system

Abstract

We provide the system. [Solution] A means of obtaining physiological data and goals from users, A means for automatically generating exercise and nutrition plans to achieve health goals based on acquired physiological data, A means of presenting the generated exercise plan in a virtual space, detecting the user's movements, and providing feedback, A means of adjusting exercise and nutrition plans based on user feedback and the latest physiological data, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern times, it is difficult to easily obtain suitable exercise and nutrition plans according to individual health goals such as maintaining health, managing weight, and increasing muscle strength. In addition, conventional fitness programs are insufficiently personalized and cannot fully meet the needs of individual users. In particular, there are also problems such as the high cost of personal gyms and the uniformity of online services. In addition, since feedback cannot be obtained in real time, users cannot appropriately grasp their own progress and may lose motivation halfway. The present invention aims to solve these problems and provide an optimized fitness experience according to individual needs.

Means for Solving the Problems

[0005] This invention provides means for acquiring physiological data and goals from the user. This allows for the creation of exercise and nutrition plans based on real-world data regarding the user's health status and goals. Furthermore, it includes means for automatically generating optimal exercise and nutrition plans to achieve health goals using a generating AI based on the acquired physiological data. In addition, the system presents the generated exercise plan in a virtual space and includes means for detecting the user's movements using sensors and providing real-time feedback while the user trains in the VR environment. This allows the user to train with proper form and constantly check guidelines for achieving their goals. Moreover, by providing means for continuously adjusting the exercise and nutrition plans based on user feedback and the latest physiological data, the system can continuously provide optimized plans. These means enable the provision of a cost-effective and personalized fitness experience to the user.

[0006] "Physiological data" refers to basic physical information such as height, weight, age, heart rate, and exercise history that is collected to indicate the user's health status.

[0007] A "goal" is a specific objective that a user wants to achieve in health management or fitness, and examples include weight loss or muscle gain.

[0008] An "exercise plan" is a plan that specifies the type, frequency, and intensity of exercise over a certain period, designed based on the user's individual needs.

[0009] A "nutrition plan" is a plan that manages the content, quantity, and timing of meals to help users achieve their health goals.

[0010] "Health goals" refer to specific outcomes that users aim to achieve in the process of fitness or health management, such as weight loss, muscle strengthening, and improved endurance.

[0011] A "virtual space" is a digitally constructed three-dimensional space, distinct from the actual physical space, that users experience through VR technology.

[0012] "Feedback" refers to fitness guidance and improvement instructions provided in real time in response to the user's actions, and is information used to improve the accuracy and effectiveness of exercise. [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] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

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, a labeled processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one 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, a labeled 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, a labeled 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 signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[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 a fitness system that combines VR technology and generative AI to efficiently support users in achieving their health goals. The system consists of three main components: the user, the terminal, and the server.

[0035] First, users input physiological data and set health goals they wish to achieve using a wearable device or dedicated application. This physiological data includes height, weight, age, heart rate, and exercise history. This data is transmitted to a server via the device.

[0036] The server performs data analysis based on physiological data and goals submitted by the user. The generating AI automatically creates optimal exercise and nutrition plans. In doing so, the AI ​​considers the user's current fitness level and health goals to ensure the plan is most suitable. Furthermore, the generated plan is adjusted to meet the user's individual needs, resulting in an effective and personalized experience.

[0037] The generated exercise plan is presented to the user in a virtual space via the device. The user wears a VR headset and can experience a realistic training session. The device tracks the user's movements in the VR space using sensors and sends the data back to the server in real time. The server analyzes this data, and an AI agent provides real-time feedback. This feedback includes advice on improving form and exercise intensity.

[0038] For example, if a user sets a goal of "losing 10 kilograms," the server will provide an exercise plan that includes aerobic exercise focused on calorie consumption, as well as a nutrition plan that manages calorie intake. As the user exercises in the VR space, the device tracks their movements, and if any form errors are detected, the server immediately provides instructions to correct them.

[0039] Furthermore, based on newly acquired physiological data and feedback, the server continuously evaluates the user's progress and updates the plan as needed. This ensures that users always have access to the latest, optimized fitness and nutrition plans.

[0040] Thus, this system integrates advanced personalization and real-time feedback functions to provide users with an effective and efficient means of health management.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users input physiological data (height, weight, age, heart rate, etc.) and health goals using a dedicated app or wearable device. The device collects this data and sends it to a server.

[0044] Step 2:

[0045] The server performs data analysis using the received physiological data and health goals. A generating AI analyzes the data and creates an optimized exercise and nutrition plan for the user. In this process, the most suitable type of exercise and nutritional balance for each user is considered.

[0046] Step 3:

[0047] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset and begins training in the virtual space. The training content is visually presented in the virtual space, and the user performs the exercises according to the instructions.

[0048] Step 4:

[0049] The device tracks the user's movements. Sensors do this, monitoring the user's exercise form and the accuracy of their movements. This tracking data is sent to the server in real time.

[0050] Step 5:

[0051] The server analyzes the received tracking data. An AI agent evaluates the user's exercise form and generates corrective instructions if necessary. This includes advice on areas for improvement in form and the properness of the movements.

[0052] Step 6:

[0053] The server generates feedback and provides it to the user in real time via the terminal. The user receives this feedback and makes adjustments to their form during exercise.

[0054] Step 7:

[0055] The user regularly inputs new physical data and reports their progress. The device sends this data to a server, which reviews the exercise and nutrition plan based on the latest data. The plan is updated as needed to continuously provide the user with the most suitable content.

[0056] These steps allow users to receive support in effectively achieving their health goals.

[0057] (Example 1)

[0058] 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."

[0059] Traditional fitness systems struggled to propose efficient plans based on users' physiological data and goals, and real-time feedback and plan adjustments were limited. Furthermore, they lacked personalized health management tools, making it difficult to meet individual user needs.

[0060] 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.

[0061] In this invention, the server includes means for acquiring human body data and goals from the user, means for automatically generating an exercise plan and a nutrition plan to achieve the health goals based on the acquired human body data, and means for providing immediate feedback on the exercise plan via a generated AI model through a display device equipped with a virtual training environment. This makes it possible to provide the user with a highly personalized exercise and nutrition plan.

[0062] A "user" refers to an individual who uses the system to achieve their own health goals.

[0063] "Human body data" refers to numerical information such as height, weight, age, heart rate, and exercise history used to assess the user's health status.

[0064] "Goals" refer to specific health improvement objectives that users attempt to achieve through the system.

[0065] An "exercise plan" refers to a specific schedule or set of activities that provides guidance on the physical activity necessary for a user to achieve their goals.

[0066] A "nutrition plan" refers to specific advice and suggestions that provide users with guidelines for the types of meals and nutrients they need to achieve their goals.

[0067] A "virtual domain" refers to a computer-generated digital space used by users to gain an immersive training experience.

[0068] A "generative AI model" refers to an artificial intelligence-based algorithm that automatically constructs an optimal exercise and nutrition plan based on the user's personal data and goals.

[0069] "Feedback" refers to advice provided to users to help them effectively engage in activities within the virtual realm, including form modifications and motivational suggestions.

[0070] "Resistance exercise" refers to physical activity performed through specific resistance with the aim of strengthening muscles.

[0071] A "display device" is a computer-connected technological device used to provide visual information to a user, and an example of this is a VR headset.

[0072] This system is a fitness platform that integrates virtual reality technology and generative AI to achieve health goals. It consists of three main components: users, terminals, and servers.

[0073] Users input their personal data using wearable devices and dedicated applications, and set health goals they want to achieve. For example, a user might use a smartwatch to record their heart rate and exercise history, and then use a dedicated app to set a goal such as "I want to lose 10 kilograms."

[0074] The terminal sends data obtained from the user to the server. In this case, the terminal uses a secure protocol to transfer data via the internet connection.

[0075] The server uses a generative AI model to analyze data sent from the user. This analysis automatically generates an optimal exercise and nutrition plan for each individual user. In doing so, the AI ​​model analyzes the user's heart rate and exercise history to suggest personalized exercise intensity and menus.

[0076] The generated exercise plan is presented to the user via a device. The user then wears a VR headset and experiences a realistic training session within a virtual environment. For example, a scene of the user performing aerobic exercise is recreated in VR.

[0077] The device uses sensors to track the user's movements in the virtual environment in real time and sends that data back to the server. The server analyzes this data, and a generated AI model provides real-time feedback on improving exercise form and appropriate exercise intensity.

[0078] An example of a prompt message would be something like, "What kind of aerobic exercise should the user do to lose 10 kilograms?" This prompt allows the generating AI model to automatically create an appropriate exercise plan, providing the user with a personalized fitness experience.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] Users input their physiological information into the device using a wearable device or dedicated application. Specifically, data such as height, weight, age, heart rate, and past exercise history are entered. This input data serves as foundational information used for subsequent analysis and is stored on the device. As output, the entered physiological information is recorded in a database within the device.

[0082] Step 2:

[0083] The terminal sends physiological information obtained from the user to the server. Specifically, the terminal securely encrypts this data and sends it to the server via the internet. In this step, the physiological information arrives at the server as output and is ready for analysis.

[0084] Step 3:

[0085] The server receives the user's physiological information and analyzes it using a generative AI model. Based on the input data, it automatically generates an optimal exercise and nutrition plan. The server uses the AI ​​model to perform data calculations based on the user's health goals and fitness level, and outputs individually customized suggestions. The output of this process is a personalized exercise and nutrition plan tailored to the user.

[0086] Step 4:

[0087] The generated exercise plan is presented to the user via a terminal. The terminal streams the information to a VR headset, which the user wears to experience a training session in a virtual environment. Specifically, it includes an exercise scenario provided as visual information, which the user then physically moves. The output of this step is for the user to begin a personalized exercise in the virtual space based on the feedback.

[0088] Step 5:

[0089] The device tracks the user's body movements in real time during a VR session and sends the data back to the server. As input, the user's movement data is captured by sensors and sent to the server. As output, the movement data received by the server forms the basis for the subsequent feedback process.

[0090] Step 6:

[0091] The server analyzes the user's exercise data, and the AI ​​agent provides real-time feedback. Specifically, it generates advice on improving form and instructions on adjusting exercise intensity. The output of the analysis, based on the data obtained from the input, is an adjustment suggestion that is immediately provided to the user.

[0092] Step 7:

[0093] Based on feedback and newly acquired physiological information, the server adjusts the exercise and nutrition plans as needed, ensuring that users always have access to the optimal plan. The output of this step is a personalized plan that the user can use again as an updated plan.

[0094] (Application Example 1)

[0095] 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."

[0096] In modern society, individual health management is a crucial issue. However, it is difficult for users to obtain personalized and effective exercise and nutritional guidelines, and there is a lack of means to continuously adjust and effectively implement them. Furthermore, user-friendly interactive feedback mechanisms are insufficient. To address this challenge, an efficient method is needed that provides users with real-time, personalized feedback to support the achievement of their health goals.

[0097] 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.

[0098] In this invention, the server includes means for acquiring physiological information and goals from the user; means for automatically generating exercise and nutritional guidelines to achieve health goals based on the acquired physiological information; means for presenting the generated exercise guidelines in a virtual space, detecting the user's movements and providing feedback; means for correcting the user's exercise form and adjusting the exercise intensity in real time through a personal robot; and means for adjusting the exercise and nutritional guidelines based on the latest physiological data and feedback. As a result, the user can receive a personalized and optimal health management plan in real time and efficiently achieve their health goals.

[0099] A "user" refers to an individual who uses the invention for health management.

[0100] "Physiological information" refers to an individual's physical data, such as height, weight, age, heart rate, and exercise history.

[0101] "Health goals" refer to the health status or fitness level that the user wishes to achieve.

[0102] An "exercise guideline" refers to a plan that outlines the type and frequency of exercise necessary to achieve the user's health goals.

[0103] "Nutritional guidelines" refer to the dietary content and nutrient intake plan necessary to achieve the user's health goals.

[0104] "Virtual space" refers to a computer-generated three-dimensional space that users experience using VR technology.

[0105] "Feedback" refers to information that provides real-time evaluations and advice on the user's exercise and activities.

[0106] A "personal robot" refers to a device used in the home that is designed to assist the user and support exercise and health management.

[0107] "Real-time" refers to a state where processing or responses are performed almost instantly.

[0108] "Correcting the shape" refers to adjustments made to correct the user's posture and movements during exercise.

[0109] "Adjusting exercise intensity" refers to appropriately changing the load and intensity of exercise according to the user's physical fitness and abilities.

[0110] To implement this invention, a user, a terminal, and a server are required. First, the user uses a wearable device or a dedicated application to input their physiological information and set health goals they wish to achieve. This information is transmitted to the server via the terminal.

[0111] The server uses cloud services such as AWS® Lambda and Google® Cloud Functions to process the received physiological information. Next, a generative AI model is used to automatically generate exercise and nutritional guidelines best suited to the user's health goals. This generation process involves data analysis using Python libraries. Furthermore, a plan is created that takes into account the user's fitness level and individual needs.

[0112] The generated exercise guidelines are presented to the user via a terminal, and the user wears a VR headset such as the Oculus Quest 2 to experience a realistic training session in a virtual space. The terminal tracks the user's movements with sensors and transmits that data to the server in real time.

[0113] The server analyzes the received data, and an AI agent provides the user with real-time, personalized feedback. This feedback includes advice on improving form and exercise intensity. Users can also receive support from a personal robot installed in their home, enabling them to continue their training.

[0114] For example, if a user sets a goal of "completing a marathon within three months," the AI ​​will propose a plan primarily focused on aerobic exercise to cultivate perseverance. Following this plan, the user can train under the guidance of a personal robot.

[0115] An example of a prompt message would be: "The user's goal is to complete a full marathon within three months. Please generate the optimal training program and nutrition plan for this purpose."

[0116] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0117] Step 1:

[0118] Users input physiological information (e.g., height, weight, heart rate) and health goals using wearable devices or dedicated applications. This input information is transmitted to a server via the terminal. JSON or XML is used as the data format, from which health goals and individual physiological parameters are extracted.

[0119] Step 2:

[0120] The server processes the received physiological information and health goals using AWS Lambda. Based on the input data, it performs data analysis using Python libraries and other tools to generate exercise and nutritional guidelines tailored to the user's fitness level. The generating AI model creates the optimal plan by executing algorithms that take into account past exercise data and current goals. The output is personalized guidelines.

[0121] Step 3:

[0122] The generated exercise guidelines are provided to the user via a terminal. The user wears a VR headset such as an Oculus Quest 2 and starts an exercise session in a virtual space. The terminal tracks the user's movements in the VR space using sensors. The input is movement data from the sensors, and the output is feedback information regarding the user's progress.

[0123] Step 4:

[0124] The server receives user movement data transmitted from the device and performs real-time analysis. The server uses an AI agent to analyze the movement data and immediately provides advice on areas for improvement in form and exercise intensity. This process generates feedback. The output, containing information about the advice, is presented to the user.

[0125] Step 5:

[0126] Users receive further support through a personal robot in their home. The robot provides physical feedback and support to the user based on instructions from a server. The input is specific motion instructions provided by the server, and the robot performs the actions accordingly. The output is an improvement in the user's movement patterns.

[0127] 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.

[0128] This invention is an advanced fitness system that combines VR technology, generative AI, and an emotion engine. The system consists of three main components: the user, the terminal, and the server, enabling the provision of personalized fitness and nutrition plans to individual users.

[0129] Users input physiological data (e.g., height, weight, age) and health goals via a dedicated application or wearable device. This physiological data and goals are transmitted from the device to the server. Furthermore, the emotion engine acquires the user's emotional data and provides this data to the server for use in customizing the fitness plan.

[0130] The server first analyzes the user's physiological data and goals, and then generates an exercise and nutrition plan to achieve those goals. The AI ​​generates the optimal plan automatically based on the user's fitness level, goals, and emotional data. The generated exercise plan includes aerobic exercise and strength training, and its details take into account the user's motivation and stress level.

[0131] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset, enters the virtual environment, and begins exercising. The device's sensors track the user's movements in real time and send the movement data to the server. The server analyzes this data and provides feedback to correct inaccurate form and improve motivation.

[0132] In particular, this system uses an emotion engine to evaluate the user's emotional state in real time and dynamically adjust the exercise plan and feedback. For example, if a user is feeling stressed, the emotion engine adjusts the exercise intensity to promote relaxation or adds exercises aimed at stress relief. Also, if the system determines that the user's motivation is low based on emotional data, it sets exercise goals in small increments to provide encouragement and a sense of accomplishment.

[0133] For example, if a user sets a goal of losing 5 kg through exercise three times a week and is in an emotional state prone to stress during exercise, the server generates a plan that combines light aerobic exercise incorporating relaxation elements with short, highly efficient strength training sessions. As the user exercises in the VR space, the emotion engine provides real-time feedback to alleviate stress and supports training tailored to the user's condition.

[0134] This invention allows users to obtain a more effective and personalized fitness experience based on physiological and emotional data, enabling them to efficiently achieve their health goals.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] Users input physiological data (height, weight, age, etc.) and health goals via a dedicated app or wearable device. In addition, an emotion engine acquires emotional data from the user's facial expressions and voice. The device then transmits this data to a server.

[0138] Step 2:

[0139] The server analyzes the received physiological data, health goals, and emotional data. Based on this data, the generating AI automatically creates optimal exercise and nutrition plans. In doing so, it takes into account the user's fitness level and emotional state to generate individually optimized plans.

[0140] Step 3:

[0141] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset and begins exercising in the virtual environment. During this time, the device tracks the user's movements using sensors and sends the movement data to the server.

[0142] Step 4:

[0143] The server analyzes tracking data to evaluate the user's exercise form and the accuracy of their movements. Additionally, an emotion engine evaluates the user's emotional state in real time and generates feedback based on that data.

[0144] Step 5:

[0145] The server sends the generated feedback to the device, providing it to the user in real time. This feedback may include instructions for form correction and encouraging messages. The user receives this feedback and adjusts their exercise accordingly.

[0146] Step 6:

[0147] Users regularly input new physiological data and feedback into the system. The terminal sends this data to the server, which reviews the exercise and nutrition plan based on the latest data. The plan is updated as needed, and the latest information is provided to the user.

[0148] These steps allow users to gain a fitness experience that best suits their emotional and physical condition.

[0149] (Example 2)

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

[0151] Traditional fitness systems have limitations in providing plans based on individual users' physiological data and goals, and also in providing dynamic feedback that takes into account the user's emotional state. As a result, it has been difficult for users to obtain an optimal fitness experience and achieve their goals effectively.

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

[0153] In this invention, the server includes means for acquiring personal data and goals from the user, means for measuring the user's emotional state using an emotion analysis device, and a knowledge processing device for automatically generating a physical activity plan and a nutrition plan to achieve the goals based on the acquired personal data and emotional state. This enables the provision of a personalized fitness plan adapted to the user's individual circumstances and allows for dynamically adjusted feedback during exercise.

[0154] "Personal data" refers to information that indicates a user's physiological state and health goals, including basic information such as height, weight, and age, as well as set fitness goals.

[0155] "Goals" refer to the health conditions or fitness outcomes that the user wishes to achieve, and specifically include things like weight loss, muscle building, and improved endurance.

[0156] An "emotion analysis device" is a device that determines a user's emotional state based on their facial expressions, voice, and movement patterns.

[0157] "Emotional state" refers to the user's psychological or emotional state, and includes factors such as stress, motivation, and relaxation level.

[0158] A "physical activity plan" is a plan that outlines the schedule and content of exercise created to help a user achieve their health goals.

[0159] A "virtual environment" is a computer-generated simulation environment that users experience using VR headsets or similar devices, enabling them to engage in fitness activities in an immersive way.

[0160] "Feedback" refers to the feedback provided to users during their workouts, including advice for correcting form and improving motivation.

[0161] The following is a description of embodiments for specifically carrying out the present invention.

[0162] Users input their personal data and health goals using a dedicated application or wearable device. This includes basic information such as the user's height, weight, and age, as well as specific health goals such as "aim to lose 5 kilograms by exercising three times a week."

[0163] The terminal's role is to transmit entered personal data and goals to the server. It also uses an emotion analysis device to measure the user's emotional state and provides this information to the server. During this process, sensors within the terminal analyze the user's facial expressions and voice to determine their stress and relaxation levels.

[0164] Based on the received personal data and emotional state, the server uses a generative AI model to automatically generate a physical activity plan and nutrition plan tailored to the user. This AI model devises plans, including endurance activities and muscle-strengthening activities, according to the user's fitness level and emotional fluctuations.

[0165] The generated plan is presented to the user via the device, and the user puts on a VR headset and begins exercising in the virtual environment. This virtual environment is designed to allow users to experience activities such as running in a simulated park. The device tracks the user's movements in real time and transmits the motion data.

[0166] The server analyzes this data and provides suggestions for correction if the operation is inaccurate. It can also dynamically adjust the exercise plan and feedback based on the user's emotional state.

[0167] For example, if a user inputs the prompt "I want to lose 5 kg by exercising three times a week," the generating AI model will suggest a plan that includes light endurance exercises emphasizing relaxation and time-efficient strength training. This process allows the user to enjoy a personalized fitness experience.

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] Users enter personal data as part of the initial setup through a dedicated application or wearable device. This includes height, weight, age, and health goals. The data entered by the user is collected by the device. The entered personal data is then prepared to be transferred to the server as basic information necessary for subsequent processing steps.

[0171] Step 2:

[0172] The device transmits personal data and health goals collected from the user to the server. In addition, the device uses an emotion analysis device to measure the user's emotional state (stress, relaxation level, etc.) and transmits this data to the server. Here, emotional data obtained from the user's facial expressions and voice indicators is processed to reveal the user's emotional state, and this information is transmitted to the server.

[0173] Step 3:

[0174] The server analyzes the received personal and emotional data and uses a generative AI model to automatically generate a physical activity plan and nutrition plan tailored to the user. Inputs include the user's fitness level, health goals, and current emotional state. The server processes this information and outputs a plan that includes optimal endurance and muscle-strengthening activities for the user.

[0175] Step 4:

[0176] The generated plan is presented to the user via a device. The device uses a VR headset to construct a virtual environment based on the generated plan. The user then enters this virtual environment and begins exercising. Specifically, running in a simulated park and various exercises are visualized.

[0177] Step 5:

[0178] The device's sensors track the user's movements in real time and transmit that data to the server. The input includes specific movement data from the user during exercise. This enables real-time feedback.

[0179] Step 6:

[0180] The server analyzes motion data sent from the terminal to check whether the exercise is being performed correctly. If inappropriate form or motion is detected, it generates feedback for correction and provides it to the user through the terminal. The content of the feedback is also dynamically adjusted based on the user's emotional state.

[0181] Step 7:

[0182] Users receive feedback from the server and modify their exercises as needed. They then use this feedback to improve their next training session, aiming for sustained fitness improvement. Once a user completes a training session, all data is saved for creating their next training plan.

[0183] (Application Example 2)

[0184] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0185] In modern society, it is crucial for individuals to effectively utilize fitness and nutrition plans to achieve their health goals. However, these plans are often rigid and lack the dynamic adjustments necessary to consider individual physiological data, emotional states, and even location information. Furthermore, if a fitness plan does not align with a user's real-world environment, it can be difficult for users to maintain motivation. This can hinder effective health management.

[0186] 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.

[0187] In this invention, the server includes means for acquiring physiological data and goals from the user, means for automatically generating exercise and nutrition plans to achieve health goals based on the acquired physiological data, and means for dynamically customizing the fitness plan based on the user's location information and environment. This makes it possible to provide a flexible fitness experience adapted to the individual circumstances of the user.

[0188] "Physiological data" refers to information about an individual's physique, age, and health status, and is used to customize the user's fitness plan.

[0189] "Health goals" refer to specific targets related to the health state or fitness level that an individual wishes to achieve, and serve as a basis for creating a plan.

[0190] An "exercise plan" refers to a specific plan of exercise and training designed to help a user achieve their health goals.

[0191] A "nutrition plan" refers to a plan outlining recommended meals and nutritional intake to help a user achieve their health goals.

[0192] A "virtual environment" refers to a digital space that users experience through digital technology, either by mimicking or uniquely designing a real-world environment.

[0193] "Location information" refers to geographical data that indicates the user's current location, and is used to customize fitness plans.

[0194] "Emotional data" refers to information that reflects the user's emotional state and is used to adjust exercise plans and provide feedback.

[0195] To implement this invention, the user must first install a dedicated application on their smartphone or AR-enabled smart glasses. Upon launching the application and inputting their physiological data and health goals, the data is transmitted from the device to a server. At this point, the server utilizes a generative AI model to automatically generate an exercise plan and nutrition plan to achieve the user's health goals. This generation process also takes into account the user's emotional data and location information.

[0196] The device presents the generated exercise plan to the user in a virtual environment, and the user begins exercising according to the instructions. When the user exercises, the system provides a fitness plan appropriate to the location based on location information. For example, when visiting a park, aerobic exercise suited to that environment will be recommended.

[0197] During exercise, sensors in the device track the user's movements in real time and send the data to a server. The server then analyzes the received movement data and provides feedback to the user. This includes advice on correcting incorrect form and improving motivation.

[0198] This system's emotion engine has the ability to evaluate the user's emotional state in real time and dynamically adjust the exercise plan. For example, if the user is feeling stressed, the exercise content will be changed to something that promotes relaxation. Specifically, if the user has a goal of "continuing to exercise three times a week while relaxing," it will recommend light aerobic exercise in a relaxing environment.

[0199] An example of a prompt to a generative AI model is: "Location: park, User's mood: tired, Please provide a recommended fitness plan."

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] Users launch a dedicated application on their smartphone or AR-enabled smart glasses and input physiological data (height, weight, age, etc.) and health goals. The input data is sent to the server by the device. The input here consists of the user's physiological data and goals, which become the output data to the server.

[0203] Step 2:

[0204] The server automatically generates optimal exercise and nutrition plans using an AI model based on received physiological data and health goals. It uses the user's physiological data and goals as input data, analyzing and processing this data to output the exercise and nutrition plans. The generated plans include aerobic exercise and strength training, and are customized for each user.

[0205] Step 3:

[0206] The terminal presents the user with an exercise plan received from the server in a virtual environment. The user then uses VR or AR technology to begin exercising according to the plan. In this case, the generated exercise plan is the input data, and the provision of a visual training scene in the virtual environment is the output.

[0207] Step 4:

[0208] When a user exercises, sensors built into the device track the user's movements in real time. The device sends the collected movement data to a server. In this process, the movement data is the input, and the transmission to the server is the output.

[0209] Step 5:

[0210] The server analyzes the received motion data and generates feedback for the user. The input is previously tracked motion data, and the output is feedback information. The feedback includes advice for correcting exercise form and maintaining motivation.

[0211] Step 6:

[0212] The emotion engine evaluates the user's emotional state in real time and dynamically adjusts the exercise plan. The user's emotional data is used as input, and adjustments to exercise intensity and content are output. For example, if the user is feeling stressed, exercises that promote relaxation will be suggested.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] 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.

[0219] 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).

[0220] 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.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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".

[0229] This invention is a fitness system that combines VR technology and generative AI to efficiently support users in achieving their health goals. The system consists of three main components: the user, the terminal, and the server.

[0230] First, users input physiological data and set health goals they wish to achieve using a wearable device or dedicated application. This physiological data includes height, weight, age, heart rate, and exercise history. This data is transmitted to a server via the device.

[0231] The server performs data analysis based on physiological data and goals submitted by the user. The generating AI automatically creates optimal exercise and nutrition plans. In doing so, the AI ​​considers the user's current fitness level and health goals to ensure the plan is most suitable. Furthermore, the generated plan is adjusted to meet the user's individual needs, resulting in an effective and personalized experience.

[0232] The generated exercise plan is presented to the user in a virtual space via the device. The user wears a VR headset and can experience a realistic training session. The device tracks the user's movements in the VR space using sensors and sends the data back to the server in real time. The server analyzes this data, and an AI agent provides real-time feedback. This feedback includes advice on improving form and exercise intensity.

[0233] For example, if a user sets a goal of "losing 10 kilograms," the server will provide an exercise plan that includes aerobic exercise focused on calorie consumption, as well as a nutrition plan that manages calorie intake. As the user exercises in the VR space, the device tracks their movements, and if any form errors are detected, the server immediately provides instructions to correct them.

[0234] Furthermore, based on newly acquired physiological data and feedback, the server continuously evaluates the user's progress and updates the plan as needed. This ensures that users always have access to the latest, optimized fitness and nutrition plans.

[0235] Thus, this system integrates advanced personalization and real-time feedback functions to provide users with an effective and efficient means of health management.

[0236] The following describes the processing flow.

[0237] Step 1:

[0238] Users input physiological data (height, weight, age, heart rate, etc.) and health goals using a dedicated app or wearable device. The device collects this data and sends it to a server.

[0239] Step 2:

[0240] The server performs data analysis using the received physiological data and health goals. A generating AI analyzes the data and creates an optimized exercise and nutrition plan for the user. In this process, the most suitable type of exercise and nutritional balance for each user is considered.

[0241] Step 3:

[0242] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset and begins training in the virtual space. The training content is visually presented in the virtual space, and the user performs the exercises according to the instructions.

[0243] Step 4:

[0244] The device tracks the user's movements. Sensors do this, monitoring the user's exercise form and the accuracy of their movements. This tracking data is sent to the server in real time.

[0245] Step 5:

[0246] The server analyzes the received tracking data. An AI agent evaluates the user's exercise form and generates corrective instructions if necessary. This includes advice on areas for improvement in form and the properness of the movements.

[0247] Step 6:

[0248] The server generates feedback and provides it to the user in real time via the terminal. The user receives this feedback and makes adjustments to their form during exercise.

[0249] Step 7:

[0250] The user regularly inputs new physical data and reports their progress. The device sends this data to a server, which reviews the exercise and nutrition plan based on the latest data. The plan is updated as needed to continuously provide the user with the most suitable content.

[0251] These steps allow users to receive support in effectively achieving their health goals.

[0252] (Example 1)

[0253] 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."

[0254] Traditional fitness systems struggled to propose efficient plans based on users' physiological data and goals, and real-time feedback and plan adjustments were limited. Furthermore, they lacked personalized health management tools, making it difficult to meet individual user needs.

[0255] 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.

[0256] In this invention, the server includes means for acquiring human body data and goals from the user, means for automatically generating an exercise plan and a nutrition plan to achieve the health goals based on the acquired human body data, and means for providing immediate feedback on the exercise plan via a generated AI model through a display device equipped with a virtual training environment. This makes it possible to provide the user with a highly personalized exercise and nutrition plan.

[0257] A "user" refers to an individual who uses the system to achieve their own health goals.

[0258] "Human body data" refers to numerical information such as height, weight, age, heart rate, and exercise history used to assess the user's health status.

[0259] "Goals" refer to specific health improvement objectives that users attempt to achieve through the system.

[0260] An "exercise plan" refers to a specific schedule or set of activities that provides guidance on the physical activity necessary for a user to achieve their goals.

[0261] A "nutrition plan" refers to specific advice and suggestions that provide users with guidelines for the types of meals and nutrients they need to achieve their goals.

[0262] A "virtual domain" refers to a computer-generated digital space used by users to gain an immersive training experience.

[0263] A "generative AI model" refers to an artificial intelligence-based algorithm that automatically constructs an optimal exercise and nutrition plan based on the user's personal data and goals.

[0264] "Feedback" refers to advice provided to users to help them effectively engage in activities within the virtual realm, including form modifications and motivational suggestions.

[0265] "Resistance exercise" refers to physical activity performed through specific resistance with the aim of strengthening muscles.

[0266] A "display device" is a computer-connected technological device used to provide visual information to a user, and an example of this is a VR headset.

[0267] This system is a fitness platform that integrates virtual reality technology and generative AI to achieve health goals. It consists of three main components: users, terminals, and servers.

[0268] Users input their personal data using wearable devices and dedicated applications, and set health goals they want to achieve. For example, a user might use a smartwatch to record their heart rate and exercise history, and then use a dedicated app to set a goal such as "I want to lose 10 kilograms."

[0269] The terminal sends data obtained from the user to the server. In this case, the terminal uses a secure protocol to transfer data via the internet connection.

[0270] The server uses a generative AI model to analyze data sent from the user. This analysis automatically generates an optimal exercise and nutrition plan for each individual user. In doing so, the AI ​​model analyzes the user's heart rate and exercise history to suggest personalized exercise intensity and menus.

[0271] The generated exercise plan is presented to the user via a device. The user then wears a VR headset and experiences a realistic training session within a virtual environment. For example, a scene of the user performing aerobic exercise is recreated in VR.

[0272] The device uses sensors to track the user's movements in the virtual environment in real time and sends that data back to the server. The server analyzes this data, and a generated AI model provides real-time feedback on improving exercise form and appropriate exercise intensity.

[0273] An example of a prompt message would be something like, "What kind of aerobic exercise should the user do to lose 10 kilograms?" This prompt allows the generating AI model to automatically create an appropriate exercise plan, providing the user with a personalized fitness experience.

[0274] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0275] Step 1:

[0276] Users input their physiological information into the device using a wearable device or dedicated application. Specifically, data such as height, weight, age, heart rate, and past exercise history are entered. This input data serves as foundational information used for subsequent analysis and is stored on the device. As output, the entered physiological information is recorded in a database within the device.

[0277] Step 2:

[0278] The terminal sends physiological information obtained from the user to the server. Specifically, the terminal securely encrypts this data and sends it to the server via the internet. In this step, the physiological information arrives at the server as output and is ready for analysis.

[0279] Step 3:

[0280] The server receives the user's physiological information and analyzes it using a generative AI model. Based on the input data, it automatically generates an optimal exercise and nutrition plan. The server uses the AI ​​model to perform data calculations based on the user's health goals and fitness level, and outputs individually customized suggestions. The output of this process is a personalized exercise and nutrition plan tailored to the user.

[0281] Step 4:

[0282] The generated exercise plan is presented to the user through the terminal. The terminal streams information to the VR headset, and the user wears it to experience the training session in the virtual area. Specifically, it includes an exercise scenario provided as visual information, and the user physically moves their body. The output of this step is for the user to start personalized exercises based on feedback within the virtual space.

[0283] Step 5:

[0284] The terminal tracks the user's body movements in real time during the VR session and sends the data back to the server. As input, the user's exercise data is captured by the sensor and sent to the server. As output, the exercise data received by the server serves as the basis for the subsequent feedback process.

[0285] Step 6:

[0286] The server analyzes the received user exercise data, and the AI agent provides real-time feedback. Specifically, it generates improvement advice for form and instructions for adjusting exercise intensity. The output of the analysis based on the data obtained from the input is the adjustment plan provided to the user immediately.

[0287] Step 7:

[0288] The server adjusts the exercise plan and nutrition plan as needed based on feedback and newly acquired physiological information, so that the user can always use the optimal plan. The output of this step is a personalized plan that the user can use again as an updated plan.

[0289] (Application Example 1)

[0290] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0291] In modern society, individual health management is a crucial issue. However, it is difficult for users to obtain personalized and effective exercise and nutritional guidelines, and there is a lack of means to continuously adjust and effectively implement them. Furthermore, user-friendly interactive feedback mechanisms are insufficient. To address this challenge, an efficient method is needed that provides users with real-time, personalized feedback to support the achievement of their health goals.

[0292] 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.

[0293] In this invention, the server includes means for acquiring physiological information and goals from the user; means for automatically generating exercise and nutritional guidelines to achieve health goals based on the acquired physiological information; means for presenting the generated exercise guidelines in a virtual space, detecting the user's movements and providing feedback; means for correcting the user's exercise form and adjusting the exercise intensity in real time through a personal robot; and means for adjusting the exercise and nutritional guidelines based on the latest physiological data and feedback. As a result, the user can receive a personalized and optimal health management plan in real time and efficiently achieve their health goals.

[0294] A "user" refers to an individual who uses the invention for health management.

[0295] "Physiological information" refers to an individual's physical data, such as height, weight, age, heart rate, and exercise history.

[0296] "Health goals" refer to the health status or fitness level that the user wishes to achieve.

[0297] An "exercise guideline" refers to a plan that outlines the type and frequency of exercise necessary to achieve the user's health goals.

[0298] "Nutritional guidelines" refer to the dietary content and nutrient intake plan necessary to achieve the user's health goals.

[0299] "Virtual space" refers to a computer-generated three-dimensional space that users experience using VR technology.

[0300] "Feedback" refers to information that provides real-time evaluations and advice on the user's exercise and activities.

[0301] A "personal robot" refers to a device used in the home that is designed to assist the user and support exercise and health management.

[0302] "Real-time" refers to a state where processing or responses are performed almost instantly.

[0303] "Correcting the shape" refers to adjustments made to correct the user's posture and movements during exercise.

[0304] "Adjusting exercise intensity" refers to appropriately changing the load and intensity of exercise according to the user's physical fitness and abilities.

[0305] To implement this invention, a user, a terminal, and a server are required. First, the user uses a wearable device or a dedicated application to input their physiological information and set health goals they wish to achieve. This information is transmitted to the server via the terminal.

[0306] The server uses cloud services such as AWS Lambda and Google Cloud Functions to process the received physiological information. Next, a generative AI model is used to automatically generate exercise and nutritional guidelines best suited to the user's health goals. This generation process includes data analysis using Python libraries. Furthermore, a plan is created that takes into account the user's fitness level and individual needs.

[0307] The generated exercise guidelines are presented to the user through the terminal, and the user wears a VR headset such as Oculus Quest 2 to experience a realistic training session in the virtual space. The terminal uses sensors to track the user's movements and transmits the data to the server in real time.

[0308] The server analyzes the received data, and the AI agent provides real-time and personalized feedback to the user. This feedback includes advice on form improvement points and exercise intensity. The user can also receive support from a personal robot installed in the home and can continue training.

[0309] As a specific example, when the user sets a goal of "completing a marathon within three months", the AI proposes an aerobic exercise-based plan to cultivate perseverance. According to this plan, the user can receive training under the guidance of the personal robot.

[0310] An example of the prompt text is "The user's goal is to complete a full marathon within three months. Please generate the most suitable training program and nutrition plan for this."

[0311] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0312] Step 1:

[0313] The user uses a wearable device or a dedicated application to input physiological information (e.g., height, weight, heart rate) and health goals. This input information is transmitted to the server through the terminal. JSON or XML is used as the data format, and the health goals and each physiological parameter are extracted from it.

[0314] Step 2:

[0315] The server processes the received physiological information and health goals using AWS Lambda. Based on the input data, it performs data analysis using Python libraries and other tools to generate exercise and nutritional guidelines tailored to the user's fitness level. The generating AI model creates the optimal plan by executing algorithms that take into account past exercise data and current goals. The output is personalized guidelines.

[0316] Step 3:

[0317] The generated exercise guidelines are provided to the user via a terminal. The user wears a VR headset such as an Oculus Quest 2 and starts an exercise session in a virtual space. The terminal tracks the user's movements in the VR space using sensors. The input is movement data from the sensors, and the output is feedback information regarding the user's progress.

[0318] Step 4:

[0319] The server receives user movement data transmitted from the device and performs real-time analysis. The server uses an AI agent to analyze the movement data and immediately provides advice on areas for improvement in form and exercise intensity. This process generates feedback. The output, containing information about the advice, is presented to the user.

[0320] Step 5:

[0321] Users receive further support through a personal robot in their home. The robot provides physical feedback and support to the user based on instructions from a server. The input is specific motion instructions provided by the server, and the robot performs the actions accordingly. The output is an improvement in the user's movement patterns.

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

[0323] This invention is an advanced fitness system that combines VR technology, generative AI, and an emotion engine. The system consists of three main components: the user, the terminal, and the server, enabling the provision of personalized fitness and nutrition plans to individual users.

[0324] Users input physiological data (e.g., height, weight, age) and health goals via a dedicated application or wearable device. This physiological data and goals are transmitted from the device to the server. Furthermore, the emotion engine acquires the user's emotional data and provides this data to the server for use in customizing the fitness plan.

[0325] The server first analyzes the user's physiological data and goals, and then generates an exercise and nutrition plan to achieve those goals. The AI ​​generates the optimal plan automatically based on the user's fitness level, goals, and emotional data. The generated exercise plan includes aerobic exercise and strength training, and its details take into account the user's motivation and stress level.

[0326] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset, enters the virtual environment, and begins exercising. The device's sensors track the user's movements in real time and send the movement data to the server. The server analyzes this data and provides feedback to correct inaccurate form and improve motivation.

[0327] In particular, this system uses an emotion engine to evaluate the user's emotional state in real time and dynamically adjust the exercise plan and feedback. For example, if a user is feeling stressed, the emotion engine adjusts the exercise intensity to promote relaxation or adds exercises aimed at stress relief. Also, if the system determines that the user's motivation is low based on emotional data, it sets exercise goals in small increments to provide encouragement and a sense of accomplishment.

[0328] For example, if a user sets a goal of losing 5 kg through exercise three times a week and is in an emotional state prone to stress during exercise, the server generates a plan that combines light aerobic exercise incorporating relaxation elements with short, highly efficient strength training sessions. As the user exercises in the VR space, the emotion engine provides real-time feedback to alleviate stress and supports training tailored to the user's condition.

[0329] This invention allows users to obtain a more effective and personalized fitness experience based on physiological and emotional data, enabling them to efficiently achieve their health goals.

[0330] The following describes the processing flow.

[0331] Step 1:

[0332] Users input physiological data (height, weight, age, etc.) and health goals via a dedicated app or wearable device. In addition, an emotion engine acquires emotional data from the user's facial expressions and voice. The device then transmits this data to a server.

[0333] Step 2:

[0334] The server analyzes the received physiological data, health goals, and emotional data. Based on this data, the generating AI automatically creates optimal exercise and nutrition plans. In doing so, it takes into account the user's fitness level and emotional state to generate individually optimized plans.

[0335] Step 3:

[0336] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset and begins exercising in the virtual environment. During this time, the device tracks the user's movements using sensors and sends the movement data to the server.

[0337] Step 4:

[0338] The server analyzes tracking data to evaluate the user's exercise form and the accuracy of their movements. Additionally, an emotion engine evaluates the user's emotional state in real time and generates feedback based on that data.

[0339] Step 5:

[0340] The server sends the generated feedback to the device, providing it to the user in real time. This feedback may include instructions for form correction and encouraging messages. The user receives this feedback and adjusts their exercise accordingly.

[0341] Step 6:

[0342] Users regularly input new physiological data and feedback into the system. The terminal sends this data to the server, which reviews the exercise and nutrition plan based on the latest data. The plan is updated as needed, and the latest information is provided to the user.

[0343] These steps allow users to gain a fitness experience that best suits their emotional and physical condition.

[0344] (Example 2)

[0345] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0346] Traditional fitness systems have limitations in providing plans based on individual users' physiological data and goals, and also in providing dynamic feedback that takes into account the user's emotional state. As a result, it has been difficult for users to obtain an optimal fitness experience and achieve their goals effectively.

[0347] 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.

[0348] In this invention, the server includes means for acquiring personal data and goals from the user, means for measuring the user's emotional state using an emotion analysis device, and a knowledge processing device for automatically generating a physical activity plan and a nutrition plan to achieve the goals based on the acquired personal data and emotional state. This enables the provision of a personalized fitness plan adapted to the user's individual circumstances and allows for dynamically adjusted feedback during exercise.

[0349] "Personal data" refers to information that indicates a user's physiological state and health goals, including basic information such as height, weight, and age, as well as set fitness goals.

[0350] "Goals" refer to the health conditions or fitness outcomes that the user wishes to achieve, and specifically include things like weight loss, muscle building, and improved endurance.

[0351] An "emotion analysis device" is a device that determines a user's emotional state based on their facial expressions, voice, and movement patterns.

[0352] "Emotional state" refers to the user's psychological or emotional state, and includes factors such as stress, motivation, and relaxation level.

[0353] A "physical activity plan" is a plan that outlines the schedule and content of exercise created to help a user achieve their health goals.

[0354] A "virtual environment" is a computer-generated simulation environment that users experience using VR headsets or similar devices, enabling them to engage in fitness activities in an immersive way.

[0355] "Feedback" refers to the feedback provided to users during their workouts, including advice for correcting form and improving motivation.

[0356] The following is a description of embodiments for specifically carrying out the present invention.

[0357] Users input their personal data and health goals using a dedicated application or wearable device. This includes basic information such as the user's height, weight, and age, as well as specific health goals such as "aim to lose 5 kilograms by exercising three times a week."

[0358] The terminal's role is to transmit entered personal data and goals to the server. It also uses an emotion analysis device to measure the user's emotional state and provides this information to the server. During this process, sensors within the terminal analyze the user's facial expressions and voice to determine their stress and relaxation levels.

[0359] Based on the received personal data and emotional state, the server uses a generative AI model to automatically generate a physical activity plan and nutrition plan tailored to the user. This AI model devises plans, including endurance activities and muscle-strengthening activities, according to the user's fitness level and emotional fluctuations.

[0360] The generated plan is presented to the user via the device, and the user puts on a VR headset and begins exercising in the virtual environment. This virtual environment is designed to allow users to experience activities such as running in a simulated park. The device tracks the user's movements in real time and transmits the motion data.

[0361] The server analyzes this data and provides suggestions for correction if the operation is inaccurate. It can also dynamically adjust the exercise plan and feedback based on the user's emotional state.

[0362] For example, if a user inputs the prompt "I want to lose 5 kg by exercising three times a week," the generating AI model will suggest a plan that includes light endurance exercises emphasizing relaxation and time-efficient strength training. This process allows the user to enjoy a personalized fitness experience.

[0363] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0364] Step 1:

[0365] Users enter personal data as part of the initial setup through a dedicated application or wearable device. This includes height, weight, age, and health goals. The data entered by the user is collected by the device. The entered personal data is then prepared to be transferred to the server as basic information necessary for subsequent processing steps.

[0366] Step 2:

[0367] The device transmits personal data and health goals collected from the user to the server. In addition, the device uses an emotion analysis device to measure the user's emotional state (stress, relaxation level, etc.) and transmits this data to the server. Here, emotional data obtained from the user's facial expressions and voice indicators is processed to reveal the user's emotional state, and this information is transmitted to the server.

[0368] Step 3:

[0369] The server analyzes the received personal and emotional data and uses a generative AI model to automatically generate a physical activity plan and nutrition plan tailored to the user. Inputs include the user's fitness level, health goals, and current emotional state. The server processes this information and outputs a plan that includes optimal endurance and muscle-strengthening activities for the user.

[0370] Step 4:

[0371] The generated plan is presented to the user via a device. The device uses a VR headset to construct a virtual environment based on the generated plan. The user then enters this virtual environment and begins exercising. Specifically, running in a simulated park and various exercises are visualized.

[0372] Step 5:

[0373] The device's sensors track the user's movements in real time and transmit that data to the server. The input includes specific movement data from the user during exercise. This enables real-time feedback.

[0374] Step 6:

[0375] The server analyzes motion data sent from the terminal to check whether the exercise is being performed correctly. If inappropriate form or motion is detected, it generates feedback for correction and provides it to the user through the terminal. The content of the feedback is also dynamically adjusted based on the user's emotional state.

[0376] Step 7:

[0377] Users receive feedback from the server and modify their exercises as needed. They then use this feedback to improve their next training session, aiming for sustained fitness improvement. Once a user completes a training session, all data is saved for creating their next training plan.

[0378] (Application Example 2)

[0379] 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 as the "terminal".

[0380] In modern society, it is crucial for individuals to effectively utilize fitness and nutrition plans to achieve their health goals. However, these plans are often rigid and lack the dynamic adjustments necessary to consider individual physiological data, emotional states, and even location information. Furthermore, if a fitness plan does not align with a user's real-world environment, it can be difficult for users to maintain motivation. This can hinder effective health management.

[0381] 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.

[0382] In this invention, the server includes means for acquiring physiological data and goals from the user, means for automatically generating exercise and nutrition plans to achieve health goals based on the acquired physiological data, and means for dynamically customizing the fitness plan based on the user's location information and environment. This makes it possible to provide a flexible fitness experience adapted to the individual circumstances of the user.

[0383] "Physiological data" refers to information about an individual's physique, age, and health status, and is used to customize the user's fitness plan.

[0384] "Health goals" refer to specific targets related to the health state or fitness level that an individual wishes to achieve, and serve as a basis for creating a plan.

[0385] An "exercise plan" refers to a specific plan of exercise and training designed to help a user achieve their health goals.

[0386] A "nutrition plan" refers to a plan outlining recommended meals and nutritional intake to help a user achieve their health goals.

[0387] A "virtual environment" refers to a digital space that users experience through digital technology, either by mimicking or uniquely designing a real-world environment.

[0388] "Location information" refers to geographical data that indicates the user's current location, and is used to customize fitness plans.

[0389] "Emotional data" refers to information that reflects the user's emotional state and is used to adjust exercise plans and provide feedback.

[0390] To implement this invention, the user must first install a dedicated application on their smartphone or AR-enabled smart glasses. Upon launching the application and inputting their physiological data and health goals, the data is transmitted from the device to a server. At this point, the server utilizes a generative AI model to automatically generate an exercise plan and nutrition plan to achieve the user's health goals. This generation process also takes into account the user's emotional data and location information.

[0391] The device presents the generated exercise plan to the user in a virtual environment, and the user begins exercising according to the instructions. When the user exercises, the system provides a fitness plan appropriate to the location based on location information. For example, when visiting a park, aerobic exercise suited to that environment will be recommended.

[0392] During exercise, sensors in the device track the user's movements in real time and send the data to a server. The server then analyzes the received movement data and provides feedback to the user. This includes advice on correcting incorrect form and improving motivation.

[0393] This system's emotion engine has the ability to evaluate the user's emotional state in real time and dynamically adjust the exercise plan. For example, if the user is feeling stressed, the exercise content will be changed to something that promotes relaxation. Specifically, if the user has a goal of "continuing to exercise three times a week while relaxing," it will recommend light aerobic exercise in a relaxing environment.

[0394] An example of a prompt to a generative AI model is: "Location: park, User's mood: tired, Please provide a recommended fitness plan."

[0395] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0396] Step 1:

[0397] Users launch a dedicated application on their smartphone or AR-enabled smart glasses and input physiological data (height, weight, age, etc.) and health goals. The input data is sent to the server by the device. The input here consists of the user's physiological data and goals, which become the output data to the server.

[0398] Step 2:

[0399] The server automatically generates optimal exercise and nutrition plans using an AI model based on received physiological data and health goals. It uses the user's physiological data and goals as input data, analyzing and processing this data to output the exercise and nutrition plans. The generated plans include aerobic exercise and strength training, and are customized for each user.

[0400] Step 3:

[0401] The terminal presents the user with an exercise plan received from the server in a virtual environment. The user then uses VR or AR technology to begin exercising according to the plan. In this case, the generated exercise plan is the input data, and the provision of a visual training scene in the virtual environment is the output.

[0402] Step 4:

[0403] When a user exercises, sensors built into the device track the user's movements in real time. The device sends the collected movement data to a server. In this process, the movement data is the input, and the transmission to the server is the output.

[0404] Step 5:

[0405] The server analyzes the received motion data and generates feedback for the user. The input is previously tracked motion data, and the output is feedback information. The feedback includes advice for correcting exercise form and maintaining motivation.

[0406] Step 6:

[0407] The emotion engine evaluates the user's emotional state in real time and dynamically adjusts the exercise plan. The user's emotional data is used as input, and adjustments to exercise intensity and content are output. For example, if the user is feeling stressed, exercises that promote relaxation will be suggested.

[0408] 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.

[0409] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0410] 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.

[0411] [Third Embodiment]

[0412] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0413] 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.

[0414] 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).

[0415] 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.

[0416] 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.

[0417] 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).

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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".

[0424] This invention is a fitness system that combines VR technology and generative AI to efficiently support users in achieving their health goals. The system consists of three main components: the user, the terminal, and the server.

[0425] First, users input physiological data and set health goals they wish to achieve using a wearable device or dedicated application. This physiological data includes height, weight, age, heart rate, and exercise history. This data is transmitted to a server via the device.

[0426] The server performs data analysis based on physiological data and goals submitted by the user. The generating AI automatically creates optimal exercise and nutrition plans. In doing so, the AI ​​considers the user's current fitness level and health goals to ensure the plan is most suitable. Furthermore, the generated plan is adjusted to meet the user's individual needs, resulting in an effective and personalized experience.

[0427] The generated exercise plan is presented to the user in a virtual space via the device. The user wears a VR headset and can experience a realistic training session. The device tracks the user's movements in the VR space using sensors and sends the data back to the server in real time. The server analyzes this data, and an AI agent provides real-time feedback. This feedback includes advice on improving form and exercise intensity.

[0428] For example, if a user sets a goal of "losing 10 kilograms," the server will provide an exercise plan that includes aerobic exercise focused on calorie consumption, as well as a nutrition plan that manages calorie intake. As the user exercises in the VR space, the device tracks their movements, and if any form errors are detected, the server immediately provides instructions to correct them.

[0429] Furthermore, based on newly acquired physiological data and feedback, the server continuously evaluates the user's progress and updates the plan as needed. This ensures that users always have access to the latest, optimized fitness and nutrition plans.

[0430] Thus, this system integrates advanced personalization and real-time feedback functions to provide users with an effective and efficient means of health management.

[0431] The following describes the processing flow.

[0432] Step 1:

[0433] Users input physiological data (height, weight, age, heart rate, etc.) and health goals using a dedicated app or wearable device. The device collects this data and sends it to a server.

[0434] Step 2:

[0435] The server performs data analysis using the received physiological data and health goals. A generating AI analyzes the data and creates an optimized exercise and nutrition plan for the user. In this process, the most suitable type of exercise and nutritional balance for each user is considered.

[0436] Step 3:

[0437] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset and begins training in the virtual space. The training content is visually presented in the virtual space, and the user performs the exercises according to the instructions.

[0438] Step 4:

[0439] The device tracks the user's movements. Sensors do this, monitoring the user's exercise form and the accuracy of their movements. This tracking data is sent to the server in real time.

[0440] Step 5:

[0441] The server analyzes the received tracking data. An AI agent evaluates the user's exercise form and generates corrective instructions if necessary. This includes advice on areas for improvement in form and the properness of the movements.

[0442] Step 6:

[0443] The server generates feedback and provides it to the user in real time via the terminal. The user receives this feedback and makes adjustments to their form during exercise.

[0444] Step 7:

[0445] The user regularly inputs new physical data and reports their progress. The device sends this data to a server, which reviews the exercise and nutrition plan based on the latest data. The plan is updated as needed to continuously provide the user with the most suitable content.

[0446] These steps allow users to receive support in effectively achieving their health goals.

[0447] (Example 1)

[0448] 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."

[0449] Traditional fitness systems struggled to propose efficient plans based on users' physiological data and goals, and real-time feedback and plan adjustments were limited. Furthermore, they lacked personalized health management tools, making it difficult to meet individual user needs.

[0450] 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.

[0451] In this invention, the server includes means for acquiring human body data and goals from the user, means for automatically generating an exercise plan and a nutrition plan to achieve the health goals based on the acquired human body data, and means for providing immediate feedback on the exercise plan via a generated AI model through a display device equipped with a virtual training environment. This makes it possible to provide the user with a highly personalized exercise and nutrition plan.

[0452] A "user" refers to an individual who uses the system to achieve their own health goals.

[0453] "Human body data" refers to numerical information such as height, weight, age, heart rate, and exercise history used to assess the user's health status.

[0454] "Goals" refer to specific health improvement objectives that users attempt to achieve through the system.

[0455] An "exercise plan" refers to a specific schedule or set of activities that provides guidance on the physical activity necessary for a user to achieve their goals.

[0456] A "nutrition plan" refers to specific advice and suggestions that provide users with guidelines for the types of meals and nutrients they need to achieve their goals.

[0457] A "virtual domain" refers to a computer-generated digital space used by users to gain an immersive training experience.

[0458] A "generative AI model" refers to an artificial intelligence-based algorithm that automatically constructs an optimal exercise and nutrition plan based on the user's personal data and goals.

[0459] "Feedback" refers to advice provided to users to help them effectively engage in activities within the virtual realm, including form modifications and motivational suggestions.

[0460] "Resistance exercise" refers to physical activity performed through specific resistance with the aim of strengthening muscles.

[0461] A "display device" is a computer-connected technological device used to provide visual information to a user, and an example of this is a VR headset.

[0462] This system is a fitness platform that integrates virtual reality technology and generative AI to achieve health goals. It consists of three main components: users, terminals, and servers.

[0463] Users input their personal data using wearable devices and dedicated applications, and set health goals they want to achieve. For example, a user might use a smartwatch to record their heart rate and exercise history, and then use a dedicated app to set a goal such as "I want to lose 10 kilograms."

[0464] The terminal sends data obtained from the user to the server. In this case, the terminal uses a secure protocol to transfer data via the internet connection.

[0465] The server uses a generative AI model to analyze data sent from the user. This analysis automatically generates an optimal exercise and nutrition plan for each individual user. In doing so, the AI ​​model analyzes the user's heart rate and exercise history to suggest personalized exercise intensity and menus.

[0466] The generated exercise plan is presented to the user via a device. The user then wears a VR headset and experiences a realistic training session within a virtual environment. For example, a scene of the user performing aerobic exercise is recreated in VR.

[0467] The device uses sensors to track the user's movements in the virtual environment in real time and sends that data back to the server. The server analyzes this data, and a generated AI model provides real-time feedback on improving exercise form and appropriate exercise intensity.

[0468] An example of a prompt message would be something like, "What kind of aerobic exercise should the user do to lose 10 kilograms?" This prompt allows the generating AI model to automatically create an appropriate exercise plan, providing the user with a personalized fitness experience.

[0469] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0470] Step 1:

[0471] Users input their physiological information into the device using a wearable device or dedicated application. Specifically, data such as height, weight, age, heart rate, and past exercise history are entered. This input data serves as foundational information used for subsequent analysis and is stored on the device. As output, the entered physiological information is recorded in a database within the device.

[0472] Step 2:

[0473] The terminal sends physiological information obtained from the user to the server. Specifically, the terminal securely encrypts this data and sends it to the server via the internet. In this step, the physiological information arrives at the server as output and is ready for analysis.

[0474] Step 3:

[0475] The server receives the user's physiological information and analyzes it using a generative AI model. Based on the input data, it automatically generates an optimal exercise and nutrition plan. The server uses the AI ​​model to perform data calculations based on the user's health goals and fitness level, and outputs individually customized suggestions. The output of this process is a personalized exercise and nutrition plan tailored to the user.

[0476] Step 4:

[0477] The generated exercise plan is presented to the user via a terminal. The terminal streams the information to a VR headset, which the user wears to experience a training session in a virtual environment. Specifically, it includes an exercise scenario provided as visual information, which the user then physically moves. The output of this step is for the user to begin a personalized exercise in the virtual space based on the feedback.

[0478] Step 5:

[0479] The device tracks the user's body movements in real time during a VR session and sends the data back to the server. As input, the user's movement data is captured by sensors and sent to the server. As output, the movement data received by the server forms the basis for the subsequent feedback process.

[0480] Step 6:

[0481] The server analyzes the user's exercise data, and the AI ​​agent provides real-time feedback. Specifically, it generates advice on improving form and instructions on adjusting exercise intensity. The output of the analysis, based on the data obtained from the input, is an adjustment suggestion that is immediately provided to the user.

[0482] Step 7:

[0483] Based on feedback and newly acquired physiological information, the server adjusts the exercise and nutrition plans as needed, ensuring that users always have access to the optimal plan. The output of this step is a personalized plan that the user can use again as an updated plan.

[0484] (Application Example 1)

[0485] 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."

[0486] In modern society, individual health management is a crucial issue. However, it is difficult for users to obtain personalized and effective exercise and nutritional guidelines, and there is a lack of means to continuously adjust and effectively implement them. Furthermore, user-friendly interactive feedback mechanisms are insufficient. To address this challenge, an efficient method is needed that provides users with real-time, personalized feedback to support the achievement of their health goals.

[0487] 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.

[0488] In this invention, the server includes means for acquiring physiological information and goals from the user; means for automatically generating exercise and nutritional guidelines to achieve health goals based on the acquired physiological information; means for presenting the generated exercise guidelines in a virtual space, detecting the user's movements and providing feedback; means for correcting the user's exercise form and adjusting the exercise intensity in real time through a personal robot; and means for adjusting the exercise and nutritional guidelines based on the latest physiological data and feedback. As a result, the user can receive a personalized and optimal health management plan in real time and efficiently achieve their health goals.

[0489] A "user" refers to an individual who uses the invention for health management.

[0490] "Physiological information" refers to an individual's physical data, such as height, weight, age, heart rate, and exercise history.

[0491] "Health goals" refer to the health status or fitness level that the user wishes to achieve.

[0492] An "exercise guideline" refers to a plan that outlines the type and frequency of exercise necessary to achieve the user's health goals.

[0493] "Nutritional guidelines" refer to the dietary content and nutrient intake plan necessary to achieve the user's health goals.

[0494] "Virtual space" refers to a computer-generated three-dimensional space that users experience using VR technology.

[0495] "Feedback" refers to information that provides real-time evaluations and advice on the user's exercise and activities.

[0496] A "personal robot" refers to a device used in the home that is designed to assist the user and support exercise and health management.

[0497] "Real-time" refers to a state where processing or responses are performed almost instantly.

[0498] "Correcting the shape" refers to adjustments made to correct the user's posture and movements during exercise.

[0499] "Adjusting exercise intensity" refers to appropriately changing the load and intensity of exercise according to the user's physical fitness and abilities.

[0500] To implement this invention, a user, a terminal, and a server are required. First, the user uses a wearable device or a dedicated application to input their physiological information and set health goals they wish to achieve. This information is transmitted to the server via the terminal.

[0501] The server uses cloud services such as AWS Lambda and Google Cloud Functions to process the received physiological information. Next, a generative AI model is used to automatically generate exercise and nutritional guidelines best suited to the user's health goals. This generation process includes data analysis using Python libraries. Furthermore, a plan is created that takes into account the user's fitness level and individual needs.

[0502] The generated exercise guidelines are presented to the user via a terminal, and the user wears a VR headset such as the Oculus Quest 2 to experience a realistic training session in a virtual space. The terminal tracks the user's movements with sensors and transmits that data to the server in real time.

[0503] The server analyzes the received data, and an AI agent provides the user with real-time, personalized feedback. This feedback includes advice on improving form and exercise intensity. Users can also receive support from a personal robot installed in their home, enabling them to continue their training.

[0504] For example, if a user sets a goal of "completing a marathon within three months," the AI ​​will propose a plan primarily focused on aerobic exercise to cultivate perseverance. Following this plan, the user can train under the guidance of a personal robot.

[0505] An example of a prompt message would be: "The user's goal is to complete a full marathon within three months. Please generate the optimal training program and nutrition plan for this purpose."

[0506] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0507] Step 1:

[0508] Users input physiological information (e.g., height, weight, heart rate) and health goals using wearable devices or dedicated applications. This input information is transmitted to a server via the terminal. JSON or XML is used as the data format, from which health goals and individual physiological parameters are extracted.

[0509] Step 2:

[0510] The server processes the received physiological information and health goals using AWS Lambda. Based on the input data, it performs data analysis using Python libraries and other tools to generate exercise and nutritional guidelines tailored to the user's fitness level. The generating AI model creates the optimal plan by executing algorithms that take into account past exercise data and current goals. The output is personalized guidelines.

[0511] Step 3:

[0512] The generated exercise guidelines are provided to the user via a terminal. The user wears a VR headset such as an Oculus Quest 2 and starts an exercise session in a virtual space. The terminal tracks the user's movements in the VR space using sensors. The input is movement data from the sensors, and the output is feedback information regarding the user's progress.

[0513] Step 4:

[0514] The server receives user movement data transmitted from the device and performs real-time analysis. The server uses an AI agent to analyze the movement data and immediately provides advice on areas for improvement in form and exercise intensity. This process generates feedback. The output, containing information about the advice, is presented to the user.

[0515] Step 5:

[0516] Users receive further support through a personal robot in their home. The robot provides physical feedback and support to the user based on instructions from a server. The input is specific motion instructions provided by the server, and the robot performs the actions accordingly. The output is an improvement in the user's movement patterns.

[0517] 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.

[0518] This invention is an advanced fitness system that combines VR technology, generative AI, and an emotion engine. The system consists of three main components: the user, the terminal, and the server, enabling the provision of personalized fitness and nutrition plans to individual users.

[0519] Users input physiological data (e.g., height, weight, age) and health goals via a dedicated application or wearable device. This physiological data and goals are transmitted from the device to the server. Furthermore, the emotion engine acquires the user's emotional data and provides this data to the server for use in customizing the fitness plan.

[0520] The server first analyzes the user's physiological data and goals, and then generates an exercise and nutrition plan to achieve those goals. The AI ​​generates the optimal plan automatically based on the user's fitness level, goals, and emotional data. The generated exercise plan includes aerobic exercise and strength training, and its details take into account the user's motivation and stress level.

[0521] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset, enters the virtual environment, and begins exercising. The device's sensors track the user's movements in real time and send the movement data to the server. The server analyzes this data and provides feedback to correct inaccurate form and improve motivation.

[0522] In particular, this system uses an emotion engine to evaluate the user's emotional state in real time and dynamically adjust the exercise plan and feedback. For example, if a user is feeling stressed, the emotion engine adjusts the exercise intensity to promote relaxation or adds exercises aimed at stress relief. Also, if the system determines that the user's motivation is low based on emotional data, it sets exercise goals in small increments to provide encouragement and a sense of accomplishment.

[0523] For example, if a user sets a goal of losing 5 kg through exercise three times a week and is in an emotional state prone to stress during exercise, the server generates a plan that combines light aerobic exercise incorporating relaxation elements with short, highly efficient strength training sessions. As the user exercises in the VR space, the emotion engine provides real-time feedback to alleviate stress and supports training tailored to the user's condition.

[0524] This invention allows users to obtain a more effective and personalized fitness experience based on physiological and emotional data, enabling them to efficiently achieve their health goals.

[0525] The following describes the processing flow.

[0526] Step 1:

[0527] Users input physiological data (height, weight, age, etc.) and health goals via a dedicated app or wearable device. In addition, an emotion engine acquires emotional data from the user's facial expressions and voice. The device then transmits this data to a server.

[0528] Step 2:

[0529] The server analyzes the received physiological data, health goals, and emotional data. Based on this data, the generating AI automatically creates optimal exercise and nutrition plans. In doing so, it takes into account the user's fitness level and emotional state to generate individually optimized plans.

[0530] Step 3:

[0531] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset and begins exercising in the virtual environment. During this time, the device tracks the user's movements using sensors and sends the movement data to the server.

[0532] Step 4:

[0533] The server analyzes tracking data to evaluate the user's exercise form and the accuracy of their movements. Additionally, an emotion engine evaluates the user's emotional state in real time and generates feedback based on that data.

[0534] Step 5:

[0535] The server sends the generated feedback to the device, providing it to the user in real time. This feedback may include instructions for form correction and encouraging messages. The user receives this feedback and adjusts their exercise accordingly.

[0536] Step 6:

[0537] Users regularly input new physiological data and feedback into the system. The terminal sends this data to the server, which reviews the exercise and nutrition plan based on the latest data. The plan is updated as needed, and the latest information is provided to the user.

[0538] These steps allow users to gain a fitness experience that best suits their emotional and physical condition.

[0539] (Example 2)

[0540] 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."

[0541] Traditional fitness systems have limitations in providing plans based on individual users' physiological data and goals, and also in providing dynamic feedback that takes into account the user's emotional state. As a result, it has been difficult for users to obtain an optimal fitness experience and achieve their goals effectively.

[0542] 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.

[0543] In this invention, the server includes means for acquiring personal data and goals from the user, means for measuring the user's emotional state using an emotion analysis device, and a knowledge processing device for automatically generating a physical activity plan and a nutrition plan to achieve the goals based on the acquired personal data and emotional state. This enables the provision of a personalized fitness plan adapted to the user's individual circumstances and allows for dynamically adjusted feedback during exercise.

[0544] "Personal data" refers to information that indicates a user's physiological state and health goals, including basic information such as height, weight, and age, as well as set fitness goals.

[0545] "Goals" refer to the health conditions or fitness outcomes that the user wishes to achieve, and specifically include things like weight loss, muscle building, and improved endurance.

[0546] An "emotion analysis device" is a device that determines a user's emotional state based on their facial expressions, voice, and movement patterns.

[0547] "Emotional state" refers to the user's psychological or emotional state, and includes factors such as stress, motivation, and relaxation level.

[0548] A "physical activity plan" is a plan that outlines the schedule and content of exercise created to help a user achieve their health goals.

[0549] A "virtual environment" is a computer-generated simulation environment that users experience using VR headsets or similar devices, enabling them to engage in fitness activities in an immersive way.

[0550] "Feedback" refers to the feedback provided to users during their workouts, including advice for correcting form and improving motivation.

[0551] The following is a description of embodiments for specifically carrying out the present invention.

[0552] Users input their personal data and health goals using a dedicated application or wearable device. This includes basic information such as the user's height, weight, and age, as well as specific health goals such as "aim to lose 5 kilograms by exercising three times a week."

[0553] The terminal's role is to transmit entered personal data and goals to the server. It also uses an emotion analysis device to measure the user's emotional state and provides this information to the server. During this process, sensors within the terminal analyze the user's facial expressions and voice to determine their stress and relaxation levels.

[0554] Based on the received personal data and emotional state, the server uses a generative AI model to automatically generate a physical activity plan and nutrition plan tailored to the user. This AI model devises plans, including endurance activities and muscle-strengthening activities, according to the user's fitness level and emotional fluctuations.

[0555] The generated plan is presented to the user via the device, and the user puts on a VR headset and begins exercising in the virtual environment. This virtual environment is designed to allow users to experience activities such as running in a simulated park. The device tracks the user's movements in real time and transmits the motion data.

[0556] The server analyzes this data and provides suggestions for correction if the operation is inaccurate. It can also dynamically adjust the exercise plan and feedback based on the user's emotional state.

[0557] For example, if a user inputs the prompt "I want to lose 5 kg by exercising three times a week," the generating AI model will suggest a plan that includes light endurance exercises emphasizing relaxation and time-efficient strength training. This process allows the user to enjoy a personalized fitness experience.

[0558] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0559] Step 1:

[0560] Users enter personal data as part of the initial setup through a dedicated application or wearable device. This includes height, weight, age, and health goals. The data entered by the user is collected by the device. The entered personal data is then prepared to be transferred to the server as basic information necessary for subsequent processing steps.

[0561] Step 2:

[0562] The device transmits personal data and health goals collected from the user to the server. In addition, the device uses an emotion analysis device to measure the user's emotional state (stress, relaxation level, etc.) and transmits this data to the server. Here, emotional data obtained from the user's facial expressions and voice indicators is processed to reveal the user's emotional state, and this information is transmitted to the server.

[0563] Step 3:

[0564] The server analyzes the received personal and emotional data and uses a generative AI model to automatically generate a physical activity plan and nutrition plan tailored to the user. Inputs include the user's fitness level, health goals, and current emotional state. The server processes this information and outputs a plan that includes optimal endurance and muscle-strengthening activities for the user.

[0565] Step 4:

[0566] The generated plan is presented to the user via a device. The device uses a VR headset to construct a virtual environment based on the generated plan. The user then enters this virtual environment and begins exercising. Specifically, running in a simulated park and various exercises are visualized.

[0567] Step 5:

[0568] The device's sensors track the user's movements in real time and transmit that data to the server. The input includes specific movement data from the user during exercise. This enables real-time feedback.

[0569] Step 6:

[0570] The server analyzes motion data sent from the terminal to check whether the exercise is being performed correctly. If inappropriate form or motion is detected, it generates feedback for correction and provides it to the user through the terminal. The content of the feedback is also dynamically adjusted based on the user's emotional state.

[0571] Step 7:

[0572] Users receive feedback from the server and modify their exercises as needed. They then use this feedback to improve their next training session, aiming for sustained fitness improvement. Once a user completes a training session, all data is saved for creating their next training plan.

[0573] (Application Example 2)

[0574] 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."

[0575] In modern society, it is crucial for individuals to effectively utilize fitness and nutrition plans to achieve their health goals. However, these plans are often rigid and lack the dynamic adjustments necessary to consider individual physiological data, emotional states, and even location information. Furthermore, if a fitness plan does not align with a user's real-world environment, it can be difficult for users to maintain motivation. This can hinder effective health management.

[0576] 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.

[0577] In this invention, the server includes means for acquiring physiological data and goals from the user, means for automatically generating exercise and nutrition plans to achieve health goals based on the acquired physiological data, and means for dynamically customizing the fitness plan based on the user's location information and environment. This makes it possible to provide a flexible fitness experience adapted to the individual circumstances of the user.

[0578] "Physiological data" refers to information about an individual's physique, age, and health status, and is used to customize the user's fitness plan.

[0579] "Health goals" refer to specific targets related to the health state or fitness level that an individual wishes to achieve, and serve as a basis for creating a plan.

[0580] An "exercise plan" refers to a specific plan of exercise and training designed to help a user achieve their health goals.

[0581] A "nutrition plan" refers to a plan outlining recommended meals and nutritional intake to help a user achieve their health goals.

[0582] A "virtual environment" refers to a digital space that users experience through digital technology, either by mimicking or uniquely designing a real-world environment.

[0583] "Location information" refers to geographical data that indicates the user's current location, and is used to customize fitness plans.

[0584] "Emotional data" refers to information that reflects the user's emotional state and is used to adjust exercise plans and provide feedback.

[0585] To implement this invention, the user must first install a dedicated application on their smartphone or AR-enabled smart glasses. Upon launching the application and inputting their physiological data and health goals, the data is transmitted from the device to a server. At this point, the server utilizes a generative AI model to automatically generate an exercise plan and nutrition plan to achieve the user's health goals. This generation process also takes into account the user's emotional data and location information.

[0586] The device presents the generated exercise plan to the user in a virtual environment, and the user begins exercising according to the instructions. When the user exercises, the system provides a fitness plan appropriate to the location based on location information. For example, when visiting a park, aerobic exercise suited to that environment will be recommended.

[0587] During exercise, sensors in the device track the user's movements in real time and send the data to a server. The server then analyzes the received movement data and provides feedback to the user. This includes advice on correcting incorrect form and improving motivation.

[0588] This system's emotion engine has the ability to evaluate the user's emotional state in real time and dynamically adjust the exercise plan. For example, if the user is feeling stressed, the exercise content will be changed to something that promotes relaxation. Specifically, if the user has a goal of "continuing to exercise three times a week while relaxing," it will recommend light aerobic exercise in a relaxing environment.

[0589] An example of a prompt to a generative AI model is: "Location: park, User's mood: tired, Please provide a recommended fitness plan."

[0590] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0591] Step 1:

[0592] Users launch a dedicated application on their smartphone or AR-enabled smart glasses and input physiological data (height, weight, age, etc.) and health goals. The input data is sent to the server by the device. The input here consists of the user's physiological data and goals, which become the output data to the server.

[0593] Step 2:

[0594] The server automatically generates optimal exercise and nutrition plans using an AI model based on received physiological data and health goals. It uses the user's physiological data and goals as input data, analyzing and processing this data to output the exercise and nutrition plans. The generated plans include aerobic exercise and strength training, and are customized for each user.

[0595] Step 3:

[0596] The terminal presents the user with an exercise plan received from the server in a virtual environment. The user then uses VR or AR technology to begin exercising according to the plan. In this case, the generated exercise plan is the input data, and the provision of a visual training scene in the virtual environment is the output.

[0597] Step 4:

[0598] When a user exercises, sensors built into the device track the user's movements in real time. The device sends the collected movement data to a server. In this process, the movement data is the input, and the transmission to the server is the output.

[0599] Step 5:

[0600] The server analyzes the received motion data and generates feedback for the user. The input is previously tracked motion data, and the output is feedback information. The feedback includes advice for correcting exercise form and maintaining motivation.

[0601] Step 6:

[0602] The emotion engine evaluates the user's emotional state in real time and dynamically adjusts the exercise plan. The user's emotional data is used as input, and adjustments to exercise intensity and content are output. For example, if the user is feeling stressed, exercises that promote relaxation will be suggested.

[0603] 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.

[0604] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0605] 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.

[0606] [Fourth Embodiment]

[0607] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0608] 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.

[0609] 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).

[0610] 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.

[0611] 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.

[0612] 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).

[0613] 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.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] 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.

[0618] 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.

[0619] 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".

[0620] This invention is a fitness system that combines VR technology and generative AI to efficiently support users in achieving their health goals. The system consists of three main components: the user, the terminal, and the server.

[0621] First, users input physiological data and set health goals they wish to achieve using a wearable device or dedicated application. This physiological data includes height, weight, age, heart rate, and exercise history. This data is transmitted to a server via the device.

[0622] The server performs data analysis based on physiological data and goals submitted by the user. The generating AI automatically creates optimal exercise and nutrition plans. In doing so, the AI ​​considers the user's current fitness level and health goals to ensure the plan is most suitable. Furthermore, the generated plan is adjusted to meet the user's individual needs, resulting in an effective and personalized experience.

[0623] The generated exercise plan is presented to the user in a virtual space via the device. The user wears a VR headset and can experience a realistic training session. The device tracks the user's movements in the VR space using sensors and sends the data back to the server in real time. The server analyzes this data, and an AI agent provides real-time feedback. This feedback includes advice on improving form and exercise intensity.

[0624] For example, if a user sets a goal of "losing 10 kilograms," the server will provide an exercise plan that includes aerobic exercise focused on calorie consumption, as well as a nutrition plan that manages calorie intake. As the user exercises in the VR space, the device tracks their movements, and if any form errors are detected, the server immediately provides instructions to correct them.

[0625] Furthermore, based on newly acquired physiological data and feedback, the server continuously evaluates the user's progress and updates the plan as needed. This ensures that users always have access to the latest, optimized fitness and nutrition plans.

[0626] Thus, this system integrates advanced personalization and real-time feedback functions to provide users with an effective and efficient means of health management.

[0627] The following describes the processing flow.

[0628] Step 1:

[0629] Users input physiological data (height, weight, age, heart rate, etc.) and health goals using a dedicated app or wearable device. The device collects this data and sends it to a server.

[0630] Step 2:

[0631] The server performs data analysis using the received physiological data and health goals. A generating AI analyzes the data and creates an optimized exercise and nutrition plan for the user. In this process, the most suitable type of exercise and nutritional balance for each user is considered.

[0632] Step 3:

[0633] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset and begins training in the virtual space. The training content is visually presented in the virtual space, and the user performs the exercises according to the instructions.

[0634] Step 4:

[0635] The device tracks the user's movements. Sensors do this, monitoring the user's exercise form and the accuracy of their movements. This tracking data is sent to the server in real time.

[0636] Step 5:

[0637] The server analyzes the received tracking data. An AI agent evaluates the user's exercise form and generates corrective instructions if necessary. This includes advice on areas for improvement in form and the properness of the movements.

[0638] Step 6:

[0639] The server generates feedback and provides it to the user in real time via the terminal. The user receives this feedback and makes adjustments to their form during exercise.

[0640] Step 7:

[0641] The user regularly inputs new physical data and reports their progress. The device sends this data to a server, which reviews the exercise and nutrition plan based on the latest data. The plan is updated as needed to continuously provide the user with the most suitable content.

[0642] These steps allow users to receive support in effectively achieving their health goals.

[0643] (Example 1)

[0644] 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".

[0645] Traditional fitness systems struggled to propose efficient plans based on users' physiological data and goals, and real-time feedback and plan adjustments were limited. Furthermore, they lacked personalized health management tools, making it difficult to meet individual user needs.

[0646] 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.

[0647] In this invention, the server includes means for acquiring human body data and goals from the user, means for automatically generating an exercise plan and a nutrition plan to achieve the health goals based on the acquired human body data, and means for providing immediate feedback on the exercise plan via a generated AI model through a display device equipped with a virtual training environment. This makes it possible to provide the user with a highly personalized exercise and nutrition plan.

[0648] A "user" refers to an individual who uses the system to achieve their own health goals.

[0649] "Human body data" refers to numerical information such as height, weight, age, heart rate, and exercise history used to assess the user's health status.

[0650] "Goals" refer to specific health improvement objectives that users attempt to achieve through the system.

[0651] An "exercise plan" refers to a specific schedule or set of activities that provides guidance on the physical activity necessary for a user to achieve their goals.

[0652] A "nutrition plan" refers to specific advice and suggestions that provide users with guidelines for the types of meals and nutrients they need to achieve their goals.

[0653] A "virtual domain" refers to a computer-generated digital space used by users to gain an immersive training experience.

[0654] A "generative AI model" refers to an artificial intelligence-based algorithm that automatically constructs an optimal exercise and nutrition plan based on the user's personal data and goals.

[0655] "Feedback" refers to advice provided to users to help them effectively engage in activities within the virtual realm, including form modifications and motivational suggestions.

[0656] "Resistance exercise" refers to physical activity performed through specific resistance with the aim of strengthening muscles.

[0657] A "display device" is a computer-connected technological device used to provide visual information to a user, and an example of this is a VR headset.

[0658] This system is a fitness platform that integrates virtual reality technology and generative AI to achieve health goals. It consists of three main components: users, terminals, and servers.

[0659] Users input their personal data using wearable devices and dedicated applications, and set health goals they want to achieve. For example, a user might use a smartwatch to record their heart rate and exercise history, and then use a dedicated app to set a goal such as "I want to lose 10 kilograms."

[0660] The terminal sends data obtained from the user to the server. In this case, the terminal uses a secure protocol to transfer data via the internet connection.

[0661] The server uses a generative AI model to analyze data sent from the user. This analysis automatically generates an optimal exercise and nutrition plan for each individual user. In doing so, the AI ​​model analyzes the user's heart rate and exercise history to suggest personalized exercise intensity and menus.

[0662] The generated exercise plan is presented to the user via a device. The user then wears a VR headset and experiences a realistic training session within a virtual environment. For example, a scene of the user performing aerobic exercise is recreated in VR.

[0663] The device uses sensors to track the user's movements in the virtual environment in real time and sends that data back to the server. The server analyzes this data, and a generated AI model provides real-time feedback on improving exercise form and appropriate exercise intensity.

[0664] An example of a prompt message would be something like, "What kind of aerobic exercise should the user do to lose 10 kilograms?" This prompt allows the generating AI model to automatically create an appropriate exercise plan, providing the user with a personalized fitness experience.

[0665] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0666] Step 1:

[0667] Users input their physiological information into the device using a wearable device or dedicated application. Specifically, data such as height, weight, age, heart rate, and past exercise history are entered. This input data serves as foundational information used for subsequent analysis and is stored on the device. As output, the entered physiological information is recorded in a database within the device.

[0668] Step 2:

[0669] The terminal sends physiological information obtained from the user to the server. Specifically, the terminal securely encrypts this data and sends it to the server via the internet. In this step, the physiological information arrives at the server as output and is ready for analysis.

[0670] Step 3:

[0671] The server receives the user's physiological information and analyzes it using a generative AI model. Based on the input data, it automatically generates an optimal exercise and nutrition plan. The server uses the AI ​​model to perform data calculations based on the user's health goals and fitness level, and outputs individually customized suggestions. The output of this process is a personalized exercise and nutrition plan tailored to the user.

[0672] Step 4:

[0673] The generated exercise plan is presented to the user via a terminal. The terminal streams the information to a VR headset, which the user wears to experience a training session in a virtual environment. Specifically, it includes an exercise scenario provided as visual information, which the user then physically moves. The output of this step is for the user to begin a personalized exercise in the virtual space based on the feedback.

[0674] Step 5:

[0675] The device tracks the user's body movements in real time during a VR session and sends the data back to the server. As input, the user's movement data is captured by sensors and sent to the server. As output, the movement data received by the server forms the basis for the subsequent feedback process.

[0676] Step 6:

[0677] The server analyzes the user's exercise data, and the AI ​​agent provides real-time feedback. Specifically, it generates advice on improving form and instructions on adjusting exercise intensity. The output of the analysis, based on the data obtained from the input, is an adjustment suggestion that is immediately provided to the user.

[0678] Step 7:

[0679] Based on feedback and newly acquired physiological information, the server adjusts the exercise and nutrition plans as needed, ensuring that users always have access to the optimal plan. The output of this step is a personalized plan that the user can use again as an updated plan.

[0680] (Application Example 1)

[0681] 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".

[0682] In modern society, individual health management is a crucial issue. However, it is difficult for users to obtain personalized and effective exercise and nutritional guidelines, and there is a lack of means to continuously adjust and effectively implement them. Furthermore, user-friendly interactive feedback mechanisms are insufficient. To address this challenge, an efficient method is needed that provides users with real-time, personalized feedback to support the achievement of their health goals.

[0683] 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.

[0684] In this invention, the server includes means for acquiring physiological information and goals from the user; means for automatically generating exercise and nutritional guidelines to achieve health goals based on the acquired physiological information; means for presenting the generated exercise guidelines in a virtual space, detecting the user's movements and providing feedback; means for correcting the user's exercise form and adjusting the exercise intensity in real time through a personal robot; and means for adjusting the exercise and nutritional guidelines based on the latest physiological data and feedback. As a result, the user can receive a personalized and optimal health management plan in real time and efficiently achieve their health goals.

[0685] A "user" refers to an individual who uses the invention for health management.

[0686] "Physiological information" refers to an individual's physical data, such as height, weight, age, heart rate, and exercise history.

[0687] "Health goals" refer to the health status or fitness level that the user wishes to achieve.

[0688] An "exercise guideline" refers to a plan that outlines the type and frequency of exercise necessary to achieve the user's health goals.

[0689] "Nutritional guidelines" refer to the dietary content and nutrient intake plan necessary to achieve the user's health goals.

[0690] "Virtual space" refers to a computer-generated three-dimensional space that users experience using VR technology.

[0691] "Feedback" refers to information that provides real-time evaluations and advice on the user's exercise and activities.

[0692] A "personal robot" refers to a device used in the home that is designed to assist the user and support exercise and health management.

[0693] "Real-time" refers to a state where processing or responses are performed almost instantly.

[0694] "Correcting the shape" refers to adjustments made to correct the user's posture and movements during exercise.

[0695] "Adjusting exercise intensity" refers to appropriately changing the load and intensity of exercise according to the user's physical fitness and abilities.

[0696] To implement this invention, a user, a terminal, and a server are required. First, the user uses a wearable device or a dedicated application to input their physiological information and set health goals they wish to achieve. This information is transmitted to the server via the terminal.

[0697] The server uses cloud services such as AWS Lambda and Google Cloud Functions to process the received physiological information. Next, a generative AI model is used to automatically generate exercise and nutritional guidelines best suited to the user's health goals. This generation process includes data analysis using Python libraries. Furthermore, a plan is created that takes into account the user's fitness level and individual needs.

[0698] The generated exercise guidelines are presented to the user via a terminal, and the user wears a VR headset such as the Oculus Quest 2 to experience a realistic training session in a virtual space. The terminal tracks the user's movements with sensors and transmits that data to the server in real time.

[0699] The server analyzes the received data, and an AI agent provides the user with real-time, personalized feedback. This feedback includes advice on improving form and exercise intensity. Users can also receive support from a personal robot installed in their home, enabling them to continue their training.

[0700] For example, if a user sets a goal of "completing a marathon within three months," the AI ​​will propose a plan primarily focused on aerobic exercise to cultivate perseverance. Following this plan, the user can train under the guidance of a personal robot.

[0701] An example of a prompt message would be: "The user's goal is to complete a full marathon within three months. Please generate the optimal training program and nutrition plan for this purpose."

[0702] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0703] Step 1:

[0704] Users input physiological information (e.g., height, weight, heart rate) and health goals using wearable devices or dedicated applications. This input information is transmitted to a server via the terminal. JSON or XML is used as the data format, from which health goals and individual physiological parameters are extracted.

[0705] Step 2:

[0706] The server processes the received physiological information and health goals using AWS Lambda. Based on the input data, it performs data analysis using Python libraries and other tools to generate exercise and nutritional guidelines tailored to the user's fitness level. The generating AI model creates the optimal plan by executing algorithms that take into account past exercise data and current goals. The output is personalized guidelines.

[0707] Step 3:

[0708] The generated exercise guidelines are provided to the user via a terminal. The user wears a VR headset such as an Oculus Quest 2 and starts an exercise session in a virtual space. The terminal tracks the user's movements in the VR space using sensors. The input is movement data from the sensors, and the output is feedback information regarding the user's progress.

[0709] Step 4:

[0710] The server receives user movement data transmitted from the device and performs real-time analysis. The server uses an AI agent to analyze the movement data and immediately provides advice on areas for improvement in form and exercise intensity. This process generates feedback. The output, containing information about the advice, is presented to the user.

[0711] Step 5:

[0712] Users receive further support through a personal robot in their home. The robot provides physical feedback and support to the user based on instructions from a server. The input is specific motion instructions provided by the server, and the robot performs the actions accordingly. The output is an improvement in the user's movement patterns.

[0713] 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.

[0714] This invention is an advanced fitness system that combines VR technology, generative AI, and an emotion engine. The system consists of three main components: the user, the terminal, and the server, enabling the provision of personalized fitness and nutrition plans to individual users.

[0715] Users input physiological data (e.g., height, weight, age) and health goals via a dedicated application or wearable device. This physiological data and goals are transmitted from the device to the server. Furthermore, the emotion engine acquires the user's emotional data and provides this data to the server for use in customizing the fitness plan.

[0716] The server first analyzes the user's physiological data and goals, and then generates an exercise and nutrition plan to achieve those goals. The AI ​​generates the optimal plan automatically based on the user's fitness level, goals, and emotional data. The generated exercise plan includes aerobic exercise and strength training, and its details take into account the user's motivation and stress level.

[0717] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset, enters the virtual environment, and begins exercising. The device's sensors track the user's movements in real time and send the movement data to the server. The server analyzes this data and provides feedback to correct inaccurate form and improve motivation.

[0718] In particular, this system uses an emotion engine to evaluate the user's emotional state in real time and dynamically adjust the exercise plan and feedback. For example, if a user is feeling stressed, the emotion engine adjusts the exercise intensity to promote relaxation or adds exercises aimed at stress relief. Also, if the system determines that the user's motivation is low based on emotional data, it sets exercise goals in small increments to provide encouragement and a sense of accomplishment.

[0719] For example, if a user sets a goal of losing 5 kg through exercise three times a week and is in an emotional state prone to stress during exercise, the server generates a plan that combines light aerobic exercise incorporating relaxation elements with short, highly efficient strength training sessions. As the user exercises in the VR space, the emotion engine provides real-time feedback to alleviate stress and supports training tailored to the user's condition.

[0720] This invention allows users to obtain a more effective and personalized fitness experience based on physiological and emotional data, enabling them to efficiently achieve their health goals.

[0721] The following describes the processing flow.

[0722] Step 1:

[0723] Users input physiological data (height, weight, age, etc.) and health goals via a dedicated app or wearable device. In addition, an emotion engine acquires emotional data from the user's facial expressions and voice. The device then transmits this data to a server.

[0724] Step 2:

[0725] The server analyzes the received physiological data, health goals, and emotional data. Based on this data, the generating AI automatically creates optimal exercise and nutrition plans. In doing so, it takes into account the user's fitness level and emotional state to generate individually optimized plans.

[0726] Step 3:

[0727] The device presents the generated exercise plan to the user in a VR space. The user puts on a VR headset and begins exercising in the virtual environment. During this time, the device tracks the user's movements using sensors and sends the movement data to the server.

[0728] Step 4:

[0729] The server analyzes tracking data to evaluate the user's exercise form and the accuracy of their movements. Additionally, an emotion engine evaluates the user's emotional state in real time and generates feedback based on that data.

[0730] Step 5:

[0731] The server sends the generated feedback to the device, providing it to the user in real time. This feedback may include instructions for form correction and encouraging messages. The user receives this feedback and adjusts their exercise accordingly.

[0732] Step 6:

[0733] Users regularly input new physiological data and feedback into the system. The terminal sends this data to the server, which reviews the exercise and nutrition plan based on the latest data. The plan is updated as needed, and the latest information is provided to the user.

[0734] These steps allow users to gain a fitness experience that best suits their emotional and physical condition.

[0735] (Example 2)

[0736] 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".

[0737] Traditional fitness systems have limitations in providing plans based on individual users' physiological data and goals, and also in providing dynamic feedback that takes into account the user's emotional state. As a result, it has been difficult for users to obtain an optimal fitness experience and achieve their goals effectively.

[0738] 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.

[0739] In this invention, the server includes means for acquiring personal data and goals from the user, means for measuring the user's emotional state using an emotion analysis device, and a knowledge processing device for automatically generating a physical activity plan and a nutrition plan to achieve the goals based on the acquired personal data and emotional state. This enables the provision of a personalized fitness plan adapted to the user's individual circumstances and allows for dynamically adjusted feedback during exercise.

[0740] "Personal data" refers to information that indicates a user's physiological state and health goals, including basic information such as height, weight, and age, as well as set fitness goals.

[0741] "Goals" refer to the health conditions or fitness outcomes that the user wishes to achieve, and specifically include things like weight loss, muscle building, and improved endurance.

[0742] An "emotion analysis device" is a device that determines a user's emotional state based on their facial expressions, voice, and movement patterns.

[0743] "Emotional state" refers to the user's psychological or emotional state, and includes factors such as stress, motivation, and relaxation level.

[0744] A "physical activity plan" is a plan that outlines the schedule and content of exercise created to help a user achieve their health goals.

[0745] A "virtual environment" is a computer-generated simulation environment that users experience using VR headsets or similar devices, enabling them to engage in fitness activities in an immersive way.

[0746] "Feedback" refers to the feedback provided to users during their workouts, including advice for correcting form and improving motivation.

[0747] The following is a description of embodiments for specifically carrying out the present invention.

[0748] Users input their personal data and health goals using a dedicated application or wearable device. This includes basic information such as the user's height, weight, and age, as well as specific health goals such as "aim to lose 5 kilograms by exercising three times a week."

[0749] The terminal's role is to transmit entered personal data and goals to the server. It also uses an emotion analysis device to measure the user's emotional state and provides this information to the server. During this process, sensors within the terminal analyze the user's facial expressions and voice to determine their stress and relaxation levels.

[0750] Based on the received personal data and emotional state, the server uses a generative AI model to automatically generate a physical activity plan and nutrition plan tailored to the user. This AI model devises plans, including endurance activities and muscle-strengthening activities, according to the user's fitness level and emotional fluctuations.

[0751] The generated plan is presented to the user via the device, and the user puts on a VR headset and begins exercising in the virtual environment. This virtual environment is designed to allow users to experience activities such as running in a simulated park. The device tracks the user's movements in real time and transmits the motion data.

[0752] The server analyzes this data and provides suggestions for correction if the operation is inaccurate. It can also dynamically adjust the exercise plan and feedback based on the user's emotional state.

[0753] For example, if a user inputs the prompt "I want to lose 5 kg by exercising three times a week," the generating AI model will suggest a plan that includes light endurance exercises emphasizing relaxation and time-efficient strength training. This process allows the user to enjoy a personalized fitness experience.

[0754] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0755] Step 1:

[0756] Users enter personal data as part of the initial setup through a dedicated application or wearable device. This includes height, weight, age, and health goals. The data entered by the user is collected by the device. The entered personal data is then prepared to be transferred to the server as basic information necessary for subsequent processing steps.

[0757] Step 2:

[0758] The device transmits personal data and health goals collected from the user to the server. In addition, the device uses an emotion analysis device to measure the user's emotional state (stress, relaxation level, etc.) and transmits this data to the server. Here, emotional data obtained from the user's facial expressions and voice indicators is processed to reveal the user's emotional state, and this information is transmitted to the server.

[0759] Step 3:

[0760] The server analyzes the received personal and emotional data and uses a generative AI model to automatically generate a physical activity plan and nutrition plan tailored to the user. Inputs include the user's fitness level, health goals, and current emotional state. The server processes this information and outputs a plan that includes optimal endurance and muscle-strengthening activities for the user.

[0761] Step 4:

[0762] The generated plan is presented to the user via a device. The device uses a VR headset to construct a virtual environment based on the generated plan. The user then enters this virtual environment and begins exercising. Specifically, running in a simulated park and various exercises are visualized.

[0763] Step 5:

[0764] The device's sensors track the user's movements in real time and transmit that data to the server. The input includes specific movement data from the user during exercise. This enables real-time feedback.

[0765] Step 6:

[0766] The server analyzes motion data sent from the terminal to check whether the exercise is being performed correctly. If inappropriate form or motion is detected, it generates feedback for correction and provides it to the user through the terminal. The content of the feedback is also dynamically adjusted based on the user's emotional state.

[0767] Step 7:

[0768] Users receive feedback from the server and modify their exercises as needed. They then use this feedback to improve their next training session, aiming for sustained fitness improvement. Once a user completes a training session, all data is saved for creating their next training plan.

[0769] (Application Example 2)

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

[0771] In modern society, it is crucial for individuals to effectively utilize fitness and nutrition plans to achieve their health goals. However, these plans are often rigid and lack the dynamic adjustments necessary to consider individual physiological data, emotional states, and even location information. Furthermore, if a fitness plan does not align with a user's real-world environment, it can be difficult for users to maintain motivation. This can hinder effective health management.

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

[0773] In this invention, the server includes means for acquiring physiological data and goals from the user, means for automatically generating exercise and nutrition plans to achieve health goals based on the acquired physiological data, and means for dynamically customizing the fitness plan based on the user's location information and environment. This makes it possible to provide a flexible fitness experience adapted to the individual circumstances of the user.

[0774] "Physiological data" refers to information about an individual's physique, age, and health status, and is used to customize the user's fitness plan.

[0775] "Health goals" refer to specific targets related to the health state or fitness level that an individual wishes to achieve, and serve as a basis for creating a plan.

[0776] An "exercise plan" refers to a specific plan of exercise and training designed to help a user achieve their health goals.

[0777] A "nutrition plan" refers to a plan outlining recommended meals and nutritional intake to help a user achieve their health goals.

[0778] A "virtual environment" refers to a digital space that users experience through digital technology, either by mimicking or uniquely designing a real-world environment.

[0779] "Location information" refers to geographical data that indicates the user's current location, and is used to customize fitness plans.

[0780] "Emotional data" refers to information that reflects the user's emotional state and is used to adjust exercise plans and provide feedback.

[0781] To implement this invention, the user must first install a dedicated application on their smartphone or AR-enabled smart glasses. Upon launching the application and inputting their physiological data and health goals, the data is transmitted from the device to a server. At this point, the server utilizes a generative AI model to automatically generate an exercise plan and nutrition plan to achieve the user's health goals. This generation process also takes into account the user's emotional data and location information.

[0782] The device presents the generated exercise plan to the user in a virtual environment, and the user begins exercising according to the instructions. When the user exercises, the system provides a fitness plan appropriate to the location based on location information. For example, when visiting a park, aerobic exercise suited to that environment will be recommended.

[0783] During exercise, sensors in the device track the user's movements in real time and send the data to a server. The server then analyzes the received movement data and provides feedback to the user. This includes advice on correcting incorrect form and improving motivation.

[0784] This system's emotion engine has the ability to evaluate the user's emotional state in real time and dynamically adjust the exercise plan. For example, if the user is feeling stressed, the exercise content will be changed to something that promotes relaxation. Specifically, if the user has a goal of "continuing to exercise three times a week while relaxing," it will recommend light aerobic exercise in a relaxing environment.

[0785] An example of a prompt to a generative AI model is: "Location: park, User's mood: tired, Please provide a recommended fitness plan."

[0786] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0787] Step 1:

[0788] Users launch a dedicated application on their smartphone or AR-enabled smart glasses and input physiological data (height, weight, age, etc.) and health goals. The input data is sent to the server by the device. The input here consists of the user's physiological data and goals, which become the output data to the server.

[0789] Step 2:

[0790] The server automatically generates optimal exercise and nutrition plans using an AI model based on received physiological data and health goals. It uses the user's physiological data and goals as input data, analyzing and processing this data to output the exercise and nutrition plans. The generated plans include aerobic exercise and strength training, and are customized for each user.

[0791] Step 3:

[0792] The terminal presents the user with an exercise plan received from the server in a virtual environment. The user then uses VR or AR technology to begin exercising according to the plan. In this case, the generated exercise plan is the input data, and the provision of a visual training scene in the virtual environment is the output.

[0793] Step 4:

[0794] When a user exercises, sensors built into the device track the user's movements in real time. The device sends the collected movement data to a server. In this process, the movement data is the input, and the transmission to the server is the output.

[0795] Step 5:

[0796] The server analyzes the received motion data and generates feedback for the user. The input is previously tracked motion data, and the output is feedback information. The feedback includes advice for correcting exercise form and maintaining motivation.

[0797] Step 6:

[0798] The emotion engine evaluates the user's emotional state in real time and dynamically adjusts the exercise plan. The user's emotional data is used as input, and adjustments to exercise intensity and content are output. For example, if the user is feeling stressed, exercises that promote relaxation will be suggested.

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

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

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

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

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

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

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

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

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

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

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

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

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

[0812] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0813] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

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

[0815] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

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

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

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

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

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

[0821] (Claim 1)

[0822] A means of obtaining physiological data and goals from users,

[0823] A means for automatically generating exercise and nutrition plans to achieve health goals based on acquired physiological data,

[0824] A means of presenting the generated exercise plan in a virtual space, detecting the user's movements, and providing feedback,

[0825] A means of adjusting exercise and nutrition plans based on user feedback and the latest physiological data,

[0826] A system that includes this.

[0827] (Claim 2)

[0828] The system according to claim 1, further comprising means for tracking the user's actions in the virtual space and analyzing the data in real time.

[0829] (Claim 3)

[0830] The system according to claim 1, further comprising means of including aerobic exercise and strength training in the exercise plan generated based on the user's goal setting.

[0831] "Example 1"

[0832] (Claim 1)

[0833] A means of obtaining human body data and goals from the user,

[0834] A means for automatically generating exercise and nutrition plans to achieve health goals based on acquired human body data,

[0835] A means of presenting the generated exercise plan in a virtual domain, detecting the user's physical activity, and providing feedback,

[0836] A means of adjusting exercise and nutrition plans based on user feedback and the latest human body data,

[0837] A means of providing immediate feedback on exercise planning through a generated AI model via a display device equipped with a virtual training environment,

[0838] A system that includes this.

[0839] (Claim 2)

[0840] The system according to claim 1, further comprising means for tracking user activity in the virtual domain and immediately analyzing the data.

[0841] (Claim 3)

[0842] The system according to claim 1, further comprising means for including aerobic exercise and resistance exercise in the exercise plan generated based on the user's goal setting.

[0843] "Application Example 1"

[0844] (Claim 1)

[0845] Means for obtaining physiological information and goals from the user,

[0846] A means for automatically generating exercise and nutritional guidelines to achieve health goals based on acquired physiological information,

[0847] A means of presenting generated movement guidelines in a virtual space, detecting the user's movements, and providing feedback,

[0848] A means of correcting the shape of the user's movements and adjusting the exercise intensity in real time through a personal robot,

[0849] Means for adjusting exercise and nutritional guidelines based on the latest physiological data and feedback,

[0850] A system that includes this.

[0851] (Claim 2)

[0852] The system according to claim 1, further comprising means for tracking the user's movements using the virtual space and personal robot and analyzing the data in real time.

[0853] (Claim 3)

[0854] The system according to claim 1, further comprising means for including aerobic exercise and resistance exercise in the exercise guidelines generated based on the user's goal setting.

[0855] "Example 2 of combining an emotion engine"

[0856] (Claim 1)

[0857] Means of obtaining personal data and goals from users,

[0858] A means of measuring a user's emotional state using an emotion analysis device,

[0859] A means including a knowledge processing device for automatically generating a physical activity plan and a nutrition plan to achieve goals based on acquired personal data and emotional state,

[0860] A means of presenting the generated physical activity plan in a virtual environment, detecting the user's activity, and providing feedback,

[0861] A means of adjusting physical activity plans and nutrition plans based on user feedback and the latest personal data,

[0862] A system that includes this.

[0863] (Claim 2)

[0864] The system according to claim 1, further comprising means for tracking user actions in the virtual environment and instantly analyzing the information.

[0865] (Claim 3)

[0866] The system according to claim 1, further comprising means of including endurance activities and muscle-strengthening exercises in the physical activity plan generated based on the user's goal setting.

[0867] "Application example 2 when combining with an emotional engine"

[0868] (Claim 1)

[0869] A means of obtaining physiological data and goals from users,

[0870] A means for automatically generating exercise and nutrition plans to achieve health goals based on acquired physiological data,

[0871] A means of presenting the generated exercise plan in a virtual environment, detecting the user's movements, and providing feedback,

[0872] A means for dynamically customizing a fitness plan based on the user's location and environment,

[0873] A means of adjusting exercise and nutrition plans based on user feedback and the latest physiological data,

[0874] A system that includes this.

[0875] (Claim 2)

[0876] The system according to claim 1, further comprising means for tracking the user's actions in the virtual space and analyzing the data in real time.

[0877] (Claim 3)

[0878] The system according to claim 1, further comprising means of including aerobic exercise and strength training in the exercise plan generated based on the user's goal setting. [Explanation of Symbols]

[0879] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of obtaining physiological data and goals from users, A means for automatically generating exercise and nutrition plans to achieve health goals based on acquired physiological data, A means of presenting the generated exercise plan in a virtual space, detecting the user's movements, and providing feedback, A means of adjusting exercise and nutrition plans based on user feedback and the latest physiological data, A system that includes this.

2. The system according to claim 1, further comprising means for tracking the user's actions in the virtual space and analyzing the data in real time.

3. The system according to claim 1, further comprising means of including aerobic exercise and strength training in the exercise plan generated based on the user's goal setting.

Images