system

Abstract

We provide the system. [Solution] A means of receiving the user's physical information, A means for generating an individualized exercise training program based on received physical information, A means of presenting the generated exercise training program to the user, A means of recording the user's progress and visualizing and presenting their ideal future body shape, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, due to the increasing health awareness, more people are interested in exercise and training, but there are situations where there is a lack of methods and information for carrying them out and it is difficult to access a gym. As a result, many people cannot start training, and there is a problem that they cannot obtain the expected effects from self-designed training. Furthermore, there is also a problem that it is difficult to maintain motivation and it is hard to make a continuous training plan.

Means for Solving the Problems

[0005] This invention provides a system that supports efficient and effective training by collecting users' physical information and generating individualized exercise training programs based on that information. Specifically, it utilizes artificial intelligence based on received physical information and processes various data simultaneously to generate an exercise training program optimized for each user. It also supports maintaining and improving motivation by continuously recording the user's progress and visualizing and presenting their ideal future physique. Furthermore, it supports continuous exercise by using push notifications to encourage the user to perform their training.

[0006] A "user" is an individual or group that uses the system and inputs physical information to receive an exercise training program.

[0007] "Physical information" refers to data about the user's personal characteristics necessary for generating an exercise training program, such as height, weight, age, gender, exercise experience, and health status.

[0008] An "exercise training program" is a plan that includes a series of exercises and training activities generated based on the user's physical information, and serves as a guideline for efficiently achieving exercise benefits.

[0009] "Generation" refers to the process of combining data and information according to a specific purpose to construct new exercise training programs or visualization data.

[0010] "Artificial intelligence" is a technology in which computer systems mimic human intelligent activity, particularly by simultaneously processing diverse data to generate meaningful information and programs.

[0011] "Diverse data" refers to a collection of information that has multiple different types and formats, including physical information and training-related data.

[0012] "Visualization" is the process of converting information and data into a visible form to make them easier to understand.

[0013] A "push notification" is an immediate alert or message sent by a system or application to a user, and is a means of communication used to encourage participation in training. [Brief explanation of the drawing]

[0014] [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 flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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.

[0018] 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.

[0019] 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, and the like.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] An embodiment of the present invention is a system that allows users to easily perform individually optimized exercise training programs at home. The user first inputs their physical information via a terminal. This information includes height, weight, age, gender, and exercise experience. The input information is then transmitted from the terminal to a server.

[0036] The server processes the received physical information and uses artificial intelligence to generate an optimal exercise training program for each user. This allows users to obtain an exercise plan tailored to their health condition and goals. For example, a complete beginner might be presented with a program that includes light stretching exercises three times a week, while a user with some exercise experience might be offered a more intense training program.

[0037] The device visually displays the generated exercise training program to the user and reminds them to remember the schedule and timing through push notifications. For example, if training is scheduled for 7:00 AM, the notification will be sent a little before that time.

[0038] Furthermore, user progress is recorded on the device and periodically synchronized with the server. This allows the server to use the progress data to track changes in the user's physique and visualize and display their ideal future physique on the device. This visualization serves as motivation for users to continue their training.

[0039] As a concrete example, consider a user who has started managing their body fat percentage for health maintenance. The user sets a target body fat percentage of 15%, and the system suggests an exercise program that matches this goal. The server generates a program incorporating ABS and HIIT (High-Intensity Interval Training) and presents it through the terminal. The user trains according to the program and enters the results into the app, allowing them to see their progress at a glance.

[0040] This invention, by incorporating the functions described above, enables the provision of various services that help users achieve their health goals. It is a system that can achieve high effectiveness through data processing utilizing artificial intelligence and user feedback.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user enters their physical information using a terminal. This information includes height, weight, age, gender, and exercise experience. Once the input is complete, the terminal verifies the information and prepares to send it to the server.

[0044] Step 2:

[0045] The terminal sends the entered physical information to the server. After transmission, the server receives the data, verifies its integrity, and stores it in its database.

[0046] Step 3:

[0047] The server uses artificial intelligence to generate an optimal exercise training program based on the received physical information. This program is adjusted according to the user's health condition and goals. The generated program is temporarily stored on the server.

[0048] Step 4:

[0049] The server sends the generated training program to the terminal. The terminal visually presents the received program to the user, taking care to ensure that the user can easily understand it.

[0050] Step 5:

[0051] The device uses push notifications to inform the user of the training schedule. The notifications are sent at appropriate times based on the schedule to ensure the user doesn't forget.

[0052] Step 6:

[0053] Once the user completes the training, they input progress data using a device. The device records this information, updates it, and then sends it to the server.

[0054] Step 7:

[0055] The server receives progress data and analyzes the user's exercise history. Based on the analysis, it generates an ideal body shape image for the user and uses it to adjust the next exercise program.

[0056] Step 8:

[0057] The server sends the generated ideal body shape image to the device. The device displays this image to the user, helping to boost their motivation.

[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] In the process of providing users with individually optimized exercise programs, challenges include the inability to continuously monitor their progress and insufficient means to encourage continued exercise. Furthermore, there is a need to improve the reliability of whether the generated programs accurately reflect the diverse physical information of the users.

[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 means for acquiring information about the user's body, means for generating an individualized exercise training plan using artificial intelligence based on the acquired information about the body, and means for visually displaying the generated exercise training plan to the user. This makes it possible to provide a training program that meets the user's individual exercise needs, as well as to monitor its progress in real time and promote the execution of exercise at the appropriate time.

[0063] "Information about the user's physical characteristics" refers to data that shows an individual's physical characteristics, such as the user's height, weight, age, gender, exercise experience, and health goals.

[0064] "Artificial intelligence" refers to a technology that mimics human intellectual activity using computer systems, and is particularly used for automating data analysis and decision-making processes.

[0065] An "individualized exercise training plan" is a training program optimized based on the user's physical characteristics and goals, and includes exercise suggestions tailored to the individual.

[0066] "Visually displaying" refers to presenting information in a way that users can see, generally involving the use of screens or displays to show content.

[0067] "Activity progress" refers to data on the exercises and training performed by users and the status of their implementation, indicating the degree of achievement towards the set goals.

[0068] "Ideal future physical condition" refers to the optimal physical state that can be expected based on the health and exercise goals set by the user, and is used to motivate the user through visualization.

[0069] This invention is a system for providing personalized exercise training programs, enabling users to easily manage their health at home. The following describes embodiments for carrying out this invention.

[0070] The system consists of a terminal and a server. Users input their physical information using the terminal. This terminal is generally assumed to be a smartphone or tablet computer, and information can be entered via a user interface. The information entered includes height, weight, age, gender, exercise experience, and health goals.

[0071] The terminal transmits the entered physical information to the server. The server, equipped with a high-performance processor and artificial intelligence frameworks such as TENSORFLOW® and PyTorch, uses the received information to generate an optimal exercise training program for each user. This program utilizes advanced information processing technology to identify and propose the most suitable training content and pace for each individual user.

[0072] The generated exercise training program is sent to the terminal in an appropriate format such as JSON and displayed visually. The user then performs the exercise according to the displayed program. For example, a program including light stretching exercises to improve flexibility is suggested for complete beginners, while a program including HIIT (High-Intensity Interval Training) is provided for users with some exercise experience.

[0073] Furthermore, the device encourages users to exercise through push notifications. It can also record the user's training progress and periodically synchronize that data with a server. This allows the server to track the user's progress and visualize and display their ideal future physique.

[0074] An example of a prompt would be: "A 30-year-old female, 160cm tall, weighing 55kg, with exercise experience including yoga once a week. Please suggest an exercise program aimed at weight loss."

[0075] In this way, the present invention supports exercise habits in daily life by providing users with personalized health management methods.

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The terminal displays a screen for the user to enter their physical information. The user enters information such as height, weight, age, gender, exercise experience, and health goals. The terminal formats this information and temporarily stores it for future use. The input data is the user's physical information, and the output is formatted data that can be sent to the server.

[0079] Step 2:

[0080] The terminal transmits the entered biometric information to the server. During this process, the data is encrypted and transmitted using a secure protocol. The input data is formatted biometric information, and the output is a notification to the user confirming the transmission status.

[0081] Step 3:

[0082] The server processes the received physical information. Specifically, it uses artificial intelligence to generate an optimal exercise training program for each user. Data processing includes analysis of numerical data such as height and weight, and pattern recognition based on exercise experience. The input is physical information transmitted from the terminal, and the output is an optimized exercise training program.

[0083] Step 4:

[0084] The server sends the generated exercise training program to the terminal. The terminal receives this information and prepares an interface to display it visually to the user. The input is the program data generated by the server, and the output includes a user interface that visualizes the program content.

[0085] Step 5:

[0086] The device sets up push notifications to encourage the user to exercise. Notifications are sent based on a schedule set by the user. The input data is the exercise schedule, and the output is the sending of notifications at the appropriate time.

[0087] Step 6:

[0088] The user records the progress of their exercise on their device. The device periodically synchronizes this data with the server and saves it as progress data. The input is the progress data recorded by the user, and the output is the progress history stored on the server.

[0089] (Application Example 1)

[0090] 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."

[0091] Modern consumers are seeking efficient and personalized ways to maintain their health and make exercise a habit amidst their busy daily lives. However, support from a personal trainer is time-consuming and costly, and self-managed exercise at home presents challenges in maintaining motivation and correct form. As a result, many people find it difficult to achieve sustained health improvement.

[0092] 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.

[0093] In this invention, the server includes means for receiving the user's physical information, means for generating an individualized exercise training program based on the received physical information, and means for providing the user with the correct form of exercise in real time using a visual display device. This makes it possible for the user to continue training with the correct form while receiving efficient and personalized exercise guidance, and to maintain motivation.

[0094] "Means for receiving user physical information" refers to a system for obtaining physical data from individual users. This data includes height, weight, age, gender, etc.

[0095] "Means for generating individual exercise training programs" refers to a system for creating an exercise plan optimized for the user based on received physical information.

[0096] "Means for presenting the generated exercise training program to the user" refers to a mechanism for visually showing the created exercise plan to the user.

[0097] "A means of recording the user's progress and visually presenting their ideal future physique" refers to a device that tracks the user's exercise results and visually represents their future physique based on their progress.

[0098] A "visual display device" is a device that displays visual information to the user in real time and conveys the correct form of movement.

[0099] This invention is a system for users to efficiently perform exercise training. First, the user inputs their physical information via a dedicated terminal, and this information is sent to a server. Based on this physical information, the server generates an individualized exercise training program using an AI algorithm. The software used includes machine learning libraries for data analysis and a user interface for visualization.

[0100] The generated exercise training program is visualized in real time through the user's smart glasses or head-mounted display. This visual display provides proper form and movement, improving the accuracy of the training. Visual recognition and sensor data are used for this movement monitoring.

[0101] Progress records are periodically synchronized from the device to the server, which analyzes the user's performance and predicts and displays their ideal future physique on the device. This allows users to quickly grasp their progress and maintain motivation towards achieving their goals.

[0102] For example, if a user sets a goal of losing 5 kilograms, the system will present a training program tailored to that goal. An example of a prompt might be, "Generate an exercise program to efficiently lose weight."

[0103] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0104] Step 1:

[0105] Users enter their physical information into the terminal. This information includes height, weight, age, gender, and exercise experience. Accuracy is required because this input data will later be used to generate individually optimized exercise training programs.

[0106] Step 2:

[0107] The terminal transmits the entered physical information to the server. The server receives this data and stores it in a database. The received data becomes crucial foundational information for the AI ​​algorithm to generate an optimal exercise training program for the user.

[0108] Step 3:

[0109] The server processes the received physical information using a generating AI model. The AI ​​model utilizes machine learning algorithms to generate exercise programs tailored to each user's characteristics. The input is physical information, and the output is an individualized exercise plan.

[0110] Step 4:

[0111] The generated exercise training program is sent from the server to the terminal. The terminal displays the program content on a visual display device and provides the user with the resulting exercise plan. The input here is the program data from the server, and the output is the information displayed on the terminal.

[0112] Step 5:

[0113] The user performs the training according to the exercise program presented using a visual display device. The display device ensures the accuracy of the training by providing the user with real-time information on the correct form of the exercise and the next steps.

[0114] Step 6:

[0115] After completing a workout, the device records exercise progress data. This data is synchronized with a server to analyze the effectiveness of the training and help adjust future programs. The progress data is the input, and the plan used to suggest the next workout is the output.

[0116] Step 7:

[0117] The server analyzes progress data and predicts the user's ideal future physique based on their growth and achievements. This information is visualized to the user in real time on their device, serving as motivation for continued exercise.

[0118] 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.

[0119] Embodiments of the present invention are systems that, in addition to individual exercise training programs, recognize the user's emotions and reflect them in the training plan. As an initial setup, the user inputs their physical information via a terminal. The input information is sent to a server so that the AI ​​can generate an optimal exercise training program based on the user's exercise goals and health condition.

[0120] The server processes the received physical information along with various other data and uses artificial intelligence to create a personalized exercise training program. The generated program is sent to the user's terminal and presented visually. At this stage, an emotion engine is also incorporated into the program to recognize the user's emotional state in real time.

[0121] Emotion recognition is performed through sensors in the device's camera and microphone, detecting emotions through facial expression analysis and voice tone analysis. For example, if a user shows signs of fatigue, the emotion engine recognizes this, and the server adjusts the training program based on that information. Specifically, it can reduce the intensity of the program or add more engaging variations.

[0122] The device presents the user with updated programs and provides training notifications to encourage participation. Furthermore, after the user completes the training and continuously inputs progress and emotional information, the device records this information and sends it to the server. The server analyzes this information to further refine new training plans to help the user achieve their long-term health goals.

[0123] As a concrete example, when a user engages in training, daily emotional data is collected, and if negative emotions persist, the emotional engine recommends relaxation exercises. Conversely, if the user is highly motivated, the server incorporates more challenging exercises. This provides a flexible and effective training environment tailored to each individual user. This invention enables dynamic exercise management based on emotions, efficiently supporting users in achieving their body shape goals.

[0124] The following describes the processing flow.

[0125] Step 1:

[0126] The user enters their physical information using a terminal. This information includes height, weight, age, gender, and exercise experience. The terminal verifies the entered information and prepares to send it to the server.

[0127] Step 2:

[0128] The terminal sends input data to the server. The server verifies the received data and stores it in the database in the appropriate format.

[0129] Step 3:

[0130] The server uses accumulated physical information and artificial intelligence to generate an optimal exercise training program for each user. The program is customized based on each user's health condition and goals.

[0131] Step 4:

[0132] The server sends the generated exercise training program to the terminal. The terminal presents the program content to the user and provides an interface to facilitate understanding.

[0133] Step 5:

[0134] The device recognizes the user's real-time emotional state through its emotion engine. This involves analyzing facial expressions and voice tone using the device's camera and microphone.

[0135] Step 6:

[0136] Emotional data recognized by the device is sent to the server. The server adjusts the exercise training program based on the emotional data. If excessive fatigue is detected, the server suggests a program with reduced intensity.

[0137] Step 7:

[0138] The device then presents the adjusted program to the user again. The device sends a push notification to the user to encourage them to complete the training and ensure they don't forget their appointments.

[0139] Step 8:

[0140] After the training is complete, the user reports their progress and emotional state using a device. The device records this information, sends it to a server, and stores it in a database.

[0141] Step 9:

[0142] The server analyzes accumulated progress and emotional data, performs long-term tuning, and incorporates the results into subsequent exercise training programs. Users receive a plan that reflects these results, which helps them maintain their motivation.

[0143] (Example 2)

[0144] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0145] In recent years, there has been growing interest in health management and maintaining one's physique, but systems that provide exercise plans tailored to individual physical characteristics and emotional states are limited. Furthermore, fixed exercise programs make it difficult to maintain user motivation and continue effective exercise. Therefore, there is a need for exercise programs that can adapt to diverse situations and be adjusted in real time.

[0146] 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.

[0147] In this invention, the server includes means for acquiring the user's physical characteristics information, means for generating an individualized exercise plan based on the acquired physical characteristics information, and means for analyzing the user's emotional state. This makes it possible to provide dynamic and flexible exercise programs tailored to individual needs.

[0148] "User physical characteristics information" refers to data that includes individual user characteristics such as height, weight, age, health status, and exercise goals.

[0149] An "exercise plan" is a plan that outlines the type, intensity, and frequency of exercise, generated based on the user's individual physical characteristics and emotional state.

[0150] "Emotional state" refers to emotion-related data detected from the user's facial expressions and voice, and includes fatigue, motivation, stress, etc.

[0151] "Dynamic adjustment" means flexibly changing the exercise plan according to the situation at the time, reflecting the user's real-time emotional state.

[0152] A "computer processing unit" refers to an electronic device or system used to process diverse information and generate motion plans.

[0153] "Communicating and promoting the continuation of exercise" refers to the act of sending regular notifications to users to encourage them to exercise and support their continued efforts.

[0154] This invention is a system that dynamically generates and adjusts an exercise plan based on the user's physical characteristics and emotional state. The necessary hardware for implementation is an information terminal such as a smartphone or tablet. The software is installed on the terminal as a dedicated application and handles data input, display, and data collection via sensors.

[0155] Users input physical characteristics information such as height, weight, age, health status, and exercise goals through a dedicated application. This information is sent from the terminal to a server. The server generates an individualized exercise plan using AI technology. Specific technologies include generative AI models using TensorFlow and PyTorch. These models have the ability to learn from past data and generate optimized exercise plans in real time.

[0156] Furthermore, the device monitors the user's emotional state using a camera and microphone. Technologies used include facial expression analysis and voice tone analysis via OpenCV. The server analyzes this emotional data and dynamically adjusts the exercise plan. An API known as the emotion engine is used for emotion recognition, appropriately changing the intensity and content of the exercises in response to user feedback.

[0157] For example, if a user plans to train several times a week, and their daily emotions are unstable, relaxation-focused exercises will be suggested. Conversely, when they are highly motivated, more challenging exercises will be incorporated. This dynamic adjustment ensures that users always receive an exercise plan that is optimal for their current state.

[0158] As an example of an input prompt for the generating AI model, one could ask the system a question in the form of, "I'm a 30-year-old male aiming to lose weight. I've been feeling unmotivated lately. What kind of exercise program would be suitable for me?" This system provides a customized exercise experience for each user, enabling support towards long-term health goals.

[0159] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0160] Step 1:

[0161] The user enters physical characteristics information such as height, weight, age, health status, and exercise goals into a dedicated application on the device. The entered data is formatted and securely transmitted to the server using encryption. In this step, the input is physical characteristics information, and the output is formatted data ready to be sent to the server.

[0162] Step 2:

[0163] The server analyzes the received physical characteristics information. First, it stores it in a database and uses it as basic data for processing by the AI ​​model. The generative AI model used here generates individual exercise plans by referring to past training data and similar user data. The input for this step is the user's physical characteristics information data, and the output is the generated exercise plan.

[0164] Step 3:

[0165] The device visually displays the exercise plan sent from the server using a dedicated app. The user reviews the displayed plan and prepares to execute it. The input for this step is the generated exercise plan, and the output is the exercise plan presented to the user.

[0166] Step 4:

[0167] The device begins measuring the user's emotional state using its built-in camera and microphone. The emotion engine measures emotions in real time through facial expression analysis and voice tone analysis, and sends this data to the server. The input for this step is the user's facial expressions and voice data, and the output is emotional state data.

[0168] Step 5:

[0169] The server analyzes the received emotional state data and dynamically adjusts the exercise plan. For example, if the server determines that the user is tired, it automatically reduces the intensity of the exercise and incorporates exercises that promote relaxation. The input for this step is emotional state data, and the output is the adjusted exercise plan.

[0170] Step 6:

[0171] The terminal receives the adjusted exercise plan from the server and presents it to the user again. The user reviews the updated plan and performs the exercise according to the instructions. The input for this step is the adjusted exercise plan, and the output is the new exercise plan presented to the user.

[0172] Step 7:

[0173] After the user completes their workout, the device collects training progress and new emotional data again and sends it to the server. The server stores this information and uses it to generate the next workout plan. The input for this step is the data after the workout has been completed, and the output is the completed data sent to the server.

[0174] (Application Example 2)

[0175] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0176] Even when individual exercise training programs are created based on a user's physical information, there is a problem in that they cannot dynamically respond to the user's emotional state, making it difficult to perform optimal exercise. Furthermore, there is a need to accurately reflect progress and emotional changes and provide flexible training that matches the user's goals.

[0177] 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.

[0178] In this invention, the server includes means for receiving the user's physical information and emotional data, means for generating an individualized exercise training program based on the received physical information and emotional data, and means for recording the user's progress and emotional changes, and visualizing an ideal health state based on goals. This enables the provision of an optimal exercise program tailored to the user's emotional state, allowing for efficient health management.

[0179] "Physical information" refers to information including the user's physical data, health status, and exercise history, and is the basis for the exercise training program.

[0180] "Emotional data" refers to data that shows the user's psychological state and emotional changes, and is used to adjust the exercise program.

[0181] An "exercise training program" is a program that provides an individualized exercise schedule and exercise content, generated based on the user's physical information and emotional data.

[0182] "Progress" refers to data showing the implementation status and results of users' exercise plans, and is used to improve future training plans.

[0183] "Artificial intelligence" refers to computational models and algorithms used to analyze diverse information and generate exercise training programs tailored to the user.

[0184] "Notification" refers to a means of communicating information to encourage users to implement an exercise program, including the timing and content of the notification.

[0185] In embodiments of this invention, a system is formed in which communication takes place between the user's terminal and a server, and an individualized exercise training program is provided. The terminal has the function of collecting the user's physical information and emotional data and transmitting it to the server. A smartphone or wearable device is used for this information collection, and data analysis is performed through a camera and microphone.

[0186] The server uses an AI model to generate personalized exercise training programs based on received physical and emotional data. This AI model is built using Python and Flask, and utilizes libraries such as TensorFlow and OpenCV to process diverse information. The generated program is sent to the user's device in real time and presented visually.

[0187] Furthermore, the server records the user's progress and emotional changes, accumulating and analyzing data to inform future training plans. Therefore, continuous data collection and analysis are crucial elements.

[0188] For example, if a user's emotional data detects "fatigue" when they are about to start exercising, the system will suggest a stretching program to promote relaxation. Conversely, if an emotion such as "energetic" is detected, the system can present a more challenging exercise.

[0189] An example of a prompt to input into the generating AI model is: "Based on emotional data and physical information, recommend the optimal training package for the user. The emotional state is reported as 'fatigued,' and the progress is reported as 'on track.'"

[0190] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0191] Step 1:

[0192] The device collects the user's physical and emotional data. The user's smartphone or wearable device uses a camera to collect facial data and a microphone to analyze voice tone. This allows the system to obtain physical and emotional data as input.

[0193] Step 2:

[0194] The device transmits collected physical and emotional data to the server. The data is encrypted during transmission to ensure security. The server receives this data and uses it in the next processing step.

[0195] Step 3:

[0196] The server uses an AI model to analyze the received information. The input here is the data received in step 2. The server uses TensorFlow to process the data with an AI model and generates an optimal exercise training program for the user's physical condition and emotions.

[0197] Step 4:

[0198] The server sends the generated exercise training program to the terminal. The output includes an individualized exercise program and recommendations for exercises tailored to the user. The terminal receives this, presents it visually to the user, and guides them through the next exercise step.

[0199] Step 5:

[0200] When a user performs an exercise, the device records their progress and emotional changes again. This information serves as input data for optimizing future exercise programs. The recorded data is sent back to the server in the next step.

[0201] Step 6:

[0202] The server analyzes progress and emotional data submitted by users and makes further adjustments to provide new training plans. This results in the output of a refined program designed to support users in achieving their long-term exercise goals.

[0203] 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.

[0204] 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.

[0205] 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.

[0206] [Second Embodiment]

[0207] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0208] 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.

[0209] 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).

[0210] 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.

[0211] 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.

[0212] 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).

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] 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".

[0219] An embodiment of the present invention is a system that allows users to easily perform individually optimized exercise training programs at home. The user first inputs their physical information via a terminal. This information includes height, weight, age, gender, and exercise experience. The input information is then transmitted from the terminal to a server.

[0220] The server processes the received physical information and uses artificial intelligence to generate an optimal exercise training program for each user. This allows users to obtain an exercise plan tailored to their health condition and goals. For example, a complete beginner might be presented with a program that includes light stretching exercises three times a week, while a user with some exercise experience might be offered a more intense training program.

[0221] The device visually displays the generated exercise training program to the user and reminds them to remember the schedule and timing through push notifications. For example, if training is scheduled for 7:00 AM, the notification will be sent a little before that time.

[0222] Furthermore, user progress is recorded on the device and periodically synchronized with the server. This allows the server to use the progress data to track changes in the user's physique and visualize and display their ideal future physique on the device. This visualization serves as motivation for users to continue their training.

[0223] As a concrete example, consider a user who has started managing their body fat percentage for health maintenance. The user sets a target body fat percentage of 15%, and the system suggests an exercise program that matches this goal. The server generates a program incorporating ABS and HIIT (High-Intensity Interval Training) and presents it through the terminal. The user trains according to the program and enters the results into the app, allowing them to see their progress at a glance.

[0224] This invention, by incorporating the functions described above, enables the provision of various services that help users achieve their health goals. It is a system that can achieve high effectiveness through data processing utilizing artificial intelligence and user feedback.

[0225] The following describes the processing flow.

[0226] Step 1:

[0227] The user enters their physical information using a terminal. This information includes height, weight, age, gender, and exercise experience. Once the input is complete, the terminal verifies the information and prepares to send it to the server.

[0228] Step 2:

[0229] The terminal sends the entered physical information to the server. After transmission, the server receives the data, verifies its integrity, and stores it in its database.

[0230] Step 3:

[0231] The server uses artificial intelligence to generate an optimal exercise training program based on the received physical information. This program is adjusted according to the user's health condition and goals. The generated program is temporarily stored on the server.

[0232] Step 4:

[0233] The server sends the generated training program to the terminal. The terminal visually presents the received program to the user, taking care to ensure that the user can easily understand it.

[0234] Step 5:

[0235] The device uses push notifications to inform the user of the training schedule. The notifications are sent at appropriate times based on the schedule to ensure the user doesn't forget.

[0236] Step 6:

[0237] Once the user completes the training, they input progress data using a device. The device records this information, updates it, and then sends it to the server.

[0238] Step 7:

[0239] The server receives progress data and analyzes the user's exercise history. Based on the analysis, it generates an ideal body shape image for the user and uses it to adjust the next exercise program.

[0240] Step 8:

[0241] The server sends the generated ideal body shape image to the device. The device displays this image to the user, helping to boost their motivation.

[0242] (Example 1)

[0243] 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."

[0244] In the process of providing users with individually optimized exercise programs, challenges include the inability to continuously monitor their progress and insufficient means to encourage continued exercise. Furthermore, there is a need to improve the reliability of whether the generated programs accurately reflect the diverse physical information of the users.

[0245] 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.

[0246] In this invention, the server includes means for acquiring information about the user's body, means for generating an individualized exercise training plan using artificial intelligence based on the acquired information about the body, and means for visually displaying the generated exercise training plan to the user. This makes it possible to provide a training program that meets the user's individual exercise needs, as well as to monitor its progress in real time and promote the execution of exercise at the appropriate time.

[0247] "Information about the user's physical characteristics" refers to data that shows an individual's physical characteristics, such as the user's height, weight, age, gender, exercise experience, and health goals.

[0248] "Artificial intelligence" refers to a technology that mimics human intellectual activity using computer systems, and is particularly used for automating data analysis and decision-making processes.

[0249] An "individualized exercise training plan" is a training program optimized based on the user's physical characteristics and goals, and includes exercise suggestions tailored to the individual.

[0250] "Visually displaying" refers to presenting information in a way that users can see, generally involving the use of screens or displays to show content.

[0251] "Activity progress" refers to data on the exercises and training performed by users and the status of their implementation, indicating the degree of achievement towards the set goals.

[0252] "Ideal future physical condition" refers to the optimal physical state that can be expected based on the health and exercise goals set by the user, and is used to motivate the user through visualization.

[0253] This invention is a system for providing personalized exercise training programs, enabling users to easily manage their health at home. The following describes embodiments for carrying out this invention.

[0254] The system consists of a terminal and a server. Users input their physical information using the terminal. This terminal is generally assumed to be a smartphone or tablet computer, and information can be entered via a user interface. The information entered includes height, weight, age, gender, exercise experience, and health goals.

[0255] The terminal transmits the entered physical information to the server. The server, equipped with a high-performance processor and artificial intelligence frameworks such as TensorFlow and PyTorch, uses the received information to generate an optimal exercise training program for each user. This program utilizes advanced information processing technology to identify and propose the most suitable training content and pace for each individual user.

[0256] The generated exercise training program is sent to the terminal in an appropriate format such as JSON and displayed visually. The user then performs the exercise according to the displayed program. For example, a program including light stretching exercises to improve flexibility is suggested for complete beginners, while a program including HIIT (High-Intensity Interval Training) is provided for users with some exercise experience.

[0257] Furthermore, the device encourages users to exercise through push notifications. It can also record the user's training progress and periodically synchronize that data with a server. This allows the server to track the user's progress and visualize and display their ideal future physique.

[0258] An example of a prompt would be: "A 30-year-old female, 160cm tall, weighing 55kg, with exercise experience including yoga once a week. Please suggest an exercise program aimed at weight loss."

[0259] In this way, the present invention supports exercise habits in daily life by providing users with personalized health management methods.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] The terminal displays a screen for the user to enter their physical information. The user enters information such as height, weight, age, gender, exercise experience, and health goals. The terminal formats this information and temporarily stores it for future use. The input data is the user's physical information, and the output is formatted data that can be sent to the server.

[0263] Step 2:

[0264] The terminal transmits the entered biometric information to the server. During this process, the data is encrypted and transmitted using a secure protocol. The input data is formatted biometric information, and the output is a notification to the user confirming the transmission status.

[0265] Step 3:

[0266] The server processes the received physical information. Specifically, it uses artificial intelligence to generate an optimal exercise training program for each user. Data processing includes analysis of numerical data such as height and weight, and pattern recognition based on exercise experience. The input is physical information transmitted from the terminal, and the output is an optimized exercise training program.

[0267] Step 4:

[0268] The server sends the generated exercise training program to the terminal. The terminal receives this information and prepares an interface to display it visually to the user. The input is the program data generated by the server, and the output includes a user interface that visualizes the program content.

[0269] Step 5:

[0270] The device sets up push notifications to encourage the user to exercise. Notifications are sent based on a schedule set by the user. The input data is the exercise schedule, and the output is the sending of notifications at the appropriate time.

[0271] Step 6:

[0272] The user records the progress of their exercise on their device. The device periodically synchronizes this data with the server and saves it as progress data. The input is the progress data recorded by the user, and the output is the progress history stored on the server.

[0273] (Application Example 1)

[0274] 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."

[0275] Modern consumers are seeking efficient and personalized ways to maintain their health and make exercise a habit amidst their busy daily lives. However, support from a personal trainer is time-consuming and costly, and self-managed exercise at home presents challenges in maintaining motivation and correct form. As a result, many people find it difficult to achieve sustained health improvement.

[0276] 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.

[0277] In this invention, the server includes means for receiving the user's physical information, means for generating an individualized exercise training program based on the received physical information, and means for providing the user with the correct form of exercise in real time using a visual display device. This makes it possible for the user to continue training with the correct form while receiving efficient and personalized exercise guidance, and to maintain motivation.

[0278] "Means for receiving user physical information" refers to a system for obtaining physical data from individual users. This data includes height, weight, age, gender, etc.

[0279] The "means for generating an individual exercise training program" is a mechanism for creating an exercise plan optimized for the user based on the received physical information.

[0280] The "means for presenting the generated exercise training program to the user" is a mechanism for visually showing the created exercise plan to the user.

[0281] The "means for recording the user's progress and visually presenting an ideal future body shape" is a device with the function of tracking the user's exercise results and visually expressing the future body shape based on the progress.

[0282] The "visual display device" is a device for displaying visual information to the user in real time and conveying the correct form of exercise.

[0283] This invention is a system for the user to efficiently perform exercise training. First, the user inputs their physical information via a dedicated terminal, and this information is sent to the server. The server generates an individual exercise training program using an AI algorithm based on this physical information. As software, a machine learning library for data analysis and a user interface for visualization are used.

[0284] The generated exercise training program is visualized in real time through the user's smart glasses or head-mounted display. This visual display equipment provides an appropriate form and movement, improving the accuracy of training. For this movement monitoring, visual recognition and sensor data are utilized.

[0285] The recording of progress is synchronized from the terminal to the server regularly, and the server analyzes the user's achievements, predicts an ideal future body shape, and displays it on the terminal. Thereby, the user can quickly grasp their progress situation and maintain motivation towards achieving the goal.

[0286] As a specific example, when a user sets a goal to lose 5 kilograms in weight, the system presents a training program corresponding to that goal. As an example of a prompt sentence, an instruction such as "Please generate an exercise program for efficiently losing weight" can be considered.

[0287] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0288] Step 1:

[0289] The user inputs their physical information into the terminal. This physical information includes height, weight, age, gender, exercise experience, etc. Since this input data will be used later to generate an individually optimized exercise training program, accuracy is required.

[0290] Step 2:

[0291] The terminal transmits the input physical information to the server. The server receives this data and stores it in the database. The received data becomes important basic information for the AI algorithm to generate an optimal exercise training program for the user.

[0292] Step 3:

[0293] The server performs processing using the received physical information with a generated AI model. The AI model utilizes a machine learning algorithm to generate an exercise program tailored to the characteristics of each user. The input is the physical information, and the output is an individualized exercise plan.

[0294] Step 4:

[0295] The generated exercise training program is transmitted from the server to the terminal. The terminal displays the content of the program on a visual display device and provides the obtained exercise plan to the user. Here, the input is the program data from the server, and the output is the display information on the terminal.

[0296] Step 5:

[0297] The user performs the training according to the exercise program presented using a visual display device. The display device ensures the accuracy of the training by providing the user with real-time information on the correct form of the exercise and the next steps.

[0298] Step 6:

[0299] After completing a workout, the device records exercise progress data. This data is synchronized with a server to analyze the effectiveness of the training and help adjust future programs. The progress data is the input, and the plan used to suggest the next workout is the output.

[0300] Step 7:

[0301] The server analyzes progress data and predicts the user's ideal future physique based on their growth and achievements. This information is visualized to the user in real time on their device, serving as motivation for continued exercise.

[0302] 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.

[0303] Embodiments of the present invention are systems that, in addition to individual exercise training programs, recognize the user's emotions and reflect them in the training plan. As an initial setup, the user inputs their physical information via a terminal. The input information is sent to a server so that the AI ​​can generate an optimal exercise training program based on the user's exercise goals and health condition.

[0304] The server processes the received physical information together with various data and creates an individual exercise training program using artificial intelligence. The generated program is transmitted to the user's terminal and presented visually. At this stage, an emotion engine is also incorporated into the program to recognize the user's emotional state in real time.

[0305] Emotion recognition is performed through sensors such as cameras and microphones mounted on the terminal, and emotions are detected from facial expression analysis, voice tone analysis, etc. For example, when the user shows signs of fatigue, the emotion engine recognizes this, and the server adjusts the training program based on this information. Specifically, it is possible to reduce the intensity of the program or add variations to make it more interesting.

[0306] The terminal presents the updated program to the user, issues training notifications to promote execution. Further, after the user conducts training and continuously inputs progress and emotion information, the terminal records this and transmits it to the server. The server analyzes this information and further refines a new training plan to reach the user's long-term health goals.

[0307] As a specific example, when the user engages in training, daily emotion data is collected. If negative emotions persist, the emotion engine recommends relaxation exercises. Also, when the user is in a highly motivated state, the server incorporates more challenging exercises. This provides a flexible and effective training environment tailored to the individual user. The present invention enables emotion-based dynamic exercise management and efficiently supports the user's achievement of body shape goals.

[0308] The following describes the processing flow.

[0309] Step 1:

[0310] The user enters their physical information using a terminal. This information includes height, weight, age, gender, and exercise experience. The terminal verifies the entered information and prepares to send it to the server.

[0311] Step 2:

[0312] The terminal sends input data to the server. The server verifies the received data and stores it in the database in the appropriate format.

[0313] Step 3:

[0314] The server uses accumulated physical information and artificial intelligence to generate an optimal exercise training program for each user. The program is customized based on each user's health condition and goals.

[0315] Step 4:

[0316] The server sends the generated exercise training program to the terminal. The terminal presents the program content to the user and provides an interface to facilitate understanding.

[0317] Step 5:

[0318] The device recognizes the user's real-time emotional state through its emotion engine. This involves analyzing facial expressions and voice tone using the device's camera and microphone.

[0319] Step 6:

[0320] Emotional data recognized by the device is sent to the server. The server adjusts the exercise training program based on the emotional data. If excessive fatigue is detected, the server suggests a program with reduced intensity.

[0321] Step 7:

[0322] The device then presents the adjusted program to the user again. The device sends a push notification to the user to encourage them to complete the training and ensure they don't forget their appointments.

[0323] Step 8:

[0324] After the training is complete, the user reports their progress and emotional state using a device. The device records this information, sends it to a server, and stores it in a database.

[0325] Step 9:

[0326] The server analyzes accumulated progress and emotional data, performs long-term tuning, and incorporates the results into subsequent exercise training programs. Users receive a plan that reflects these results, which helps them maintain their motivation.

[0327] (Example 2)

[0328] 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".

[0329] In recent years, there has been growing interest in health management and maintaining one's physique, but systems that provide exercise plans tailored to individual physical characteristics and emotional states are limited. Furthermore, fixed exercise programs make it difficult to maintain user motivation and continue effective exercise. Therefore, there is a need for exercise programs that can adapt to diverse situations and be adjusted in real time.

[0330] 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.

[0331] In this invention, the server includes means for acquiring the user's physical characteristics information, means for generating an individualized exercise plan based on the acquired physical characteristics information, and means for analyzing the user's emotional state. This makes it possible to provide dynamic and flexible exercise programs tailored to individual needs.

[0332] "User physical characteristics information" refers to data that includes individual user characteristics such as height, weight, age, health status, and exercise goals.

[0333] An "exercise plan" is a plan that outlines the type, intensity, and frequency of exercise, generated based on the user's individual physical characteristics and emotional state.

[0334] "Emotional state" refers to emotion-related data detected from the user's facial expressions and voice, and includes fatigue, motivation, stress, etc.

[0335] "Dynamic adjustment" means flexibly changing the exercise plan according to the situation at the time, reflecting the user's real-time emotional state.

[0336] A "computer processing unit" refers to an electronic device or system used to process diverse information and generate motion plans.

[0337] "Communicating and promoting the continuation of exercise" refers to the act of sending regular notifications to users to encourage them to exercise and support their continued efforts.

[0338] This invention is a system that dynamically generates and adjusts an exercise plan based on the user's physical characteristics and emotional state. The necessary hardware for implementation is an information terminal such as a smartphone or tablet. The software is installed on the terminal as a dedicated application and handles data input, display, and data collection via sensors.

[0339] Users input physical characteristics information such as height, weight, age, health status, and exercise goals through a dedicated application. This information is sent from the terminal to a server. The server generates an individualized exercise plan using AI technology. Specific technologies include generative AI models using TensorFlow and PyTorch. These models have the ability to learn from past data and generate optimized exercise plans in real time.

[0340] Furthermore, the device monitors the user's emotional state using a camera and microphone. Technologies used include facial expression analysis and voice tone analysis via OpenCV. The server analyzes this emotional data and dynamically adjusts the exercise plan. An API known as the emotion engine is used for emotion recognition, appropriately changing the intensity and content of the exercises in response to user feedback.

[0341] For example, if a user plans to train several times a week, and their daily emotions are unstable, relaxation-focused exercises will be suggested. Conversely, when they are highly motivated, more challenging exercises will be incorporated. This dynamic adjustment ensures that users always receive an exercise plan that is optimal for their current state.

[0342] As an example of an input prompt for the generating AI model, one could ask the system a question in the form of, "I'm a 30-year-old male aiming to lose weight. I've been feeling unmotivated lately. What kind of exercise program would be suitable for me?" This system provides a customized exercise experience for each user, enabling support towards long-term health goals.

[0343] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0344] Step 1:

[0345] The user enters physical characteristics information such as height, weight, age, health status, and exercise goals into a dedicated application on the device. The entered data is formatted and securely transmitted to the server using encryption. In this step, the input is physical characteristics information, and the output is formatted data ready to be sent to the server.

[0346] Step 2:

[0347] The server analyzes the received physical characteristics information. First, it stores it in a database and uses it as basic data for processing by the AI ​​model. The generative AI model used here generates individual exercise plans by referring to past training data and similar user data. The input for this step is the user's physical characteristics information data, and the output is the generated exercise plan.

[0348] Step 3:

[0349] The device visually displays the exercise plan sent from the server using a dedicated app. The user reviews the displayed plan and prepares to execute it. The input for this step is the generated exercise plan, and the output is the exercise plan presented to the user.

[0350] Step 4:

[0351] The device begins measuring the user's emotional state using its built-in camera and microphone. The emotion engine measures emotions in real time through facial expression analysis and voice tone analysis, and sends this data to the server. The input for this step is the user's facial expressions and voice data, and the output is emotional state data.

[0352] Step 5:

[0353] The server analyzes the received emotional state data and dynamically adjusts the exercise plan. For example, if the server determines that the user is tired, it automatically reduces the intensity of the exercise and incorporates exercises that promote relaxation. The input for this step is emotional state data, and the output is the adjusted exercise plan.

[0354] Step 6:

[0355] The terminal receives the adjusted exercise plan from the server and presents it to the user again. The user reviews the updated plan and performs the exercise according to the instructions. The input for this step is the adjusted exercise plan, and the output is the new exercise plan presented to the user.

[0356] Step 7:

[0357] After the user completes their workout, the device collects training progress and new emotional data again and sends it to the server. The server stores this information and uses it to generate the next workout plan. The input for this step is the data after the workout has been completed, and the output is the completed data sent to the server.

[0358] (Application Example 2)

[0359] 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."

[0360] Even when individual exercise training programs are created based on a user's physical information, there is a problem in that they cannot dynamically respond to the user's emotional state, making it difficult to perform optimal exercise. Furthermore, there is a need to accurately reflect progress and emotional changes and provide flexible training that matches the user's goals.

[0361] 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.

[0362] In this invention, the server includes means for receiving the user's physical information and emotional data, means for generating an individualized exercise training program based on the received physical information and emotional data, and means for recording the user's progress and emotional changes, and visualizing an ideal health state based on goals. This enables the provision of an optimal exercise program tailored to the user's emotional state, allowing for efficient health management.

[0363] "Physical information" refers to information including the user's physical data, health status, and exercise history, and is the basis for the exercise training program.

[0364] "Emotional data" refers to data that shows the user's psychological state and emotional changes, and is used to adjust the exercise program.

[0365] An "exercise training program" is a program that provides an individualized exercise schedule and exercise content, generated based on the user's physical information and emotional data.

[0366] "Progress" refers to data showing the implementation status and results of users' exercise plans, and is used to improve future training plans.

[0367] "Artificial intelligence" refers to computational models and algorithms used to analyze diverse information and generate exercise training programs tailored to the user.

[0368] "Notification" refers to a means of communicating information to encourage users to implement an exercise program, including the timing and content of the notification.

[0369] In embodiments of this invention, a system is formed in which communication takes place between the user's terminal and a server, and an individualized exercise training program is provided. The terminal has the function of collecting the user's physical information and emotional data and transmitting it to the server. A smartphone or wearable device is used for this information collection, and data analysis is performed through a camera and microphone.

[0370] The server uses an AI model to generate personalized exercise training programs based on received physical and emotional data. This AI model is built using Python and Flask, and utilizes libraries such as TensorFlow and OpenCV to process diverse information. The generated program is sent to the user's device in real time and presented visually.

[0371] Furthermore, the server records the user's progress and emotional changes, accumulating and analyzing data to inform future training plans. Therefore, continuous data collection and analysis are crucial elements.

[0372] For example, if a user's emotional data detects "fatigue" when they are about to start exercising, the system will suggest a stretching program to promote relaxation. Conversely, if an emotion such as "energetic" is detected, the system can present a more challenging exercise.

[0373] An example of a prompt to input into the generating AI model is: "Based on emotional data and physical information, recommend the optimal training package for the user. The emotional state is reported as 'fatigued,' and the progress is reported as 'on track.'"

[0374] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0375] Step 1:

[0376] The device collects the user's physical and emotional data. The user's smartphone or wearable device uses a camera to collect facial data and a microphone to analyze voice tone. This allows the system to obtain physical and emotional data as input.

[0377] Step 2:

[0378] The device transmits collected physical and emotional data to the server. The data is encrypted during transmission to ensure security. The server receives this data and uses it in the next processing step.

[0379] Step 3:

[0380] The server uses an AI model to analyze the received information. The input here is the data received in step 2. The server uses TensorFlow to process the data with an AI model and generates an optimal exercise training program for the user's physical condition and emotions.

[0381] Step 4:

[0382] The server sends the generated exercise training program to the terminal. The output includes an individualized exercise program and recommendations for exercises tailored to the user. The terminal receives this, presents it visually to the user, and guides them through the next exercise step.

[0383] Step 5:

[0384] When a user performs an exercise, the device records their progress and emotional changes again. This information serves as input data for optimizing future exercise programs. The recorded data is sent back to the server in the next step.

[0385] Step 6:

[0386] The server analyzes progress and emotional data submitted by users and makes further adjustments to provide new training plans. This results in the output of a refined program designed to support users in achieving their long-term exercise goals.

[0387] 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.

[0388] 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.

[0389] 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.

[0390] [Third Embodiment]

[0391] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0392] 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.

[0393] 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).

[0394] 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.

[0395] 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.

[0396] 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).

[0397] 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.

[0398] 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.

[0399] 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.

[0400] 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.

[0401] 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.

[0402] 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".

[0403] An embodiment of the present invention is a system that allows users to easily perform individually optimized exercise training programs at home. The user first inputs their physical information via a terminal. This information includes height, weight, age, gender, and exercise experience. The input information is then transmitted from the terminal to a server.

[0404] The server processes the received physical information and uses artificial intelligence to generate an optimal exercise training program for each user. This allows users to obtain an exercise plan tailored to their health condition and goals. For example, a complete beginner might be presented with a program that includes light stretching exercises three times a week, while a user with some exercise experience might be offered a more intense training program.

[0405] The device visually displays the generated exercise training program to the user and reminds them to remember the schedule and timing through push notifications. For example, if training is scheduled for 7:00 AM, the notification will be sent a little before that time.

[0406] Furthermore, user progress is recorded on the device and periodically synchronized with the server. This allows the server to use the progress data to track changes in the user's physique and visualize and display their ideal future physique on the device. This visualization serves as motivation for users to continue their training.

[0407] As a concrete example, consider a user who has started managing their body fat percentage for health maintenance. The user sets a target body fat percentage of 15%, and the system suggests an exercise program that matches this goal. The server generates a program incorporating ABS and HIIT (High-Intensity Interval Training) and presents it through the terminal. The user trains according to the program and enters the results into the app, allowing them to see their progress at a glance.

[0408] This invention, by incorporating the functions described above, enables the provision of various services that help users achieve their health goals. It is a system that can achieve high effectiveness through data processing utilizing artificial intelligence and user feedback.

[0409] The following describes the processing flow.

[0410] Step 1:

[0411] The user enters their physical information using a terminal. This information includes height, weight, age, gender, and exercise experience. Once the input is complete, the terminal verifies the information and prepares to send it to the server.

[0412] Step 2:

[0413] The terminal sends the entered physical information to the server. After transmission, the server receives the data, verifies its integrity, and stores it in its database.

[0414] Step 3:

[0415] The server uses artificial intelligence to generate an optimal exercise training program based on the received physical information. This program is adjusted according to the user's health condition and goals. The generated program is temporarily stored on the server.

[0416] Step 4:

[0417] The server sends the generated training program to the terminal. The terminal visually presents the received program to the user, taking care to ensure that the user can easily understand it.

[0418] Step 5:

[0419] The device uses push notifications to inform the user of the training schedule. The notifications are sent at appropriate times based on the schedule to ensure the user doesn't forget.

[0420] Step 6:

[0421] Once the user completes the training, they input progress data using a device. The device records this information, updates it, and then sends it to the server.

[0422] Step 7:

[0423] The server receives progress data and analyzes the user's exercise history. Based on the analysis, it generates an ideal body shape image for the user and uses it to adjust the next exercise program.

[0424] Step 8:

[0425] The server sends the generated ideal body shape image to the device. The device displays this image to the user, helping to boost their motivation.

[0426] (Example 1)

[0427] 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."

[0428] In the process of providing users with individually optimized exercise programs, challenges include the inability to continuously monitor their progress and insufficient means to encourage continued exercise. Furthermore, there is a need to improve the reliability of whether the generated programs accurately reflect the diverse physical information of the users.

[0429] 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.

[0430] In this invention, the server includes means for acquiring information about the user's body, means for generating an individualized exercise training plan using artificial intelligence based on the acquired information about the body, and means for visually displaying the generated exercise training plan to the user. This makes it possible to provide a training program that meets the user's individual exercise needs, as well as to monitor its progress in real time and promote the execution of exercise at the appropriate time.

[0431] "Information about the user's physical characteristics" refers to data that shows an individual's physical characteristics, such as the user's height, weight, age, gender, exercise experience, and health goals.

[0432] "Artificial intelligence" refers to a technology that mimics human intellectual activity using computer systems, and is particularly used for automating data analysis and decision-making processes.

[0433] An "individualized exercise training plan" is a training program optimized based on the user's physical characteristics and goals, and includes exercise suggestions tailored to the individual.

[0434] "Visually displaying" refers to presenting information in a way that users can see, generally involving the use of screens or displays to show content.

[0435] "Activity progress" refers to data on the exercises and training performed by users and the status of their implementation, indicating the degree of achievement towards the set goals.

[0436] "Ideal future physical condition" refers to the optimal physical state that can be expected based on the health and exercise goals set by the user, and is used to motivate the user through visualization.

[0437] This invention is a system for providing personalized exercise training programs, enabling users to easily manage their health at home. The following describes embodiments for carrying out this invention.

[0438] The system consists of a terminal and a server. Users input their physical information using the terminal. This terminal is generally assumed to be a smartphone or tablet computer, and information can be entered via a user interface. The information entered includes height, weight, age, gender, exercise experience, and health goals.

[0439] The terminal transmits the entered physical information to the server. The server, equipped with a high-performance processor and artificial intelligence frameworks such as TensorFlow and PyTorch, uses the received information to generate an optimal exercise training program for each user. This program utilizes advanced information processing technology to identify and propose the most suitable training content and pace for each individual user.

[0440] The generated exercise training program is sent to the terminal in an appropriate format such as JSON and displayed visually. The user then performs the exercise according to the displayed program. For example, a program including light stretching exercises to improve flexibility is suggested for complete beginners, while a program including HIIT (High-Intensity Interval Training) is provided for users with some exercise experience.

[0441] Furthermore, the device encourages users to exercise through push notifications. It can also record the user's training progress and periodically synchronize that data with a server. This allows the server to track the user's progress and visualize and display their ideal future physique.

[0442] An example of a prompt would be: "A 30-year-old female, 160cm tall, weighing 55kg, with exercise experience including yoga once a week. Please suggest an exercise program aimed at weight loss."

[0443] In this way, the present invention supports exercise habits in daily life by providing users with personalized health management methods.

[0444] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0445] Step 1:

[0446] The terminal displays a screen for the user to enter their physical information. The user enters information such as height, weight, age, gender, exercise experience, and health goals. The terminal formats this information and temporarily stores it for future use. The input data is the user's physical information, and the output is formatted data that can be sent to the server.

[0447] Step 2:

[0448] The terminal transmits the entered biometric information to the server. During this process, the data is encrypted and transmitted using a secure protocol. The input data is formatted biometric information, and the output is a notification to the user confirming the transmission status.

[0449] Step 3:

[0450] The server processes the received physical information. Specifically, it uses artificial intelligence to generate an optimal exercise training program for each user. Data processing includes analysis of numerical data such as height and weight, and pattern recognition based on exercise experience. The input is physical information transmitted from the terminal, and the output is an optimized exercise training program.

[0451] Step 4:

[0452] The server sends the generated exercise training program to the terminal. The terminal receives this information and prepares an interface to display it visually to the user. The input is the program data generated by the server, and the output includes a user interface that visualizes the program content.

[0453] Step 5:

[0454] The device sets up push notifications to encourage the user to exercise. Notifications are sent based on a schedule set by the user. The input data is the exercise schedule, and the output is the sending of notifications at the appropriate time.

[0455] Step 6:

[0456] The user records the progress of their exercise on their device. The device periodically synchronizes this data with the server and saves it as progress data. The input is the progress data recorded by the user, and the output is the progress history stored on the server.

[0457] (Application Example 1)

[0458] 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."

[0459] Modern consumers are seeking efficient and personalized ways to maintain their health and make exercise a habit amidst their busy daily lives. However, support from a personal trainer is time-consuming and costly, and self-managed exercise at home presents challenges in maintaining motivation and correct form. As a result, many people find it difficult to achieve sustained health improvement.

[0460] 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.

[0461] In this invention, the server includes means for receiving the user's physical information, means for generating an individualized exercise training program based on the received physical information, and means for providing the user with the correct form of exercise in real time using a visual display device. This makes it possible for the user to continue training with the correct form while receiving efficient and personalized exercise guidance, and to maintain motivation.

[0462] "Means for receiving user physical information" refers to a system for obtaining physical data from individual users. This data includes height, weight, age, gender, etc.

[0463] "Means for generating individual exercise training programs" refers to a system for creating an exercise plan optimized for the user based on received physical information.

[0464] "Means for presenting the generated exercise training program to the user" refers to a mechanism for visually showing the created exercise plan to the user.

[0465] "A means of recording the user's progress and visually presenting their ideal future physique" refers to a device that tracks the user's exercise results and visually represents their future physique based on their progress.

[0466] A "visual display device" is a device that displays visual information to the user in real time and conveys the correct form of movement.

[0467] This invention is a system for users to efficiently perform exercise training. First, the user inputs their physical information via a dedicated terminal, and this information is sent to a server. Based on this physical information, the server generates an individualized exercise training program using an AI algorithm. The software used includes machine learning libraries for data analysis and a user interface for visualization.

[0468] The generated exercise training program is visualized in real time through the user's smart glasses or head-mounted display. This visual display provides proper form and movement, improving the accuracy of the training. Visual recognition and sensor data are used for this movement monitoring.

[0469] Progress records are periodically synchronized from the device to the server, which analyzes the user's performance and predicts and displays their ideal future physique on the device. This allows users to quickly grasp their progress and maintain motivation towards achieving their goals.

[0470] For example, if a user sets a goal of losing 5 kilograms, the system will present a training program tailored to that goal. An example of a prompt might be, "Generate an exercise program to efficiently lose weight."

[0471] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0472] Step 1:

[0473] Users enter their physical information into the terminal. This information includes height, weight, age, gender, and exercise experience. Accuracy is required because this input data will later be used to generate individually optimized exercise training programs.

[0474] Step 2:

[0475] The terminal transmits the entered physical information to the server. The server receives this data and stores it in a database. The received data becomes crucial foundational information for the AI ​​algorithm to generate an optimal exercise training program for the user.

[0476] Step 3:

[0477] The server processes the received physical information using a generating AI model. The AI ​​model utilizes machine learning algorithms to generate exercise programs tailored to each user's characteristics. The input is physical information, and the output is an individualized exercise plan.

[0478] Step 4:

[0479] The generated exercise training program is sent from the server to the terminal. The terminal displays the program content on a visual display device and provides the user with the resulting exercise plan. The input here is the program data from the server, and the output is the information displayed on the terminal.

[0480] Step 5:

[0481] The user performs the training according to the exercise program presented using a visual display device. The display device ensures the accuracy of the training by providing the user with real-time information on the correct form of the exercise and the next steps.

[0482] Step 6:

[0483] After completing a workout, the device records exercise progress data. This data is synchronized with a server to analyze the effectiveness of the training and help adjust future programs. The progress data is the input, and the plan used to suggest the next workout is the output.

[0484] Step 7:

[0485] The server analyzes progress data and predicts the user's ideal future physique based on their growth and achievements. This information is visualized to the user in real time on their device, serving as motivation for continued exercise.

[0486] 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.

[0487] Embodiments of the present invention are systems that, in addition to individual exercise training programs, recognize the user's emotions and reflect them in the training plan. As an initial setup, the user inputs their physical information via a terminal. The input information is sent to a server so that the AI ​​can generate an optimal exercise training program based on the user's exercise goals and health condition.

[0488] The server processes the received physical information along with various other data and uses artificial intelligence to create a personalized exercise training program. The generated program is sent to the user's terminal and presented visually. At this stage, an emotion engine is also incorporated into the program to recognize the user's emotional state in real time.

[0489] Emotion recognition is performed through sensors in the device's camera and microphone, detecting emotions through facial expression analysis and voice tone analysis. For example, if a user shows signs of fatigue, the emotion engine recognizes this, and the server adjusts the training program based on that information. Specifically, it can reduce the intensity of the program or add more engaging variations.

[0490] The device presents the user with updated programs and provides training notifications to encourage participation. Furthermore, after the user completes the training and continuously inputs progress and emotional information, the device records this information and sends it to the server. The server analyzes this information to further refine new training plans to help the user achieve their long-term health goals.

[0491] As a concrete example, when a user engages in training, daily emotional data is collected, and if negative emotions persist, the emotional engine recommends relaxation exercises. Conversely, if the user is highly motivated, the server incorporates more challenging exercises. This provides a flexible and effective training environment tailored to each individual user. This invention enables dynamic exercise management based on emotions, efficiently supporting users in achieving their body shape goals.

[0492] The following describes the processing flow.

[0493] Step 1:

[0494] The user enters their physical information using a terminal. This information includes height, weight, age, gender, and exercise experience. The terminal verifies the entered information and prepares to send it to the server.

[0495] Step 2:

[0496] The terminal sends input data to the server. The server verifies the received data and stores it in the database in the appropriate format.

[0497] Step 3:

[0498] The server uses accumulated physical information and artificial intelligence to generate an optimal exercise training program for each user. The program is customized based on each user's health condition and goals.

[0499] Step 4:

[0500] The server sends the generated exercise training program to the terminal. The terminal presents the program content to the user and provides an interface to facilitate understanding.

[0501] Step 5:

[0502] The device recognizes the user's real-time emotional state through its emotion engine. This involves analyzing facial expressions and voice tone using the device's camera and microphone.

[0503] Step 6:

[0504] Emotional data recognized by the device is sent to the server. The server adjusts the exercise training program based on the emotional data. If excessive fatigue is detected, the server suggests a program with reduced intensity.

[0505] Step 7:

[0506] The device then presents the adjusted program to the user again. The device sends a push notification to the user to encourage them to complete the training and ensure they don't forget their appointments.

[0507] Step 8:

[0508] After the training is complete, the user reports their progress and emotional state using a device. The device records this information, sends it to a server, and stores it in a database.

[0509] Step 9:

[0510] The server analyzes accumulated progress and emotional data, performs long-term tuning, and incorporates the results into subsequent exercise training programs. Users receive a plan that reflects these results, which helps them maintain their motivation.

[0511] (Example 2)

[0512] 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."

[0513] In recent years, there has been growing interest in health management and maintaining one's physique, but systems that provide exercise plans tailored to individual physical characteristics and emotional states are limited. Furthermore, fixed exercise programs make it difficult to maintain user motivation and continue effective exercise. Therefore, there is a need for exercise programs that can adapt to diverse situations and be adjusted in real time.

[0514] 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.

[0515] In this invention, the server includes means for acquiring the user's physical characteristics information, means for generating an individualized exercise plan based on the acquired physical characteristics information, and means for analyzing the user's emotional state. This makes it possible to provide dynamic and flexible exercise programs tailored to individual needs.

[0516] "User physical characteristics information" refers to data that includes individual user characteristics such as height, weight, age, health status, and exercise goals.

[0517] An "exercise plan" is a plan that outlines the type, intensity, and frequency of exercise, generated based on the user's individual physical characteristics and emotional state.

[0518] "Emotional state" refers to emotion-related data detected from the user's facial expressions and voice, and includes fatigue, motivation, stress, etc.

[0519] "Dynamic adjustment" means flexibly changing the exercise plan according to the situation at the time, reflecting the user's real-time emotional state.

[0520] A "computer processing unit" refers to an electronic device or system used to process diverse information and generate motion plans.

[0521] "Communicating and promoting the continuation of exercise" refers to the act of sending regular notifications to users to encourage them to exercise and support their continued efforts.

[0522] This invention is a system that dynamically generates and adjusts an exercise plan based on the user's physical characteristics and emotional state. The necessary hardware for implementation is an information terminal such as a smartphone or tablet. The software is installed on the terminal as a dedicated application and handles data input, display, and data collection via sensors.

[0523] Users input physical characteristics information such as height, weight, age, health status, and exercise goals through a dedicated application. This information is sent from the terminal to a server. The server generates an individualized exercise plan using AI technology. Specific technologies include generative AI models using TensorFlow and PyTorch. These models have the ability to learn from past data and generate optimized exercise plans in real time.

[0524] Furthermore, the device monitors the user's emotional state using a camera and microphone. Technologies used include facial expression analysis and voice tone analysis via OpenCV. The server analyzes this emotional data and dynamically adjusts the exercise plan. An API known as the emotion engine is used for emotion recognition, appropriately changing the intensity and content of the exercises in response to user feedback.

[0525] For example, if a user plans to train several times a week, and their daily emotions are unstable, relaxation-focused exercises will be suggested. Conversely, when they are highly motivated, more challenging exercises will be incorporated. This dynamic adjustment ensures that users always receive an exercise plan that is optimal for their current state.

[0526] As an example of an input prompt for the generating AI model, one could ask the system a question in the form of, "I'm a 30-year-old male aiming to lose weight. I've been feeling unmotivated lately. What kind of exercise program would be suitable for me?" This system provides a customized exercise experience for each user, enabling support towards long-term health goals.

[0527] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0528] Step 1:

[0529] The user enters physical characteristics information such as height, weight, age, health status, and exercise goals into a dedicated application on the device. The entered data is formatted and securely transmitted to the server using encryption. In this step, the input is physical characteristics information, and the output is formatted data ready to be sent to the server.

[0530] Step 2:

[0531] The server analyzes the received physical characteristics information. First, it stores it in a database and uses it as basic data for processing by the AI ​​model. The generative AI model used here generates individual exercise plans by referring to past training data and similar user data. The input for this step is the user's physical characteristics information data, and the output is the generated exercise plan.

[0532] Step 3:

[0533] The device visually displays the exercise plan sent from the server using a dedicated app. The user reviews the displayed plan and prepares to execute it. The input for this step is the generated exercise plan, and the output is the exercise plan presented to the user.

[0534] Step 4:

[0535] The device begins measuring the user's emotional state using its built-in camera and microphone. The emotion engine measures emotions in real time through facial expression analysis and voice tone analysis, and sends this data to the server. The input for this step is the user's facial expressions and voice data, and the output is emotional state data.

[0536] Step 5:

[0537] The server analyzes the received emotional state data and dynamically adjusts the exercise plan. For example, if the server determines that the user is tired, it automatically reduces the intensity of the exercise and incorporates exercises that promote relaxation. The input for this step is emotional state data, and the output is the adjusted exercise plan.

[0538] Step 6:

[0539] The terminal receives the adjusted exercise plan from the server and presents it to the user again. The user reviews the updated plan and performs the exercise according to the instructions. The input for this step is the adjusted exercise plan, and the output is the new exercise plan presented to the user.

[0540] Step 7:

[0541] After the user completes their workout, the device collects training progress and new emotional data again and sends it to the server. The server stores this information and uses it to generate the next workout plan. The input for this step is the data after the workout has been completed, and the output is the completed data sent to the server.

[0542] (Application Example 2)

[0543] 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."

[0544] Even when individual exercise training programs are created based on a user's physical information, there is a problem in that they cannot dynamically respond to the user's emotional state, making it difficult to perform optimal exercise. Furthermore, there is a need to accurately reflect progress and emotional changes and provide flexible training that matches the user's goals.

[0545] 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.

[0546] In this invention, the server includes means for receiving the user's physical information and emotional data, means for generating an individualized exercise training program based on the received physical information and emotional data, and means for recording the user's progress and emotional changes, and visualizing an ideal health state based on goals. This enables the provision of an optimal exercise program tailored to the user's emotional state, allowing for efficient health management.

[0547] "Physical information" refers to information including the user's physical data, health status, and exercise history, and is the basis for the exercise training program.

[0548] "Emotional data" refers to data that shows the user's psychological state and emotional changes, and is used to adjust the exercise program.

[0549] An "exercise training program" is a program that provides an individualized exercise schedule and exercise content, generated based on the user's physical information and emotional data.

[0550] "Progress" refers to data showing the implementation status and results of users' exercise plans, and is used to improve future training plans.

[0551] "Artificial intelligence" refers to computational models and algorithms used to analyze diverse information and generate exercise training programs tailored to the user.

[0552] "Notification" refers to a means of communicating information to encourage users to implement an exercise program, including the timing and content of the notification.

[0553] In embodiments of this invention, a system is formed in which communication takes place between the user's terminal and a server, and an individualized exercise training program is provided. The terminal has the function of collecting the user's physical information and emotional data and transmitting it to the server. A smartphone or wearable device is used for this information collection, and data analysis is performed through a camera and microphone.

[0554] The server uses an AI model to generate personalized exercise training programs based on received physical and emotional data. This AI model is built using Python and Flask, and utilizes libraries such as TensorFlow and OpenCV to process diverse information. The generated program is sent to the user's device in real time and presented visually.

[0555] Furthermore, the server records the user's progress and emotional changes, accumulating and analyzing data to inform future training plans. Therefore, continuous data collection and analysis are crucial elements.

[0556] For example, if a user's emotional data detects "fatigue" when they are about to start exercising, the system will suggest a stretching program to promote relaxation. Conversely, if an emotion such as "energetic" is detected, the system can present a more challenging exercise.

[0557] An example of a prompt to input into the generating AI model is: "Based on emotional data and physical information, recommend the optimal training package for the user. The emotional state is reported as 'fatigued,' and the progress is reported as 'on track.'"

[0558] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0559] Step 1:

[0560] The device collects the user's physical and emotional data. The user's smartphone or wearable device uses a camera to collect facial data and a microphone to analyze voice tone. This allows the system to obtain physical and emotional data as input.

[0561] Step 2:

[0562] The device transmits collected physical and emotional data to the server. The data is encrypted during transmission to ensure security. The server receives this data and uses it in the next processing step.

[0563] Step 3:

[0564] The server uses an AI model to analyze the received information. The input here is the data received in step 2. The server uses TensorFlow to process the data with an AI model and generates an optimal exercise training program for the user's physical condition and emotions.

[0565] Step 4:

[0566] The server sends the generated exercise training program to the terminal. The output includes an individualized exercise program and recommendations for exercises tailored to the user. The terminal receives this, presents it visually to the user, and guides them through the next exercise step.

[0567] Step 5:

[0568] When a user performs an exercise, the device records their progress and emotional changes again. This information serves as input data for optimizing future exercise programs. The recorded data is sent back to the server in the next step.

[0569] Step 6:

[0570] The server analyzes progress and emotional data submitted by users and makes further adjustments to provide new training plans. This results in the output of a refined program designed to support users in achieving their long-term exercise goals.

[0571] 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.

[0572] 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.

[0573] 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.

[0574] [Fourth Embodiment]

[0575] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0576] 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.

[0577] 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).

[0578] 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.

[0579] 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.

[0580] 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).

[0581] 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.

[0582] 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.

[0583] 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.

[0584] 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.

[0585] 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.

[0586] 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.

[0587] 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".

[0588] An embodiment of the present invention is a system that allows users to easily perform individually optimized exercise training programs at home. The user first inputs their physical information via a terminal. This information includes height, weight, age, gender, and exercise experience. The input information is then transmitted from the terminal to a server.

[0589] The server processes the received physical information and uses artificial intelligence to generate an optimal exercise training program for each user. This allows users to obtain an exercise plan tailored to their health condition and goals. For example, a complete beginner might be presented with a program that includes light stretching exercises three times a week, while a user with some exercise experience might be offered a more intense training program.

[0590] The device visually displays the generated exercise training program to the user and reminds them to remember the schedule and timing through push notifications. For example, if training is scheduled for 7:00 AM, the notification will be sent a little before that time.

[0591] Furthermore, user progress is recorded on the device and periodically synchronized with the server. This allows the server to use the progress data to track changes in the user's physique and visualize and display their ideal future physique on the device. This visualization serves as motivation for users to continue their training.

[0592] As a concrete example, consider a user who has started managing their body fat percentage for health maintenance. The user sets a target body fat percentage of 15%, and the system suggests an exercise program that matches this goal. The server generates a program incorporating ABS and HIIT (High-Intensity Interval Training) and presents it through the terminal. The user trains according to the program and enters the results into the app, allowing them to see their progress at a glance.

[0593] This invention, by incorporating the functions described above, enables the provision of various services that help users achieve their health goals. It is a system that can achieve high effectiveness through data processing utilizing artificial intelligence and user feedback.

[0594] The following describes the processing flow.

[0595] Step 1:

[0596] The user enters their physical information using a terminal. This information includes height, weight, age, gender, and exercise experience. Once the input is complete, the terminal verifies the information and prepares to send it to the server.

[0597] Step 2:

[0598] The terminal sends the entered physical information to the server. After transmission, the server receives the data, verifies its integrity, and stores it in its database.

[0599] Step 3:

[0600] The server uses artificial intelligence to generate an optimal exercise training program based on the received physical information. This program is adjusted according to the user's health condition and goals. The generated program is temporarily stored on the server.

[0601] Step 4:

[0602] The server sends the generated training program to the terminal. The terminal visually presents the received program to the user, taking care to ensure that the user can easily understand it.

[0603] Step 5:

[0604] The device uses push notifications to inform the user of the training schedule. The notifications are sent at appropriate times based on the schedule to ensure the user doesn't forget.

[0605] Step 6:

[0606] Once the user completes the training, they input progress data using a device. The device records this information, updates it, and then sends it to the server.

[0607] Step 7:

[0608] The server receives progress data and analyzes the user's exercise history. Based on the analysis, it generates an ideal body shape image for the user and uses it to adjust the next exercise program.

[0609] Step 8:

[0610] The server sends the generated ideal body shape image to the device. The device displays this image to the user, helping to boost their motivation.

[0611] (Example 1)

[0612] 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".

[0613] In the process of providing users with individually optimized exercise programs, challenges include the inability to continuously monitor their progress and insufficient means to encourage continued exercise. Furthermore, there is a need to improve the reliability of whether the generated programs accurately reflect the diverse physical information of the users.

[0614] 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.

[0615] In this invention, the server includes means for acquiring information about the user's body, means for generating an individualized exercise training plan using artificial intelligence based on the acquired information about the body, and means for visually displaying the generated exercise training plan to the user. This makes it possible to provide a training program that meets the user's individual exercise needs, as well as to monitor its progress in real time and promote the execution of exercise at the appropriate time.

[0616] "Information about the user's physical characteristics" refers to data that shows an individual's physical characteristics, such as the user's height, weight, age, gender, exercise experience, and health goals.

[0617] "Artificial intelligence" refers to a technology that mimics human intellectual activity using computer systems, and is particularly used for automating data analysis and decision-making processes.

[0618] An "individualized exercise training plan" is a training program optimized based on the user's physical characteristics and goals, and includes exercise suggestions tailored to the individual.

[0619] "Visually displaying" refers to presenting information in a way that users can see, generally involving the use of screens or displays to show content.

[0620] "Activity progress" refers to data on the exercises and training performed by users and the status of their implementation, indicating the degree of achievement towards the set goals.

[0621] "Ideal future physical condition" refers to the optimal physical state that can be expected based on the health and exercise goals set by the user, and is used to motivate the user through visualization.

[0622] This invention is a system for providing personalized exercise training programs, enabling users to easily manage their health at home. The following describes embodiments for carrying out this invention.

[0623] The system consists of a terminal and a server. Users input their physical information using the terminal. This terminal is generally assumed to be a smartphone or tablet computer, and information can be entered via a user interface. The information entered includes height, weight, age, gender, exercise experience, and health goals.

[0624] The terminal transmits the entered physical information to the server. The server, equipped with a high-performance processor and artificial intelligence frameworks such as TensorFlow and PyTorch, uses the received information to generate an optimal exercise training program for each user. This program utilizes advanced information processing technology to identify and propose the most suitable training content and pace for each individual user.

[0625] The generated exercise training program is sent to the terminal in an appropriate format such as JSON and displayed visually. The user then performs the exercise according to the displayed program. For example, a program including light stretching exercises to improve flexibility is suggested for complete beginners, while a program including HIIT (High-Intensity Interval Training) is provided for users with some exercise experience.

[0626] Furthermore, the device encourages users to exercise through push notifications. It can also record the user's training progress and periodically synchronize that data with a server. This allows the server to track the user's progress and visualize and display their ideal future physique.

[0627] An example of a prompt would be: "A 30-year-old female, 160cm tall, weighing 55kg, with exercise experience including yoga once a week. Please suggest an exercise program aimed at weight loss."

[0628] In this way, the present invention supports exercise habits in daily life by providing users with personalized health management methods.

[0629] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0630] Step 1:

[0631] The terminal displays a screen for the user to enter their physical information. The user enters information such as height, weight, age, gender, exercise experience, and health goals. The terminal formats this information and temporarily stores it for future use. The input data is the user's physical information, and the output is formatted data that can be sent to the server.

[0632] Step 2:

[0633] The terminal transmits the entered biometric information to the server. During this process, the data is encrypted and transmitted using a secure protocol. The input data is formatted biometric information, and the output is a notification to the user confirming the transmission status.

[0634] Step 3:

[0635] The server processes the received physical information. Specifically, it uses artificial intelligence to generate an optimal exercise training program for each user. Data processing includes analysis of numerical data such as height and weight, and pattern recognition based on exercise experience. The input is physical information transmitted from the terminal, and the output is an optimized exercise training program.

[0636] Step 4:

[0637] The server sends the generated exercise training program to the terminal. The terminal receives this information and prepares an interface to display it visually to the user. The input is the program data generated by the server, and the output includes a user interface that visualizes the program content.

[0638] Step 5:

[0639] The device sets up push notifications to encourage the user to exercise. Notifications are sent based on a schedule set by the user. The input data is the exercise schedule, and the output is the sending of notifications at the appropriate time.

[0640] Step 6:

[0641] The user records the progress of their exercise on their device. The device periodically synchronizes this data with the server and saves it as progress data. The input is the progress data recorded by the user, and the output is the progress history stored on the server.

[0642] (Application Example 1)

[0643] 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".

[0644] Modern consumers are seeking efficient and personalized ways to maintain their health and make exercise a habit amidst their busy daily lives. However, support from a personal trainer is time-consuming and costly, and self-managed exercise at home presents challenges in maintaining motivation and correct form. As a result, many people find it difficult to achieve sustained health improvement.

[0645] 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.

[0646] In this invention, the server includes means for receiving the user's physical information, means for generating an individualized exercise training program based on the received physical information, and means for providing the user with the correct form of exercise in real time using a visual display device. This makes it possible for the user to continue training with the correct form while receiving efficient and personalized exercise guidance, and to maintain motivation.

[0647] "Means for receiving user physical information" refers to a system for obtaining physical data from individual users. This data includes height, weight, age, gender, etc.

[0648] "Means for generating individual exercise training programs" refers to a system for creating an exercise plan optimized for the user based on received physical information.

[0649] "Means for presenting the generated exercise training program to the user" refers to a mechanism for visually showing the created exercise plan to the user.

[0650] "A means of recording the user's progress and visually presenting their ideal future physique" refers to a device that tracks the user's exercise results and visually represents their future physique based on their progress.

[0651] A "visual display device" is a device that displays visual information to the user in real time and conveys the correct form of movement.

[0652] This invention is a system for users to efficiently perform exercise training. First, the user inputs their physical information via a dedicated terminal, and this information is sent to a server. Based on this physical information, the server generates an individualized exercise training program using an AI algorithm. The software used includes machine learning libraries for data analysis and a user interface for visualization.

[0653] The generated exercise training program is visualized in real time through the user's smart glasses or head-mounted display. This visual display provides proper form and movement, improving the accuracy of the training. Visual recognition and sensor data are used for this movement monitoring.

[0654] Progress records are periodically synchronized from the device to the server, which analyzes the user's performance and predicts and displays their ideal future physique on the device. This allows users to quickly grasp their progress and maintain motivation towards achieving their goals.

[0655] For example, if a user sets a goal of losing 5 kilograms, the system will present a training program tailored to that goal. An example of a prompt might be, "Generate an exercise program to efficiently lose weight."

[0656] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0657] Step 1:

[0658] Users enter their physical information into the terminal. This information includes height, weight, age, gender, and exercise experience. Accuracy is required because this input data will later be used to generate individually optimized exercise training programs.

[0659] Step 2:

[0660] The terminal transmits the entered physical information to the server. The server receives this data and stores it in a database. The received data becomes crucial foundational information for the AI ​​algorithm to generate an optimal exercise training program for the user.

[0661] Step 3:

[0662] The server processes the received physical information using a generating AI model. The AI ​​model utilizes machine learning algorithms to generate exercise programs tailored to each user's characteristics. The input is physical information, and the output is an individualized exercise plan.

[0663] Step 4:

[0664] The generated exercise training program is sent from the server to the terminal. The terminal displays the program content on a visual display device and provides the user with the resulting exercise plan. The input here is the program data from the server, and the output is the information displayed on the terminal.

[0665] Step 5:

[0666] The user performs the training according to the exercise program presented using a visual display device. The display device ensures the accuracy of the training by providing the user with real-time information on the correct form of the exercise and the next steps.

[0667] Step 6:

[0668] After completing a workout, the device records exercise progress data. This data is synchronized with a server to analyze the effectiveness of the training and help adjust future programs. The progress data is the input, and the plan used to suggest the next workout is the output.

[0669] Step 7:

[0670] The server analyzes progress data and predicts the user's ideal future physique based on their growth and achievements. This information is visualized to the user in real time on their device, serving as motivation for continued exercise.

[0671] 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.

[0672] Embodiments of the present invention are systems that, in addition to individual exercise training programs, recognize the user's emotions and reflect them in the training plan. As an initial setup, the user inputs their physical information via a terminal. The input information is sent to a server so that the AI ​​can generate an optimal exercise training program based on the user's exercise goals and health condition.

[0673] The server processes the received physical information along with various other data and uses artificial intelligence to create a personalized exercise training program. The generated program is sent to the user's terminal and presented visually. At this stage, an emotion engine is also incorporated into the program to recognize the user's emotional state in real time.

[0674] Emotion recognition is performed through sensors in the device's camera and microphone, detecting emotions through facial expression analysis and voice tone analysis. For example, if a user shows signs of fatigue, the emotion engine recognizes this, and the server adjusts the training program based on that information. Specifically, it can reduce the intensity of the program or add more engaging variations.

[0675] The device presents the user with updated programs and provides training notifications to encourage participation. Furthermore, after the user completes the training and continuously inputs progress and emotional information, the device records this information and sends it to the server. The server analyzes this information to further refine new training plans to help the user achieve their long-term health goals.

[0676] As a concrete example, when a user engages in training, daily emotional data is collected, and if negative emotions persist, the emotional engine recommends relaxation exercises. Conversely, if the user is highly motivated, the server incorporates more challenging exercises. This provides a flexible and effective training environment tailored to each individual user. This invention enables dynamic exercise management based on emotions, efficiently supporting users in achieving their body shape goals.

[0677] The following describes the processing flow.

[0678] Step 1:

[0679] The user enters their physical information using a terminal. This information includes height, weight, age, gender, and exercise experience. The terminal verifies the entered information and prepares to send it to the server.

[0680] Step 2:

[0681] The terminal sends input data to the server. The server verifies the received data and stores it in the database in the appropriate format.

[0682] Step 3:

[0683] The server uses accumulated physical information and artificial intelligence to generate an optimal exercise training program for each user. The program is customized based on each user's health condition and goals.

[0684] Step 4:

[0685] The server sends the generated exercise training program to the terminal. The terminal presents the program content to the user and provides an interface to facilitate understanding.

[0686] Step 5:

[0687] The device recognizes the user's real-time emotional state through its emotion engine. This involves analyzing facial expressions and voice tone using the device's camera and microphone.

[0688] Step 6:

[0689] Emotional data recognized by the device is sent to the server. The server adjusts the exercise training program based on the emotional data. If excessive fatigue is detected, the server suggests a program with reduced intensity.

[0690] Step 7:

[0691] The device then presents the adjusted program to the user again. The device sends a push notification to the user to encourage them to complete the training and ensure they don't forget their appointments.

[0692] Step 8:

[0693] After the training is complete, the user reports their progress and emotional state using a device. The device records this information, sends it to a server, and stores it in a database.

[0694] Step 9:

[0695] The server analyzes accumulated progress and emotional data, performs long-term tuning, and incorporates the results into subsequent exercise training programs. Users receive a plan that reflects these results, which helps them maintain their motivation.

[0696] (Example 2)

[0697] 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".

[0698] In recent years, there has been growing interest in health management and maintaining one's physique, but systems that provide exercise plans tailored to individual physical characteristics and emotional states are limited. Furthermore, fixed exercise programs make it difficult to maintain user motivation and continue effective exercise. Therefore, there is a need for exercise programs that can adapt to diverse situations and be adjusted in real time.

[0699] 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.

[0700] In this invention, the server includes means for acquiring the user's physical characteristics information, means for generating an individualized exercise plan based on the acquired physical characteristics information, and means for analyzing the user's emotional state. This makes it possible to provide dynamic and flexible exercise programs tailored to individual needs.

[0701] "User physical characteristics information" refers to data that includes individual user characteristics such as height, weight, age, health status, and exercise goals.

[0702] An "exercise plan" is a plan that outlines the type, intensity, and frequency of exercise, generated based on the user's individual physical characteristics and emotional state.

[0703] "Emotional state" refers to emotion-related data detected from the user's facial expressions and voice, and includes fatigue, motivation, stress, etc.

[0704] "Dynamic adjustment" means flexibly changing the exercise plan according to the situation at the time, reflecting the user's real-time emotional state.

[0705] A "computer processing unit" refers to an electronic device or system used to process diverse information and generate motion plans.

[0706] "Communicating and promoting the continuation of exercise" refers to the act of sending regular notifications to users to encourage them to exercise and support their continued efforts.

[0707] This invention is a system that dynamically generates and adjusts an exercise plan based on the user's physical characteristics and emotional state. The necessary hardware for implementation is an information terminal such as a smartphone or tablet. The software is installed on the terminal as a dedicated application and handles data input, display, and data collection via sensors.

[0708] Users input physical characteristics information such as height, weight, age, health status, and exercise goals through a dedicated application. This information is sent from the terminal to a server. The server generates an individualized exercise plan using AI technology. Specific technologies include generative AI models using TensorFlow and PyTorch. These models have the ability to learn from past data and generate optimized exercise plans in real time.

[0709] Furthermore, the device monitors the user's emotional state using a camera and microphone. Technologies used include facial expression analysis and voice tone analysis via OpenCV. The server analyzes this emotional data and dynamically adjusts the exercise plan. An API known as the emotion engine is used for emotion recognition, appropriately changing the intensity and content of the exercises in response to user feedback.

[0710] For example, if a user plans to train several times a week, and their daily emotions are unstable, relaxation-focused exercises will be suggested. Conversely, when they are highly motivated, more challenging exercises will be incorporated. This dynamic adjustment ensures that users always receive an exercise plan that is optimal for their current state.

[0711] As an example of an input prompt for the generating AI model, one could ask the system a question in the form of, "I'm a 30-year-old male aiming to lose weight. I've been feeling unmotivated lately. What kind of exercise program would be suitable for me?" This system provides a customized exercise experience for each user, enabling support towards long-term health goals.

[0712] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0713] Step 1:

[0714] The user enters physical characteristics information such as height, weight, age, health status, and exercise goals into a dedicated application on the device. The entered data is formatted and securely transmitted to the server using encryption. In this step, the input is physical characteristics information, and the output is formatted data ready to be sent to the server.

[0715] Step 2:

[0716] The server analyzes the received physical characteristics information. First, it stores it in a database and uses it as basic data for processing by the AI ​​model. The generative AI model used here generates individual exercise plans by referring to past training data and similar user data. The input for this step is the user's physical characteristics information data, and the output is the generated exercise plan.

[0717] Step 3:

[0718] The device visually displays the exercise plan sent from the server using a dedicated app. The user reviews the displayed plan and prepares to execute it. The input for this step is the generated exercise plan, and the output is the exercise plan presented to the user.

[0719] Step 4:

[0720] The device begins measuring the user's emotional state using its built-in camera and microphone. The emotion engine measures emotions in real time through facial expression analysis and voice tone analysis, and sends this data to the server. The input for this step is the user's facial expressions and voice data, and the output is emotional state data.

[0721] Step 5:

[0722] The server analyzes the received emotional state data and dynamically adjusts the exercise plan. For example, if the server determines that the user is tired, it automatically reduces the intensity of the exercise and incorporates exercises that promote relaxation. The input for this step is emotional state data, and the output is the adjusted exercise plan.

[0723] Step 6:

[0724] The terminal receives the adjusted exercise plan from the server and presents it to the user again. The user reviews the updated plan and performs the exercise according to the instructions. The input for this step is the adjusted exercise plan, and the output is the new exercise plan presented to the user.

[0725] Step 7:

[0726] After the user completes their workout, the device collects training progress and new emotional data again and sends it to the server. The server stores this information and uses it to generate the next workout plan. The input for this step is the data after the workout has been completed, and the output is the completed data sent to the server.

[0727] (Application Example 2)

[0728] 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".

[0729] Even when individual exercise training programs are created based on a user's physical information, there is a problem in that they cannot dynamically respond to the user's emotional state, making it difficult to perform optimal exercise. Furthermore, there is a need to accurately reflect progress and emotional changes and provide flexible training that matches the user's goals.

[0730] 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.

[0731] In this invention, the server includes means for receiving the user's physical information and emotional data, means for generating an individualized exercise training program based on the received physical information and emotional data, and means for recording the user's progress and emotional changes, and visualizing an ideal health state based on goals. This enables the provision of an optimal exercise program tailored to the user's emotional state, allowing for efficient health management.

[0732] "Physical information" refers to information including the user's physical data, health status, and exercise history, and is the basis for the exercise training program.

[0733] "Emotional data" refers to data that shows the user's psychological state and emotional changes, and is used to adjust the exercise program.

[0734] An "exercise training program" is a program that provides an individualized exercise schedule and exercise content, generated based on the user's physical information and emotional data.

[0735] "Progress" refers to data showing the implementation status and results of users' exercise plans, and is used to improve future training plans.

[0736] "Artificial intelligence" refers to computational models and algorithms used to analyze diverse information and generate exercise training programs tailored to the user.

[0737] "Notification" refers to a means of communicating information to encourage users to implement an exercise program, including the timing and content of the notification.

[0738] In embodiments of this invention, a system is formed in which communication takes place between the user's terminal and a server, and an individualized exercise training program is provided. The terminal has the function of collecting the user's physical information and emotional data and transmitting it to the server. A smartphone or wearable device is used for this information collection, and data analysis is performed through a camera and microphone.

[0739] The server uses an AI model to generate personalized exercise training programs based on received physical and emotional data. This AI model is built using Python and Flask, and utilizes libraries such as TensorFlow and OpenCV to process diverse information. The generated program is sent to the user's device in real time and presented visually.

[0740] Furthermore, the server records the user's progress and emotional changes, accumulating and analyzing data to inform future training plans. Therefore, continuous data collection and analysis are crucial elements.

[0741] For example, if a user's emotional data detects "fatigue" when they are about to start exercising, the system will suggest a stretching program to promote relaxation. Conversely, if an emotion such as "energetic" is detected, the system can present a more challenging exercise.

[0742] An example of a prompt to input into the generating AI model is: "Based on emotional data and physical information, recommend the optimal training package for the user. The emotional state is reported as 'fatigued,' and the progress is reported as 'on track.'"

[0743] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0744] Step 1:

[0745] The device collects the user's physical and emotional data. The user's smartphone or wearable device uses a camera to collect facial data and a microphone to analyze voice tone. This allows the system to obtain physical and emotional data as input.

[0746] Step 2:

[0747] The device transmits collected physical and emotional data to the server. The data is encrypted during transmission to ensure security. The server receives this data and uses it in the next processing step.

[0748] Step 3:

[0749] The server uses an AI model to analyze the received information. The input here is the data received in step 2. The server uses TensorFlow to process the data with an AI model and generates an optimal exercise training program for the user's physical condition and emotions.

[0750] Step 4:

[0751] The server sends the generated exercise training program to the terminal. The output includes an individualized exercise program and recommendations for exercises tailored to the user. The terminal receives this, presents it visually to the user, and guides them through the next exercise step.

[0752] Step 5:

[0753] When a user performs an exercise, the device records their progress and emotional changes again. This information serves as input data for optimizing future exercise programs. The recorded data is sent back to the server in the next step.

[0754] Step 6:

[0755] The server analyzes progress and emotional data submitted by users and makes further adjustments to provide new training plans. This results in the output of a refined program designed to support users in achieving their long-term exercise goals.

[0756] 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.

[0757] 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.

[0758] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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."

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0777] The following is further disclosed regarding the embodiments described above.

[0778] (Claim 1)

[0779] A means of receiving the user's physical information,

[0780] A means for generating an individualized exercise training program based on received physical information,

[0781] A means of presenting the generated exercise training program to the user,

[0782] A means of recording the user's progress and visualizing and presenting their ideal future body shape,

[0783] A system that includes this.

[0784] (Claim 2)

[0785] The system according to claim 1, which uses artificial intelligence to simultaneously process diverse data in order to generate an exercise training program based on received physical information.

[0786] (Claim 3)

[0787] The system according to claim 1, comprising means for notifying users and promoting the performance of exercise.

[0788] "Example 1"

[0789] (Claim 1)

[0790] Means for obtaining information about the user's body,

[0791] A means for generating an individualized exercise training plan using artificial intelligence based on acquired physical information,

[0792] A means of visually displaying the generated exercise training plan to the user,

[0793] A means for recording the user's activity progress and displaying an ideal future physical state using past progress data,

[0794] A system that includes this.

[0795] (Claim 2)

[0796] The system according to claim 1, which utilizes intelligent processing to simultaneously process diverse information in order to generate a motion plan based on received information.

[0797] (Claim 3)

[0798] The system according to claim 1, comprising a function to notify the user and encourage them to perform exercise.

[0799] "Application Example 1"

[0800] (Claim 1)

[0801] A means of receiving the user's physical information,

[0802] A means for generating an individualized exercise training program based on received physical information,

[0803] A means of presenting the generated exercise training program to the user,

[0804] A means of recording the user's progress and visualizing and presenting their ideal future body shape,

[0805] A means of providing users with the correct form of movement in real time using a visual display device,

[0806] A system that includes this.

[0807] (Claim 2)

[0808] The system according to claim 1, which uses artificial intelligence to simultaneously process diverse data in order to generate an exercise training program based on received physical information.

[0809] (Claim 3)

[0810] The system according to claim 1, comprising means for notifying users and promoting the performance of exercise.

[0811] "Example 2 of combining an emotion engine"

[0812] (Claim 1)

[0813] Means for acquiring information on the user's physical characteristics,

[0814] A means for generating an individualized exercise plan based on acquired physical characteristic information,

[0815] A means of displaying the generated exercise plan to the user,

[0816] A means of analyzing the emotional state of users,

[0817] A means of dynamically adjusting the motor plan based on emotional state,

[0818] A means of notifying users of the adjusted exercise plan,

[0819] A means of collecting information on users' exercise activity and emotional state and transmitting it to the service provider,

[0820] Based on the collected information, a means of proposing a new exercise plan aligned with long-term health goals,

[0821] A system that includes this.

[0822] (Claim 2)

[0823] The system according to claim 1, which uses a computer processing unit that simultaneously processes various information in order to generate an exercise plan based on acquired physical characteristic information.

[0824] (Claim 3)

[0825] The system according to claim 1, comprising means for communicating with the user and promoting the continuation of exercise.

[0826] "Application example 2 when combining with an emotional engine"

[0827] (Claim 1)

[0828] A means of receiving the user's physical information and emotional data,

[0829] A means for generating an individualized exercise training program based on received physical information and emotional data,

[0830] A means of presenting the generated exercise training program to the user and selecting the optimal training content,

[0831] A means of recording the user's progress and emotional changes, and visualizing and presenting an ideal health state based on future goals,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, which uses artificial intelligence to simultaneously process diverse information in order to generate an exercise training program based on received physical information and emotional data.

[0835] (Claim 3)

[0836] The system according to claim 1, comprising means for notifying the user and promoting the execution of optimal exercise in real time. [Explanation of symbols]

[0837] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving the user's physical information, A means for generating an individualized exercise training program based on received physical information, A means of presenting the generated exercise training program to the user, A means of recording the user's progress and visualizing and presenting their ideal future body shape, A system that includes this.

2. The system according to claim 1, which uses artificial intelligence to simultaneously process diverse data in order to generate an exercise training program based on received physical information.

3. The system according to claim 1, comprising means for notifying users and promoting the performance of exercise.

Images