System

Abstract

A system is provided.SOLUTION: A system includes means for collecting registration information from a user, means for generating a personalized exercise plan based on the collected information, means for providing the generated exercise plan to the user, means for collecting and analyzing exercise data of the user in real-time, means for providing real-time feedback based on the collected exercise data, means for providing exercise challenges and rewards to the user, means for collecting nutritional data of the user and generating a personalized diet plan, and means for periodically analyzing the exercise data and adjusting the exercise plan.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In modern society, many people are becoming less active due to the increase in telecommuting and lifestyle changes. Furthermore, maintaining motivation to exercise regularly and creating training plans tailored to individual fitness needs are challenging. Traditional training programs are generally uniform and lack personalization tailored to individual abilities and goals. Furthermore, the lack of real-time feedback and social interaction makes it difficult to develop effective and sustainable exercise habits. [Means for solving the problem]

[0005] The present invention provides a system including means for collecting registration information from a user, means for generating a personalized exercise plan based on the collected information, means for providing the generated exercise plan to the user, means for collecting and analyzing the user's exercise data in real time, means for providing real-time feedback based on the collected exercise data, means for providing the user with exercise challenges and rewards, means for collecting the user's nutritional data and generating a personalized meal plan, and means for periodically analyzing the exercise data and adjusting the exercise plan, thereby making it easier for users to continue training tailored to their individual fitness needs and supporting effective and sustainable health management.

[0006] "User" means an individual who uses the System and receives the training plan and feedback.

[0007] "Registration Information" refers to your basic personal information and initial fitness data, including, but not limited to, your name, gender, age, height, weight, fitness level, and goals.

[0008] A "personalized exercise plan" is a personalized training program generated by AI based on the user's registration information and fitness needs.

[0009] "Exercise data" refers to data generated by a user during training, specifically information related to physical activity such as type of movement, number of repetitions, number of sets, time, and heart rate.

[0010] "Means of collecting and analyzing in real time" refers to devices and programs that use sensors and motion capture technology to instantly acquire users' movement data and then use AI to analyze it.

[0011] "Real-time feedback" refers to information such as advice, points to note, and correction instructions that are immediately provided to users during training based on the exercise data they have acquired.

[0012] "Means for providing challenges and rewards" refers to devices or programs that provide gamified training elements to increase user motivation and issue rewards such as points or badges for achieving exercise goals.

[0013] A "meal plan" is a plan that provides balanced meal suggestions and menu recommendations based on a user's nutritional data and fitness goals.

[0014] The "means for adjusting the exercise plan" refers to a device or program that analyzes the exercise data collected periodically and updates or modifies the exercise plan according to the user's progress. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10]1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a 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.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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.

[0029] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The system of the present invention is designed to help users improve their fitness, and specifically provides a personalized exercise plan based on the user's registered information, and provides feedback and nutritional advice in real time. Specific embodiments for implementing the present invention and the process flow thereof are described below.

[0037] User registration and initial evaluation

[0038] First, users install the application and create an account by entering initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is then sent to the server via their device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[0039] Providing and implementing exercise plans

[0040] The device displays the generated exercise plan to the user and encourages them to exercise. Once the user begins exercising, the device's camera and accelerometer are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, duration, and angle. The server analyzes the collected exercise data and provides accurate feedback to the device. For example, it can provide real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[0041] Gamification and points system

[0042] The server provides specific challenges and rewards based on the user's exercise data. For example, a specific number of points may be awarded for exercising for seven consecutive days. This allows users to maintain a consistent exercise habit while having fun. The device displays the user's current challenge progress and the points earned.

[0043] Nutrition advice and meal plans

[0044] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[0045] Monitor progress and adjust plans

[0046] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[0047] Specific examples

[0048] For example, if a 40-year-old male user registers an account with the goal of losing weight, the system operates as follows:

[0049] 1. User: Enter your name, gender, age, height, weight, current fitness level (beginner) and goal (weight loss).

[0050] 2. Server: Based on this information, an appropriate exercise plan (e.g., a combination of aerobic exercise and strength training for 30 minutes, four times a week) is generated and sent to the device.

[0051] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[0052] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[0053] 5. Server: Analyzes this data and sends real-time feedback to the device (e.g., "Bend your knees a little more").

[0054] 6. Device: Provides feedback to the user and encourages proper exercise form.

[0055] 7. Server: Awards points to users when they complete exercises and notifies them when specific challenges are completed.

[0056] 8. Terminal: Displays points and challenge completion status to users.

[0057] 9. User: Enters daily meal information into the terminal, which then sends it to the server.

[0058] 10. Server: Generates nutritionally balanced meal plans and sends them to the device.

[0059] 11. Terminal: Display the meal plan to the user.

[0060] 12. Server: Periodically analyzes exercise data and generates progress reports.

[0061] 13. Device: Shows the user progress and suggests new exercise plans.

[0062] In this way, users can enjoy sustained exercise while effectively progressing towards their fitness goals.

[0063] The processing flow will be explained below.

[0064] Specific explanation of program processing

[0065] User registration and initial evaluation

[0066] Step 1:

[0067] The user installs and launches the JoyFitHub application.

[0068] Step 2:

[0069] On the account registration screen, users enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals.

[0070] Step 3:

[0071] The terminal transmits the information entered by the user to the server.

[0072] Step 4:

[0073] The server stores the received information in a database.

[0074] Step 5:

[0075] The server uses an AI engine to generate an optimal exercise plan for the user based on the stored information.

[0076] Providing and implementing exercise plans

[0077] Step 1:

[0078] The terminal displays the generated exercise plan to the user and prompts the user to confirm it.

[0079] Step 2:

[0080] The user checks the displayed exercise plan and presses the "Start Exercise" button.

[0081] Step 3:

[0082] The device prepares the device to start the exercise and sets the timer and other necessary settings.

[0083] Step 4:

[0084] The user performs an exercise (e.g., squats or push-ups).

[0085] Step 5:

[0086] The device uses a camera and accelerometer to collect the user's movement data (e.g., type of movement, number of times, duration, angle, etc.) in real time.

[0087] Step 6:

[0088] The terminal transmits the collected exercise data to a server.

[0089] Step 7:

[0090] The server analyzes the received exercise data and uses an AI engine to generate real-time feedback (e.g., proper form and areas for improvement).

[0091] Step 8:

[0092] The server transmits the generated feedback to the terminal.

[0093] Step 9:

[0094] The device displays feedback to the user, providing immediate audio and visual feedback (e.g., "Bend your knees more").

[0095] Gamification and points system

[0096] Step 1:

[0097] The server generates challenges and rewards based on the user's exercise data (e.g., rewards for exercising for seven consecutive days).

[0098] Step 2:

[0099] The terminal displays the generated challenge content to the user.

[0100] Step 3:

[0101] The user participates in the presented challenge and continues exercising.

[0102] Step 4:

[0103] The server monitors whether the challenge is met and adds points if it is met.

[0104] Step 5:

[0105] The terminal displays the user's earned points and achievement status.

[0106] Nutrition advice and meal plans

[0107] Step 1:

[0108] Users enter their daily dietary preferences and food restrictions (e.g., vegetarian, allergy information, etc.) within the application.

[0109] Step 2:

[0110] The terminal transmits the input information to the server.

[0111] Step 3:

[0112] The server stores the received nutritional data and uses an AI engine to generate a balanced meal plan.

[0113] Step 4:

[0114] The device then displays the generated meal plan to the user, including specific recipes and ingredient lists.

[0115] Monitor progress and adjust plans

[0116] Step 1:

[0117] The terminal periodically transmits the exercise data to the server.

[0118] Step 2:

[0119] The server stores the received data in a database and analyzes the user's progress.

[0120] Step 3:

[0121] The server uses an AI engine to generate progress reports (e.g., how much strength has improved, weight fluctuations, etc.).

[0122] Step 4:

[0123] The terminal displays progress reports to the user in the form of graphs and text.

[0124] Step 5:

[0125] The server adjusts exercise and meal plans based on the analyzed progress data.

[0126] Step 6:

[0127] The device will notify the user of the updated plan and prompt them to confirm.

[0128] In this way, the system provides a personalized exercise plan based on the user's registration information, and provides real-time feedback and nutritional advice to support an effective and sustainable fitness program.

[0129] Example 1

[0130] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0131] While systems exist that provide effective fitness planning and nutritional management, helping users achieve their fitness goals while enjoying consistent exercise, only a limited number offer real-time feedback and personalized advice. Furthermore, they lack features that keep users motivated through gamification or point systems. Therefore, a system that supports users in continuing to exercise is needed.

[0132] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0133] In this invention, the server includes a means for using the device's sensors to collect the user's exercise data in real time, a means for linking the server and the device to provide real-time feedback based on the collected exercise data, and a means for including gamification elements to provide the user with exercise challenges and rewards. This allows users to consistently and effectively implement fitness plans and exercise safely by receiving real-time feedback and advice. Furthermore, the introduction of gamification elements and a point system can increase users' motivation, helping them develop a consistent exercise habit.

[0134] "User" refers to an individual who uses the System and who uses the Application to improve fitness.

[0135] "Registration Information" means personal information provided by a User to the System, including initial data such as name, gender, age, height, weight, fitness level, and fitness goals.

[0136] "Exercise plan" refers to an exercise or training plan that is personalized and generated based on the user's registration information, and includes specific exercises, frequency, number of times, intensity, etc.

[0137] "Exercise Data" means data collected through the device's sensors and camera when a user exercises, including metrics such as type of exercise, number of times, time, and angle.

[0138] "Real-time feedback" refers to advice and instructions provided instantly based on the analysis of exercise data, with the aim of improving exercise form or adjusting the number of repetitions, etc.

[0139] "Device" refers to an electronic device carried or used by a user, including hardware such as a smartphone, tablet, or wearable device.

[0140] "Server" refers to a computer system that centrally manages the system and processes data, and stores and analyzes data sent from users, generates exercise plans, etc.

[0141] "Gamification elements" refers to challenges and reward systems introduced to increase users' motivation to exercise, including specific achievement goals and point systems.

[0142] "Nutrition Data" means the information provided by you regarding your daily diet and food preferences and restrictions that is used to generate a meal plan.

[0143] "Meal Plan" means a nutritionally balanced meal plan generated based on a User's nutritional data, including specific recipes and ingredient lists.

[0144] "Means of collaboration" refers to the protocols and infrastructure that allow the server and terminal to communicate and send and receive data, and is a mechanism for maintaining data consistency and immediacy.

[0145] MODE FOR CARRYING OUT THE INVENTION

[0146] The present invention relates to a system for supporting users in improving their fitness. Specifically, the system provides a personalized exercise plan based on the user's registered information, and provides feedback and nutritional advice in real time. Specific embodiments for implementing the present invention are described in detail below.

[0147] Hardware and software for user registration and initial evaluation

[0148] Users must first install a dedicated application on their mobile device. They launch the application and enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals on the account creation screen. This information is sent from the user's mobile device to the server. The server stores the received data in a database and uses an AI engine (e.g., Tensorflow® or PyTorch) to generate a personalized exercise plan.

[0149] Hardware and software for providing and executing motor planning

[0150] The device provides the generated exercise plan to the user. The exercise plan includes specific exercises, frequency, number of repetitions, and intensity. When the user starts exercising, exercise data is collected in real time using the device's camera and accelerometer (e.g., IMU sensor). The server analyzes this collected data and provides real-time feedback. The feedback may include whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[0151] Gamification and points systems: hardware and software

[0152] The server provides specific challenges and rewards based on exercise data. For example, a challenge such as "exercise for seven consecutive days" can be set, and points and rewards will be awarded if the challenge is achieved. The device displays the current challenge progress and the points earned to the user. This function makes it easier for users to continue exercising.

[0153] Hardware and software in nutrition advice and meal planning

[0154] The user enters their daily dietary habits and food preferences and restrictions into the application. The device then sends this information to the server, which then generates a meal plan that takes nutritional balance into account. Specifically, the server references a nutrition database (e.g., the USDA Nutrition Database) and creates appropriate recipes and ingredient lists. The device then displays the generated meal plan to the user to support daily nutritional intake.

[0155] Hardware and software for monitoring progress and adjusting plans

[0156] The server continuously collects exercise data and periodically analyzes it. Based on the analysis results, it adjusts the exercise plan as needed and generates a new exercise plan. This new plan is then notified to the user via their device, allowing them to effectively progress toward their fitness goals.

[0157] Example: Weight loss in a 40-year-old male user

[0158] For example, if a 40-year-old male user registers an account with the goal of losing weight, the system operates as follows:

[0159] 1. User: Enter your name, gender, age, height, weight, current fitness level (beginner), and goal (weight loss).

[0160] 2. Server: Based on the user's information, it generates an exercise plan (e.g., a combination of aerobic exercise and strength training for 30 minutes four times a week) and sends it to the device.

[0161] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[0162] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[0163] 5. Server: Analyzes this data and sends real-time feedback to the device (e.g., "Bend your knees a little more").

[0164] 6. Device: Provides feedback to the user and encourages proper exercise form.

[0165] 7. Server: Awards points to users when they complete exercises and notifies them when a specific challenge has been completed.

[0166] 8. Terminal: Displays points and challenge completion status to users.

[0167] 9. User: Enters daily meal information into the terminal, which then sends it to the server.

[0168] 10. Server: Generates nutritionally balanced meal plans and sends them to the device.

[0169] 11. Terminal: Display the meal plan to the user.

[0170] 12. Server: Periodically analyzes exercise data and generates progress reports.

[0171] 13. Device: Shows the user progress and suggests new exercise plans.

[0172] Examples of explicit prompts that have been given so far include:

[0173] "A 40-year-old male user signed up for an account with the goal of losing weight. He is a beginner and wants a workout plan that includes 30 minutes of cardio and strength training four times a week. How does the system work and what kind of workout plan does it provide?"

[0174] The system of the present invention allows users to effectively progress towards their fitness goals while enjoying sustained exercise.

[0175] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0176] Step 1:

[0177] First, users install the fitness support application on their mobile device, which prepares the environment for using the system.

[0178] Enter: Install application

[0179] Output: App installation complete

[0180] Step 2:

[0181] On the account creation screen, users enter initial information such as name, gender, age, height, weight, fitness level, and fitness goals. This information is entered through a form on the device.

[0182] Input: Name, Gender, Age, Height, Weight, Fitness Level, Fitness Goal

[0183] Output: Initial information entered

[0184] Step 3:

[0185] The terminal sends the input information to the server as an HTTP request.

[0186] Input: Initial information

[0187] Output: Data sent to server completed

[0188] Step 4:

[0189] The server stores the received data in a database and uses an AI engine (e.g., TensorFlow or PyTorch) to generate a personalized exercise plan. This process involves calculating the appropriate type, frequency, number of repetitions, and intensity of exercise based on the registered information.

[0190] Input: Initial information

[0191] Data processing: Data analysis using an AI engine

[0192] Output: personalized exercise plan

[0193] Step 5:

[0194] The device displays the generated exercise plan to the user, with details of each exercise and instructions for execution available within the app.

[0195] Input: personalized exercise plans

[0196] Output: Display of exercise plan

[0197] Step 6:

[0198] When a user starts exercising, exercise data is collected in real time using the device's camera and accelerometer (e.g., IMU sensor).

[0199] Input: User starts exercising

[0200] Output: Collected exercise data

[0201] Step 7:

[0202] The server analyzes the exercise data and calculates metrics such as type of exercise, number of repetitions, duration, angle, etc. The analysis is performed using a specific algorithm (e.g., motion analysis algorithm).

[0203] Input: Exercise data

[0204] Data processing: Analysis of movement data

[0205] Output: Analysis results

[0206] Step 8:

[0207] The server generates real-time feedback based on the analysis results and sends it to the device, which displays this feedback to the user and encourages them to exercise in the correct manner.

[0208] Input: Analysis results

[0209] Output: Generating and displaying feedback

[0210] Step 9:

[0211] The server provides specific challenges and rewards based on the exercise data. For example, a challenge such as "exercise for seven consecutive days" is set, and the achievement status is recorded on the server.

[0212] Input: Parsed movement data

[0213] Output: Challenge settings and records

[0214] Step 10:

[0215] The device will display the current challenge progress and points earned to the user, allowing the user to check their progress.

[0216] Input: Challenge progress

[0217] Output: Show challenge progress

[0218] Step 11:

[0219] Users input their daily dietary habits and food preferences and restrictions into the application.

[0220] Input: Meal information

[0221] Output: Input meal information

[0222] Step 12:

[0223] The terminal transmits the input meal information to the server.

[0224] Input: Meal information

[0225] Output: Data sent to server completed

[0226] Step 13:

[0227] The server generates a nutritionally balanced meal plan based on the dietary information, and creates recipes and ingredient lists tailored to the user, referencing a specific nutrition database (e.g., the USDA Nutrition Database).

[0228] Input: Meal information

[0229] Data processing: Analysis of nutritional information

[0230] Output: personalized meal plan

[0231] Step 14:

[0232] The terminal displays the generated meal plan to the user.

[0233] Enter: personalized meal plans.

[0234] Output: Display of meal plan

[0235] Step 15:

[0236] The server periodically analyzes the collected exercise data and monitors progress, adjusting the exercise plan as needed and generating a new one.

[0237] Input: Collected and analyzed movement data

[0238] Data processing: Progress analysis

[0239] Output: Coordinated movement planning

[0240] Step 16:

[0241] The device notifies the user of the newly generated exercise plan and prompts them to take action for the next step.

[0242] Input: Coordinated movement plan

[0243] Output: Exercise plan notification

[0244] (Application example 1)

[0245] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0246] Currently, there are systems that allow users to create individual exercise plans and stay fit, but there are still a lack of systems that provide comprehensive support, including real-time feedback, data collection during exercise, nutritional advice, progress management, and communication with other users in fitness facilities. Furthermore, systems that provide gamification elements to increase exercise motivation or real-time feedback using dedicated head-mounted displays or smart glasses are also uncommon.

[0247] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0248] In this invention, the server includes means for collecting registration information from users, means for generating a personalized exercise plan based on the collected information, means for providing the generated exercise plan to users, means for collecting and analyzing users' exercise data in real time, means for providing real-time feedback based on the collected exercise data, means for providing exercise challenges and rewards to users, means for collecting users' nutritional data and generating a personalized meal plan, means for periodically analyzing the exercise data and adjusting the exercise plan, means for using sensors to collect data during exercise, means for using head-mounted displays or smart glasses to display users' feedback in real time, and means for providing users with a function for communicating with other users within the fitness facility. This allows users to enjoy continuous fitness activities, receive real-time feedback, and effectively achieve their goals in accordance with the personalized exercise and nutrition plans. Furthermore, the interaction and competitive spirit can enhance a sense of community and motivation within the fitness facility.

[0249] "User" means any person who uses the Fitness System.

[0250] "Registration Information" means information entered by a User when accessing the System for the first time, including, but not limited to, name, gender, age, height, weight, fitness level, and fitness goals.

[0251] An "exercise plan" is a personalized exercise specification generated based on a user's registration information, including specific exercises, frequency, number of repetitions, intensity, etc.

[0252] "Exercise data" refers to information collected when a user exercises, and includes the type of exercise, number of times, time, angle, etc.

[0253] "Real-time feedback" refers to feedback provided instantly based on collected athletic data.

[0254] "Nutrition Data" refers to information entered by the user regarding their daily diet and food preferences and restrictions.

[0255] A "meal plan" is a personalized meal specification generated based on nutritional data, including specific recipes and ingredient lists.

[0256] "Sensor" refers to a hardware device used to collect real-time data during a user's exercise.

[0257] A "head-mounted display" is a display device worn by a user and used to provide visual information.

[0258] "Smart glasses" are eyeglass-type devices worn by users and used to provide visual information.

[0259] A "fitness facility" is a dedicated location for users to exercise, such as a gym or sports facility.

[0260] "Communication Features" means features provided within a fitness facility that enable users to exchange information and interact with other users.

[0261] The system of the present invention is designed to help users improve their fitness by allowing them to follow a personalized exercise plan, receive real-time feedback, and provide comprehensive support including nutritional advice, progress monitoring, and communication with other users within the fitness facility.

[0262] User registration and initial evaluation

[0263] First, users install the application using their smartphone or head-mounted display, and when creating an account, they enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is sent to the server via the device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[0264] Providing and implementing exercise plans

[0265] The device displays the generated exercise plan to the user and encourages them to execute the exercise. Once the user starts exercising, the device's camera and sensors (such as smart glasses or a head-mounted display) are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, duration, and angle. The server analyzes the collected exercise data and provides accurate feedback. For example, it provides real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[0266] Nutrition advice and meal plans

[0267] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[0268] Monitor progress and adjust plans

[0269] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[0270] Gamification and points system

[0271] The server provides specific challenges and rewards based on the user's exercise data. For example, points are awarded for exercising for seven consecutive days. This allows users to maintain a sustainable exercise habit while having fun. The device displays the user's progress in the current challenge and the points earned.

[0272] Communication features within fitness facilities

[0273] It also provides a function that allows users to communicate with other users in the fitness facility while exercising, allowing them to cooperate and compete towards common goals, increasing motivation for fitness activities.

[0274] Prompt Sentence Examples

[0275] A user's profile includes the following information: name, age, gender, height, weight, fitness level, and fitness goals. Based on this information, generate a personalized exercise plan for the user. For example, if a 40-year-old male wants to lose weight, suggest an appropriate exercise plan.

[0276] This system allows users to enjoy continuous fitness activities, receive real-time feedback, and effectively achieve their goals through personalized exercise and nutrition plans. Furthermore, the interaction and competitive spirit with other users within the fitness facility enhances a sense of community and motivation.

[0277] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0278] Step 1:

[0279] A user installs the application using a smartphone or head-mounted display and creates an account. Input data, such as name, gender, age, height, weight, fitness level, and fitness goals, is entered into the device. The device then sends this input data to the server. The server stores the received data in a database and uses an AI engine to generate an exercise plan tailored to the user.

[0280] Step 2:

[0281] The exercise plan generated by the server includes specific exercises, frequency, number of repetitions, intensity, etc. This exercise plan is sent from the server to the device, which displays it to the user. The user then begins exercising based on the displayed exercise plan.

[0282] Step 3:

[0283] The device uses the smartphone camera, smart glasses, and head-mounted display sensors to collect the user's exercise data (type of exercise, number of times, duration, angle, etc.) in real time. This exercise data is then sent from the device to a server.

[0284] Step 4:

[0285] The server uses an AI model to analyze the received exercise data and check whether the exercise is being performed with the correct form and whether the number of repetitions is sufficient. The analysis results are sent to the device in real time as feedback. The device displays this feedback to the user, encouraging them to adjust their exercise form and number of repetitions appropriately.

[0286] Step 5:

[0287] The user inputs the details of their daily meals into the device and sends the information to the server. The server generates a nutritionally balanced meal plan based on the received nutritional data. The generated meal plan (specific recipes, ingredient lists, etc.) is sent from the server to the device, which displays it to support the user's daily eating habits.

[0288] Step 6:

[0289] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains or weight loss and adjusts the exercise plan as needed. The server notifies the device of the new exercise plan, which is then displayed to the user.

[0290] Step 7:

[0291] The server provides specific challenges and rewards based on the user's exercise data. For example, points are awarded for exercising for seven consecutive days. The device displays the user's current challenge progress and earned points, further motivating them to exercise.

[0292] Step 8:

[0293] The devices also provide a function for users to communicate with other users within the fitness facility, for example, allowing users to cooperate or compete with other users while exercising, further increasing motivation and a sense of community.

[0294] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0295] The system of the present invention supports users in improving their fitness, and in particular, by incorporating an emotion engine, it takes into account the user's emotional state and provides more effective exercise planning and feedback. Specific embodiments for implementing the present invention and their processing flow are described below.

[0296] User registration and initial evaluation

[0297] First, users install the application and create an account by entering initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is then sent to the server via their device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[0298] Providing and implementing exercise plans

[0299] The device displays the generated exercise plan to the user and encourages them to exercise. Once the user begins exercising, the device's camera and sensors are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, time, and angle. The server analyzes the collected exercise data and provides accurate feedback to the device. For example, it provides real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[0300] Gamification and points system

[0301] The server provides specific challenges and rewards based on the user's exercise data. For example, a specific number of points may be awarded for exercising for seven consecutive days. This allows users to maintain a consistent exercise habit while having fun. The device displays the user's current challenge progress and the points earned.

[0302] Nutrition advice and meal plans

[0303] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[0304] Monitor progress and adjust plans

[0305] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[0306] Emotion engine integration

[0307] The device uses a camera and microphone to collect the user's facial expressions and voice in real time. This data is sent to a server to recognize the user's emotional state (e.g., joy, sadness, surprise, stress, etc.). The server uses an emotion engine to analyze the collected data and identify the user's emotional state. Based on this, the device adjusts the exercise plan and real-time feedback.

[0308] For example, if a user feels fatigued or stressed during exercise, the emotion engine can detect this and suggest reducing the intensity of the exercise. Conversely, if the user is highly motivated, it can suggest a further challenge. In this way, fine-tuned adjustments based on the user's emotional state are possible.

[0309] Specific examples

[0310] For example, if a 30-year-old female user registers an account with the goal of reducing stress, the system will operate as follows.

[0311] 1. User: Enter your name, gender, age, height, weight, current fitness level (intermediate) and goal (stress reduction).

[0312] 2. Server: Based on this information, it generates an appropriate exercise plan (e.g., a combination of yoga and breathing exercises for 40 minutes three times a week) and sends it to the device.

[0313] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[0314] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[0315] 5. Server: Analyzes this data and sends real-time feedback to the device.

[0316] 6. Device: Provides feedback to the user and encourages proper exercise form.

[0317] 7. Terminal: Uses a camera and microphone to collect the user's facial expressions and voice, and sends the emotional data to the server.

[0318] 8. Server: Utilizes the emotion engine to analyze the emotion data and identify the user's emotional state (e.g., increased stress).

[0319] 9. Server: Adjusts exercise plans and suggests lower intensity exercises based on emotional state.

[0320] 10. Device: Displays the adjusted exercise plan to the user and prompts them for the next step.

[0321] In this way, exercise plans and feedback are provided that take into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[0322] The processing flow will be explained below.

[0323] Specific explanation of program processing

[0324] User registration and initial evaluation

[0325] Step 1:

[0326] The user installs and launches the application.

[0327] Step 2:

[0328] On the account registration screen, users enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals.

[0329] Step 3:

[0330] The terminal transmits the information entered by the user to the server.

[0331] Step 4:

[0332] The server stores the received information in a database.

[0333] Step 5:

[0334] The server uses an AI engine to generate an optimal exercise plan for the user based on the stored information.

[0335] Providing and implementing exercise plans

[0336] Step 1:

[0337] The terminal displays the generated exercise plan to the user and prompts the user to confirm it.

[0338] Step 2:

[0339] The user checks the displayed exercise plan and presses the "Start Exercise" button.

[0340] Step 3:

[0341] The device prepares the device to start the exercise and sets the timer and other necessary settings.

[0342] Step 4:

[0343] The user performs an exercise (e.g., squats or push-ups).

[0344] Step 5:

[0345] The device uses a camera and accelerometer to collect the user's movement data (e.g., type of movement, number of times, duration, angle, etc.) in real time.

[0346] Step 6:

[0347] The terminal transmits the collected exercise data to a server.

[0348] Step 7:

[0349] The server analyzes the received exercise data and uses an AI engine to generate real-time feedback (e.g., proper form and areas for improvement).

[0350] Step 8:

[0351] The server transmits the generated feedback to the terminal.

[0352] Step 9:

[0353] The device displays feedback to the user, providing immediate audio and visual feedback (e.g., "Bend your knees more").

[0354] Emotion engine integration

[0355] Step 1:

[0356] The device uses a camera and microphone to collect the user's facial expressions and voice in real time.

[0357] Step 2:

[0358] The terminal transmits the collected emotion data to the server.

[0359] Step 3:

[0360] The server uses an emotion engine to analyze facial and voice data to identify the user's emotional state (e.g., joy, sadness, surprise, stress, etc.).

[0361] Step 4:

[0362] The server adjusts exercise plans and real-time feedback based on emotional state (e.g., reducing exercise intensity if stress is high).

[0363] Step 5:

[0364] The device displays adjusted exercise plans and feedback to the user (e.g., "Try a light exercise today").

[0365] Gamification and points system

[0366] Step 1:

[0367] The server generates challenges and rewards based on the user's exercise data (e.g., rewards for exercising for seven consecutive days).

[0368] Step 2:

[0369] The terminal displays the generated challenge content to the user.

[0370] Step 3:

[0371] The user participates in the presented challenge and continues exercising.

[0372] Step 4:

[0373] The server monitors whether the challenge is met and adds points if it is met.

[0374] Step 5:

[0375] The terminal displays the user's earned points and achievement status.

[0376] Nutrition advice and meal plans

[0377] Step 1:

[0378] Users enter their daily dietary preferences and food restrictions (e.g., vegetarian, allergy information, etc.) within the application.

[0379] Step 2:

[0380] The terminal transmits the input information to the server.

[0381] Step 3:

[0382] The server stores the received nutritional data and uses an AI engine to generate a balanced meal plan.

[0383] Step 4:

[0384] The device then displays the generated meal plan to the user, including specific recipes and ingredient lists.

[0385] Monitor progress and adjust plans

[0386] Step 1:

[0387] The terminal periodically transmits the exercise data to the server.

[0388] Step 2:

[0389] The server stores the received data in a database and analyzes the user's progress.

[0390] Step 3:

[0391] The server uses an AI engine to generate progress reports (e.g., how much strength has improved, weight fluctuations, etc.).

[0392] Step 4:

[0393] The terminal displays progress reports to the user in the form of graphs and text.

[0394] Step 5:

[0395] The server adjusts exercise and meal plans based on the analyzed progress data.

[0396] Step 6:

[0397] The device will notify the user of the updated plan and prompt them to confirm.

[0398] In this way, by integrating an emotion engine, the system provides personalized exercise plans and feedback that take into account the user's emotional state, enabling a sustainable and effective fitness program.

[0399] Example 2

[0400] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0401] Conventional fitness systems have difficulty providing effective fitness programs because they are unable to provide exercise plans that take into account the individual state and emotions of each user. They also face the challenge of not providing sufficient support for users to maintain their motivation or plan their meals.

[0402] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0403] In this invention, the server includes means for collecting registration information from a user, means for generating a personalized exercise plan based on the collected information, means for providing the generated exercise plan to the user, means for collecting and analyzing the user's exercise data in real time, means for providing real-time feedback based on the collected exercise data, means for providing the user with exercise challenges and rewards, means for collecting the user's nutritional data and generating a personalized meal plan, means for periodically analyzing the exercise data and adjusting the exercise plan, means for collecting the user's emotional data and analyzing the emotional state, and means for adjusting the exercise plan and feedback based on the emotional state. This makes it possible to provide a more effective and sustainable fitness program that takes into account the user's individual condition and emotions.

[0404] "Registration Information" refers to the initial data a user provides to the system, such as name, gender, age, height, weight, fitness level, and goals.

[0405] An "exercise plan" is a schedule and content of exercises created based on the user's individual condition and goals.

[0406] "Exercise data" is data collected when a user exercises, and includes the type of exercise, number of times, time, angle, etc.

[0407] "Real-time feedback" refers to immediate advice and instructions given to users while they are exercising.

[0408] A "challenge" is a task or goal set for a user to achieve a specific exercise goal.

[0409] "Rewards" are incentives given to users when they achieve a specific exercise goal or challenge.

[0410] "Nutrition Data" refers to information about the user's daily diet and food preferences and restrictions.

[0411] A "meal plan" is a balanced meal suggestion, recipe, and ingredient list generated based on the user's nutritional data.

[0412] "Analysis" is the process of analyzing information based on collected data.

[0413] "Emotional data" refers to facial and voice data collected by a camera or microphone to indicate a user's emotional state.

[0414] "Emotional state" refers to the psychological state of a user that is identified based on analyzed emotional data.

[0415] "Feedback adjustment" refers to changing the exercise plan and real-time feedback content depending on the user's emotional state.

[0416] The system of the present invention is designed to help users improve their fitness, and in particular, by combining an emotion engine, it takes into account the user's emotional state and provides more effective exercise planning and feedback. Specific embodiments for implementing the present invention and their processing flow are described below.

[0417] User registration and initial evaluation

[0418] First, users install a dedicated application on their smartphone or tablet. When creating an account, they enter initial information into the application, such as their name, gender, age, height, weight, fitness level, and fitness goals. The device then sends this information to a server, which stores the received data in a database. An AI engine is then used to generate a personalized exercise plan based on the stored information, including specific exercises, frequency, number of repetitions, and intensity.

[0419] Providing and implementing exercise plans

[0420] The device displays the generated exercise plan on the application's user interface and prompts the user to perform the exercise. Once the user begins exercising, the device's camera and built-in sensors (accelerometer, gyro sensor, etc.) are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, time, angle, etc. The server analyzes the collected exercise data, determines whether the form is correct and whether the number of repetitions is sufficient, and sends real-time feedback to the device. For example, specific advice such as "Bend your knees a little more" is provided.

[0421] Gamification and points system

[0422] The server provides specific challenges and rewards based on the user's exercise data, such as "exercise for seven consecutive days and receive 100 points." The device displays the user's current challenge progress and earned points within the application to help keep them motivated.

[0423] Nutrition advice and meal plans

[0424] Through the application, users can input their daily dietary needs and food preferences and restrictions. This information is also sent to the server via the device. Based on the received data, the server uses an AI engine to generate a nutritionally balanced meal plan, including specific recipes and ingredient lists. This plan is also provided to the user via the device.

[0425] Monitor progress and adjust plans

[0426] The server periodically analyzes the user's exercise data and monitors their progress. For example, it measures specific results, such as "I lost 2 kg in 4 weeks." Based on the progress, it adjusts the exercise plan and suggests new exercise menus. This is also notified to the user via their device.

[0427] Emotion engine integration

[0428] The device uses a camera and microphone to collect the user's facial expressions and voice in real time. This data is sent to a server and analyzed using an emotion engine (e.g., OpenFace or EmotionAPI). The server identifies the user's emotional state from the analysis results and adjusts the exercise plan and real-time feedback accordingly. For example, if the user feels fatigued or stressed, it suggests reducing the exercise intensity.

[0429] Specific examples

[0430] For example, if a 30-year-old female user registers an account with the goal of reducing stress, the system will operate as follows.

[0431] 1. The user enters their name, gender, age, height, weight, current fitness level (intermediate) and goal (stress reduction).

[0432] 2. The device sends this initial information to the server.

[0433] 3. The server uses this information to generate an appropriate exercise plan (e.g., a combination of yoga and breathing exercises for 40 minutes three times a week) and sends it to the device.

[0434] 4. The device displays the exercise plan to the user and prompts them to start exercising.

[0435] 5. When the user exercises, the device uses the camera and sensors to collect exercise data.

[0436] 6. The server analyzes the collected data and sends real-time feedback to the device.

[0437] 7. The device displays feedback to the user to encourage proper exercise form.

[0438] 8. The device uses a camera and microphone to collect the user's facial expressions and voice, and transmits the emotional data to the server.

[0439] 9. The server uses an emotion engine to analyze the emotion data and identify the user's emotional state (e.g., increased stress).

[0440] 10. The server adjusts your exercise plan based on your emotional state and suggests lower intensity exercises.

[0441] 11. The device displays the adjusted exercise plan to the user and prompts them for next steps.

[0442] In this way, exercise planning and feedback are provided that takes into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[0443] Prompt Sentence Examples

[0444] "A 30-year-old female user has signed up for an account with the goal of reducing stress. Generate an optimal exercise plan for her, along with feedback based on that plan and adjustments that take into account her emotional state. Initial information includes: Name, Gender, Age, Height, Weight, Fitness Level (Intermediate), and Stress Reduction Goal."

[0445] By inputting this prompt into a generative AI model, it is possible to make adjustments that take into account appropriate motor planning, feedback, and emotional state.

[0446] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0447] Step 1: User registration and initial evaluation

[0448] Input: The user enters initial information into the device, such as name, gender, age, height, weight, fitness level, and fitness goals.

[0449] Operation: The device sends the entered registration information to the server's API.

[0450] Output: The server stores the received registration information in a database, and the AI ​​engine generates a personalized exercise plan based on that information. The generated exercise plan is stored in the database.

[0451] Step 2: Provide an exercise plan

[0452] Input: The server retrieves the exercise plan stored in the database.

[0453] Operation: The server sends the exercise plan to the device, which displays the exercise plan on the user interface.

[0454] Output: The user confirms the received exercise plan and prepares to start exercising.

[0455] Step 3: Exercise execution and data collection

[0456] Input: The user begins to exercise.

[0457] How it works: The device uses its built-in camera and sensors to collect the user's exercise data (type, number of times, duration, angle) in real time.

[0458] Output: The collected movement data is sent to the server.

[0459] Step 4: Data analysis and feedback

[0460] Input: The server receives the exercise data received from the device.

[0461] How it works: The server analyzes the exercise data and evaluates the accuracy of form and the number of repetitions completed.

[0462] Output: The server sends real-time feedback to the device based on the evaluation, for example specific instructions such as "bend your knees a bit more."

[0463] Step 5: Challenges and Rewards

[0464] Input: The server evaluates the user's progress based on their exercise data.

[0465] How it works: The server sets a specific challenge (e.g., exercise for seven days in a row) and offers points and rewards based on that.

[0466] Output: This information is sent to the user via their device. The user can check their progress and earned points within the app.

[0467] Step 6: Enter your nutritional data and plan your meals

[0468] Input: Users input their daily dietary preferences and food restrictions through the application.

[0469] How it works: The nutritional data entered is sent via the device to a server, which receives it, analyzes it, and generates a balanced meal plan.

[0470] Output: The resulting meal plan is sent to a device where it is displayed to the user, including specific recipes and ingredient lists.

[0471] Step 7: Monitor progress and adjust plans

[0472] Input: The server periodically collects the user's exercise data.

[0473] How it works: Using the collected data, the server monitors your progress and adjusts your exercise plan as needed.

[0474] Output: The adjusted new movement plan is sent to the device and the user is notified.

[0475] Step 8: Collect and analyze emotion data

[0476] Input: The device uses a camera and microphone to collect the user's facial expressions and voice in real time.

[0477] How it works: Collected emotion data is sent to a server, which analyzes it using an emotion engine to identify emotional states such as stress or fatigue.

[0478] Output: Emotional state analysis is used to adjust motor planning and feedback.

[0479] Step 9: Emotion-Based Feedback Adjustment

[0480] Input: The server uses the analysis results of the emotion data.

[0481] How it works: The server adjusts exercise plans and feedback based on the analysis results. For example, it reduces exercise intensity if fatigue is detected. If high motivation is detected, it suggests challenges.

[0482] Output: The adjusted exercise plan and feedback are sent to the device and notified to the user.

[0483] In this way, a system is realized that utilizes the data obtained at each processing step in the next step and provides the user with an appropriate exercise plan and feedback.

[0484] (Application example 2)

[0485] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0486] Current fitness management systems and applications provide exercise plans based on users' physical data, but do not take into account the user's emotional state, making it difficult to maximize the benefits of exercise or ensure its sustainability. Effective exercise plans based on emotional data are also needed in security services, where it is necessary to quickly identify when employees are feeling stressed and provide appropriate fitness plans.

[0487] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0488] In this invention, the server includes means for collecting registration information from a user, means for generating a personalized exercise plan based on the collected information, and means for providing the generated exercise plan to the user, thereby enabling the exercise plan to be adjusted based on the user's emotional state.

[0489] "User" means an individual or employee who uses the System to improve their fitness.

[0490] "Registration Information" refers to initial information such as a User's name, gender, age, height, weight, fitness level, and fitness goals.

[0491] "Means of collection" refers to technological means such as sensors, cameras, and online forms used to collect registration information, movement data, and emotional data from users.

[0492] An "exercise plan" is a plan that includes specific exercise types, frequency, number of times, intensity, etc., generated based on the user's registered information and emotional state.

[0493] The "means for providing" refers to a terminal or application that notifies the user of the generated exercise plan visually, audibly, or the like.

[0494] "Exercise data" refers to data that records the type, number of times, time, angle, etc. of a user's exercise.

[0495] The "analysis means" refers to algorithms and AI engines that analyze the collected exercise data and evaluate the accuracy and effectiveness of the user's exercise.

[0496] "Real-time feedback" refers to immediate responses provided during exercise, such as suggestions for correcting exercise form or instructions to increase motivation.

[0497] "Means for providing challenges and rewards" refers to a system for providing rewards such as points or badges when users achieve certain athletic achievements.

[0498] "Nutrition Data" refers to information such as the user's dietary habits and food preferences and restrictions.

[0499] A "meal plan" is a plan that includes nutritionally balanced meal plans, specific recipes, and ingredient lists.

[0500] An "emotion recognition engine" is an AI technology that analyzes a user's facial expressions and voice to identify their emotional state.

[0501] "Emotion data" is data that represents the user's emotional state, such as joy, sadness, surprise, or stress.

[0502] The system of the present invention is designed for users who want to improve their fitness, and is implemented by combining a server, a terminal, and a sensor.

[0503] First, the user enters their initial registration information into the terminal through the application, including their name, gender, age, height, weight, fitness level, and fitness goals. The registration information is immediately sent to the server and stored in the database.

[0504] The server uses a generative AI model to generate a personalized exercise plan based on the collected information, including specific exercise types, frequency, number of repetitions, and intensity. The plan is then sent to the device and provided to the user.

[0505] When a user starts exercising, the device's built-in cameras and sensors collect exercise data in real time. This exercise data includes the type of exercise, number of repetitions, time, and angle. The collected data is then sent back to the server and analyzed by an AI engine. The server generates real-time feedback based on the collected exercise data and sends appropriate exercise form and correction suggestions to the device.

[0506] Additionally, the device uses a camera and microphone to capture the user's facial expressions and voice in real time to obtain emotional data. An emotion recognition engine analyzes this data to identify the user's emotional state. For example, if the device determines that the user is feeling stressed, it will suggest reducing the intensity of the exercise. Conversely, if the user is highly motivated, it can suggest further challenges.

[0507] The system also includes a means to adjust exercise plans based on emotional state, maximizing fitness benefits and helping users maintain a consistent exercise routine.

[0508] This system can also be effectively used in security services, for example, to quickly identify situations that cause stress to security guards and provide them with appropriate fitness plans.

[0509] An example prompt is:

[0510] "User: Yamada Taro, Age: 30, Gender: Male, Height: 175cm, Weight: 70kg, Fitness Level: Intermediate, Goal: Stress reduction. Based on this, please generate an appropriate exercise plan. It should be a specific plan including the type, frequency, number of repetitions, and intensity of exercise."

[0511] Implemented in this manner, the system of the present invention provides exercise planning and real-time feedback that takes into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[0512] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0513] Step 1:

[0514] The user enters initial registration information into the application. The entered information includes name, gender, age, height, weight, fitness level, and fitness goal. This is the input, and the device sends it to the server. The entered data is stored on the server and used for subsequent processing.

[0515] Step 2:

[0516] The server uses a generative AI model to generate a personalized exercise plan based on the collected registration information. Specifically, the information stored in the database is passed to the model as input, and an exercise plan is generated as output. This exercise plan includes specific exercise types, frequency, number of repetitions, intensity, etc. The server then sends the generated exercise plan to the device.

[0517] Step 3:

[0518] The terminal displays the exercise plan received from the server to the user. The user starts exercising based on the displayed exercise plan. At this point, the exercise plan is the input and what the terminal displays is the output.

[0519] Step 4:

[0520] When a user exercises, the camera and sensors on the device collect exercise data in real time, including the type of exercise, number of repetitions, time, angle, etc. The collected exercise data is sent as input to the server, which receives it and stores it in a database.

[0521] Step 5:

[0522] The server analyzes the received exercise data using an AI engine. Specifically, it analyzes the input exercise data and evaluates the accuracy and effectiveness of the exercise. The analysis results are the output, and the calculations performed by the AI ​​engine are the data processing. The server generates real-time feedback based on the analysis results and sends it to the device.

[0523] Step 6:

[0524] The device displays the feedback sent from the server to the user, including proper exercise form and suggested corrections. This feedback is the output, and the device displays the specific movement.

[0525] Step 7:

[0526] The device uses a camera and microphone to collect the user's facial expressions and voice in real time, which is the input, and the collected emotional data is sent to the server, which is the output.

[0527] Step 8:

[0528] The server analyzes the collected emotional data using an emotion recognition engine. Specifically, it identifies the user's emotional state based on the input emotional data. The analysis results are the output, and the data processing by the emotion recognition engine is the operation.

[0529] Step 9:

[0530] The server adjusts the exercise plan based on the user's emotional state. For example, if the user feels stressed, it suggests reducing the exercise intensity. The adjusted exercise plan is the output, and the server sends it to the device.

[0531] Step 10:

[0532] The terminal displays the adjusted exercise plan to the user and prompts the user to take the next exercise step. This is the output, and the display on the terminal is the specific action.

[0533] These steps allow for exercise planning and real-time feedback that takes into account the user's emotional state.

[0534] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0535] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0536] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0537] [Second embodiment]

[0538] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0539] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0540] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0541] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0542] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0543] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0544] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0545] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0546] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0547] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0548] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0549] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0550] The system of the present invention is designed to help users improve their fitness, and specifically provides a personalized exercise plan based on the user's registered information, and provides feedback and nutritional advice in real time. Specific embodiments for implementing the present invention and the process flow thereof are described below.

[0551] User registration and initial evaluation

[0552] First, users install the application and create an account by entering initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is then sent to the server via their device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[0553] Providing and implementing exercise plans

[0554] The device displays the generated exercise plan to the user and encourages them to exercise. Once the user begins exercising, the device's camera and accelerometer are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, duration, and angle. The server analyzes the collected exercise data and provides accurate feedback to the device. For example, it can provide real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[0555] Gamification and points system

[0556] The server provides specific challenges and rewards based on the user's exercise data. For example, a specific number of points may be awarded for exercising for seven consecutive days. This allows users to maintain a consistent exercise habit while having fun. The device displays the user's current challenge progress and the points earned.

[0557] Nutrition advice and meal plans

[0558] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[0559] Monitor progress and adjust plans

[0560] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[0561] Specific examples

[0562] For example, if a 40-year-old male user registers an account with the goal of losing weight, the system operates as follows:

[0563] 1. User: Enter your name, gender, age, height, weight, current fitness level (beginner) and goal (weight loss).

[0564] 2. Server: Based on this information, an appropriate exercise plan (e.g., a combination of aerobic exercise and strength training for 30 minutes, four times a week) is generated and sent to the device.

[0565] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[0566] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[0567] 5. Server: Analyzes this data and sends real-time feedback to the device (e.g., "Bend your knees a little more").

[0568] 6. Device: Provides feedback to the user and encourages proper exercise form.

[0569] 7. Server: Awards points to users when they complete exercises and notifies them when specific challenges are completed.

[0570] 8. Terminal: Displays points and challenge completion status to users.

[0571] 9. User: Enters daily meal information into the terminal, which then sends it to the server.

[0572] 10. Server: Generates nutritionally balanced meal plans and sends them to the device.

[0573] 11. Terminal: Display the meal plan to the user.

[0574] 12. Server: Periodically analyzes exercise data and generates progress reports.

[0575] 13. Device: Shows the user progress and suggests new exercise plans.

[0576] In this way, users can enjoy sustained exercise while effectively progressing towards their fitness goals.

[0577] The processing flow will be explained below.

[0578] Specific explanation of program processing

[0579] User registration and initial evaluation

[0580] Step 1:

[0581] The user installs and launches the JoyFitHub application.

[0582] Step 2:

[0583] On the account registration screen, users enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals.

[0584] Step 3:

[0585] The terminal transmits the information entered by the user to the server.

[0586] Step 4:

[0587] The server stores the received information in a database.

[0588] Step 5:

[0589] The server uses an AI engine to generate an optimal exercise plan for the user based on the stored information.

[0590] Providing and implementing exercise plans

[0591] Step 1:

[0592] The terminal displays the generated exercise plan to the user and prompts the user to confirm it.

[0593] Step 2:

[0594] The user checks the displayed exercise plan and presses the "Start Exercise" button.

[0595] Step 3:

[0596] The device prepares the device to start the exercise and sets the timer and other necessary settings.

[0597] Step 4:

[0598] The user performs an exercise (e.g., squats or push-ups).

[0599] Step 5:

[0600] The device uses a camera and accelerometer to collect the user's movement data (e.g., type of movement, number of times, duration, angle, etc.) in real time.

[0601] Step 6:

[0602] The terminal transmits the collected exercise data to a server.

[0603] Step 7:

[0604] The server analyzes the received exercise data and uses an AI engine to generate real-time feedback (e.g., proper form and areas for improvement).

[0605] Step 8:

[0606] The server transmits the generated feedback to the terminal.

[0607] Step 9:

[0608] The device displays feedback to the user, providing immediate audio and visual feedback (e.g., "Bend your knees more").

[0609] Gamification and points system

[0610] Step 1:

[0611] The server generates challenges and rewards based on the user's exercise data (e.g., rewards for exercising for seven consecutive days).

[0612] Step 2:

[0613] The terminal displays the generated challenge content to the user.

[0614] Step 3:

[0615] The user participates in the presented challenge and continues exercising.

[0616] Step 4:

[0617] The server monitors whether the challenge is met and adds points if it is met.

[0618] Step 5:

[0619] The terminal displays the user's earned points and achievement status.

[0620] Nutrition advice and meal plans

[0621] Step 1:

[0622] Users enter their daily dietary preferences and food restrictions (e.g., vegetarian, allergy information, etc.) within the application.

[0623] Step 2:

[0624] The terminal transmits the input information to the server.

[0625] Step 3:

[0626] The server stores the received nutritional data and uses an AI engine to generate a balanced meal plan.

[0627] Step 4:

[0628] The device then displays the generated meal plan to the user, including specific recipes and ingredient lists.

[0629] Monitor progress and adjust plans

[0630] Step 1:

[0631] The terminal periodically transmits the exercise data to the server.

[0632] Step 2:

[0633] The server stores the received data in a database and analyzes the user's progress.

[0634] Step 3:

[0635] The server uses an AI engine to generate progress reports (e.g., how much strength has improved, weight fluctuations, etc.).

[0636] Step 4:

[0637] The terminal displays progress reports to the user in the form of graphs and text.

[0638] Step 5:

[0639] The server adjusts exercise and meal plans based on the analyzed progress data.

[0640] Step 6:

[0641] The device will notify the user of the updated plan and prompt them to confirm.

[0642] In this way, the system provides a personalized exercise plan based on the user's registration information, and provides real-time feedback and nutritional advice to support an effective and sustainable fitness program.

[0643] Example 1

[0644] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0645] While systems exist that provide effective fitness planning and nutritional management, helping users achieve their fitness goals while enjoying consistent exercise, only a limited number offer real-time feedback and personalized advice. Furthermore, they lack features that keep users motivated through gamification or point systems. Therefore, a system that supports users in continuing to exercise is needed.

[0646] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0647] In this invention, the server includes a means for using the device's sensors to collect the user's exercise data in real time, a means for linking the server and the device to provide real-time feedback based on the collected exercise data, and a means for including gamification elements to provide the user with exercise challenges and rewards. This allows users to consistently and effectively implement fitness plans and exercise safely by receiving real-time feedback and advice. Furthermore, the introduction of gamification elements and a point system can increase users' motivation, helping them develop a consistent exercise habit.

[0648] "User" refers to an individual who uses the System and who uses the Application to improve fitness.

[0649] "Registration Information" means personal information provided by a User to the System, including initial data such as name, gender, age, height, weight, fitness level, and fitness goals.

[0650] "Exercise plan" refers to an exercise or training plan that is personalized and generated based on the user's registration information, and includes specific exercises, frequency, number of times, intensity, etc.

[0651] "Exercise Data" means data collected through the device's sensors and camera when a user exercises, including metrics such as type of exercise, number of times, time, and angle.

[0652] "Real-time feedback" refers to advice and instructions provided instantly based on the analysis of exercise data, with the aim of improving exercise form or adjusting the number of repetitions, etc.

[0653] "Device" refers to an electronic device carried or used by a user, including hardware such as a smartphone, tablet, or wearable device.

[0654] "Server" refers to a computer system that centrally manages the system and processes data, and stores and analyzes data sent from users, generates exercise plans, etc.

[0655] "Gamification elements" refers to challenges and reward systems introduced to increase users' motivation to exercise, including specific achievement goals and point systems.

[0656] "Nutrition Data" means the information provided by you regarding your daily diet and food preferences and restrictions that is used to generate a meal plan.

[0657] "Meal Plan" means a nutritionally balanced meal plan generated based on a User's nutritional data, including specific recipes and ingredient lists.

[0658] "Means of collaboration" refers to the protocols and infrastructure that allow the server and terminal to communicate and send and receive data, and is a mechanism for maintaining data consistency and immediacy.

[0659] MODE FOR CARRYING OUT THE INVENTION

[0660] The present invention relates to a system for supporting users in improving their fitness. Specifically, the system provides a personalized exercise plan based on the user's registered information, and provides feedback and nutritional advice in real time. Specific embodiments for implementing the present invention are described in detail below.

[0661] Hardware and software for user registration and initial evaluation

[0662] Users must first install a dedicated application on their mobile device. They launch the application and enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals on the account creation screen. This information is sent from the user's mobile device to a server. The server stores the received data in a database and uses an AI engine (e.g., TensorFlow or PyTorch) to generate a personalized exercise plan.

[0663] Hardware and software for providing and executing motor planning

[0664] The device provides the generated exercise plan to the user. The exercise plan includes specific exercises, frequency, number of repetitions, and intensity. When the user starts exercising, exercise data is collected in real time using the device's camera and accelerometer (e.g., IMU sensor). The server analyzes this collected data and provides real-time feedback. The feedback may include whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[0665] Gamification and points systems: hardware and software

[0666] The server provides specific challenges and rewards based on exercise data. For example, a challenge such as "exercise for seven consecutive days" can be set, and points and rewards will be awarded if the challenge is achieved. The device displays the current challenge progress and the points earned to the user. This function makes it easier for users to continue exercising.

[0667] Hardware and software in nutrition advice and meal planning

[0668] The user enters their daily dietary habits and food preferences and restrictions into the application. The device then sends this information to the server, which then generates a meal plan that takes nutritional balance into account. Specifically, the server references a nutrition database (e.g., the USDA Nutrition Database) and creates appropriate recipes and ingredient lists. The device then displays the generated meal plan to the user to support daily nutritional intake.

[0669] Hardware and software for monitoring progress and adjusting plans

[0670] The server continuously collects exercise data and periodically analyzes it. Based on the analysis results, it adjusts the exercise plan as needed and generates a new exercise plan. This new plan is then notified to the user via their device, allowing them to effectively progress toward their fitness goals.

[0671] Example: Weight loss in a 40-year-old male user

[0672] For example, if a 40-year-old male user registers an account with the goal of losing weight, the system operates as follows:

[0673] 1. User: Enter your name, gender, age, height, weight, current fitness level (beginner), and goal (weight loss).

[0674] 2. Server: Based on the user's information, it generates an exercise plan (e.g., a combination of aerobic exercise and strength training for 30 minutes four times a week) and sends it to the device.

[0675] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[0676] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[0677] 5. Server: Analyzes this data and sends real-time feedback to the device (e.g., "Bend your knees a little more").

[0678] 6. Device: Provides feedback to the user and encourages proper exercise form.

[0679] 7. Server: Awards points to users when they complete exercises and notifies them when a specific challenge has been completed.

[0680] 8. Terminal: Displays points and challenge completion status to users.

[0681] 9. User: Enters daily meal information into the terminal, which then sends it to the server.

[0682] 10. Server: Generates nutritionally balanced meal plans and sends them to the device.

[0683] 11. Terminal: Display the meal plan to the user.

[0684] 12. Server: Periodically analyzes exercise data and generates progress reports.

[0685] 13. Device: Shows the user progress and suggests new exercise plans.

[0686] Examples of explicit prompts that have been given so far include:

[0687] "A 40-year-old male user signed up for an account with the goal of losing weight. He is a beginner and wants a workout plan that includes 30 minutes of cardio and strength training four times a week. How does the system work and what kind of workout plan does it provide?"

[0688] The system of the present invention allows users to effectively progress towards their fitness goals while enjoying sustained exercise.

[0689] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0690] Step 1:

[0691] First, users install the fitness support application on their mobile device, which prepares the environment for using the system.

[0692] Enter: Install application

[0693] Output: App installation complete

[0694] Step 2:

[0695] On the account creation screen, users enter initial information such as name, gender, age, height, weight, fitness level, and fitness goals. This information is entered through a form on the device.

[0696] Input: Name, Gender, Age, Height, Weight, Fitness Level, Fitness Goal

[0697] Output: Initial information entered

[0698] Step 3:

[0699] The terminal sends the input information to the server as an HTTP request.

[0700] Input: Initial information

[0701] Output: Data sent to server completed

[0702] Step 4:

[0703] The server stores the received data in a database and uses an AI engine (e.g., TensorFlow or PyTorch) to generate a personalized exercise plan. This process involves calculating the appropriate type, frequency, number of repetitions, and intensity of exercise based on the registered information.

[0704] Input: Initial information

[0705] Data processing: Data analysis using an AI engine

[0706] Output: personalized exercise plan

[0707] Step 5:

[0708] The device displays the generated exercise plan to the user, with details of each exercise and instructions for execution available within the app.

[0709] Input: personalized exercise plans

[0710] Output: Display of exercise plan

[0711] Step 6:

[0712] When a user starts exercising, exercise data is collected in real time using the device's camera and accelerometer (e.g., IMU sensor).

[0713] Input: User starts exercising

[0714] Output: Collected exercise data

[0715] Step 7:

[0716] The server analyzes the exercise data and calculates metrics such as type of exercise, number of repetitions, duration, angle, etc. The analysis is performed using a specific algorithm (e.g., motion analysis algorithm).

[0717] Input: Exercise data

[0718] Data processing: Analysis of movement data

[0719] Output: Analysis results

[0720] Step 8:

[0721] The server generates real-time feedback based on the analysis results and sends it to the device, which displays this feedback to the user and encourages them to exercise in the correct manner.

[0722] Input: Analysis results

[0723] Output: Generating and displaying feedback

[0724] Step 9:

[0725] The server provides specific challenges and rewards based on the exercise data. For example, a challenge such as "exercise for seven consecutive days" is set, and the achievement status is recorded on the server.

[0726] Input: Parsed movement data

[0727] Output: Challenge settings and records

[0728] Step 10:

[0729] The device will display the current challenge progress and points earned to the user, allowing the user to check their progress.

[0730] Input: Challenge progress

[0731] Output: Show challenge progress

[0732] Step 11:

[0733] Users input their daily dietary habits and food preferences and restrictions into the application.

[0734] Input: Meal information

[0735] Output: Input meal information

[0736] Step 12:

[0737] The terminal transmits the input meal information to the server.

[0738] Input: Meal information

[0739] Output: Data sent to server completed

[0740] Step 13:

[0741] The server generates a nutritionally balanced meal plan based on the dietary information, and creates recipes and ingredient lists tailored to the user, referencing a specific nutrition database (e.g., the USDA Nutrition Database).

[0742] Input: Meal information

[0743] Data processing: Analysis of nutritional information

[0744] Output: personalized meal plan

[0745] Step 14:

[0746] The terminal displays the generated meal plan to the user.

[0747] Enter: personalized meal plans.

[0748] Output: Display of meal plan

[0749] Step 15:

[0750] The server periodically analyzes the collected exercise data and monitors progress, adjusting the exercise plan as needed and generating a new one.

[0751] Input: Collected and analyzed movement data

[0752] Data processing: Progress analysis

[0753] Output: Coordinated movement planning

[0754] Step 16:

[0755] The device notifies the user of the newly generated exercise plan and prompts them to take action for the next step.

[0756] Input: Coordinated movement plan

[0757] Output: Exercise plan notification

[0758] (Application example 1)

[0759] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0760] Currently, there are systems that allow users to create individual exercise plans and stay fit, but there are still a lack of systems that provide comprehensive support, including real-time feedback, data collection during exercise, nutritional advice, progress management, and communication with other users in fitness facilities. Furthermore, systems that provide gamification elements to increase exercise motivation or real-time feedback using dedicated head-mounted displays or smart glasses are also uncommon.

[0761] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0762] In this invention, the server includes means for collecting registration information from users, means for generating a personalized exercise plan based on the collected information, means for providing the generated exercise plan to users, means for collecting and analyzing users' exercise data in real time, means for providing real-time feedback based on the collected exercise data, means for providing exercise challenges and rewards to users, means for collecting users' nutritional data and generating a personalized meal plan, means for periodically analyzing the exercise data and adjusting the exercise plan, means for using sensors to collect data during exercise, means for using head-mounted displays or smart glasses to display users' feedback in real time, and means for providing users with a function for communicating with other users within the fitness facility. This allows users to enjoy continuous fitness activities, receive real-time feedback, and effectively achieve their goals in accordance with the personalized exercise and nutrition plans. Furthermore, the interaction and competitive spirit can enhance a sense of community and motivation within the fitness facility.

[0763] "User" means any person who uses the Fitness System.

[0764] "Registration Information" means information entered by a User when accessing the System for the first time, including, but not limited to, name, gender, age, height, weight, fitness level, and fitness goals.

[0765] An "exercise plan" is a personalized exercise specification generated based on a user's registration information, including specific exercises, frequency, number of repetitions, intensity, etc.

[0766] "Exercise data" refers to information collected when a user exercises, and includes the type of exercise, number of times, time, angle, etc.

[0767] "Real-time feedback" refers to feedback provided instantly based on collected athletic data.

[0768] "Nutrition Data" refers to information entered by the user regarding their daily diet and food preferences and restrictions.

[0769] A "meal plan" is a personalized meal specification generated based on nutritional data, including specific recipes and ingredient lists.

[0770] "Sensor" refers to a hardware device used to collect real-time data during a user's exercise.

[0771] A "head-mounted display" is a display device worn by a user and used to provide visual information.

[0772] "Smart glasses" are eyeglass-type devices worn by users and used to provide visual information.

[0773] A "fitness facility" is a dedicated location for users to exercise, such as a gym or sports facility.

[0774] "Communication Features" means features provided within a fitness facility that enable users to exchange information and interact with other users.

[0775] The system of the present invention is designed to help users improve their fitness by allowing them to follow a personalized exercise plan, receive real-time feedback, and provide comprehensive support including nutritional advice, progress monitoring, and communication with other users within the fitness facility.

[0776] User registration and initial evaluation

[0777] First, users install the application using their smartphone or head-mounted display, and when creating an account, they enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is sent to the server via the device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[0778] Providing and implementing exercise plans

[0779] The device displays the generated exercise plan to the user and encourages them to execute the exercise. Once the user starts exercising, the device's camera and sensors (such as smart glasses or a head-mounted display) are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, duration, and angle. The server analyzes the collected exercise data and provides accurate feedback. For example, it provides real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[0780] Nutrition advice and meal plans

[0781] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[0782] Monitor progress and adjust plans

[0783] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[0784] Gamification and points system

[0785] The server provides specific challenges and rewards based on the user's exercise data. For example, points are awarded for exercising for seven consecutive days. This allows users to maintain a sustainable exercise habit while having fun. The device displays the user's progress in the current challenge and the points earned.

[0786] Communication features within fitness facilities

[0787] It also provides a function that allows users to communicate with other users in the fitness facility while exercising, allowing them to cooperate and compete towards common goals, increasing motivation for fitness activities.

[0788] Prompt Sentence Examples

[0789] A user's profile includes the following information: name, age, gender, height, weight, fitness level, and fitness goals. Based on this information, generate a personalized exercise plan for the user. For example, if a 40-year-old male wants to lose weight, suggest an appropriate exercise plan.

[0790] This system allows users to enjoy continuous fitness activities, receive real-time feedback, and effectively achieve their goals through personalized exercise and nutrition plans. Furthermore, the interaction and competitive spirit with other users within the fitness facility enhances a sense of community and motivation.

[0791] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0792] Step 1:

[0793] A user installs the application using a smartphone or head-mounted display and creates an account. Input data, such as name, gender, age, height, weight, fitness level, and fitness goals, is entered into the device. The device then sends this input data to the server. The server stores the received data in a database and uses an AI engine to generate an exercise plan tailored to the user.

[0794] Step 2:

[0795] The exercise plan generated by the server includes specific exercises, frequency, number of repetitions, intensity, etc. This exercise plan is sent from the server to the device, which displays it to the user. The user then begins exercising based on the displayed exercise plan.

[0796] Step 3:

[0797] The device uses the smartphone camera, smart glasses, and head-mounted display sensors to collect the user's exercise data (type of exercise, number of times, duration, angle, etc.) in real time. This exercise data is then sent from the device to a server.

[0798] Step 4:

[0799] The server uses an AI model to analyze the received exercise data and check whether the exercise is being performed with the correct form and whether the number of repetitions is sufficient. The analysis results are sent to the device in real time as feedback. The device displays this feedback to the user, encouraging them to adjust their exercise form and number of repetitions appropriately.

[0800] Step 5:

[0801] The user inputs the details of their daily meals into the device and sends the information to the server. The server generates a nutritionally balanced meal plan based on the received nutritional data. The generated meal plan (specific recipes, ingredient lists, etc.) is sent from the server to the device, which displays it to support the user's daily eating habits.

[0802] Step 6:

[0803] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains or weight loss and adjusts the exercise plan as needed. The server notifies the device of the new exercise plan, which is then displayed to the user.

[0804] Step 7:

[0805] The server provides specific challenges and rewards based on the user's exercise data. For example, points are awarded for exercising for seven consecutive days. The device displays the user's current challenge progress and earned points, further motivating them to exercise.

[0806] Step 8:

[0807] The devices also provide a function for users to communicate with other users within the fitness facility, for example, allowing users to cooperate or compete with other users while exercising, further increasing motivation and a sense of community.

[0808] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0809] The system of the present invention supports users in improving their fitness, and in particular, by incorporating an emotion engine, it takes into account the user's emotional state and provides more effective exercise planning and feedback. Specific embodiments for implementing the present invention and their processing flow are described below.

[0810] User registration and initial evaluation

[0811] First, users install the application and create an account by entering initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is then sent to the server via their device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[0812] Providing and implementing exercise plans

[0813] The device displays the generated exercise plan to the user and encourages them to exercise. Once the user begins exercising, the device's camera and sensors are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, time, and angle. The server analyzes the collected exercise data and provides accurate feedback to the device. For example, it provides real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[0814] Gamification and points system

[0815] The server provides specific challenges and rewards based on the user's exercise data. For example, a specific number of points may be awarded for exercising for seven consecutive days. This allows users to maintain a consistent exercise habit while having fun. The device displays the user's current challenge progress and the points earned.

[0816] Nutrition advice and meal plans

[0817] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[0818] Monitor progress and adjust plans

[0819] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[0820] Emotion engine integration

[0821] The device uses a camera and microphone to collect the user's facial expressions and voice in real time. This data is sent to a server to recognize the user's emotional state (e.g., joy, sadness, surprise, stress, etc.). The server uses an emotion engine to analyze the collected data and identify the user's emotional state. Based on this, the device adjusts the exercise plan and real-time feedback.

[0822] For example, if a user feels fatigued or stressed during exercise, the emotion engine can detect this and suggest reducing the intensity of the exercise. Conversely, if the user is highly motivated, it can suggest a further challenge. In this way, fine-tuned adjustments based on the user's emotional state are possible.

[0823] Specific examples

[0824] For example, if a 30-year-old female user registers an account with the goal of reducing stress, the system will operate as follows.

[0825] 1. User: Enter your name, gender, age, height, weight, current fitness level (intermediate) and goal (stress reduction).

[0826] 2. Server: Based on this information, it generates an appropriate exercise plan (e.g., a combination of yoga and breathing exercises for 40 minutes three times a week) and sends it to the device.

[0827] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[0828] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[0829] 5. Server: Analyzes this data and sends real-time feedback to the device.

[0830] 6. Device: Provides feedback to the user and encourages proper exercise form.

[0831] 7. Terminal: Uses a camera and microphone to collect the user's facial expressions and voice, and sends the emotional data to the server.

[0832] 8. Server: Utilizes the emotion engine to analyze the emotion data and identify the user's emotional state (e.g., increased stress).

[0833] 9. Server: Adjusts exercise plans and suggests lower intensity exercises based on emotional state.

[0834] 10. Device: Displays the adjusted exercise plan to the user and prompts them for the next step.

[0835] In this way, exercise plans and feedback are provided that take into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[0836] The processing flow will be explained below.

[0837] Specific explanation of program processing

[0838] User registration and initial evaluation

[0839] Step 1:

[0840] The user installs and launches the application.

[0841] Step 2:

[0842] On the account registration screen, users enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals.

[0843] Step 3:

[0844] The terminal transmits the information entered by the user to the server.

[0845] Step 4:

[0846] The server stores the received information in a database.

[0847] Step 5:

[0848] The server uses an AI engine to generate an optimal exercise plan for the user based on the stored information.

[0849] Providing and implementing exercise plans

[0850] Step 1:

[0851] The terminal displays the generated exercise plan to the user and prompts the user to confirm it.

[0852] Step 2:

[0853] The user checks the displayed exercise plan and presses the "Start Exercise" button.

[0854] Step 3:

[0855] The device prepares the device to start the exercise and sets the timer and other necessary settings.

[0856] Step 4:

[0857] The user performs an exercise (e.g., squats or push-ups).

[0858] Step 5:

[0859] The device uses a camera and accelerometer to collect the user's movement data (e.g., type of movement, number of times, duration, angle, etc.) in real time.

[0860] Step 6:

[0861] The terminal transmits the collected exercise data to a server.

[0862] Step 7:

[0863] The server analyzes the received exercise data and uses an AI engine to generate real-time feedback (e.g., proper form and areas for improvement).

[0864] Step 8:

[0865] The server transmits the generated feedback to the terminal.

[0866] Step 9:

[0867] The device displays feedback to the user, providing immediate audio and visual feedback (e.g., "Bend your knees more").

[0868] Emotion engine integration

[0869] Step 1:

[0870] The device uses a camera and microphone to collect the user's facial expressions and voice in real time.

[0871] Step 2:

[0872] The terminal transmits the collected emotion data to the server.

[0873] Step 3:

[0874] The server uses an emotion engine to analyze facial and voice data to identify the user's emotional state (e.g., joy, sadness, surprise, stress, etc.).

[0875] Step 4:

[0876] The server adjusts exercise plans and real-time feedback based on emotional state (e.g., reducing exercise intensity if stress is high).

[0877] Step 5:

[0878] The device displays adjusted exercise plans and feedback to the user (e.g., "Try a light exercise today").

[0879] Gamification and points system

[0880] Step 1:

[0881] The server generates challenges and rewards based on the user's exercise data (e.g., rewards for exercising for seven consecutive days).

[0882] Step 2:

[0883] The terminal displays the generated challenge content to the user.

[0884] Step 3:

[0885] The user participates in the presented challenge and continues exercising.

[0886] Step 4:

[0887] The server monitors whether the challenge is met and adds points if it is met.

[0888] Step 5:

[0889] The terminal displays the user's earned points and achievement status.

[0890] Nutrition advice and meal plans

[0891] Step 1:

[0892] Users enter their daily dietary preferences and food restrictions (e.g., vegetarian, allergy information, etc.) within the application.

[0893] Step 2:

[0894] The terminal transmits the input information to the server.

[0895] Step 3:

[0896] The server stores the received nutritional data and uses an AI engine to generate a balanced meal plan.

[0897] Step 4:

[0898] The device then displays the generated meal plan to the user, including specific recipes and ingredient lists.

[0899] Monitor progress and adjust plans

[0900] Step 1:

[0901] The terminal periodically transmits the exercise data to the server.

[0902] Step 2:

[0903] The server stores the received data in a database and analyzes the user's progress.

[0904] Step 3:

[0905] The server uses an AI engine to generate progress reports (e.g., how much strength has improved, weight fluctuations, etc.).

[0906] Step 4:

[0907] The terminal displays progress reports to the user in the form of graphs and text.

[0908] Step 5:

[0909] The server adjusts exercise and meal plans based on the analyzed progress data.

[0910] Step 6:

[0911] The device will notify the user of the updated plan and prompt them to confirm.

[0912] In this way, by integrating an emotion engine, the system provides personalized exercise plans and feedback that take into account the user's emotional state, enabling a sustainable and effective fitness program.

[0913] Example 2

[0914] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0915] Conventional fitness systems have difficulty providing effective fitness programs because they are unable to provide exercise plans that take into account the individual state and emotions of each user. They also face the challenge of not providing sufficient support for users to maintain their motivation or plan their meals.

[0916] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0917] In this invention, the server includes means for collecting registration information from a user, means for generating a personalized exercise plan based on the collected information, means for providing the generated exercise plan to the user, means for collecting and analyzing the user's exercise data in real time, means for providing real-time feedback based on the collected exercise data, means for providing the user with exercise challenges and rewards, means for collecting the user's nutritional data and generating a personalized meal plan, means for periodically analyzing the exercise data and adjusting the exercise plan, means for collecting the user's emotional data and analyzing the emotional state, and means for adjusting the exercise plan and feedback based on the emotional state. This makes it possible to provide a more effective and sustainable fitness program that takes into account the user's individual condition and emotions.

[0918] "Registration Information" refers to the initial data a user provides to the system, such as name, gender, age, height, weight, fitness level, and goals.

[0919] An "exercise plan" is a schedule and content of exercises created based on the user's individual condition and goals.

[0920] "Exercise data" is data collected when a user exercises, and includes the type of exercise, number of times, time, angle, etc.

[0921] "Real-time feedback" refers to immediate advice and instructions given to users while they are exercising.

[0922] A "challenge" is a task or goal set for a user to achieve a specific exercise goal.

[0923] "Rewards" are incentives given to users when they achieve a specific exercise goal or challenge.

[0924] "Nutrition Data" refers to information about the user's daily diet and food preferences and restrictions.

[0925] A "meal plan" is a balanced meal suggestion, recipe, and ingredient list generated based on the user's nutritional data.

[0926] "Analysis" is the process of analyzing information based on collected data.

[0927] "Emotional data" refers to facial and voice data collected by a camera or microphone to indicate a user's emotional state.

[0928] "Emotional state" refers to the psychological state of a user that is identified based on analyzed emotional data.

[0929] "Feedback adjustment" refers to changing the exercise plan and real-time feedback content depending on the user's emotional state.

[0930] The system of the present invention is designed to help users improve their fitness, and in particular, by combining an emotion engine, it takes into account the user's emotional state and provides more effective exercise planning and feedback. Specific embodiments for implementing the present invention and their processing flow are described below.

[0931] User registration and initial evaluation

[0932] First, users install a dedicated application on their smartphone or tablet. When creating an account, they enter initial information into the application, such as their name, gender, age, height, weight, fitness level, and fitness goals. The device then sends this information to a server, which stores the received data in a database. An AI engine is then used to generate a personalized exercise plan based on the stored information, including specific exercises, frequency, number of repetitions, and intensity.

[0933] Providing and implementing exercise plans

[0934] The device displays the generated exercise plan on the application's user interface and prompts the user to perform the exercise. Once the user begins exercising, the device's camera and built-in sensors (accelerometer, gyro sensor, etc.) are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, time, angle, etc. The server analyzes the collected exercise data, determines whether the form is correct and whether the number of repetitions is sufficient, and sends real-time feedback to the device. For example, specific advice such as "Bend your knees a little more" is provided.

[0935] Gamification and points system

[0936] The server provides specific challenges and rewards based on the user's exercise data, such as "exercise for seven consecutive days and receive 100 points." The device displays the user's current challenge progress and earned points within the application to help keep them motivated.

[0937] Nutrition advice and meal plans

[0938] Through the application, users can input their daily dietary needs and food preferences and restrictions. This information is also sent to the server via the device. Based on the received data, the server uses an AI engine to generate a nutritionally balanced meal plan, including specific recipes and ingredient lists. This plan is also provided to the user via the device.

[0939] Monitor progress and adjust plans

[0940] The server periodically analyzes the user's exercise data and monitors their progress. For example, it measures specific results, such as "I lost 2 kg in 4 weeks." Based on the progress, it adjusts the exercise plan and suggests new exercise menus. This is also notified to the user via their device.

[0941] Emotion engine integration

[0942] The device uses a camera and microphone to collect the user's facial expressions and voice in real time. This data is sent to a server and analyzed using an emotion engine (e.g., OpenFace or EmotionAPI). The server identifies the user's emotional state from the analysis results and adjusts the exercise plan and real-time feedback accordingly. For example, if the user feels fatigued or stressed, it suggests reducing the exercise intensity.

[0943] Specific examples

[0944] For example, if a 30-year-old female user registers an account with the goal of reducing stress, the system will operate as follows.

[0945] 1. The user enters their name, gender, age, height, weight, current fitness level (intermediate) and goal (stress reduction).

[0946] 2. The device sends this initial information to the server.

[0947] 3. The server uses this information to generate an appropriate exercise plan (e.g., a combination of yoga and breathing exercises for 40 minutes three times a week) and sends it to the device.

[0948] 4. The device displays the exercise plan to the user and prompts them to start exercising.

[0949] 5. When the user exercises, the device uses the camera and sensors to collect exercise data.

[0950] 6. The server analyzes the collected data and sends real-time feedback to the device.

[0951] 7. The device displays feedback to the user to encourage proper exercise form.

[0952] 8. The device uses a camera and microphone to collect the user's facial expressions and voice, and transmits the emotional data to the server.

[0953] 9. The server uses an emotion engine to analyze the emotion data and identify the user's emotional state (e.g., increased stress).

[0954] 10. The server adjusts your exercise plan based on your emotional state and suggests lower intensity exercises.

[0955] 11. The device displays the adjusted exercise plan to the user and prompts them for next steps.

[0956] In this way, exercise planning and feedback are provided that takes into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[0957] Prompt Sentence Examples

[0958] "A 30-year-old female user has signed up for an account with the goal of reducing stress. Generate an optimal exercise plan for her, along with feedback based on that plan and adjustments that take into account her emotional state. Initial information includes: Name, Gender, Age, Height, Weight, Fitness Level (Intermediate), and Stress Reduction Goal."

[0959] By inputting this prompt into a generative AI model, it is possible to make adjustments that take into account appropriate motor planning, feedback, and emotional state.

[0960] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0961] Step 1: User registration and initial evaluation

[0962] Input: The user enters initial information into the device, such as name, gender, age, height, weight, fitness level, and fitness goals.

[0963] Operation: The device sends the entered registration information to the server's API.

[0964] Output: The server stores the received registration information in a database, and the AI ​​engine generates a personalized exercise plan based on that information. The generated exercise plan is stored in the database.

[0965] Step 2: Provide an exercise plan

[0966] Input: The server retrieves the exercise plan stored in the database.

[0967] Operation: The server sends the exercise plan to the device, which displays the exercise plan on the user interface.

[0968] Output: The user confirms the received exercise plan and prepares to start exercising.

[0969] Step 3: Exercise execution and data collection

[0970] Input: The user begins to exercise.

[0971] How it works: The device uses its built-in camera and sensors to collect the user's exercise data (type, number of times, duration, angle) in real time.

[0972] Output: The collected movement data is sent to the server.

[0973] Step 4: Data analysis and feedback

[0974] Input: The server receives the exercise data received from the device.

[0975] How it works: The server analyzes the exercise data and evaluates the accuracy of form and the number of repetitions completed.

[0976] Output: The server sends real-time feedback to the device based on the evaluation, for example specific instructions such as "bend your knees a bit more."

[0977] Step 5: Challenges and Rewards

[0978] Input: The server evaluates the user's progress based on their exercise data.

[0979] How it works: The server sets a specific challenge (e.g., exercise for seven days in a row) and offers points and rewards based on that.

[0980] Output: This information is sent to the user via their device. The user can check their progress and earned points within the app.

[0981] Step 6: Enter your nutritional data and plan your meals

[0982] Input: Users input their daily dietary preferences and food restrictions through the application.

[0983] How it works: The nutritional data entered is sent via the device to a server, which receives it, analyzes it, and generates a balanced meal plan.

[0984] Output: The resulting meal plan is sent to a device where it is displayed to the user, including specific recipes and ingredient lists.

[0985] Step 7: Monitor progress and adjust plans

[0986] Input: The server periodically collects the user's exercise data.

[0987] How it works: Using the collected data, the server monitors your progress and adjusts your exercise plan as needed.

[0988] Output: The adjusted new movement plan is sent to the device and the user is notified.

[0989] Step 8: Collect and analyze emotion data

[0990] Input: The device uses a camera and microphone to collect the user's facial expressions and voice in real time.

[0991] How it works: Collected emotion data is sent to a server, which analyzes it using an emotion engine to identify emotional states such as stress or fatigue.

[0992] Output: Emotional state analysis is used to adjust motor planning and feedback.

[0993] Step 9: Emotion-Based Feedback Adjustment

[0994] Input: The server uses the analysis results of the emotion data.

[0995] How it works: The server adjusts exercise plans and feedback based on the analysis results. For example, it reduces exercise intensity if fatigue is detected. If high motivation is detected, it suggests challenges.

[0996] Output: The adjusted exercise plan and feedback are sent to the device and notified to the user.

[0997] In this way, a system is realized that utilizes the data obtained at each processing step in the next step and provides the user with an appropriate exercise plan and feedback.

[0998] (Application example 2)

[0999] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1000] Current fitness management systems and applications provide exercise plans based on users' physical data, but do not take into account the user's emotional state, making it difficult to maximize the benefits of exercise or ensure its sustainability. Effective exercise plans based on emotional data are also needed in security services, where it is necessary to quickly identify when employees are feeling stressed and provide appropriate fitness plans.

[1001] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1002] In this invention, the server includes means for collecting registration information from a user, means for generating a personalized exercise plan based on the collected information, and means for providing the generated exercise plan to the user, thereby enabling the exercise plan to be adjusted based on the user's emotional state.

[1003] "User" means an individual or employee who uses the System to improve their fitness.

[1004] "Registration Information" refers to initial information such as a User's name, gender, age, height, weight, fitness level, and fitness goals.

[1005] "Means of collection" refers to technological means such as sensors, cameras, and online forms used to collect registration information, movement data, and emotional data from users.

[1006] An "exercise plan" is a plan that includes specific exercise types, frequency, number of times, intensity, etc., generated based on the user's registered information and emotional state.

[1007] The "means for providing" refers to a terminal or application that notifies the user of the generated exercise plan visually, audibly, or the like.

[1008] "Exercise data" refers to data that records the type, number of times, time, angle, etc. of a user's exercise.

[1009] The "analysis means" refers to algorithms and AI engines that analyze the collected exercise data and evaluate the accuracy and effectiveness of the user's exercise.

[1010] "Real-time feedback" refers to immediate responses provided during exercise, such as suggestions for correcting exercise form or instructions to increase motivation.

[1011] "Means for providing challenges and rewards" refers to a system for providing rewards such as points or badges when users achieve certain athletic achievements.

[1012] "Nutrition Data" refers to information such as the user's dietary habits and food preferences and restrictions.

[1013] A "meal plan" is a plan that includes nutritionally balanced meal plans, specific recipes, and ingredient lists.

[1014] An "emotion recognition engine" is an AI technology that analyzes a user's facial expressions and voice to identify their emotional state.

[1015] "Emotion data" is data that represents the user's emotional state, such as joy, sadness, surprise, or stress.

[1016] The system of the present invention is designed for users who want to improve their fitness, and is implemented by combining a server, a terminal, and a sensor.

[1017] First, the user enters their initial registration information into the terminal through the application, including their name, gender, age, height, weight, fitness level, and fitness goals. The registration information is immediately sent to the server and stored in the database.

[1018] The server uses a generative AI model to generate a personalized exercise plan based on the collected information, including specific exercise types, frequency, number of repetitions, and intensity. The plan is then sent to the device and provided to the user.

[1019] When a user starts exercising, the device's built-in cameras and sensors collect exercise data in real time. This exercise data includes the type of exercise, number of repetitions, time, and angle. The collected data is then sent back to the server and analyzed by an AI engine. The server generates real-time feedback based on the collected exercise data and sends appropriate exercise form and correction suggestions to the device.

[1020] Additionally, the device uses a camera and microphone to capture the user's facial expressions and voice in real time to obtain emotional data. An emotion recognition engine analyzes this data to identify the user's emotional state. For example, if the device determines that the user is feeling stressed, it will suggest reducing the intensity of the exercise. Conversely, if the user is highly motivated, it can suggest further challenges.

[1021] The system also includes a means to adjust exercise plans based on emotional state, maximizing fitness benefits and helping users maintain a consistent exercise routine.

[1022] This system can also be effectively used in security services, for example, to quickly identify situations that cause stress to security guards and provide them with appropriate fitness plans.

[1023] An example prompt is:

[1024] "User: Yamada Taro, Age: 30, Gender: Male, Height: 175cm, Weight: 70kg, Fitness Level: Intermediate, Goal: Stress reduction. Based on this, please generate an appropriate exercise plan. It should be a specific plan including the type, frequency, number of repetitions, and intensity of exercise."

[1025] Implemented in this manner, the system of the present invention provides exercise planning and real-time feedback that takes into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[1026] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1027] Step 1:

[1028] The user enters initial registration information into the application. The entered information includes name, gender, age, height, weight, fitness level, and fitness goal. This is the input, and the device sends it to the server. The entered data is stored on the server and used for subsequent processing.

[1029] Step 2:

[1030] The server uses a generative AI model to generate a personalized exercise plan based on the collected registration information. Specifically, the information stored in the database is passed to the model as input, and an exercise plan is generated as output. This exercise plan includes specific exercise types, frequency, number of repetitions, intensity, etc. The server then sends the generated exercise plan to the device.

[1031] Step 3:

[1032] The terminal displays the exercise plan received from the server to the user. The user starts exercising based on the displayed exercise plan. At this point, the exercise plan is the input and what the terminal displays is the output.

[1033] Step 4:

[1034] When a user exercises, the camera and sensors on the device collect exercise data in real time, including the type of exercise, number of repetitions, time, angle, etc. The collected exercise data is sent as input to the server, which receives it and stores it in a database.

[1035] Step 5:

[1036] The server analyzes the received exercise data using an AI engine. Specifically, it analyzes the input exercise data and evaluates the accuracy and effectiveness of the exercise. The analysis results are the output, and the calculations performed by the AI ​​engine are the data processing. The server generates real-time feedback based on the analysis results and sends it to the device.

[1037] Step 6:

[1038] The device displays the feedback sent from the server to the user, including proper exercise form and suggested corrections. This feedback is the output, and the device displays the specific movement.

[1039] Step 7:

[1040] The device uses a camera and microphone to collect the user's facial expressions and voice in real time, which is the input, and the collected emotional data is sent to the server, which is the output.

[1041] Step 8:

[1042] The server analyzes the collected emotional data using an emotion recognition engine. Specifically, it identifies the user's emotional state based on the input emotional data. The analysis results are the output, and the data processing by the emotion recognition engine is the operation.

[1043] Step 9:

[1044] The server adjusts the exercise plan based on the user's emotional state. For example, if the user feels stressed, it suggests reducing the exercise intensity. The adjusted exercise plan is the output, and the server sends it to the device.

[1045] Step 10:

[1046] The terminal displays the adjusted exercise plan to the user and prompts the user to take the next exercise step. This is the output, and the display on the terminal is the specific action.

[1047] These steps allow for exercise planning and real-time feedback that takes into account the user's emotional state.

[1048] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1049] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1050] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1051] [Third embodiment]

[1052] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1053] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1054] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1055] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1056] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1057] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1058] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1059] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1060] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1061] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1062] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1063] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[1064] The system of the present invention is designed to help users improve their fitness, and specifically provides a personalized exercise plan based on the user's registered information, and provides feedback and nutritional advice in real time. Specific embodiments for implementing the present invention and the process flow thereof are described below.

[1065] User registration and initial evaluation

[1066] First, users install the application and create an account by entering initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is then sent to the server via their device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[1067] Providing and implementing exercise plans

[1068] The device displays the generated exercise plan to the user and encourages them to exercise. Once the user begins exercising, the device's camera and accelerometer are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, duration, and angle. The server analyzes the collected exercise data and provides accurate feedback to the device. For example, it can provide real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[1069] Gamification and points system

[1070] The server provides specific challenges and rewards based on the user's exercise data. For example, a specific number of points may be awarded for exercising for seven consecutive days. This allows users to maintain a consistent exercise habit while having fun. The device displays the user's current challenge progress and the points earned.

[1071] Nutrition advice and meal plans

[1072] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[1073] Monitor progress and adjust plans

[1074] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[1075] Specific examples

[1076] For example, if a 40-year-old male user registers an account with the goal of losing weight, the system operates as follows:

[1077] 1. User: Enter your name, gender, age, height, weight, current fitness level (beginner) and goal (weight loss).

[1078] 2. Server: Based on this information, an appropriate exercise plan (e.g., a combination of aerobic exercise and strength training for 30 minutes, four times a week) is generated and sent to the device.

[1079] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[1080] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[1081] 5. Server: Analyzes this data and sends real-time feedback to the device (e.g., "Bend your knees a little more").

[1082] 6. Device: Provides feedback to the user and encourages proper exercise form.

[1083] 7. Server: Awards points to users when they complete exercises and notifies them when specific challenges are completed.

[1084] 8. Terminal: Displays points and challenge completion status to users.

[1085] 9. User: Enters daily meal information into the terminal, which then sends it to the server.

[1086] 10. Server: Generates nutritionally balanced meal plans and sends them to the device.

[1087] 11. Terminal: Display the meal plan to the user.

[1088] 12. Server: Periodically analyzes exercise data and generates progress reports.

[1089] 13. Device: Shows the user progress and suggests new exercise plans.

[1090] In this way, users can enjoy sustained exercise while effectively progressing towards their fitness goals.

[1091] The processing flow will be explained below.

[1092] Specific explanation of program processing

[1093] User registration and initial evaluation

[1094] Step 1:

[1095] The user installs and launches the JoyFitHub application.

[1096] Step 2:

[1097] On the account registration screen, users enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals.

[1098] Step 3:

[1099] The terminal transmits the information entered by the user to the server.

[1100] Step 4:

[1101] The server stores the received information in a database.

[1102] Step 5:

[1103] The server uses an AI engine to generate an optimal exercise plan for the user based on the stored information.

[1104] Providing and implementing exercise plans

[1105] Step 1:

[1106] The terminal displays the generated exercise plan to the user and prompts the user to confirm it.

[1107] Step 2:

[1108] The user checks the displayed exercise plan and presses the "Start Exercise" button.

[1109] Step 3:

[1110] The device prepares the device to start the exercise and sets the timer and other necessary settings.

[1111] Step 4:

[1112] The user performs an exercise (e.g., squats or push-ups).

[1113] Step 5:

[1114] The device uses a camera and accelerometer to collect the user's movement data (e.g., type of movement, number of times, duration, angle, etc.) in real time.

[1115] Step 6:

[1116] The terminal transmits the collected exercise data to a server.

[1117] Step 7:

[1118] The server analyzes the received exercise data and uses an AI engine to generate real-time feedback (e.g., proper form and areas for improvement).

[1119] Step 8:

[1120] The server transmits the generated feedback to the terminal.

[1121] Step 9:

[1122] The device displays feedback to the user, providing immediate audio and visual feedback (e.g., "Bend your knees more").

[1123] Gamification and points system

[1124] Step 1:

[1125] The server generates challenges and rewards based on the user's exercise data (e.g., rewards for exercising for seven consecutive days).

[1126] Step 2:

[1127] The terminal displays the generated challenge content to the user.

[1128] Step 3:

[1129] The user participates in the presented challenge and continues exercising.

[1130] Step 4:

[1131] The server monitors whether the challenge is met and adds points if it is met.

[1132] Step 5:

[1133] The terminal displays the user's earned points and achievement status.

[1134] Nutrition advice and meal plans

[1135] Step 1:

[1136] Users enter their daily dietary preferences and food restrictions (e.g., vegetarian, allergy information, etc.) within the application.

[1137] Step 2:

[1138] The terminal transmits the input information to the server.

[1139] Step 3:

[1140] The server stores the received nutritional data and uses an AI engine to generate a balanced meal plan.

[1141] Step 4:

[1142] The device then displays the generated meal plan to the user, including specific recipes and ingredient lists.

[1143] Monitor progress and adjust plans

[1144] Step 1:

[1145] The terminal periodically transmits the exercise data to the server.

[1146] Step 2:

[1147] The server stores the received data in a database and analyzes the user's progress.

[1148] Step 3:

[1149] The server uses an AI engine to generate progress reports (e.g., how much strength has improved, weight fluctuations, etc.).

[1150] Step 4:

[1151] The terminal displays progress reports to the user in the form of graphs and text.

[1152] Step 5:

[1153] The server adjusts exercise and meal plans based on the analyzed progress data.

[1154] Step 6:

[1155] The device will notify the user of the updated plan and prompt them to confirm.

[1156] In this way, the system provides a personalized exercise plan based on the user's registration information, and provides real-time feedback and nutritional advice to support an effective and sustainable fitness program.

[1157] Example 1

[1158] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1159] While systems exist that provide effective fitness planning and nutritional management, helping users achieve their fitness goals while enjoying consistent exercise, only a limited number offer real-time feedback and personalized advice. Furthermore, they lack features that keep users motivated through gamification or point systems. Therefore, a system that supports users in continuing to exercise is needed.

[1160] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1161] In this invention, the server includes a means for using the device's sensors to collect the user's exercise data in real time, a means for linking the server and the device to provide real-time feedback based on the collected exercise data, and a means for including gamification elements to provide the user with exercise challenges and rewards. This allows users to consistently and effectively implement fitness plans and exercise safely by receiving real-time feedback and advice. Furthermore, the introduction of gamification elements and a point system can increase users' motivation, helping them develop a consistent exercise habit.

[1162] "User" refers to an individual who uses the System and who uses the Application to improve fitness.

[1163] "Registration Information" means personal information provided by a User to the System, including initial data such as name, gender, age, height, weight, fitness level, and fitness goals.

[1164] "Exercise plan" refers to an exercise or training plan that is personalized and generated based on the user's registration information, and includes specific exercises, frequency, number of times, intensity, etc.

[1165] "Exercise Data" means data collected through the device's sensors and camera when a user exercises, including metrics such as type of exercise, number of times, time, and angle.

[1166] "Real-time feedback" refers to advice and instructions provided instantly based on the analysis of exercise data, with the aim of improving exercise form or adjusting the number of repetitions, etc.

[1167] "Device" refers to an electronic device carried or used by a user, including hardware such as a smartphone, tablet, or wearable device.

[1168] "Server" refers to a computer system that centrally manages the system and processes data, and stores and analyzes data sent from users, generates exercise plans, etc.

[1169] "Gamification elements" refers to challenges and reward systems introduced to increase users' motivation to exercise, including specific achievement goals and point systems.

[1170] "Nutrition Data" means the information provided by you regarding your daily diet and food preferences and restrictions that is used to generate a meal plan.

[1171] "Meal Plan" means a nutritionally balanced meal plan generated based on a User's nutritional data, including specific recipes and ingredient lists.

[1172] "Means of collaboration" refers to the protocols and infrastructure that allow the server and terminal to communicate and send and receive data, and is a mechanism for maintaining data consistency and immediacy.

[1173] MODE FOR CARRYING OUT THE INVENTION

[1174] The present invention relates to a system for supporting users in improving their fitness. Specifically, the system provides a personalized exercise plan based on the user's registered information, and provides feedback and nutritional advice in real time. Specific embodiments for implementing the present invention are described in detail below.

[1175] Hardware and software for user registration and initial evaluation

[1176] Users must first install a dedicated application on their mobile device. They launch the application and enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals on the account creation screen. This information is sent from the user's mobile device to a server. The server stores the received data in a database and uses an AI engine (e.g., TensorFlow or PyTorch) to generate a personalized exercise plan.

[1177] Hardware and software for providing and executing motor planning

[1178] The device provides the generated exercise plan to the user. The exercise plan includes specific exercises, frequency, number of repetitions, and intensity. When the user starts exercising, exercise data is collected in real time using the device's camera and accelerometer (e.g., IMU sensor). The server analyzes this collected data and provides real-time feedback. The feedback may include whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[1179] Gamification and points systems: hardware and software

[1180] The server provides specific challenges and rewards based on exercise data. For example, a challenge such as "exercise for seven consecutive days" can be set, and points and rewards will be awarded if the challenge is achieved. The device displays the current challenge progress and the points earned to the user. This function makes it easier for users to continue exercising.

[1181] Hardware and software in nutrition advice and meal planning

[1182] The user enters their daily dietary habits and food preferences and restrictions into the application. The device then sends this information to the server, which then generates a meal plan that takes nutritional balance into account. Specifically, the server references a nutrition database (e.g., the USDA Nutrition Database) and creates appropriate recipes and ingredient lists. The device then displays the generated meal plan to the user to support daily nutritional intake.

[1183] Hardware and software for monitoring progress and adjusting plans

[1184] The server continuously collects exercise data and periodically analyzes it. Based on the analysis results, it adjusts the exercise plan as needed and generates a new exercise plan. This new plan is then notified to the user via their device, allowing them to effectively progress toward their fitness goals.

[1185] Example: Weight loss in a 40-year-old male user

[1186] For example, if a 40-year-old male user registers an account with the goal of losing weight, the system operates as follows:

[1187] 1. User: Enter your name, gender, age, height, weight, current fitness level (beginner), and goal (weight loss).

[1188] 2. Server: Based on the user's information, it generates an exercise plan (e.g., a combination of aerobic exercise and strength training for 30 minutes four times a week) and sends it to the device.

[1189] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[1190] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[1191] 5. Server: Analyzes this data and sends real-time feedback to the device (e.g., "Bend your knees a little more").

[1192] 6. Device: Provides feedback to the user and encourages proper exercise form.

[1193] 7. Server: Awards points to users when they complete exercises and notifies them when a specific challenge has been completed.

[1194] 8. Terminal: Displays points and challenge completion status to users.

[1195] 9. User: Enters daily meal information into the terminal, which then sends it to the server.

[1196] 10. Server: Generates nutritionally balanced meal plans and sends them to the device.

[1197] 11. Terminal: Display the meal plan to the user.

[1198] 12. Server: Periodically analyzes exercise data and generates progress reports.

[1199] 13. Device: Shows the user progress and suggests new exercise plans.

[1200] Examples of explicit prompts that have been given so far include:

[1201] "A 40-year-old male user signed up for an account with the goal of losing weight. He is a beginner and wants a workout plan that includes 30 minutes of cardio and strength training four times a week. How does the system work and what kind of workout plan does it provide?"

[1202] The system of the present invention allows users to effectively progress towards their fitness goals while enjoying sustained exercise.

[1203] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1204] Step 1:

[1205] First, users install the fitness support application on their mobile device, which prepares the environment for using the system.

[1206] Enter: Install application

[1207] Output: App installation complete

[1208] Step 2:

[1209] On the account creation screen, users enter initial information such as name, gender, age, height, weight, fitness level, and fitness goals. This information is entered through a form on the device.

[1210] Input: Name, Gender, Age, Height, Weight, Fitness Level, Fitness Goal

[1211] Output: Initial information entered

[1212] Step 3:

[1213] The terminal sends the input information to the server as an HTTP request.

[1214] Input: Initial information

[1215] Output: Data sent to server completed

[1216] Step 4:

[1217] The server stores the received data in a database and uses an AI engine (e.g., TensorFlow or PyTorch) to generate a personalized exercise plan. This process involves calculating the appropriate type, frequency, number of repetitions, and intensity of exercise based on the registered information.

[1218] Input: Initial information

[1219] Data processing: Data analysis using an AI engine

[1220] Output: personalized exercise plan

[1221] Step 5:

[1222] The device displays the generated exercise plan to the user, with details of each exercise and instructions for execution available within the app.

[1223] Input: personalized exercise plans

[1224] Output: Display of exercise plan

[1225] Step 6:

[1226] When a user starts exercising, exercise data is collected in real time using the device's camera and accelerometer (e.g., IMU sensor).

[1227] Input: User starts exercising

[1228] Output: Collected exercise data

[1229] Step 7:

[1230] The server analyzes the exercise data and calculates metrics such as type of exercise, number of repetitions, duration, angle, etc. The analysis is performed using a specific algorithm (e.g., motion analysis algorithm).

[1231] Input: Exercise data

[1232] Data processing: Analysis of movement data

[1233] Output: Analysis results

[1234] Step 8:

[1235] The server generates real-time feedback based on the analysis results and sends it to the device, which displays this feedback to the user and encourages them to exercise in the correct manner.

[1236] Input: Analysis results

[1237] Output: Generating and displaying feedback

[1238] Step 9:

[1239] The server provides specific challenges and rewards based on the exercise data. For example, a challenge such as "exercise for seven consecutive days" is set, and the achievement status is recorded on the server.

[1240] Input: Parsed movement data

[1241] Output: Challenge settings and records

[1242] Step 10:

[1243] The device will display the current challenge progress and points earned to the user, allowing the user to check their progress.

[1244] Input: Challenge progress

[1245] Output: Show challenge progress

[1246] Step 11:

[1247] Users input their daily dietary habits and food preferences and restrictions into the application.

[1248] Input: Meal information

[1249] Output: Input meal information

[1250] Step 12:

[1251] The terminal transmits the input meal information to the server.

[1252] Input: Meal information

[1253] Output: Data sent to server completed

[1254] Step 13:

[1255] The server generates a nutritionally balanced meal plan based on the dietary information, and creates recipes and ingredient lists tailored to the user, referencing a specific nutrition database (e.g., the USDA Nutrition Database).

[1256] Input: Meal information

[1257] Data processing: Analysis of nutritional information

[1258] Output: personalized meal plan

[1259] Step 14:

[1260] The terminal displays the generated meal plan to the user.

[1261] Enter: personalized meal plans.

[1262] Output: Display of meal plan

[1263] Step 15:

[1264] The server periodically analyzes the collected exercise data and monitors progress, adjusting the exercise plan as needed and generating a new one.

[1265] Input: Collected and analyzed movement data

[1266] Data processing: Progress analysis

[1267] Output: Coordinated movement planning

[1268] Step 16:

[1269] The device notifies the user of the newly generated exercise plan and prompts them to take action for the next step.

[1270] Input: Coordinated movement plan

[1271] Output: Exercise plan notification

[1272] (Application example 1)

[1273] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1274] Currently, there are systems that allow users to create individual exercise plans and stay fit, but there are still a lack of systems that provide comprehensive support, including real-time feedback, data collection during exercise, nutritional advice, progress management, and communication with other users in fitness facilities. Furthermore, systems that provide gamification elements to increase exercise motivation or real-time feedback using dedicated head-mounted displays or smart glasses are also uncommon.

[1275] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1276] In this invention, the server includes means for collecting registration information from users, means for generating a personalized exercise plan based on the collected information, means for providing the generated exercise plan to users, means for collecting and analyzing users' exercise data in real time, means for providing real-time feedback based on the collected exercise data, means for providing exercise challenges and rewards to users, means for collecting users' nutritional data and generating a personalized meal plan, means for periodically analyzing the exercise data and adjusting the exercise plan, means for using sensors to collect data during exercise, means for using head-mounted displays or smart glasses to display users' feedback in real time, and means for providing users with a function for communicating with other users within the fitness facility. This allows users to enjoy continuous fitness activities, receive real-time feedback, and effectively achieve their goals in accordance with the personalized exercise and nutrition plans. Furthermore, the interaction and competitive spirit can enhance a sense of community and motivation within the fitness facility.

[1277] "User" means any person who uses the Fitness System.

[1278] "Registration Information" means information entered by a User when accessing the System for the first time, including, but not limited to, name, gender, age, height, weight, fitness level, and fitness goals.

[1279] An "exercise plan" is a personalized exercise specification generated based on a user's registration information, including specific exercises, frequency, number of repetitions, intensity, etc.

[1280] "Exercise data" refers to information collected when a user exercises, and includes the type of exercise, number of times, time, angle, etc.

[1281] "Real-time feedback" refers to feedback provided instantly based on collected athletic data.

[1282] "Nutrition Data" refers to information entered by the user regarding their daily diet and food preferences and restrictions.

[1283] A "meal plan" is a personalized meal specification generated based on nutritional data, including specific recipes and ingredient lists.

[1284] "Sensor" refers to a hardware device used to collect real-time data during a user's exercise.

[1285] A "head-mounted display" is a display device worn by a user and used to provide visual information.

[1286] "Smart glasses" are eyeglass-type devices worn by users and used to provide visual information.

[1287] A "fitness facility" is a dedicated location for users to exercise, such as a gym or sports facility.

[1288] "Communication Features" means features provided within a fitness facility that enable users to exchange information and interact with other users.

[1289] The system of the present invention is designed to help users improve their fitness by allowing them to follow a personalized exercise plan, receive real-time feedback, and provide comprehensive support including nutritional advice, progress monitoring, and communication with other users within the fitness facility.

[1290] User registration and initial evaluation

[1291] First, users install the application using their smartphone or head-mounted display, and when creating an account, they enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is sent to the server via the device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[1292] Providing and implementing exercise plans

[1293] The device displays the generated exercise plan to the user and encourages them to execute the exercise. Once the user starts exercising, the device's camera and sensors (such as smart glasses or a head-mounted display) are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, duration, and angle. The server analyzes the collected exercise data and provides accurate feedback. For example, it provides real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[1294] Nutrition advice and meal plans

[1295] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[1296] Monitor progress and adjust plans

[1297] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[1298] Gamification and points system

[1299] The server provides specific challenges and rewards based on the user's exercise data. For example, points are awarded for exercising for seven consecutive days. This allows users to maintain a sustainable exercise habit while having fun. The device displays the user's progress in the current challenge and the points earned.

[1300] Communication features within fitness facilities

[1301] It also provides a function that allows users to communicate with other users in the fitness facility while exercising, allowing them to cooperate and compete towards common goals, increasing motivation for fitness activities.

[1302] Prompt Sentence Examples

[1303] A user's profile includes the following information: name, age, gender, height, weight, fitness level, and fitness goals. Based on this information, generate a personalized exercise plan for the user. For example, if a 40-year-old male wants to lose weight, suggest an appropriate exercise plan.

[1304] This system allows users to enjoy continuous fitness activities, receive real-time feedback, and effectively achieve their goals through personalized exercise and nutrition plans. Furthermore, the interaction and competitive spirit with other users within the fitness facility enhances a sense of community and motivation.

[1305] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1306] Step 1:

[1307] A user installs the application using a smartphone or head-mounted display and creates an account. Input data, such as name, gender, age, height, weight, fitness level, and fitness goals, is entered into the device. The device then sends this input data to the server. The server stores the received data in a database and uses an AI engine to generate an exercise plan tailored to the user.

[1308] Step 2:

[1309] The exercise plan generated by the server includes specific exercises, frequency, number of repetitions, intensity, etc. This exercise plan is sent from the server to the device, which displays it to the user. The user then begins exercising based on the displayed exercise plan.

[1310] Step 3:

[1311] The device uses the smartphone camera, smart glasses, and head-mounted display sensors to collect the user's exercise data (type of exercise, number of times, duration, angle, etc.) in real time. This exercise data is then sent from the device to a server.

[1312] Step 4:

[1313] The server uses an AI model to analyze the received exercise data and check whether the exercise is being performed with the correct form and whether the number of repetitions is sufficient. The analysis results are sent to the device in real time as feedback. The device displays this feedback to the user, encouraging them to adjust their exercise form and number of repetitions appropriately.

[1314] Step 5:

[1315] The user inputs the details of their daily meals into the device and sends the information to the server. The server generates a nutritionally balanced meal plan based on the received nutritional data. The generated meal plan (specific recipes, ingredient lists, etc.) is sent from the server to the device, which displays it to support the user's daily eating habits.

[1316] Step 6:

[1317] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains or weight loss and adjusts the exercise plan as needed. The server notifies the device of the new exercise plan, which is then displayed to the user.

[1318] Step 7:

[1319] The server provides specific challenges and rewards based on the user's exercise data. For example, points are awarded for exercising for seven consecutive days. The device displays the user's current challenge progress and earned points, further motivating them to exercise.

[1320] Step 8:

[1321] The devices also provide a function for users to communicate with other users within the fitness facility, for example, allowing users to cooperate or compete with other users while exercising, further increasing motivation and a sense of community.

[1322] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1323] The system of the present invention supports users in improving their fitness, and in particular, by incorporating an emotion engine, it takes into account the user's emotional state and provides more effective exercise planning and feedback. Specific embodiments for implementing the present invention and their processing flow are described below.

[1324] User registration and initial evaluation

[1325] First, users install the application and create an account by entering initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is then sent to the server via their device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[1326] Providing and implementing exercise plans

[1327] The device displays the generated exercise plan to the user and encourages them to exercise. Once the user begins exercising, the device's camera and sensors are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, time, and angle. The server analyzes the collected exercise data and provides accurate feedback to the device. For example, it provides real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[1328] Gamification and points system

[1329] The server provides specific challenges and rewards based on the user's exercise data. For example, a specific number of points may be awarded for exercising for seven consecutive days. This allows users to maintain a consistent exercise habit while having fun. The device displays the user's current challenge progress and the points earned.

[1330] Nutrition advice and meal plans

[1331] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[1332] Monitor progress and adjust plans

[1333] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[1334] Emotion engine integration

[1335] The device uses a camera and microphone to collect the user's facial expressions and voice in real time. This data is sent to a server to recognize the user's emotional state (e.g., joy, sadness, surprise, stress, etc.). The server uses an emotion engine to analyze the collected data and identify the user's emotional state. Based on this, the device adjusts the exercise plan and real-time feedback.

[1336] For example, if a user feels fatigued or stressed during exercise, the emotion engine can detect this and suggest reducing the intensity of the exercise. Conversely, if the user is highly motivated, it can suggest a further challenge. In this way, fine-tuned adjustments based on the user's emotional state are possible.

[1337] Specific examples

[1338] For example, if a 30-year-old female user registers an account with the goal of reducing stress, the system will operate as follows.

[1339] 1. User: Enter your name, gender, age, height, weight, current fitness level (intermediate) and goal (stress reduction).

[1340] 2. Server: Based on this information, it generates an appropriate exercise plan (e.g., a combination of yoga and breathing exercises for 40 minutes three times a week) and sends it to the device.

[1341] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[1342] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[1343] 5. Server: Analyzes this data and sends real-time feedback to the device.

[1344] 6. Device: Provides feedback to the user and encourages proper exercise form.

[1345] 7. Terminal: Uses a camera and microphone to collect the user's facial expressions and voice, and sends the emotional data to the server.

[1346] 8. Server: Utilizes the emotion engine to analyze the emotion data and identify the user's emotional state (e.g., increased stress).

[1347] 9. Server: Adjusts exercise plans and suggests lower intensity exercises based on emotional state.

[1348] 10. Device: Displays the adjusted exercise plan to the user and prompts them for the next step.

[1349] In this way, exercise plans and feedback are provided that take into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[1350] The processing flow will be explained below.

[1351] Specific explanation of program processing

[1352] User registration and initial evaluation

[1353] Step 1:

[1354] The user installs and launches the application.

[1355] Step 2:

[1356] On the account registration screen, users enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals.

[1357] Step 3:

[1358] The terminal transmits the information entered by the user to the server.

[1359] Step 4:

[1360] The server stores the received information in a database.

[1361] Step 5:

[1362] The server uses an AI engine to generate an optimal exercise plan for the user based on the stored information.

[1363] Providing and implementing exercise plans

[1364] Step 1:

[1365] The terminal displays the generated exercise plan to the user and prompts the user to confirm it.

[1366] Step 2:

[1367] The user checks the displayed exercise plan and presses the "Start Exercise" button.

[1368] Step 3:

[1369] The device prepares the device to start the exercise and sets the timer and other necessary settings.

[1370] Step 4:

[1371] The user performs an exercise (e.g., squats or push-ups).

[1372] Step 5:

[1373] The device uses a camera and accelerometer to collect the user's movement data (e.g., type of movement, number of times, duration, angle, etc.) in real time.

[1374] Step 6:

[1375] The terminal transmits the collected exercise data to a server.

[1376] Step 7:

[1377] The server analyzes the received exercise data and uses an AI engine to generate real-time feedback (e.g., proper form and areas for improvement).

[1378] Step 8:

[1379] The server transmits the generated feedback to the terminal.

[1380] Step 9:

[1381] The device displays feedback to the user, providing immediate audio and visual feedback (e.g., "Bend your knees more").

[1382] Emotion engine integration

[1383] Step 1:

[1384] The device uses a camera and microphone to collect the user's facial expressions and voice in real time.

[1385] Step 2:

[1386] The terminal transmits the collected emotion data to the server.

[1387] Step 3:

[1388] The server uses an emotion engine to analyze facial and voice data to identify the user's emotional state (e.g., joy, sadness, surprise, stress, etc.).

[1389] Step 4:

[1390] The server adjusts exercise plans and real-time feedback based on emotional state (e.g., reducing exercise intensity if stress is high).

[1391] Step 5:

[1392] The device displays adjusted exercise plans and feedback to the user (e.g., "Try a light exercise today").

[1393] Gamification and points system

[1394] Step 1:

[1395] The server generates challenges and rewards based on the user's exercise data (e.g., rewards for exercising for seven consecutive days).

[1396] Step 2:

[1397] The terminal displays the generated challenge content to the user.

[1398] Step 3:

[1399] The user participates in the presented challenge and continues exercising.

[1400] Step 4:

[1401] The server monitors whether the challenge is met and adds points if it is met.

[1402] Step 5:

[1403] The terminal displays the user's earned points and achievement status.

[1404] Nutrition advice and meal plans

[1405] Step 1:

[1406] Users enter their daily dietary preferences and food restrictions (e.g., vegetarian, allergy information, etc.) within the application.

[1407] Step 2:

[1408] The terminal transmits the input information to the server.

[1409] Step 3:

[1410] The server stores the received nutritional data and uses an AI engine to generate a balanced meal plan.

[1411] Step 4:

[1412] The device then displays the generated meal plan to the user, including specific recipes and ingredient lists.

[1413] Monitor progress and adjust plans

[1414] Step 1:

[1415] The terminal periodically transmits the exercise data to the server.

[1416] Step 2:

[1417] The server stores the received data in a database and analyzes the user's progress.

[1418] Step 3:

[1419] The server uses an AI engine to generate progress reports (e.g., how much strength has improved, weight fluctuations, etc.).

[1420] Step 4:

[1421] The terminal displays progress reports to the user in the form of graphs and text.

[1422] Step 5:

[1423] The server adjusts exercise and meal plans based on the analyzed progress data.

[1424] Step 6:

[1425] The device will notify the user of the updated plan and prompt them to confirm.

[1426] In this way, by integrating an emotion engine, the system provides personalized exercise plans and feedback that take into account the user's emotional state, enabling a sustainable and effective fitness program.

[1427] Example 2

[1428] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1429] Conventional fitness systems have difficulty providing effective fitness programs because they are unable to provide exercise plans that take into account the individual state and emotions of each user. They also face the challenge of not providing sufficient support for users to maintain their motivation or plan their meals.

[1430] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1431] In this invention, the server includes means for collecting registration information from a user, means for generating a personalized exercise plan based on the collected information, means for providing the generated exercise plan to the user, means for collecting and analyzing the user's exercise data in real time, means for providing real-time feedback based on the collected exercise data, means for providing the user with exercise challenges and rewards, means for collecting the user's nutritional data and generating a personalized meal plan, means for periodically analyzing the exercise data and adjusting the exercise plan, means for collecting the user's emotional data and analyzing the emotional state, and means for adjusting the exercise plan and feedback based on the emotional state. This makes it possible to provide a more effective and sustainable fitness program that takes into account the user's individual condition and emotions.

[1432] "Registration Information" refers to the initial data a user provides to the system, such as name, gender, age, height, weight, fitness level, and goals.

[1433] An "exercise plan" is a schedule and content of exercises created based on the user's individual condition and goals.

[1434] "Exercise data" is data collected when a user exercises, and includes the type of exercise, number of times, time, angle, etc.

[1435] "Real-time feedback" refers to immediate advice and instructions given to users while they are exercising.

[1436] A "challenge" is a task or goal set for a user to achieve a specific exercise goal.

[1437] "Rewards" are incentives given to users when they achieve a specific exercise goal or challenge.

[1438] "Nutrition Data" refers to information about the user's daily diet and food preferences and restrictions.

[1439] A "meal plan" is a balanced meal suggestion, recipe, and ingredient list generated based on the user's nutritional data.

[1440] "Analysis" is the process of analyzing information based on collected data.

[1441] "Emotional data" refers to facial and voice data collected by a camera or microphone to indicate a user's emotional state.

[1442] "Emotional state" refers to the psychological state of a user that is identified based on analyzed emotional data.

[1443] "Feedback adjustment" refers to changing the exercise plan and real-time feedback content depending on the user's emotional state.

[1444] The system of the present invention is designed to help users improve their fitness, and in particular, by combining an emotion engine, it takes into account the user's emotional state and provides more effective exercise planning and feedback. Specific embodiments for implementing the present invention and their processing flow are described below.

[1445] User registration and initial evaluation

[1446] First, users install a dedicated application on their smartphone or tablet. When creating an account, they enter initial information into the application, such as their name, gender, age, height, weight, fitness level, and fitness goals. The device then sends this information to a server, which stores the received data in a database. An AI engine is then used to generate a personalized exercise plan based on the stored information, including specific exercises, frequency, number of repetitions, and intensity.

[1447] Providing and implementing exercise plans

[1448] The device displays the generated exercise plan on the application's user interface and prompts the user to perform the exercise. Once the user begins exercising, the device's camera and built-in sensors (accelerometer, gyro sensor, etc.) are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, time, angle, etc. The server analyzes the collected exercise data, determines whether the form is correct and whether the number of repetitions is sufficient, and sends real-time feedback to the device. For example, specific advice such as "Bend your knees a little more" is provided.

[1449] Gamification and points system

[1450] The server provides specific challenges and rewards based on the user's exercise data, such as "exercise for seven consecutive days and receive 100 points." The device displays the user's current challenge progress and earned points within the application to help keep them motivated.

[1451] Nutrition advice and meal plans

[1452] Through the application, users can input their daily dietary needs and food preferences and restrictions. This information is also sent to the server via the device. Based on the received data, the server uses an AI engine to generate a nutritionally balanced meal plan, including specific recipes and ingredient lists. This plan is also provided to the user via the device.

[1453] Monitor progress and adjust plans

[1454] The server periodically analyzes the user's exercise data and monitors their progress. For example, it measures specific results, such as "I lost 2 kg in 4 weeks." Based on the progress, it adjusts the exercise plan and suggests new exercise menus. This is also notified to the user via their device.

[1455] Emotion engine integration

[1456] The device uses a camera and microphone to collect the user's facial expressions and voice in real time. This data is sent to a server and analyzed using an emotion engine (e.g., OpenFace or EmotionAPI). The server identifies the user's emotional state from the analysis results and adjusts the exercise plan and real-time feedback accordingly. For example, if the user feels fatigued or stressed, it suggests reducing the exercise intensity.

[1457] Specific examples

[1458] For example, if a 30-year-old female user registers an account with the goal of reducing stress, the system will operate as follows.

[1459] 1. The user enters their name, gender, age, height, weight, current fitness level (intermediate) and goal (stress reduction).

[1460] 2. The device sends this initial information to the server.

[1461] 3. The server uses this information to generate an appropriate exercise plan (e.g., a combination of yoga and breathing exercises for 40 minutes three times a week) and sends it to the device.

[1462] 4. The device displays the exercise plan to the user and prompts them to start exercising.

[1463] 5. When the user exercises, the device uses the camera and sensors to collect exercise data.

[1464] 6. The server analyzes the collected data and sends real-time feedback to the device.

[1465] 7. The device displays feedback to the user to encourage proper exercise form.

[1466] 8. The device uses a camera and microphone to collect the user's facial expressions and voice, and transmits the emotional data to the server.

[1467] 9. The server uses an emotion engine to analyze the emotion data and identify the user's emotional state (e.g., increased stress).

[1468] 10. The server adjusts your exercise plan based on your emotional state and suggests lower intensity exercises.

[1469] 11. The device displays the adjusted exercise plan to the user and prompts them for next steps.

[1470] In this way, exercise planning and feedback are provided that takes into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[1471] Prompt Sentence Examples

[1472] "A 30-year-old female user has signed up for an account with the goal of reducing stress. Generate an optimal exercise plan for her, along with feedback based on that plan and adjustments that take into account her emotional state. Initial information includes: Name, Gender, Age, Height, Weight, Fitness Level (Intermediate), and Stress Reduction Goal."

[1473] By inputting this prompt into a generative AI model, it is possible to make adjustments that take into account appropriate motor planning, feedback, and emotional state.

[1474] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1475] Step 1: User registration and initial evaluation

[1476] Input: The user enters initial information into the device, such as name, gender, age, height, weight, fitness level, and fitness goals.

[1477] Operation: The device sends the entered registration information to the server's API.

[1478] Output: The server stores the received registration information in a database, and the AI ​​engine generates a personalized exercise plan based on that information. The generated exercise plan is stored in the database.

[1479] Step 2: Provide an exercise plan

[1480] Input: The server retrieves the exercise plan stored in the database.

[1481] Operation: The server sends the exercise plan to the device, which displays the exercise plan on the user interface.

[1482] Output: The user confirms the received exercise plan and prepares to start exercising.

[1483] Step 3: Exercise execution and data collection

[1484] Input: The user begins to exercise.

[1485] How it works: The device uses its built-in camera and sensors to collect the user's exercise data (type, number of times, duration, angle) in real time.

[1486] Output: The collected movement data is sent to the server.

[1487] Step 4: Data analysis and feedback

[1488] Input: The server receives the exercise data received from the device.

[1489] How it works: The server analyzes the exercise data and evaluates the accuracy of form and the number of repetitions completed.

[1490] Output: The server sends real-time feedback to the device based on the evaluation, for example specific instructions such as "bend your knees a bit more."

[1491] Step 5: Challenges and Rewards

[1492] Input: The server evaluates the user's progress based on their exercise data.

[1493] How it works: The server sets a specific challenge (e.g., exercise for seven days in a row) and offers points and rewards based on that.

[1494] Output: This information is sent to the user via their device. The user can check their progress and earned points within the app.

[1495] Step 6: Enter your nutritional data and plan your meals

[1496] Input: Users input their daily dietary preferences and food restrictions through the application.

[1497] How it works: The nutritional data entered is sent via the device to a server, which receives it, analyzes it, and generates a balanced meal plan.

[1498] Output: The resulting meal plan is sent to a device where it is displayed to the user, including specific recipes and ingredient lists.

[1499] Step 7: Monitor progress and adjust plans

[1500] Input: The server periodically collects the user's exercise data.

[1501] How it works: Using the collected data, the server monitors your progress and adjusts your exercise plan as needed.

[1502] Output: The adjusted new movement plan is sent to the device and the user is notified.

[1503] Step 8: Collect and analyze emotion data

[1504] Input: The device uses a camera and microphone to collect the user's facial expressions and voice in real time.

[1505] How it works: Collected emotion data is sent to a server, which analyzes it using an emotion engine to identify emotional states such as stress or fatigue.

[1506] Output: Emotional state analysis is used to adjust motor planning and feedback.

[1507] Step 9: Emotion-Based Feedback Adjustment

[1508] Input: The server uses the analysis results of the emotion data.

[1509] How it works: The server adjusts exercise plans and feedback based on the analysis results. For example, it reduces exercise intensity if fatigue is detected. If high motivation is detected, it suggests challenges.

[1510] Output: The adjusted exercise plan and feedback are sent to the device and notified to the user.

[1511] In this way, a system is realized that utilizes the data obtained at each processing step in the next step and provides the user with an appropriate exercise plan and feedback.

[1512] (Application example 2)

[1513] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1514] Current fitness management systems and applications provide exercise plans based on users' physical data, but do not take into account the user's emotional state, making it difficult to maximize the benefits of exercise or ensure its sustainability. Effective exercise plans based on emotional data are also needed in security services, where it is necessary to quickly identify when employees are feeling stressed and provide appropriate fitness plans.

[1515] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1516] In this invention, the server includes means for collecting registration information from a user, means for generating a personalized exercise plan based on the collected information, and means for providing the generated exercise plan to the user, thereby enabling the exercise plan to be adjusted based on the user's emotional state.

[1517] "User" means an individual or employee who uses the System to improve their fitness.

[1518] "Registration Information" refers to initial information such as a User's name, gender, age, height, weight, fitness level, and fitness goals.

[1519] "Means of collection" refers to technological means such as sensors, cameras, and online forms used to collect registration information, movement data, and emotional data from users.

[1520] An "exercise plan" is a plan that includes specific exercise types, frequency, number of times, intensity, etc., generated based on the user's registered information and emotional state.

[1521] The "means for providing" refers to a terminal or application that notifies the user of the generated exercise plan visually, audibly, or the like.

[1522] "Exercise data" refers to data that records the type, number of times, time, angle, etc. of a user's exercise.

[1523] The "analysis means" refers to algorithms and AI engines that analyze the collected exercise data and evaluate the accuracy and effectiveness of the user's exercise.

[1524] "Real-time feedback" refers to immediate responses provided during exercise, such as suggestions for correcting exercise form or instructions to increase motivation.

[1525] "Means for providing challenges and rewards" refers to a system for providing rewards such as points or badges when users achieve certain athletic achievements.

[1526] "Nutrition Data" refers to information such as the user's dietary habits and food preferences and restrictions.

[1527] A "meal plan" is a plan that includes nutritionally balanced meal plans, specific recipes, and ingredient lists.

[1528] An "emotion recognition engine" is an AI technology that analyzes a user's facial expressions and voice to identify their emotional state.

[1529] "Emotion data" is data that represents the user's emotional state, such as joy, sadness, surprise, or stress.

[1530] The system of the present invention is designed for users who want to improve their fitness, and is implemented by combining a server, a terminal, and a sensor.

[1531] First, the user enters their initial registration information into the terminal through the application, including their name, gender, age, height, weight, fitness level, and fitness goals. The registration information is immediately sent to the server and stored in the database.

[1532] The server uses a generative AI model to generate a personalized exercise plan based on the collected information, including specific exercise types, frequency, number of repetitions, and intensity. The plan is then sent to the device and provided to the user.

[1533] When a user starts exercising, the device's built-in cameras and sensors collect exercise data in real time. This exercise data includes the type of exercise, number of repetitions, time, and angle. The collected data is then sent back to the server and analyzed by an AI engine. The server generates real-time feedback based on the collected exercise data and sends appropriate exercise form and correction suggestions to the device.

[1534] Additionally, the device uses a camera and microphone to capture the user's facial expressions and voice in real time to obtain emotional data. An emotion recognition engine analyzes this data to identify the user's emotional state. For example, if the device determines that the user is feeling stressed, it will suggest reducing the intensity of the exercise. Conversely, if the user is highly motivated, it can suggest further challenges.

[1535] The system also includes a means to adjust exercise plans based on emotional state, maximizing fitness benefits and helping users maintain a consistent exercise routine.

[1536] This system can also be effectively used in security services, for example, to quickly identify situations that cause stress to security guards and provide them with appropriate fitness plans.

[1537] An example prompt is:

[1538] "User: Yamada Taro, Age: 30, Gender: Male, Height: 175cm, Weight: 70kg, Fitness Level: Intermediate, Goal: Stress reduction. Based on this, please generate an appropriate exercise plan. It should be a specific plan including the type, frequency, number of repetitions, and intensity of exercise."

[1539] Implemented in this manner, the system of the present invention provides exercise planning and real-time feedback that takes into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[1540] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1541] Step 1:

[1542] The user enters initial registration information into the application. The entered information includes name, gender, age, height, weight, fitness level, and fitness goal. This is the input, and the device sends it to the server. The entered data is stored on the server and used for subsequent processing.

[1543] Step 2:

[1544] The server uses a generative AI model to generate a personalized exercise plan based on the collected registration information. Specifically, the information stored in the database is passed to the model as input, and an exercise plan is generated as output. This exercise plan includes specific exercise types, frequency, number of repetitions, intensity, etc. The server then sends the generated exercise plan to the device.

[1545] Step 3:

[1546] The terminal displays the exercise plan received from the server to the user. The user starts exercising based on the displayed exercise plan. At this point, the exercise plan is the input and what the terminal displays is the output.

[1547] Step 4:

[1548] When a user exercises, the camera and sensors on the device collect exercise data in real time, including the type of exercise, number of repetitions, time, angle, etc. The collected exercise data is sent as input to the server, which receives it and stores it in a database.

[1549] Step 5:

[1550] The server analyzes the received exercise data using an AI engine. Specifically, it analyzes the input exercise data and evaluates the accuracy and effectiveness of the exercise. The analysis results are the output, and the calculations performed by the AI ​​engine are the data processing. The server generates real-time feedback based on the analysis results and sends it to the device.

[1551] Step 6:

[1552] The device displays the feedback sent from the server to the user, including proper exercise form and suggested corrections. This feedback is the output, and the device displays the specific movement.

[1553] Step 7:

[1554] The device uses a camera and microphone to collect the user's facial expressions and voice in real time, which is the input, and the collected emotional data is sent to the server, which is the output.

[1555] Step 8:

[1556] The server analyzes the collected emotional data using an emotion recognition engine. Specifically, it identifies the user's emotional state based on the input emotional data. The analysis results are the output, and the data processing by the emotion recognition engine is the operation.

[1557] Step 9:

[1558] The server adjusts the exercise plan based on the user's emotional state. For example, if the user feels stressed, it suggests reducing the exercise intensity. The adjusted exercise plan is the output, and the server sends it to the device.

[1559] Step 10:

[1560] The terminal displays the adjusted exercise plan to the user and prompts the user to take the next exercise step. This is the output, and the display on the terminal is the specific action.

[1561] These steps allow for exercise planning and real-time feedback that takes into account the user's emotional state.

[1562] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1563] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1564] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1565] [Fourth embodiment]

[1566] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1567] 7, a 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.

[1568] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1569] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1570] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1571] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1572] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1573] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1574] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1575] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1576] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1577] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1578] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1579] The system of the present invention is designed to help users improve their fitness, and specifically provides a personalized exercise plan based on the user's registered information, and provides feedback and nutritional advice in real time. Specific embodiments for implementing the present invention and the process flow thereof are described below.

[1580] User registration and initial evaluation

[1581] First, users install the application and create an account by entering initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is then sent to the server via their device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[1582] Providing and implementing exercise plans

[1583] The device displays the generated exercise plan to the user and encourages them to exercise. Once the user begins exercising, the device's camera and accelerometer are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, duration, and angle. The server analyzes the collected exercise data and provides accurate feedback to the device. For example, it can provide real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[1584] Gamification and points system

[1585] The server provides specific challenges and rewards based on the user's exercise data. For example, a specific number of points may be awarded for exercising for seven consecutive days. This allows users to maintain a consistent exercise habit while having fun. The device displays the user's current challenge progress and the points earned.

[1586] Nutrition advice and meal plans

[1587] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[1588] Monitor progress and adjust plans

[1589] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[1590] Specific examples

[1591] For example, if a 40-year-old male user registers an account with the goal of losing weight, the system operates as follows:

[1592] 1. User: Enter your name, gender, age, height, weight, current fitness level (beginner) and goal (weight loss).

[1593] 2. Server: Based on this information, an appropriate exercise plan (e.g., a combination of aerobic exercise and strength training for 30 minutes, four times a week) is generated and sent to the device.

[1594] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[1595] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[1596] 5. Server: Analyzes this data and sends real-time feedback to the device (e.g., "Bend your knees a little more").

[1597] 6. Device: Provides feedback to the user and encourages proper exercise form.

[1598] 7. Server: Awards points to users when they complete exercises and notifies them when specific challenges are completed.

[1599] 8. Terminal: Displays points and challenge completion status to users.

[1600] 9. User: Enters daily meal information into the terminal, which then sends it to the server.

[1601] 10. Server: Generates nutritionally balanced meal plans and sends them to the device.

[1602] 11. Terminal: Display the meal plan to the user.

[1603] 12. Server: Periodically analyzes exercise data and generates progress reports.

[1604] 13. Device: Shows the user progress and suggests new exercise plans.

[1605] In this way, users can enjoy sustained exercise while effectively progressing towards their fitness goals.

[1606] The processing flow will be explained below.

[1607] Specific explanation of program processing

[1608] User registration and initial evaluation

[1609] Step 1:

[1610] The user installs and launches the JoyFitHub application.

[1611] Step 2:

[1612] On the account registration screen, users enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals.

[1613] Step 3:

[1614] The terminal transmits the information entered by the user to the server.

[1615] Step 4:

[1616] The server stores the received information in a database.

[1617] Step 5:

[1618] The server uses an AI engine to generate an optimal exercise plan for the user based on the stored information.

[1619] Providing and implementing exercise plans

[1620] Step 1:

[1621] The terminal displays the generated exercise plan to the user and prompts the user to confirm it.

[1622] Step 2:

[1623] The user checks the displayed exercise plan and presses the "Start Exercise" button.

[1624] Step 3:

[1625] The device prepares the device to start the exercise and sets the timer and other necessary settings.

[1626] Step 4:

[1627] The user performs an exercise (e.g., squats or push-ups).

[1628] Step 5:

[1629] The device uses a camera and accelerometer to collect the user's movement data (e.g., type of movement, number of times, duration, angle, etc.) in real time.

[1630] Step 6:

[1631] The terminal transmits the collected exercise data to a server.

[1632] Step 7:

[1633] The server analyzes the received exercise data and uses an AI engine to generate real-time feedback (e.g., proper form and areas for improvement).

[1634] Step 8:

[1635] The server transmits the generated feedback to the terminal.

[1636] Step 9:

[1637] The device displays feedback to the user, providing immediate audio and visual feedback (e.g., "Bend your knees more").

[1638] Gamification and points system

[1639] Step 1:

[1640] The server generates challenges and rewards based on the user's exercise data (e.g., rewards for exercising for seven consecutive days).

[1641] Step 2:

[1642] The terminal displays the generated challenge content to the user.

[1643] Step 3:

[1644] The user participates in the presented challenge and continues exercising.

[1645] Step 4:

[1646] The server monitors whether the challenge is met and adds points if it is met.

[1647] Step 5:

[1648] The terminal displays the user's earned points and achievement status.

[1649] Nutrition advice and meal plans

[1650] Step 1:

[1651] Users enter their daily dietary preferences and food restrictions (e.g., vegetarian, allergy information, etc.) within the application.

[1652] Step 2:

[1653] The terminal transmits the input information to the server.

[1654] Step 3:

[1655] The server stores the received nutritional data and uses an AI engine to generate a balanced meal plan.

[1656] Step 4:

[1657] The device then displays the generated meal plan to the user, including specific recipes and ingredient lists.

[1658] Monitor progress and adjust plans

[1659] Step 1:

[1660] The terminal periodically transmits the exercise data to the server.

[1661] Step 2:

[1662] The server stores the received data in a database and analyzes the user's progress.

[1663] Step 3:

[1664] The server uses an AI engine to generate progress reports (e.g., how much strength has improved, weight fluctuations, etc.).

[1665] Step 4:

[1666] The terminal displays progress reports to the user in the form of graphs and text.

[1667] Step 5:

[1668] The server adjusts exercise and meal plans based on the analyzed progress data.

[1669] Step 6:

[1670] The device will notify the user of the updated plan and prompt them to confirm.

[1671] In this way, the system provides a personalized exercise plan based on the user's registration information, and provides real-time feedback and nutritional advice to support an effective and sustainable fitness program.

[1672] Example 1

[1673] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1674] While systems exist that provide effective fitness planning and nutritional management, helping users achieve their fitness goals while enjoying consistent exercise, only a limited number offer real-time feedback and personalized advice. Furthermore, they lack features that keep users motivated through gamification or point systems. Therefore, a system that supports users in continuing to exercise is needed.

[1675] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1676] In this invention, the server includes a means for using the device's sensors to collect the user's exercise data in real time, a means for linking the server and the device to provide real-time feedback based on the collected exercise data, and a means for including gamification elements to provide the user with exercise challenges and rewards. This allows users to consistently and effectively implement fitness plans and exercise safely by receiving real-time feedback and advice. Furthermore, the introduction of gamification elements and a point system can increase users' motivation, helping them develop a consistent exercise habit.

[1677] "User" refers to an individual who uses the System and who uses the Application to improve fitness.

[1678] "Registration Information" means personal information provided by a User to the System, including initial data such as name, gender, age, height, weight, fitness level, and fitness goals.

[1679] "Exercise plan" refers to an exercise or training plan that is personalized and generated based on the user's registration information, and includes specific exercises, frequency, number of times, intensity, etc.

[1680] "Exercise Data" means data collected through the device's sensors and camera when a user exercises, including metrics such as type of exercise, number of times, time, and angle.

[1681] "Real-time feedback" refers to advice and instructions provided instantly based on the analysis of exercise data, with the aim of improving exercise form or adjusting the number of repetitions, etc.

[1682] "Device" refers to an electronic device carried or used by a user, including hardware such as a smartphone, tablet, or wearable device.

[1683] "Server" refers to a computer system that centrally manages the system and processes data, and stores and analyzes data sent from users, generates exercise plans, etc.

[1684] "Gamification elements" refers to challenges and reward systems introduced to increase users' motivation to exercise, including specific achievement goals and point systems.

[1685] "Nutrition Data" means the information provided by you regarding your daily diet and food preferences and restrictions that is used to generate a meal plan.

[1686] "Meal Plan" means a nutritionally balanced meal plan generated based on a User's nutritional data, including specific recipes and ingredient lists.

[1687] "Means of collaboration" refers to the protocols and infrastructure that allow the server and terminal to communicate and send and receive data, and is a mechanism for maintaining data consistency and immediacy.

[1688] MODE FOR CARRYING OUT THE INVENTION

[1689] The present invention relates to a system for supporting users in improving their fitness. Specifically, the system provides a personalized exercise plan based on the user's registered information, and provides feedback and nutritional advice in real time. Specific embodiments for implementing the present invention are described in detail below.

[1690] Hardware and software for user registration and initial evaluation

[1691] Users must first install a dedicated application on their mobile device. They launch the application and enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals on the account creation screen. This information is sent from the user's mobile device to a server. The server stores the received data in a database and uses an AI engine (e.g., TensorFlow or PyTorch) to generate a personalized exercise plan.

[1692] Hardware and software for providing and executing motor planning

[1693] The device provides the generated exercise plan to the user. The exercise plan includes specific exercises, frequency, number of repetitions, and intensity. When the user starts exercising, exercise data is collected in real time using the device's camera and accelerometer (e.g., IMU sensor). The server analyzes this collected data and provides real-time feedback. The feedback may include whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[1694] Gamification and points systems: hardware and software

[1695] The server provides specific challenges and rewards based on exercise data. For example, a challenge such as "exercise for seven consecutive days" can be set, and points and rewards will be awarded if the challenge is achieved. The device displays the current challenge progress and the points earned to the user. This function makes it easier for users to continue exercising.

[1696] Hardware and software in nutrition advice and meal planning

[1697] The user enters their daily dietary habits and food preferences and restrictions into the application. The device then sends this information to the server, which then generates a meal plan that takes nutritional balance into account. Specifically, the server references a nutrition database (e.g., the USDA Nutrition Database) and creates appropriate recipes and ingredient lists. The device then displays the generated meal plan to the user to support daily nutritional intake.

[1698] Hardware and software for monitoring progress and adjusting plans

[1699] The server continuously collects exercise data and periodically analyzes it. Based on the analysis results, it adjusts the exercise plan as needed and generates a new exercise plan. This new plan is then notified to the user via their device, allowing them to effectively progress toward their fitness goals.

[1700] Example: Weight loss in a 40-year-old male user

[1701] For example, if a 40-year-old male user registers an account with the goal of losing weight, the system operates as follows:

[1702] 1. User: Enter your name, gender, age, height, weight, current fitness level (beginner), and goal (weight loss).

[1703] 2. Server: Based on the user's information, it generates an exercise plan (e.g., a combination of aerobic exercise and strength training for 30 minutes four times a week) and sends it to the device.

[1704] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[1705] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[1706] 5. Server: Analyzes this data and sends real-time feedback to the device (e.g., "Bend your knees a little more").

[1707] 6. Device: Provides feedback to the user and encourages proper exercise form.

[1708] 7. Server: Awards points to users when they complete exercises and notifies them when a specific challenge has been completed.

[1709] 8. Terminal: Displays points and challenge completion status to users.

[1710] 9. User: Enters daily meal information into the terminal, which then sends it to the server.

[1711] 10. Server: Generates nutritionally balanced meal plans and sends them to the device.

[1712] 11. Terminal: Display the meal plan to the user.

[1713] 12. Server: Periodically analyzes exercise data and generates progress reports.

[1714] 13. Device: Shows the user progress and suggests new exercise plans.

[1715] Examples of explicit prompts that have been given so far include:

[1716] "A 40-year-old male user signed up for an account with the goal of losing weight. He is a beginner and wants a workout plan that includes 30 minutes of cardio and strength training four times a week. How does the system work and what kind of workout plan does it provide?"

[1717] The system of the present invention allows users to effectively progress towards their fitness goals while enjoying sustained exercise.

[1718] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1719] Step 1:

[1720] First, users install the fitness support application on their mobile device, which prepares the environment for using the system.

[1721] Enter: Install application

[1722] Output: App installation complete

[1723] Step 2:

[1724] On the account creation screen, users enter initial information such as name, gender, age, height, weight, fitness level, and fitness goals. This information is entered through a form on the device.

[1725] Input: Name, Gender, Age, Height, Weight, Fitness Level, Fitness Goal

[1726] Output: Initial information entered

[1727] Step 3:

[1728] The terminal sends the input information to the server as an HTTP request.

[1729] Input: Initial information

[1730] Output: Data sent to server completed

[1731] Step 4:

[1732] The server stores the received data in a database and uses an AI engine (e.g., TensorFlow or PyTorch) to generate a personalized exercise plan. This process involves calculating the appropriate type, frequency, number of repetitions, and intensity of exercise based on the registered information.

[1733] Input: Initial information

[1734] Data processing: Data analysis using an AI engine

[1735] Output: personalized exercise plan

[1736] Step 5:

[1737] The device displays the generated exercise plan to the user, with details of each exercise and instructions for execution available within the app.

[1738] Input: personalized exercise plans

[1739] Output: Display of exercise plan

[1740] Step 6:

[1741] When a user starts exercising, exercise data is collected in real time using the device's camera and accelerometer (e.g., IMU sensor).

[1742] Input: User starts exercising

[1743] Output: Collected exercise data

[1744] Step 7:

[1745] The server analyzes the exercise data and calculates metrics such as type of exercise, number of repetitions, duration, angle, etc. The analysis is performed using a specific algorithm (e.g., motion analysis algorithm).

[1746] Input: Exercise data

[1747] Data processing: Analysis of movement data

[1748] Output: Analysis results

[1749] Step 8:

[1750] The server generates real-time feedback based on the analysis results and sends it to the device, which displays this feedback to the user and encourages them to exercise in the correct manner.

[1751] Input: Analysis results

[1752] Output: Generating and displaying feedback

[1753] Step 9:

[1754] The server provides specific challenges and rewards based on the exercise data. For example, a challenge such as "exercise for seven consecutive days" is set, and the achievement status is recorded on the server.

[1755] Input: Parsed movement data

[1756] Output: Challenge settings and records

[1757] Step 10:

[1758] The device will display the current challenge progress and points earned to the user, allowing the user to check their progress.

[1759] Input: Challenge progress

[1760] Output: Show challenge progress

[1761] Step 11:

[1762] Users input their daily dietary habits and food preferences and restrictions into the application.

[1763] Input: Meal information

[1764] Output: Input meal information

[1765] Step 12:

[1766] The terminal transmits the input meal information to the server.

[1767] Input: Meal information

[1768] Output: Data sent to server completed

[1769] Step 13:

[1770] The server generates a nutritionally balanced meal plan based on the dietary information, and creates recipes and ingredient lists tailored to the user, referencing a specific nutrition database (e.g., the USDA Nutrition Database).

[1771] Input: Meal information

[1772] Data processing: Analysis of nutritional information

[1773] Output: personalized meal plan

[1774] Step 14:

[1775] The terminal displays the generated meal plan to the user.

[1776] Enter: personalized meal plans.

[1777] Output: Display of meal plan

[1778] Step 15:

[1779] The server periodically analyzes the collected exercise data and monitors progress, adjusting the exercise plan as needed and generating a new one.

[1780] Input: Collected and analyzed movement data

[1781] Data processing: Progress analysis

[1782] Output: Coordinated movement planning

[1783] Step 16:

[1784] The device notifies the user of the newly generated exercise plan and prompts them to take action for the next step.

[1785] Input: Coordinated movement plan

[1786] Output: Exercise plan notification

[1787] (Application example 1)

[1788] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1789] Currently, there are systems that allow users to create individual exercise plans and stay fit, but there are still a lack of systems that provide comprehensive support, including real-time feedback, data collection during exercise, nutritional advice, progress management, and communication with other users in fitness facilities. Furthermore, systems that provide gamification elements to increase exercise motivation or real-time feedback using dedicated head-mounted displays or smart glasses are also uncommon.

[1790] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1791] In this invention, the server includes means for collecting registration information from users, means for generating a personalized exercise plan based on the collected information, means for providing the generated exercise plan to users, means for collecting and analyzing users' exercise data in real time, means for providing real-time feedback based on the collected exercise data, means for providing exercise challenges and rewards to users, means for collecting users' nutritional data and generating a personalized meal plan, means for periodically analyzing the exercise data and adjusting the exercise plan, means for using sensors to collect data during exercise, means for using head-mounted displays or smart glasses to display users' feedback in real time, and means for providing users with a function for communicating with other users within the fitness facility. This allows users to enjoy continuous fitness activities, receive real-time feedback, and effectively achieve their goals in accordance with the personalized exercise and nutrition plans. Furthermore, the interaction and competitive spirit can enhance a sense of community and motivation within the fitness facility.

[1792] "User" means any person who uses the Fitness System.

[1793] "Registration Information" means information entered by a User when accessing the System for the first time, including, but not limited to, name, gender, age, height, weight, fitness level, and fitness goals.

[1794] An "exercise plan" is a personalized exercise specification generated based on a user's registration information, including specific exercises, frequency, number of repetitions, intensity, etc.

[1795] "Exercise data" refers to information collected when a user exercises, and includes the type of exercise, number of times, time, angle, etc.

[1796] "Real-time feedback" refers to feedback provided instantly based on collected athletic data.

[1797] "Nutrition Data" refers to information entered by the user regarding their daily diet and food preferences and restrictions.

[1798] A "meal plan" is a personalized meal specification generated based on nutritional data, including specific recipes and ingredient lists.

[1799] "Sensor" refers to a hardware device used to collect real-time data during a user's exercise.

[1800] A "head-mounted display" is a display device worn by a user and used to provide visual information.

[1801] "Smart glasses" are eyeglass-type devices worn by users and used to provide visual information.

[1802] A "fitness facility" is a dedicated location for users to exercise, such as a gym or sports facility.

[1803] "Communication Features" means features provided within a fitness facility that enable users to exchange information and interact with other users.

[1804] The system of the present invention is designed to help users improve their fitness by allowing them to follow a personalized exercise plan, receive real-time feedback, and provide comprehensive support including nutritional advice, progress monitoring, and communication with other users within the fitness facility.

[1805] User registration and initial evaluation

[1806] First, users install the application using their smartphone or head-mounted display, and when creating an account, they enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is sent to the server via the device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[1807] Providing and implementing exercise plans

[1808] The device displays the generated exercise plan to the user and encourages them to execute the exercise. Once the user starts exercising, the device's camera and sensors (such as smart glasses or a head-mounted display) are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, duration, and angle. The server analyzes the collected exercise data and provides accurate feedback. For example, it provides real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[1809] Nutrition advice and meal plans

[1810] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[1811] Monitor progress and adjust plans

[1812] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[1813] Gamification and points system

[1814] The server provides specific challenges and rewards based on the user's exercise data. For example, points are awarded for exercising for seven consecutive days. This allows users to maintain a sustainable exercise habit while having fun. The device displays the user's progress in the current challenge and the points earned.

[1815] Communication features within fitness facilities

[1816] It also provides a function that allows users to communicate with other users in the fitness facility while exercising, allowing them to cooperate and compete towards common goals, increasing motivation for fitness activities.

[1817] Prompt Sentence Examples

[1818] A user's profile includes the following information: name, age, gender, height, weight, fitness level, and fitness goals. Based on this information, generate a personalized exercise plan for the user. For example, if a 40-year-old male wants to lose weight, suggest an appropriate exercise plan.

[1819] This system allows users to enjoy continuous fitness activities, receive real-time feedback, and effectively achieve their goals through personalized exercise and nutrition plans. Furthermore, the interaction and competitive spirit with other users within the fitness facility enhances a sense of community and motivation.

[1820] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1821] Step 1:

[1822] A user installs the application using a smartphone or head-mounted display and creates an account. Input data, such as name, gender, age, height, weight, fitness level, and fitness goals, is entered into the device. The device then sends this input data to the server. The server stores the received data in a database and uses an AI engine to generate an exercise plan tailored to the user.

[1823] Step 2:

[1824] The exercise plan generated by the server includes specific exercises, frequency, number of repetitions, intensity, etc. This exercise plan is sent from the server to the device, which displays it to the user. The user then begins exercising based on the displayed exercise plan.

[1825] Step 3:

[1826] The device uses the smartphone camera, smart glasses, and head-mounted display sensors to collect the user's exercise data (type of exercise, number of times, duration, angle, etc.) in real time. This exercise data is then sent from the device to a server.

[1827] Step 4:

[1828] The server uses an AI model to analyze the received exercise data and check whether the exercise is being performed with the correct form and whether the number of repetitions is sufficient. The analysis results are sent to the device in real time as feedback. The device displays this feedback to the user, encouraging them to adjust their exercise form and number of repetitions appropriately.

[1829] Step 5:

[1830] The user inputs the details of their daily meals into the device and sends the information to the server. The server generates a nutritionally balanced meal plan based on the received nutritional data. The generated meal plan (specific recipes, ingredient lists, etc.) is sent from the server to the device, which displays it to support the user's daily eating habits.

[1831] Step 6:

[1832] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains or weight loss and adjusts the exercise plan as needed. The server notifies the device of the new exercise plan, which is then displayed to the user.

[1833] Step 7:

[1834] The server provides specific challenges and rewards based on the user's exercise data. For example, points are awarded for exercising for seven consecutive days. The device displays the user's current challenge progress and earned points, further motivating them to exercise.

[1835] Step 8:

[1836] The devices also provide a function for users to communicate with other users within the fitness facility, for example, allowing users to cooperate or compete with other users while exercising, further increasing motivation and a sense of community.

[1837] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1838] The system of the present invention supports users in improving their fitness, and in particular, by incorporating an emotion engine, it takes into account the user's emotional state and provides more effective exercise planning and feedback. Specific embodiments for implementing the present invention and their processing flow are described below.

[1839] User registration and initial evaluation

[1840] First, users install the application and create an account by entering initial information such as their name, gender, age, height, weight, fitness level, and fitness goals. This information is then sent to the server via their device. The server stores the received data in a database, and an AI engine uses this information to generate an exercise plan tailored to the user. This exercise plan includes specific exercises, frequency, number of repetitions, intensity, etc.

[1841] Providing and implementing exercise plans

[1842] The device displays the generated exercise plan to the user and encourages them to exercise. Once the user begins exercising, the device's camera and sensors are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, time, and angle. The server analyzes the collected exercise data and provides accurate feedback to the device. For example, it provides real-time feedback to the device on whether the exercise is being performed with proper form and whether the number of repetitions is sufficient.

[1843] Gamification and points system

[1844] The server provides specific challenges and rewards based on the user's exercise data. For example, a specific number of points may be awarded for exercising for seven consecutive days. This allows users to maintain a consistent exercise habit while having fun. The device displays the user's current challenge progress and the points earned.

[1845] Nutrition advice and meal plans

[1846] Users can input their daily dietary preferences and food restrictions. This information is also sent to the server via the device. The server generates a nutritionally balanced meal plan based on the received data and provides specific recipes and ingredient lists. The device displays the meal plan to the user, helping them improve their daily eating habits.

[1847] Monitor progress and adjust plans

[1848] The server periodically analyzes the user's exercise data and monitors their progress. For example, it tracks changes such as muscle strength gains and weight loss. Based on this, it adjusts the exercise plan as needed and presents a new plan for the next step. The user is also notified of these adjustments via their device.

[1849] Emotion engine integration

[1850] The device uses a camera and microphone to collect the user's facial expressions and voice in real time. This data is sent to a server to recognize the user's emotional state (e.g., joy, sadness, surprise, stress, etc.). The server uses an emotion engine to analyze the collected data and identify the user's emotional state. Based on this, the device adjusts the exercise plan and real-time feedback.

[1851] For example, if a user feels fatigued or stressed during exercise, the emotion engine can detect this and suggest reducing the intensity of the exercise. Conversely, if the user is highly motivated, it can suggest a further challenge. In this way, fine-tuned adjustments based on the user's emotional state are possible.

[1852] Specific examples

[1853] For example, if a 30-year-old female user registers an account with the goal of reducing stress, the system will operate as follows.

[1854] 1. User: Enter your name, gender, age, height, weight, current fitness level (intermediate) and goal (stress reduction).

[1855] 2. Server: Based on this information, it generates an appropriate exercise plan (e.g., a combination of yoga and breathing exercises for 40 minutes three times a week) and sends it to the device.

[1856] 3. Terminal: Displays the exercise plan to the user and allows them to start exercising.

[1857] 4. User: Performs exercise, and the device collects exercise data using the camera and sensors.

[1858] 5. Server: Analyzes this data and sends real-time feedback to the device.

[1859] 6. Device: Provides feedback to the user and encourages proper exercise form.

[1860] 7. Terminal: Uses a camera and microphone to collect the user's facial expressions and voice, and sends the emotional data to the server.

[1861] 8. Server: Utilizes the emotion engine to analyze the emotion data and identify the user's emotional state (e.g., increased stress).

[1862] 9. Server: Adjusts exercise plans and suggests lower intensity exercises based on emotional state.

[1863] 10. Device: Displays the adjusted exercise plan to the user and prompts them for the next step.

[1864] In this way, exercise plans and feedback are provided that take into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[1865] The processing flow will be explained below.

[1866] Specific explanation of program processing

[1867] User registration and initial evaluation

[1868] Step 1:

[1869] The user installs and launches the application.

[1870] Step 2:

[1871] On the account registration screen, users enter initial information such as their name, gender, age, height, weight, fitness level, and fitness goals.

[1872] Step 3:

[1873] The terminal transmits the information entered by the user to the server.

[1874] Step 4:

[1875] The server stores the received information in a database.

[1876] Step 5:

[1877] The server uses an AI engine to generate an optimal exercise plan for the user based on the stored information.

[1878] Providing and implementing exercise plans

[1879] Step 1:

[1880] The terminal displays the generated exercise plan to the user and prompts the user to confirm it.

[1881] Step 2:

[1882] The user checks the displayed exercise plan and presses the "Start Exercise" button.

[1883] Step 3:

[1884] The device prepares the device to start the exercise and sets the timer and other necessary settings.

[1885] Step 4:

[1886] The user performs an exercise (e.g., squats or push-ups).

[1887] Step 5:

[1888] The device uses a camera and accelerometer to collect the user's movement data (e.g., type of movement, number of times, duration, angle, etc.) in real time.

[1889] Step 6:

[1890] The terminal transmits the collected exercise data to a server.

[1891] Step 7:

[1892] The server analyzes the received exercise data and uses an AI engine to generate real-time feedback (e.g., proper form and areas for improvement).

[1893] Step 8:

[1894] The server transmits the generated feedback to the terminal.

[1895] Step 9:

[1896] The device displays feedback to the user, providing immediate audio and visual feedback (e.g., "Bend your knees more").

[1897] Emotion engine integration

[1898] Step 1:

[1899] The device uses a camera and microphone to collect the user's facial expressions and voice in real time.

[1900] Step 2:

[1901] The terminal transmits the collected emotion data to the server.

[1902] Step 3:

[1903] The server uses an emotion engine to analyze facial and voice data to identify the user's emotional state (e.g., joy, sadness, surprise, stress, etc.).

[1904] Step 4:

[1905] The server adjusts exercise plans and real-time feedback based on emotional state (e.g., reducing exercise intensity if stress is high).

[1906] Step 5:

[1907] The device displays adjusted exercise plans and feedback to the user (e.g., "Try a light exercise today").

[1908] Gamification and points system

[1909] Step 1:

[1910] The server generates challenges and rewards based on the user's exercise data (e.g., rewards for exercising for seven consecutive days).

[1911] Step 2:

[1912] The terminal displays the generated challenge content to the user.

[1913] Step 3:

[1914] The user participates in the presented challenge and continues exercising.

[1915] Step 4:

[1916] The server monitors whether the challenge is met and adds points if it is met.

[1917] Step 5:

[1918] The terminal displays the user's earned points and achievement status.

[1919] Nutrition advice and meal plans

[1920] Step 1:

[1921] Users enter their daily dietary preferences and food restrictions (e.g., vegetarian, allergy information, etc.) within the application.

[1922] Step 2:

[1923] The terminal transmits the input information to the server.

[1924] Step 3:

[1925] The server stores the received nutritional data and uses an AI engine to generate a balanced meal plan.

[1926] Step 4:

[1927] The device then displays the generated meal plan to the user, including specific recipes and ingredient lists.

[1928] Monitor progress and adjust plans

[1929] Step 1:

[1930] The terminal periodically transmits the exercise data to the server.

[1931] Step 2:

[1932] The server stores the received data in a database and analyzes the user's progress.

[1933] Step 3:

[1934] The server uses an AI engine to generate progress reports (e.g., how much strength has improved, weight fluctuations, etc.).

[1935] Step 4:

[1936] The terminal displays progress reports to the user in the form of graphs and text.

[1937] Step 5:

[1938] The server adjusts exercise and meal plans based on the analyzed progress data.

[1939] Step 6:

[1940] The device will notify the user of the updated plan and prompt them to confirm.

[1941] In this way, by integrating an emotion engine, the system provides personalized exercise plans and feedback that take into account the user's emotional state, enabling a sustainable and effective fitness program.

[1942] Example 2

[1943] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1944] Conventional fitness systems have difficulty providing effective fitness programs because they are unable to provide exercise plans that take into account the individual state and emotions of each user. They also face the challenge of not providing sufficient support for users to maintain their motivation or plan their meals.

[1945] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1946] In this invention, the server includes means for collecting registration information from a user, means for generating a personalized exercise plan based on the collected information, means for providing the generated exercise plan to the user, means for collecting and analyzing the user's exercise data in real time, means for providing real-time feedback based on the collected exercise data, means for providing the user with exercise challenges and rewards, means for collecting the user's nutritional data and generating a personalized meal plan, means for periodically analyzing the exercise data and adjusting the exercise plan, means for collecting the user's emotional data and analyzing the emotional state, and means for adjusting the exercise plan and feedback based on the emotional state. This makes it possible to provide a more effective and sustainable fitness program that takes into account the user's individual condition and emotions.

[1947] "Registration Information" refers to the initial data a user provides to the system, such as name, gender, age, height, weight, fitness level, and goals.

[1948] An "exercise plan" is a schedule and content of exercises created based on the user's individual condition and goals.

[1949] "Exercise data" is data collected when a user exercises, and includes the type of exercise, number of times, time, angle, etc.

[1950] "Real-time feedback" refers to immediate advice and instructions given to users while they are exercising.

[1951] A "challenge" is a task or goal set for a user to achieve a specific exercise goal.

[1952] "Rewards" are incentives given to users when they achieve a specific exercise goal or challenge.

[1953] "Nutrition Data" refers to information about the user's daily diet and food preferences and restrictions.

[1954] A "meal plan" is a balanced meal suggestion, recipe, and ingredient list generated based on the user's nutritional data.

[1955] "Analysis" is the process of analyzing information based on collected data.

[1956] "Emotional data" refers to facial and voice data collected by a camera or microphone to indicate a user's emotional state.

[1957] "Emotional state" refers to the psychological state of a user that is identified based on analyzed emotional data.

[1958] "Feedback adjustment" refers to changing the exercise plan and real-time feedback content depending on the user's emotional state.

[1959] The system of the present invention is designed to help users improve their fitness, and in particular, by combining an emotion engine, it takes into account the user's emotional state and provides more effective exercise planning and feedback. Specific embodiments for implementing the present invention and their processing flow are described below.

[1960] User registration and initial evaluation

[1961] First, users install a dedicated application on their smartphone or tablet. When creating an account, they enter initial information into the application, such as their name, gender, age, height, weight, fitness level, and fitness goals. The device then sends this information to a server, which stores the received data in a database. An AI engine is then used to generate a personalized exercise plan based on the stored information, including specific exercises, frequency, number of repetitions, and intensity.

[1962] Providing and implementing exercise plans

[1963] The device displays the generated exercise plan on the application's user interface and prompts the user to perform the exercise. Once the user begins exercising, the device's camera and built-in sensors (accelerometer, gyro sensor, etc.) are used to collect exercise data in real time. This data includes the type of exercise, number of repetitions, time, angle, etc. The server analyzes the collected exercise data, determines whether the form is correct and whether the number of repetitions is sufficient, and sends real-time feedback to the device. For example, specific advice such as "Bend your knees a little more" is provided.

[1964] Gamification and points system

[1965] The server provides specific challenges and rewards based on the user's exercise data, such as "exercise for seven consecutive days and receive 100 points." The device displays the user's current challenge progress and earned points within the application to help keep them motivated.

[1966] Nutrition advice and meal plans

[1967] Through the application, users can input their daily dietary needs and food preferences and restrictions. This information is also sent to the server via the device. Based on the received data, the server uses an AI engine to generate a nutritionally balanced meal plan, including specific recipes and ingredient lists. This plan is also provided to the user via the device.

[1968] Monitor progress and adjust plans

[1969] The server periodically analyzes the user's exercise data and monitors their progress. For example, it measures specific results, such as "I lost 2 kg in 4 weeks." Based on the progress, it adjusts the exercise plan and suggests new exercise menus. This is also notified to the user via their device.

[1970] Emotion engine integration

[1971] The device uses a camera and microphone to collect the user's facial expressions and voice in real time. This data is sent to a server and analyzed using an emotion engine (e.g., OpenFace or EmotionAPI). The server identifies the user's emotional state from the analysis results and adjusts the exercise plan and real-time feedback accordingly. For example, if the user feels fatigued or stressed, it suggests reducing the exercise intensity.

[1972] Specific examples

[1973] For example, if a 30-year-old female user registers an account with the goal of reducing stress, the system will operate as follows.

[1974] 1. The user enters their name, gender, age, height, weight, current fitness level (intermediate) and goal (stress reduction).

[1975] 2. The device sends this initial information to the server.

[1976] 3. The server uses this information to generate an appropriate exercise plan (e.g., a combination of yoga and breathing exercises for 40 minutes three times a week) and sends it to the device.

[1977] 4. The device displays the exercise plan to the user and prompts them to start exercising.

[1978] 5. When the user exercises, the device uses the camera and sensors to collect exercise data.

[1979] 6. The server analyzes the collected data and sends real-time feedback to the device.

[1980] 7. The device displays feedback to the user to encourage proper exercise form.

[1981] 8. The device uses a camera and microphone to collect the user's facial expressions and voice, and transmits the emotional data to the server.

[1982] 9. The server uses an emotion engine to analyze the emotion data and identify the user's emotional state (e.g., increased stress).

[1983] 10. The server adjusts your exercise plan based on your emotional state and suggests lower intensity exercises.

[1984] 11. The device displays the adjusted exercise plan to the user and prompts them for next steps.

[1985] In this way, exercise planning and feedback are provided that takes into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[1986] Prompt Sentence Examples

[1987] "A 30-year-old female user has signed up for an account with the goal of reducing stress. Generate an optimal exercise plan for her, along with feedback based on that plan and adjustments that take into account her emotional state. Initial information includes: Name, Gender, Age, Height, Weight, Fitness Level (Intermediate), and Stress Reduction Goal."

[1988] By inputting this prompt into a generative AI model, it is possible to make adjustments that take into account appropriate motor planning, feedback, and emotional state.

[1989] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1990] Step 1: User registration and initial evaluation

[1991] Input: The user enters initial information into the device, such as name, gender, age, height, weight, fitness level, and fitness goals.

[1992] Operation: The device sends the entered registration information to the server's API.

[1993] Output: The server stores the received registration information in a database, and the AI ​​engine generates a personalized exercise plan based on that information. The generated exercise plan is stored in the database.

[1994] Step 2: Provide an exercise plan

[1995] Input: The server retrieves the exercise plan stored in the database.

[1996] Operation: The server sends the exercise plan to the device, which displays the exercise plan on the user interface.

[1997] Output: The user confirms the received exercise plan and prepares to start exercising.

[1998] Step 3: Exercise execution and data collection

[1999] Input: The user begins to exercise.

[2000] How it works: The device uses its built-in camera and sensors to collect the user's exercise data (type, number of times, duration, angle) in real time.

[2001] Output: The collected movement data is sent to the server.

[2002] Step 4: Data analysis and feedback

[2003] Input: The server receives the exercise data received from the device.

[2004] How it works: The server analyzes the exercise data and evaluates the accuracy of form and the number of repetitions completed.

[2005] Output: The server sends real-time feedback to the device based on the evaluation, for example specific instructions such as "bend your knees a bit more."

[2006] Step 5: Challenges and Rewards

[2007] Input: The server evaluates the user's progress based on their exercise data.

[2008] How it works: The server sets a specific challenge (e.g., exercise for seven days in a row) and offers points and rewards based on that.

[2009] Output: This information is sent to the user via their device. The user can check their progress and earned points within the app.

[2010] Step 6: Enter your nutritional data and plan your meals

[2011] Input: Users input their daily dietary preferences and food restrictions through the application.

[2012] How it works: The nutritional data entered is sent via the device to a server, which receives it, analyzes it, and generates a balanced meal plan.

[2013] Output: The resulting meal plan is sent to a device where it is displayed to the user, including specific recipes and ingredient lists.

[2014] Step 7: Monitor progress and adjust plans

[2015] Input: The server periodically collects the user's exercise data.

[2016] How it works: Using the collected data, the server monitors your progress and adjusts your exercise plan as needed.

[2017] Output: The adjusted new movement plan is sent to the device and the user is notified.

[2018] Step 8: Collect and analyze emotion data

[2019] Input: The device uses a camera and microphone to collect the user's facial expressions and voice in real time.

[2020] How it works: Collected emotion data is sent to a server, which analyzes it using an emotion engine to identify emotional states such as stress or fatigue.

[2021] Output: Emotional state analysis is used to adjust motor planning and feedback.

[2022] Step 9: Emotion-Based Feedback Adjustment

[2023] Input: The server uses the analysis results of the emotion data.

[2024] How it works: The server adjusts exercise plans and feedback based on the analysis results. For example, it reduces exercise intensity if fatigue is detected. If high motivation is detected, it suggests challenges.

[2025] Output: The adjusted exercise plan and feedback are sent to the device and notified to the user.

[2026] In this way, a system is realized that utilizes the data obtained at each processing step in the next step and provides the user with an appropriate exercise plan and feedback.

[2027] (Application example 2)

[2028] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2029] Current fitness management systems and applications provide exercise plans based on users' physical data, but do not take into account the user's emotional state, making it difficult to maximize the benefits of exercise or ensure its sustainability. Effective exercise plans based on emotional data are also needed in security services, where it is necessary to quickly identify when employees are feeling stressed and provide appropriate fitness plans.

[2030] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2031] In this invention, the server includes means for collecting registration information from a user, means for generating a personalized exercise plan based on the collected information, and means for providing the generated exercise plan to the user, thereby enabling the exercise plan to be adjusted based on the user's emotional state.

[2032] "User" means an individual or employee who uses the System to improve their fitness.

[2033] "Registration Information" refers to initial information such as a User's name, gender, age, height, weight, fitness level, and fitness goals.

[2034] "Means of collection" refers to technological means such as sensors, cameras, and online forms used to collect registration information, movement data, and emotional data from users.

[2035] An "exercise plan" is a plan that includes specific exercise types, frequency, number of times, intensity, etc., generated based on the user's registered information and emotional state.

[2036] The "means for providing" refers to a terminal or application that notifies the user of the generated exercise plan visually, audibly, or the like.

[2037] "Exercise data" refers to data that records the type, number of times, time, angle, etc. of a user's exercise.

[2038] The "analysis means" refers to algorithms and AI engines that analyze the collected exercise data and evaluate the accuracy and effectiveness of the user's exercise.

[2039] "Real-time feedback" refers to immediate responses provided during exercise, such as suggestions for correcting exercise form or instructions to increase motivation.

[2040] "Means for providing challenges and rewards" refers to a system for providing rewards such as points or badges when users achieve certain athletic achievements.

[2041] "Nutrition Data" refers to information such as the user's dietary habits and food preferences and restrictions.

[2042] A "meal plan" is a plan that includes nutritionally balanced meal plans, specific recipes, and ingredient lists.

[2043] An "emotion recognition engine" is an AI technology that analyzes a user's facial expressions and voice to identify their emotional state.

[2044] "Emotion data" is data that represents the user's emotional state, such as joy, sadness, surprise, or stress.

[2045] The system of the present invention is designed for users who want to improve their fitness, and is implemented by combining a server, a terminal, and a sensor.

[2046] First, the user enters their initial registration information into the terminal through the application, including their name, gender, age, height, weight, fitness level, and fitness goals. The registration information is immediately sent to the server and stored in the database.

[2047] The server uses a generative AI model to generate a personalized exercise plan based on the collected information, including specific exercise types, frequency, number of repetitions, and intensity. The plan is then sent to the device and provided to the user.

[2048] When a user starts exercising, the device's built-in cameras and sensors collect exercise data in real time. This exercise data includes the type of exercise, number of repetitions, time, and angle. The collected data is then sent back to the server and analyzed by an AI engine. The server generates real-time feedback based on the collected exercise data and sends appropriate exercise form and correction suggestions to the device.

[2049] Additionally, the device uses a camera and microphone to capture the user's facial expressions and voice in real time to obtain emotional data. An emotion recognition engine analyzes this data to identify the user's emotional state. For example, if the device determines that the user is feeling stressed, it will suggest reducing the intensity of the exercise. Conversely, if the user is highly motivated, it can suggest further challenges.

[2050] The system also includes a means to adjust exercise plans based on emotional state, maximizing fitness benefits and helping users maintain a consistent exercise routine.

[2051] This system can also be effectively used in security services, for example, to quickly identify situations that cause stress to security guards and provide them with appropriate fitness plans.

[2052] An example prompt is:

[2053] "User: Yamada Taro, Age: 30, Gender: Male, Height: 175cm, Weight: 70kg, Fitness Level: Intermediate, Goal: Stress reduction. Based on this, please generate an appropriate exercise plan. It should be a specific plan including the type, frequency, number of repetitions, and intensity of exercise."

[2054] Implemented in this manner, the system of the present invention provides exercise planning and real-time feedback that takes into account the user's emotional state, resulting in a more effective and sustainable fitness program.

[2055] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2056] Step 1:

[2057] The user enters initial registration information into the application. The entered information includes name, gender, age, height, weight, fitness level, and fitness goal. This is the input, and the device sends it to the server. The entered data is stored on the server and used for subsequent processing.

[2058] Step 2:

[2059] The server uses a generative AI model to generate a personalized exercise plan based on the collected registration information. Specifically, the information stored in the database is passed to the model as input, and an exercise plan is generated as output. This exercise plan includes specific exercise types, frequency, number of repetitions, intensity, etc. The server then sends the generated exercise plan to the device.

[2060] Step 3:

[2061] The terminal displays the exercise plan received from the server to the user. The user starts exercising based on the displayed exercise plan. At this point, the exercise plan is the input and what the terminal displays is the output.

[2062] Step 4:

[2063] When a user exercises, the camera and sensors on the device collect exercise data in real time, including the type of exercise, number of repetitions, time, angle, etc. The collected exercise data is sent as input to the server, which receives it and stores it in a database.

[2064] Step 5:

[2065] The server analyzes the received exercise data using an AI engine. Specifically, it analyzes the input exercise data and evaluates the accuracy and effectiveness of the exercise. The analysis results are the output, and the calculations performed by the AI ​​engine are the data processing. The server generates real-time feedback based on the analysis results and sends it to the device.

[2066] Step 6:

[2067] The device displays the feedback sent from the server to the user, including proper exercise form and suggested corrections. This feedback is the output, and the device displays the specific movement.

[2068] Step 7:

[2069] The device uses a camera and microphone to collect the user's facial expressions and voice in real time, which is the input, and the collected emotional data is sent to the server, which is the output.

[2070] Step 8:

[2071] The server analyzes the collected emotional data using an emotion recognition engine. Specifically, it identifies the user's emotional state based on the input emotional data. The analysis results are the output, and the data processing by the emotion recognition engine is the operation.

[2072] Step 9:

[2073] The server adjusts the exercise plan based on the user's emotional state. For example, if the user feels stressed, it suggests reducing the exercise intensity. The adjusted exercise plan is the output, and the server sends it to the device.

[2074] Step 10:

[2075] The terminal displays the adjusted exercise plan to the user and prompts the user to take the next exercise step. This is the output, and the display on the terminal is the specific action.

[2076] These steps allow for exercise planning and real-time feedback that takes into account the user's emotional state.

[2077] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2078] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2079] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2080] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2081] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2082] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2083] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2084] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.j...

Claims

1. a means of collecting registration information from users; means for generating a personalized exercise plan based on the collected information; A means for providing the generated exercise plan to a user; A means for collecting and analyzing user exercise data in real time; means for providing real-time feedback based on the collected motion data; a means of providing exercise challenges and rewards to users; a means for collecting nutritional data of a user and generating a personalized meal plan; means for periodically analyzing exercise data and adjusting exercise plans; A system including:

2. 10. The system of claim 1, wherein users can earn points through exercise.

3. 10. The system of claim 1, wherein a user can cooperate or compete with other users in exercise.

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