system

Abstract

We provide the system. [Solution] A receiving mechanism for inputting fitness goals, fitness levels, and past injury information from users, A generation means that creates an individualized training menu using a generation algorithm based on the information acquired by the receiving means, A display means that visually displays the training menu created by the generation means using a hologram projector, An analysis means that detects the user's movements during training presented by the display means using a camera and analyzes the data, The analysis means compares the user's actions detected with the proposed actions and provides guidance to correct inappropriate actions. A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In order to make fitness a habit, users often do not have time to go to the gym or cannot receive dedicated guidance, and there is a problem that the risk of injury increases in self-styled training. Therefore, there is a demand for a system that can provide safe and effective personalized fitness guidance at home. 【Means for Solving the Problems】 【0005】 This invention provides a system that generates personalized training menus using means for inputting fitness goals, fitness levels, and past injury information from the user, and visualizes them using a hologram projector to provide correct form. Furthermore, it ensures safe and effective training by tracking the user's movements in real time using a camera and analysis means, and correcting any inappropriate movements using instruction means. In addition, it encourages continuous fitness activities by recording the user's progress using progress management means and voice interaction means, and supporting feedback and motivation enhancement. 【0006】 "Receiving means" refers to a device or method for inputting and acquiring fitness goals, fitness levels, and past injury information from a user. 【0007】 "Generation means" refers to an apparatus or method that automatically creates an individualized training menu using a generation algorithm based on acquired user information. 【0008】 "Display means" refers to a device or method that uses a hologram projector to display a generated training menu to provide the user with a visual representation. 【0009】 "Analysis means" refers to a device or method that uses a camera to detect and analyze the user's actions in response to the displayed training. 【0010】 "Instructional means" refers to a device or method that provides feedback to encourage correct actions and gives instructions to correct inappropriate actions, based on user action data acquired by analysis means. 【0011】 A "progress management device" is a device or method that records the user's training progress and provides feedback based on that information. 【0012】 "Voice dialogue means" refers to a device or method that has the function of improving motivation through natural conversation with the user. [Brief explanation of the drawing] 【0013】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing of a data processing system in Application Example 2 when combined with an emotion engine. 【Embodiments for Carrying Out the Invention】 【0014】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0015】 First, the terms used in the following description will be explained. 【0016】 In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0017】 In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0018】 In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0019】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0020】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0021】 [First Embodiment] 【0022】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0023】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0024】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0025】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0026】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0027】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0028】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0029】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0030】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0031】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0032】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0033】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0034】 This invention relates to an AI-driven hologram fitness assistant system that enables users to receive high-quality fitness guidance at home. The system generates personalized training menus based on the user's fitness goals, fitness level, and past injury information, and provides visual guidance through a hologram projector. 【0035】 In using the system, users first launch a dedicated app and input their fitness goals and profile information into their device. The device sends this information to a server, which then generates a personalized training menu. This generation uses an AI algorithm to suggest exercises that are best suited to the user's needs. 【0036】 The generated training menu is transmitted via the terminal to a hologram projector and displayed in a functional format in front of the user. For example, the correct form for squats and push-ups is shown in 3D. This visual guide allows the user to intuitively understand how to perform the movements. 【0037】 Furthermore, a camera built into the device captures the user's training movements in real time and sends the video data to a server. The server analyzes the video data using AI to evaluate whether the user's movements are correct. If inappropriate movements are detected, the server notifies the user via the device with instructions for improvement. This guidance process allows users to maximize the effectiveness of their training while reducing the risk of injury. 【0038】 The server also records training progress and manages the user's progress toward their fitness goals. The device periodically reports progress to the user and provides feedback according to the milestones achieved. This makes it easier for the user to maintain motivation. 【0039】 Finally, the device interacts with the user through voice dialogue, further increasing motivation for training through natural conversation. For example, if the user says, "I'm tired today," the device will encourage them by saying, "It's important to keep going, even if you have to reduce the workload a little. Let's do our best!" 【0040】 In this way, this system enables users to receive the specialized fitness instruction they need at home, supporting their health improvement. 【0041】 The following describes the processing flow. 【0042】 Step 1: 【0043】 Users launch a dedicated app on their device and enter information such as their fitness goals, current fitness level, and past injury history. This information is then sent from the device to the server. 【0044】 Step 2: 【0045】 The server uses an AI algorithm to generate personalized training menus based on information received from the user. The generated menus are then adjusted to match the user's needs and constraints. 【0046】 Step 3: 【0047】 The terminal receives the training menu from the server and sends it to a hologram projector, which then visualizes and displays the training movements in 3D in front of the user. 【0048】 Step 4: 【0049】 When a user begins training, the camera on the device captures the user's movements in real time. This video data is sent to the server. 【0050】 Step 5: 【0051】 The server analyzes the video data and uses AI to evaluate whether the user's movements are in line with the correct form. This helps determine if the user is training correctly. 【0052】 Step 6: 【0053】 If inappropriate behavior is detected, the server generates appropriate feedback and notifies the user through the terminal. The user can then correct their behavior based on the hologram and audio guidance. 【0054】 Step 7: 【0055】 The server records and analyzes training results and progress to manage progress toward long-term fitness goals. Users receive regular progress feedback from their devices. 【0056】 Step 8: 【0057】 The device utilizes voice interaction capabilities to engage with the user and provide the necessary support to maintain motivation during training. This interaction allows the user to continue training more effectively. 【0058】 (Example 1) 【0059】 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." 【0060】 Traditional personalized fitness instruction often lacked the ability to provide accurate movements and effective training plans without a professional trainer, making it difficult for individuals to safely and efficiently engage in fitness at home. Furthermore, challenges remained in properly assessing movements and maintaining motivation. 【0061】 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. 【0062】 In this invention, the server includes a device for acquiring information on the user's physical ability goals, health status, and medical history; a device for generating personalized exercise guidance using artificial intelligence technology; and a device for providing the guidance visually using 3D display technology. This enables the user to train safely and efficiently at home, and to properly evaluate their movements and maintain motivation. 【0063】 A "user" refers to an individual who uses the system to create a fitness plan and improve their health. 【0064】 "Physical ability goals" refer to objectives related to the fitness level or exercise results that the user wants to achieve. 【0065】 "Health status" refers to information about the user's current physical condition, health history, and past injuries. 【0066】 "Medical history information" refers to data about injuries and illnesses that a user has experienced in the past, and is used by the system to provide personalized training. 【0067】 "Device" refers to each component of this system, specifically a combination of hardware and software designed to perform a particular function. 【0068】 "Artificial intelligence technology" refers to machine learning and data processing technologies used to analyze user information and provide optimized exercise guidance. 【0069】 "Personalized exercise instruction" refers to a training program customized to the user's specific needs and goals. 【0070】 "3D display technology" refers to technology that uses hologram projectors and other devices to display information in three dimensions, enabling users to receive exercise instruction visually. 【0071】 "Presenting information visually" refers to a method of displaying information through visual means to help users understand it. 【0072】 This invention provides a system that allows users to receive professional fitness instruction at home, offering personalized training tailored to the user's goals and health condition. This system is realized by combining various hardware and software technologies. 【0073】 Users input information about their physical abilities, health status, and medical history using a dedicated terminal. The terminal transmits this information to a server using a secure communication protocol. The terminal includes devices such as smartphones and tablets. 【0074】 The server uses artificial intelligence technology to generate personalized exercise guidance based on the information it receives. This AI technology includes machine learning algorithms to process user data and propose the optimal fitness plan. The server can utilize a cloud computing environment or a dedicated on-premises server. 【0075】 The generated exercise instructions are transmitted via a terminal to a device using 3D display technology, such as a hologram projector, and displayed as visual feedback around the user. This allows the user to intuitively understand and imitate the prescribed forms and movements. For example, the correct posture for squats and push-ups is presented in three dimensions. 【0076】 The device is equipped with a camera that captures the user's movements in real time. The captured video data is sent to a server, where AI technology is used to analyze the movements. Based on the analysis results, the server provides feedback on the user's form and supports them in correcting their movements appropriately. 【0077】 For example, when a user enters a prompt such as "I want to do full-body training three times a week," the AI ​​generates a corresponding training program and provides visual guidance through a hologram. In this way, the present invention provides an optimized fitness experience for each individual user and supports health promotion. 【0078】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0079】 Step 1: 【0080】 The user launches a dedicated application and enters information about their physical abilities, health status, and medical history into the terminal. The entered data is formatted along with the user ID and prepared to be sent to the server. For example, the user might enter information such as "Age: 35, Goal: Lose 5kg, History of knee injury." 【0081】 Step 2: 【0082】 The terminal transmits user input data to the server using a secure protocol. User information, which is the input, is protected by communication encryption technology before being sent to the server, and this data is temporarily stored in the user database. 【0083】 Step 3: 【0084】 The server generates personalized exercise guidance using a generated AI model based on the received user information. In this process, an algorithm is used to analyze the input data and determine the optimal exercise plan for the user's goals. The server might output results such as "30 minutes of low-intensity aerobic exercise three times a week." 【0085】 Step 4: 【0086】 The exercise instruction plan generated on the server is sent to the terminal, which converts it into a visual hologram display and presents it to the user. Specifically, the terminal uses a hologram projector to show the user movements such as "squats" and "planks" in three dimensions. 【0087】 Step 5: 【0088】 The camera on the device captures the user's training in real time. This is to verify the user's form according to the hologram display, and the captured data is sent to the server as input. 【0089】 Step 6: 【0090】 The server analyzes the captured video data and uses a motion analysis algorithm to evaluate the user's form appropriately. Based on this input data, output feedback is generated, such as "the knee angle is too shallow." 【0091】 Step 7: 【0092】 Feedback from the server is communicated to the user via the terminal. The terminal conveys this information to the user via voice or text, guiding them through necessary form corrections. A concrete example of this action is to give instructions such as, "Please squat down a little deeper." 【0093】 Step 8: 【0094】 The server also stores training data and manages user progress. This records the user's progress towards their fitness goals and is used to suggest future training sessions. At this step, progress reports can be output, such as "30% of goal achieved." 【0095】 (Application Example 1) 【0096】 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." 【0097】 In recent years, with the rise in health awareness, there has been an increasing demand for personalized health maintenance methods. However, traditional exercise guidance is uniform, making it difficult to provide appropriate approaches tailored to the characteristics of individual residents. Furthermore, there is a need to eliminate health disparities among residents and improve the overall health level by providing consistent health guidance within residential facilities. In addition, there is a need for natural means of dialogue that will increase residents' motivation. 【0098】 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. 【0099】 In this invention, the server includes an acquisition means for inputting goals, health levels, and historical information from users; a generation means for creating an individualized exercise plan using a generation method based on the information acquired by the acquisition means; and a management means for providing health guidance to residents within a residential facility and for visualizing the health information of the collective. This enables the provision of individualized and appropriate health guidance, improving the health level and motivation of residents. 【0100】 "Acquisition means" refers to a device or method for inputting user goals, health levels, and historical information. 【0101】 "Generation means" refers to a device or method that creates an individualized movement plan using a generation method based on information obtained by acquisition means. 【0102】 "Display means" refers to a device or method for visually presenting a motion plan created by a generation means. 【0103】 "Analysis means" refers to a device or method that analyzes user activity information detected by an imaging device and compares it with proposed activities. 【0104】 "Instructional means" refers to a device or method for correcting inappropriate activities based on comparative results obtained through analytical means. 【0105】 "Management means" refers to a device or method for providing health guidance to residents within a residential facility and for visualizing healthy information about the collective. 【0106】 "Voice dialogue means" refers to a device or method for conducting natural dialogue in order to improve residents' motivation. 【0107】 The system for implementing this invention mainly consists of a server, terminals in each household, an imaging device, and a display device. First, the user uses the terminal to input their goals, health level, and history information, and transmits the data to the server via an acquisition means. Based on the acquired data, the server uses a generation AI model to create a personalized exercise plan. The generated exercise plan is sent to the display device via the terminal to provide visual guidance. 【0108】 During the user's exercise, the imaging device captures the user's movements in real time and transmits the data to a server for analysis. The server uses analysis tools to evaluate the user's activity and provides the user with guidance on areas that need correction. This allows the user to exercise safely and effectively. 【0109】 Furthermore, the management system aggregates and visualizes health data from all residents within the residential facility, enabling the sharing of health information among residents. The voice interaction system is used to improve motivation through interaction with the user. For example, if a user says they want to stop exercising, it generates and responds with a prompt such as, "Let's take a short break. You can maintain your health by continuing afterward." 【0110】 A concrete example of this system is a scenario where residents receive individual yoga or strength training instruction in a shared fitness room. Residents can receive health advice from their respective terminals and motivate each other. An example of a prompt message for the generated AI model is the question the server might receive: "Please tell me how residents can maintain their motivation to continue fitness at home." 【0111】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0112】 Step 1: 【0113】 The user uses a terminal to input goals, health levels, and historical information. The terminal sends this input data to the server. The input here includes the user's fitness goals and past injury information, and the output is the user data sent to the server. 【0114】 Step 2: 【0115】 The server uses a generative AI model to generate a personalized exercise plan based on the received user data. This process creates an exercise menu tailored to the user's goals and fitness level. The input is user data, and the output is the personalized exercise plan. 【0116】 Step 3: 【0117】 The generated exercise plan is transmitted to the display device via the terminal. The terminal visually presents the plan and manipulates a hologram to provide fitness guidance to the user. The input is the generated exercise plan, and the output is the displayed hologram menu. 【0118】 Step 4: 【0119】 When a user performs an exercise, the imaging device captures the user's movements in real time and transmits the data to the server. The input is the user's movement video, and the output is the activity data sent to the server. 【0120】 Step 5: 【0121】 The server evaluates the received video data using analysis tools to determine whether the user's actions are appropriate. Based on the analysis results, it generates improvement suggestions as needed. The input is activity data, and the output is action evaluation and improvement suggestions. 【0122】 Step 6: 【0123】 Improvement suggestions are sent to the terminal, and the user is instructed accordingly. The terminal provides feedback to the user and instructs them to continue using the correct form and actions. The input is improvement suggestions, and the output is feedback to the user. 【0124】 Step 7: 【0125】 Using voice interaction, the device engages in natural conversation with the user, facilitating discussions designed to increase motivation for exercise. For example, prompts such as, "Let's take a short break. Continuing afterward will help maintain your health," are generated. Input is the user's utterances, and output is conversational support. 【0126】 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. 【0127】 This invention is a system that provides a personalized training experience tailored to the user's emotional state by incorporating an emotion engine into an AI-driven fitness assistant that enables users to effectively perform fitness training at home. Based on fitness goals, fitness levels, and past injury information entered by the user, the system uses AI to generate an individualized training menu. 【0128】 The system begins with the user launching a dedicated app on their device and entering the necessary information. The device then sends this information to a server. The server uses a generation algorithm to create a training menu tailored to the user's needs. This created menu is then visually displayed to the user via a hologram projector. For example, squats and yoga poses are displayed in 3D in front of the user. 【0129】 Furthermore, this system uses the terminal's camera to capture the user's movements during training in real time. This video data is analyzed on a server to evaluate whether the user is performing the exercises with proper form. If inappropriate movements are detected, the server sends instructions to the user to improve their form. 【0130】 A key feature of this invention is the incorporation of an emotion engine that recognizes the user's emotional state based on their actions and voice data. This emotion engine analyzes the user's facial expressions and tone of voice to evaluate their stress level, fatigue, and motivation. As a result, the server dynamically adjusts the intensity and type of exercise to provide the user with the most suitable training content. 【0131】 For example, if a user expresses fatigue, the device can provide feedback to lower the difficulty of the exercise or recommend relaxing exercises. The device also uses natural voice interaction to provide appropriate messages to boost user motivation. For instance, if it detects that the user's expression is discouraged, it might offer encouraging words such as, "Keep going like this and you'll see results!" 【0132】 In this way, the AI-driven hologram fitness assistant system can adapt to the user's emotions and physical condition, providing a fitness experience tailored to individual needs and supporting safe and sustainable training. 【0133】 The following describes the processing flow. 【0134】 Step 1: 【0135】 Users launch a dedicated app on their device and enter their fitness goals, fitness level, and past injury history. This information is then transmitted to the server via the device. 【0136】 Step 2: 【0137】 The server uses a generation algorithm to create a training menu tailored to the individual user's needs, based on the information obtained from the user. The exercises best suited to the user's current condition are selected. 【0138】 Step 3: 【0139】 The terminal receives the training menu from the server and sends it to a hologram projector, displaying it visually in front of the user. This allows the user to confirm the specific actions. 【0140】 Step 4: 【0141】 When a user begins training, the camera on the device captures the user's movements in real time and sends the video data to the server. 【0142】 Step 5: 【0143】 The server analyzes the video data and uses an AI algorithm to evaluate whether the user's actions are in the correct form. If there are any inappropriate actions, they are detected. 【0144】 Step 6: 【0145】 If inappropriate behavior is detected, the server identifies the behavior that needs correction, generates feedback to provide guidance on correct form, and notifies the user via the terminal. 【0146】 Step 7: 【0147】 The emotion engine analyzes the user's actions and voice data, recognizing the user's emotional state based on facial expressions and tone. This analysis identifies states such as fatigue or stress. 【0148】 Step 8: 【0149】 The server automatically adjusts the training content based on the analysis results of the emotion engine. For example, if the user is fatigued, it will either reduce the intensity of the exercise or recommend recovery exercises. 【0150】 Step 9: 【0151】 The device utilizes voice interaction capabilities to provide feedback to the user and support their motivation. For example, if it detects that the user's motivation is low, it will send an encouraging message. 【0152】 This process allows users to receive training tailored to their emotions and physical condition, enabling them to engage in fitness safely and sustainably. 【0153】 (Example 2) 【0154】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0155】 Traditional home fitness training has faced challenges such as users not receiving sufficient support regarding individualized exercise plans and motivation, leading to a lack of consistency and an increased risk of injury due to incorrect form. In addition, the lack of flexible support tailored to the user's emotional state limited training satisfaction and effectiveness. 【0156】 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. 【0157】 In this invention, the server includes an acquisition means for inputting exercise goals, physical fitness status, and past health information from the user; a generation means for generating an individualized exercise plan using a generative AI model; and an emotion analysis and adjustment means for evaluating the user's emotional state and dynamically adjusting the exercise content based on that evaluation. This enables users to receive individually optimized training at home, resulting in a safer, more effective, and sustainable fitness experience. 【0158】 "Means of acquisition" refers to the functions and mechanisms necessary for users to input their exercise goals, physical fitness status, and past health information. 【0159】 "Generation means" refers to a function or mechanism that generates an individualized motor plan using a generation AI model based on information obtained through acquisition means. 【0160】 "Presentation means" refers to functions or mechanisms for visually presenting the generated motion plan using a stereoscopic display device. 【0161】 "Analysis means" refers to functions or mechanisms for analyzing user motion data detected using imaging equipment and comparing it with proposed actions. 【0162】 "Instructional tools" refer to functions and mechanisms that provide guidance and advice to correct inaccurate movements based on the results of motion comparisons performed by analytical tools. 【0163】 An "emotional analysis and adjustment mechanism" is a function or system that evaluates the user's emotional state and dynamically adjusts the exercise content based on the evaluation results. 【0164】 A "progress management system" refers to a function or mechanism for recording the progress of exercise and providing users with information on its results and evaluations. 【0165】 "Voice dialogue means" refers to functions and mechanisms that use natural language processing to engage in voice dialogue with users and promote motivation. 【0166】 This invention is a system for users to effectively perform fitness training at home, utilizing AI technology to provide training tailored to the user's individual needs. The main components of this system include a server, a terminal, and user input. 【0167】 Users input their exercise goals, fitness level, and past health information using a dedicated app on their device. This information is transmitted to a server in real time. The server utilizes a generative AI model to generate a personalized exercise plan based on the received data. This generated exercise plan is then visually presented to the user via a 3D display on the device, specifically a hologram projector. For example, exercises such as squats and yoga are displayed as 3D models, providing visually clear instruction. 【0168】 Furthermore, the device captures the user's movements in real time during training through its built-in camera. This video data is analyzed on a server to evaluate whether the user is performing the exercises with proper form. For example, if the form is incorrect, corrective instructions such as "lower your hips a little more" are immediately provided. The server also analyzes the user's emotional state based on their facial expressions and tone of voice, and dynamically adjusts the exercise content accordingly. If fatigue is detected, the training intensity is reduced or relaxation exercises are suggested, enabling training that takes into account the user's health condition and motivation. 【0169】 Devices equipped with voice interaction capabilities can provide users with encouraging messages via voice to boost their motivation. For example, if a device detects that a user is feeling discouraged, it might send a message such as, "Keep going! You'll see results soon!" 【0170】 This system provides an optimal training environment based on the user's individual health data and emotional state, supporting a safe and effective fitness experience. 【0171】 Example of a prompt: 【0172】 "Analyze the user's emotional state and propose effective messages to boost their motivation." 【0173】 "Please generate an algorithm to calculate the optimal exercise intensity based on this user's activity data." 【0174】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0175】 Step 1: 【0176】 The user launches a dedicated app on their device and enters their exercise goals, fitness level, and past health information. The entered data, along with the user ID, is sent from the device to the server. The input in this step is fitness-related information provided by the user, and the output is the transmission of information to the server. 【0177】 Step 2: 【0178】 The server uses a generative AI model to generate a personalized exercise plan based on the received data. This process compares the data with various exercise data stored in a database to determine the optimal training program for the user. The input is the user's fitness information, and the output is the personalized exercise plan. 【0179】 Step 3: 【0180】 The server sends the generated exercise plan to the terminal, which then visually presents it to the user using a 3D display device. Specifically, a hologram projector displays the selected exercise in 3D. The input is the generated exercise plan, and the output is the visual presentation to the user. 【0181】 Step 4: 【0182】 When a user begins training, the device's camera captures the user's movements in real time. This video data is sent to a server for motion analysis. The input is video of the user's training movements, and the output is data for analysis. 【0183】 Step 5: 【0184】 The server uses analysis tools to evaluate the user's movements and verify whether the exercises are being performed with correct form. This evaluation is based on machine learning algorithms, and the data is processed to provide guidance on proper form. The input is video data, and the output is the results of the movement evaluation. 【0185】 Step 6: 【0186】 Based on the evaluation results, the server sends corrective instructions to the terminal as needed. If incorrect operation is detected, the terminal provides feedback to the user, such as "lower your stance a little." The input is the operation evaluation result, and the output is the corrective instructions to the user. 【0187】 Step 7: 【0188】 The device captures the user's facial expressions and voice and sends this data to the server. The server performs emotion analysis and dynamically adjusts the movement. The input is the user's facial expressions and voice data, and the output is the emotion evaluation result. 【0189】 Step 8: 【0190】 The server dynamically adjusts the exercise plan based on the emotional assessment results. If the server determines that the user is fatigued, it will reduce the exercise intensity or suggest relaxing exercises. The input is the emotional assessment results, and the output is the adjusted exercise plan. 【0191】 Step 9: 【0192】 The device uses natural language processing to provide the user with motivational voice messages. For example, if the user's motivation is low, a message such as "Keep going! You'll see results soon!" is sent. The input is a tailored exercise plan and emotional assessment, and the output is a voice message. 【0193】 (Application Example 2) 【0194】 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". 【0195】 The problem that this invention aims to solve is to provide personalized fitness training to individual users and to realize a training experience that takes into account the user's emotional state. In particular, it is necessary to dynamically adjust the training according to the user's motivation and physical condition, and to support the user's safety and sustainable improvement of fitness. Conventional systems have lacked an approach that reflects the individual emotional state of users, so there is a need to respond to user needs more effectively. 【0196】 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. 【0197】 In this invention, the server includes data receiving means for inputting fitness goals, fitness levels, and past injury information from the user; information generating means for creating an individualized training menu using a generation algorithm based on the information acquired by the data receiving means; and output means for visually communicating the training menu created by the information generating means using a three-dimensional display device. This enables the user to receive appropriate training tailored to their individual needs during fitness training at home. 【0198】 A "user" is an individual who uses a fitness training system to receive personalized training. 【0199】 "Data receiving means" refers to a device or method for inputting and collecting information from users, such as fitness goals, fitness levels, and past injury information. 【0200】 A "generative algorithm" is a process or procedure that creates personalized training menus based on the user information entered. 【0201】 "Information generation means" refers to a device or method for creating a training menu tailored to a user using a generation algorithm. 【0202】 A "three-dimensional display device" is a device that visually displays training menus and movements in three dimensions for the user. 【0203】 "Output means" refers to a device or method that visually communicates the created training menu to the user. 【0204】 A "video device" is a device that captures the user's training movements and processes them as video data. 【0205】 "Information analysis means" refers to a device or method for analyzing data captured by a video device and evaluating the user's actions. 【0206】 "Action guidance means" refers to a device or method that identifies an inappropriate user action and provides instructions to correct it. 【0207】 "Emotion recognition means" refers to a device or method for analyzing a user's facial expressions and voice and evaluating their emotional state. 【0208】 "Motor adjustment means" refers to a device or method for dynamically adjusting training content based on evaluation results from emotion recognition means. 【0209】 The system for carrying out this invention is an AI-driven fitness assistant system that provides personalized fitness training to the user. The system has the ability to take into account the user's emotional state and dynamically adjust the training plan. 【0210】 First, the user uses the device to input their fitness goals, fitness level, and past injury information. This information is sent to the server via a data receiving device. Based on the received information, the server runs a generative AI model to generate a personalized training menu. This generation process uses a generation algorithm that suggests the most suitable training for the user's health condition and goals. 【0211】 Next, the server presents the generated training menu to the user via a three-dimensional display device. The user performs the training according to the displayed image. The user's movements are captured by the video device and transmitted to the server. The server uses information analysis means to analyze the captured user movements and evaluate the accuracy of the training. If inappropriate movements are detected, the server uses movement guidance means to send instructions to the user to perform the correct movements. 【0212】 Furthermore, the system uses emotion recognition to analyze the user's facial expressions and voice to evaluate their emotional state. Based on the evaluation results, the exercise adjustment mechanism dynamically changes the training content, enabling the user to continue with optimal training tailored to their tone of voice and mood. For example, if the system determines that the user is tired, it will either reduce the intensity of the exercise or suggest exercises that promote relaxation. 【0213】 For example, if the emotion recognition system determines that the user is feeling down, the server will output a message such as, "If you keep going like this, you'll see results!" 【0214】 An example of a prompt message would be: "Based on the user's health and emotional state, provide an appropriate fitness plan and adjust the exercise in real time." 【0215】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0216】 Step 1: 【0217】 The user uses a device to input their fitness goals, fitness level, and past injury information, and sends this data to the server. The data receiving device records this user input and converts it into a format usable by the server. The server, upon receiving the input information, performs preprocessing to run the generative AI model. 【0218】 Step 2: 【0219】 The server uses a generative AI model based on the entered user information to create a personalized training menu. Specifically, the server applies a generative algorithm to select exercises that match the user's goals and fitness level. This process also takes into account limitations based on past injuries and health conditions. The resulting training menu is customized for each individual user. 【0220】 Step 3: 【0221】 The server visually presents the generated training menu to the user via a three-dimensional display device. The input here is the customized training menu, and the output is a visual training guide. The server converts this data into an appropriate format so that the display device can reproduce the image in three dimensions. 【0222】 Step 4: 【0223】 A video device installed on the terminal captures the user's movements in real time during training. This video data is sent to a server for analysis. The input is video of the user's training movements, and the server uses this video to perform motion analysis. 【0224】 Step 5: 【0225】 The server uses information analysis tools to analyze the user's movements and evaluate the accuracy of the training. In this step, the server analyzes the user's posture and movement form based on the input video data. If inappropriate movements are identified as a result, the movement instruction tool generates corrective instructions and sends them to the user. 【0226】 Step 6: 【0227】 The server analyzes the user's facial expressions and voice data to evaluate their emotional state. This evaluation is performed using emotion recognition technology. The input consists of the user's facial image and voice data, which are analyzed to infer the user's psychological state. The output is evaluation information regarding the user's emotional state. 【0228】 Step 7: 【0229】 The server dynamically adjusts the training content using exercise adjustment mechanisms based on the results of emotion recognition evaluations. The input here is emotion evaluation information, and the output is the adjusted training menu. For example, if the user indicates fatigue, the server reduces the intensity of the exercise and recommends more relaxing exercises. This adjustment allows the user to continue having an optimal fitness experience. 【0230】 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. 【0231】 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. 【0232】 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. 【0233】 [Second Embodiment] 【0234】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0235】 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. 【0236】 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). 【0237】 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. 【0238】 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. 【0239】 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). 【0240】 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. 【0241】 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. 【0242】 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. 【0243】 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. 【0244】 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. 【0245】 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". 【0246】 This invention relates to an AI-driven hologram fitness assistant system that enables users to receive high-quality fitness guidance at home. The system generates personalized training menus based on the user's fitness goals, fitness level, and past injury information, and provides visual guidance through a hologram projector. 【0247】 In using the system, users first launch a dedicated app and input their fitness goals and profile information into their device. The device sends this information to a server, which then generates a personalized training menu. This generation uses an AI algorithm to suggest exercises that are best suited to the user's needs. 【0248】 The generated training menu is transmitted via the terminal to a hologram projector and displayed in a functional format in front of the user. For example, the correct form for squats and push-ups is shown in 3D. This visual guide allows the user to intuitively understand how to perform the movements. 【0249】 Furthermore, a camera built into the device captures the user's training movements in real time and sends the video data to a server. The server analyzes the video data using AI to evaluate whether the user's movements are correct. If inappropriate movements are detected, the server notifies the user via the device with instructions for improvement. This guidance process allows users to maximize the effectiveness of their training while reducing the risk of injury. 【0250】 The server also records training progress and manages the user's progress toward their fitness goals. The device periodically reports progress to the user and provides feedback according to the milestones achieved. This makes it easier for the user to maintain motivation. 【0251】 Finally, the device interacts with the user through voice dialogue, further increasing motivation for training through natural conversation. For example, if the user says, "I'm tired today," the device will encourage them by saying, "It's important to keep going, even if you have to reduce the workload a little. Let's do our best!" 【0252】 In this way, this system enables users to receive the specialized fitness instruction they need at home, supporting their health improvement. 【0253】 The following describes the processing flow. 【0254】 Step 1: 【0255】 Users launch a dedicated app on their device and enter information such as their fitness goals, current fitness level, and past injury history. This information is then sent from the device to the server. 【0256】 Step 2: 【0257】 The server uses an AI algorithm to generate personalized training menus based on information received from the user. The generated menus are then adjusted to match the user's needs and constraints. 【0258】 Step 3: 【0259】 The terminal receives the training menu from the server and sends it to a hologram projector, which then visualizes and displays the training movements in 3D in front of the user. 【0260】 Step 4: 【0261】 When a user begins training, the camera on the device captures the user's movements in real time. This video data is sent to the server. 【0262】 Step 5: 【0263】 The server analyzes the video data and uses AI to evaluate whether the user's movements are in line with the correct form. This helps determine if the user is training correctly. 【0264】 Step 6: 【0265】 If inappropriate behavior is detected, the server generates appropriate feedback and notifies the user through the terminal. The user can then correct their behavior based on the hologram and audio guidance. 【0266】 Step 7: 【0267】 The server records and analyzes training results and progress to manage progress toward long-term fitness goals. Users receive regular progress feedback from their devices. 【0268】 Step 8: 【0269】 The device utilizes voice interaction capabilities to engage with the user and provide the necessary support to maintain motivation during training. This interaction allows the user to continue training more effectively. 【0270】 (Example 1) 【0271】 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." 【0272】 Traditional personalized fitness instruction often lacked the ability to provide accurate movements and effective training plans without a professional trainer, making it difficult for individuals to safely and efficiently engage in fitness at home. Furthermore, challenges remained in properly assessing movements and maintaining motivation. 【0273】 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. 【0274】 In this invention, the server includes a device for acquiring information on the user's physical ability goals, health status, and medical history; a device for generating personalized exercise guidance using artificial intelligence technology; and a device for providing the guidance visually using 3D display technology. This enables the user to train safely and efficiently at home, and to properly evaluate their movements and maintain motivation. 【0275】 A "user" refers to an individual who uses the system to create a fitness plan and improve their health. 【0276】 "Physical ability goals" refer to objectives related to the fitness level or exercise results that the user wants to achieve. 【0277】 "Health status" refers to information about the user's current physical condition, health history, and past injuries. 【0278】 "Medical history information" refers to data about injuries and illnesses that a user has experienced in the past, and is used by the system to provide personalized training. 【0279】 "Device" refers to each component of this system, specifically a combination of hardware and software designed to perform a particular function. 【0280】 "Artificial intelligence technology" refers to machine learning and data processing technologies used to analyze user information and provide optimized exercise guidance. 【0281】 "Personalized exercise instruction" refers to a training program customized to the user's specific needs and goals. 【0282】 "3D display technology" refers to technology that uses hologram projectors and other devices to display information in three dimensions, enabling users to receive exercise instruction visually. 【0283】 "Visually provide" refers to a method of presenting information visually to appeal to the user's vision and enable understanding by the user. 【0284】 The present invention is a system that enables a user to receive professional fitness guidance at home and provides personalized training according to the user's goals and health status. This system is realized by combining various hardware and software technologies. 【0285】 The user inputs information regarding their physical ability goals, health status, and past medical history using a dedicated terminal. The terminal transmits this information to the server using a secure communication protocol. The terminal includes devices such as smartphones and tablets. 【0286】 The server uses artificial intelligence technology to generate personalized exercise guidance based on the received information. This AI technology includes machine learning algorithms for processing user data and proposing an optimal fitness plan. The server can utilize a cloud computing environment or a dedicated on-premises server. 【0287】 The generated exercise guidance is transmitted via the terminal to a device using stereoscopic display technology, such as a hologram projector, and is displayed as visual feedback around the user. This allows the user to intuitively understand and imitate a given form or movement. For example, the correct postures of squats and push-ups are presented in three-dimensional form. 【0288】 The terminal is equipped with a camera that captures the user's movements in real-time. The captured video data is transmitted to the server, and the movements are analyzed using AI technology. The server provides feedback on the user's form based on the analysis results and supports corrections to appropriate movements. 【0289】 For example, when a user enters a prompt such as "I want to do full-body training three times a week," the AI ​​generates a corresponding training program and provides visual guidance through a hologram. In this way, the present invention provides an optimized fitness experience for each individual user and supports health promotion. 【0290】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0291】 Step 1: 【0292】 The user launches a dedicated application and enters information about their physical abilities, health status, and medical history into the terminal. The entered data is formatted along with the user ID and prepared to be sent to the server. For example, the user might enter information such as "Age: 35, Goal: Lose 5kg, History of knee injury." 【0293】 Step 2: 【0294】 The terminal transmits user input data to the server using a secure protocol. User information, which is the input, is protected by communication encryption technology before being sent to the server, and this data is temporarily stored in the user database. 【0295】 Step 3: 【0296】 The server generates personalized exercise guidance using a generated AI model based on the received user information. In this process, an algorithm is used to analyze the input data and determine the optimal exercise plan for the user's goals. The server might output results such as "30 minutes of low-intensity aerobic exercise three times a week." 【0297】 Step 4: 【0298】 The exercise guidance plan generated by the server is sent to the terminal, which converts it into a visual hologram display and provides it to the user. As a specific operation, the terminal uses a hologram projector to show actions such as "squat" and "plank" to the user in three dimensions. 【0299】 Step 5: 【0300】 The camera mounted on the terminal captures the user's training situation in real time. This is to check the user's form according to the hologram display, and the captured data is sent to the server as input. 【0301】 Step 6: 【0302】 The server analyzes the captured video data and performs an appropriate evaluation of the user's form using an action analysis algorithm. Based on this input data, output feedback such as "the knee angle is too shallow" is generated. 【0303】 [[ID=​​​​​​​​​​​​​​​​​​​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." 【0309】 In recent years, with the rise in health awareness, there has been an increasing demand for personalized health maintenance methods. However, traditional exercise guidance is uniform, making it difficult to provide appropriate approaches tailored to the characteristics of individual residents. Furthermore, there is a need to eliminate health disparities among residents and improve the overall health level by providing consistent health guidance within residential facilities. In addition, there is a need for natural means of dialogue that will increase residents' motivation. 【0310】 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. 【0311】 In this invention, the server includes an acquisition means for inputting goals, health levels, and historical information from users; a generation means for creating an individualized exercise plan using a generation method based on the information acquired by the acquisition means; and a management means for providing health guidance to residents within a residential facility and for visualizing the health information of the collective. This enables the provision of individualized and appropriate health guidance, improving the health level and motivation of residents. 【0312】 "Acquisition means" refers to a device or method for inputting user goals, health levels, and historical information. 【0313】 "Generation means" refers to a device or method that creates an individualized movement plan using a generation method based on information obtained by acquisition means. 【0314】 "Display means" refers to a device or method for visually presenting a motion plan created by a generation means. 【0315】 "Analysis means" refers to a device or method that analyzes user activity information detected by an imaging device and compares it with proposed activities. 【0316】 "Instructional means" refers to a device or method for correcting inappropriate activities based on comparative results obtained through analytical means. 【0317】 "Management means" refers to a device or method for providing health guidance to residents within a residential facility and for visualizing healthy information about the collective. 【0318】 "Voice dialogue means" refers to a device or method for conducting natural dialogue in order to improve residents' motivation. 【0319】 The system for implementing this invention mainly consists of a server, terminals in each household, an imaging device, and a display device. First, the user uses the terminal to input their goals, health level, and history information, and transmits the data to the server via an acquisition means. Based on the acquired data, the server uses a generation AI model to create a personalized exercise plan. The generated exercise plan is sent to the display device via the terminal to provide visual guidance. 【0320】 During the user's exercise, the imaging device captures the user's movements in real time and transmits the data to a server for analysis. The server uses analysis tools to evaluate the user's activity and provides the user with guidance on areas that need correction. This allows the user to exercise safely and effectively. 【0321】 Furthermore, the management system aggregates and visualizes health data from all residents within the residential facility, enabling the sharing of health information among residents. The voice interaction system is used to improve motivation through interaction with the user. For example, if a user says they want to stop exercising, it generates and responds with a prompt such as, "Let's take a short break. You can maintain your health by continuing afterward." 【0322】 A concrete example of this system is a scenario where residents receive individual yoga or strength training instruction in a shared fitness room. Residents can receive health advice from their respective terminals and motivate each other. An example of a prompt message for the generated AI model is the question the server might receive: "Please tell me how residents can maintain their motivation to continue fitness at home." 【0323】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0324】 Step 1: 【0325】 The user uses a terminal to input goals, health levels, and historical information. The terminal sends this input data to the server. The input here includes the user's fitness goals and past injury information, and the output is the user data sent to the server. 【0326】 Step 2: 【0327】 The server uses a generative AI model to generate a personalized exercise plan based on the received user data. This process creates an exercise menu tailored to the user's goals and fitness level. The input is user data, and the output is the personalized exercise plan. 【0328】 Step 3: 【0329】 The generated exercise plan is transmitted to the display device via the terminal. The terminal visually presents the plan and manipulates a hologram to provide fitness guidance to the user. The input is the generated exercise plan, and the output is the displayed hologram menu. 【0330】 Step 4: 【0331】 When a user performs an exercise, the imaging device captures the user's movements in real time and transmits the data to the server. The input is the user's movement video, and the output is the activity data sent to the server. 【0332】 Step 5: 【0333】 The server evaluates the received video data using analysis tools to determine whether the user's actions are appropriate. Based on the analysis results, it generates improvement suggestions as needed. The input is activity data, and the output is action evaluation and improvement suggestions. 【0334】 Step 6: 【0335】 Improvement suggestions are sent to the terminal, and the user is instructed accordingly. The terminal provides feedback to the user and instructs them to continue using the correct form and actions. The input is improvement suggestions, and the output is feedback to the user. 【0336】 Step 7: 【0337】 Using voice interaction, the device engages in natural conversation with the user, facilitating discussions designed to increase motivation for exercise. For example, prompts such as, "Let's take a short break. Continuing afterward will help maintain your health," are generated. Input is the user's utterances, and output is conversational support. 【0338】 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. 【0339】 This invention is a system that provides a personalized training experience tailored to the user's emotional state by incorporating an emotion engine into an AI-driven fitness assistant that enables users to effectively perform fitness training at home. Based on fitness goals, fitness levels, and past injury information entered by the user, the system uses AI to generate an individualized training menu. 【0340】 The system begins with the user launching a dedicated app on their device and entering the necessary information. The device then sends this information to a server. The server uses a generation algorithm to create a training menu tailored to the user's needs. This created menu is then visually displayed to the user via a hologram projector. For example, squats and yoga poses are displayed in 3D in front of the user. 【0341】 Furthermore, this system uses the terminal's camera to capture the user's movements during training in real time. This video data is analyzed on a server to evaluate whether the user is performing the exercises with proper form. If inappropriate movements are detected, the server sends instructions to the user to improve their form. 【0342】 A key feature of this invention is the incorporation of an emotion engine that recognizes the user's emotional state based on their actions and voice data. This emotion engine analyzes the user's facial expressions and tone of voice to evaluate their stress level, fatigue, and motivation. As a result, the server dynamically adjusts the intensity and type of exercise to provide the user with the most suitable training content. 【0343】 For example, if a user expresses fatigue, the device can provide feedback to lower the difficulty of the exercise or recommend relaxing exercises. The device also uses natural voice interaction to provide appropriate messages to boost user motivation. For instance, if it detects that the user's expression is discouraged, it might offer encouraging words such as, "Keep going like this and you'll see results!" 【0344】 In this way, the AI-driven hologram fitness assistant system can adapt to the user's emotions and physical condition, providing a fitness experience tailored to individual needs and supporting safe and sustainable training. 【0345】 The following describes the processing flow. 【0346】 Step 1: 【0347】 Users launch a dedicated app on their device and enter their fitness goals, fitness level, and past injury history. This information is then transmitted to the server via the device. 【0348】 Step 2: 【0349】 The server uses a generation algorithm to create a training menu tailored to the individual user's needs, based on the information obtained from the user. The exercises best suited to the user's current condition are selected. 【0350】 Step 3: 【0351】 The terminal receives the training menu from the server and sends it to a hologram projector, displaying it visually in front of the user. This allows the user to confirm the specific actions. 【0352】 Step 4: 【0353】 When a user begins training, the camera on the device captures the user's movements in real time and sends the video data to the server. 【0354】 Step 5: 【0355】 The server analyzes the video data and uses an AI algorithm to evaluate whether the user's actions are in the correct form. If there are any inappropriate actions, they are detected. 【0356】 Step 6: 【0357】 If inappropriate behavior is detected, the server identifies the behavior that needs correction, generates feedback to provide guidance on correct form, and notifies the user via the terminal. 【0358】 Step 7: 【0359】 The emotion engine analyzes the user's actions and voice data, recognizing the user's emotional state based on facial expressions and tone. This analysis identifies states such as fatigue or stress. 【0360】 Step 8: 【0361】 The server automatically adjusts the training content based on the analysis results of the emotion engine. For example, if the user is fatigued, it will either reduce the intensity of the exercise or recommend recovery exercises. 【0362】 Step 9: 【0363】 The device utilizes voice interaction capabilities to provide feedback to the user and support their motivation. For example, if it detects that the user's motivation is low, it will send an encouraging message. 【0364】 This process allows users to receive training tailored to their emotions and physical condition, enabling them to engage in fitness safely and sustainably. 【0365】 (Example 2) 【0366】 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". 【0367】 Traditional home fitness training has faced challenges such as users not receiving sufficient support regarding individualized exercise plans and motivation, leading to a lack of consistency and an increased risk of injury due to incorrect form. In addition, the lack of flexible support tailored to the user's emotional state limited training satisfaction and effectiveness. 【0368】 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. 【0369】 In this invention, the server includes an acquisition means for inputting exercise goals, physical fitness status, and past health information from the user; a generation means for generating an individualized exercise plan using a generative AI model; and an emotion analysis and adjustment means for evaluating the user's emotional state and dynamically adjusting the exercise content based on that evaluation. This enables users to receive individually optimized training at home, resulting in a safer, more effective, and sustainable fitness experience. 【0370】 "Means of acquisition" refers to the functions and mechanisms necessary for users to input their exercise goals, physical fitness status, and past health information. 【0371】 "Generation means" refers to a function or mechanism that generates an individualized motor plan using a generation AI model based on information obtained through acquisition means. 【0372】 "Presentation means" refers to functions or mechanisms for visually presenting the generated motion plan using a stereoscopic display device. 【0373】 "Analysis means" refers to functions or mechanisms for analyzing user motion data detected using imaging equipment and comparing it with proposed actions. 【0374】 "Instructional tools" refer to functions and mechanisms that provide guidance and advice to correct inaccurate movements based on the results of motion comparisons performed by analytical tools. 【0375】 An "emotional analysis and adjustment mechanism" is a function or system that evaluates the user's emotional state and dynamically adjusts the exercise content based on the evaluation results. 【0376】 A "progress management system" refers to a function or mechanism for recording the progress of exercise and providing users with information on its results and evaluations. 【0377】 "Voice dialogue means" refers to functions and mechanisms that use natural language processing to engage in voice dialogue with users and promote motivation. 【0378】 This invention is a system for users to effectively perform fitness training at home, utilizing AI technology to provide training tailored to the user's individual needs. The main components of this system include a server, a terminal, and user input. 【0379】 Users input their exercise goals, fitness level, and past health information using a dedicated app on their device. This information is transmitted to a server in real time. The server utilizes a generative AI model to generate a personalized exercise plan based on the received data. This generated exercise plan is then visually presented to the user via a 3D display on the device, specifically a hologram projector. For example, exercises such as squats and yoga are displayed as 3D models, providing visually clear instruction. 【0380】 Furthermore, the device captures the user's movements in real time during training through its built-in camera. This video data is analyzed on a server to evaluate whether the user is performing the exercises with proper form. For example, if the form is incorrect, corrective instructions such as "lower your hips a little more" are immediately provided. The server also analyzes the user's emotional state based on their facial expressions and tone of voice, and dynamically adjusts the exercise content accordingly. If fatigue is detected, the training intensity is reduced or relaxation exercises are suggested, enabling training that takes into account the user's health condition and motivation. 【0381】 Devices equipped with voice interaction capabilities can provide users with encouraging messages via voice to boost their motivation. For example, if a device detects that a user is feeling discouraged, it might send a message such as, "Keep going! You'll see results soon!" 【0382】 This system provides an optimal training environment based on the user's individual health data and emotional state, supporting a safe and effective fitness experience. 【0383】 Example of a prompt: 【0384】 "Analyze the user's emotional state and propose effective messages to boost their motivation." 【0385】 "Please generate an algorithm to calculate the optimal exercise intensity based on this user's activity data." 【0386】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0387】 Step 1: 【0388】 The user launches a dedicated app on their device and enters their exercise goals, fitness level, and past health information. The entered data, along with the user ID, is sent from the device to the server. The input in this step is fitness-related information provided by the user, and the output is the transmission of information to the server. 【0389】 Step 2: 【0390】 The server uses a generative AI model to generate a personalized exercise plan based on the received data. This process compares the data with various exercise data stored in a database to determine the optimal training program for the user. The input is the user's fitness information, and the output is the personalized exercise plan. 【0391】 Step 3: 【0392】 The server sends the generated exercise plan to the terminal, which then visually presents it to the user using a 3D display device. Specifically, a hologram projector displays the selected exercise in 3D. The input is the generated exercise plan, and the output is the visual presentation to the user. 【0393】 Step 4: 【0394】 When a user begins training, the device's camera captures the user's movements in real time. This video data is sent to a server for motion analysis. The input is video of the user's training movements, and the output is data for analysis. 【0395】 Step 5: 【0396】 The server uses analysis tools to evaluate the user's movements and verify whether the exercises are being performed with correct form. This evaluation is based on machine learning algorithms, and the data is processed to provide guidance on proper form. The input is video data, and the output is the results of the movement evaluation. 【0397】 Step 6: 【0398】 Based on the evaluation results, the server sends corrective instructions to the terminal as needed. If incorrect operation is detected, the terminal provides feedback to the user, such as "lower your stance a little." The input is the operation evaluation result, and the output is the corrective instructions to the user. 【0399】 Step 7: 【0400】 The device captures the user's facial expressions and voice and sends this data to the server. The server performs emotion analysis and dynamically adjusts the movement. The input is the user's facial expressions and voice data, and the output is the emotion evaluation result. 【0401】 Step 8: 【0402】 The server dynamically adjusts the exercise plan based on the emotional assessment results. If the server determines that the user is fatigued, it will reduce the exercise intensity or suggest relaxing exercises. The input is the emotional assessment results, and the output is the adjusted exercise plan. 【0403】 Step 9: 【0404】 The device uses natural language processing to provide the user with motivational voice messages. For example, if the user's motivation is low, a message such as "Keep going! You'll see results soon!" is sent. The input is a tailored exercise plan and emotional assessment, and the output is a voice message. 【0405】 (Application Example 2) 【0406】 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." 【0407】 The problem that this invention aims to solve is to provide personalized fitness training to individual users and to realize a training experience that takes into account the user's emotional state. In particular, it is necessary to dynamically adjust the training according to the user's motivation and physical condition, and to support the user's safety and sustainable improvement of fitness. Conventional systems have lacked an approach that reflects the individual emotional state of users, so there is a need to respond to user needs more effectively. 【0408】 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. 【0409】 In this invention, the server includes data receiving means for inputting fitness goals, fitness levels, and past injury information from the user; information generating means for creating an individualized training menu using a generation algorithm based on the information acquired by the data receiving means; and output means for visually communicating the training menu created by the information generating means using a three-dimensional display device. This enables the user to receive appropriate training tailored to their individual needs during fitness training at home. 【0410】 A "user" is an individual who uses a fitness training system to receive personalized training. 【0411】 "Data receiving means" refers to a device or method for inputting and collecting information from users, such as fitness goals, fitness levels, and past injury information. 【0412】 A "generative algorithm" is a process or procedure that creates personalized training menus based on the user information entered. 【0413】 "Information generation means" refers to a device or method for creating a training menu tailored to a user using a generation algorithm. 【0414】 A "three-dimensional display device" is a device that visually displays training menus and movements in three dimensions for the user. 【0415】 "Output means" refers to a device or method that visually communicates the created training menu to the user. 【0416】 A "video device" is a device that captures the user's training movements and processes them as video data. 【0417】 "Information analysis means" refers to a device or method for analyzing data captured by a video device and evaluating the user's actions. 【0418】 "Action guidance means" refers to a device or method that identifies an inappropriate user action and provides instructions to correct it. 【0419】 "Emotion recognition means" refers to a device or method for analyzing a user's facial expressions and voice and evaluating their emotional state. 【0420】 "Motor adjustment means" refers to a device or method for dynamically adjusting training content based on evaluation results from emotion recognition means. 【0421】 The system for carrying out this invention is an AI-driven fitness assistant system that provides personalized fitness training to the user. The system has the ability to take into account the user's emotional state and dynamically adjust the training plan. 【0422】 First, the user uses the device to input their fitness goals, fitness level, and past injury information. This information is sent to the server via a data receiving device. Based on the received information, the server runs a generative AI model to generate a personalized training menu. This generation process uses a generation algorithm that suggests the most suitable training for the user's health condition and goals. 【0423】 Next, the server presents the generated training menu to the user via a three-dimensional display device. The user performs the training according to the displayed image. The user's movements are captured by the video device and transmitted to the server. The server uses information analysis means to analyze the captured user movements and evaluate the accuracy of the training. If inappropriate movements are detected, the server uses movement guidance means to send instructions to the user to perform the correct movements. 【0424】 Furthermore, the system uses emotion recognition to analyze the user's facial expressions and voice to evaluate their emotional state. Based on the evaluation results, the exercise adjustment mechanism dynamically changes the training content, enabling the user to continue with optimal training tailored to their tone of voice and mood. For example, if the system determines that the user is tired, it will either reduce the intensity of the exercise or suggest exercises that promote relaxation. 【0425】 For example, if the emotion recognition system determines that the user is feeling down, the server will output a message such as, "If you keep going like this, you'll see results!" 【0426】 An example of a prompt message would be: "Based on the user's health and emotional state, provide an appropriate fitness plan and adjust the exercise in real time." 【0427】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0428】 Step 1: 【0429】 The user uses a device to input their fitness goals, fitness level, and past injury information, and sends this data to the server. The data receiving device records this user input and converts it into a format usable by the server. The server, upon receiving the input information, performs preprocessing to run the generative AI model. 【0430】 Step 2: 【0431】 The server uses a generative AI model based on the entered user information to create a personalized training menu. Specifically, the server applies a generative algorithm to select exercises that match the user's goals and fitness level. This process also takes into account limitations based on past injuries and health conditions. The resulting training menu is customized for each individual user. 【0432】 Step 3: 【0433】 The server visually presents the generated training menu to the user via a three-dimensional display device. The input here is the customized training menu, and the output is a visual training guide. The server converts this data into an appropriate format so that the display device can reproduce the image in three dimensions. 【0434】 Step 4: 【0435】 A video device installed on the terminal captures the user's movements in real time during training. This video data is sent to a server for analysis. The input is video of the user's training movements, and the server uses this video to perform motion analysis. 【0436】 Step 5: 【0437】 The server uses information analysis tools to analyze the user's movements and evaluate the accuracy of the training. In this step, the server analyzes the user's posture and movement form based on the input video data. If inappropriate movements are identified as a result, the movement instruction tool generates corrective instructions and sends them to the user. 【0438】 Step 6: 【0439】 The server analyzes the user's facial expressions and voice data to evaluate their emotional state. This evaluation is performed using emotion recognition technology. The input consists of the user's facial image and voice data, which are analyzed to infer the user's psychological state. The output is evaluation information regarding the user's emotional state. 【0440】 Step 7: 【0441】 The server dynamically adjusts the training content using exercise adjustment mechanisms based on the results of emotion recognition evaluations. The input here is emotion evaluation information, and the output is the adjusted training menu. For example, if the user indicates fatigue, the server reduces the intensity of the exercise and recommends more relaxing exercises. This adjustment allows the user to continue having an optimal fitness experience. 【0442】 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. 【0443】 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. 【0444】 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. 【0445】 [Third Embodiment] 【0446】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0447】 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. 【0448】 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). 【0449】 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. 【0450】 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. 【0451】 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). 【0452】 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. 【0453】 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. 【0454】 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. 【0455】 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. 【0456】 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. 【0457】 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". 【0458】 This invention relates to an AI-driven hologram fitness assistant system that enables users to receive high-quality fitness guidance at home. The system generates personalized training menus based on the user's fitness goals, fitness level, and past injury information, and provides visual guidance through a hologram projector. 【0459】 In using the system, users first launch a dedicated app and input their fitness goals and profile information into their device. The device sends this information to a server, which then generates a personalized training menu. This generation uses an AI algorithm to suggest exercises that are best suited to the user's needs. 【0460】 The generated training menu is transmitted via the terminal to a hologram projector and displayed in a functional format in front of the user. For example, the correct form for squats and push-ups is shown in 3D. This visual guide allows the user to intuitively understand how to perform the movements. 【0461】 Furthermore, a camera built into the device captures the user's training movements in real time and sends the video data to a server. The server analyzes the video data using AI to evaluate whether the user's movements are correct. If inappropriate movements are detected, the server notifies the user via the device with instructions for improvement. This guidance process allows users to maximize the effectiveness of their training while reducing the risk of injury. 【0462】 The server also records training progress and manages the user's progress toward their fitness goals. The device periodically reports progress to the user and provides feedback according to the milestones achieved. This makes it easier for the user to maintain motivation. 【0463】 Finally, the device interacts with the user through voice dialogue, further increasing motivation for training through natural conversation. For example, if the user says, "I'm tired today," the device will encourage them by saying, "It's important to keep going, even if you have to reduce the workload a little. Let's do our best!" 【0464】 In this way, this system enables users to receive the specialized fitness instruction they need at home, supporting their health improvement. 【0465】 The following describes the processing flow. 【0466】 Step 1: 【0467】 Users launch a dedicated app on their device and enter information such as their fitness goals, current fitness level, and past injury history. This information is then sent from the device to the server. 【0468】 Step 2: 【0469】 The server uses an AI algorithm to generate personalized training menus based on information received from the user. The generated menus are then adjusted to match the user's needs and constraints. 【0470】 Step 3: 【0471】 The terminal receives the training menu from the server and sends it to a hologram projector, which then visualizes and displays the training movements in 3D in front of the user. 【0472】 Step 4: 【0473】 When a user begins training, the camera on the device captures the user's movements in real time. This video data is sent to the server. 【0474】 Step 5: 【0475】 The server analyzes the video data and uses AI to evaluate whether the user's movements are in line with the correct form. This helps determine if the user is training correctly. 【0476】 Step 6: 【0477】 If inappropriate behavior is detected, the server generates appropriate feedback and notifies the user through the terminal. The user can then correct their behavior based on the hologram and audio guidance. 【0478】 Step 7: 【0479】 The server records and analyzes training results and progress to manage progress toward long-term fitness goals. Users receive regular progress feedback from their devices. 【0480】 Step 8: 【0481】 The device utilizes voice interaction capabilities to engage with the user and provide the necessary support to maintain motivation during training. This interaction allows the user to continue training more effectively. 【0482】 (Example 1) 【0483】 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." 【0484】 Traditional personalized fitness instruction often lacked the ability to provide accurate movements and effective training plans without a professional trainer, making it difficult for individuals to safely and efficiently engage in fitness at home. Furthermore, challenges remained in properly assessing movements and maintaining motivation. 【0485】 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. 【0486】 In this invention, the server includes a device for acquiring information on the user's physical ability goals, health status, and medical history; a device for generating personalized exercise guidance using artificial intelligence technology; and a device for providing the guidance visually using 3D display technology. This enables the user to train safely and efficiently at home, and to properly evaluate their movements and maintain motivation. 【0487】 A "user" refers to an individual who uses the system to create a fitness plan and improve their health. 【0488】 "Physical ability goals" refer to objectives related to the fitness level or exercise results that the user wants to achieve. 【0489】 "Health status" refers to information about the user's current physical condition, health history, and past injuries. 【0490】 "Medical history information" refers to data about injuries and illnesses that a user has experienced in the past, and is used by the system to provide personalized training. 【0491】 "Device" refers to each component of this system, specifically a combination of hardware and software designed to perform a particular function. 【0492】 "Artificial intelligence technology" refers to machine learning and data processing technologies used to analyze user information and provide optimized exercise guidance. 【0493】 "Personalized exercise instruction" refers to a training program customized to the user's specific needs and goals. 【0494】 "3D display technology" refers to technology that uses hologram projectors and other devices to display information in three dimensions, enabling users to receive exercise instruction visually. 【0495】 "Presenting information visually" refers to a method of displaying information through visual means to help users understand it. 【0496】 This invention provides a system that allows users to receive professional fitness instruction at home, offering personalized training tailored to the user's goals and health condition. This system is realized by combining various hardware and software technologies. 【0497】 Users input information about their physical abilities, health status, and medical history using a dedicated terminal. The terminal transmits this information to a server using a secure communication protocol. The terminal includes devices such as smartphones and tablets. 【0498】 The server uses artificial intelligence technology to generate personalized exercise guidance based on the information it receives. This AI technology includes machine learning algorithms to process user data and propose the optimal fitness plan. The server can utilize a cloud computing environment or a dedicated on-premises server. 【0499】 The generated exercise instructions are transmitted via a terminal to a device using 3D display technology, such as a hologram projector, and displayed as visual feedback around the user. This allows the user to intuitively understand and imitate the prescribed forms and movements. For example, the correct posture for squats and push-ups is presented in three dimensions. 【0500】 The device is equipped with a camera that captures the user's movements in real time. The captured video data is sent to a server, where AI technology is used to analyze the movements. Based on the analysis results, the server provides feedback on the user's form and supports them in correcting their movements appropriately. 【0501】 For example, when a user enters a prompt such as "I want to do full-body training three times a week," the AI ​​generates a corresponding training program and provides visual guidance through a hologram. In this way, the present invention provides an optimized fitness experience for each individual user and supports health promotion. 【0502】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0503】 Step 1: 【0504】 The user launches a dedicated application and enters information about their physical abilities, health status, and medical history into the terminal. The entered data is formatted along with the user ID and prepared to be sent to the server. For example, the user might enter information such as "Age: 35, Goal: Lose 5kg, History of knee injury." 【0505】 Step 2: 【0506】 The terminal transmits user input data to the server using a secure protocol. User information, which is the input, is protected by communication encryption technology before being sent to the server, and this data is temporarily stored in the user database. 【0507】 Step 3: 【0508】 The server generates personalized exercise guidance using a generated AI model based on the received user information. In this process, an algorithm is used to analyze the input data and determine the optimal exercise plan for the user's goals. The server might output results such as "30 minutes of low-intensity aerobic exercise three times a week." 【0509】 Step 4: 【0510】 The exercise instruction plan generated on the server is sent to the terminal, which converts it into a visual hologram display and presents it to the user. Specifically, the terminal uses a hologram projector to show the user movements such as "squats" and "planks" in three dimensions. 【0511】 Step 5: 【0512】 The camera on the device captures the user's training in real time. This is to verify the user's form according to the hologram display, and the captured data is sent to the server as input. 【0513】 Step 6: 【0514】 The server analyzes the captured video data and uses a motion analysis algorithm to evaluate the user's form appropriately. Based on this input data, output feedback is generated, such as "the knee angle is too shallow." 【0515】 Step 7: 【0516】 Feedback from the server is communicated to the user via the terminal. The terminal conveys this information to the user via voice or text, guiding them through necessary form corrections. A concrete example of this action is to give instructions such as, "Please squat down a little deeper." 【0517】 Step 8: 【0518】 The server also stores training data and manages user progress. This records the user's progress towards their fitness goals and is used to suggest future training sessions. At this step, progress reports can be output, such as "30% of goal achieved." 【0519】 (Application Example 1) 【0520】 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." 【0521】 In recent years, with the rise in health awareness, there has been an increasing demand for personalized health maintenance methods. However, traditional exercise guidance is uniform, making it difficult to provide appropriate approaches tailored to the characteristics of individual residents. Furthermore, there is a need to eliminate health disparities among residents and improve the overall health level by providing consistent health guidance within residential facilities. In addition, there is a need for natural means of dialogue that will increase residents' motivation. 【0522】 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. 【0523】 In this invention, the server includes an acquisition means for inputting goals, health levels, and historical information from users; a generation means for creating an individualized exercise plan using a generation method based on the information acquired by the acquisition means; and a management means for providing health guidance to residents within a residential facility and for visualizing the health information of the collective. This enables the provision of individualized and appropriate health guidance, improving the health level and motivation of residents. 【0524】 "Acquisition means" refers to a device or method for inputting user goals, health levels, and historical information. 【0525】 "Generation means" refers to a device or method that creates an individualized movement plan using a generation method based on information obtained by acquisition means. 【0526】 "Display means" refers to a device or method for visually presenting a motion plan created by a generation means. 【0527】 "Analysis means" refers to a device or method that analyzes user activity information detected by an imaging device and compares it with proposed activities. 【0528】 "Instructional means" refers to a device or method for correcting inappropriate activities based on comparative results obtained through analytical means. 【0529】 "Management means" refers to a device or method for providing health guidance to residents within a residential facility and for visualizing healthy information about the collective. 【0530】 "Voice dialogue means" refers to a device or method for conducting natural dialogue in order to improve residents' motivation. 【0531】 The system for implementing this invention mainly consists of a server, terminals in each household, an imaging device, and a display device. First, the user uses the terminal to input their goals, health level, and history information, and transmits the data to the server via an acquisition means. Based on the acquired data, the server uses a generation AI model to create a personalized exercise plan. The generated exercise plan is sent to the display device via the terminal to provide visual guidance. 【0532】 During the user's exercise, the imaging device captures the user's movements in real time and transmits the data to a server for analysis. The server uses analysis tools to evaluate the user's activity and provides the user with guidance on areas that need correction. This allows the user to exercise safely and effectively. 【0533】 Furthermore, the management system aggregates and visualizes health data from all residents within the residential facility, enabling the sharing of health information among residents. The voice interaction system is used to improve motivation through interaction with the user. For example, if a user says they want to stop exercising, it generates and responds with a prompt such as, "Let's take a short break. You can maintain your health by continuing afterward." 【0534】 A concrete example of this system is a scenario where residents receive individual yoga or strength training instruction in a shared fitness room. Residents can receive health advice from their respective terminals and motivate each other. An example of a prompt message for the generated AI model is the question the server might receive: "Please tell me how residents can maintain their motivation to continue fitness at home." 【0535】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0536】 Step 1: 【0537】 The user uses a terminal to input goals, health levels, and historical information. The terminal sends this input data to the server. The input here includes the user's fitness goals and past injury information, and the output is the user data sent to the server. 【0538】 Step 2: 【0539】 The server uses a generative AI model to generate a personalized exercise plan based on the received user data. This process creates an exercise menu tailored to the user's goals and fitness level. The input is user data, and the output is the personalized exercise plan. 【0540】 Step 3: 【0541】 The generated exercise plan is transmitted to the display device via the terminal. The terminal visually presents the plan and manipulates a hologram to provide fitness guidance to the user. The input is the generated exercise plan, and the output is the displayed hologram menu. 【0542】 Step 4: 【0543】 When a user performs an exercise, the imaging device captures the user's movements in real time and transmits the data to the server. The input is the user's movement video, and the output is the activity data sent to the server. 【0544】 Step 5: 【0545】 The server evaluates the received video data using analysis tools to determine whether the user's actions are appropriate. Based on the analysis results, it generates improvement suggestions as needed. The input is activity data, and the output is action evaluation and improvement suggestions. 【0546】 Step 6: 【0547】 Improvement suggestions are sent to the terminal, and the user is instructed accordingly. The terminal provides feedback to the user and instructs them to continue using the correct form and actions. The input is improvement suggestions, and the output is feedback to the user. 【0548】 Step 7: 【0549】 Using voice interaction, the device engages in natural conversation with the user, facilitating discussions designed to increase motivation for exercise. For example, prompts such as, "Let's take a short break. Continuing afterward will help maintain your health," are generated. Input is the user's utterances, and output is conversational support. 【0550】 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. 【0551】 This invention is a system that provides a personalized training experience tailored to the user's emotional state by incorporating an emotion engine into an AI-driven fitness assistant that enables users to effectively perform fitness training at home. Based on fitness goals, fitness levels, and past injury information entered by the user, the system uses AI to generate an individualized training menu. 【0552】 The system begins with the user launching a dedicated app on their device and entering the necessary information. The device then sends this information to a server. The server uses a generation algorithm to create a training menu tailored to the user's needs. This created menu is then visually displayed to the user via a hologram projector. For example, squats and yoga poses are displayed in 3D in front of the user. 【0553】 Furthermore, this system uses the terminal's camera to capture the user's movements during training in real time. This video data is analyzed on a server to evaluate whether the user is performing the exercises with proper form. If inappropriate movements are detected, the server sends instructions to the user to improve their form. 【0554】 A key feature of this invention is the incorporation of an emotion engine that recognizes the user's emotional state based on their actions and voice data. This emotion engine analyzes the user's facial expressions and tone of voice to evaluate their stress level, fatigue, and motivation. As a result, the server dynamically adjusts the intensity and type of exercise to provide the user with the most suitable training content. 【0555】 For example, if a user expresses fatigue, the device can provide feedback to lower the difficulty of the exercise or recommend relaxing exercises. The device also uses natural voice interaction to provide appropriate messages to boost user motivation. For instance, if it detects that the user's expression is discouraged, it might offer encouraging words such as, "Keep going like this and you'll see results!" 【0556】 In this way, the AI-driven hologram fitness assistant system can adapt to the user's emotions and physical condition, providing a fitness experience tailored to individual needs and supporting safe and sustainable training. 【0557】 The following describes the processing flow. 【0558】 Step 1: 【0559】 Users launch a dedicated app on their device and enter their fitness goals, fitness level, and past injury history. This information is then transmitted to the server via the device. 【0560】 Step 2: 【0561】 The server uses a generation algorithm to create a training menu tailored to the individual user's needs, based on the information obtained from the user. The exercises best suited to the user's current condition are selected. 【0562】 Step 3: 【0563】 The terminal receives the training menu from the server and sends it to a hologram projector, displaying it visually in front of the user. This allows the user to confirm the specific actions. 【0564】 Step 4: 【0565】 When a user begins training, the camera on the device captures the user's movements in real time and sends the video data to the server. 【0566】 Step 5: 【0567】 The server analyzes the video data and uses an AI algorithm to evaluate whether the user's actions are in the correct form. If there are any inappropriate actions, they are detected. 【0568】 Step 6: 【0569】 If inappropriate behavior is detected, the server identifies the behavior that needs correction, generates feedback to provide guidance on correct form, and notifies the user via the terminal. 【0570】 Step 7: 【0571】 The emotion engine analyzes the user's actions and voice data, recognizing the user's emotional state based on facial expressions and tone. This analysis identifies states such as fatigue or stress. 【0572】 Step 8: 【0573】 The server automatically adjusts the training content based on the analysis results of the emotion engine. For example, if the user is fatigued, it will either reduce the intensity of the exercise or recommend recovery exercises. 【0574】 Step 9: 【0575】 The device utilizes voice interaction capabilities to provide feedback to the user and support their motivation. For example, if it detects that the user's motivation is low, it will send an encouraging message. 【0576】 This process allows users to receive training tailored to their emotions and physical condition, enabling them to engage in fitness safely and sustainably. 【0577】 (Example 2) 【0578】 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." 【0579】 Traditional home fitness training has faced challenges such as users not receiving sufficient support regarding individualized exercise plans and motivation, leading to a lack of consistency and an increased risk of injury due to incorrect form. In addition, the lack of flexible support tailored to the user's emotional state limited training satisfaction and effectiveness. 【0580】 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. 【0581】 In this invention, the server includes an acquisition means for inputting exercise goals, physical fitness status, and past health information from the user; a generation means for generating an individualized exercise plan using a generative AI model; and an emotion analysis and adjustment means for evaluating the user's emotional state and dynamically adjusting the exercise content based on that evaluation. This enables users to receive individually optimized training at home, resulting in a safer, more effective, and sustainable fitness experience. 【0582】 "Means of acquisition" refers to the functions and mechanisms necessary for users to input their exercise goals, physical fitness status, and past health information. 【0583】 "Generation means" refers to a function or mechanism that generates an individualized motor plan using a generation AI model based on information obtained through acquisition means. 【0584】 "Presentation means" refers to functions or mechanisms for visually presenting the generated motion plan using a stereoscopic display device. 【0585】 "Analysis means" refers to functions or mechanisms for analyzing user motion data detected using imaging equipment and comparing it with proposed actions. 【0586】 "Instructional tools" refer to functions and mechanisms that provide guidance and advice to correct inaccurate movements based on the results of motion comparisons performed by analytical tools. 【0587】 An "emotional analysis and adjustment mechanism" is a function or system that evaluates the user's emotional state and dynamically adjusts the exercise content based on the evaluation results. 【0588】 A "progress management system" refers to a function or mechanism for recording the progress of exercise and providing users with information on its results and evaluations. 【0589】 "Voice dialogue means" refers to functions and mechanisms that use natural language processing to engage in voice dialogue with users and promote motivation. 【0590】 This invention is a system for users to effectively perform fitness training at home, utilizing AI technology to provide training tailored to the user's individual needs. The main components of this system include a server, a terminal, and user input. 【0591】 Users input their exercise goals, fitness level, and past health information using a dedicated app on their device. This information is transmitted to a server in real time. The server utilizes a generative AI model to generate a personalized exercise plan based on the received data. This generated exercise plan is then visually presented to the user via a 3D display on the device, specifically a hologram projector. For example, exercises such as squats and yoga are displayed as 3D models, providing visually clear instruction. 【0592】 Furthermore, the device captures the user's movements in real time during training through its built-in camera. This video data is analyzed on a server to evaluate whether the user is performing the exercises with proper form. For example, if the form is incorrect, corrective instructions such as "lower your hips a little more" are immediately provided. The server also analyzes the user's emotional state based on their facial expressions and tone of voice, and dynamically adjusts the exercise content accordingly. If fatigue is detected, the training intensity is reduced or relaxation exercises are suggested, enabling training that takes into account the user's health condition and motivation. 【0593】 Devices equipped with voice interaction capabilities can provide users with encouraging messages via voice to boost their motivation. For example, if a device detects that a user is feeling discouraged, it might send a message such as, "Keep going! You'll see results soon!" 【0594】 This system provides an optimal training environment based on the user's individual health data and emotional state, supporting a safe and effective fitness experience. 【0595】 Example of a prompt: 【0596】 "Analyze the user's emotional state and propose effective messages to boost their motivation." 【0597】 "Please generate an algorithm to calculate the optimal exercise intensity based on this user's activity data." 【0598】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0599】 Step 1: 【0600】 The user launches a dedicated app on their device and enters their exercise goals, fitness level, and past health information. The entered data, along with the user ID, is sent from the device to the server. The input in this step is fitness-related information provided by the user, and the output is the transmission of information to the server. 【0601】 Step 2: 【0602】 The server uses a generative AI model to generate a personalized exercise plan based on the received data. This process compares the data with various exercise data stored in a database to determine the optimal training program for the user. The input is the user's fitness information, and the output is the personalized exercise plan. 【0603】 Step 3: 【0604】 The server sends the generated exercise plan to the terminal, which then visually presents it to the user using a 3D display device. Specifically, a hologram projector displays the selected exercise in 3D. The input is the generated exercise plan, and the output is the visual presentation to the user. 【0605】 Step 4: 【0606】 When a user begins training, the device's camera captures the user's movements in real time. This video data is sent to a server for motion analysis. The input is video of the user's training movements, and the output is data for analysis. 【0607】 Step 5: 【0608】 The server uses analysis tools to evaluate the user's movements and verify whether the exercises are being performed with correct form. This evaluation is based on machine learning algorithms, and the data is processed to provide guidance on proper form. The input is video data, and the output is the results of the movement evaluation. 【0609】 Step 6: 【0610】 Based on the evaluation results, the server sends corrective instructions to the terminal as needed. If incorrect operation is detected, the terminal provides feedback to the user, such as "lower your stance a little." The input is the operation evaluation result, and the output is the corrective instructions to the user. 【0611】 Step 7: 【0612】 The device captures the user's facial expressions and voice and sends this data to the server. The server performs emotion analysis and dynamically adjusts the movement. The input is the user's facial expressions and voice data, and the output is the emotion evaluation result. 【0613】 Step 8: 【0614】 The server dynamically adjusts the exercise plan based on the emotional assessment results. If the server determines that the user is fatigued, it will reduce the exercise intensity or suggest relaxing exercises. The input is the emotional assessment results, and the output is the adjusted exercise plan. 【0615】 Step 9: 【0616】 The device uses natural language processing to provide the user with motivational voice messages. For example, if the user's motivation is low, a message such as "Keep going! You'll see results soon!" is sent. The input is a tailored exercise plan and emotional assessment, and the output is a voice message. 【0617】 (Application Example 2) 【0618】 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." 【0619】 The problem that this invention aims to solve is to provide personalized fitness training to individual users and to realize a training experience that takes into account the user's emotional state. In particular, it is necessary to dynamically adjust the training according to the user's motivation and physical condition, and to support the user's safety and sustainable improvement of fitness. Conventional systems have lacked an approach that reflects the individual emotional state of users, so there is a need to respond to user needs more effectively. 【0620】 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. 【0621】 In this invention, the server includes data receiving means for inputting fitness goals, fitness levels, and past injury information from the user; information generating means for creating an individualized training menu using a generation algorithm based on the information acquired by the data receiving means; and output means for visually communicating the training menu created by the information generating means using a three-dimensional display device. This enables the user to receive appropriate training tailored to their individual needs during fitness training at home. 【0622】 A "user" is an individual who uses a fitness training system to receive personalized training. 【0623】 "Data receiving means" refers to a device or method for inputting and collecting information from users, such as fitness goals, fitness levels, and past injury information. 【0624】 A "generative algorithm" is a process or procedure that creates personalized training menus based on the user information entered. 【0625】 "Information generation means" refers to a device or method for creating a training menu tailored to a user using a generation algorithm. 【0626】 A "three-dimensional display device" is a device that visually displays training menus and movements in three dimensions for the user. 【0627】 "Output means" refers to a device or method that visually communicates the created training menu to the user. 【0628】 A "video device" is a device that captures the user's training movements and processes them as video data. 【0629】 "Information analysis means" refers to a device or method for analyzing data captured by a video device and evaluating the user's actions. 【0630】 "Action guidance means" refers to a device or method that identifies an inappropriate user action and provides instructions to correct it. 【0631】 "Emotion recognition means" refers to a device or method for analyzing a user's facial expressions and voice and evaluating their emotional state. 【0632】 "Motor adjustment means" refers to a device or method for dynamically adjusting training content based on evaluation results from emotion recognition means. 【0633】 The system for carrying out this invention is an AI-driven fitness assistant system that provides personalized fitness training to the user. The system has the ability to take into account the user's emotional state and dynamically adjust the training plan. 【0634】 First, the user uses the device to input their fitness goals, fitness level, and past injury information. This information is sent to the server via a data receiving device. Based on the received information, the server runs a generative AI model to generate a personalized training menu. This generation process uses a generation algorithm that suggests the most suitable training for the user's health condition and goals. 【0635】 Next, the server presents the generated training menu to the user via a three-dimensional display device. The user performs the training according to the displayed image. The user's movements are captured by the video device and transmitted to the server. The server uses information analysis means to analyze the captured user movements and evaluate the accuracy of the training. If inappropriate movements are detected, the server uses movement guidance means to send instructions to the user to perform the correct movements. 【0636】 Furthermore, the system uses emotion recognition to analyze the user's facial expressions and voice to evaluate their emotional state. Based on the evaluation results, the exercise adjustment mechanism dynamically changes the training content, enabling the user to continue with optimal training tailored to their tone of voice and mood. For example, if the system determines that the user is tired, it will either reduce the intensity of the exercise or suggest exercises that promote relaxation. 【0637】 For example, if the emotion recognition system determines that the user is feeling down, the server will output a message such as, "If you keep going like this, you'll see results!" 【0638】 An example of a prompt message would be: "Based on the user's health and emotional state, provide an appropriate fitness plan and adjust the exercise in real time." 【0639】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0640】 Step 1: 【0641】 The user uses a device to input their fitness goals, fitness level, and past injury information, and sends this data to the server. The data receiving device records this user input and converts it into a format usable by the server. The server, upon receiving the input information, performs preprocessing to run the generative AI model. 【0642】 Step 2: 【0643】 The server uses a generative AI model based on the entered user information to create a personalized training menu. Specifically, the server applies a generative algorithm to select exercises that match the user's goals and fitness level. This process also takes into account limitations based on past injuries and health conditions. The resulting training menu is customized for each individual user. 【0644】 Step 3: 【0645】 The server visually presents the generated training menu to the user via a three-dimensional display device. The input here is the customized training menu, and the output is a visual training guide. The server converts this data into an appropriate format so that the display device can reproduce the image in three dimensions. 【0646】 Step 4: 【0647】 A video device installed on the terminal captures the user's movements in real time during training. This video data is sent to a server for analysis. The input is video of the user's training movements, and the server uses this video to perform motion analysis. 【0648】 Step 5: 【0649】 The server uses information analysis tools to analyze the user's movements and evaluate the accuracy of the training. In this step, the server analyzes the user's posture and movement form based on the input video data. If inappropriate movements are identified as a result, the movement instruction tool generates corrective instructions and sends them to the user. 【0650】 Step 6: 【0651】 The server analyzes the user's facial expressions and voice data to evaluate their emotional state. This evaluation is performed using emotion recognition technology. The input consists of the user's facial image and voice data, which are analyzed to infer the user's psychological state. The output is evaluation information regarding the user's emotional state. 【0652】 Step 7: 【0653】 The server dynamically adjusts the training content using exercise adjustment mechanisms based on the results of emotion recognition evaluations. The input here is emotion evaluation information, and the output is the adjusted training menu. For example, if the user indicates fatigue, the server reduces the intensity of the exercise and recommends more relaxing exercises. This adjustment allows the user to continue having an optimal fitness experience. 【0654】 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. 【0655】 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. 【0656】 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. 【0657】 [Fourth Embodiment] 【0658】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0659】 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. 【0660】 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). 【0661】 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. 【0662】 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. 【0663】 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). 【0664】 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. 【0665】 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. 【0666】 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. 【0667】 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. 【0668】 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. 【0669】 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. 【0670】 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". 【0671】 This invention relates to an AI-driven hologram fitness assistant system that enables users to receive high-quality fitness guidance at home. The system generates personalized training menus based on the user's fitness goals, fitness level, and past injury information, and provides visual guidance through a hologram projector. 【0672】 In using the system, users first launch a dedicated app and input their fitness goals and profile information into their device. The device sends this information to a server, which then generates a personalized training menu. This generation uses an AI algorithm to suggest exercises that are best suited to the user's needs. 【0673】 The generated training menu is transmitted via the terminal to a hologram projector and displayed in a functional format in front of the user. For example, the correct form for squats and push-ups is shown in 3D. This visual guide allows the user to intuitively understand how to perform the movements. 【0674】 Furthermore, a camera built into the device captures the user's training movements in real time and sends the video data to a server. The server analyzes the video data using AI to evaluate whether the user's movements are correct. If inappropriate movements are detected, the server notifies the user via the device with instructions for improvement. This guidance process allows users to maximize the effectiveness of their training while reducing the risk of injury. 【0675】 The server also records training progress and manages the user's progress toward their fitness goals. The device periodically reports progress to the user and provides feedback according to the milestones achieved. This makes it easier for the user to maintain motivation. 【0676】 Finally, the device interacts with the user through voice dialogue, further increasing motivation for training through natural conversation. For example, if the user says, "I'm tired today," the device will encourage them by saying, "It's important to keep going, even if you have to reduce the workload a little. Let's do our best!" 【0677】 In this way, this system enables users to receive the specialized fitness instruction they need at home, supporting their health improvement. 【0678】 The following describes the processing flow. 【0679】 Step 1: 【0680】 Users launch a dedicated app on their device and enter information such as their fitness goals, current fitness level, and past injury history. This information is then sent from the device to the server. 【0681】 Step 2: 【0682】 The server uses an AI algorithm to generate personalized training menus based on information received from the user. The generated menus are then adjusted to match the user's needs and constraints. 【0683】 Step 3: 【0684】 The terminal receives the training menu from the server and sends it to a hologram projector, which then visualizes and displays the training movements in 3D in front of the user. 【0685】 Step 4: 【0686】 When a user begins training, the camera on the device captures the user's movements in real time. This video data is sent to the server. 【0687】 Step 5: 【0688】 The server analyzes the video data and uses AI to evaluate whether the user's movements are in line with the correct form. This helps determine if the user is training correctly. 【0689】 Step 6: 【0690】 If inappropriate behavior is detected, the server generates appropriate feedback and notifies the user through the terminal. The user can then correct their behavior based on the hologram and audio guidance. 【0691】 Step 7: 【0692】 The server records and analyzes training results and progress to manage progress toward long-term fitness goals. Users receive regular progress feedback from their devices. 【0693】 Step 8: 【0694】 The device utilizes voice interaction capabilities to engage with the user and provide the necessary support to maintain motivation during training. This interaction allows the user to continue training more effectively. 【0695】 (Example 1) 【0696】 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". 【0697】 Traditional personalized fitness instruction often lacked the ability to provide accurate movements and effective training plans without a professional trainer, making it difficult for individuals to safely and efficiently engage in fitness at home. Furthermore, challenges remained in properly assessing movements and maintaining motivation. 【0698】 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. 【0699】 In this invention, the server includes a device for acquiring information on the user's physical ability goals, health status, and medical history; a device for generating personalized exercise guidance using artificial intelligence technology; and a device for providing the guidance visually using 3D display technology. This enables the user to train safely and efficiently at home, and to properly evaluate their movements and maintain motivation. 【0700】 A "user" refers to an individual who uses the system to create a fitness plan and improve their health. 【0701】 "Physical ability goals" refer to objectives related to the fitness level or exercise results that the user wants to achieve. 【0702】 "Health status" refers to information about the user's current physical condition, health history, and past injuries. 【0703】 "Medical history information" refers to data about injuries and illnesses that a user has experienced in the past, and is used by the system to provide personalized training. 【0704】 "Device" refers to each component of this system, specifically a combination of hardware and software designed to perform a particular function. 【0705】 "Artificial intelligence technology" refers to machine learning and data processing technologies used to analyze user information and provide optimized exercise guidance. 【0706】 "Personalized exercise instruction" refers to a training program customized to the user's specific needs and goals. 【0707】 "3D display technology" refers to technology that uses hologram projectors and other devices to display information in three dimensions, enabling users to receive exercise instruction visually. 【0708】 "Presenting information visually" refers to a method of displaying information through visual means to help users understand it. 【0709】 This invention provides a system that allows users to receive professional fitness instruction at home, offering personalized training tailored to the user's goals and health condition. This system is realized by combining various hardware and software technologies. 【0710】 Users input information about their physical abilities, health status, and medical history using a dedicated terminal. The terminal transmits this information to a server using a secure communication protocol. The terminal includes devices such as smartphones and tablets. 【0711】 The server uses artificial intelligence technology to generate personalized exercise guidance based on the information it receives. This AI technology includes machine learning algorithms to process user data and propose the optimal fitness plan. The server can utilize a cloud computing environment or a dedicated on-premises server. 【0712】 The generated exercise instructions are transmitted via a terminal to a device using 3D display technology, such as a hologram projector, and displayed as visual feedback around the user. This allows the user to intuitively understand and imitate the prescribed forms and movements. For example, the correct posture for squats and push-ups is presented in three dimensions. 【0713】 The device is equipped with a camera that captures the user's movements in real time. The captured video data is sent to a server, where AI technology is used to analyze the movements. Based on the analysis results, the server provides feedback on the user's form and supports them in correcting their movements appropriately. 【0714】 For example, when a user enters a prompt such as "I want to do full-body training three times a week," the AI ​​generates a corresponding training program and provides visual guidance through a hologram. In this way, the present invention provides an optimized fitness experience for each individual user and supports health promotion. 【0715】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0716】 Step 1: 【0717】 The user launches a dedicated application and enters information about their physical abilities, health status, and medical history into the terminal. The entered data is formatted along with the user ID and prepared to be sent to the server. For example, the user might enter information such as "Age: 35, Goal: Lose 5kg, History of knee injury." 【0718】 Step 2: 【0719】 The terminal transmits user input data to the server using a secure protocol. User information, which is the input, is protected by communication encryption technology before being sent to the server, and this data is temporarily stored in the user database. 【0720】 Step 3: 【0721】 The server generates personalized exercise guidance using a generated AI model based on the received user information. In this process, an algorithm is used to analyze the input data and determine the optimal exercise plan for the user's goals. The server might output results such as "30 minutes of low-intensity aerobic exercise three times a week." 【0722】 Step 4: 【0723】 The exercise instruction plan generated on the server is sent to the terminal, which converts it into a visual hologram display and presents it to the user. Specifically, the terminal uses a hologram projector to show the user movements such as "squats" and "planks" in three dimensions. 【0724】 Step 5: 【0725】 The camera on the device captures the user's training in real time. This is to verify the user's form according to the hologram display, and the captured data is sent to the server as input. 【0726】 Step 6: 【0727】 The server analyzes the captured video data and uses a motion analysis algorithm to evaluate the user's form appropriately. Based on this input data, output feedback is generated, such as "the knee angle is too shallow." 【0728】 Step 7: 【0729】 Feedback from the server is communicated to the user via the terminal. The terminal conveys this information to the user via voice or text, guiding them through necessary form corrections. A concrete example of this action is to give instructions such as, "Please squat down a little deeper." 【0730】 Step 8: 【0731】 The server also stores training data and manages user progress. This records the user's progress towards their fitness goals and is used to suggest future training sessions. At this step, progress reports can be output, such as "30% of goal achieved." 【0732】 (Application Example 1) 【0733】 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". 【0734】 In recent years, with the rise in health awareness, there has been an increasing demand for personalized health maintenance methods. However, traditional exercise guidance is uniform, making it difficult to provide appropriate approaches tailored to the characteristics of individual residents. Furthermore, there is a need to eliminate health disparities among residents and improve the overall health level by providing consistent health guidance within residential facilities. In addition, there is a need for natural means of dialogue that will increase residents' motivation. 【0735】 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. 【0736】 In this invention, the server includes an acquisition means for inputting goals, health levels, and historical information from users; a generation means for creating an individualized exercise plan using a generation method based on the information acquired by the acquisition means; and a management means for providing health guidance to residents within a residential facility and for visualizing the health information of the collective. This enables the provision of individualized and appropriate health guidance, improving the health level and motivation of residents. 【0737】 "Acquisition means" refers to a device or method for inputting user goals, health levels, and historical information. 【0738】 "Generation means" refers to a device or method that creates an individualized movement plan using a generation method based on information obtained by acquisition means. 【0739】 "Display means" refers to a device or method for visually presenting a motion plan created by a generation means. 【0740】 "Analysis means" refers to a device or method that analyzes user activity information detected by an imaging device and compares it with proposed activities. 【0741】 "Instructional means" refers to a device or method for correcting inappropriate activities based on comparative results obtained through analytical means. 【0742】 "Management means" refers to a device or method for providing health guidance to residents within a residential facility and for visualizing healthy information about the collective. 【0743】 "Voice dialogue means" refers to a device or method for conducting natural dialogue in order to improve residents' motivation. 【0744】 The system for implementing this invention mainly consists of a server, terminals in each household, an imaging device, and a display device. First, the user uses the terminal to input their goals, health level, and history information, and transmits the data to the server via an acquisition means. Based on the acquired data, the server uses a generation AI model to create a personalized exercise plan. The generated exercise plan is sent to the display device via the terminal to provide visual guidance. 【0745】 During the user's exercise, the imaging device captures the user's movements in real time and transmits the data to a server for analysis. The server uses analysis tools to evaluate the user's activity and provides the user with guidance on areas that need correction. This allows the user to exercise safely and effectively. 【0746】 Furthermore, the management system aggregates and visualizes health data from all residents within the residential facility, enabling the sharing of health information among residents. The voice interaction system is used to improve motivation through interaction with the user. For example, if a user says they want to stop exercising, it generates and responds with a prompt such as, "Let's take a short break. You can maintain your health by continuing afterward." 【0747】 A concrete example of this system is a scenario where residents receive individual yoga or strength training instruction in a shared fitness room. Residents can receive health advice from their respective terminals and motivate each other. An example of a prompt message for the generated AI model is the question the server might receive: "Please tell me how residents can maintain their motivation to continue fitness at home." 【0748】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0749】 Step 1: 【0750】 The user uses a terminal to input goals, health levels, and historical information. The terminal sends this input data to the server. The input here includes the user's fitness goals and past injury information, and the output is the user data sent to the server. 【0751】 Step 2: 【0752】 The server uses a generative AI model to generate a personalized exercise plan based on the received user data. This process creates an exercise menu tailored to the user's goals and fitness level. The input is user data, and the output is the personalized exercise plan. 【0753】 Step 3: 【0754】 The generated exercise plan is transmitted to the display device via the terminal. The terminal visually presents the plan and manipulates a hologram to provide fitness guidance to the user. The input is the generated exercise plan, and the output is the displayed hologram menu. 【0755】 Step 4: 【0756】 When a user performs an exercise, the imaging device captures the user's movements in real time and transmits the data to the server. The input is the user's movement video, and the output is the activity data sent to the server. 【0757】 Step 5: 【0758】 The server evaluates the received video data using analysis tools to determine whether the user's actions are appropriate. Based on the analysis results, it generates improvement suggestions as needed. The input is activity data, and the output is action evaluation and improvement suggestions. 【0759】 Step 6: 【0760】 Improvement suggestions are sent to the terminal, and the user is instructed accordingly. The terminal provides feedback to the user and instructs them to continue using the correct form and actions. The input is improvement suggestions, and the output is feedback to the user. 【0761】 Step 7: 【0762】 Using voice interaction, the device engages in natural conversation with the user, facilitating discussions designed to increase motivation for exercise. For example, prompts such as, "Let's take a short break. Continuing afterward will help maintain your health," are generated. Input is the user's utterances, and output is conversational support. 【0763】 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. 【0764】 This invention is a system that provides a personalized training experience tailored to the user's emotional state by incorporating an emotion engine into an AI-driven fitness assistant that enables users to effectively perform fitness training at home. Based on fitness goals, fitness levels, and past injury information entered by the user, the system uses AI to generate an individualized training menu. 【0765】 The system begins with the user launching a dedicated app on their device and entering the necessary information. The device then sends this information to a server. The server uses a generation algorithm to create a training menu tailored to the user's needs. This created menu is then visually displayed to the user via a hologram projector. For example, squats and yoga poses are displayed in 3D in front of the user. 【0766】 Furthermore, this system uses the terminal's camera to capture the user's movements during training in real time. This video data is analyzed on a server to evaluate whether the user is performing the exercises with proper form. If inappropriate movements are detected, the server sends instructions to the user to improve their form. 【0767】 A key feature of this invention is the incorporation of an emotion engine that recognizes the user's emotional state based on their actions and voice data. This emotion engine analyzes the user's facial expressions and tone of voice to evaluate their stress level, fatigue, and motivation. As a result, the server dynamically adjusts the intensity and type of exercise to provide the user with the most suitable training content. 【0768】 For example, if a user expresses fatigue, the device can provide feedback to lower the difficulty of the exercise or recommend relaxing exercises. The device also uses natural voice interaction to provide appropriate messages to boost user motivation. For instance, if it detects that the user's expression is discouraged, it might offer encouraging words such as, "Keep going like this and you'll see results!" 【0769】 In this way, the AI-driven hologram fitness assistant system can adapt to the user's emotions and physical condition, providing a fitness experience tailored to individual needs and supporting safe and sustainable training. 【0770】 The following describes the processing flow. 【0771】 Step 1: 【0772】 Users launch a dedicated app on their device and enter their fitness goals, fitness level, and past injury history. This information is then transmitted to the server via the device. 【0773】 Step 2: 【0774】 The server uses a generation algorithm to create a training menu tailored to the individual user's needs, based on the information obtained from the user. The exercises best suited to the user's current condition are selected. 【0775】 Step 3: 【0776】 The terminal receives the training menu from the server and sends it to a hologram projector, displaying it visually in front of the user. This allows the user to confirm the specific actions. 【0777】 Step 4: 【0778】 When a user begins training, the camera on the device captures the user's movements in real time and sends the video data to the server. 【0779】 Step 5: 【0780】 The server analyzes the video data and uses an AI algorithm to evaluate whether the user's actions are in the correct form. If there are any inappropriate actions, they are detected. 【0781】 Step 6: 【0782】 If inappropriate behavior is detected, the server identifies the behavior that needs correction, generates feedback to provide guidance on correct form, and notifies the user via the terminal. 【0783】 Step 7: 【0784】 The emotion engine analyzes the user's actions and voice data, recognizing the user's emotional state based on facial expressions and tone. This analysis identifies states such as fatigue or stress. 【0785】 Step 8: 【0786】 The server automatically adjusts the training content based on the analysis results of the emotion engine. For example, if the user is fatigued, it will either reduce the intensity of the exercise or recommend recovery exercises. 【0787】 Step 9: 【0788】 The device utilizes voice interaction capabilities to provide feedback to the user and support their motivation. For example, if it detects that the user's motivation is low, it will send an encouraging message. 【0789】 This process allows users to receive training tailored to their emotions and physical condition, enabling them to engage in fitness safely and sustainably. 【0790】 (Example 2) 【0791】 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". 【0792】 Traditional home fitness training has faced challenges such as users not receiving sufficient support regarding individualized exercise plans and motivation, leading to a lack of consistency and an increased risk of injury due to incorrect form. In addition, the lack of flexible support tailored to the user's emotional state limited training satisfaction and effectiveness. 【0793】 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. 【0794】 In this invention, the server includes an acquisition means for inputting exercise goals, physical fitness status, and past health information from the user; a generation means for generating an individualized exercise plan using a generative AI model; and an emotion analysis and adjustment means for evaluating the user's emotional state and dynamically adjusting the exercise content based on that evaluation. This enables users to receive individually optimized training at home, resulting in a safer, more effective, and sustainable fitness experience. 【0795】 "Means of acquisition" refers to the functions and mechanisms necessary for users to input their exercise goals, physical fitness status, and past health information. 【0796】 "Generation means" refers to a function or mechanism that generates an individualized motor plan using a generation AI model based on information obtained through acquisition means. 【0797】 "Presentation means" refers to functions or mechanisms for visually presenting the generated motion plan using a stereoscopic display device. 【0798】 "Analysis means" refers to functions or mechanisms for analyzing user motion data detected using imaging equipment and comparing it with proposed actions. 【0799】 "Instructional tools" refer to functions and mechanisms that provide guidance and advice to correct inaccurate movements based on the results of motion comparisons performed by analytical tools. 【0800】 An "emotional analysis and adjustment mechanism" is a function or system that evaluates the user's emotional state and dynamically adjusts the exercise content based on the evaluation results. 【0801】 A "progress management system" refers to a function or mechanism for recording the progress of exercise and providing users with information on its results and evaluations. 【0802】 "Voice dialogue means" refers to functions and mechanisms that use natural language processing to engage in voice dialogue with users and promote motivation. 【0803】 This invention is a system for users to effectively perform fitness training at home, utilizing AI technology to provide training tailored to the user's individual needs. The main components of this system include a server, a terminal, and user input. 【0804】 Users input their exercise goals, fitness level, and past health information using a dedicated app on their device. This information is transmitted to a server in real time. The server utilizes a generative AI model to generate a personalized exercise plan based on the received data. This generated exercise plan is then visually presented to the user via a 3D display on the device, specifically a hologram projector. For example, exercises such as squats and yoga are displayed as 3D models, providing visually clear instruction. 【0805】 Furthermore, the device captures the user's movements in real time during training through its built-in camera. This video data is analyzed on a server to evaluate whether the user is performing the exercises with proper form. For example, if the form is incorrect, corrective instructions such as "lower your hips a little more" are immediately provided. The server also analyzes the user's emotional state based on their facial expressions and tone of voice, and dynamically adjusts the exercise content accordingly. If fatigue is detected, the training intensity is reduced or relaxation exercises are suggested, enabling training that takes into account the user's health condition and motivation. 【0806】 Devices equipped with voice interaction capabilities can provide users with encouraging messages via voice to boost their motivation. For example, if a device detects that a user is feeling discouraged, it might send a message such as, "Keep going! You'll see results soon!" 【0807】 This system provides an optimal training environment based on the user's individual health data and emotional state, supporting a safe and effective fitness experience. 【0808】 Example of a prompt: 【0809】 "Analyze the user's emotional state and propose effective messages to boost their motivation." 【0810】 "Please generate an algorithm to calculate the optimal exercise intensity based on this user's activity data." 【0811】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0812】 Step 1: 【0813】 The user launches a dedicated app on their device and enters their exercise goals, fitness level, and past health information. The entered data, along with the user ID, is sent from the device to the server. The input in this step is fitness-related information provided by the user, and the output is the transmission of information to the server. 【0814】 Step 2: 【0815】 The server uses a generative AI model to generate a personalized exercise plan based on the received data. This process compares the data with various exercise data stored in a database to determine the optimal training program for the user. The input is the user's fitness information, and the output is the personalized exercise plan. 【0816】 Step 3: 【0817】 The server sends the generated exercise plan to the terminal, which then visually presents it to the user using a 3D display device. Specifically, a hologram projector displays the selected exercise in 3D. The input is the generated exercise plan, and the output is the visual presentation to the user. 【0818】 Step 4: 【0819】 When a user begins training, the device's camera captures the user's movements in real time. This video data is sent to a server for motion analysis. The input is video of the user's training movements, and the output is data for analysis. 【0820】 Step 5: 【0821】 The server uses analysis tools to evaluate the user's movements and verify whether the exercises are being performed with correct form. This evaluation is based on machine learning algorithms, and the data is processed to provide guidance on proper form. The input is video data, and the output is the results of the movement evaluation. 【0822】 Step 6: 【0823】 Based on the evaluation results, the server sends corrective instructions to the terminal as needed. If incorrect operation is detected, the terminal provides feedback to the user, such as "lower your stance a little." The input is the operation evaluation result, and the output is the corrective instructions to the user. 【0824】 Step 7: 【0825】 The device captures the user's facial expressions and voice and sends this data to the server. The server performs emotion analysis and dynamically adjusts the movement. The input is the user's facial expressions and voice data, and the output is the emotion evaluation result. 【0826】 Step 8: 【0827】 The server dynamically adjusts the exercise plan based on the emotional assessment results. If the server determines that the user is fatigued, it will reduce the exercise intensity or suggest relaxing exercises. The input is the emotional assessment results, and the output is the adjusted exercise plan. 【0828】 Step 9: 【0829】 The device uses natural language processing to provide the user with motivational voice messages. For example, if the user's motivation is low, a message such as "Keep going! You'll see results soon!" is sent. The input is a tailored exercise plan and emotional assessment, and the output is a voice message. 【0830】 (Application Example 2) 【0831】 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". 【0832】 The problem that this invention aims to solve is to provide personalized fitness training to individual users and to realize a training experience that takes into account the user's emotional state. In particular, it is necessary to dynamically adjust the training according to the user's motivation and physical condition, and to support the user's safety and sustainable improvement of fitness. Conventional systems have lacked an approach that reflects the individual emotional state of users, so there is a need to respond to user needs more effectively. 【0833】 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. 【0834】 In this invention, the server includes data receiving means for inputting fitness goals, fitness levels, and past injury information from the user; information generating means for creating an individualized training menu using a generation algorithm based on the information acquired by the data receiving means; and output means for visually communicating the training menu created by the information generating means using a three-dimensional display device. This enables the user to receive appropriate training tailored to their individual needs during fitness training at home. 【0835】 A "user" is an individual who uses a fitness training system to receive personalized training. 【0836】 "Data receiving means" refers to a device or method for inputting and collecting information from users, such as fitness goals, fitness levels, and past injury information. 【0837】 A "generative algorithm" is a process or procedure that creates personalized training menus based on the user information entered. 【0838】 "Information generation means" refers to a device or method for creating a training menu tailored to a user using a generation algorithm. 【0839】 A "three-dimensional display device" is a device that visually displays training menus and movements in three dimensions for the user. 【0840】 "Output means" refers to a device or method that visually communicates the created training menu to the user. 【0841】 A "video device" is a device that captures the user's training movements and processes them as video data. 【0842】 "Information analysis means" refers to a device or method for analyzing data captured by a video device and evaluating the user's actions. 【0843】 "Action guidance means" refers to a device or method that identifies an inappropriate user action and provides instructions to correct it. 【0844】 "Emotion recognition means" refers to a device or method for analyzing a user's facial expressions and voice and evaluating their emotional state. 【0845】 "Motor adjustment means" refers to a device or method for dynamically adjusting training content based on evaluation results from emotion recognition means. 【0846】 The system for carrying out this invention is an AI-driven fitness assistant system that provides personalized fitness training to the user. The system has the ability to take into account the user's emotional state and dynamically adjust the training plan. 【0847】 First, the user uses the device to input their fitness goals, fitness level, and past injury information. This information is sent to the server via a data receiving device. Based on the received information, the server runs a generative AI model to generate a personalized training menu. This generation process uses a generation algorithm that suggests the most suitable training for the user's health condition and goals. 【0848】 Next, the server presents the generated training menu to the user via a three-dimensional display device. The user performs the training according to the displayed image. The user's movements are captured by the video device and transmitted to the server. The server uses information analysis means to analyze the captured user movements and evaluate the accuracy of the training. If inappropriate movements are detected, the server uses movement guidance means to send instructions to the user to perform the correct movements. 【0849】 Furthermore, the system uses emotion recognition to analyze the user's facial expressions and voice to evaluate their emotional state. Based on the evaluation results, the exercise adjustment mechanism dynamically changes the training content, enabling the user to continue with optimal training tailored to their tone of voice and mood. For example, if the system determines that the user is tired, it will either reduce the intensity of the exercise or suggest exercises that promote relaxation. 【0850】 For example, if the emotion recognition system determines that the user is feeling down, the server will output a message such as, "If you keep going like this, you'll see results!" 【0851】 An example of a prompt message would be: "Based on the user's health and emotional state, provide an appropriate fitness plan and adjust the exercise in real time." 【0852】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0853】 Step 1: 【0854】 The user uses a device to input their fitness goals, fitness level, and past injury information, and sends this data to the server. The data receiving device records this user input and converts it into a format usable by the server. The server, upon receiving the input information, performs preprocessing to run the generative AI model. 【0855】 Step 2: 【0856】 The server uses a generative AI model based on the entered user information to create a personalized training menu. Specifically, the server applies a generative algorithm to select exercises that match the user's goals and fitness level. This process also takes into account limitations based on past injuries and health conditions. The resulting training menu is customized for each individual user. 【0857】 Step 3: 【0858】 The server visually presents the generated training menu to the user via a three-dimensional display device. The input here is the customized training menu, and the output is a visual training guide. The server converts this data into an appropriate format so that the display device can reproduce the image in three dimensions. 【0859】 Step 4: 【0860】 A video device installed on the terminal captures the user's movements in real time during training. This video data is sent to a server for analysis. The input is video of the user's training movements, and the server uses this video to perform motion analysis. 【0861】 Step 5: 【0862】 The server uses information analysis tools to analyze the user's movements and evaluate the accuracy of the training. In this step, the server analyzes the user's posture and movement form based on the input video data. If inappropriate movements are identified as a result, the movement instruction tool generates corrective instructions and sends them to the user. 【0863】 Step 6: 【0864】 The server analyzes the user's facial expressions and voice data to evaluate their emotional state. This evaluation is performed using emotion recognition technology. The input consists of the user's facial image and voice data, which are analyzed to infer the user's psychological state. The output is evaluation information regarding the user's emotional state. 【0865】 Step 7: 【0866】 The server dynamically adjusts the training content using exercise adjustment mechanisms based on the results of emotion recognition evaluations. The input here is emotion evaluation information, and the output is the adjusted training menu. For example, if the user indicates fatigue, the server reduces the intensity of the exercise and recommends more relaxing exercises. This adjustment allows the user to continue having an optimal fitness experience. 【0867】 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. 【0868】 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. 【0869】 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. 【0870】 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. 【0871】 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. 【0872】 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. 【0873】 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. 【0874】 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. 【0875】 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." 【0876】 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. 【0877】 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. 【0878】 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. 【0879】 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. 【0880】 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. 【0881】 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. 【0882】 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. 【0883】 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. 【0884】 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. 【0885】 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. 【0886】 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. 【0887】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0888】 The following is further disclosed regarding the embodiments described above. 【0889】 (Claim 1) 【0890】 A receiving mechanism for inputting fitness goals, fitness levels, and past injury information from users, 【0891】 A generation means that creates an individualized training menu using a generation algorithm based on the information acquired by the receiving means, 【0892】 A display means that visually displays the training menu created by the generation means using a hologram projector, 【0893】 An analysis means that detects the user's movements during training presented by the display means using a camera and analyzes the data, 【0894】 The analysis means compares the user's actions detected with the proposed actions and provides guidance to correct inappropriate actions. 【0895】 A system that includes this. 【0896】 (Claim 2) 【0897】 The system according to claim 1, further comprising progress management means for recording the progress of the training and providing feedback to the user. 【0898】 (Claim 3) 【0899】 The system according to claim 1, further comprising voice dialogue means for engaging in natural conversation in order to improve the user's motivation. 【0900】 "Example 1" 【0901】 (Claim 1) 【0902】 A device that acquires information from users regarding their physical ability goals, health status, and medical history. 【0903】 A device that generates personalized exercise guidance using artificial intelligence technology based on data acquired by the aforementioned device, 【0904】 A device that visually provides exercise instructions created by the aforementioned generation device using three-dimensional display technology, 【0905】 An analysis device that detects the user's movements in the exercise presented by the aforementioned providing device using an optical device and processes the information thereof, 【0906】 A guidance device that compares the user's actions confirmed by the aforementioned analysis device with the provided actions and corrects inappropriate actions, 【0907】 A system that includes this. 【0908】 (Claim 2) 【0909】 The system according to claim 1, further comprising a management device that manages the progress of the exercise instruction and provides feedback to the user. 【0910】 (Claim 3) 【0911】 The system according to claim 1, further comprising a voice communication device for conducting natural language dialogue in order to improve the user's motivation to engage in activities. 【0912】 "Application Example 1" 【0913】 (Claim 1) 【0914】 A means of acquiring user goals, health levels, and historical information, 【0915】 A generation means that creates an individualized movement plan using a generation method based on the information acquired by the acquisition means, 【0916】 A display means that visually displays the motion plan created by the generation means using a display device, 【0917】 An analysis means for detecting the user's activity in the movement presented by the display means using an imaging device and analyzing the information thereof, 【0918】 The analysis means compares the user's activities with the suggested activities and provides guidance to correct inappropriate activities. 【0919】 A management system for providing health guidance to residents within residential facilities and for visualizing healthy information about the collective, 【0920】 A system that includes this. 【0921】 (Claim 2) 【0922】 The system according to claim 1, further comprising management means for recording the progress of the exercise and providing a response to the user. 【0923】 (Claim 3) 【0924】 The system according to claim 1, further comprising voice dialogue means for conducting natural dialogue in order to improve the motivation of the residents. 【0925】 "Example 2 of combining an emotion engine" 【0926】 (Claim 1) 【0927】 A means of acquiring user information, including exercise goals, physical fitness status, and past health information. 【0928】 Based on the information obtained by the acquisition means, a generation means generates an individualized motor plan using a generated AI model, 【0929】 A presentation means for visually presenting the motion plan generated by the generation means using a stereoscopic display device, 【0930】 An analysis means for detecting the user's movements in the exercises presented by the aforementioned presentation means using a camera and analyzing the data, 【0931】 The analysis means compares the user's actions detected with the proposed actions and provides guidance to correct inaccurate actions. 【0932】 An emotion analysis and adjustment means that evaluates the user's emotional state and dynamically adjusts the movement content based on that evaluation, 【0933】 A system that includes this. 【0934】 (Claim 2) 【0935】 The system according to claim 1, further comprising progress management means for recording the progress of the exercise and providing evaluation to the user. 【0936】 (Claim 3) 【0937】 The system according to claim 1, further comprising a voice dialogue means utilizing natural language processing to promote the motivation of the user. 【0938】 "Application example 2 when combining with an emotional engine" 【0939】 (Claim 1) 【0940】 A data receiving method for inputting user fitness goals, fitness levels, and past injury information, 【0941】 Information generation means that creates an individualized training menu using a generation algorithm based on the information acquired by the data receiving means, 【0942】 Output means for visually conveying the training menu created by the information generation means using a three-dimensional display device, 【0943】 Information analysis means that captures the user's movements during training presented by the output means using a video device and analyzes that information, 【0944】 The information analysis means compares the user's actions captured with the proposed actions and provides instructions to correct inappropriate actions; 【0945】 An emotion recognition method that analyzes the user's expressions and voice information to evaluate their emotional state, 【0946】 A movement adjustment means that dynamically adjusts the training content based on the emotion recognition means, 【0947】 A system that includes this. 【0948】 (Claim 2) 【0949】 The system according to claim 1, further comprising progress management means for recording the progress of the training and providing feedback to the user. 【0950】 (Claim 3) 【0951】 The system according to claim 1, further comprising voice dialogue means for engaging in natural conversation in order to improve the user's motivation. [Explanation of Symbols] 【0952】 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

[Claim 1] A receiving mechanism for inputting fitness goals, fitness levels, and past injury information from users, A generation means that creates an individualized training menu using a generation algorithm based on the information acquired by the receiving means, A display means that visually displays the training menu created by the generation means using a hologram projector, An analysis means that detects the user's movements during training presented by the display means using a camera and analyzes the data, The analysis means compares the user's actions detected with the proposed actions and provides guidance to correct inappropriate actions. A system that includes this. [Claim 2] The system according to claim 1, further comprising progress management means for recording the progress of the training and providing feedback to the user. [Claim 3] The system according to claim 1, further comprising voice dialogue means for engaging in natural conversation in order to improve the user's motivation.

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