system

Abstract

We provide the system. [Solution] A means for generating an individual training plan using a trainer generated based on a virtualized character selected by the user, A means of analyzing the user's exercise in real time and providing immediate feedback according to the training performance, A means of recording training results and managing rewards based on points awarded to users, A means of providing community features to share results among users and promote competition, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the modern fitness market, although users are seeking individualized training guidance and continuous motivation, traditional fitness programs and self-learning form applications have limitations. Also, there are insufficient entertainment elements for users to enjoy fitness more, and there is a lack of motivation to achieve fitness goals. Furthermore, there is a lack of a system that utilizes communication and competition among users, making it difficult to improve individual achievements.

Means for Solving the Problems

[0005] This invention proposes a system that provides personalized training plans by utilizing a virtual character selected by the user as a trainer. This system includes a function that analyzes the user's movements in real time and provides accurate feedback immediately. Furthermore, it increases user motivation by awarding points according to training results and managing rewards based on these points. It also aims to improve the effectiveness of fitness through interaction and competition by providing a community function for users to share their results.

[0006] A "user" refers to a person who uses the system and receives personalized training plans and feedback.

[0007] A "virtualized character" refers to a fictional person or entity that has been digitized for use by a user as a trainer.

[0008] A "trainer" is a character who provides training guidance and feedback to users, and this can include virtual characters.

[0009] A "personalized training plan" refers to a customized exercise plan tailored specifically to the user, based on their fitness level and goals.

[0010] "Real-time analysis" refers to a process that instantly analyzes user behavior and immediately reflects the results.

[0011] "Instant feedback" refers to advice and improvement information provided in real time during user training.

[0012] "Training results" refer to the progress and degree to which a user has achieved their goals through training.

[0013] "Points" refer to numerical values ​​awarded based on a user's training performance, and are used for managing and evaluating rewards.

[0014] "Special privilege" refers to rewards or services that can be obtained by users through the utilization of points.

[0015] "Community function" refers to a function on the system that enables communication, result sharing, and ranking competition among users.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. <000E086>It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

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

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

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

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

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

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

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

[0024] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] This invention relates to an embodiment of an online system in which a user selects a virtualized character as a trainer and is provided with a personalized fitness plan. The system consists of three main components: a server, a terminal, and a user.

[0038] The server generates a trainer based on the virtualized character selected by the user. The trainer creates a personalized fitness plan for the user and sends it to the device. This plan is customized according to the user's goals and fitness level, and incorporates appropriate exercises. The server also receives the user's training data and provides analysis results, sending real-time feedback to the device.

[0039] The device functions as an interface for the user, displaying the fitness plan received from the server. A virtual trainer character guides the user through the plan and supports their training progress. The user's exercise is recorded via the device's camera and transmitted to the server in real time. The device immediately notifies the user of the feedback received from the server, encouraging them to improve their training.

[0040] Users perform training based on fitness plans received via their devices. During training, they receive feedback and encouragement from virtual characters to maintain motivation. Users also accumulate points for completing specific exercises, which can be used to earn rewards within the system. Furthermore, community features allow users to share their progress with other users and compare rankings.

[0041] For example, if a user sets "establishing healthy lifestyle habits" as their goal, the system will suggest a plan including aerobic exercise and stretching, tailored to the user's fitness level. During this time, a selected character will deliver encouraging messages, ensuring the user remains motivated throughout the exercise. At the end of each training session, the user receives detailed feedback on how many calories they burned and the results of their exercise. In this way, users can increase their awareness of fitness and be helped to lead a healthier life.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user launches the application on their device, enters their user information, and creates an account.

[0045] Step 2:

[0046] The terminal sends user information to the server, and the server stores that information in a database.

[0047] Step 3:

[0048] Users can select their preferred virtual character and set them as their training trainer.

[0049] Step 4:

[0050] The server considers the user's fitness level and goals, and generates a personalized fitness plan based on the selected character.

[0051] Step 5:

[0052] The server generates a fitness plan and sends it to the device, which then displays it to the user.

[0053] Step 6:

[0054] The user follows their fitness plan and begins training, and the device records the user's exercise via its camera.

[0055] Step 7:

[0056] The device analyzes exercise data in real time and sends the results to the server.

[0057] Step 8:

[0058] The server generates feedback based on the received data and sends it to the terminal.

[0059] Step 9:

[0060] The terminal notifies the user of feedback received from the server, informing them of areas for improvement in the next training session.

[0061] Step 10:

[0062] The server records the training results and awards points to the user.

[0063] Step 11:

[0064] When users use their accumulated points to obtain rewards, they select the rewards via their device.

[0065] Step 12:

[0066] Users utilize community features to share their achievements and rankings with other users using their devices.

[0067] (Example 1)

[0068] 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."

[0069] In today's world, there is a need for systems that easily provide training plans tailored to individual fitness needs. Furthermore, there is a lack of means to analyze users' training data in real time and provide immediate feedback, making it difficult to maintain motivation. Additionally, there is a need for a system that efficiently integrates features to promote mutual communication among users and foster a sense of competition.

[0070] 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.

[0071] In this invention, the server includes means for generating a trainer based on a virtualized character selected by the user and creating an individualized training plan using a generation AI model; means for analyzing the user's exercise in real time and generating immediate feedback according to the training performance using the generation AI model; and means for recording training results and managing rewards based on a reward system granted to the user. This enables personalized training guidance for users, improves motivation through real-time feedback and a reward system, and provides a system that promotes communication and competition among users.

[0072] A "user-selected virtualized character" is a digital representation of a person or animal that the user can select as an image or computer-generated image from the system's interface, and which serves as a trainer.

[0073] "Generating a trainer" means creating an interactive program based on a selected virtual character, in which that character presents and supports the user with a fitness plan.

[0074] A "generative AI model" is an artificial intelligence algorithm designed to produce specific outputs or predictions based on user input and historical data.

[0075] A "training plan" is a detailed plan that schedules and sequentially performs specific exercises and activities according to the fitness goals that the user wants to achieve.

[0076] "Real-time analysis" means instantly converting a user's exercise or activity into data in its original state, and immediately processing and analyzing this information.

[0077] "Immediate feedback" refers to advice and evaluations provided in real time during training, including information on areas for improvement and encouragement that users can gain while exercising.

[0078] A "reward system" is a mechanism in which points or rewards are awarded to users based on the results and actions they achieve during training, and it is a means of promoting increased motivation.

[0079] "Community features" are functions that enable users to share their achievements, communicate, and compete with each other within the system.

[0080] This invention provides a specific embodiment of an online system in which a user selects a virtualized character and is provided with a personalized fitness plan using that character as a trainer. The system consists of three main components: a server, a terminal, and a user.

[0081] The server generates a trainer based on a virtual character selected by the user through their terminal. The software used here is a generation AI model, which creates a customized fitness plan tailored to the user's fitness goals and fitness level. During this process, the server prompts the AI ​​model with a message such as, "Generate the optimal training plan for the user's health goals," and obtains a suitable plan. The server also receives and analyzes the user's training data in real time to generate immediate feedback, which is then sent to the terminal.

[0082] The terminal plays the role of providing the user with an interface to this system. It displays the fitness plan received from the server to the user, and a virtual trainer guides the user through the training on the screen. The terminal is equipped with a camera that records the user's exercise in real time and sends that data to the server. The terminal also notifies the user of immediate feedback from the server to support exercise improvement and motivation maintenance.

[0083] Users train according to fitness plans received via their devices. During training, they receive feedback and encouraging messages from a virtual trainer, helping them stay motivated towards achieving their goals. Each time they complete a specific exercise, users earn points based on a reward system, which they can then redeem for rewards within the system. Furthermore, users can use the community feature to share their progress with other users and check rankings.

[0084] For example, if a user sets "weight loss" as their goal, the server uses a generative AI model to generate a plan and provides a menu that combines cardio and strength training. The virtual trainer provides specific instructions such as, "Today's target calorie expenditure is 500," and after the training, provides feedback such as, "Congratulations, you have achieved your goal."

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] The user logs into the system using their device and selects a trainer from a list of virtualized characters. The input is the user's character selection, and the output is the information of the selected character. This information is sent to the server via the device. Specifically, the user confirms their character selection by tapping on the options on the screen.

[0088] Step 2:

[0089] The server generates a trainer using character information received from the terminal. The input is character information and basic user information, and the output is the generated virtual trainer. In this process, the character's attributes are input to the AI ​​model as a prompt message, "Generate an appropriate training plan based on the selected character," and the trainer is generated.

[0090] Step 3:

[0091] The server creates a training plan based on the user's goals and current fitness level. Inputs include the user's goals, fitness level, and trainer information, while output is a personalized fitness plan. During data processing, a generative AI model incorporates exercises and other elements appropriate to the user's goals into the plan. The server then sends this plan to the user's device.

[0092] Step 4:

[0093] The terminal displays the fitness plan received from the server to the user. The input is the fitness plan, and the output is a visual display of the plan. Specifically, the screen displays the training steps and their details, and a virtual trainer provides instructions via voice or text.

[0094] Step 5:

[0095] The user begins training through the device. The user's movements are recorded in real time using the device's camera function. The input is the user's real-time movement data, and the output is the recorded movement data. The device sends this data to the server.

[0096] Step 6:

[0097] The server analyzes training data sent by the user. The input is motion data, and the output is generated feedback. As a data processing step, the server uses a generative AI model to evaluate the motion, analyze areas for improvement and successes, and generate real-time feedback.

[0098] Step 7:

[0099] The device receives feedback from the server and notifies the user. The input is the content of the feedback, and the output is the notification information for the user. Specifically, feedback is displayed via on-screen pop-ups and audio guidance to encourage the user to improve their exercise.

[0100] Step 8:

[0101] Users review the results of their training sessions and receive points as rewards. Input is point information based on training performance, and output is rewards based on the reward system. Users can also take actions necessary to share their results within the community.

[0102] (Application Example 1)

[0103] 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."

[0104] While modern fitness programs are becoming increasingly personalized, maintaining motivation is difficult, and the lack of real-time feedback to users can hinder the maximization of training effectiveness. Furthermore, limited means for users to maintain motivation and visualize their progress highlight the need to improve the user experience.

[0105] 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.

[0106] In this invention, the server includes means for generating an individualized training plan using a trainer generated based on a virtualized character selected by the user; means for the virtual trainer to provide real-time feedback and exercise movements through a visual display device; and means for analyzing the user's movements in real time and providing immediate feedback according to the training performance. This enables the user to effectively perform individualized training while receiving real-time feedback and increasing their motivation.

[0107] A "user" is an individual who selects a virtualized character and receives a fitness plan.

[0108] A "virtualized character" is a digital character that a user can select and that functions as a trainer.

[0109] A "trainer" is a fitness instructor who is generated based on a virtualized character selected by the user.

[0110] An "individualized training plan" is an exercise program customized according to the user's goals and fitness level.

[0111] A "visual display device" is a device that allows a virtual trainer to visually demonstrate exercise movements and provide feedback, and includes smart glasses and head-mounted displays.

[0112] "Real-time feedback" is a process that analyzes the user's movement patterns and provides appropriate information immediately.

[0113] "Evaluation" refers to a numerical display or points awarded based on the results and progress a user achieves during training.

[0114] The "information sharing function" is a feature that allows users to compare and share their training results and progress with other users.

[0115] The system for implementing this invention consists of a server in a cloud environment, terminals including smart glasses or head-mounted displays, and a user who operates them. The server generates an individualized training plan based on a virtual character selected by the user and instructs the user on it via a visual display device. Specifically, the server uses an AI model to analyze the user's goals and fitness level, and uses Unity to design real-time feedback from the virtual trainer.

[0116] The system utilizes smart glasses, allowing users to visually view a virtual trainer while training. Using TENSORFLOW®, a camera integrated into the glasses analyzes the user's movements and instantly transmits the data to a server, providing immediate feedback on exercise errors and areas for improvement. This enables users to train efficiently while receiving encouragement from their virtual trainer.

[0117] For example, if a user sets "improving flexibility" as their goal, the server will create a plan centered around stretching movements. While the user is training, the virtual trainer will provide real-time feedback such as, "Straighten your back and move a little more slowly." An example of a prompt would be, "The virtual trainer will monitor the degree of knee flexion and provide specific instructions to encourage further improvement."

[0118] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0119] Step 1:

[0120] The server receives a virtual character selected by the user and individual fitness goals. The input includes the user's goals and character selection data, and a generative AI model is used to generate a training plan based on this data. The output is a user-specific training plan. The server uses Unity to configure this plan and prepares it for transmission to the device.

[0121] Step 2:

[0122] The terminal displays individual training plans and virtual character information received from the server. The input is fitness plan data from the server, which is then visualized and presented to the user. The virtual trainer provides exercise instructions in real time through the visual display device. The output is a screen display for the user to visually understand.

[0123] Step 3:

[0124] The user performs exercises according to the displayed instructions. The device's camera captures the user's movements, and TensorFlow is used to analyze whether the exercises are being performed correctly. The input includes the captured image data, and by analyzing this data, information on the accuracy of the movements is generated. The output provides information for detailed feedback on the user's movements.

[0125] Step 4:

[0126] The server receives motion information sent from the terminal and generates real-time feedback based on the analysis results. User motion analysis data is used as input, and the AI ​​model calculates the optimal feedback. The output is a message of improvement and encouragement, and the feedback is immediately sent back to the terminal and delivered to the user.

[0127] Step 5:

[0128] Users adjust their exercises based on the feedback they receive and earn points upon completion of specific exercises. Input is feedback from the server, and output is updated point information and actions taken in response to further instructions for improvement. Users continuously improve their training by repeating this process.

[0129] 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.

[0130] This invention enhances the fitness experience by combining a personalized training system using virtualized characters with an emotion engine that recognizes user emotions. The system is centered around a server, terminals, and users, with each component playing a specific role.

[0131] The server generates a trainer based on the user's selected virtual character and provides a personalized training plan tailored to the user's fitness level and goals. This creates a customized program to meet the user's specific fitness needs. The server also incorporates an emotion engine that analyzes emotional data sent by the user and adjusts the feedback accordingly.

[0132] The terminal displays the training plan sent from the server to the user and also functions as an interface for monitoring the user during training. The terminal is equipped with sensors that capture the user's facial expressions and voice, and this data is sent to the emotion engine to understand the user's emotional state. Once the user's emotions are analyzed, feedback and training guidance are appropriately adjusted based on that information.

[0133] As users train, they receive feedback from a virtual character via their device. The user's emotional state is reflected in this feedback; for example, if the user is tired, they may receive encouragement or guidance to slow down. This emotionally responsive feedback helps users maintain high motivation and supports their continued training.

[0134] Furthermore, users' training results are recorded as points and used to provide rewards. Users can also utilize community features through their devices to share their results with other users and compare rankings. This promotes competition and interaction within the fitness community, creating a system that supports individual users in achieving their fitness goals.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] The user launches the application on their device, creates an account, and enters personal information and fitness goals.

[0138] Step 2:

[0139] The terminal sends user information and data for the selected virtual character to the server, which then generates a trainer based on this information.

[0140] Step 3:

[0141] The server creates a personalized training plan based on the user's fitness goals and level, and sends it to the device.

[0142] Step 4:

[0143] The terminal displays the training plan received from the server to the user and begins the training guidance. A virtual character introduces the training content to the user.

[0144] Step 5:

[0145] The user begins training, and the device captures the user's facial expressions and voice through its built-in sensors, sending this data to the server as emotion data.

[0146] Step 6:

[0147] The server uses an emotion engine to analyze the user's emotional state and adjusts the content of the feedback and training instructions based on the results.

[0148] Step 7:

[0149] The server sends tailored feedback to the device, which then notifies the user in real time. The feedback includes encouraging messages tailored to the user's emotions and advice on training pace.

[0150] Step 8:

[0151] When the user finishes training, the device records the results and sends that data to the server.

[0152] Step 9:

[0153] The server records the user's training results as points in a database and sends a list of eligible rewards to the user's device.

[0154] Step 10:

[0155] Users can select rewards based on the points they have earned through their devices.

[0156] Step 11:

[0157] Users can enjoy interaction and competition by using the community features on their devices to share their training results with other users and check rankings.

[0158] (Example 2)

[0159] 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".

[0160] Traditional fitness systems often offered standardized programs and feedback that didn't consider emotional states, leading to a lack of user motivation and retention. Furthermore, they struggled to provide personalized instruction tailored to individual needs.

[0161] 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.

[0162] In this invention, the server includes means for generating an individualized exercise plan using an instructor generated based on a virtualized character selected by the user; means for analyzing the user's exercise state and emotional data in real time and providing exercise guidance and immediate feedback according to the emotional state; and means for recording exercise results and managing rewards based on the compensation given to the user. This provides an individually customized exercise plan and allows the user to receive feedback tailored to their own pace and emotions.

[0163] A "coach" is a virtual entity created to provide exercise plans and offer guidance and feedback to users.

[0164] An "exercise plan" refers to a customized training schedule or program based on the user's fitness level and goals.

[0165] "Emotional data" refers to data captured from a user's facial expressions and voice, and is used to analyze the user's emotional state.

[0166] "Instant feedback" refers to advice and evaluations provided instantly based on real-time analysis of the user's physical and emotional state.

[0167] "Rewards" refer to points or rewards that users earn based on their exercise performance, and benefits are managed based on these points.

[0168] "Cooperative features" are functions that help users share their exercise results and interact with other users to promote competition.

[0169] A "detector" refers to a device or sensor used to capture user behavior and emotional data.

[0170] This invention provides a system that personalizes the user's fitness experience and offers feedback that takes their emotional state into consideration. The system is centered around a server, a terminal, and the user, with each component playing a specific role.

[0171] The server generates a virtual instructor character based on user input. The server performs calculations to develop an exercise plan based on the user's selected character, fitness level, and set goals. Furthermore, the server integrates an emotion engine that analyzes the user's emotional data. This analysis allows the server to determine in real time what kind of feedback the user needs during exercise and generate tailored feedback accordingly.

[0172] The device presents the user with the exercise plan and feedback transmitted from the server, and functions as a crucial interface for monitoring the user's movements. The device incorporates multiple sensors to capture the user's facial expressions and voice. This allows the device to continuously accumulate data on the user's emotional state, which is then transmitted to the emotion engine.

[0173] Users receive feedback that reflects their emotional state captured during exercise. For example, if a user is feeling tired, a virtual character on the device might display an encouraging message such as, "Let's slow down the pace a bit during today's workout and keep it fun." In this way, the fitness session provides a supportive experience for the user.

[0174] As a concrete example, the following is an example of an input prompt statement for a generative AI model:

[0175] "Please suggest feedback that corresponds to the emotional state the user is currently displaying. The user is currently feeling tired."

[0176] Through this system, personalized exercise plans and appropriate feedback help maintain user motivation and support the continuation of training.

[0177] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0178] Step 1:

[0179] Users log in via their device and enter their fitness level and goals. The device then sends this information to the server. This information is used as basic data necessary for creating an exercise plan.

[0180] Step 2:

[0181] The server generates a virtual character based on the received user information. Specifically, it identifies a character that matches the user's preferences and builds a coaching model to generate an exercise plan tailored to that character. In this process, the server analyzes the user's input data and calculates the optimal exercise program.

[0182] Step 3:

[0183] After the exercise plan is generated, the server sends this plan to the terminal. The terminal then displays the received plan to the user. The exercise plan includes specific exercises and the set duration.

[0184] Step 4:

[0185] The device uses sensors to capture user emotional data during training. This includes the user's facial expressions and voice data. The collected data is sent to a server, which serves as input for analyzing the emotional state.

[0186] Step 5:

[0187] The server analyzes the received emotional data using an emotion engine. The emotion engine inputs the received data as prompts into an AI model to determine the user's current emotional state. For example, if the server determines that the user is showing signs of fatigue, it generates an encouraging message.

[0188] Step 6:

[0189] The generated feedback is sent from the server to the terminal and communicated to the user. The terminal provides appropriate guidance and support to the user through a virtual character. The feedback includes pacing adjustments and words of encouragement.

[0190] Step 7:

[0191] Once a user completes their exercise, the device records their progress and sends it to the server. The server calculates the reward based on the recorded data and adds points to the user's account. This information is also used later for managing rewards.

[0192] (Application Example 2)

[0193] 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".

[0194] In today's industrial environment, there is a demand to maximize the efficiency of robots and their operators working in factories. However, conventional training systems struggle to provide real-time feedback that takes into account the operator's psychological state, which can lead to increased operator stress. Furthermore, there is a lack of mechanisms to effectively manage work results and promote competition.

[0195] 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.

[0196] In this invention, the server includes means for generating individual training plans using instructors generated based on virtualized characters selected by the user; means for analyzing the user's work in real time and providing immediate guidance according to the training execution status; means for adjusting feedback provided by an emotion engine that recognizes the user's emotions and presenting encouragement from the virtual character according to the operator's psychological state; means for recording work results and managing rewards based on performance points awarded to the user; and means for providing collective functions to share results among users and promote competition. This makes it possible to improve work efficiency and enhance competitiveness while taking into account the operator's psychological state, and to reduce stress in the work environment.

[0197] A "user-selected virtual character" is a digital virtual entity generated based on user instructions, which functions as an instructor providing an individualized training plan.

[0198] An "individualized training plan" is a learning or work schedule customized to each user's specific needs and goals.

[0199] An "emotion engine" is a technology that analyzes the user's emotional state and adjusts feedback based on that data.

[0200] "Feedback adjustment" is a process that dynamically changes the information and support provided by the virtual instructor according to the user's emotions and work status.

[0201] "The operator's psychological state" refers to the operator's mental state, including their stress level and mood during the operation.

[0202] "Work results" refer to the specific achievements and progress obtained as a result of the work or training activities performed by the user.

[0203] "Performance points" are numerical values ​​or points calculated based on the user's work output and used for rewards and comparisons between users.

[0204] "Collective functions" refer to systems that provide platforms and features for users to share results and compete with each other.

[0205] This invention is a system for improving the work efficiency of operators and robots in a factory. The system uses a virtualized character to provide operators with individualized training plans, analyzes the operators' emotional state, and adjusts feedback to suit the situation.

[0206] The server generates a personalized training plan based on the virtual character selected by the pilot. This plan is customized to the pilot's experience and goals. The server uses Python and Flask, enabling it to provide plans in real time.

[0207] The device is equipped with sensors to capture the user's facial expressions and voice, and sends this data to an emotion engine. This engine uses OpenCV and TensorFlow to analyze the user's emotions and can receive feedback from a server according to that state.

[0208] Users receive real-time feedback from virtual characters via their smartphones or tablets. For example, if they feel tired while working, the character will notify them with an encouraging message such as, "You'll be able to take a break soon. Keep going!"

[0209] Such a system makes it easier for operators to maintain high motivation and improve work efficiency. An example of a prompt message is: "Create feedback based on the operator's emotional data and display an encouraging message through the virtual character."

[0210] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0211] Step 1:

[0212] The server generates individual training plans based on the virtual character selected by the user. It receives user-selected character information, past work history, and target data as input, analyzes this information, and outputs a customized training plan. Specifically, it uses Python or Flask to perform calculations that build a plan optimized for the user in real time.

[0213] Step 2:

[0214] The device uses sensors to capture the user's facial expressions and voice. Based on this input data, an emotion engine performs emotion analysis. Using OpenCV and TensorFlow, it recognizes changes in facial expressions and voice tone from image and audio data, and outputs numerical emotion data.

[0215] Step 3:

[0216] The emotion engine sends the analyzed emotion data to the server. The server then processes the feedback based on the received emotion data. For example, if the emotion data indicates fatigue, the server will output encouraging messages or instructions regarding work pace.

[0217] Step 4:

[0218] The user receives feedback via their device. Feedback, which is output from the server, is sent to the device and displayed on the screen through a virtual character. Specifically, the screen display changes according to the feedback content, and the user is guided to the next step based on their actions.

[0219] Step 5:

[0220] The server records user work output and calculates performance points. It takes user work data as input, scores it based on predetermined criteria, and outputs the result as performance points. These performance points are then used in subsequent reward systems and user comparisons.

[0221] Step 6:

[0222] The device provides a collective function for sharing information with other users. It uses user performance data as input, shares it with other users via the network, and performs specific actions to promote competition by outputting rankings and comment functions.

[0223] 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.

[0224] 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.

[0225] 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.

[0226] [Second Embodiment]

[0227] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0228] 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.

[0229] 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).

[0230] 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.

[0231] 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.

[0232] 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).

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] 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".

[0239] This invention relates to an embodiment of an online system in which a user selects a virtualized character as a trainer and is provided with a personalized fitness plan. The system consists of three main components: a server, a terminal, and a user.

[0240] The server generates a trainer based on the virtualized character selected by the user. The trainer creates a personalized fitness plan for the user and sends it to the device. This plan is customized according to the user's goals and fitness level, and incorporates appropriate exercises. The server also receives the user's training data and provides analysis results, sending real-time feedback to the device.

[0241] The device functions as an interface for the user, displaying the fitness plan received from the server. A virtual trainer character guides the user through the plan and supports their training progress. The user's exercise is recorded via the device's camera and transmitted to the server in real time. The device immediately notifies the user of the feedback received from the server, encouraging them to improve their training.

[0242] Users perform training based on fitness plans received via their devices. During training, they receive feedback and encouragement from virtual characters to maintain motivation. Users also accumulate points for completing specific exercises, which can be used to earn rewards within the system. Furthermore, community features allow users to share their progress with other users and compare rankings.

[0243] For example, if a user sets "establishing healthy lifestyle habits" as their goal, the system will suggest a plan including aerobic exercise and stretching, tailored to the user's fitness level. During this time, a selected character will deliver encouraging messages, ensuring the user remains motivated throughout the exercise. At the end of each training session, the user receives detailed feedback on how many calories they burned and the results of their exercise. In this way, users can increase their awareness of fitness and be helped to lead a healthier life.

[0244] The following describes the processing flow.

[0245] Step 1:

[0246] The user launches the application on their device, enters their user information, and creates an account.

[0247] Step 2:

[0248] The terminal sends user information to the server, and the server stores that information in a database.

[0249] Step 3:

[0250] Users can select their preferred virtual character and set them as their training trainer.

[0251] Step 4:

[0252] The server considers the user's fitness level and goals, and generates a personalized fitness plan based on the selected character.

[0253] Step 5:

[0254] The server generates a fitness plan and sends it to the device, which then displays it to the user.

[0255] Step 6:

[0256] The user follows their fitness plan and begins training, and the device records the user's exercise via its camera.

[0257] Step 7:

[0258] The device analyzes exercise data in real time and sends the results to the server.

[0259] Step 8:

[0260] The server generates feedback based on the received data and sends it to the terminal.

[0261] Step 9:

[0262] The terminal notifies the user of feedback received from the server, informing them of areas for improvement in the next training session.

[0263] Step 10:

[0264] The server records the training results and awards points to the user.

[0265] Step 11:

[0266] When users use their accumulated points to obtain rewards, they select the rewards via their device.

[0267] Step 12:

[0268] Users utilize community features to share their achievements and rankings with other users using their devices.

[0269] (Example 1)

[0270] 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."

[0271] In today's world, there is a need for systems that easily provide training plans tailored to individual fitness needs. Furthermore, there is a lack of means to analyze users' training data in real time and provide immediate feedback, making it difficult to maintain motivation. Additionally, there is a need for a system that efficiently integrates features to promote mutual communication among users and foster a sense of competition.

[0272] 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.

[0273] In this invention, the server includes means for generating a trainer based on a virtualized character selected by the user and creating an individualized training plan using a generation AI model; means for analyzing the user's exercise in real time and generating immediate feedback according to the training performance using the generation AI model; and means for recording training results and managing rewards based on a reward system granted to the user. This enables personalized training guidance for users, improves motivation through real-time feedback and a reward system, and provides a system that promotes communication and competition among users.

[0274] A "user-selected virtualized character" is a digital representation of a person or animal that the user can select as an image or computer-generated image from the system's interface, and which serves as a trainer.

[0275] "Generating a trainer" means creating an interactive program based on a selected virtual character, in which that character presents and supports the user with a fitness plan.

[0276] A "generative AI model" is an artificial intelligence algorithm designed to produce specific outputs or predictions based on user input and historical data.

[0277] A "training plan" is a detailed plan that schedules and sequentially performs specific exercises and activities according to the fitness goals that the user wants to achieve.

[0278] "Real-time analysis" means instantly converting a user's exercise or activity into data in its original state, and immediately processing and analyzing this information.

[0279] "Immediate feedback" refers to advice and evaluations provided in real time during training, including information on areas for improvement and encouragement that users can gain while exercising.

[0280] A "reward system" is a mechanism in which points or rewards are awarded to users based on the results and actions they achieve during training, and it is a means of promoting increased motivation.

[0281] "Community features" are functions that enable users to share their achievements, communicate, and compete with each other within the system.

[0282] This invention provides a specific embodiment of an online system in which a user selects a virtualized character and is provided with a personalized fitness plan using that character as a trainer. The system consists of three main components: a server, a terminal, and a user.

[0283] The server generates a trainer based on a virtual character selected by the user through their terminal. The software used here is a generation AI model, which creates a customized fitness plan tailored to the user's fitness goals and fitness level. During this process, the server prompts the AI ​​model with a message such as, "Generate the optimal training plan for the user's health goals," and obtains a suitable plan. The server also receives and analyzes the user's training data in real time to generate immediate feedback, which is then sent to the terminal.

[0284] The terminal plays a role in providing an interface for the user with this system. It displays the fitness plan received from the server to the user, and the virtual trainer guides the training content on the screen. The terminal is equipped with a camera and has the function of recording the user's movements in real time and sending the data to the server. The terminal also notifies the user of the immediate feedback from the server and supports the improvement of the exercise and the maintenance of motivation.

[0285] The user conducts training according to the fitness plan received through the terminal. During the training, the user can receive feedback and encouraging messages from the virtual trainer and maintain motivation towards achieving the goals. Every time a specific exercise is completed, the user can obtain points based on the reward system and can get benefits within the system. Furthermore, the user can utilize the community function to share achievements with other users and check the rankings.

[0286] As a specific example, when the user targets "weight loss", the server uses a generative AI model to generate a plan and provides a menu combining cardio and strength training. The virtual trainer provides specific instructions such as "Today's target calorie consumption is 500", and gives feedback such as "Congratulations, you have achieved your goal" after the training.

[0287] The flow of the specific process in Example 1 will be described using FIG. 11.

[0288] Step 1:

[0289] The user logs in to the system using the terminal and selects a trainer from the list of virtual characters. The input is the user's character selection, and the output is the selected character information. This information is sent to the server via the terminal. As a specific operation, the character is determined by tapping on the options on the screen.

[0290] Step 2:

[0291] The server generates a trainer using character information received from the terminal. The input is character information and basic user information, and the output is the generated virtual trainer. In this process, the character's attributes are input to the AI ​​model as a prompt message, "Generate an appropriate training plan based on the selected character," and the trainer is generated.

[0292] Step 3:

[0293] The server creates a training plan based on the user's goals and current fitness level. Inputs include the user's goals, fitness level, and trainer information, while output is a personalized fitness plan. During data processing, a generative AI model incorporates exercises and other elements appropriate to the user's goals into the plan. The server then sends this plan to the user's device.

[0294] Step 4:

[0295] The terminal displays the fitness plan received from the server to the user. The input is the fitness plan, and the output is a visual display of the plan. Specifically, the screen displays the training steps and their details, and a virtual trainer provides instructions via voice or text.

[0296] Step 5:

[0297] The user begins training through the device. The user's movements are recorded in real time using the device's camera function. The input is the user's real-time movement data, and the output is the recorded movement data. The device sends this data to the server.

[0298] Step 6:

[0299] The server analyzes training data sent by the user. The input is motion data, and the output is generated feedback. As a data processing step, the server uses a generative AI model to evaluate the motion, analyze areas for improvement and successes, and generate real-time feedback.

[0300] Step 7:

[0301] The device receives feedback from the server and notifies the user. The input is the content of the feedback, and the output is the notification information for the user. Specifically, feedback is displayed via on-screen pop-ups and audio guidance to encourage the user to improve their exercise.

[0302] Step 8:

[0303] Users review the results of their training sessions and receive points as rewards. Input is point information based on training performance, and output is rewards based on the reward system. Users can also take actions necessary to share their results within the community.

[0304] (Application Example 1)

[0305] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0306] While modern fitness programs are becoming increasingly personalized, maintaining motivation is difficult, and the lack of real-time feedback to users can hinder the maximization of training effectiveness. Furthermore, limited means for users to maintain motivation and visualize their progress highlight the need to improve the user experience.

[0307] 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.

[0308] In this invention, the server includes means for generating an individual training plan using a trainer generated based on a virtual character selected by the user, means for the virtual trainer to show feedback and exercise actions in real time through a visual display device, and means for analyzing the user's movement in real time and providing immediate feedback according to the execution status of the training. Thereby, the user can effectively perform individual training while receiving feedback in real time and enhancing motivation.

[0309] A "user" is an individual who selects a virtual character and receives a fitness plan.

[0310] A "virtual character" is a digital character selected by the user that functions as a trainer.

[0311] A "trainer" is something that plays the role of a fitness instructor generated based on a virtual character selected by the user.

[0312] An "individual training plan" is an exercise program customized according to the user's goals and fitness level.

[0313] A "visual display device" is a device for the virtual trainer to visually show exercise actions and feedback, including smart glasses and head-mounted displays.

[0314] "Feedback in real time" is a process of analyzing the user's movement situation and immediately providing appropriate information.

[0315] An "evaluation" is a numerical display or points given based on the results and progress achieved by the user during training.

[0316] The "information sharing function" is a feature that allows users to compare and share their training results and progress with other users.

[0317] The system for implementing this invention consists of a server in a cloud environment, terminals including smart glasses or head-mounted displays, and a user who operates them. The server generates an individualized training plan based on a virtual character selected by the user and instructs the user on it via a visual display device. Specifically, the server uses an AI model to analyze the user's goals and fitness level, and uses Unity to design real-time feedback from the virtual trainer.

[0318] The system utilizes smart glasses, allowing users to visually view a virtual trainer while training. Using TensorFlow, the glasses' built-in camera analyzes the user's movements, instantly sending data to a server for immediate feedback on exercise errors and areas for improvement. This enables users to train efficiently while receiving encouragement from their virtual trainer.

[0319] For example, if a user sets "improving flexibility" as their goal, the server will create a plan centered around stretching movements. While the user is training, the virtual trainer will provide real-time feedback such as, "Straighten your back and move a little more slowly." An example of a prompt would be, "The virtual trainer will monitor the degree of knee flexion and provide specific instructions to encourage further improvement."

[0320] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0321] Step 1:

[0322] The server receives a virtual character selected by the user and individual fitness goals. The input includes the user's goals and character selection data, and a generative AI model is used to generate a training plan based on this data. The output is a user-specific training plan. The server uses Unity to configure this plan and prepares it for transmission to the device.

[0323] Step 2:

[0324] The terminal displays individual training plans and virtual character information received from the server. The input is fitness plan data from the server, which is then visualized and presented to the user. The virtual trainer provides exercise instructions in real time through the visual display device. The output is a screen display for the user to visually understand.

[0325] Step 3:

[0326] The user performs exercises according to the displayed instructions. The device's camera captures the user's movements, and TensorFlow is used to analyze whether the exercises are being performed correctly. The input includes the captured image data, and by analyzing this data, information on the accuracy of the movements is generated. The output provides information for detailed feedback on the user's movements.

[0327] Step 4:

[0328] The server receives motion information sent from the terminal and generates real-time feedback based on the analysis results. User motion analysis data is used as input, and the AI ​​model calculates the optimal feedback. The output is a message of improvement and encouragement, and the feedback is immediately sent back to the terminal and delivered to the user.

[0329] Step 5:

[0330] Users adjust their exercises based on the feedback they receive and earn points upon completion of specific exercises. Input is feedback from the server, and output is updated point information and actions taken in response to further instructions for improvement. Users continuously improve their training by repeating this process.

[0331] 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.

[0332] This invention enhances the fitness experience by combining a personalized training system using virtualized characters with an emotion engine that recognizes user emotions. The system is centered around a server, terminals, and users, with each component playing a specific role.

[0333] The server generates a trainer based on the user's selected virtual character and provides a personalized training plan tailored to the user's fitness level and goals. This creates a customized program to meet the user's specific fitness needs. The server also incorporates an emotion engine that analyzes emotional data sent by the user and adjusts the feedback accordingly.

[0334] The terminal displays the training plan sent from the server to the user and also functions as an interface for monitoring the user during training. The terminal is equipped with sensors that capture the user's facial expressions and voice, and this data is sent to the emotion engine to understand the user's emotional state. Once the user's emotions are analyzed, feedback and training guidance are appropriately adjusted based on that information.

[0335] As users train, they receive feedback from a virtual character via their device. The user's emotional state is reflected in this feedback; for example, if the user is tired, they may receive encouragement or guidance to slow down. This emotionally responsive feedback helps users maintain high motivation and supports their continued training.

[0336] Furthermore, users' training results are recorded as points and used to provide rewards. Users can also utilize community features through their devices to share their results with other users and compare rankings. This promotes competition and interaction within the fitness community, creating a system that supports individual users in achieving their fitness goals.

[0337] The following describes the processing flow.

[0338] Step 1:

[0339] The user launches the application on their device, creates an account, and enters personal information and fitness goals.

[0340] Step 2:

[0341] The terminal sends user information and data for the selected virtual character to the server, which then generates a trainer based on this information.

[0342] Step 3:

[0343] The server creates a personalized training plan based on the user's fitness goals and level, and sends it to the device.

[0344] Step 4:

[0345] The terminal displays the training plan received from the server to the user and begins the training guidance. A virtual character introduces the training content to the user.

[0346] Step 5:

[0347] The user begins training, and the device captures the user's facial expressions and voice through its built-in sensors, sending this data to the server as emotion data.

[0348] Step 6:

[0349] The server uses an emotion engine to analyze the user's emotional state and adjusts the content of the feedback and training instructions based on the results.

[0350] Step 7:

[0351] The server sends tailored feedback to the device, which then notifies the user in real time. The feedback includes encouraging messages tailored to the user's emotions and advice on training pace.

[0352] Step 8:

[0353] When the user finishes training, the device records the results and sends that data to the server.

[0354] Step 9:

[0355] The server records the user's training results as points in a database and sends a list of eligible rewards to the user's device.

[0356] Step 10:

[0357] Users can select rewards based on the points they have earned through their devices.

[0358] Step 11:

[0359] Users can enjoy interaction and competition by using the community features on their devices to share their training results with other users and check rankings.

[0360] (Example 2)

[0361] 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".

[0362] Traditional fitness systems often offered standardized programs and feedback that didn't consider emotional states, leading to a lack of user motivation and retention. Furthermore, they struggled to provide personalized instruction tailored to individual needs.

[0363] 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.

[0364] In this invention, the server includes means for generating an individualized exercise plan using an instructor generated based on a virtualized character selected by the user; means for analyzing the user's exercise state and emotional data in real time and providing exercise guidance and immediate feedback according to the emotional state; and means for recording exercise results and managing rewards based on the compensation given to the user. This provides an individually customized exercise plan and allows the user to receive feedback tailored to their own pace and emotions.

[0365] A "coach" is a virtual entity created to provide exercise plans and offer guidance and feedback to users.

[0366] An "exercise plan" refers to a customized training schedule or program based on the user's fitness level and goals.

[0367] "Emotional data" refers to data captured from a user's facial expressions and voice, and is used to analyze the user's emotional state.

[0368] "Instant feedback" refers to advice and evaluations provided instantly based on real-time analysis of the user's physical and emotional state.

[0369] "Rewards" refer to points or rewards that users earn based on their exercise performance, and benefits are managed based on these points.

[0370] "Cooperative features" are functions that help users share their exercise results and interact with other users to promote competition.

[0371] A "detector" refers to a device or sensor used to capture user behavior and emotional data.

[0372] This invention provides a system that personalizes the user's fitness experience and offers feedback that takes their emotional state into consideration. The system is centered around a server, a terminal, and the user, with each component playing a specific role.

[0373] The server generates a virtual instructor character based on user input. The server performs calculations to develop an exercise plan based on the user's selected character, fitness level, and set goals. Furthermore, the server integrates an emotion engine that analyzes the user's emotional data. This analysis allows the server to determine in real time what kind of feedback the user needs during exercise and generate tailored feedback accordingly.

[0374] The device presents the user with the exercise plan and feedback transmitted from the server, and functions as a crucial interface for monitoring the user's movements. The device incorporates multiple sensors to capture the user's facial expressions and voice. This allows the device to continuously accumulate data on the user's emotional state, which is then transmitted to the emotion engine.

[0375] Users receive feedback that reflects their emotional state captured during exercise. For example, if a user is feeling tired, a virtual character on the device might display an encouraging message such as, "Let's slow down the pace a bit during today's workout and keep it fun." In this way, the fitness session provides a supportive experience for the user.

[0376] As a concrete example, the following is an example of an input prompt statement for a generative AI model:

[0377] "Please suggest feedback that corresponds to the emotional state the user is currently displaying. The user is currently feeling tired."

[0378] Through this system, personalized exercise plans and appropriate feedback help maintain user motivation and support the continuation of training.

[0379] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0380] Step 1:

[0381] Users log in via their device and enter their fitness level and goals. The device then sends this information to the server. This information is used as basic data necessary for creating an exercise plan.

[0382] Step 2:

[0383] The server generates a virtual character based on the received user information. Specifically, it identifies a character that matches the user's preferences and builds a coaching model to generate an exercise plan tailored to that character. In this process, the server analyzes the user's input data and calculates the optimal exercise program.

[0384] Step 3:

[0385] After the exercise plan is generated, the server sends this plan to the terminal. The terminal then displays the received plan to the user. The exercise plan includes specific exercises and the set duration.

[0386] Step 4:

[0387] The device uses sensors to capture user emotional data during training. This includes the user's facial expressions and voice data. The collected data is sent to a server, which serves as input for analyzing the emotional state.

[0388] Step 5:

[0389] The server analyzes the received emotional data using an emotion engine. The emotion engine inputs the received data as prompts into an AI model to determine the user's current emotional state. For example, if the server determines that the user is showing signs of fatigue, it generates an encouraging message.

[0390] Step 6:

[0391] The generated feedback is sent from the server to the terminal and communicated to the user. The terminal provides appropriate guidance and support to the user through a virtual character. The feedback includes pacing adjustments and words of encouragement.

[0392] Step 7:

[0393] Once a user completes their exercise, the device records their progress and sends it to the server. The server calculates the reward based on the recorded data and adds points to the user's account. This information is also used later for managing rewards.

[0394] (Application Example 2)

[0395] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0396] In today's industrial environment, there is a demand to maximize the efficiency of robots and their operators working in factories. However, conventional training systems struggle to provide real-time feedback that takes into account the operator's psychological state, which can lead to increased operator stress. Furthermore, there is a lack of mechanisms to effectively manage work results and promote competition.

[0397] 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.

[0398] In this invention, the server includes means for generating individual training plans using instructors generated based on virtualized characters selected by the user; means for analyzing the user's work in real time and providing immediate guidance according to the training execution status; means for adjusting feedback provided by an emotion engine that recognizes the user's emotions and presenting encouragement from the virtual character according to the operator's psychological state; means for recording work results and managing rewards based on performance points awarded to the user; and means for providing collective functions to share results among users and promote competition. This makes it possible to improve work efficiency and enhance competitiveness while taking into account the operator's psychological state, and to reduce stress in the work environment.

[0399] A "user-selected virtual character" is a digital virtual entity generated based on user instructions, which functions as an instructor providing an individualized training plan.

[0400] An "individualized training plan" is a learning or work schedule customized to each user's specific needs and goals.

[0401] An "emotion engine" is a technology that analyzes the user's emotional state and adjusts feedback based on that data.

[0402] "Feedback adjustment" is a process that dynamically changes the information and support provided by the virtual instructor according to the user's emotions and work status.

[0403] "The operator's psychological state" refers to the operator's mental state, including their stress level and mood during the operation.

[0404] "Work results" refer to the specific achievements and progress obtained as a result of the work or training activities performed by the user.

[0405] "Performance points" are numerical values ​​or points calculated based on the user's work output and used for rewards and comparisons between users.

[0406] "Collective functions" refer to systems that provide platforms and features for users to share results and compete with each other.

[0407] This invention is a system for improving the work efficiency of operators and robots in a factory. The system uses a virtualized character to provide operators with individualized training plans, analyzes the operators' emotional state, and adjusts feedback to suit the situation.

[0408] The server generates a personalized training plan based on the virtual character selected by the pilot. This plan is customized to the pilot's experience and goals. The server uses Python and Flask, enabling it to provide plans in real time.

[0409] The device is equipped with sensors to capture the user's facial expressions and voice, and sends this data to an emotion engine. This engine uses OpenCV and TensorFlow to analyze the user's emotions and can receive feedback from a server according to that state.

[0410] Users receive real-time feedback from virtual characters via their smartphones or tablets. For example, if they feel tired while working, the character will notify them with an encouraging message such as, "You'll be able to take a break soon. Keep going!"

[0411] Such a system makes it easier for operators to maintain high motivation and improve work efficiency. An example of a prompt message is: "Create feedback based on the operator's emotional data and display an encouraging message through the virtual character."

[0412] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0413] Step 1:

[0414] The server generates individual training plans based on the virtual character selected by the user. It receives user-selected character information, past work history, and target data as input, analyzes this information, and outputs a customized training plan. Specifically, it uses Python or Flask to perform calculations that build a plan optimized for the user in real time.

[0415] Step 2:

[0416] The device uses sensors to capture the user's facial expressions and voice. Based on this input data, an emotion engine performs emotion analysis. Using OpenCV and TensorFlow, it recognizes changes in facial expressions and voice tone from image and audio data, and outputs numerical emotion data.

[0417] Step 3:

[0418] The emotion engine sends the analyzed emotion data to the server. The server then processes the feedback based on the received emotion data. For example, if the emotion data indicates fatigue, the server will output encouraging messages or instructions regarding work pace.

[0419] Step 4:

[0420] The user receives feedback via their device. Feedback, which is output from the server, is sent to the device and displayed on the screen through a virtual character. Specifically, the screen display changes according to the feedback content, and the user is guided to the next step based on their actions.

[0421] Step 5:

[0422] The server records user work output and calculates performance points. It takes user work data as input, scores it based on predetermined criteria, and outputs the result as performance points. These performance points are then used in subsequent reward systems and user comparisons.

[0423] Step 6:

[0424] The device provides a collective function for sharing information with other users. It uses user performance data as input, shares it with other users via the network, and performs specific actions to promote competition by outputting rankings and comment functions.

[0425] 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.

[0426] 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.

[0427] 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.

[0428] [Third Embodiment]

[0429] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0430] 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.

[0431] 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).

[0432] 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.

[0433] 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.

[0434] 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).

[0435] 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.

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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".

[0441] This invention relates to an embodiment of an online system in which a user selects a virtualized character as a trainer and is provided with a personalized fitness plan. The system consists of three main components: a server, a terminal, and a user.

[0442] The server generates a trainer based on the virtualized character selected by the user. The trainer creates a personalized fitness plan for the user and sends it to the device. This plan is customized according to the user's goals and fitness level, and incorporates appropriate exercises. The server also receives the user's training data and provides analysis results, sending real-time feedback to the device.

[0443] The device functions as an interface for the user, displaying the fitness plan received from the server. A virtual trainer character guides the user through the plan and supports their training progress. The user's exercise is recorded via the device's camera and transmitted to the server in real time. The device immediately notifies the user of the feedback received from the server, encouraging them to improve their training.

[0444] Users perform training based on fitness plans received via their devices. During training, they receive feedback and encouragement from virtual characters to maintain motivation. Users also accumulate points for completing specific exercises, which can be used to earn rewards within the system. Furthermore, community features allow users to share their progress with other users and compare rankings.

[0445] For example, if a user sets "establishing healthy lifestyle habits" as their goal, the system will suggest a plan including aerobic exercise and stretching, tailored to the user's fitness level. During this time, a selected character will deliver encouraging messages, ensuring the user remains motivated throughout the exercise. At the end of each training session, the user receives detailed feedback on how many calories they burned and the results of their exercise. In this way, users can increase their awareness of fitness and be helped to lead a healthier life.

[0446] The following describes the processing flow.

[0447] Step 1:

[0448] The user launches the application on their device, enters their user information, and creates an account.

[0449] Step 2:

[0450] The terminal sends user information to the server, and the server stores that information in a database.

[0451] Step 3:

[0452] Users can select their preferred virtual character and set them as their training trainer.

[0453] Step 4:

[0454] The server considers the user's fitness level and goals, and generates a personalized fitness plan based on the selected character.

[0455] Step 5:

[0456] The server generates a fitness plan and sends it to the device, which then displays it to the user.

[0457] Step 6:

[0458] The user follows their fitness plan and begins training, and the device records the user's exercise via its camera.

[0459] Step 7:

[0460] The device analyzes exercise data in real time and sends the results to the server.

[0461] Step 8:

[0462] The server generates feedback based on the received data and sends it to the terminal.

[0463] Step 9:

[0464] The terminal notifies the user of feedback received from the server, informing them of areas for improvement in the next training session.

[0465] Step 10:

[0466] The server records the training results and awards points to the user.

[0467] Step 11:

[0468] When users use their accumulated points to obtain rewards, they select the rewards via their device.

[0469] Step 12:

[0470] Users utilize community features to share their achievements and rankings with other users using their devices.

[0471] (Example 1)

[0472] 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."

[0473] In today's world, there is a need for systems that easily provide training plans tailored to individual fitness needs. Furthermore, there is a lack of means to analyze users' training data in real time and provide immediate feedback, making it difficult to maintain motivation. Additionally, there is a need for a system that efficiently integrates features to promote mutual communication among users and foster a sense of competition.

[0474] 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.

[0475] In this invention, the server includes means for generating a trainer based on a virtualized character selected by the user and creating an individualized training plan using a generation AI model; means for analyzing the user's exercise in real time and generating immediate feedback according to the training performance using the generation AI model; and means for recording training results and managing rewards based on a reward system granted to the user. This enables personalized training guidance for users, improves motivation through real-time feedback and a reward system, and provides a system that promotes communication and competition among users.

[0476] A "user-selected virtualized character" is a digital representation of a person or animal that the user can select as an image or computer-generated image from the system's interface, and which serves as a trainer.

[0477] "Generating a trainer" means creating an interactive program based on a selected virtual character, in which that character presents and supports the user with a fitness plan.

[0478] A "generative AI model" is an artificial intelligence algorithm designed to produce specific outputs or predictions based on user input and historical data.

[0479] A "training plan" is a detailed plan that schedules and sequentially performs specific exercises and activities according to the fitness goals that the user wants to achieve.

[0480] "Real-time analysis" means instantly converting a user's exercise or activity into data in its original state, and immediately processing and analyzing this information.

[0481] "Immediate feedback" refers to advice and evaluations provided in real time during training, including information on areas for improvement and encouragement that users can gain while exercising.

[0482] A "reward system" is a mechanism in which points or rewards are awarded to users based on the results and actions they achieve during training, and it is a means of promoting increased motivation.

[0483] "Community features" are functions that enable users to share their achievements, communicate, and compete with each other within the system.

[0484] This invention provides a specific embodiment of an online system in which a user selects a virtualized character and is provided with a personalized fitness plan using that character as a trainer. The system consists of three main components: a server, a terminal, and a user.

[0485] The server generates a trainer based on a virtual character selected by the user through their terminal. The software used here is a generation AI model, which creates a customized fitness plan tailored to the user's fitness goals and fitness level. During this process, the server prompts the AI ​​model with a message such as, "Generate the optimal training plan for the user's health goals," and obtains a suitable plan. The server also receives and analyzes the user's training data in real time to generate immediate feedback, which is then sent to the terminal.

[0486] The terminal plays the role of providing the user with an interface to this system. It displays the fitness plan received from the server to the user, and a virtual trainer guides the user through the training on the screen. The terminal is equipped with a camera that records the user's exercise in real time and sends that data to the server. The terminal also notifies the user of immediate feedback from the server to support exercise improvement and motivation maintenance.

[0487] Users train according to fitness plans received via their devices. During training, they receive feedback and encouraging messages from a virtual trainer, helping them stay motivated towards achieving their goals. Each time they complete a specific exercise, users earn points based on a reward system, which they can then redeem for rewards within the system. Furthermore, users can use the community feature to share their progress with other users and check rankings.

[0488] For example, if a user sets "weight loss" as their goal, the server uses a generative AI model to generate a plan and provides a menu that combines cardio and strength training. The virtual trainer provides specific instructions such as, "Today's target calorie expenditure is 500," and after the training, provides feedback such as, "Congratulations, you have achieved your goal."

[0489] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0490] Step 1:

[0491] The user logs into the system using their device and selects a trainer from a list of virtualized characters. The input is the user's character selection, and the output is the information of the selected character. This information is sent to the server via the device. Specifically, the user confirms their character selection by tapping on the options on the screen.

[0492] Step 2:

[0493] The server generates a trainer using character information received from the terminal. The input is character information and basic user information, and the output is the generated virtual trainer. In this process, the character's attributes are input to the AI ​​model as a prompt message, "Generate an appropriate training plan based on the selected character," and the trainer is generated.

[0494] Step 3:

[0495] The server creates a training plan based on the user's goals and current fitness level. Inputs include the user's goals, fitness level, and trainer information, while output is a personalized fitness plan. During data processing, a generative AI model incorporates exercises and other elements appropriate to the user's goals into the plan. The server then sends this plan to the user's device.

[0496] Step 4:

[0497] The terminal displays the fitness plan received from the server to the user. The input is the fitness plan, and the output is a visual display of the plan. Specifically, the screen displays the training steps and their details, and a virtual trainer provides instructions via voice or text.

[0498] Step 5:

[0499] The user begins training through the device. The user's movements are recorded in real time using the device's camera function. The input is the user's real-time movement data, and the output is the recorded movement data. The device sends this data to the server.

[0500] Step 6:

[0501] The server analyzes training data sent by the user. The input is motion data, and the output is generated feedback. As a data processing step, the server uses a generative AI model to evaluate the motion, analyze areas for improvement and successes, and generate real-time feedback.

[0502] Step 7:

[0503] The device receives feedback from the server and notifies the user. The input is the content of the feedback, and the output is the notification information for the user. Specifically, feedback is displayed via on-screen pop-ups and audio guidance to encourage the user to improve their exercise.

[0504] Step 8:

[0505] Users review the results of their training sessions and receive points as rewards. Input is point information based on training performance, and output is rewards based on the reward system. Users can also take actions necessary to share their results within the community.

[0506] (Application Example 1)

[0507] 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."

[0508] While modern fitness programs are becoming increasingly personalized, maintaining motivation is difficult, and the lack of real-time feedback to users can hinder the maximization of training effectiveness. Furthermore, limited means for users to maintain motivation and visualize their progress highlight the need to improve the user experience.

[0509] 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.

[0510] In this invention, the server includes means for generating an individualized training plan using a trainer generated based on a virtualized character selected by the user; means for the virtual trainer to provide real-time feedback and exercise movements through a visual display device; and means for analyzing the user's movements in real time and providing immediate feedback according to the training performance. This enables the user to effectively perform individualized training while receiving real-time feedback and increasing their motivation.

[0511] A "user" is an individual who selects a virtualized character and receives a fitness plan.

[0512] A "virtualized character" is a digital character that a user can select and that functions as a trainer.

[0513] A "trainer" is a fitness instructor who is generated based on a virtualized character selected by the user.

[0514] An "individualized training plan" is an exercise program customized according to the user's goals and fitness level.

[0515] A "visual display device" is a device that allows a virtual trainer to visually demonstrate exercise movements and provide feedback, and includes smart glasses and head-mounted displays.

[0516] "Real-time feedback" is a process that analyzes the user's movement patterns and provides appropriate information immediately.

[0517] "Evaluation" refers to a numerical display or points awarded based on the results and progress a user achieves during training.

[0518] The "information sharing function" is a feature that allows users to compare and share their training results and progress with other users.

[0519] The system for implementing this invention consists of a server in a cloud environment, terminals including smart glasses or head-mounted displays, and a user who operates them. The server generates an individualized training plan based on a virtual character selected by the user and instructs the user on it via a visual display device. Specifically, the server uses an AI model to analyze the user's goals and fitness level, and uses Unity to design real-time feedback from the virtual trainer.

[0520] The system utilizes smart glasses, allowing users to visually view a virtual trainer while training. Using TensorFlow, the glasses' built-in camera analyzes the user's movements, instantly sending data to a server for immediate feedback on exercise errors and areas for improvement. This enables users to train efficiently while receiving encouragement from their virtual trainer.

[0521] For example, if a user sets "improving flexibility" as their goal, the server will create a plan centered around stretching movements. While the user is training, the virtual trainer will provide real-time feedback such as, "Straighten your back and move a little more slowly." An example of a prompt would be, "The virtual trainer will monitor the degree of knee flexion and provide specific instructions to encourage further improvement."

[0522] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0523] Step 1:

[0524] The server receives a virtual character selected by the user and individual fitness goals. The input includes the user's goals and character selection data, and a generative AI model is used to generate a training plan based on this data. The output is a user-specific training plan. The server uses Unity to configure this plan and prepares it for transmission to the device.

[0525] Step 2:

[0526] The terminal displays individual training plans and virtual character information received from the server. The input is fitness plan data from the server, which is then visualized and presented to the user. The virtual trainer provides exercise instructions in real time through the visual display device. The output is a screen display for the user to visually understand.

[0527] Step 3:

[0528] The user performs exercises according to the displayed instructions. The device's camera captures the user's movements, and TensorFlow is used to analyze whether the exercises are being performed correctly. The input includes the captured image data, and by analyzing this data, information on the accuracy of the movements is generated. The output provides information for detailed feedback on the user's movements.

[0529] Step 4:

[0530] The server receives motion information sent from the terminal and generates real-time feedback based on the analysis results. User motion analysis data is used as input, and the AI ​​model calculates the optimal feedback. The output is a message of improvement and encouragement, and the feedback is immediately sent back to the terminal and delivered to the user.

[0531] Step 5:

[0532] Users adjust their exercises based on the feedback they receive and earn points upon completion of specific exercises. Input is feedback from the server, and output is updated point information and actions taken in response to further instructions for improvement. Users continuously improve their training by repeating this process.

[0533] 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.

[0534] This invention enhances the fitness experience by combining a personalized training system using virtualized characters with an emotion engine that recognizes user emotions. The system is centered around a server, terminals, and users, with each component playing a specific role.

[0535] The server generates a trainer based on the user's selected virtual character and provides a personalized training plan tailored to the user's fitness level and goals. This creates a customized program to meet the user's specific fitness needs. The server also incorporates an emotion engine that analyzes emotional data sent by the user and adjusts the feedback accordingly.

[0536] The terminal displays the training plan sent from the server to the user and also functions as an interface for monitoring the user during training. The terminal is equipped with sensors that capture the user's facial expressions and voice, and this data is sent to the emotion engine to understand the user's emotional state. Once the user's emotions are analyzed, feedback and training guidance are appropriately adjusted based on that information.

[0537] As users train, they receive feedback from a virtual character via their device. The user's emotional state is reflected in this feedback; for example, if the user is tired, they may receive encouragement or guidance to slow down. This emotionally responsive feedback helps users maintain high motivation and supports their continued training.

[0538] Furthermore, users' training results are recorded as points and used to provide rewards. Users can also utilize community features through their devices to share their results with other users and compare rankings. This promotes competition and interaction within the fitness community, creating a system that supports individual users in achieving their fitness goals.

[0539] The following describes the processing flow.

[0540] Step 1:

[0541] The user launches the application on their device, creates an account, and enters personal information and fitness goals.

[0542] Step 2:

[0543] The terminal sends user information and data for the selected virtual character to the server, which then generates a trainer based on this information.

[0544] Step 3:

[0545] The server creates a personalized training plan based on the user's fitness goals and level, and sends it to the device.

[0546] Step 4:

[0547] The terminal displays the training plan received from the server to the user and begins the training guidance. A virtual character introduces the training content to the user.

[0548] Step 5:

[0549] The user begins training, and the device captures the user's facial expressions and voice through its built-in sensors, sending this data to the server as emotion data.

[0550] Step 6:

[0551] The server uses an emotion engine to analyze the user's emotional state and adjusts the content of the feedback and training instructions based on the results.

[0552] Step 7:

[0553] The server sends tailored feedback to the device, which then notifies the user in real time. The feedback includes encouraging messages tailored to the user's emotions and advice on training pace.

[0554] Step 8:

[0555] When the user finishes training, the device records the results and sends that data to the server.

[0556] Step 9:

[0557] The server records the user's training results as points in a database and sends a list of eligible rewards to the user's device.

[0558] Step 10:

[0559] Users can select rewards based on the points they have earned through their devices.

[0560] Step 11:

[0561] Users can enjoy interaction and competition by using the community features on their devices to share their training results with other users and check rankings.

[0562] (Example 2)

[0563] 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."

[0564] Traditional fitness systems often offered standardized programs and feedback that didn't consider emotional states, leading to a lack of user motivation and retention. Furthermore, they struggled to provide personalized instruction tailored to individual needs.

[0565] 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.

[0566] In this invention, the server includes means for generating an individualized exercise plan using an instructor generated based on a virtualized character selected by the user; means for analyzing the user's exercise state and emotional data in real time and providing exercise guidance and immediate feedback according to the emotional state; and means for recording exercise results and managing rewards based on the compensation given to the user. This provides an individually customized exercise plan and allows the user to receive feedback tailored to their own pace and emotions.

[0567] A "coach" is a virtual entity created to provide exercise plans and offer guidance and feedback to users.

[0568] An "exercise plan" refers to a customized training schedule or program based on the user's fitness level and goals.

[0569] "Emotional data" refers to data captured from a user's facial expressions and voice, and is used to analyze the user's emotional state.

[0570] "Instant feedback" refers to advice and evaluations provided instantly based on real-time analysis of the user's physical and emotional state.

[0571] "Rewards" refer to points or rewards that users earn based on their exercise performance, and benefits are managed based on these points.

[0572] "Cooperative features" are functions that help users share their exercise results and interact with other users to promote competition.

[0573] A "detector" refers to a device or sensor used to capture user behavior and emotional data.

[0574] This invention provides a system that personalizes the user's fitness experience and offers feedback that takes their emotional state into consideration. The system is centered around a server, a terminal, and the user, with each component playing a specific role.

[0575] The server generates a virtual instructor character based on user input. The server performs calculations to develop an exercise plan based on the user's selected character, fitness level, and set goals. Furthermore, the server integrates an emotion engine that analyzes the user's emotional data. This analysis allows the server to determine in real time what kind of feedback the user needs during exercise and generate tailored feedback accordingly.

[0576] The device presents the user with the exercise plan and feedback transmitted from the server, and functions as a crucial interface for monitoring the user's movements. The device incorporates multiple sensors to capture the user's facial expressions and voice. This allows the device to continuously accumulate data on the user's emotional state, which is then transmitted to the emotion engine.

[0577] Users receive feedback that reflects their emotional state captured during exercise. For example, if a user is feeling tired, a virtual character on the device might display an encouraging message such as, "Let's slow down the pace a bit during today's workout and keep it fun." In this way, the fitness session provides a supportive experience for the user.

[0578] As a concrete example, the following is an example of an input prompt statement for a generative AI model:

[0579] "Please suggest feedback that corresponds to the emotional state the user is currently displaying. The user is currently feeling tired."

[0580] Through this system, personalized exercise plans and appropriate feedback help maintain user motivation and support the continuation of training.

[0581] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0582] Step 1:

[0583] Users log in via their device and enter their fitness level and goals. The device then sends this information to the server. This information is used as basic data necessary for creating an exercise plan.

[0584] Step 2:

[0585] The server generates a virtual character based on the received user information. Specifically, it identifies a character that matches the user's preferences and builds a coaching model to generate an exercise plan tailored to that character. In this process, the server analyzes the user's input data and calculates the optimal exercise program.

[0586] Step 3:

[0587] After the exercise plan is generated, the server sends this plan to the terminal. The terminal then displays the received plan to the user. The exercise plan includes specific exercises and the set duration.

[0588] Step 4:

[0589] The device uses sensors to capture user emotional data during training. This includes the user's facial expressions and voice data. The collected data is sent to a server, which serves as input for analyzing the emotional state.

[0590] Step 5:

[0591] The server analyzes the received emotional data using an emotion engine. The emotion engine inputs the received data as prompts into an AI model to determine the user's current emotional state. For example, if the server determines that the user is showing signs of fatigue, it generates an encouraging message.

[0592] Step 6:

[0593] The generated feedback is sent from the server to the terminal and communicated to the user. The terminal provides appropriate guidance and support to the user through a virtual character. The feedback includes pacing adjustments and words of encouragement.

[0594] Step 7:

[0595] Once a user completes their exercise, the device records their progress and sends it to the server. The server calculates the reward based on the recorded data and adds points to the user's account. This information is also used later for managing rewards.

[0596] (Application Example 2)

[0597] 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."

[0598] In today's industrial environment, there is a demand to maximize the efficiency of robots and their operators working in factories. However, conventional training systems struggle to provide real-time feedback that takes into account the operator's psychological state, which can lead to increased operator stress. Furthermore, there is a lack of mechanisms to effectively manage work results and promote competition.

[0599] 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.

[0600] In this invention, the server includes means for generating individual training plans using instructors generated based on virtualized characters selected by the user; means for analyzing the user's work in real time and providing immediate guidance according to the training execution status; means for adjusting feedback provided by an emotion engine that recognizes the user's emotions and presenting encouragement from the virtual character according to the operator's psychological state; means for recording work results and managing rewards based on performance points awarded to the user; and means for providing collective functions to share results among users and promote competition. This makes it possible to improve work efficiency and enhance competitiveness while taking into account the operator's psychological state, and to reduce stress in the work environment.

[0601] A "user-selected virtual character" is a digital virtual entity generated based on user instructions, which functions as an instructor providing an individualized training plan.

[0602] An "individualized training plan" is a learning or work schedule customized to each user's specific needs and goals.

[0603] An "emotion engine" is a technology that analyzes the user's emotional state and adjusts feedback based on that data.

[0604] "Feedback adjustment" is a process that dynamically changes the information and support provided by the virtual instructor according to the user's emotions and work status.

[0605] "The operator's psychological state" refers to the operator's mental state, including their stress level and mood during the operation.

[0606] "Work results" refer to the specific achievements and progress obtained as a result of the work or training activities performed by the user.

[0607] "Performance points" are numerical values ​​or points calculated based on the user's work output and used for rewards and comparisons between users.

[0608] "Collective functions" refer to systems that provide platforms and features for users to share results and compete with each other.

[0609] This invention is a system for improving the work efficiency of operators and robots in a factory. The system uses a virtualized character to provide operators with individualized training plans, analyzes the operators' emotional state, and adjusts feedback to suit the situation.

[0610] The server generates a personalized training plan based on the virtual character selected by the pilot. This plan is customized to the pilot's experience and goals. The server uses Python and Flask, enabling it to provide plans in real time.

[0611] The device is equipped with sensors to capture the user's facial expressions and voice, and sends this data to an emotion engine. This engine uses OpenCV and TensorFlow to analyze the user's emotions and can receive feedback from a server according to that state.

[0612] Users receive real-time feedback from virtual characters via their smartphones or tablets. For example, if they feel tired while working, the character will notify them with an encouraging message such as, "You'll be able to take a break soon. Keep going!"

[0613] Such a system makes it easier for operators to maintain high motivation and improve work efficiency. An example of a prompt message is: "Create feedback based on the operator's emotional data and display an encouraging message through the virtual character."

[0614] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0615] Step 1:

[0616] The server generates individual training plans based on the virtual character selected by the user. It receives user-selected character information, past work history, and target data as input, analyzes this information, and outputs a customized training plan. Specifically, it uses Python or Flask to perform calculations that build a plan optimized for the user in real time.

[0617] Step 2:

[0618] The device uses sensors to capture the user's facial expressions and voice. Based on this input data, an emotion engine performs emotion analysis. Using OpenCV and TensorFlow, it recognizes changes in facial expressions and voice tone from image and audio data, and outputs numerical emotion data.

[0619] Step 3:

[0620] The emotion engine sends the analyzed emotion data to the server. The server then processes the feedback based on the received emotion data. For example, if the emotion data indicates fatigue, the server will output encouraging messages or instructions regarding work pace.

[0621] Step 4:

[0622] The user receives feedback via their device. Feedback, which is output from the server, is sent to the device and displayed on the screen through a virtual character. Specifically, the screen display changes according to the feedback content, and the user is guided to the next step based on their actions.

[0623] Step 5:

[0624] The server records user work output and calculates performance points. It takes user work data as input, scores it based on predetermined criteria, and outputs the result as performance points. These performance points are then used in subsequent reward systems and user comparisons.

[0625] Step 6:

[0626] The device provides a collective function for sharing information with other users. It uses user performance data as input, shares it with other users via the network, and performs specific actions to promote competition by outputting rankings and comment functions.

[0627] 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.

[0628] 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.

[0629] 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.

[0630] [Fourth Embodiment]

[0631] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0632] 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.

[0633] 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).

[0634] 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.

[0635] 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.

[0636] 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).

[0637] 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.

[0638] 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.

[0639] 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.

[0640] 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.

[0641] 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.

[0642] 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.

[0643] 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".

[0644] This invention relates to an embodiment of an online system in which a user selects a virtualized character as a trainer and is provided with a personalized fitness plan. The system consists of three main components: a server, a terminal, and a user.

[0645] The server generates a trainer based on the virtualized character selected by the user. The trainer creates a personalized fitness plan for the user and sends it to the device. This plan is customized according to the user's goals and fitness level, and incorporates appropriate exercises. The server also receives the user's training data and provides analysis results, sending real-time feedback to the device.

[0646] The device functions as an interface for the user, displaying the fitness plan received from the server. A virtual trainer character guides the user through the plan and supports their training progress. The user's exercise is recorded via the device's camera and transmitted to the server in real time. The device immediately notifies the user of the feedback received from the server, encouraging them to improve their training.

[0647] Users perform training based on fitness plans received via their devices. During training, they receive feedback and encouragement from virtual characters to maintain motivation. Users also accumulate points for completing specific exercises, which can be used to earn rewards within the system. Furthermore, community features allow users to share their progress with other users and compare rankings.

[0648] For example, if a user sets "establishing healthy lifestyle habits" as their goal, the system will suggest a plan including aerobic exercise and stretching, tailored to the user's fitness level. During this time, a selected character will deliver encouraging messages, ensuring the user remains motivated throughout the exercise. At the end of each training session, the user receives detailed feedback on how many calories they burned and the results of their exercise. In this way, users can increase their awareness of fitness and be helped to lead a healthier life.

[0649] The following describes the processing flow.

[0650] Step 1:

[0651] The user launches the application on their device, enters their user information, and creates an account.

[0652] Step 2:

[0653] The terminal sends user information to the server, and the server stores that information in a database.

[0654] Step 3:

[0655] Users can select their preferred virtual character and set them as their training trainer.

[0656] Step 4:

[0657] The server considers the user's fitness level and goals, and generates a personalized fitness plan based on the selected character.

[0658] Step 5:

[0659] The server generates a fitness plan and sends it to the device, which then displays it to the user.

[0660] Step 6:

[0661] The user follows their fitness plan and begins training, and the device records the user's exercise via its camera.

[0662] Step 7:

[0663] The device analyzes exercise data in real time and sends the results to the server.

[0664] Step 8:

[0665] The server generates feedback based on the received data and sends it to the terminal.

[0666] Step 9:

[0667] The terminal notifies the user of feedback received from the server, informing them of areas for improvement in the next training session.

[0668] Step 10:

[0669] The server records the training results and awards points to the user.

[0670] Step 11:

[0671] When users use their accumulated points to obtain rewards, they select the rewards via their device.

[0672] Step 12:

[0673] Users utilize community features to share their achievements and rankings with other users using their devices.

[0674] (Example 1)

[0675] 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".

[0676] In today's world, there is a need for systems that easily provide training plans tailored to individual fitness needs. Furthermore, there is a lack of means to analyze users' training data in real time and provide immediate feedback, making it difficult to maintain motivation. Additionally, there is a need for a system that efficiently integrates features to promote mutual communication among users and foster a sense of competition.

[0677] 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.

[0678] In this invention, the server includes means for generating a trainer based on a virtualized character selected by the user and creating an individualized training plan using a generation AI model; means for analyzing the user's exercise in real time and generating immediate feedback according to the training performance using the generation AI model; and means for recording training results and managing rewards based on a reward system granted to the user. This enables personalized training guidance for users, improves motivation through real-time feedback and a reward system, and provides a system that promotes communication and competition among users.

[0679] A "user-selected virtualized character" is a digital representation of a person or animal that the user can select as an image or computer-generated image from the system's interface, and which serves as a trainer.

[0680] "Generating a trainer" means creating an interactive program based on a selected virtual character, in which that character presents and supports the user with a fitness plan.

[0681] A "generative AI model" is an artificial intelligence algorithm designed to produce specific outputs or predictions based on user input and historical data.

[0682] A "training plan" is a detailed plan that schedules and sequentially performs specific exercises and activities according to the fitness goals that the user wants to achieve.

[0683] "Real-time analysis" means instantly converting a user's exercise or activity into data in its original state, and immediately processing and analyzing this information.

[0684] "Immediate feedback" refers to advice and evaluations provided in real time during training, including information on areas for improvement and encouragement that users can gain while exercising.

[0685] A "reward system" is a mechanism in which points or rewards are awarded to users based on the results and actions they achieve during training, and it is a means of promoting increased motivation.

[0686] "Community features" are functions that enable users to share their achievements, communicate, and compete with each other within the system.

[0687] This invention provides a specific embodiment of an online system in which a user selects a virtualized character and is provided with a personalized fitness plan using that character as a trainer. The system consists of three main components: a server, a terminal, and a user.

[0688] The server generates a trainer based on a virtual character selected by the user through their terminal. The software used here is a generation AI model, which creates a customized fitness plan tailored to the user's fitness goals and fitness level. During this process, the server prompts the AI ​​model with a message such as, "Generate the optimal training plan for the user's health goals," and obtains a suitable plan. The server also receives and analyzes the user's training data in real time to generate immediate feedback, which is then sent to the terminal.

[0689] The terminal plays the role of providing the user with an interface to this system. It displays the fitness plan received from the server to the user, and a virtual trainer guides the user through the training on the screen. The terminal is equipped with a camera that records the user's exercise in real time and sends that data to the server. The terminal also notifies the user of immediate feedback from the server to support exercise improvement and motivation maintenance.

[0690] Users train according to fitness plans received via their devices. During training, they receive feedback and encouraging messages from a virtual trainer, helping them stay motivated towards achieving their goals. Each time they complete a specific exercise, users earn points based on a reward system, which they can then redeem for rewards within the system. Furthermore, users can use the community feature to share their progress with other users and check rankings.

[0691] For example, if a user sets "weight loss" as their goal, the server uses a generative AI model to generate a plan and provides a menu that combines cardio and strength training. The virtual trainer provides specific instructions such as, "Today's target calorie expenditure is 500," and after the training, provides feedback such as, "Congratulations, you have achieved your goal."

[0692] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0693] Step 1:

[0694] The user logs into the system using their device and selects a trainer from a list of virtualized characters. The input is the user's character selection, and the output is the information of the selected character. This information is sent to the server via the device. Specifically, the user confirms their character selection by tapping on the options on the screen.

[0695] Step 2:

[0696] The server generates a trainer using character information received from the terminal. The input is character information and basic user information, and the output is the generated virtual trainer. In this process, the character's attributes are input to the AI ​​model as a prompt message, "Generate an appropriate training plan based on the selected character," and the trainer is generated.

[0697] Step 3:

[0698] The server creates a training plan based on the user's goals and current fitness level. Inputs include the user's goals, fitness level, and trainer information, while output is a personalized fitness plan. During data processing, a generative AI model incorporates exercises and other elements appropriate to the user's goals into the plan. The server then sends this plan to the user's device.

[0699] Step 4:

[0700] The terminal displays the fitness plan received from the server to the user. The input is the fitness plan, and the output is a visual display of the plan. Specifically, the screen displays the training steps and their details, and a virtual trainer provides instructions via voice or text.

[0701] Step 5:

[0702] The user begins training through the device. The user's movements are recorded in real time using the device's camera function. The input is the user's real-time movement data, and the output is the recorded movement data. The device sends this data to the server.

[0703] Step 6:

[0704] The server analyzes training data sent by the user. The input is motion data, and the output is generated feedback. As a data processing step, the server uses a generative AI model to evaluate the motion, analyze areas for improvement and successes, and generate real-time feedback.

[0705] Step 7:

[0706] The device receives feedback from the server and notifies the user. The input is the content of the feedback, and the output is the notification information for the user. Specifically, feedback is displayed via on-screen pop-ups and audio guidance to encourage the user to improve their exercise.

[0707] Step 8:

[0708] Users review the results of their training sessions and receive points as rewards. Input is point information based on training performance, and output is rewards based on the reward system. Users can also take actions necessary to share their results within the community.

[0709] (Application Example 1)

[0710] 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".

[0711] While modern fitness programs are becoming increasingly personalized, maintaining motivation is difficult, and the lack of real-time feedback to users can hinder the maximization of training effectiveness. Furthermore, limited means for users to maintain motivation and visualize their progress highlight the need to improve the user experience.

[0712] 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.

[0713] In this invention, the server includes means for generating an individualized training plan using a trainer generated based on a virtualized character selected by the user; means for the virtual trainer to provide real-time feedback and exercise movements through a visual display device; and means for analyzing the user's movements in real time and providing immediate feedback according to the training performance. This enables the user to effectively perform individualized training while receiving real-time feedback and increasing their motivation.

[0714] A "user" is an individual who selects a virtualized character and receives a fitness plan.

[0715] A "virtualized character" is a digital character that a user can select and that functions as a trainer.

[0716] A "trainer" is a fitness instructor who is generated based on a virtualized character selected by the user.

[0717] An "individualized training plan" is an exercise program customized according to the user's goals and fitness level.

[0718] A "visual display device" is a device that allows a virtual trainer to visually demonstrate exercise movements and provide feedback, and includes smart glasses and head-mounted displays.

[0719] "Real-time feedback" is a process that analyzes the user's movement patterns and provides appropriate information immediately.

[0720] "Evaluation" refers to a numerical display or points awarded based on the results and progress a user achieves during training.

[0721] The "information sharing function" is a feature that allows users to compare and share their training results and progress with other users.

[0722] The system for implementing this invention consists of a server in a cloud environment, terminals including smart glasses or head-mounted displays, and a user who operates them. The server generates an individualized training plan based on a virtual character selected by the user and instructs the user on it via a visual display device. Specifically, the server uses an AI model to analyze the user's goals and fitness level, and uses Unity to design real-time feedback from the virtual trainer.

[0723] The system utilizes smart glasses, allowing users to visually view a virtual trainer while training. Using TensorFlow, the glasses' built-in camera analyzes the user's movements, instantly sending data to a server for immediate feedback on exercise errors and areas for improvement. This enables users to train efficiently while receiving encouragement from their virtual trainer.

[0724] For example, if a user sets "improving flexibility" as their goal, the server will create a plan centered around stretching movements. While the user is training, the virtual trainer will provide real-time feedback such as, "Straighten your back and move a little more slowly." An example of a prompt would be, "The virtual trainer will monitor the degree of knee flexion and provide specific instructions to encourage further improvement."

[0725] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0726] Step 1:

[0727] The server receives a virtual character selected by the user and individual fitness goals. The input includes the user's goals and character selection data, and a generative AI model is used to generate a training plan based on this data. The output is a user-specific training plan. The server uses Unity to configure this plan and prepares it for transmission to the device.

[0728] Step 2:

[0729] The terminal displays individual training plans and virtual character information received from the server. The input is fitness plan data from the server, which is then visualized and presented to the user. The virtual trainer provides exercise instructions in real time through the visual display device. The output is a screen display for the user to visually understand.

[0730] Step 3:

[0731] The user performs exercises according to the displayed instructions. The device's camera captures the user's movements, and TensorFlow is used to analyze whether the exercises are being performed correctly. The input includes the captured image data, and by analyzing this data, information on the accuracy of the movements is generated. The output provides information for detailed feedback on the user's movements.

[0732] Step 4:

[0733] The server receives motion information sent from the terminal and generates real-time feedback based on the analysis results. User motion analysis data is used as input, and the AI ​​model calculates the optimal feedback. The output is a message of improvement and encouragement, and the feedback is immediately sent back to the terminal and delivered to the user.

[0734] Step 5:

[0735] Users adjust their exercises based on the feedback they receive and earn points upon completion of specific exercises. Input is feedback from the server, and output is updated point information and actions taken in response to further instructions for improvement. Users continuously improve their training by repeating this process.

[0736] 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.

[0737] This invention enhances the fitness experience by combining a personalized training system using virtualized characters with an emotion engine that recognizes user emotions. The system is centered around a server, terminals, and users, with each component playing a specific role.

[0738] The server generates a trainer based on the user's selected virtual character and provides a personalized training plan tailored to the user's fitness level and goals. This creates a customized program to meet the user's specific fitness needs. The server also incorporates an emotion engine that analyzes emotional data sent by the user and adjusts the feedback accordingly.

[0739] The terminal displays the training plan sent from the server to the user and also functions as an interface for monitoring the user during training. The terminal is equipped with sensors that capture the user's facial expressions and voice, and this data is sent to the emotion engine to understand the user's emotional state. Once the user's emotions are analyzed, feedback and training guidance are appropriately adjusted based on that information.

[0740] As users train, they receive feedback from a virtual character via their device. The user's emotional state is reflected in this feedback; for example, if the user is tired, they may receive encouragement or guidance to slow down. This emotionally responsive feedback helps users maintain high motivation and supports their continued training.

[0741] Furthermore, users' training results are recorded as points and used to provide rewards. Users can also utilize community features through their devices to share their results with other users and compare rankings. This promotes competition and interaction within the fitness community, creating a system that supports individual users in achieving their fitness goals.

[0742] The following describes the processing flow.

[0743] Step 1:

[0744] The user launches the application on their device, creates an account, and enters personal information and fitness goals.

[0745] Step 2:

[0746] The terminal sends user information and data for the selected virtual character to the server, which then generates a trainer based on this information.

[0747] Step 3:

[0748] The server creates a personalized training plan based on the user's fitness goals and level, and sends it to the device.

[0749] Step 4:

[0750] The terminal displays the training plan received from the server to the user and begins the training guidance. A virtual character introduces the training content to the user.

[0751] Step 5:

[0752] The user begins training, and the device captures the user's facial expressions and voice through its built-in sensors, sending this data to the server as emotion data.

[0753] Step 6:

[0754] The server uses an emotion engine to analyze the user's emotional state and adjusts the content of the feedback and training instructions based on the results.

[0755] Step 7:

[0756] The server sends tailored feedback to the device, which then notifies the user in real time. The feedback includes encouraging messages tailored to the user's emotions and advice on training pace.

[0757] Step 8:

[0758] When the user finishes training, the device records the results and sends that data to the server.

[0759] Step 9:

[0760] The server records the user's training results as points in a database and sends a list of eligible rewards to the user's device.

[0761] Step 10:

[0762] Users can select rewards based on the points they have earned through their devices.

[0763] Step 11:

[0764] Users can enjoy interaction and competition by using the community features on their devices to share their training results with other users and check rankings.

[0765] (Example 2)

[0766] 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".

[0767] Traditional fitness systems often offered standardized programs and feedback that didn't consider emotional states, leading to a lack of user motivation and retention. Furthermore, they struggled to provide personalized instruction tailored to individual needs.

[0768] 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.

[0769] In this invention, the server includes means for generating an individualized exercise plan using an instructor generated based on a virtualized character selected by the user; means for analyzing the user's exercise state and emotional data in real time and providing exercise guidance and immediate feedback according to the emotional state; and means for recording exercise results and managing rewards based on the compensation given to the user. This provides an individually customized exercise plan and allows the user to receive feedback tailored to their own pace and emotions.

[0770] A "coach" is a virtual entity created to provide exercise plans and offer guidance and feedback to users.

[0771] An "exercise plan" refers to a customized training schedule or program based on the user's fitness level and goals.

[0772] "Emotional data" refers to data captured from a user's facial expressions and voice, and is used to analyze the user's emotional state.

[0773] "Instant feedback" refers to advice and evaluations provided instantly based on real-time analysis of the user's physical and emotional state.

[0774] "Rewards" refer to points or rewards that users earn based on their exercise performance, and benefits are managed based on these points.

[0775] "Cooperative features" are functions that help users share their exercise results and interact with other users to promote competition.

[0776] A "detector" refers to a device or sensor used to capture user behavior and emotional data.

[0777] This invention provides a system that personalizes the user's fitness experience and offers feedback that takes their emotional state into consideration. The system is centered around a server, a terminal, and the user, with each component playing a specific role.

[0778] The server generates a virtual instructor character based on user input. The server performs calculations to develop an exercise plan based on the user's selected character, fitness level, and set goals. Furthermore, the server integrates an emotion engine that analyzes the user's emotional data. This analysis allows the server to determine in real time what kind of feedback the user needs during exercise and generate tailored feedback accordingly.

[0779] The device presents the user with the exercise plan and feedback transmitted from the server, and functions as a crucial interface for monitoring the user's movements. The device incorporates multiple sensors to capture the user's facial expressions and voice. This allows the device to continuously accumulate data on the user's emotional state, which is then transmitted to the emotion engine.

[0780] Users receive feedback that reflects their emotional state captured during exercise. For example, if a user is feeling tired, a virtual character on the device might display an encouraging message such as, "Let's slow down the pace a bit during today's workout and keep it fun." In this way, the fitness session provides a supportive experience for the user.

[0781] As a concrete example, the following is an example of an input prompt statement for a generative AI model:

[0782] "Please suggest feedback that corresponds to the emotional state the user is currently displaying. The user is currently feeling tired."

[0783] Through this system, personalized exercise plans and appropriate feedback help maintain user motivation and support the continuation of training.

[0784] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0785] Step 1:

[0786] Users log in via their device and enter their fitness level and goals. The device then sends this information to the server. This information is used as basic data necessary for creating an exercise plan.

[0787] Step 2:

[0788] The server generates a virtual character based on the received user information. Specifically, it identifies a character that matches the user's preferences and builds a coaching model to generate an exercise plan tailored to that character. In this process, the server analyzes the user's input data and calculates the optimal exercise program.

[0789] Step 3:

[0790] After the exercise plan is generated, the server sends this plan to the terminal. The terminal then displays the received plan to the user. The exercise plan includes specific exercises and the set duration.

[0791] Step 4:

[0792] The device uses sensors to capture user emotional data during training. This includes the user's facial expressions and voice data. The collected data is sent to a server, which serves as input for analyzing the emotional state.

[0793] Step 5:

[0794] The server analyzes the received emotional data using an emotion engine. The emotion engine inputs the received data as prompts into an AI model to determine the user's current emotional state. For example, if the server determines that the user is showing signs of fatigue, it generates an encouraging message.

[0795] Step 6:

[0796] The generated feedback is sent from the server to the terminal and communicated to the user. The terminal provides appropriate guidance and support to the user through a virtual character. The feedback includes pacing adjustments and words of encouragement.

[0797] Step 7:

[0798] Once a user completes their exercise, the device records their progress and sends it to the server. The server calculates the reward based on the recorded data and adds points to the user's account. This information is also used later for managing rewards.

[0799] (Application Example 2)

[0800] 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".

[0801] In today's industrial environment, there is a demand to maximize the efficiency of robots and their operators working in factories. However, conventional training systems struggle to provide real-time feedback that takes into account the operator's psychological state, which can lead to increased operator stress. Furthermore, there is a lack of mechanisms to effectively manage work results and promote competition.

[0802] 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.

[0803] In this invention, the server includes means for generating individual training plans using instructors generated based on virtualized characters selected by the user; means for analyzing the user's work in real time and providing immediate guidance according to the training execution status; means for adjusting feedback provided by an emotion engine that recognizes the user's emotions and presenting encouragement from the virtual character according to the operator's psychological state; means for recording work results and managing rewards based on performance points awarded to the user; and means for providing collective functions to share results among users and promote competition. This makes it possible to improve work efficiency and enhance competitiveness while taking into account the operator's psychological state, and to reduce stress in the work environment.

[0804] A "user-selected virtual character" is a digital virtual entity generated based on user instructions, which functions as an instructor providing an individualized training plan.

[0805] An "individualized training plan" is a learning or work schedule customized to each user's specific needs and goals.

[0806] An "emotion engine" is a technology that analyzes the user's emotional state and adjusts feedback based on that data.

[0807] "Feedback adjustment" is a process that dynamically changes the information and support provided by the virtual instructor according to the user's emotions and work status.

[0808] "The operator's psychological state" refers to the operator's mental state, including their stress level and mood during the operation.

[0809] "Work results" refer to the specific achievements and progress obtained as a result of the work or training activities performed by the user.

[0810] "Performance points" are numerical values ​​or points calculated based on the user's work output and used for rewards and comparisons between users.

[0811] "Collective functions" refer to systems that provide platforms and features for users to share results and compete with each other.

[0812] This invention is a system for improving the work efficiency of operators and robots in a factory. The system uses a virtualized character to provide operators with individualized training plans, analyzes the operators' emotional state, and adjusts feedback to suit the situation.

[0813] The server generates a personalized training plan based on the virtual character selected by the pilot. This plan is customized to the pilot's experience and goals. The server uses Python and Flask, enabling it to provide plans in real time.

[0814] The device is equipped with sensors to capture the user's facial expressions and voice, and sends this data to an emotion engine. This engine uses OpenCV and TensorFlow to analyze the user's emotions and can receive feedback from a server according to that state.

[0815] Users receive real-time feedback from virtual characters via their smartphones or tablets. For example, if they feel tired while working, the character will notify them with an encouraging message such as, "You'll be able to take a break soon. Keep going!"

[0816] Such a system makes it easier for operators to maintain high motivation and improve work efficiency. An example of a prompt message is: "Create feedback based on the operator's emotional data and display an encouraging message through the virtual character."

[0817] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0818] Step 1:

[0819] The server generates individual training plans based on the virtual character selected by the user. It receives user-selected character information, past work history, and target data as input, analyzes this information, and outputs a customized training plan. Specifically, it uses Python or Flask to perform calculations that build a plan optimized for the user in real time.

[0820] Step 2:

[0821] The device uses sensors to capture the user's facial expressions and voice. Based on this input data, an emotion engine performs emotion analysis. Using OpenCV and TensorFlow, it recognizes changes in facial expressions and voice tone from image and audio data, and outputs numerical emotion data.

[0822] Step 3:

[0823] The emotion engine sends the analyzed emotion data to the server. The server then processes the feedback based on the received emotion data. For example, if the emotion data indicates fatigue, the server will output encouraging messages or instructions regarding work pace.

[0824] Step 4:

[0825] The user receives feedback via their device. Feedback, which is output from the server, is sent to the device and displayed on the screen through a virtual character. Specifically, the screen display changes according to the feedback content, and the user is guided to the next step based on their actions.

[0826] Step 5:

[0827] The server records user work output and calculates performance points. It takes user work data as input, scores it based on predetermined criteria, and outputs the result as performance points. These performance points are then used in subsequent reward systems and user comparisons.

[0828] Step 6:

[0829] The device provides a collective function for sharing information with other users. It uses user performance data as input, shares it with other users via the network, and performs specific actions to promote competition by outputting rankings and comment functions.

[0830] 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.

[0831] 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.

[0832] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0833] 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.

[0834] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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."

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0851] The following is further disclosed regarding the embodiments described above.

[0852] (Claim 1)

[0853] A means for generating an individual training plan using a trainer generated based on a virtualized character selected by the user,

[0854] A means of analyzing the user's exercise in real time and providing immediate feedback according to the training performance,

[0855] A means of recording training results and managing rewards based on points awarded to users,

[0856] A means of providing community features to share results among users and promote competition,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, which generates feedback in combination with a sensor for analyzing user movements.

[0860] (Claim 3)

[0861] The system according to claim 1, wherein rewards based on points are provided based on predetermined criteria.

[0862] "Example 1"

[0863] (Claim 1)

[0864] A means of generating a trainer based on a virtualized character selected by the user, and creating an individual training plan using a generated AI model,

[0865] A means for analyzing the user's movements in real time and generating immediate feedback according to the training performance using a generative AI model,

[0866] A means of recording training results and managing rewards based on a reward system granted to users,

[0867] A means of providing community features to share results among users and promote competition,

[0868] A system that includes this.

[0869] (Claim 2)

[0870] The system according to claim 1, which generates feedback in combination with a detection device for analyzing user movements.

[0871] (Claim 3)

[0872] The system according to claim 1, wherein the provision of benefits based on the reward system is carried out based on predetermined criteria.

[0873] "Application Example 1"

[0874] (Claim 1)

[0875] A means for generating an individual training plan using a trainer generated based on a virtualized character selected by the user,

[0876] A means of analyzing the user's exercise in real time and providing immediate feedback according to the training performance,

[0877] A means of recording training results and managing rewards based on evaluations given to users,

[0878] A means of providing information sharing functions to facilitate the sharing and comparison of results among users,

[0879] A means by which a virtual trainer provides real-time feedback and demonstrates exercise movements through a visual display device,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, which generates feedback that guides physical actions through a visual display, in combination with sensors for analyzing user movements.

[0883] (Claim 3)

[0884] The system according to claim 1, wherein the provision of rewards based on evaluations is carried out according to predetermined criteria and is notified sequentially via a visual display device.

[0885] "Example 2 of combining an emotion engine"

[0886] (Claim 1)

[0887] A means for generating an individual exercise plan using an instructor generated based on a virtualized character selected by the user,

[0888] A means for analyzing the user's exercise status and emotional data in real time and providing exercise guidance and immediate feedback tailored to their emotional state,

[0889] A means of recording exercise results and managing rewards based on the compensation given to users,

[0890] A means of providing collaborative features to share results among users and promote competition,

[0891] A system that includes this.

[0892] (Claim 2)

[0893] The system according to claim 1, which generates feedback in combination with a detector for analyzing user behavior and emotion data.

[0894] (Claim 3)

[0895] The system according to claim 1, in which the provision of benefits based on consideration is carried out according to predetermined criteria.

[0896] "Application example 2 when combining with an emotional engine"

[0897] (Claim 1)

[0898] A means for generating individual training plans using instructors generated based on virtual characters selected by the user,

[0899] A means of analyzing user work in real time and providing immediate guidance according to the training execution status,

[0900] A means for recording the results of work and managing rewards based on the performance points awarded to users,

[0901] A means of providing feedback adjustments through an emotion engine that recognizes the user's emotions, and presenting encouragement from a virtual character according to the operator's psychological state,

[0902] A means of providing collective functionality to share results among users and promote competition,

[0903] A system that includes this.

[0904] (Claim 2)

[0905] The system according to claim 1, which generates guidance in combination with a sensor for analyzing user movements.

[0906] (Claim 3)

[0907] The system according to claim 1, wherein rewards based on performance points are provided based on predetermined criteria. [Explanation of symbols]

[0908] 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 for generating an individual training plan using a trainer generated based on a virtualized character selected by the user, A means of analyzing the user's exercise in real time and providing immediate feedback according to the training performance, A means of recording training results and managing rewards based on points awarded to users, A means of providing community features to share results among users and promote competition, A system that includes this.

2. The system according to claim 1, which generates feedback in combination with a sensor for analyzing user movements.

3. The system according to claim 1, wherein rewards based on points are provided based on predetermined criteria.

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