxation scenarios optimized for the user,

[0812] A means of generating a virtual environment using a generative AI model based on the generated scenario,

[0813] A means of presenting the generated virtual environment to the user,

[0814] Gathering user feedback and optimizing the next virtual environment experience,

[0815] A system that includes this.

[0816] (Claim 2)

[0817] The system according to claim 1, comprising means for generating a relaxation scenario optimized for the user by analyzing the user's past usage data and biometric data, and providing a virtual environment generated based on thereon.

[0818] (Claim 3)

[0819] The system according to claim 1, comprising means for monitoring a user's biometric data in real time while providing a virtual environment and treating the analysis results as feedback.

[0820] "Application Example 1"

[0821] (Claim 1)

[0822] A means of acquiring and analyzing a user's biometric information,

[0823] A means for generating a virtual environment for relaxation based on acquired biometric information,

[0824] A means of providing the generated virtual environment to the user,

[0825] A means of collecting user feedback and optimizing the next experience,

[0826] In consumer electronics, means of providing a virtual experience,

[0827] A system that includes this.

[0828] (Claim 2)

[0829] The system according to claim 1, comprising means for generating a relaxation scenario optimized for the user by acquiring and analyzing the user's past usage data.

[0830] (Claim 3)

[0831] The system according to claim 1, comprising means for monitoring the user's stress level in real time and accumulating that information while providing a virtual environment.

[0832] "Example 2 of combining an emotion engine"

[0833] (Claim 1)

[0834] A means of acquiring and analyzing a user's biometric information,

[0835] A means of generating a virtual environment for relaxation using a generative AI model based on acquired biometric information and user emotional information,

[0836] A means of providing the generated virtual environment to the user through the user terminal,

[0837] A means of monitoring user emotion data in real time and dynamically adjusting the virtual environment,

[0838] A means of collecting user feedback on their experience and optimizing the next experience,

[0839] A system that includes this.

[0840] (Claim 2)

[0841] The system according to claim 1, comprising means for dynamically generating relaxation scenarios tailored to the user's preferences by acquiring and analyzing the user's past usage history and feedback data.

[0842] (Claim 3)

[0843] The system according to claim 1, comprising means for monitoring the user's emotional state in real time via a user terminal and accumulating the data while providing a virtual environment.

[0844] "Application example 2 when combining with an emotional engine"

[0845] (Claim 1)

[0846] A means of acquiring and analyzing a user's biometric information,

[0847] A means for generating a virtual environment for comfort based on acquired biometric information,

[0848] A means of presenting the generated virtual environment to the user,

[0849] A means of collecting user evaluation data to optimize the next experience,

[0850] A means of recognizing the user's emotional state in real time and dynamically adjusting the virtual environment based on that information,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, comprising means for generating a relaxation process optimized for the user by obtaining and analyzing the user's past usage history.

[0854] (Claim 3)

[0855] The system according to claim 1, comprising means for monitoring the user's psychological state in real time and accumulating that information while providing a virtual environment. [Explanation of Symbols]

[0856] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of acquiring and analyzing users' biometric data, A means for generating a virtual environment for relaxation based on acquired biometric data, A means of providing the generated virtual environment to the user, A means of collecting user feedback and optimizing the next experience, A system that includes this.

2. The system according to claim 1, comprising means for generating a relaxation scenario optimized for the user by acquiring and analyzing the user's past usage data.

3. The system according to claim 1, comprising means for monitoring the user's stress level in real time and accumulating the data while providing a virtual environment.

Images