system

Abstract

We provide the system. [Solution] A device for collecting individual biological information, A processing device that analyzes collected biological information and generates an exercise plan and a meal plan, An output device that provides real-time feedback in a virtual space based on the generated plan, Software that provides customized instruction to users using interactive dialogue functions, 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 persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, the importance of health management is increasing, but systems that can provide individually customized exercise and diet plans based on an individual's health status are limited. In addition, current fitness support does not have a sufficient mechanism for maintaining motivation and has the problem that it is difficult to form long-term healthy habits.

Means for Solving the Problems

[0005] This invention provides a processing device that collects an individual's biological information and uses that data to generate an optimal exercise and diet plan. This processing device provides real-time feedback in a virtual space and further provides customized guidance to the user using interactive dialogue functions, thereby constituting a system that enables appropriate health management tailored to individual needs.

[0006] "Individual biometric information" refers to data including motion data and physiological indicators that show an individual's physical activity and health status.

[0007] A "device" is a hardware device used to collect biometric information from a user's body.

[0008] A "processing device" is a computing unit that analyzes collected biological information and generates optimal exercise and diet plans.

[0009] A "plan" is a set of exercise and dietary guidelines designed to improve and maintain the user's health.

[0010] An "output device" is a device that provides users with visual and audio feedback in a virtual space.

[0011] An "interactive dialogue function" is a feature that responds in real time to user input and provides customized feedback and guidance.

[0012] "Software" refers to programs that run on hardware, controlling the entire system and managing its interaction with the user. [Brief explanation of the drawing]

[0013] [Figure 1] This 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.

MODE FOR CARRYING OUT THE INVENTION

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the 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.

[0019] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention is used to realize a system that comprehensively manages an individual's health status and provides a customized health plan to the user. Specific embodiments are described below.

[0035] First, the device collects biometric information in real time from the VR device and wearable sensors worn by the user. This includes the user's motion data, heart rate, respiratory rate, and body temperature. The device is equipped with communication capabilities to periodically send this data to a server.

[0036] Next, the server analyzes the received biometric information. This process uses AI algorithms to assess the user's health status. For example, it can determine the day's activity level from heart rate and movement patterns, and issue warnings about excessive or insufficient activity.

[0037] Based on the generated information, the server creates an optimal exercise and meal plan for the user. This planning function allows for flexible modification of the plan according to the user's goals and daily performance. For example, if fatigue is detected, the plan for the next day can be adjusted to include lighter exercise.

[0038] The device then provides feedback to the user in virtual reality based on the generated plan. This feedback is displayed as voice instructions or visual guides using 3D avatars. For example, an animated guide might be presented to demonstrate the correct form for squats.

[0039] Finally, users can receive personalized training and advice through interactive dialogue with the system. For example, users can use voice commands to communicate requests to the system such as "I want to avoid strenuous exercise" or "I want to try a longer running course."

[0040] In this way, the present invention enables flexible and personalized health management tailored to the user's health condition, supporting the formation of effective healthy habits while maintaining the user's motivation.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The device works in conjunction with the VR device worn by the user, collecting biometric information in real time from motion sensors and heart rate monitors. This data includes the user's movement patterns, heart rate, and calories burned. The collected biometric information is transmitted to a server at regular intervals.

[0044] Step 2:

[0045] The server analyzes the received biometric information. Using AI algorithms, it analyzes the user's exercise patterns and current heart rate to assess their health status in real time. During this process, it checks whether the exercise load is excessive and whether there are any abnormalities in the heart rate.

[0046] Step 3:

[0047] Based on the analysis results, the server generates an optimal exercise and meal plan for the user. This plan is individually customized based on past data and the user's health goals. For example, if the user's heart rate was high, the next plan might recommend low-intensity exercise.

[0048] Step 4:

[0049] The device provides feedback to the user in a VR space based on the generated plan. Specifically, it uses voice instructions and 3D avatars to demonstrate effective exercise form and provides encouraging messages based on progress. This feedback is provided in real time to help the user exercise properly.

[0050] Step 5:

[0051] Users receive feedback and guidance through interactive dialogue features. During this time, they can communicate with the device using voice commands and gestures, and receive real-time advice from the system. For example, they can immediately communicate requests such as, "I want to do more intense exercise."

[0052] Step 6:

[0053] The server aggregates data after each session and evaluates the user's daily activity level. Based on this, it adjusts exercise and meal plans for the following days, continuously optimizing the entire system to optimize the user's health.

[0054] (Example 1)

[0055] 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."

[0056] In today's world, providing customized health management tailored to individual health conditions is challenging. In particular, there is a need to collect users' biometric information in real time and flexibly provide exercise and dietary guidelines based on that information. Furthermore, it is desirable for the system to have the ability for users to actively interact with it and instantly adjust their plans. Such a system is crucial for providing more effective and personalized health management for users.

[0057] 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.

[0058] In this invention, the server includes a device for acquiring biometric information, processing means for analyzing the acquired biometric information and generating customized exercise and dietary guidelines, and output means for providing real-time feedback in a virtual space based on the generated guidelines. This allows users to receive personalized exercise and dietary guidance tailored to their health condition. Furthermore, by including a function to dynamically adjust the plan based on the user's voice instructions, flexible management in response to daily changes in condition becomes possible.

[0059] "Biometric information" refers to data that indicates an individual's health status, and includes physiological and physical indicators such as heart rate, body temperature, and motion data.

[0060] "Device" refers to hardware components used to acquire biometric information, such as wearable sensors and VR devices.

[0061] "Analysis" is the process of processing acquired biometric information to evaluate the user's health status and activity level.

[0062] "Guidelines" refer to specific suggestions regarding exercise and diet that are generated with the aim of improving the user's health.

[0063] "Processing means" refers to a set of software and hardware functions for analyzing digital data and generating guidelines.

[0064] "Output means" refers to devices or interfaces used to provide the generated guidelines to the user visually or audibly.

[0065] "Feedback" refers to information and instructions given to users in real time based on generated guidelines.

[0066] "Interactive conversation features" are functions that allow users to communicate with the system via voice or text and receive personalized guidance.

[0067] The "dynamic plan adjustment function" refers to the ability to change exercise and dietary guidelines in response to user input and changes in biometric information.

[0068] In order to implement this invention, the system functions through the cooperation of a server, a terminal, and a user.

[0069] The terminal first collects biometric information via wearable or VR devices worn by the user. These devices include heart rate sensors, accelerometers, and body temperature sensors. The various data acquired by these sensors are transmitted to a server as physiological and physical indicators. This data is transmitted in real time or periodically, allowing for continuous monitoring of the user's condition.

[0070] The server uses AI-based analysis software to analyze biometric information transmitted from the terminal. This software evaluates the user's activity level and health status based on the biometric information. Specifically, the AI ​​analyzes heart rate and motion patterns to assess the day's activity level and detect anomalies. For example, a higher-than-normal heart rate may indicate that the user is experiencing excessive stress.

[0071] Next, the server automatically generates exercise and dietary guidelines tailored to the user's health condition based on the analysis results. These guidelines are adjusted to the user's individual goals and past data. For example, if the user's activity level was low the previous day, it might recommend light exercise or suggest a meal plan to ensure a balanced intake of necessary nutrients.

[0072] The system provides real-time feedback to the user in a virtual space based on the generated guidelines. This feedback includes visual guidance and voice instructions via the device. For example, a 3D avatar can demonstrate the correct squat form to help the user perform the exercise correctly.

[0073] Users interact with the system through voice commands and an interface to receive personalized guidance. For example, they can make specific requests such as "increase the intensity in the next training session" or "avoid certain foods." This interactive functionality provides the flexibility to dynamically adjust the plan based on the user's condition and requests on any given day.

[0074] An example of a prompt to the generating AI model is, "Based on the latest heart rate and activity data, please suggest the optimal exercise plan for the user." This advanced system enables users to develop effective healthy habits and manage their health comprehensively.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] The device collects biometric information in real time using wearable sensors and VR devices worn by the user. This input includes heart rate, body temperature, and motion data. This data is aggregated by the device at regular intervals. The device quickly reviews the data and performs an initial check for any abnormal values. The data is then transmitted to a server using wireless communication.

[0078] Step 2:

[0079] The server analyzes biometric information received from the terminal using an AI algorithm. The specific data processing performed at this stage involves cleaning and normalizing the collected biometric data. The analysis results in an evaluation of the user's health status, activity level, and the presence or absence of abnormalities. For example, if the heart rate changes rapidly, the AI ​​model will operate to determine whether it is due to stress or exercise. As output, exercise and dietary guidelines tailored to the user's condition are generated.

[0080] Step 3:

[0081] Exercise and dietary guidelines generated on the server are sent back to the device for feedback. The device then provides real-time feedback in a virtual space based on these guidelines. Specifically, a 3D avatar visually guides the user through appropriate exercises, and a voice assistant provides verbal advice regarding diet. Furthermore, the device can improve the accuracy of its feedback by monitoring the user's reactions.

[0082] Step 4:

[0083] Users interact with the system while taking actual exercise and dietary actions based on feedback. This process allows users to operate the interface using voice commands to modify and adjust their plans. For example, if a user requests to "take it easy today," the system dynamically adjusts the plan based on that input. This action helps maintain user motivation and supports effective health management.

[0084] (Application Example 1)

[0085] 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."

[0086] In conventional health management systems, devices that collect personal biometric information and the suggested exercise and diet plans often failed to adequately integrate with each user's living environment and real-time health status. This resulted in challenges such as insufficient user convenience and inadequate health management. In particular, there was a lack of means to sustainably support users' health and safety within their daily lives.

[0087] 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.

[0088] In this invention, the server includes a measuring device for acquiring an individual's biological information, a computing device for analyzing the acquired biological information and generating an exercise plan and a nutrition plan, and a control program that provides personalized guidance to the user through interactive dialogue. This makes it possible to flexibly and effectively manage health using consumer robots in a way that is closely integrated into the user's daily life.

[0089] "Individual biometric information" refers to physiological and behavioral data, including the user's heart rate, body temperature, and movements.

[0090] A "measuring device" is a device used to acquire an individual's biological information in real time, and includes wearable sensors and VR devices.

[0091] A "computational device" is a computer system that analyzes collected biological information and generates an optimal exercise and nutrition plan for the user.

[0092] A "display device" is a device that provides feedback to the user based on a calculated plan, presenting information through sound and video.

[0093] A "control program" is software that provides interactive guidance and individualized advice tailored to the user.

[0094] "Support measures" refer to methods that utilize consumer robots used to support health management in a home environment.

[0095] This invention is based on a system that integrates a measuring device, a computing device, a display device, a control program, and support means in order to realize health management closely related to the user's daily life.

[0096] The server first acquires the user's biometric information through a measurement device. This device includes wearable sensors and VR devices to monitor heart rate, body temperature, and movement, enabling real-time data collection.

[0097] Next, the server analyzes the collected biometric information via a computing device. This analysis uses data processing algorithms with programming languages ​​such as Python, and AI models utilizing TENSORFLOW® and PyTorch. The analysis generates an optimal exercise and nutrition plan for the user.

[0098] The generated plan is fed back to the user via a display device. The feedback is provided to the user visually and audibly as audio and video. Specifically, this is achieved through speech recognition using Google® Cloud Speech-to-Text API and 3D animation using Unity.

[0099] The control program provides personalized advice through interactive dialogue with the user. It responds to the user's voice commands and flexibly adjusts the plan according to their health goals.

[0100] For example, when a user goes for a run in the morning, the system suggests an appropriate exercise intensity based on their measured heart rate and body temperature. If the user says, "I want to slow down a bit today," the exercise plan displayed on the screen is automatically adjusted.

[0101] An example of a prompt message is, "How can we create an exercise and meal plan for tomorrow based on the user's biometric information?"

[0102] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0103] Step 1:

[0104] The device collects biometric information from the user. It uses heart rate, body temperature, and motion data obtained from wearable sensors and VR devices as input. This data is temporarily stored within the device and transmitted to a server via its communication function.

[0105] Step 2:

[0106] The server analyzes the received biometric data. Based on this input data, an AI algorithm (using TensorFlow or PyTorch) evaluates the user's health status. The data calculations performed here include time-series data analysis and anomaly detection algorithms, evaluating the user's heart rate patterns and activity levels, and generating warnings as needed.

[0107] Step 3:

[0108] The server generates an optimal exercise and nutrition plan for the user based on the analyzed health data. It uses the user's health goals and up-to-date biometric data as input, and provides a plan that includes specific exercise types, frequency, and recommended dietary content as output. In this process, a generation AI model is utilized to create a personalized plan based on the user's past data and current condition.

[0109] Step 4:

[0110] The terminal provides feedback to communicate the generated plan to the user. Using a display device, information is presented to the user through voice instructions and visual guidance via a 3D avatar. The output information is designed to aid user understanding and encourage implementation, and is implemented using Google Cloud Speech-to-Text API and Unity.

[0111] Step 5:

[0112] Users provide feedback and requests to the system via voice commands. The control program adjusts the plan in real time based on this input and engages in interactive dialogue tailored to the user. The output includes an adjusted plan and additional advice, making user health management more flexible and personalized. As a result, the system can receive and respond to requests such as, for example, "I'd like to do a lighter workout tomorrow."

[0113] 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.

[0114] This invention provides a health management system that incorporates an emotion engine that recognizes user emotions. This enables more personalized feedback and guidance, helping users maintain effective health habits. Specific embodiments are described below.

[0115] First, the device collects the user's biometric information along with the VR device and wearable sensors. This information includes motion data and physiological indicators (heart rate, body temperature, etc.), and also acquires data on the user's voice and facial expressions through the microphone and camera.

[0116] Next, the server analyzes the received biometric information and voice / facial expression data. In particular, the emotion engine analyzes voice and facial expressions to detect the user's emotional state (e.g., stress, happiness, fatigue). The detected emotions are considered as important factors when adjusting exercise and meal plans.

[0117] Based on the generated exercise and meal plan, the server generates personalized feedback. This feedback includes motivational and comforting messages tailored to the perceived emotional state.

[0118] The device provides the generated feedback to the user in the VR space. Specifically, it is used as voice instructions or as actions of a 3D avatar that respond to emotions. For example, if the user is feeling stressed, feedback such as relaxing voice guidance or calming images will be presented.

[0119] Finally, users engage in two-way communication with the system using interactive dialogue features. In this process, users can communicate their emotional state and goals to the system, and advice and plans are generated accordingly.

[0120] As described above, the present invention effectively utilizes an emotion engine to realize flexible and personalized health management tailored to each user's individual condition, thereby supporting a sustainable healthy lifestyle.

[0121] The following describes the processing flow.

[0122] Step 1:

[0123] The device collects biometric information in real time from the VR device and wearable sensors worn by the user. This information includes the user's motion data, heart rate, body temperature, voice, and facial expressions. The collected data is sent to a server for processing.

[0124] Step 2:

[0125] The server analyzes the received data. First, it uses an AI algorithm to evaluate the user's physiological state, and then uses an emotion engine to recognize the user's emotions from their voice and facial expressions. The recognized emotions are classified as feelings of stress, happiness, fatigue, etc.

[0126] Step 3:

[0127] The server generates an optimal exercise and meal plan for the user based on the analysis results. These plans are customized according to the user's fitness goals, current health status, and perceived emotional state. For example, if the user is tired, the server will suggest light exercise for relaxation.

[0128] Step 4:

[0129] The device provides the user with generated feedback in the VR space. This feedback includes instructions on exercise form, emotionally-responsive voice messages, and movements from a 3D avatar. For example, if the emotion engine detects the user's stress, the screen will display a relaxing scene.

[0130] Step 5:

[0131] Users perform exercises based on feedback provided in the VR space. They can respond with voice commands and gestures using interactive dialogue features. Users can also receive more personalized instruction by communicating their emotions and requests.

[0132] Step 6:

[0133] After a session ends, the server aggregates and evaluates the data obtained. Based on this, it adjusts the planning for the following days and provides information to continuously improve the user's health.

[0134] (Example 2)

[0135] 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 will be referred to as the "terminal."

[0136] Traditional health management systems generally only record users' biometric information and fail to effectively utilize the collected data to provide feedback that reflects individual emotional states. Therefore, there is a need for more personalized health guidance that takes into account users' mental and emotional states.

[0137] 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.

[0138] In this invention, the server includes means for analyzing biometric information and voice / facial expression data to identify emotional states, means for generating exercise and meal plans based on emotional states and providing real-time feedback, and a program that provides individually customized guidance using an interactive dialogue function. This enables flexible and personalized health management that responds to the user's emotional state.

[0139] "Biometric information" refers to quantifiable data about an individual's body, including information such as heart rate, body temperature, and motion details.

[0140] "Voice and facial expression data" refers to digital data that records an individual's voice tone and facial features, and is used as information for analyzing their emotional state.

[0141] "Emotional state" refers to an individual's mental and emotional condition, including stress, happiness, fatigue, and so on.

[0142] An "algorithm" is a series of computational procedures used to analyze specific data and derive a desired result, and is incorporated into a processing unit.

[0143] A "virtual space" is a three-dimensional digital space created using a computer, an environment in which users can intuitively operate the interface.

[0144] "Feedback" refers to the information and advice provided to users, which is useful for adjusting their behavior and motivating them.

[0145] An "interactive dialogue function" is a feature that allows the system and the user to exchange information with each other and adjust the instruction content in real time based on that information.

[0146] A "program" is a set of instructions used to perform a specific task on a computer system or device.

[0147] This invention is a system that supports user health management and has a configuration centered on an emotion engine that recognizes emotional states. The following describes how this system is implemented.

[0148] The device, as a wearable device, collects biometric information such as heart rate and body temperature in real time. Furthermore, it acquires voice data and facial expression data using a microphone and camera. This device can be worn by the user daily and seamlessly integrated into their lifestyle.

[0149] The server stores biometric information and voice / facial expression data transmitted from the terminal in a cloud-based database and performs analysis. This analysis utilizes an emotion engine and machine learning algorithms. This allows the server to identify the user's emotional state and determine stress, happiness, fatigue, and other emotional states.

[0150] Based on the analysis results, the server generates exercise and meal plans. Using a generation AI model, it creates specific and personalized plans. These plans include motivational messages tailored to the user's emotional state, as well as relaxation advice.

[0151] The generated feedback is provided to the user in a virtual space via the device. Through the VR device, relaxing natural images and sounds are played around the user, and a 3D avatar guides the user with a gentle voice.

[0152] Furthermore, users can input their current emotional state and health goals into the system using interactive dialogue features. This allows the system to create new plans and advice based on the user's input.

[0153] An example of a prompt would be, "If the user's current emotional state is stress, what relaxation activities or messages would you suggest?"

[0154] Through this mechanism, the present invention functions as a tool that integrates into the user's daily life and supports sustainable health management.

[0155] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0156] Step 1:

[0157] The device collects the user's biometric information using wearable devices. Specifically, it measures heart rate and body temperature with sensors and records activity levels with motion sensors. Audio data is collected by a microphone built into the device, and facial expression data is captured by a camera. This data is collected in real time and transferred to a server for further analysis.

[0158] Step 2:

[0159] The server receives biometric information, voice data, and facial expression data transmitted from the terminal and stores them in a database. Using an emotion engine, it analyzes the voice and facial expression data to identify the user's emotional state. The input here is voice tone and facial expression patterns, and based on this, it outputs emotional states such as stress and happiness.

[0160] Step 3:

[0161] The server generates exercise and meal plans based on the analyzed emotional state. A generative AI model is used to provide personalized plans. In this process, the emotional state is utilized as a parameter in the plan. For example, if stress levels are high, a plan emphasizing relaxation will be generated.

[0162] Step 4:

[0163] The terminal receives feedback from the server and provides it to the user via the VR device. Specifically, when the user puts on the VR headset, a 3D environment tailored to their emotional state is displayed. For example, if the user is feeling tired, calming natural scenery or relaxation music will be played.

[0164] Step 5:

[0165] Users communicate with the system through interactive dialogue functions. By inputting their emotional state and health goals, this information is used for subsequent analyses. User feedback is incorporated into a database and reflected in future planning. For example, if a user inputs "I want to reduce stress," this request will be taken into consideration in the next feedback.

[0166] (Application Example 2)

[0167] 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 device 14 will be referred to as the "terminal."

[0168] In modern urban environments, there is a lack of means to individually manage the health and emotional well-being of residents and promote health throughout the community. To address this challenge, there is a need for a system that monitors the health status of groups in real time and efficiently provides appropriate health events and support based on emotions.

[0169] 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.

[0170] In this invention, the server includes an information acquisition device for monitoring the health status of a group, a processing device for analyzing the acquired biometric data and emotional state and formulating health events for the entire region, and an output device for providing rapid advice in the physical and virtual spaces based on the formulated plan. This makes it possible to improve the health status of residents and enhance the overall well-being of the region.

[0171] An "information acquisition device" is a device used to acquire data, including biometric information and emotional states, of a group of people.

[0172] A "processing device" is a device that analyzes acquired data and performs calculations and processing to formulate health events for the entire region.

[0173] An "output device" is a device that provides residents with formulated health events and advice in both physical and virtual spaces.

[0174] "Interactive communication functionality" refers to a feature that provides instructions applicable to the user and enables real-time, two-way communication.

[0175] A "community medical institution" is an organization or facility that operates within a community to provide health maintenance and medical support to residents.

[0176] The system for implementing this invention includes an information acquisition device, an information processing device, and an output device. The roles and processes of each are described below.

[0177] The information acquisition device uses wearable sensors and smartphones to collect biometric information from a group in real time. This includes physiological indicators such as motion data, heart rate, and body temperature. It also acquires voice and facial expression data to understand emotional states.

[0178] The processing unit runs on a server and uses software such as Python and TensorFlow to analyze the acquired data. Based on this data, the server classifies emotional states and develops health events appropriate for the entire community. For example, if many residents are experiencing stress, it will plan relaxation events.

[0179] The output device will quickly provide residents with formulated event information and advice through physical display devices and VR devices. Furthermore, it will be equipped with a program that enables interactive communication, allowing for real-time, two-way communication with users.

[0180] As a concrete example, if the system analyzes the emotional state of residents and detects that many residents are experiencing stress, it will send a message via a smartphone app such as, "Would you like to join a free yoga class at the park this weekend?"

[0181] An example of a prompt for the generative AI model is: "Create a message that recommends effective health events to local residents based on the user's health data and emotional state."

[0182] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0183] Step 1:

[0184] The device uses wearable sensors and smartphones to collect physiological indicator data (e.g., heart rate, body temperature) and emotional data (e.g., voice, facial expressions) from residents. This data is transmitted to a cloud server in real time. The input is biometric information and emotion-related data, and the output is this data stored in the cloud.

[0185] Step 2:

[0186] The server retrieves biometric and emotional data stored in the cloud and analyzes emotional states using Python and TensorFlow. Data processing includes tone analysis of speech and emotional classification through facial feature extraction. Input is biometric and emotional data retrieved from the cloud, and output is the analyzed emotional state information.

[0187] Step 3:

[0188] The server generates health events tailored to residents based on the analysis results. It utilizes a generation AI model to generate prompts suggesting appropriate events based on the residents' emotional states. The input is emotional state information, and the output is the content of the recommended health events.

[0189] Step 4:

[0190] The server sends information about generated health events to terminals and notifies residents via a smartphone app. It uses an interface to facilitate interactive communication and delivers messages encouraging participation. The input is event information, and the output is the notification sent to residents.

[0191] Step 5:

[0192] Based on the notification they receive, users review event details and decide whether to participate. The system receives feedback and updates participant data for further analysis. The input is the notification content, and the output is user feedback and participation status.

[0193] 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.

[0194] 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.

[0195] 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.

[0196] [Second Embodiment]

[0197] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0198] 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.

[0199] 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).

[0200] 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.

[0201] 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.

[0202] 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).

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] 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.

[0208] 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".

[0209] This invention is used to realize a system that comprehensively manages an individual's health status and provides a customized health plan to the user. Specific embodiments are described below.

[0210] First, the device collects biometric information in real time from the VR device and wearable sensors worn by the user. This includes the user's motion data, heart rate, respiratory rate, and body temperature. The device is equipped with communication capabilities to periodically send this data to a server.

[0211] Next, the server analyzes the received biometric information. This process uses AI algorithms to assess the user's health status. For example, it can determine the day's activity level from heart rate and movement patterns, and issue warnings about excessive or insufficient activity.

[0212] Based on the generated information, the server creates an optimal exercise and meal plan for the user. This planning function allows for flexible modification of the plan according to the user's goals and daily performance. For example, if fatigue is detected, the plan for the next day can be adjusted to include lighter exercise.

[0213] The device then provides feedback to the user in virtual reality based on the generated plan. This feedback is displayed as voice instructions or visual guides using 3D avatars. For example, an animated guide might be presented to demonstrate the correct form for squats.

[0214] Finally, users can receive personalized training and advice through interactive dialogue with the system. For example, users can use voice commands to communicate requests to the system such as "I want to avoid strenuous exercise" or "I want to try a longer running course."

[0215] In this way, the present invention enables flexible and personalized health management tailored to the user's health condition, supporting the formation of effective healthy habits while maintaining the user's motivation.

[0216] The following describes the processing flow.

[0217] Step 1:

[0218] The device works in conjunction with the VR device worn by the user, collecting biometric information in real time from motion sensors and heart rate monitors. This data includes the user's movement patterns, heart rate, and calories burned. The collected biometric information is transmitted to a server at regular intervals.

[0219] Step 2:

[0220] The server analyzes the received biometric information. Using AI algorithms, it analyzes the user's exercise patterns and current heart rate to assess their health status in real time. During this process, it checks whether the exercise load is excessive and whether there are any abnormalities in the heart rate.

[0221] Step 3:

[0222] Based on the analysis results, the server generates an optimal exercise and meal plan for the user. This plan is individually customized based on past data and the user's health goals. For example, if the user's heart rate was high, the next plan might recommend low-intensity exercise.

[0223] Step 4:

[0224] The device provides feedback to the user in a VR space based on the generated plan. Specifically, it uses voice instructions and 3D avatars to demonstrate effective exercise form and provides encouraging messages based on progress. This feedback is provided in real time to help the user exercise properly.

[0225] Step 5:

[0226] Users receive feedback and guidance through interactive dialogue features. During this time, they can communicate with the device using voice commands and gestures, and receive real-time advice from the system. For example, they can immediately communicate requests such as, "I want to do more intense exercise."

[0227] Step 6:

[0228] The server aggregates data after each session and evaluates the user's daily activity level. Based on this, it adjusts exercise and meal plans for the following days, continuously optimizing the entire system to optimize the user's health.

[0229] (Example 1)

[0230] 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."

[0231] In today's world, providing customized health management tailored to individual health conditions is challenging. In particular, there is a need to collect users' biometric information in real time and flexibly provide exercise and dietary guidelines based on that information. Furthermore, it is desirable for the system to have the ability for users to actively interact with it and instantly adjust their plans. Such a system is crucial for providing more effective and personalized health management for users.

[0232] 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.

[0233] In this invention, the server includes a device for acquiring biometric information, processing means for analyzing the acquired biometric information and generating customized exercise and dietary guidelines, and output means for providing real-time feedback in a virtual space based on the generated guidelines. This allows users to receive personalized exercise and dietary guidance tailored to their health condition. Furthermore, by including a function to dynamically adjust the plan based on the user's voice instructions, flexible management in response to daily changes in condition becomes possible.

[0234] "Biometric information" refers to data that indicates an individual's health status, and includes physiological and physical indicators such as heart rate, body temperature, and motion data.

[0235] "Device" refers to hardware components used to acquire biometric information, such as wearable sensors and VR devices.

[0236] "Analysis" is the process of processing acquired biometric information to evaluate the user's health status and activity level.

[0237] "Guidelines" refer to specific suggestions regarding exercise and diet that are generated with the aim of improving the user's health.

[0238] "Processing means" refers to a set of software and hardware functions for analyzing digital data and generating guidelines.

[0239] "Output means" refers to devices or interfaces used to provide the generated guidelines to the user visually or audibly.

[0240] "Feedback" refers to information and instructions given to users in real time based on generated guidelines.

[0241] "Interactive conversation features" are functions that allow users to communicate with the system via voice or text and receive personalized guidance.

[0242] The "dynamic plan adjustment function" refers to the ability to change exercise and dietary guidelines in response to user input and changes in biometric information.

[0243] In order to implement this invention, the system functions through the cooperation of a server, a terminal, and a user.

[0244] The terminal first collects biometric information via wearable or VR devices worn by the user. These devices include heart rate sensors, accelerometers, and body temperature sensors. The various data acquired by these sensors are transmitted to a server as physiological and physical indicators. This data is transmitted in real time or periodically, allowing for continuous monitoring of the user's condition.

[0245] The server uses AI-based analysis software to analyze biometric information transmitted from the terminal. This software evaluates the user's activity level and health status based on the biometric information. Specifically, the AI ​​analyzes heart rate and motion patterns to assess the day's activity level and detect anomalies. For example, a higher-than-normal heart rate may indicate that the user is experiencing excessive stress.

[0246] Next, the server automatically generates exercise and dietary guidelines tailored to the user's health condition based on the analysis results. These guidelines are adjusted to the user's individual goals and past data. For example, if the user's activity level was low the previous day, it might recommend light exercise or suggest a meal plan to ensure a balanced intake of necessary nutrients.

[0247] The system provides real-time feedback to the user in a virtual space based on the generated guidelines. This feedback includes visual guidance and voice instructions via the device. For example, a 3D avatar can demonstrate the correct squat form to help the user perform the exercise correctly.

[0248] Users interact with the system through voice commands and an interface to receive personalized guidance. For example, they can make specific requests such as "increase the intensity in the next training session" or "avoid certain foods." This interactive functionality provides the flexibility to dynamically adjust the plan based on the user's condition and requests on any given day.

[0249] An example of a prompt to the generating AI model is, "Based on the latest heart rate and activity data, please suggest the optimal exercise plan for the user." This advanced system enables users to develop effective healthy habits and manage their health comprehensively.

[0250] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0251] Step 1:

[0252] The device collects biometric information in real time using wearable sensors and VR devices worn by the user. This input includes heart rate, body temperature, and motion data. This data is aggregated by the device at regular intervals. The device quickly reviews the data and performs an initial check for any abnormal values. The data is then transmitted to a server using wireless communication.

[0253] Step 2:

[0254] The server analyzes biometric information received from the terminal using an AI algorithm. The specific data processing performed at this stage involves cleaning and normalizing the collected biometric data. The analysis results in an evaluation of the user's health status, activity level, and the presence or absence of abnormalities. For example, if the heart rate changes rapidly, the AI ​​model will operate to determine whether it is due to stress or exercise. As output, exercise and dietary guidelines tailored to the user's condition are generated.

[0255] Step 3:

[0256] Exercise and dietary guidelines generated on the server are sent back to the device for feedback. The device then provides real-time feedback in a virtual space based on these guidelines. Specifically, a 3D avatar visually guides the user through appropriate exercises, and a voice assistant provides verbal advice regarding diet. Furthermore, the device can improve the accuracy of its feedback by monitoring the user's reactions.

[0257] Step 4:

[0258] Users interact with the system while taking actual exercise and dietary actions based on feedback. This process allows users to operate the interface using voice commands to modify and adjust their plans. For example, if a user requests to "take it easy today," the system dynamically adjusts the plan based on that input. This action helps maintain user motivation and supports effective health management.

[0259] (Application Example 1)

[0260] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0261] In conventional health management systems, devices that collect personal biometric information and the suggested exercise and diet plans often failed to adequately integrate with each user's living environment and real-time health status. This resulted in challenges such as insufficient user convenience and inadequate health management. In particular, there was a lack of means to sustainably support users' health and safety within their daily lives.

[0262] 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.

[0263] In this invention, the server includes a measuring device for acquiring an individual's biological information, a computing device for analyzing the acquired biological information and generating an exercise plan and a nutrition plan, and a control program that provides personalized guidance to the user through interactive dialogue. This makes it possible to flexibly and effectively manage health using consumer robots in a way that is closely integrated into the user's daily life.

[0264] "Individual biometric information" refers to physiological and behavioral data, including the user's heart rate, body temperature, and movements.

[0265] A "measuring device" is a device used to acquire an individual's biological information in real time, and includes wearable sensors and VR devices.

[0266] A "computational device" is a computer system that analyzes collected biological information and generates an optimal exercise and nutrition plan for the user.

[0267] A "display device" is a device that provides feedback to the user based on a calculated plan, presenting information through sound and video.

[0268] A "control program" is software that provides interactive guidance and individualized advice tailored to the user.

[0269] "Support measures" refer to methods that utilize consumer robots used to support health management in a home environment.

[0270] This invention is based on a system that integrates a measuring device, a computing device, a display device, a control program, and support means in order to realize health management closely related to the user's daily life.

[0271] The server first acquires the user's biometric information through a measurement device. This device includes wearable sensors and VR devices to monitor heart rate, body temperature, and movement, enabling real-time data collection.

[0272] Next, the server analyzes the collected biometric information via a computing device. This analysis uses data processing algorithms with programming languages ​​such as Python, and AI models utilizing TensorFlow and PyTorch. The analysis generates an optimal exercise and nutrition plan for the user.

[0273] The generated plan is fed back to the user via a display device. The feedback is provided to the user visually and aurally as audio and video. Specifically, this is achieved through speech recognition using the Google Cloud Speech-to-Text API and 3D animation using Unity.

[0274] The control program provides personalized advice through interactive dialogue with the user. It responds to the user's voice commands and flexibly adjusts the plan according to their health goals.

[0275] For example, when a user goes for a run in the morning, the system suggests an appropriate exercise intensity based on their measured heart rate and body temperature. If the user says, "I want to slow down a bit today," the exercise plan displayed on the screen is automatically adjusted.

[0276] An example of a prompt message is, "How can we create an exercise and meal plan for tomorrow based on the user's biometric information?"

[0277] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0278] Step 1:

[0279] The device collects biometric information from the user. It uses heart rate, body temperature, and motion data obtained from wearable sensors and VR devices as input. This data is temporarily stored within the device and transmitted to a server via its communication function.

[0280] Step 2:

[0281] The server analyzes the received biometric data. Based on this input data, the user's health status is evaluated by an AI algorithm (using TensorFlow or PyTorch). The data operations performed here include time-series data analysis and anomaly detection algorithms, which evaluate the user's heart rate pattern and activity level and generate warnings if necessary.

[0282] Step 3:

[0283] The server generates an optimal exercise plan and nutrition plan for the user based on the analyzed health data. Using the user's health goals and the latest biometric data as input, a plan including specific types of exercise, frequency, and recommended dietary content is provided as output. At this time, the generated AI model is utilized to formulate a personalized plan based on the user's past data and current state.

[0284] Step 4:

[0285] The terminal provides feedback for communicating the generated plan to the user. Using a display device, information is presented to the user through voice instructions or visual guides by 3D avatars. The output information helps the user understand and promotes implementation, and is realized using the Google Cloud Speech-to-Text API or Unity.

[0286] Step 5:

[0287] Users provide feedback and requests to the system via voice commands. The control program adjusts the plan in real time based on this input and engages in interactive dialogue tailored to the user. The output includes an adjusted plan and additional advice, making user health management more flexible and personalized. As a result, the system can receive and respond to requests such as, for example, "I'd like to do a lighter workout tomorrow."

[0288] 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.

[0289] This invention provides a health management system that incorporates an emotion engine that recognizes user emotions. This enables more personalized feedback and guidance, helping users maintain effective health habits. Specific embodiments are described below.

[0290] First, the device collects the user's biometric information along with the VR device and wearable sensors. This information includes motion data and physiological indicators (heart rate, body temperature, etc.), and also acquires data on the user's voice and facial expressions through the microphone and camera.

[0291] Next, the server analyzes the received biometric information and voice / facial expression data. In particular, the emotion engine analyzes voice and facial expressions to detect the user's emotional state (e.g., stress, happiness, fatigue). The detected emotions are considered as important factors when adjusting exercise and meal plans.

[0292] Based on the generated exercise and meal plan, the server generates personalized feedback. This feedback includes motivational and comforting messages tailored to the perceived emotional state.

[0293] The device provides the generated feedback to the user in the VR space. Specifically, it is used as voice instructions or as actions of a 3D avatar that respond to emotions. For example, if the user is feeling stressed, feedback such as relaxing voice guidance or calming images will be presented.

[0294] Finally, users engage in two-way communication with the system using interactive dialogue features. In this process, users can communicate their emotional state and goals to the system, and advice and plans are generated accordingly.

[0295] As described above, the present invention effectively utilizes an emotion engine to realize flexible and personalized health management tailored to each user's individual condition, thereby supporting a sustainable healthy lifestyle.

[0296] The following describes the processing flow.

[0297] Step 1:

[0298] The device collects biometric information in real time from the VR device and wearable sensors worn by the user. This information includes the user's motion data, heart rate, body temperature, voice, and facial expressions. The collected data is sent to a server for processing.

[0299] Step 2:

[0300] The server analyzes the received data. First, it uses an AI algorithm to evaluate the user's physiological state, and then uses an emotion engine to recognize the user's emotions from their voice and facial expressions. The recognized emotions are classified as feelings of stress, happiness, fatigue, etc.

[0301] Step 3:

[0302] The server generates an optimal exercise plan and diet plan for the user based on the analysis results. These plans are customized according to the user's fitness goals, current health status, and recognized emotional state. For example, if the user is tired, the server proposes light exercises for relaxation purposes.

[0303] Step 4:

[0304] The terminal provides the generated feedback to the user in the VR space. The feedback includes instructions on exercise forms, voice messages according to emotions, and movements by 3D avatars. For example, when the emotion engine recognizes the user's stress, a relaxing scenery is displayed on the screen.

[0305] Step 5:

[0306] The user performs exercises based on the feedback provided in the VR space. Using the interactive dialogue function, feedback can be returned via voice commands and gestures. The user can receive more personalized guidance by conveying their emotions and desires.

[0307] Step 6:

[0308] After the session ends, the server aggregates and evaluates the obtained data. Based on this, the planning for the days after the next day is adjusted, and information for continuously improving the user's health status is provided.

[0309] (Example 2)

[0310] Next, Example 2 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".

[0311] Traditional health management systems generally only record users' biometric information and fail to effectively utilize the collected data to provide feedback that reflects individual emotional states. Therefore, there is a need for more personalized health guidance that takes into account users' mental and emotional states.

[0312] 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.

[0313] In this invention, the server includes means for analyzing biometric information and voice / facial expression data to identify emotional states, means for generating exercise and meal plans based on emotional states and providing real-time feedback, and a program that provides individually customized guidance using an interactive dialogue function. This enables flexible and personalized health management that responds to the user's emotional state.

[0314] "Biometric information" refers to quantifiable data about an individual's body, including information such as heart rate, body temperature, and motion details.

[0315] "Voice and facial expression data" refers to digital data that records an individual's voice tone and facial features, and is used as information for analyzing their emotional state.

[0316] "Emotional state" refers to an individual's mental and emotional condition, including stress, happiness, fatigue, and so on.

[0317] An "algorithm" is a series of computational procedures used to analyze specific data and derive a desired result, and is incorporated into a processing unit.

[0318] A "virtual space" is a three-dimensional digital space created using a computer, an environment in which users can intuitively operate the interface.

[0319] "Feedback" refers to the information and advice provided to users, which is useful for adjusting their behavior and motivating them.

[0320] An "interactive dialogue function" is a feature that allows the system and the user to exchange information with each other and adjust the instruction content in real time based on that information.

[0321] A "program" is a set of instructions used to perform a specific task on a computer system or device.

[0322] This invention is a system that supports user health management and has a configuration centered on an emotion engine that recognizes emotional states. The following describes how this system is implemented.

[0323] The device, as a wearable device, collects biometric information such as heart rate and body temperature in real time. Furthermore, it acquires voice data and facial expression data using a microphone and camera. This device can be worn by the user daily and seamlessly integrated into their lifestyle.

[0324] The server stores biometric information and voice / facial expression data transmitted from the terminal in a cloud-based database and performs analysis. This analysis utilizes an emotion engine and machine learning algorithms. This allows the server to identify the user's emotional state and determine stress, happiness, fatigue, and other emotional states.

[0325] Based on the analysis results, the server generates exercise and meal plans. Using a generation AI model, it creates specific and personalized plans. These plans include motivational messages tailored to the user's emotional state, as well as relaxation advice.

[0326] The generated feedback is provided to the user in a virtual space via the device. Through the VR device, relaxing natural images and sounds are played around the user, and a 3D avatar guides the user with a gentle voice.

[0327] Furthermore, users can input their current emotional state and health goals into the system using interactive dialogue features. This allows the system to create new plans and advice based on the user's input.

[0328] An example of a prompt would be, "If the user's current emotional state is stress, what relaxation activities or messages would you suggest?"

[0329] Through this mechanism, the present invention functions as a tool that integrates into the user's daily life and supports sustainable health management.

[0330] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0331] Step 1:

[0332] The device collects the user's biometric information using wearable devices. Specifically, it measures heart rate and body temperature with sensors and records activity levels with motion sensors. Audio data is collected by a microphone built into the device, and facial expression data is captured by a camera. This data is collected in real time and transferred to a server for further analysis.

[0333] Step 2:

[0334] The server receives biometric information, voice data, and facial expression data transmitted from the terminal and stores them in a database. Using an emotion engine, it analyzes the voice and facial expression data to identify the user's emotional state. The input here is voice tone and facial expression patterns, and based on this, it outputs emotional states such as stress and happiness.

[0335] Step 3:

[0336] The server generates exercise and meal plans based on the analyzed emotional state. A generative AI model is used to provide personalized plans. In this process, the emotional state is utilized as a parameter in the plan. For example, if stress levels are high, a plan emphasizing relaxation will be generated.

[0337] Step 4:

[0338] The terminal receives feedback from the server and provides it to the user via the VR device. Specifically, when the user puts on the VR headset, a 3D environment tailored to their emotional state is displayed. For example, if the user is feeling tired, calming natural scenery or relaxation music will be played.

[0339] Step 5:

[0340] Users communicate with the system through interactive dialogue functions. By inputting their emotional state and health goals, this information is used for subsequent analyses. User feedback is incorporated into a database and reflected in future planning. For example, if a user inputs "I want to reduce stress," this request will be taken into consideration in the next feedback.

[0341] (Application Example 2)

[0342] 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."

[0343] In modern urban environments, there is a lack of means to individually manage the health and emotional well-being of residents and promote health throughout the community. To address this challenge, there is a need for a system that monitors the health status of groups in real time and efficiently provides appropriate health events and support based on emotions.

[0344] 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.

[0345] In this invention, the server includes an information acquisition device for monitoring the health status of a group, a processing device for analyzing the acquired biometric data and emotional state and formulating health events for the entire region, and an output device for providing rapid advice in the physical and virtual spaces based on the formulated plan. This makes it possible to improve the health status of residents and enhance the overall well-being of the region.

[0346] An "information acquisition device" is a device used to acquire data, including biometric information and emotional states, of a group of people.

[0347] A "processing device" is a device that analyzes acquired data and performs calculations and processing to formulate health events for the entire region.

[0348] An "output device" is a device that provides residents with formulated health events and advice in both physical and virtual spaces.

[0349] "Interactive communication functionality" refers to a feature that provides instructions applicable to the user and enables real-time, two-way communication.

[0350] A "community medical institution" is an organization or facility that operates within a community to provide health maintenance and medical support to residents.

[0351] The system for implementing this invention includes an information acquisition device, an information processing device, and an output device. The roles and processes of each are described below.

[0352] The information acquisition device uses wearable sensors and smartphones to collect biometric information from a group in real time. This includes physiological indicators such as motion data, heart rate, and body temperature. It also acquires voice and facial expression data to understand emotional states.

[0353] The processing unit runs on a server and uses software such as Python and TensorFlow to analyze the acquired data. Based on this data, the server classifies emotional states and develops health events appropriate for the entire community. For example, if many residents are experiencing stress, it will plan relaxation events.

[0354] The output device will quickly provide residents with formulated event information and advice through physical display devices and VR devices. Furthermore, it will be equipped with a program that enables interactive communication, allowing for real-time, two-way communication with users.

[0355] As a concrete example, if the system analyzes the emotional state of residents and detects that many residents are experiencing stress, it will send a message via a smartphone app such as, "Would you like to join a free yoga class at the park this weekend?"

[0356] An example of a prompt for the generative AI model is: "Create a message that recommends effective health events to local residents based on the user's health data and emotional state."

[0357] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0358] Step 1:

[0359] The device uses wearable sensors and smartphones to collect physiological indicator data (e.g., heart rate, body temperature) and emotional data (e.g., voice, facial expressions) from residents. This data is transmitted to a cloud server in real time. The input is biometric information and emotion-related data, and the output is this data stored in the cloud.

[0360] Step 2:

[0361] The server retrieves biometric and emotional data stored in the cloud and analyzes emotional states using Python and TensorFlow. Data processing includes tone analysis of speech and emotional classification through facial feature extraction. Input is biometric and emotional data retrieved from the cloud, and output is the analyzed emotional state information.

[0362] Step 3:

[0363] The server generates health events tailored to residents based on the analysis results. It utilizes a generation AI model to generate prompts suggesting appropriate events based on the residents' emotional states. The input is emotional state information, and the output is the content of the recommended health events.

[0364] Step 4:

[0365] The server sends information about generated health events to terminals and notifies residents via a smartphone app. It uses an interface to facilitate interactive communication and delivers messages encouraging participation. The input is event information, and the output is the notification sent to residents.

[0366] Step 5:

[0367] Based on the notification they receive, users review event details and decide whether to participate. The system receives feedback and updates participant data for further analysis. The input is the notification content, and the output is user feedback and participation status.

[0368] 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.

[0369] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0370] 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.

[0371] [Third Embodiment]

[0372] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0373] 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.

[0374] 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).

[0375] 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.

[0376] 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.

[0377] 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).

[0378] 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.

[0379] 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.

[0380] 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.

[0381] 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.

[0382] 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.

[0383] 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".

[0384] This invention is used to realize a system that comprehensively manages an individual's health status and provides a customized health plan to the user. Specific embodiments are described below.

[0385] First, the device collects biometric information in real time from the VR device and wearable sensors worn by the user. This includes the user's motion data, heart rate, respiratory rate, and body temperature. The device is equipped with communication capabilities to periodically send this data to a server.

[0386] Next, the server analyzes the received biometric information. This process uses AI algorithms to assess the user's health status. For example, it can determine the day's activity level from heart rate and movement patterns, and issue warnings about excessive or insufficient activity.

[0387] Based on the generated information, the server creates an optimal exercise and meal plan for the user. This planning function allows for flexible modification of the plan according to the user's goals and daily performance. For example, if fatigue is detected, the plan for the next day can be adjusted to include lighter exercise.

[0388] The device then provides feedback to the user in virtual reality based on the generated plan. This feedback is displayed as voice instructions or visual guides using 3D avatars. For example, an animated guide might be presented to demonstrate the correct form for squats.

[0389] Finally, users can receive personalized training and advice through interactive dialogue with the system. For example, users can use voice commands to communicate requests to the system such as "I want to avoid strenuous exercise" or "I want to try a longer running course."

[0390] In this way, the present invention enables flexible and personalized health management tailored to the user's health condition, supporting the formation of effective healthy habits while maintaining the user's motivation.

[0391] The following describes the processing flow.

[0392] Step 1:

[0393] The device works in conjunction with the VR device worn by the user, collecting biometric information in real time from motion sensors and heart rate monitors. This data includes the user's movement patterns, heart rate, and calories burned. The collected biometric information is transmitted to a server at regular intervals.

[0394] Step 2:

[0395] The server analyzes the received biometric information. Using AI algorithms, it analyzes the user's exercise patterns and current heart rate to assess their health status in real time. During this process, it checks whether the exercise load is excessive and whether there are any abnormalities in the heart rate.

[0396] Step 3:

[0397] Based on the analysis results, the server generates an optimal exercise and meal plan for the user. This plan is individually customized based on past data and the user's health goals. For example, if the user's heart rate was high, the next plan might recommend low-intensity exercise.

[0398] Step 4:

[0399] The device provides feedback to the user in a VR space based on the generated plan. Specifically, it uses voice instructions and 3D avatars to demonstrate effective exercise form and provides encouraging messages based on progress. This feedback is provided in real time to help the user exercise properly.

[0400] Step 5:

[0401] Users receive feedback and guidance through interactive dialogue features. During this time, they can communicate with the device using voice commands and gestures, and receive real-time advice from the system. For example, they can immediately communicate requests such as, "I want to do more intense exercise."

[0402] Step 6:

[0403] The server aggregates data after each session and evaluates the user's daily activity level. Based on this, it adjusts exercise and meal plans for the following days, continuously optimizing the entire system to optimize the user's health.

[0404] (Example 1)

[0405] 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."

[0406] In today's world, providing customized health management tailored to individual health conditions is challenging. In particular, there is a need to collect users' biometric information in real time and flexibly provide exercise and dietary guidelines based on that information. Furthermore, it is desirable for the system to have the ability for users to actively interact with it and instantly adjust their plans. Such a system is crucial for providing more effective and personalized health management for users.

[0407] 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.

[0408] In this invention, the server includes a device for acquiring biometric information, processing means for analyzing the acquired biometric information and generating customized exercise and dietary guidelines, and output means for providing real-time feedback in a virtual space based on the generated guidelines. This allows users to receive personalized exercise and dietary guidance tailored to their health condition. Furthermore, by including a function to dynamically adjust the plan based on the user's voice instructions, flexible management in response to daily changes in condition becomes possible.

[0409] "Biometric information" refers to data that indicates an individual's health status, and includes physiological and physical indicators such as heart rate, body temperature, and motion data.

[0410] "Device" refers to hardware components used to acquire biometric information, such as wearable sensors and VR devices.

[0411] "Analysis" is the process of processing acquired biometric information to evaluate the user's health status and activity level.

[0412] "Guidelines" refer to specific suggestions regarding exercise and diet that are generated with the aim of improving the user's health.

[0413] "Processing means" refers to a set of software and hardware functions for analyzing digital data and generating guidelines.

[0414] "Output means" refers to devices or interfaces used to provide the generated guidelines to the user visually or audibly.

[0415] "Feedback" refers to information and instructions given to users in real time based on generated guidelines.

[0416] "Interactive conversation features" are functions that allow users to communicate with the system via voice or text and receive personalized guidance.

[0417] The "dynamic plan adjustment function" refers to the ability to change exercise and dietary guidelines in response to user input and changes in biometric information.

[0418] In order to implement this invention, the system functions through the cooperation of a server, a terminal, and a user.

[0419] The terminal first collects biometric information via wearable or VR devices worn by the user. These devices include heart rate sensors, accelerometers, and body temperature sensors. The various data acquired by these sensors are transmitted to a server as physiological and physical indicators. This data is transmitted in real time or periodically, allowing for continuous monitoring of the user's condition.

[0420] The server uses AI-based analysis software to analyze biometric information transmitted from the terminal. This software evaluates the user's activity level and health status based on the biometric information. Specifically, the AI ​​analyzes heart rate and motion patterns to assess the day's activity level and detect anomalies. For example, a higher-than-normal heart rate may indicate that the user is experiencing excessive stress.

[0421] Next, the server automatically generates exercise and dietary guidelines tailored to the user's health condition based on the analysis results. These guidelines are adjusted to the user's individual goals and past data. For example, if the user's activity level was low the previous day, it might recommend light exercise or suggest a meal plan to ensure a balanced intake of necessary nutrients.

[0422] The system provides real-time feedback to the user in a virtual space based on the generated guidelines. This feedback includes visual guidance and voice instructions via the device. For example, a 3D avatar can demonstrate the correct squat form to help the user perform the exercise correctly.

[0423] Users interact with the system through voice commands and an interface to receive personalized guidance. For example, they can make specific requests such as "increase the intensity in the next training session" or "avoid certain foods." This interactive functionality provides the flexibility to dynamically adjust the plan based on the user's condition and requests on any given day.

[0424] An example of a prompt to the generating AI model is, "Based on the latest heart rate and activity data, please suggest the optimal exercise plan for the user." This advanced system enables users to develop effective healthy habits and manage their health comprehensively.

[0425] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0426] Step 1:

[0427] The device collects biometric information in real time using wearable sensors and VR devices worn by the user. This input includes heart rate, body temperature, and motion data. This data is aggregated by the device at regular intervals. The device quickly reviews the data and performs an initial check for any abnormal values. The data is then transmitted to a server using wireless communication.

[0428] Step 2:

[0429] The server analyzes biometric information received from the terminal using an AI algorithm. The specific data processing performed at this stage involves cleaning and normalizing the collected biometric data. The analysis results in an evaluation of the user's health status, activity level, and the presence or absence of abnormalities. For example, if the heart rate changes rapidly, the AI ​​model will operate to determine whether it is due to stress or exercise. As output, exercise and dietary guidelines tailored to the user's condition are generated.

[0430] Step 3:

[0431] Exercise and dietary guidelines generated on the server are sent back to the device for feedback. The device then provides real-time feedback in a virtual space based on these guidelines. Specifically, a 3D avatar visually guides the user through appropriate exercises, and a voice assistant provides verbal advice regarding diet. Furthermore, the device can improve the accuracy of its feedback by monitoring the user's reactions.

[0432] Step 4:

[0433] Users interact with the system while taking actual exercise and dietary actions based on feedback. This process allows users to operate the interface using voice commands to modify and adjust their plans. For example, if a user requests to "take it easy today," the system dynamically adjusts the plan based on that input. This action helps maintain user motivation and supports effective health management.

[0434] (Application Example 1)

[0435] 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."

[0436] In conventional health management systems, devices that collect personal biometric information and the suggested exercise and diet plans often failed to adequately integrate with each user's living environment and real-time health status. This resulted in challenges such as insufficient user convenience and inadequate health management. In particular, there was a lack of means to sustainably support users' health and safety within their daily lives.

[0437] 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.

[0438] In this invention, the server includes a measuring device for acquiring an individual's biological information, a computing device for analyzing the acquired biological information and generating an exercise plan and a nutrition plan, and a control program that provides personalized guidance to the user through interactive dialogue. This makes it possible to flexibly and effectively manage health using consumer robots in a way that is closely integrated into the user's daily life.

[0439] "Individual biometric information" refers to physiological and behavioral data, including the user's heart rate, body temperature, and movements.

[0440] A "measuring device" is a device used to acquire an individual's biological information in real time, and includes wearable sensors and VR devices.

[0441] A "computational device" is a computer system that analyzes collected biological information and generates an optimal exercise and nutrition plan for the user.

[0442] A "display device" is a device that provides feedback to the user based on a calculated plan, presenting information through sound and video.

[0443] A "control program" is software that provides interactive guidance and individualized advice tailored to the user.

[0444] "Support measures" refer to methods that utilize consumer robots used to support health management in a home environment.

[0445] This invention is based on a system that integrates a measuring device, a computing device, a display device, a control program, and support means in order to realize health management closely related to the user's daily life.

[0446] The server first acquires the user's biometric information through a measurement device. This device includes wearable sensors and VR devices to monitor heart rate, body temperature, and movement, enabling real-time data collection.

[0447] Next, the server analyzes the collected biometric information via a computing device. This analysis uses data processing algorithms with programming languages ​​such as Python, and AI models utilizing TensorFlow and PyTorch. The analysis generates an optimal exercise and nutrition plan for the user.

[0448] The generated plan is fed back to the user via a display device. The feedback is provided to the user visually and aurally as audio and video. Specifically, this is achieved through speech recognition using the Google Cloud Speech-to-Text API and 3D animation using Unity.

[0449] The control program provides personalized advice through interactive dialogue with the user. It responds to the user's voice commands and flexibly adjusts the plan according to their health goals.

[0450] For example, when a user goes for a run in the morning, the system suggests an appropriate exercise intensity based on their measured heart rate and body temperature. If the user says, "I want to slow down a bit today," the exercise plan displayed on the screen is automatically adjusted.

[0451] An example of a prompt message is, "How can we create an exercise and meal plan for tomorrow based on the user's biometric information?"

[0452] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0453] Step 1:

[0454] The device collects biometric information from the user. It uses heart rate, body temperature, and motion data obtained from wearable sensors and VR devices as input. This data is temporarily stored within the device and transmitted to a server via its communication function.

[0455] Step 2:

[0456] The server analyzes the received biometric data. Based on this input data, an AI algorithm (using TensorFlow or PyTorch) evaluates the user's health status. The data calculations performed here include time-series data analysis and anomaly detection algorithms, evaluating the user's heart rate patterns and activity levels, and generating warnings as needed.

[0457] Step 3:

[0458] The server generates an optimal exercise and nutrition plan for the user based on the analyzed health data. It uses the user's health goals and up-to-date biometric data as input, and provides a plan that includes specific exercise types, frequency, and recommended dietary content as output. In this process, a generation AI model is utilized to create a personalized plan based on the user's past data and current condition.

[0459] Step 4:

[0460] The terminal provides feedback to communicate the generated plan to the user. Using a display device, information is presented to the user through voice instructions and visual guidance via a 3D avatar. The output information is designed to aid user understanding and encourage implementation, and is implemented using Google Cloud Speech-to-Text API and Unity.

[0461] Step 5:

[0462] Users provide feedback and requests to the system via voice commands. The control program adjusts the plan in real time based on this input and engages in interactive dialogue tailored to the user. The output includes an adjusted plan and additional advice, making user health management more flexible and personalized. As a result, the system can receive and respond to requests such as, for example, "I'd like to do a lighter workout tomorrow."

[0463] 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.

[0464] This invention provides a health management system that incorporates an emotion engine that recognizes user emotions. This enables more personalized feedback and guidance, helping users maintain effective health habits. Specific embodiments are described below.

[0465] First, the device collects the user's biometric information along with the VR device and wearable sensors. This information includes motion data and physiological indicators (heart rate, body temperature, etc.), and also acquires data on the user's voice and facial expressions through the microphone and camera.

[0466] Next, the server analyzes the received biometric information and voice / facial expression data. In particular, the emotion engine analyzes voice and facial expressions to detect the user's emotional state (e.g., stress, happiness, fatigue). The detected emotions are considered as important factors when adjusting exercise and meal plans.

[0467] Based on the generated exercise and meal plan, the server generates personalized feedback. This feedback includes motivational and comforting messages tailored to the perceived emotional state.

[0468] The device provides the generated feedback to the user in the VR space. Specifically, it is used as voice instructions or as actions of a 3D avatar that respond to emotions. For example, if the user is feeling stressed, feedback such as relaxing voice guidance or calming images will be presented.

[0469] Finally, users engage in two-way communication with the system using interactive dialogue features. In this process, users can communicate their emotional state and goals to the system, and advice and plans are generated accordingly.

[0470] As described above, the present invention effectively utilizes an emotion engine to realize flexible and personalized health management tailored to each user's individual condition, thereby supporting a sustainable healthy lifestyle.

[0471] The following describes the processing flow.

[0472] Step 1:

[0473] The device collects biometric information in real time from the VR device and wearable sensors worn by the user. This information includes the user's motion data, heart rate, body temperature, voice, and facial expressions. The collected data is sent to a server for processing.

[0474] Step 2:

[0475] The server analyzes the received data. First, it uses an AI algorithm to evaluate the user's physiological state, and then uses an emotion engine to recognize the user's emotions from their voice and facial expressions. The recognized emotions are classified as feelings of stress, happiness, fatigue, etc.

[0476] Step 3:

[0477] The server generates an optimal exercise and meal plan for the user based on the analysis results. These plans are customized according to the user's fitness goals, current health status, and perceived emotional state. For example, if the user is tired, the server will suggest light exercise for relaxation.

[0478] Step 4:

[0479] The device provides the user with generated feedback in the VR space. This feedback includes instructions on exercise form, emotionally-responsive voice messages, and movements from a 3D avatar. For example, if the emotion engine detects the user's stress, the screen will display a relaxing scene.

[0480] Step 5:

[0481] Users perform exercises based on feedback provided in the VR space. They can respond with voice commands and gestures using interactive dialogue features. Users can also receive more personalized instruction by communicating their emotions and requests.

[0482] Step 6:

[0483] After a session ends, the server aggregates and evaluates the data obtained. Based on this, it adjusts the planning for the following days and provides information to continuously improve the user's health.

[0484] (Example 2)

[0485] 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."

[0486] Traditional health management systems generally only record users' biometric information and fail to effectively utilize the collected data to provide feedback that reflects individual emotional states. Therefore, there is a need for more personalized health guidance that takes into account users' mental and emotional states.

[0487] 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.

[0488] In this invention, the server includes means for analyzing biometric information and voice / facial expression data to identify emotional states, means for generating exercise and meal plans based on emotional states and providing real-time feedback, and a program that provides individually customized guidance using an interactive dialogue function. This enables flexible and personalized health management that responds to the user's emotional state.

[0489] "Biometric information" refers to quantifiable data about an individual's body, including information such as heart rate, body temperature, and motion details.

[0490] "Voice and facial expression data" refers to digital data that records an individual's voice tone and facial features, and is used as information for analyzing their emotional state.

[0491] "Emotional state" refers to an individual's mental and emotional condition, including stress, happiness, fatigue, and so on.

[0492] An "algorithm" is a series of computational procedures used to analyze specific data and derive a desired result, and is incorporated into a processing unit.

[0493] A "virtual space" is a three-dimensional digital space created using a computer, an environment in which users can intuitively operate the interface.

[0494] "Feedback" refers to the information and advice provided to users, which is useful for adjusting their behavior and motivating them.

[0495] An "interactive dialogue function" is a feature that allows the system and the user to exchange information with each other and adjust the instruction content in real time based on that information.

[0496] A "program" is a set of instructions used to perform a specific task on a computer system or device.

[0497] This invention is a system that supports user health management and has a configuration centered on an emotion engine that recognizes emotional states. The following describes how this system is implemented.

[0498] The device, as a wearable device, collects biometric information such as heart rate and body temperature in real time. Furthermore, it acquires voice data and facial expression data using a microphone and camera. This device can be worn by the user daily and seamlessly integrated into their lifestyle.

[0499] The server stores biometric information and voice / facial expression data transmitted from the terminal in a cloud-based database and performs analysis. This analysis utilizes an emotion engine and machine learning algorithms. This allows the server to identify the user's emotional state and determine stress, happiness, fatigue, and other emotional states.

[0500] Based on the analysis results, the server generates exercise and meal plans. Using a generation AI model, it creates specific and personalized plans. These plans include motivational messages tailored to the user's emotional state, as well as relaxation advice.

[0501] The generated feedback is provided to the user in a virtual space via the device. Through the VR device, relaxing natural images and sounds are played around the user, and a 3D avatar guides the user with a gentle voice.

[0502] Furthermore, users can input their current emotional state and health goals into the system using interactive dialogue features. This allows the system to create new plans and advice based on the user's input.

[0503] An example of a prompt would be, "If the user's current emotional state is stress, what relaxation activities or messages would you suggest?"

[0504] Through this mechanism, the present invention functions as a tool that integrates into the user's daily life and supports sustainable health management.

[0505] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0506] Step 1:

[0507] The device collects the user's biometric information using wearable devices. Specifically, it measures heart rate and body temperature with sensors and records activity levels with motion sensors. Audio data is collected by a microphone built into the device, and facial expression data is captured by a camera. This data is collected in real time and transferred to a server for further analysis.

[0508] Step 2:

[0509] The server receives biometric information, voice data, and facial expression data transmitted from the terminal and stores them in a database. Using an emotion engine, it analyzes the voice and facial expression data to identify the user's emotional state. The input here is voice tone and facial expression patterns, and based on this, it outputs emotional states such as stress and happiness.

[0510] Step 3:

[0511] The server generates exercise and meal plans based on the analyzed emotional state. A generative AI model is used to provide personalized plans. In this process, the emotional state is utilized as a parameter in the plan. For example, if stress levels are high, a plan emphasizing relaxation will be generated.

[0512] Step 4:

[0513] The terminal receives feedback from the server and provides it to the user via the VR device. Specifically, when the user puts on the VR headset, a 3D environment tailored to their emotional state is displayed. For example, if the user is feeling tired, calming natural scenery or relaxation music will be played.

[0514] Step 5:

[0515] Users communicate with the system through interactive dialogue functions. By inputting their emotional state and health goals, this information is used for subsequent analyses. User feedback is incorporated into a database and reflected in future planning. For example, if a user inputs "I want to reduce stress," this request will be taken into consideration in the next feedback.

[0516] (Application Example 2)

[0517] 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."

[0518] In modern urban environments, there is a lack of means to individually manage the health and emotional well-being of residents and promote health throughout the community. To address this challenge, there is a need for a system that monitors the health status of groups in real time and efficiently provides appropriate health events and support based on emotions.

[0519] 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.

[0520] In this invention, the server includes an information acquisition device for monitoring the health status of a group, a processing device for analyzing the acquired biometric data and emotional state and formulating health events for the entire region, and an output device for providing rapid advice in the physical and virtual spaces based on the formulated plan. This makes it possible to improve the health status of residents and enhance the overall well-being of the region.

[0521] An "information acquisition device" is a device used to acquire data, including biometric information and emotional states, of a group of people.

[0522] A "processing device" is a device that analyzes acquired data and performs calculations and processing to formulate health events for the entire region.

[0523] An "output device" is a device that provides residents with formulated health events and advice in both physical and virtual spaces.

[0524] "Interactive communication functionality" refers to a feature that provides instructions applicable to the user and enables real-time, two-way communication.

[0525] A "community medical institution" is an organization or facility that operates within a community to provide health maintenance and medical support to residents.

[0526] The system for implementing this invention includes an information acquisition device, an information processing device, and an output device. The roles and processes of each are described below.

[0527] The information acquisition device uses wearable sensors and smartphones to collect biometric information from a group in real time. This includes physiological indicators such as motion data, heart rate, and body temperature. It also acquires voice and facial expression data to understand emotional states.

[0528] The processing unit runs on a server and uses software such as Python and TensorFlow to analyze the acquired data. Based on this data, the server classifies emotional states and develops health events appropriate for the entire community. For example, if many residents are experiencing stress, it will plan relaxation events.

[0529] The output device will quickly provide residents with formulated event information and advice through physical display devices and VR devices. Furthermore, it will be equipped with a program that enables interactive communication, allowing for real-time, two-way communication with users.

[0530] As a concrete example, if the system analyzes the emotional state of residents and detects that many residents are experiencing stress, it will send a message via a smartphone app such as, "Would you like to join a free yoga class at the park this weekend?"

[0531] An example of a prompt for the generative AI model is: "Create a message that recommends effective health events to local residents based on the user's health data and emotional state."

[0532] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0533] Step 1:

[0534] The device uses wearable sensors and smartphones to collect physiological indicator data (e.g., heart rate, body temperature) and emotional data (e.g., voice, facial expressions) from residents. This data is transmitted to a cloud server in real time. The input is biometric information and emotion-related data, and the output is this data stored in the cloud.

[0535] Step 2:

[0536] The server retrieves biometric and emotional data stored in the cloud and analyzes emotional states using Python and TensorFlow. Data processing includes tone analysis of speech and emotional classification through facial feature extraction. Input is biometric and emotional data retrieved from the cloud, and output is the analyzed emotional state information.

[0537] Step 3:

[0538] The server generates health events tailored to residents based on the analysis results. It utilizes a generation AI model to generate prompts suggesting appropriate events based on the residents' emotional states. The input is emotional state information, and the output is the content of the recommended health events.

[0539] Step 4:

[0540] The server sends information about generated health events to terminals and notifies residents via a smartphone app. It uses an interface to facilitate interactive communication and delivers messages encouraging participation. The input is event information, and the output is the notification sent to residents.

[0541] Step 5:

[0542] Based on the notification they receive, users review event details and decide whether to participate. The system receives feedback and updates participant data for further analysis. The input is the notification content, and the output is user feedback and participation status.

[0543] 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.

[0544] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0545] 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.

[0546] [Fourth Embodiment]

[0547] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0548] 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.

[0549] 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).

[0550] 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.

[0551] 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.

[0552] 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).

[0553] 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.

[0554] 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.

[0555] 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.

[0556] 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.

[0557] 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.

[0558] 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.

[0559] 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".

[0560] This invention is used to realize a system that comprehensively manages an individual's health status and provides a customized health plan to the user. Specific embodiments are described below.

[0561] First, the device collects biometric information in real time from the VR device and wearable sensors worn by the user. This includes the user's motion data, heart rate, respiratory rate, and body temperature. The device is equipped with communication capabilities to periodically send this data to a server.

[0562] Next, the server analyzes the received biometric information. This process uses AI algorithms to assess the user's health status. For example, it can determine the day's activity level from heart rate and movement patterns, and issue warnings about excessive or insufficient activity.

[0563] Based on the generated information, the server creates an optimal exercise and meal plan for the user. This planning function allows for flexible modification of the plan according to the user's goals and daily performance. For example, if fatigue is detected, the plan for the next day can be adjusted to include lighter exercise.

[0564] The device then provides feedback to the user in virtual reality based on the generated plan. This feedback is displayed as voice instructions or visual guides using 3D avatars. For example, an animated guide might be presented to demonstrate the correct form for squats.

[0565] Finally, users can receive personalized training and advice through interactive dialogue with the system. For example, users can use voice commands to communicate requests to the system such as "I want to avoid strenuous exercise" or "I want to try a longer running course."

[0566] In this way, the present invention enables flexible and personalized health management tailored to the user's health condition, supporting the formation of effective healthy habits while maintaining the user's motivation.

[0567] The following describes the processing flow.

[0568] Step 1:

[0569] The device works in conjunction with the VR device worn by the user, collecting biometric information in real time from motion sensors and heart rate monitors. This data includes the user's movement patterns, heart rate, and calories burned. The collected biometric information is transmitted to a server at regular intervals.

[0570] Step 2:

[0571] The server analyzes the received biometric information. Using AI algorithms, it analyzes the user's exercise patterns and current heart rate to assess their health status in real time. During this process, it checks whether the exercise load is excessive and whether there are any abnormalities in the heart rate.

[0572] Step 3:

[0573] Based on the analysis results, the server generates an optimal exercise and meal plan for the user. This plan is individually customized based on past data and the user's health goals. For example, if the user's heart rate was high, the next plan might recommend low-intensity exercise.

[0574] Step 4:

[0575] The device provides feedback to the user in a VR space based on the generated plan. Specifically, it uses voice instructions and 3D avatars to demonstrate effective exercise form and provides encouraging messages based on progress. This feedback is provided in real time to help the user exercise properly.

[0576] Step 5:

[0577] Users receive feedback and guidance through interactive dialogue features. During this time, they can communicate with the device using voice commands and gestures, and receive real-time advice from the system. For example, they can immediately communicate requests such as, "I want to do more intense exercise."

[0578] Step 6:

[0579] The server aggregates data after each session and evaluates the user's daily activity level. Based on this, it adjusts exercise and meal plans for the following days, continuously optimizing the entire system to optimize the user's health.

[0580] (Example 1)

[0581] 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".

[0582] In today's world, providing customized health management tailored to individual health conditions is challenging. In particular, there is a need to collect users' biometric information in real time and flexibly provide exercise and dietary guidelines based on that information. Furthermore, it is desirable for the system to have the ability for users to actively interact with it and instantly adjust their plans. Such a system is crucial for providing more effective and personalized health management for users.

[0583] 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.

[0584] In this invention, the server includes a device for acquiring biometric information, processing means for analyzing the acquired biometric information and generating customized exercise and dietary guidelines, and output means for providing real-time feedback in a virtual space based on the generated guidelines. This allows users to receive personalized exercise and dietary guidance tailored to their health condition. Furthermore, by including a function to dynamically adjust the plan based on the user's voice instructions, flexible management in response to daily changes in condition becomes possible.

[0585] "Biometric information" refers to data that indicates an individual's health status, and includes physiological and physical indicators such as heart rate, body temperature, and motion data.

[0586] "Device" refers to hardware components used to acquire biometric information, such as wearable sensors and VR devices.

[0587] "Analysis" is the process of processing acquired biometric information to evaluate the user's health status and activity level.

[0588] "Guidelines" refer to specific suggestions regarding exercise and diet that are generated with the aim of improving the user's health.

[0589] "Processing means" refers to a set of software and hardware functions for analyzing digital data and generating guidelines.

[0590] "Output means" refers to devices or interfaces used to provide the generated guidelines to the user visually or audibly.

[0591] "Feedback" refers to information and instructions given to users in real time based on generated guidelines.

[0592] "Interactive conversation features" are functions that allow users to communicate with the system via voice or text and receive personalized guidance.

[0593] The "dynamic plan adjustment function" refers to the ability to change exercise and dietary guidelines in response to user input and changes in biometric information.

[0594] In order to implement this invention, the system functions through the cooperation of a server, a terminal, and a user.

[0595] The terminal first collects biometric information via wearable or VR devices worn by the user. These devices include heart rate sensors, accelerometers, and body temperature sensors. The various data acquired by these sensors are transmitted to a server as physiological and physical indicators. This data is transmitted in real time or periodically, allowing for continuous monitoring of the user's condition.

[0596] The server uses AI-based analysis software to analyze biometric information transmitted from the terminal. This software evaluates the user's activity level and health status based on the biometric information. Specifically, the AI ​​analyzes heart rate and motion patterns to assess the day's activity level and detect anomalies. For example, a higher-than-normal heart rate may indicate that the user is experiencing excessive stress.

[0597] Next, the server automatically generates exercise and dietary guidelines tailored to the user's health condition based on the analysis results. These guidelines are adjusted to the user's individual goals and past data. For example, if the user's activity level was low the previous day, it might recommend light exercise or suggest a meal plan to ensure a balanced intake of necessary nutrients.

[0598] The system provides real-time feedback to the user in a virtual space based on the generated guidelines. This feedback includes visual guidance and voice instructions via the device. For example, a 3D avatar can demonstrate the correct squat form to help the user perform the exercise correctly.

[0599] Users interact with the system through voice commands and an interface to receive personalized guidance. For example, they can make specific requests such as "increase the intensity in the next training session" or "avoid certain foods." This interactive functionality provides the flexibility to dynamically adjust the plan based on the user's condition and requests on any given day.

[0600] An example of a prompt to the generating AI model is, "Based on the latest heart rate and activity data, please suggest the optimal exercise plan for the user." This advanced system enables users to develop effective healthy habits and manage their health comprehensively.

[0601] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0602] Step 1:

[0603] The device collects biometric information in real time using wearable sensors and VR devices worn by the user. This input includes heart rate, body temperature, and motion data. This data is aggregated by the device at regular intervals. The device quickly reviews the data and performs an initial check for any abnormal values. The data is then transmitted to a server using wireless communication.

[0604] Step 2:

[0605] The server analyzes biometric information received from the terminal using an AI algorithm. The specific data processing performed at this stage involves cleaning and normalizing the collected biometric data. The analysis results in an evaluation of the user's health status, activity level, and the presence or absence of abnormalities. For example, if the heart rate changes rapidly, the AI ​​model will operate to determine whether it is due to stress or exercise. As output, exercise and dietary guidelines tailored to the user's condition are generated.

[0606] Step 3:

[0607] Exercise and dietary guidelines generated on the server are sent back to the device for feedback. The device then provides real-time feedback in a virtual space based on these guidelines. Specifically, a 3D avatar visually guides the user through appropriate exercises, and a voice assistant provides verbal advice regarding diet. Furthermore, the device can improve the accuracy of its feedback by monitoring the user's reactions.

[0608] Step 4:

[0609] Users interact with the system while taking actual exercise and dietary actions based on feedback. This process allows users to operate the interface using voice commands to modify and adjust their plans. For example, if a user requests to "take it easy today," the system dynamically adjusts the plan based on that input. This action helps maintain user motivation and supports effective health management.

[0610] (Application Example 1)

[0611] 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".

[0612] In conventional health management systems, devices that collect personal biometric information and the suggested exercise and diet plans often failed to adequately integrate with each user's living environment and real-time health status. This resulted in challenges such as insufficient user convenience and inadequate health management. In particular, there was a lack of means to sustainably support users' health and safety within their daily lives.

[0613] 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.

[0614] In this invention, the server includes a measuring device for acquiring an individual's biological information, a computing device for analyzing the acquired biological information and generating an exercise plan and a nutrition plan, and a control program that provides personalized guidance to the user through interactive dialogue. This makes it possible to flexibly and effectively manage health using consumer robots in a way that is closely integrated into the user's daily life.

[0615] "Individual biometric information" refers to physiological and behavioral data, including the user's heart rate, body temperature, and movements.

[0616] A "measuring device" is a device used to acquire an individual's biological information in real time, and includes wearable sensors and VR devices.

[0617] A "computational device" is a computer system that analyzes collected biological information and generates an optimal exercise and nutrition plan for the user.

[0618] A "display device" is a device that provides feedback to the user based on a calculated plan, presenting information through sound and video.

[0619] A "control program" is software that provides interactive guidance and individualized advice tailored to the user.

[0620] "Support measures" refer to methods that utilize consumer robots used to support health management in a home environment.

[0621] This invention is based on a system that integrates a measuring device, a computing device, a display device, a control program, and support means in order to realize health management closely related to the user's daily life.

[0622] The server first acquires the user's biometric information through a measurement device. This device includes wearable sensors and VR devices to monitor heart rate, body temperature, and movement, enabling real-time data collection.

[0623] Next, the server analyzes the collected biometric information via a computing device. This analysis uses data processing algorithms with programming languages ​​such as Python, and AI models utilizing TensorFlow and PyTorch. The analysis generates an optimal exercise and nutrition plan for the user.

[0624] The generated plan is fed back to the user via a display device. The feedback is provided to the user visually and aurally as audio and video. Specifically, this is achieved through speech recognition using the Google Cloud Speech-to-Text API and 3D animation using Unity.

[0625] The control program provides personalized advice through interactive dialogue with the user. It responds to the user's voice commands and flexibly adjusts the plan according to their health goals.

[0626] For example, when a user goes for a run in the morning, the system suggests an appropriate exercise intensity based on their measured heart rate and body temperature. If the user says, "I want to slow down a bit today," the exercise plan displayed on the screen is automatically adjusted.

[0627] An example of a prompt message is, "How can we create an exercise and meal plan for tomorrow based on the user's biometric information?"

[0628] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0629] Step 1:

[0630] The device collects biometric information from the user. It uses heart rate, body temperature, and motion data obtained from wearable sensors and VR devices as input. This data is temporarily stored within the device and transmitted to a server via its communication function.

[0631] Step 2:

[0632] The server analyzes the received biometric data. Based on this input data, an AI algorithm (using TensorFlow or PyTorch) evaluates the user's health status. The data calculations performed here include time-series data analysis and anomaly detection algorithms, evaluating the user's heart rate patterns and activity levels, and generating warnings as needed.

[0633] Step 3:

[0634] The server generates an optimal exercise and nutrition plan for the user based on the analyzed health data. It uses the user's health goals and up-to-date biometric data as input, and provides a plan that includes specific exercise types, frequency, and recommended dietary content as output. In this process, a generation AI model is utilized to create a personalized plan based on the user's past data and current condition.

[0635] Step 4:

[0636] The terminal provides feedback to communicate the generated plan to the user. Using a display device, information is presented to the user through voice instructions and visual guidance via a 3D avatar. The output information is designed to aid user understanding and encourage implementation, and is implemented using Google Cloud Speech-to-Text API and Unity.

[0637] Step 5:

[0638] Users provide feedback and requests to the system via voice commands. The control program adjusts the plan in real time based on this input and engages in interactive dialogue tailored to the user. The output includes an adjusted plan and additional advice, making user health management more flexible and personalized. As a result, the system can receive and respond to requests such as, for example, "I'd like to do a lighter workout tomorrow."

[0639] 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.

[0640] This invention provides a health management system that incorporates an emotion engine that recognizes user emotions. This enables more personalized feedback and guidance, helping users maintain effective health habits. Specific embodiments are described below.

[0641] First, the device collects the user's biometric information along with the VR device and wearable sensors. This information includes motion data and physiological indicators (heart rate, body temperature, etc.), and also acquires data on the user's voice and facial expressions through the microphone and camera.

[0642] Next, the server analyzes the received biometric information and voice / facial expression data. In particular, the emotion engine analyzes voice and facial expressions to detect the user's emotional state (e.g., stress, happiness, fatigue). The detected emotions are considered as important factors when adjusting exercise and meal plans.

[0643] Based on the generated exercise and meal plan, the server generates personalized feedback. This feedback includes motivational and comforting messages tailored to the perceived emotional state.

[0644] The device provides the generated feedback to the user in the VR space. Specifically, it is used as voice instructions or as actions of a 3D avatar that respond to emotions. For example, if the user is feeling stressed, feedback such as relaxing voice guidance or calming images will be presented.

[0645] Finally, users engage in two-way communication with the system using interactive dialogue features. In this process, users can communicate their emotional state and goals to the system, and advice and plans are generated accordingly.

[0646] As described above, the present invention effectively utilizes an emotion engine to realize flexible and personalized health management tailored to each user's individual condition, thereby supporting a sustainable healthy lifestyle.

[0647] The following describes the processing flow.

[0648] Step 1:

[0649] The device collects biometric information in real time from the VR device and wearable sensors worn by the user. This information includes the user's motion data, heart rate, body temperature, voice, and facial expressions. The collected data is sent to a server for processing.

[0650] Step 2:

[0651] The server analyzes the received data. First, it uses an AI algorithm to evaluate the user's physiological state, and then uses an emotion engine to recognize the user's emotions from their voice and facial expressions. The recognized emotions are classified as feelings of stress, happiness, fatigue, etc.

[0652] Step 3:

[0653] The server generates an optimal exercise and meal plan for the user based on the analysis results. These plans are customized according to the user's fitness goals, current health status, and perceived emotional state. For example, if the user is tired, the server will suggest light exercise for relaxation.

[0654] Step 4:

[0655] The device provides the user with generated feedback in the VR space. This feedback includes instructions on exercise form, emotionally-responsive voice messages, and movements from a 3D avatar. For example, if the emotion engine detects the user's stress, the screen will display a relaxing scene.

[0656] Step 5:

[0657] Users perform exercises based on feedback provided in the VR space. They can respond with voice commands and gestures using interactive dialogue features. Users can also receive more personalized instruction by communicating their emotions and requests.

[0658] Step 6:

[0659] After a session ends, the server aggregates and evaluates the data obtained. Based on this, it adjusts the planning for the following days and provides information to continuously improve the user's health.

[0660] (Example 2)

[0661] 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".

[0662] Traditional health management systems generally only record users' biometric information and fail to effectively utilize the collected data to provide feedback that reflects individual emotional states. Therefore, there is a need for more personalized health guidance that takes into account users' mental and emotional states.

[0663] 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.

[0664] In this invention, the server includes means for analyzing biometric information and voice / facial expression data to identify emotional states, means for generating exercise and meal plans based on emotional states and providing real-time feedback, and a program that provides individually customized guidance using an interactive dialogue function. This enables flexible and personalized health management that responds to the user's emotional state.

[0665] "Biometric information" refers to quantifiable data about an individual's body, including information such as heart rate, body temperature, and motion details.

[0666] "Voice and facial expression data" refers to digital data that records an individual's voice tone and facial features, and is used as information for analyzing their emotional state.

[0667] "Emotional state" refers to an individual's mental and emotional condition, including stress, happiness, fatigue, and so on.

[0668] An "algorithm" is a series of computational procedures used to analyze specific data and derive a desired result, and is incorporated into a processing unit.

[0669] A "virtual space" is a three-dimensional digital space created using a computer, an environment in which users can intuitively operate the interface.

[0670] "Feedback" refers to the information and advice provided to users, which is useful for adjusting their behavior and motivating them.

[0671] An "interactive dialogue function" is a feature that allows the system and the user to exchange information with each other and adjust the instruction content in real time based on that information.

[0672] A "program" is a set of instructions used to perform a specific task on a computer system or device.

[0673] This invention is a system that supports user health management and has a configuration centered on an emotion engine that recognizes emotional states. The following describes how this system is implemented.

[0674] The device, as a wearable device, collects biometric information such as heart rate and body temperature in real time. Furthermore, it acquires voice data and facial expression data using a microphone and camera. This device can be worn by the user daily and seamlessly integrated into their lifestyle.

[0675] The server stores biometric information and voice / facial expression data transmitted from the terminal in a cloud-based database and performs analysis. This analysis utilizes an emotion engine and machine learning algorithms. This allows the server to identify the user's emotional state and determine stress, happiness, fatigue, and other emotional states.

[0676] Based on the analysis results, the server generates exercise and meal plans. Using a generation AI model, it creates specific and personalized plans. These plans include motivational messages tailored to the user's emotional state, as well as relaxation advice.

[0677] The generated feedback is provided to the user in a virtual space via the device. Through the VR device, relaxing natural images and sounds are played around the user, and a 3D avatar guides the user with a gentle voice.

[0678] Furthermore, users can input their current emotional state and health goals into the system using interactive dialogue features. This allows the system to create new plans and advice based on the user's input.

[0679] An example of a prompt would be, "If the user's current emotional state is stress, what relaxation activities or messages would you suggest?"

[0680] Through this mechanism, the present invention functions as a tool that integrates into the user's daily life and supports sustainable health management.

[0681] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0682] Step 1:

[0683] The device collects the user's biometric information using wearable devices. Specifically, it measures heart rate and body temperature with sensors and records activity levels with motion sensors. Audio data is collected by a microphone built into the device, and facial expression data is captured by a camera. This data is collected in real time and transferred to a server for further analysis.

[0684] Step 2:

[0685] The server receives biometric information, voice data, and facial expression data transmitted from the terminal and stores them in a database. Using an emotion engine, it analyzes the voice and facial expression data to identify the user's emotional state. The input here is voice tone and facial expression patterns, and based on this, it outputs emotional states such as stress and happiness.

[0686] Step 3:

[0687] The server generates exercise and meal plans based on the analyzed emotional state. A generative AI model is used to provide personalized plans. In this process, the emotional state is utilized as a parameter in the plan. For example, if stress levels are high, a plan emphasizing relaxation will be generated.

[0688] Step 4:

[0689] The terminal receives feedback from the server and provides it to the user via the VR device. Specifically, when the user puts on the VR headset, a 3D environment tailored to their emotional state is displayed. For example, if the user is feeling tired, calming natural scenery or relaxation music will be played.

[0690] Step 5:

[0691] Users communicate with the system through interactive dialogue functions. By inputting their emotional state and health goals, this information is used for subsequent analyses. User feedback is incorporated into a database and reflected in future planning. For example, if a user inputs "I want to reduce stress," this request will be taken into consideration in the next feedback.

[0692] (Application Example 2)

[0693] 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".

[0694] In modern urban environments, there is a lack of means to individually manage the health and emotional well-being of residents and promote health throughout the community. To address this challenge, there is a need for a system that monitors the health status of groups in real time and efficiently provides appropriate health events and support based on emotions.

[0695] 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.

[0696] In this invention, the server includes an information acquisition device for monitoring the health status of a group, a processing device for analyzing the acquired biometric data and emotional state and formulating health events for the entire region, and an output device for providing rapid advice in the physical and virtual spaces based on the formulated plan. This makes it possible to improve the health status of residents and enhance the overall well-being of the region.

[0697] An "information acquisition device" is a device used to acquire data, including biometric information and emotional states, of a group of people.

[0698] A "processing device" is a device that analyzes acquired data and performs calculations and processing to formulate health events for the entire region.

[0699] An "output device" is a device that provides residents with formulated health events and advice in both physical and virtual spaces.

[0700] "Interactive communication functionality" refers to a feature that provides instructions applicable to the user and enables real-time, two-way communication.

[0701] A "community medical institution" is an organization or facility that operates within a community to provide health maintenance and medical support to residents.

[0702] The system for implementing this invention includes an information acquisition device, an information processing device, and an output device. The roles and processes of each are described below.

[0703] The information acquisition device uses wearable sensors and smartphones to collect biometric information from a group in real time. This includes physiological indicators such as motion data, heart rate, and body temperature. It also acquires voice and facial expression data to understand emotional states.

[0704] The processing unit runs on a server and uses software such as Python and TensorFlow to analyze the acquired data. Based on this data, the server classifies emotional states and develops health events appropriate for the entire community. For example, if many residents are experiencing stress, it will plan relaxation events.

[0705] The output device will quickly provide residents with formulated event information and advice through physical display devices and VR devices. Furthermore, it will be equipped with a program that enables interactive communication, allowing for real-time, two-way communication with users.

[0706] As a concrete example, if the system analyzes the emotional state of residents and detects that many residents are experiencing stress, it will send a message via a smartphone app such as, "Would you like to join a free yoga class at the park this weekend?"

[0707] An example of a prompt for the generative AI model is: "Create a message that recommends effective health events to local residents based on the user's health data and emotional state."

[0708] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0709] Step 1:

[0710] The device uses wearable sensors and smartphones to collect physiological indicator data (e.g., heart rate, body temperature) and emotional data (e.g., voice, facial expressions) from residents. This data is transmitted to a cloud server in real time. The input is biometric information and emotion-related data, and the output is this data stored in the cloud.

[0711] Step 2:

[0712] The server retrieves biometric and emotional data stored in the cloud and analyzes emotional states using Python and TensorFlow. Data processing includes tone analysis of speech and emotional classification through facial feature extraction. Input is biometric and emotional data retrieved from the cloud, and output is the analyzed emotional state information.

[0713] Step 3:

[0714] The server generates health events tailored to residents based on the analysis results. It utilizes a generation AI model to generate prompts suggesting appropriate events based on the residents' emotional states. The input is emotional state information, and the output is the content of the recommended health events.

[0715] Step 4:

[0716] The server sends information about generated health events to terminals and notifies residents via a smartphone app. It uses an interface to facilitate interactive communication and delivers messages encouraging participation. The input is event information, and the output is the notification sent to residents.

[0717] Step 5:

[0718] Based on the notification they receive, users review event details and decide whether to participate. The system receives feedback and updates participant data for further analysis. The input is the notification content, and the output is user feedback and participation status.

[0719] 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.

[0720] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0721] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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."

[0728] 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.

[0729] 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.

[0730] 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.

[0731] 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.

[0732] 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.

[0733] 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.

[0734] 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.

[0735] 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.

[0736] 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.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] The following is further disclosed regarding the embodiments described above.

[0741] (Claim 1)

[0742] A device for collecting individual biological information,

[0743] A processing device that analyzes collected biological information and generates an exercise plan and a meal plan,

[0744] An output device that provides real-time feedback in a virtual space based on the generated plan,

[0745] Software that provides customized instruction to users using interactive dialogue functions,

[0746] A system that includes this.

[0747] (Claim 2)

[0748] The system according to claim 1, further comprising means for analyzing motion data and physiological indicators as biological information.

[0749] (Claim 3)

[0750] The system according to claim 1, further comprising means for providing a message to motivate the user through audio and video based on the generated plan.

[0751] "Example 1"

[0752] (Claim 1)

[0753] A device for acquiring biological information,

[0754] A processing means for analyzing acquired biological information and generating customized exercise and dietary guidelines,

[0755] An output means that provides real-time feedback in a virtual space based on the generated guidelines,

[0756] Software that provides personalized instruction to users using interactive conversation functions,

[0757] A means that has a function to dynamically adjust the plan based on the user's voice instructions,

[0758] A system that includes this.

[0759] (Claim 2)

[0760] The system according to claim 1, further comprising means for performing activity level evaluation and anomaly detection based on biological information.

[0761] (Claim 3)

[0762] The system according to claim 1, further comprising means for providing a message to inspire the user through acoustic and visual information based on the generated guidelines.

[0763] "Application Example 1"

[0764] (Claim 1)

[0765] A measuring device for acquiring biological information of an individual,

[0766] A computing device that analyzes acquired biological information and generates an exercise plan and a nutrition plan,

[0767] A display device that provides immediate feedback in the virtual domain based on the generated plan,

[0768] A control program that provides personalized guidance to users through interactive dialogue,

[0769] To support users' daily lives based on biometric information, a support system using consumer robots that operate in a home environment,

[0770] A system that includes this.

[0771] (Claim 2)

[0772] The system according to claim 1, further comprising means for analyzing motion data and physiological indicators as biological information.

[0773] (Claim 3)

[0774] The system according to claim 1, further comprising means for providing information to inspire the user through visual and auditory means, based on the generated plan.

[0775] "Example 2 of combining an emotion engine"

[0776] (Claim 1)

[0777] A device for collecting biological information of an individual,

[0778] A processing device having an algorithm that analyzes collected biometric information and voice / facial expression data to identify emotional states,

[0779] A means of generating exercise and meal plans based on emotional state and providing real-time feedback in a virtual space,

[0780] A program that provides individually customized instruction using interactive dialogue functions,

[0781] A system that includes this.

[0782] (Claim 2)

[0783] The system according to claim 1, further comprising means for analyzing emotional states based on motion data and physiological indicators.

[0784] (Claim 3)

[0785] The system according to claim 1, further comprising means for providing motivational and comforting messages through audio and video based on emotional state.

[0786] "Application example 2 when combining with an emotional engine"

[0787] (Claim 1)

[0788] An information acquisition device for monitoring the health status of a group,

[0789] A processing device for analyzing acquired biometric data and emotional states, and for formulating health events for the entire region,

[0790] An output device for providing rapid advice in physical and virtual spaces based on the formulated plan,

[0791] A program that uses interactive communication functions to provide instructions to the user,

[0792] A system that includes this.

[0793] (Claim 2)

[0794] The system according to claim 1, further comprising means for recommending events to which participation is suggested based on emotional state.

[0795] (Claim 3)

[0796] The system according to claim 1, further comprising means for transmitting information to provide optimal support in cooperation with local medical institutions. [Explanation of symbols]

[0797] 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 device for collecting individual biological information, A processing device that analyzes collected biological information and generates an exercise plan and a meal plan, An output device that provides real-time feedback in a virtual space based on the generated plan, Software that provides customized instruction to users using interactive dialogue functions, A system that includes this.

2. The system according to claim 1, further comprising means for analyzing motion data and physiological indicators as biological information.

3. The system according to claim 1, further comprising means for providing a message to motivate the user through audio and video based on the generated plan.

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