system

Abstract

Provide a system. [Solution] A means for obtaining basic information and goal data of a user; means for generating an appearance image of the user after achieving the goal based on the goal data; means for generating an individual training menu based on the goal data and the user's fitness level; A means for analyzing exercise videos uploaded by users and evaluating and providing feedback on accurate exercise form; means for proposing an optimal meal plan based on the target data and the user's individual conditions; A way to track your progress and adjust your training and meal plans as needed; A system including:

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 today's world, an increasing number of people are seeking to maintain their health, lose weight, and build muscle. However, providing effective, personalized training and meal plans tailored to each individual's current condition and goals can be challenging. Furthermore, it can be difficult for individuals to self-evaluate the accuracy of their exercise form during training, leading to injury and reduced effectiveness due to improper exercise techniques. The present invention aims to solve these problems and provide a personal training system that allows users to achieve their goals efficiently and safely. [Means for solving the problem]

[0005] The present invention is a system that includes means for acquiring a user's basic information and goal data, means for generating an image of what the user will look like after achieving their goal based on the goal data, means for generating an individual training menu based on the goal data and the user's fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and the user's individual conditions, and means for recording progress and adjusting the training menu and meal plan as necessary. This allows the user to always receive appropriate training and dietary advice, and is effectively supported throughout the entire process of achieving their goal.

[0006] "User" refers to an individual who uses this system with the purpose of maintaining health, losing weight, or increasing muscle strength.

[0007] "Basic information" refers to personal information such as the user's height, weight, age, and gender, and is data used to understand the user's current health condition.

[0008] "Goal Data" refers to data that indicates specific health or fitness goals, such as weight loss or muscle gain, that a user wishes to achieve through the system.

[0009] The "appearance image" is image data for visually displaying the user's current and post-goal physical appearance.

[0010] "Workout Menu" refers to a series of exercise programs designed to help a user achieve their goals and that are tailored to a particular fitness level or physical strength.

[0011] "Exercise video" refers to video taken by a user while they are training, and is data for analyzing their exercise form.

[0012] The "analysis algorithm" is a program that analyzes exercise footage and evaluates and provides feedback on the accuracy of the user's exercise form.

[0013] "Meal Plan" refers to meal guidelines and suggested menus designed based on a User's goals and individual requirements.

[0014] "Progress data" refers to continuous data recorded by the user, such as daily exercise, diet, and weight changes, and indicates progress toward achieving goals.

[0015] "Feedback" is information that indicates evaluations of the user's exercise form and dietary content and areas for improvement.

[0016] The term "system" refers to an entire device and program including a series of means provided by the present invention. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle strength. This system acquires basic information and goal data about the user, and comprehensively generates training and meal plans, analyzes exercise form, and manages progress. Specific embodiments for implementing the present invention are described below.

[0039] Initial Setup

[0040] User Registration

[0041] User: After launching the app, enter basic information such as name, email address, password, height, and weight.

[0042] Terminal: Displays this information as a form and sends the input data to the server.

[0043] Server: Stores the received user information in a database and creates a user profile.

[0044] Log in

[0045] User: Enter your email address and password to log in.

[0046] Terminal: Sends authentication information to the server and displays the dashboard if authentication is successful.

[0047] Server: If authentication is successful, generate an authentication token and send it to the device.

[0048] goal setting

[0049] Goal Input

[0050] User: Enters fitness goal (e.g., lose 5 kg in 3 months) in the in-app goal setting screen.

[0051] Terminal: Sends target data to the server.

[0052] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[0053] Image generation

[0054] Morphing

[0055] User: Makes a request to see what it will look like after achieving the goal.

[0056] Terminal: Sends the request to the server.

[0057] Server: Based on the current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving the goal, and this is sent to the device.

[0058] Terminal: displays the generated image to the user.

[0059] Training menu generation

[0060] Plan creation

[0061] Server: Creates personalized training menus based on the user's goals, current fitness level, and previous training data.

[0062] Server: Sends the generated training menu to the terminal.

[0063] Terminal: Displays the training menu to the user.

[0064] Exercise form analysis

[0065] Video Analysis

[0066] User: Takes video of exercise during training and uploads the video.

[0067] Terminal: Sends the captured video to the server.

[0068] Server: Receives video data and runs exercise form analysis algorithms to evaluate accurate form and generate feedback.

[0069] Server: Sends feedback to the device.

[0070] Terminal: displays the feedback results to the user.

[0071] Meal plan suggestions

[0072] Plan Generation

[0073] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[0074] Server: Sends the generated meal plan to the device.

[0075] Terminal: Display the meal plan to the user.

[0076] Progress management

[0077] Data Entry and Management

[0078] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[0079] Terminal: Sends the entered progress data to the server.

[0080] Server: Stores the received progress data in a database, analyzes the user's progress, and adjusts training menus and meal plans as needed.

[0081] Server: Sends the adjusted plan to the device.

[0082] Device: Display the adjusted plan to the user.

[0083] Specific examples

[0084] For example, if a user sets a goal of "lose 5 kg in 3 months," the system operates as follows:

[0085] 1. After registering and logging in, enter "Lose 5 kg in 3 months" on the goal setting screen.

[0086] 2. The server retrieves the goal data and generates a personalized training menu based on it. The initial training menu includes 30 minutes of cardio and 15 minutes of strength training three times a week.

[0087] 3. The user takes a video of themselves training with a camera and uploads the video to the system.

[0088] 4. The server analyzes the uploaded video, evaluates whether the exercise form is correct, and provides necessary feedback.

[0089] 5. Furthermore, the server generates and presents a meal plan that takes into account calorie restriction and nutritional balance to help the user achieve their goals.

[0090] 6. The user enters daily progress data (e.g., diet, exercise, weight changes), and the server evaluates the progress based on this and adjusts the individual plan if necessary.

[0091] In this way, the system of the present invention allows users to always receive appropriate and personalized health management and training guidance, enabling them to progress efficiently toward their goals.

[0092] The processing flow will be explained below.

[0093] Step 1: User Registration

[0094] User: Launch the app and click the "New Registration" button.

[0095] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[0096] User: Enter the required information and press the send button.

[0097] Terminal: Sends the entered data to the server.

[0098] Server: Stores the received user information in a database and creates a user profile.

[0099] Step 2: Log in

[0100] User: Enter your email address and password and click the login button.

[0101] Terminal: Sends the entered data to the server.

[0102] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[0103] Terminal: Save the received authentication token and display the dashboard.

[0104] Step 3: Goal Setting

[0105] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[0106] Terminal: Sends the data from the target input form to the server.

[0107] Server: The received goal data is stored in a database and used as the basis for generating optimal training plans.

[0108] Step 4: Image generation

[0109] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[0110] Terminal: Sends requests to the server.

[0111] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[0112] Server: Sends the generated image to the terminal.

[0113] Terminal: displays the generated image to the user.

[0114] Step 5: Create a training menu

[0115] Server: Generates an individual training menu based on the user's goals, current fitness level, and past training data.

[0116] Server: Sends the generated training menu to the terminal.

[0117] Terminal: Displays the training menu to the user.

[0118] Step 6: Analyze your exercise form

[0119] User: Records exercise during training and uploads the video.

[0120] Device: Upload the captured video to the server.

[0121] Server: Receives uploaded video data and executes analysis algorithms.

[0122] Server: Evaluates the accuracy of the exercise form and generates the necessary feedback.

[0123] Server: Sends feedback data to the device.

[0124] Terminal: displays the feedback results to the user.

[0125] Step 7: Meal Plan Suggestion

[0126] Server: Generates an optimal meal plan based on the user's goals, current condition, allergy information, etc.

[0127] Server: Sends the generated meal plan to the device.

[0128] Terminal: Display the meal plan to the user.

[0129] Step 8: Track progress

[0130] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[0131] Terminal: Sends the entered progress data to the server.

[0132] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[0133] Server: Sends the adjusted plan to the device.

[0134] Device: Display the adjusted plan to the user.

[0135] Example 1

[0136] 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."

[0137] Conventional fitness and diet systems have problems in that they do not adequately propose detailed training menus and meal plans tailored to the user's individual needs, nor do they adequately analyze and provide feedback on exercise form. In particular, there is a demand for systems that can efficiently approach the goals set by the user. Without such systems, users may not receive appropriate guidance or adjustments to achieve their goals, which can result in a loss of motivation. Another issue is the lack of a function that reflects the user's progress data in real time and provides appropriate advice.

[0138] 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.

[0139] In this invention, the server includes: means for acquiring a user's basic information and goal data; means for generating an image of the user's appearance after achieving their goal based on the goal data; means for generating an individual training menu based on the goal data and the user's fitness level; means for analyzing exercise video data uploaded by the user and evaluating and providing feedback on accurate exercise form; means for proposing an optimal meal plan based on the goal data and the user's individual conditions; means for acquiring and recording the user's daily progress data and adjusting the training menu and meal plan as needed; and means for verifying authentication information and displaying the app's dashboard screen. This allows users to receive individually optimized training guidance and dietary advice, helping them efficiently achieve their goals. Furthermore, real-time feedback and plan adjustments based on the user's progress make it easier for them to maintain motivation.

[0140] "User" refers to an individual who uses the System.

[0141] "Basic information" refers to initial setting data such as the user's name, email address, password, height, and weight.

[0142] "Goal data" refers to the specific fitness or diet goal values ​​and details that a user wants to achieve.

[0143] The "appearance image" refers to image data that represents the virtual appearance of the user after achieving the goal.

[0144] "Fitness level" refers to information that indicates the user's current athletic ability and health condition.

[0145] A "training menu" refers to a plan that indicates the specific exercises and training content that a user will perform to achieve their goal.

[0146] "Exercise video data" refers to video data captured by a user while they are training.

[0147] "Form analysis" refers to the process of evaluating a user's exercise form and analyzing its accuracy based on their exercise video data.

[0148] "Feedback" refers to assessment and advice provided to a user regarding exercise form and progress.

[0149] "Meal Plan" refers to a meal plan suggested based on a user's goals and individual requirements.

[0150] "Progress data" refers to continuously recorded data such as a user's exercise, diet, and weight changes.

[0151] "Token" refers to a digital identifier used to identify an authenticated user's session.

[0152] "Dashboard" refers to a screen where users can check their progress and plans in one place through the app.

[0153] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle strength. This system acquires basic information and goal data about the user, and comprehensively generates training and meal plans, analyzes exercise form, and manages progress. Specific embodiments are described below.

[0154] Initial Setup

[0155] User Registration

[0156] The user launches the app and enters information such as name, email address, password, height, and weight on the input screen.

[0157] The device temporarily stores the user's input data and sends it to the server in JSON format.

[0158] The server validates the received data, stores it in a database (MySQL®), creates a new user profile, and returns a success message to the terminal.

[0159] Log in

[0160] The user enters their email address and password on the login screen.

[0161] The terminal transmits the entered authentication information to the server.

[0162] The server verifies the user information in the database and, if authentication is successful, generates a JWT (JSON Web Token).

[0163] The server returns the generated JWT to the terminal, which saves it and displays the dashboard screen.

[0164] goal setting

[0165] Goal Input

[0166] The user enters "lose 5 kg in 3 months" into the app's goal setting screen.

[0167] The device sends the entered goal data to the server in JSON format.

[0168] The server stores the received goal data in a database and generates a personalized training plan for the user based on the goals.

[0169] The server returns the generated training plan to the terminal, which displays it to the user.

[0170] Image generation

[0171] Morphing

[0172] The user makes a request to see what it will look like after achieving the goal.

[0173] The terminal sends a request to the server.

[0174] The server reads the current body shape data and runs the image generation algorithm using TENSORFLOW® along with the target data.

[0175] The server sends the generated image to the terminal, which displays the image to the user.

[0176] Training menu generation

[0177] Plan creation

[0178] The server obtains the user's goals, current fitness level, and past training data, and uses an algorithm to generate a personalized training menu.

[0179] The server transmits the generated training menu to the terminal.

[0180] The terminal displays a training menu to the user.

[0181] Exercise form analysis

[0182] Video Analysis

[0183] Users can record their workouts with a camera and upload the videos.

[0184] The device sends the captured video to the server.

[0185] The server receives the video data and runs a motion form analysis algorithm using OpenPose.

[0186] The server evaluates the user's exercise form based on the analysis results and generates feedback.

[0187] The server sends the feedback to the terminal, which displays the results to the user.

[0188] Meal plan suggestions

[0189] Plan Generation

[0190] The server takes the user's goals, current condition, and allergy information and uses an algorithm to generate an optimal meal plan.

[0191] The server transmits the generated meal plan to the terminal.

[0192] The terminal displays the meal plan to the user.

[0193] Progress management

[0194] Data Entry and Management

[0195] Users enter progress data such as daily exercise, diet, and weight changes into the app.

[0196] The terminal transmits the input data to the server.

[0197] The server stores the received progress data in a database and analyzes the progress using an algorithm.

[0198] The server will adjust your training menu and meal plan as needed based on your progress data.

[0199] The server sends the adjusted plan to the terminal, which displays it to the user.

[0200] Prompt Sentence Examples

[0201] "Generate what your goal will look like after you achieve it."

[0202] "Create a training plan to lose 5 kg in 3 months."

[0203] This system allows users to always receive appropriate and personalized health management and training guidance, enabling them to progress efficiently toward their goals.

[0204] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0205] Step 1:

[0206] User Registration

[0207] The user launches the app and enters information such as name, email address, password, height, and weight on the input screen.

[0208] Input: Name, email address, password, height, weight

[0209] The device temporarily stores the user's input data and sends it to the server in JSON format.

[0210] Output: User registration data in JSON format

[0211] The server validates the received data, stores it in a database (MySQL), creates a new user profile, and returns a success message to the terminal.

[0212] Input: JSON format user registration data

[0213] Output: Success message

[0214] Step 2:

[0215] Log in

[0216] The user enters their email address and password on the login screen.

[0217] Input: Email address, password

[0218] The terminal transmits the entered authentication information to the server.

[0219] Output: Credentials in JSON format

[0220] The server verifies the user information in the database and, if authentication is successful, generates a JWT (JSON Web Token).

[0221] Input: JSON formatted credentials

[0222] Output: JWT (JSON Web Token)

[0223] The server returns the generated JWT to the terminal, which saves it and displays the dashboard screen.

[0224] Input: JWT (JSON Web Token)

[0225] Output: Dashboard screen

[0226] Step 3:

[0227] Goal Input

[0228] The user enters "lose 5 kg in 3 months" into the app's goal setting screen.

[0229] Input: Goal data (e.g., "lose 5 kg in 3 months")

[0230] The device sends the entered goal data to the server in JSON format.

[0231] Output: Goal data in JSON format

[0232] The server stores the received goal data in a database and generates a personalized training plan for the user based on the goals.

[0233] Input: Goal data in JSON format

[0234] Data processing: Create a plan using a training plan generation algorithm

[0235] Output: Training Plan

[0236] The server returns the generated training plan to the terminal, which displays it to the user.

[0237] Input: Training plan

[0238] Output: Training plan display screen

[0239] Step 4:

[0240] Morphing Request

[0241] The user makes a request to see what it will look like after achieving the goal.

[0242] Input: Request data (check appearance after goal achievement)

[0243] The terminal sends the request to the server.

[0244] Output: Request data

[0245] The server reads the current body shape data and runs the image generation algorithm using TensorFlow along with the target data.

[0246] Input: Current body shape data, goal data

[0247] Data Computation: Morphing with Image Generation Algorithms

[0248] Output: Generated image

[0249] The server sends the generated image to the terminal, which displays the image to the user.

[0250] Input: Generated appearance image

[0251] Output: Image display screen

[0252] Step 5:

[0253] Creating a training menu

[0254] The server obtains the user's goals, current fitness level, and past training data, and uses an algorithm to generate a personalized training menu.

[0255] Input: Goal data, Fitness level, Training history

[0256] Data processing: Create a plan using a training menu generation algorithm

[0257] Output: Training menu

[0258] The server transmits the generated training menu to the terminal.

[0259] Input: Training Menu

[0260] Output: Training menu display screen

[0261] Step 6:

[0262] Exercise form analysis

[0263] Users can record their workouts with a camera and upload the videos.

[0264] Input: Exercise video data

[0265] The device sends the captured video to the server.

[0266] Output: Video data

[0267] The server receives the video data and runs a motion form analysis algorithm using OpenPose.

[0268] Input: Video data

[0269] Data processing: Form evaluation using exercise form analysis algorithms

[0270] Output: Evaluation results and feedback data

[0271] The server sends the feedback to the terminal, which displays the results to the user.

[0272] Input: Feedback data

[0273] Output: Feedback display screen

[0274] Step 7:

[0275] Meal plan suggestions

[0276] The server takes the user's goals, current condition, and allergy information and uses an algorithm to generate an optimal meal plan.

[0277] Input: goal data, current condition, allergy information

[0278] Data processing: Meal plan generation algorithm

[0279] Output: Meal plan

[0280] The server transmits the generated meal plan to the terminal.

[0281] Input: meal plan

[0282] Output: Meal plan display screen

[0283] Step 8:

[0284] Progress management

[0285] Users enter progress data such as daily exercise, diet, and weight changes into the app.

[0286] Input: Progress data (exercise, diet, weight changes)

[0287] The terminal transmits the input data to the server.

[0288] Output: Progress data

[0289] The server stores the received progress data in a database and uses an algorithm to analyze the progress.

[0290] Input: Progress data

[0291] Data Computing: Evaluation with Progress Data Analysis Algorithms

[0292] Output: Analysis results

[0293] The server will adjust your training menu and meal plan as needed based on your progress data.

[0294] Input: Analysis results

[0295] Output: Adjusted plan

[0296] The server sends the adjusted plan to the terminal, which displays it to the user.

[0297] Input: Adjusted plan

[0298] Output: Adjusted plan display screen

[0299] (Application example 1)

[0300] 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."

[0301] Conventional personal training systems have had difficulty individually examining a user's exercise form and dietary habits and providing feedback based on that. Furthermore, the generation of training and meal plans for achieving goals is based on general algorithms, which do not adequately reflect the user's individual circumstances. This makes it difficult to achieve effective training and health management.

[0302] 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.

[0303] In this invention, the server includes means for acquiring basic information and goal data of a user, means for generating an appearance image of the user after achieving the goal, means for generating an individual training menu based on the goal data and the user's fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and the user's individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, means for using a generative AI model to generate a training plan based on the user's goal settings, and means for generating prompts for the generative AI model, thereby enabling effective training and health management based on the user's individual conditions.

[0304] "User basic information" refers to personal information provided by a user, including name, email address, password, height, weight, etc.

[0305] "Goal data" refers to specific fitness or health goals set by the user, such as "lose 5 kilograms in 3 months."

[0306] An "appearance image" is an image generated to visually display the body shape and appearance of a user after achieving the goal set by the user.

[0307] "Fitness level" refers to the user's current physical strength and athletic ability, and is evaluated based on past training results and physical condition.

[0308] An "individual training menu" is an exercise plan that is optimized for each individual user and is generated based on the user's goal data and fitness level.

[0309] "Exercise footage" refers to video data taken by a user while they are training, and is used to analyze their exercise form.

[0310] "Exercise form" refers to the movements and postures that a user performs during training, and their accuracy and efficiency are evaluated.

[0311] "Feedback" refers to the evaluation and advice for improvement that the system provides to the user regarding their exercise form.

[0312] "Individual conditions" refers to information about the user's own health and lifestyle, such as the user's allergy information, favorite ingredients, and dietary restrictions.

[0313] A "meal plan" is a specific meal plan proposed based on the user's goal data and individual conditions to help the user achieve their goals.

[0314] "Progress" refers to the current exercise and dietary details, changes in weight and body shape, and the like, relative to the goal set by the user.

[0315] A "generative AI model" is an artificial intelligence model that uses deep learning and machine learning techniques to generate training plans and meal plans from user data.

[0316] A "prompt" is a document that provides instructions and input information to a generative AI model, and is created based on the user's current situation and goals.

[0317] The present invention is a personal training system that collects basic information and goal data of a user, generates an individual training menu and meal plan based on the collected information, and supports the user in maintaining their health and achieving their goals. This system is implemented as follows.

[0318] Initial Setup

[0319] The server obtains the user's basic information (such as name, email address, password, height, and weight) and stores it in a database. A user profile is created based on this information. The device (smartphone or household robot) displays a form and sends the data entered by the user to the server. The server also manages authentication information and generates an appropriate authentication token when the user logs in and sends it to the device.

[0320] goal setting

[0321] Users set fitness goals in an application on their device. For example, they can set a specific goal like "lose 5 kg in 3 months." The server receives this goal data and stores it in a database. Based on this, it generates a personalized training menu.

[0322] Training menu generation

[0323] The server generates a personalized training menu based on the user's goal data and fitness level. It uses a generative AI model and inputs prompts. These prompts contain information needed to help the user achieve their goals. For example,

[0324] To help users achieve their goals, please propose a personal training plan based on the following information:

[0325] Username: Example

[0326] Age: 35

[0327] Current weight: 75kg

[0328] Goal: Lose 5kg in 3 months

[0329] Fitness Level: Beginner

[0330] Allergies: None

[0331] This generated training menu is sent from the server to the terminal and displayed to the user.

[0332] Exercise form analysis

[0333] During exercise, users record their own training videos and upload them to a server via their device. The server receives the video data and runs an exercise form analysis algorithm (e.g., a deep learning model using Keras) to accurately evaluate their exercise form and provide feedback to the user.

[0334] Meal plan suggestions

[0335] The server generates an optimal meal plan based on the user's goals and individual conditions (allergy information, dietary preferences, etc.). This data is also processed using a generative AI model. The generated meal plan is sent from the server to the device and presented to the user.

[0336] Progress management

[0337] The user inputs their daily progress (exercise, diet, weight change, etc.) on the device. The server receives this progress data and stores it in a database. If necessary, the server adjusts the training menu and meal plan and provides the user with the latest plan.

[0338] This allows users to easily receive personal training at home and efficiently achieve their goals based on individual training and dietary advice.

[0339] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0340] Step 1: User Registration

[0341] The server receives basic information from the user (such as name, email address, password, height, and weight) and stores it in a database. The terminal displays the basic information entered by the user in a form and sends the information entered by the user to the server. The input is the user's basic information, and the output is the user's profile stored in the database.

[0342] Step 2: Log in

[0343] The server receives the authentication information (email address, password) entered by the user and checks it in the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. The terminal displays the generated authentication token and notifies the user that login was successful. The input is authentication information and the output is the authentication token.

[0344] Step 3: Goal Setting

[0345] A user sets a fitness goal (e.g., "lose 5 kg in 3 months") in an application on their device. This information is sent from the device to a server, which stores the goal data in a database. The input is the goal data, and the output is the goal data stored in the database.

[0346] Step 4: Create a training menu

[0347] The server uses a generative AI model to create prompts based on the user's goal data and fitness level. The generative AI model generates a training menu based on the prompts, and the server stores the generated menu in a database and sends it to the terminal. The terminal displays the training menu to the user. The input is the goal data and fitness level, and the output is the generated training menu.

[0348] Step 5: Analyze your exercise form

[0349] The user takes a video of themselves training on their device and uploads it to the server. The server receives the video data and runs an exercise form analysis algorithm (using Keras) to generate an analysis of their exercise form. The server stores the results in a database, generates feedback, and sends it to the device. The device displays the feedback to the user. The input is the exercise video, and the output is the feedback results.

[0350] Step 6: Meal plan suggestions

[0351] The server uses a generative AI model to generate a meal plan based on the user's goal data and individual conditions (allergy information, likes and dislikes, etc.), and stores it in a database. The server then sends the generated meal plan to the device, which displays it to the user. The input is the goal data and individual conditions, and the output is the generated meal plan.

[0352] Step 7: Track progress

[0353] The user inputs progress data, such as daily exercise, diet, and weight changes, into the device. The server receives this data, stores it in a database, and analyzes the progress. If necessary, the server adjusts the training menu and meal plan and sends the updated plan to the device. The device displays the adjusted plan to the user. The input is progress data, and the output is the adjusted training menu and meal plan.

[0354] 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.

[0355] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle, and further combines it with an emotion engine that recognizes the user's emotions. This system acquires the user's basic information and goal data, generates training plans and meal plans, analyzes exercise form, manages progress, and adjusts these plans and feedback based on the user's emotions. Specific embodiments for implementing the present invention are described below.

[0356] Initial Setup

[0357] User Registration

[0358] User: Launch the app and click the "New Registration" button.

[0359] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[0360] User: Enter the required information and press the send button.

[0361] Terminal: Sends the entered data to the server.

[0362] Server: Stores the received user information in a database and creates a user profile.

[0363] Log in

[0364] User: Enter your email address and password and click the login button.

[0365] Terminal: Sends the entered data to the server.

[0366] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[0367] Terminal: Save the received authentication token and display the dashboard.

[0368] goal setting

[0369] Goal Input

[0370] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[0371] Terminal: Sends the data from the target input form to the server.

[0372] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[0373] Image generation

[0374] Morphing

[0375] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[0376] Terminal: Sends the request to the server.

[0377] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[0378] Server: Sends the generated image to the terminal.

[0379] Terminal: displays the generated image to the user.

[0380] Training menu generation

[0381] Plan creation

[0382] Server: Creates personalized training menus based on the user's goals, current fitness level, and previous training data.

[0383] Server: Sends the generated training menu to the terminal.

[0384] Terminal: Displays the training menu to the user.

[0385] Exercise form analysis

[0386] Video Analysis

[0387] User: Records exercise during training and uploads the video.

[0388] Device: Upload the captured video to the server.

[0389] Server: Receives uploaded video data and executes analysis algorithms.

[0390] Server: Evaluates the accuracy of exercise form and generates feedback.

[0391] Server: Sends feedback data to the device.

[0392] Terminal: displays the feedback results to the user.

[0393] Meal plan suggestions

[0394] Plan Generation

[0395] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[0396] Server: Sends the generated meal plan to the device.

[0397] Terminal: Display the meal plan to the user.

[0398] emotion recognition

[0399] Introducing the Emotion Engine

[0400] Terminal: The emotion engine analyzes the user's facial expressions, voice tone, and text input.

[0401] Server: Receives the recognized emotion data and determines the user's current emotional state.

[0402] Server: Based on the emotional state, the training menu and feedback provided are adjusted appropriately.

[0403] Progress management

[0404] Data Entry and Management

[0405] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[0406] Terminal: Sends the entered progress data to the server.

[0407] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[0408] Server: Sends the adjusted plan to the device.

[0409] Device: Display the adjusted plan to the user.

[0410] Specific examples

[0411] For example, if a user sets a goal of "lose 5 kg in 3 months," the system operates as follows:

[0412] 1. After registering and logging in, enter "Lose 5 kg in 3 months" on the goal setting screen.

[0413] 2. The server retrieves the goal data and generates a personalized training menu based on it. The initial training menu includes 30 minutes of cardio and 15 minutes of strength training three times a week.

[0414] 3. The user takes a video of themselves training with a camera and uploads the video to the system.

[0415] 4. The server analyzes the uploaded video, evaluates whether the exercise form is correct, and provides necessary feedback.

[0416] 5. Furthermore, the server generates and presents a meal plan that takes into account calorie restriction and nutritional balance to help the user achieve their goals.

[0417] 6. The emotion engine recognizes the user's emotions, and if it determines that motivation is declining, it provides encouraging feedback and makes adjustments to increase motivation.

[0418] 7. The user enters daily progress data (e.g., diet, exercise, weight changes), and the server evaluates the progress based on this and adjusts the individual plan if necessary.

[0419] In this way, the system of the present invention allows users to always receive appropriate and personalized health management and training guidance, and the introduction of an emotion engine helps maintain and improve motivation, enabling users to make effective progress toward their goals.

[0420] The processing flow will be explained below.

[0421] Step 1: User Registration

[0422] User: Launch the app and click the "New Registration" button.

[0423] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[0424] User: Enter the required information and press the send button.

[0425] Terminal: Sends the entered data to the server.

[0426] Server: Stores the received user information in a database and creates a user profile.

[0427] Step 2: Log in

[0428] User: Enter your email address and password and click the login button.

[0429] Terminal: Sends the entered data to the server.

[0430] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[0431] Terminal: Save the received authentication token and display the dashboard.

[0432] Step 3: Goal Setting

[0433] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[0434] Terminal: Sends the data from the target input form to the server.

[0435] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[0436] Step 4: Image generation (morphing)

[0437] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[0438] Terminal: Sends the request to the server.

[0439] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[0440] Server: Sends the generated image to the terminal.

[0441] Terminal: displays the generated image to the user.

[0442] Step 5: Create a training menu

[0443] Server: Generates a personalized training menu based on the user's goals, current fitness level, and past training data.

[0444] Server: Sends the generated training menu to the terminal.

[0445] Terminal: Displays the training menu to the user.

[0446] Step 6: Analyze your exercise form

[0447] User: Records exercise during training and uploads the video.

[0448] Device: Upload the captured video to the server.

[0449] Server: Receives uploaded video data and executes analysis algorithms.

[0450] Server: Evaluates the accuracy of exercise form and generates feedback.

[0451] Server: Sends feedback data to the device.

[0452] Terminal: displays the feedback results to the user.

[0453] Step 7: Meal Plan Suggestion

[0454] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[0455] Server: Sends the generated meal plan to the device.

[0456] Terminal: Display the meal plan to the user.

[0457] Step 8: Emotion Recognition

[0458] Terminal: The emotion engine analyzes the user's facial expressions, voice tone, and text input.

[0459] Server: Receives the recognized emotion data and determines the user's current emotional state.

[0460] Server: Based on the emotional state, the training menu and feedback provided are adjusted appropriately.

[0461] Step 9: Track progress

[0462] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[0463] Terminal: Sends the entered progress data to the server.

[0464] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[0465] Server: Sends the adjusted plan to the device.

[0466] Device: Display the adjusted plan to the user.

[0467] Example 2

[0468] 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."

[0469] Conventional personal training systems lack the ability to generate personalized training and meal plans to help users achieve their goals, making progress management difficult, and they also lack the ability to adjust feedback based on the user's emotional state, making it difficult to maintain user motivation.

[0470] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring basic information and goal data of the user, means for generating an appearance image of the user after achieving the goal based on the goal data, means for generating an individual training menu based on the goal data and fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, and emotion recognition means for analyzing the user's facial expression, voice tone, and text input and adjusting the training menu and feedback content based on the results. This allows the user to receive individualized health management and training guidance, and makes it easier to maintain motivation through feedback adjustment based on the user's emotional state.

[0471] "User" means any individual or collective entity that uses this system.

[0472] "Basic information" is data for identifying a user, such as the user's name, email address, password, height, and weight.

[0473] "Goal Data" refers to specific fitness-related goals set by a user. An example would be "lose 5 kilograms in 3 months."

[0474] The "means for generating an appearance image" is a technical means for generating an appearance image after the user has achieved the goal based on the user's current body type data and goal data.

[0475] The "means for generating a training menu" refers to a technical means for creating an optimal training plan or exercise program for a user based on the goal data and the user's fitness level.

[0476] The "means for analyzing exercise video" refers to a technical means for analyzing the exercise video taken and uploaded by the user, and for evaluating and providing feedback on the accuracy of the exercise form.

[0477] The "means for proposing a meal plan" refers to a technical means for generating and proposing an optimal meal plan based on the user's goal data and individual conditions.

[0478] "Means for recording progress" refers to technical means for recording and managing a user's progress data, such as daily exercise, diet, and weight changes.

[0479] The "adjustment means" refers to a technical means for changing the training menu and meal plan as needed based on progress data, and providing the user with an optimal program.

[0480] "Emotion recognition means" refers to a technical means for analyzing a user's facial expressions, voice tone, text input, etc., and determining the user's emotional state based on the results, and adjusting the training menu and feedback content.

[0481] MODE FOR CARRYING OUT THE INVENTION

[0482] This invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle, and is also combined with an emotion engine that recognizes the user's emotions. This system acquires the user's basic information and goal data, generates training and meal plans, analyzes exercise form, manages progress, and adjusts these plans and feedback based on the user's emotions.

[0483] 1. User Registration

[0484] When a user launches the app and clicks the "New Registration" button, the device displays a form for the user to enter basic information such as name, email address, password, height, and weight. When the user enters the required information and presses the submit button, the data is sent to the server. The server stores the received user information in a database and creates a user profile.

[0485] 2. Log in

[0486] When a user enters their email address and password and presses the login button, the device sends the entered data to the server. The server checks the user information in the database, and if it matches, it generates an authentication token and sends it to the device. The device saves the received authentication token and displays the dashboard.

[0487] 3. Goal setting

[0488] When a user enters specific fitness goals into the app's "Goal Setting" screen and presses the submit button, the device sends the data from the goal entry form to the server, which stores the received goal data in a database and generates an optimal training plan based on it.

[0489] 4. Image Generation

[0490] When the user clicks the "Generate Image" button to check what they will look like after achieving their goal, the device sends the request to the server. The server uses an image generation algorithm to generate an image of what they will look like after achieving their goal based on the user's current body shape data and goal data. The generated image is sent to the device, which then displays it to the user.

[0491] 5. Training menu generation

[0492] The server creates a personalized training menu based on the user's goals, current fitness level, and previous training data, and sends the created training menu to the device, which then displays it to the user.

[0493] 6. Analysis of exercise form

[0494] When a user films their workout with a camera and uploads the video, the device uploads the video to a server. The server receives the uploaded video data and runs an analysis algorithm to evaluate the accuracy of the workout form and generate feedback. The feedback data is sent to the device, which displays it to the user.

[0495] 7. Meal plan suggestions

[0496] The server generates an optimal meal plan based on the user's goals, current condition, allergy information, etc. The generated meal plan is sent to the device, which then displays it to the user.

[0497] 8. Emotion recognition

[0498] Using the emotion engine, the device analyzes the user's facial expressions, voice tone, and text input. The server receives the recognized emotion data and determines the user's current emotional state. Based on the emotional state, the device appropriately adjusts the training menu and feedback provided.

[0499] 9. Progress Management

[0500] When the user enters progress data such as daily exercise, diet, and weight changes into the app, the device sends the entered progress data to the server. The server stores the received progress data in a database and evaluates the user's progress. If necessary, it adjusts the training menu and meal plan and sends it to the device. The device then displays the adjusted plan to the user.

[0501] Prompt Sentence Examples

[0502] "Please explain in detail the steps for user registration."

[0503] "Please provide a concrete example of how to lose 5 kg in 3 months."

[0504] "Please tell me more about how you analyze your exercise form and provide feedback."

[0505] "Please explain how you propose a meal plan."

[0506] These specific steps and functions enable the system of the present invention to provide the user with personalized health management and training guidance, as well as provide feedback and adjust plans that take into account the user's emotional state.

[0507] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0508] Program processing flow

[0509] Step 1: User Registration

[0510] Input: Basic information such as user name, email address, password, height, and weight

[0511] Processing: The user launches the app and clicks the "New Registration" button. The device displays a form for the user to enter basic information, and after filling it in, the user presses the submit button. The device sends the entered data to the server.

[0512] Data processing: The server stores the received user information in a database and creates a user profile.

[0513] Output: The user's basic information is saved in a database and a profile is created.

[0514] Specific operation: When the app is launched, a "New Registration" button is displayed on the main screen. When the user clicks this, a form requesting name, email address, password, etc. is displayed. When the user enters the required information and presses the submit button, the data is sent to the server.

[0515] Step 2: Log in

[0516] Input: Email address, Password

[0517] Process: The user enters their email address and password and presses the login button. The device sends the entered data to the server.

[0518] Data processing: The server compares the user information with that in the database, and if there is a match, generates an authentication token and sends it to the terminal.

[0519] Output: An authentication token is generated and sent to the device.

[0520] How it works: When a user enters their email address and password on the login screen and presses the "Login" button, the device sends this data to the server. The server compares the input information with existing user data in its database, and if there is a match, it generates an authentication token and sends it to the device.

[0521] Step 3: Goal Setting

[0522] Input: Fitness goal (e.g. lose 5 kg in 3 months)

[0523] Processing: The user enters specific fitness goals into the app's "Goal Setting" screen and presses the submit button. The device then sends the data from the goal entry form to the server.

[0524] Data processing: The server stores the received goal data in a database and generates an optimal training plan.

[0525] Output: Goal data is stored in a database and a training plan is generated.

[0526] Specific operation: The user enters specific goals on the "Goal Setting" screen and presses the send button. This data is sent to the server via the device. The server generates a training plan based on the received goal data.

[0527] Step 4: Image generation

[0528] Input: Current body shape data, goal data

[0529] Processing: The user clicks the "Generate Image" button to see what the image will look like after achieving the goal. The device sends the request to the server.

[0530] Data processing: The server uses an image generation algorithm to generate an image of what the user will look like after achieving their goal, based on the user's current body shape data and goal data.

[0531] Output: An image of the appearance after the goal is achieved is generated and sent to the device.

[0532] Specific operation: When the user clicks the "Generate Image" button, the device sends the request to the server, which then uses an image generation algorithm to generate an image based on the user's body shape data and target data.

[0533] Step 5: Create a training menu

[0534] Input: Goal data, Fitness level, Past training data

[0535] Processing: The server creates a personalized training menu based on the user's goals, fitness level, and previous training data.

[0536] Data processing: The server uses AI algorithms to generate the optimal training plan for the user.

[0537] Output: A training menu is generated and sent to the device.

[0538] How it works: The server uses an AI algorithm to generate a training menu based on your goals, fitness level, and past training data, and sends it to your device.

[0539] Step 6: Analyze your exercise form

[0540] Input: Exercise footage during training

[0541] Processing: The user takes a video of their workout with a camera and uploads the video. The device then uploads the video to the server.

[0542] Data processing: The server analyzes the uploaded video data using an analysis algorithm to evaluate the accuracy of the exercise form.

[0543] Output: Generate feedback and send it to the device.

[0544] How it works: The user takes a video of themselves training and uploads it to the system. The server then uses an analysis algorithm to evaluate the video and sends feedback to the device.

[0545] Step 7: Meal Plan Suggestion

[0546] Input: goal data, allergy information, food preferences

[0547] Processing: The server generates an optimal meal plan based on the user's goals, current condition, allergy information, food preferences, etc.

[0548] Data processing: Using AI algorithms to generate meal plans that take into account calorie restriction and nutritional balance.

[0549] Output: A meal plan is generated and sent to the device.

[0550] Specific operation: The server uses an AI algorithm to generate a meal plan taking into account goals, allergy information, food preferences, etc., and sends it to the device.

[0551] Step 8: Emotion Recognition

[0552] Input: Facial expressions, voice tone, text input

[0553] Processing: Using the emotion engine, the device analyzes the user's facial expressions, voice tone, and text input.

[0554] Data processing: The server receives the recognized emotion data and determines the user's current emotional state.

[0555] Output: Adjust the training menu and feedback content.

[0556] Specific operation: The device analyzes the user's emotions using an emotion engine, and the server adjusts the training menu and feedback based on the results.

[0557] Step 9: Track progress

[0558] Input: Progress data such as daily exercise, diet, and weight changes

[0559] Process: The user enters daily progress data into the app, and the device sends it to the server.

[0560] Data processing: The server stores the received progress data in a database and evaluates the progress using an AI algorithm.

[0561] Output: Adjust your training menu and meal plan as needed and send it to your device.

[0562] What it does: The user enters their daily progress into the app, and the server evaluates their progress based on that information, adjusts the plan as necessary, and sends it to the device.

[0563] (Application example 2)

[0564] 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."

[0565] While interest in fitness and health management is growing in modern society, providing personal training requires a lot of time and effort, and costs and resources are limited, especially when providing services at physical stores. Furthermore, it is difficult to provide feedback and support tailored to each user's emotional state and progress, making it difficult to maintain motivation. Furthermore, there is a demand for a unified service that covers everything from confirming proper exercise form to managing dietary habits when users receive training and instruction at physical stores.

[0566] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring basic information and goal data of the user, means for generating an appearance image of the user after achieving the goal based on the goal data, means for generating an individual training menu based on the goal data and the user's fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and the user's individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, means for analyzing the user's emotions and adjusting the training menu and feedback content based on the user's emotional state, and means for installing the system on a smart device (smart glasses or tablet) optimized for use in a physical store. This enables feedback and training adjustments based on emotions in real time in a physical store, enabling efficient maintenance of user motivation and comprehensive health management.

[0567] "Basic user information" refers to information necessary for creating training and meal plans, such as the user's name, height, weight, age, and gender.

[0568] "Goal Data" refers to specific fitness or health goals set by the user, such as "lose 5 kilograms in 3 months."

[0569] The "appearance image" is an image that visually shows the future body shape after the user achieves the goal, generated based on the user's current body shape data and goal data.

[0570] A "training menu" is an exercise program customized based on a user's goals and fitness level, including specific exercises, exercise frequency, and duration.

[0571] "Exercise video" is video data taken by a user while they are training, and is used to evaluate the accuracy of their exercise form.

[0572] "Exercise form" refers to the physical movements and posture of the user when exercising, and maintaining correct form leads to improved safety and effectiveness.

[0573] A "meal plan" is a meal menu suggested based on the user's goals and physical condition, taking into consideration nutritional balance and calorie restrictions.

[0574] "Progress" is data recorded by the user regarding daily exercise, diet, weight fluctuations, etc., and is used to evaluate progress toward goals.

[0575] "Emotional state" refers to the user's current emotions, analyzed based on the user's facial expressions, voice tone, text input, etc.

[0576] "Feedback content" refers to advice and encouraging messages provided based on the user's exercise form, progress, and emotional state.

[0577] A "smart device" is a device for use by a user, and in the present invention particularly refers to smart glasses or tablets.

[0578] This invention relates to a personal training system that helps users maintain their health, lose weight, and build muscle. The system acquires basic information and goal data from the user and generates individual training and meal plans. It can also recognize the user's emotions and adjust the plans and feedback accordingly.

[0579] Hardware and software used

[0580] Hardware: Smart glasses, tablets, cameras

[0581] Software: Emotion recognition engine (EmotionRecognition), training plan generation engine (TrainingRecommendation), database management system

[0582] Specific explanation of the process

[0583] 1. User Registration and Login:

[0584] The user uses a tablet to enter basic information and send it to the server, which stores it in a database.

[0585] If the user is already registered, they enter their email address and password on the login screen, and the server checks the information against the database.

[0586] 2. Goal Setting:

[0587] Users input their fitness goals using a tablet in the physical store, and the server generates an optimal training plan based on this goal data and displays it on the tablet.

[0588] 3. Training and meal plans provided:

[0589] The server generates personalized training and meal plans based on the user's goals and fitness level, which are displayed on a tablet or smart glasses.

[0590] 4. Real-time analysis of athletic form:

[0591] Cameras and smart glasses installed in the store capture footage of the workout, which is then sent to a server where an algorithm is run to assess the accuracy of the workout form, providing real-time feedback on the tablet or smart glasses.

[0592] 5. Emotion-aware feedback regulation:

[0593] An emotion recognition engine analyzes the user's emotional state based on camera footage, audio, and text input. The server then adjusts the training menu and feedback content based on the recognized emotions, providing encouraging messages as needed.

[0594] 6. Progress Management and Data Entry:

[0595] Users enter their daily exercise routines, dietary habits, weight fluctuations, etc. into a tablet, and this data is sent to a server, where progress is evaluated and the plan is adjusted as necessary.

[0596] Specific examples

[0597] For example, if a user sets a goal of "losing 5 kg in 3 months," the system will generate optimal training and meal plans based on this goal. Footage captured by the camera during training is used to analyze exercise form. Furthermore, if the system determines through an emotion recognition engine that the user's motivation is declining, appropriate feedback and encouraging messages will be displayed on the tablet or smart glasses.

[0598] Example prompt for a generative AI model:

[0599] "Given the user's current body shape data and goal data, generate an image of what they will look like after achieving their goal."

[0600] The above processing makes it possible to provide real-time feedback and adjust training according to emotions in a physical store, thereby maintaining user motivation and efficiently managing overall health.

[0601] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0602] Step 1:

[0603] A user launches the application using a tablet and clicks the "New Registration" button. They enter basic information such as their name, email address, password, height, and weight, and then presses the submit button. This input data is sent from the device to the server. The server stores the received user information in a database and creates a user profile.

[0604] Step 2:

[0605] The user logs in from the tablet using the registered email address and password. The device sends the entered authentication information to the server, which checks it against the user information in the database. If authentication is successful, the server generates an authentication token, sends it to the device, and displays the dashboard to the user.

[0606] Step 3:

[0607] The user opens the "Goal Setting" screen on the tablet and enters their specific fitness goals. The entered goal data is sent from the device to the server, which stores this information in a database. Based on the received goal data, the server generates an optimal training plan and sends it to the tablet.

[0608] Step 4:

[0609] During training, the user uses smart glasses or a camera to capture video of their exercise. This video data is then uploaded to a server via the device. The server receives the uploaded video data and runs an analysis algorithm to evaluate the accuracy of the exercise form. The server generates an evaluation result and appropriate feedback, which it then sends to the device. The device then displays the feedback to the user in real time.

[0610] Step 5:

[0611] The server proposes a customized meal plan based on the user's preset fitness goals and current health status. Taking into account the user's individual conditions (allergies, preferences, etc.), the server generates an optimal meal plan and sends it to the tablet. The device then displays the meal plan and allows the user to view the proposal.

[0612] Step 6:

[0613] The emotion engine analyzes the user's facial expressions, voice tone, and input text through a tablet or smart glasses to determine the user's emotional state. The server receives the analysis results and adjusts the training menu and feedback content according to the user's emotional state. Based on this, feedback messages and encouraging messages that interest the user are displayed on the device.

[0614] Step 7:

[0615] The user enters progress data, such as daily exercise, diet, and weight fluctuations, into a tablet, and the device sends the data to a server. The server stores the received progress data in a database and evaluates the user's progress. Based on the evaluation results, the training menu and meal plan are adjusted as necessary, and a new plan is generated. The new plan is then sent to the device and displayed to the user.

[0616] Through the above process, the system provides comprehensive support for users when receiving personal training at a physical store, and can flexibly adapt to the user's emotional state and progress.

[0617] 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.

[0618] 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.

[0619] 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.

[0620] [Second embodiment]

[0621] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0622] 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.

[0623] 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).

[0624] 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.

[0625] 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.

[0626] 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).

[0627] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0628] 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.

[0629] 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.

[0630] 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.

[0631] In the smart glasses 214, 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.

[0632] 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."

[0633] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle strength. This system acquires basic information and goal data about the user, and comprehensively generates training and meal plans, analyzes exercise form, and manages progress. Specific embodiments for implementing the present invention are described below.

[0634] Initial Setup

[0635] User Registration

[0636] User: After launching the app, enter basic information such as name, email address, password, height, and weight.

[0637] Terminal: Displays this information as a form and sends the input data to the server.

[0638] Server: Stores the received user information in a database and creates a user profile.

[0639] Log in

[0640] User: Enter your email address and password to log in.

[0641] Terminal: Sends authentication information to the server and displays the dashboard if authentication is successful.

[0642] Server: If authentication is successful, generate an authentication token and send it to the device.

[0643] goal setting

[0644] Goal Input

[0645] User: Enters fitness goal (e.g., lose 5 kg in 3 months) in the in-app goal setting screen.

[0646] Terminal: Sends target data to the server.

[0647] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[0648] Image generation

[0649] Morphing

[0650] User: Makes a request to see what it will look like after achieving the goal.

[0651] Terminal: Sends the request to the server.

[0652] Server: Based on the current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving the goal, and this is sent to the device.

[0653] Terminal: displays the generated image to the user.

[0654] Training menu generation

[0655] Plan creation

[0656] Server: Creates personalized training menus based on the user's goals, current fitness level, and previous training data.

[0657] Server: Sends the generated training menu to the terminal.

[0658] Terminal: Displays the training menu to the user.

[0659] Exercise form analysis

[0660] Video Analysis

[0661] User: Takes video of exercise during training and uploads the video.

[0662] Terminal: Sends the captured video to the server.

[0663] Server: Receives video data and runs exercise form analysis algorithms to evaluate accurate form and generate feedback.

[0664] Server: Sends feedback to the device.

[0665] Terminal: displays the feedback results to the user.

[0666] Meal plan suggestions

[0667] Plan Generation

[0668] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[0669] Server: Sends the generated meal plan to the device.

[0670] Terminal: Display the meal plan to the user.

[0671] Progress management

[0672] Data Entry and Management

[0673] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[0674] Terminal: Sends the entered progress data to the server.

[0675] Server: Stores the received progress data in a database, analyzes the user's progress, and adjusts training menus and meal plans as needed.

[0676] Server: Sends the adjusted plan to the device.

[0677] Device: Display the adjusted plan to the user.

[0678] Specific examples

[0679] For example, if a user sets a goal of "lose 5 kg in 3 months," the system operates as follows:

[0680] 1. After registering and logging in, enter "Lose 5 kg in 3 months" on the goal setting screen.

[0681] 2. The server retrieves the goal data and generates a personalized training menu based on it. The initial training menu includes 30 minutes of cardio and 15 minutes of strength training three times a week.

[0682] 3. The user takes a video of themselves training with a camera and uploads the video to the system.

[0683] 4. The server analyzes the uploaded video, evaluates whether the exercise form is correct, and provides necessary feedback.

[0684] 5. Furthermore, the server generates and presents a meal plan that takes into account calorie restriction and nutritional balance to help the user achieve their goals.

[0685] 6. The user enters daily progress data (e.g., diet, exercise, weight changes), and the server evaluates the progress based on this and adjusts the individual plan if necessary.

[0686] In this way, the system of the present invention allows users to always receive appropriate and personalized health management and training guidance, enabling them to progress efficiently toward their goals.

[0687] The processing flow will be explained below.

[0688] Step 1: User Registration

[0689] User: Launch the app and click the "New Registration" button.

[0690] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[0691] User: Enter the required information and press the send button.

[0692] Terminal: Sends the entered data to the server.

[0693] Server: Stores the received user information in a database and creates a user profile.

[0694] Step 2: Log in

[0695] User: Enter your email address and password and click the login button.

[0696] Terminal: Sends the entered data to the server.

[0697] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[0698] Terminal: Save the received authentication token and display the dashboard.

[0699] Step 3: Goal Setting

[0700] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[0701] Terminal: Sends the data from the target input form to the server.

[0702] Server: The received goal data is stored in a database and used as the basis for generating optimal training plans.

[0703] Step 4: Image generation

[0704] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[0705] Terminal: Sends requests to the server.

[0706] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[0707] Server: Sends the generated image to the terminal.

[0708] Terminal: displays the generated image to the user.

[0709] Step 5: Create a training menu

[0710] Server: Generates an individual training menu based on the user's goals, current fitness level, and past training data.

[0711] Server: Sends the generated training menu to the terminal.

[0712] Terminal: Displays the training menu to the user.

[0713] Step 6: Analyze your exercise form

[0714] User: Records exercise during training and uploads the video.

[0715] Device: Upload the captured video to the server.

[0716] Server: Receives uploaded video data and executes analysis algorithms.

[0717] Server: Evaluates the accuracy of the exercise form and generates the necessary feedback.

[0718] Server: Sends feedback data to the device.

[0719] Terminal: displays the feedback results to the user.

[0720] Step 7: Meal Plan Suggestion

[0721] Server: Generates an optimal meal plan based on the user's goals, current condition, allergy information, etc.

[0722] Server: Sends the generated meal plan to the device.

[0723] Terminal: Display the meal plan to the user.

[0724] Step 8: Track progress

[0725] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[0726] Terminal: Sends the entered progress data to the server.

[0727] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[0728] Server: Sends the adjusted plan to the device.

[0729] Device: Display the adjusted plan to the user.

[0730] Example 1

[0731] 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."

[0732] Conventional fitness and diet systems have problems in that they do not adequately propose detailed training menus and meal plans tailored to the user's individual needs, nor do they adequately analyze and provide feedback on exercise form. In particular, there is a demand for systems that can efficiently approach the goals set by the user. Without such systems, users may not receive appropriate guidance or adjustments to achieve their goals, which can result in a loss of motivation. Another issue is the lack of a function that reflects the user's progress data in real time and provides appropriate advice.

[0733] 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.

[0734] In this invention, the server includes: means for acquiring a user's basic information and goal data; means for generating an image of the user's appearance after achieving their goal based on the goal data; means for generating an individual training menu based on the goal data and the user's fitness level; means for analyzing exercise video data uploaded by the user and evaluating and providing feedback on accurate exercise form; means for proposing an optimal meal plan based on the goal data and the user's individual conditions; means for acquiring and recording the user's daily progress data and adjusting the training menu and meal plan as needed; and means for verifying authentication information and displaying the app's dashboard screen. This allows users to receive individually optimized training guidance and dietary advice, helping them efficiently achieve their goals. Furthermore, real-time feedback and plan adjustments based on the user's progress make it easier for them to maintain motivation.

[0735] "User" refers to an individual who uses the System.

[0736] "Basic information" refers to initial setting data such as the user's name, email address, password, height, and weight.

[0737] "Goal data" refers to the specific fitness or diet goal values ​​and details that a user wants to achieve.

[0738] The "appearance image" refers to image data that represents the virtual appearance of the user after achieving the goal.

[0739] "Fitness level" refers to information that indicates the user's current athletic ability and health condition.

[0740] A "training menu" refers to a plan that indicates the specific exercises and training content that a user will perform to achieve their goal.

[0741] "Exercise video data" refers to video data captured by a user while they are training.

[0742] "Form analysis" refers to the process of evaluating a user's exercise form and analyzing its accuracy based on their exercise video data.

[0743] "Feedback" refers to assessment and advice provided to a user regarding exercise form and progress.

[0744] "Meal Plan" refers to a meal plan suggested based on a user's goals and individual requirements.

[0745] "Progress data" refers to continuously recorded data such as a user's exercise, diet, and weight changes.

[0746] "Token" refers to a digital identifier used to identify an authenticated user's session.

[0747] "Dashboard" refers to a screen where users can check their progress and plans in one place through the app.

[0748] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle strength. This system acquires basic information and goal data about the user, and comprehensively generates training and meal plans, analyzes exercise form, and manages progress. Specific embodiments are described below.

[0749] Initial Setup

[0750] User Registration

[0751] The user launches the app and enters information such as name, email address, password, height, and weight on the input screen.

[0752] The device temporarily stores the user's input data and sends it to the server in JSON format.

[0753] The server validates the received data, stores it in a database (MySQL), creates a new user profile, and returns a success message to the terminal.

[0754] Log in

[0755] The user enters their email address and password on the login screen.

[0756] The terminal transmits the entered authentication information to the server.

[0757] The server verifies the user information in the database and, if authentication is successful, generates a JWT (JSON Web Token).

[0758] The server returns the generated JWT to the terminal, which saves it and displays the dashboard screen.

[0759] goal setting

[0760] Goal Input

[0761] The user enters "lose 5 kg in 3 months" into the app's goal setting screen.

[0762] The device sends the entered goal data to the server in JSON format.

[0763] The server stores the received goal data in a database and generates a personalized training plan for the user based on the goals.

[0764] The server returns the generated training plan to the terminal, which displays it to the user.

[0765] Image generation

[0766] Morphing

[0767] The user makes a request to see what it will look like after achieving the goal.

[0768] The terminal sends a request to the server.

[0769] The server reads the current body shape data and runs the image generation algorithm using TensorFlow along with the target data.

[0770] The server sends the generated image to the terminal, which displays the image to the user.

[0771] Training menu generation

[0772] Plan creation

[0773] The server obtains the user's goals, current fitness level, and past training data, and uses an algorithm to generate a personalized training menu.

[0774] The server transmits the generated training menu to the terminal.

[0775] The terminal displays a training menu to the user.

[0776] Exercise form analysis

[0777] Video Analysis

[0778] Users can record their workouts with a camera and upload the videos.

[0779] The device sends the captured video to the server.

[0780] The server receives the video data and runs a motion form analysis algorithm using OpenPose.

[0781] The server evaluates the user's exercise form based on the analysis results and generates feedback.

[0782] The server sends the feedback to the terminal, which displays the results to the user.

[0783] Meal plan suggestions

[0784] Plan Generation

[0785] The server takes the user's goals, current condition, and allergy information and uses an algorithm to generate an optimal meal plan.

[0786] The server transmits the generated meal plan to the terminal.

[0787] The terminal displays the meal plan to the user.

[0788] Progress management

[0789] Data Entry and Management

[0790] Users enter progress data such as daily exercise, diet, and weight changes into the app.

[0791] The terminal transmits the input data to the server.

[0792] The server stores the received progress data in a database and analyzes the progress using an algorithm.

[0793] The server will adjust your training menu and meal plan as needed based on your progress data.

[0794] The server sends the adjusted plan to the terminal, which displays it to the user.

[0795] Prompt Sentence Examples

[0796] "Generate what your goal will look like after you achieve it."

[0797] "Create a training plan to lose 5 kg in 3 months."

[0798] This system allows users to always receive appropriate and personalized health management and training guidance, enabling them to progress efficiently toward their goals.

[0799] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0800] Step 1:

[0801] User Registration

[0802] The user launches the app and enters information such as name, email address, password, height, and weight on the input screen.

[0803] Input: Name, email address, password, height, weight

[0804] The device temporarily stores the user's input data and sends it to the server in JSON format.

[0805] Output: User registration data in JSON format

[0806] The server validates the received data, stores it in a database (MySQL), creates a new user profile, and returns a success message to the terminal.

[0807] Input: JSON format user registration data

[0808] Output: Success message

[0809] Step 2:

[0810] Log in

[0811] The user enters their email address and password on the login screen.

[0812] Input: Email address, password

[0813] The terminal transmits the entered authentication information to the server.

[0814] Output: Credentials in JSON format

[0815] The server verifies the user information in the database and, if authentication is successful, generates a JWT (JSON Web Token).

[0816] Input: JSON formatted credentials

[0817] Output: JWT (JSON Web Token)

[0818] The server returns the generated JWT to the terminal, which saves it and displays the dashboard screen.

[0819] Input: JWT (JSON Web Token)

[0820] Output: Dashboard screen

[0821] Step 3:

[0822] Goal Input

[0823] The user enters "lose 5 kg in 3 months" into the app's goal setting screen.

[0824] Input: Goal data (e.g., "lose 5 kg in 3 months")

[0825] The device sends the entered goal data to the server in JSON format.

[0826] Output: Goal data in JSON format

[0827] The server stores the received goal data in a database and generates a personalized training plan for the user based on the goals.

[0828] Input: Goal data in JSON format

[0829] Data processing: Create a plan using a training plan generation algorithm

[0830] Output: Training Plan

[0831] The server returns the generated training plan to the terminal, which displays it to the user.

[0832] Input: Training plan

[0833] Output: Training plan display screen

[0834] Step 4:

[0835] Morphing Request

[0836] The user makes a request to see what it will look like after achieving the goal.

[0837] Input: Request data (check appearance after goal achievement)

[0838] The terminal sends the request to the server.

[0839] Output: Request data

[0840] The server reads the current body shape data and runs the image generation algorithm using TensorFlow along with the target data.

[0841] Input: Current body shape data, goal data

[0842] Data Computation: Morphing with Image Generation Algorithms

[0843] Output: Generated image

[0844] The server sends the generated image to the terminal, which displays the image to the user.

[0845] Input: Generated appearance image

[0846] Output: Image display screen

[0847] Step 5:

[0848] Creating a training menu

[0849] The server obtains the user's goals, current fitness level, and past training data, and uses an algorithm to generate a personalized training menu.

[0850] Input: Goal data, Fitness level, Training history

[0851] Data processing: Create a plan using a training menu generation algorithm

[0852] Output: Training menu

[0853] The server transmits the generated training menu to the terminal.

[0854] Input: Training Menu

[0855] Output: Training menu display screen

[0856] Step 6:

[0857] Exercise form analysis

[0858] Users can record their workouts with a camera and upload the videos.

[0859] Input: Exercise video data

[0860] The device sends the captured video to the server.

[0861] Output: Video data

[0862] The server receives the video data and runs a motion form analysis algorithm using OpenPose.

[0863] Input: Video data

[0864] Data processing: Form evaluation using exercise form analysis algorithms

[0865] Output: Evaluation results and feedback data

[0866] The server sends the feedback to the terminal, which displays the results to the user.

[0867] Input: Feedback data

[0868] Output: Feedback display screen

[0869] Step 7:

[0870] Meal plan suggestions

[0871] The server takes the user's goals, current condition, and allergy information and uses an algorithm to generate an optimal meal plan.

[0872] Input: goal data, current condition, allergy information

[0873] Data processing: Meal plan generation algorithm

[0874] Output: Meal plan

[0875] The server transmits the generated meal plan to the terminal.

[0876] Input: meal plan

[0877] Output: Meal plan display screen

[0878] Step 8:

[0879] Progress management

[0880] Users enter progress data such as daily exercise, diet, and weight changes into the app.

[0881] Input: Progress data (exercise, diet, weight changes)

[0882] The terminal transmits the input data to the server.

[0883] Output: Progress data

[0884] The server stores the received progress data in a database and uses an algorithm to analyze the progress.

[0885] Input: Progress data

[0886] Data Computing: Evaluation with Progress Data Analysis Algorithms

[0887] Output: Analysis results

[0888] The server will adjust your training menu and meal plan as needed based on your progress data.

[0889] Input: Analysis results

[0890] Output: Adjusted plan

[0891] The server sends the adjusted plan to the terminal, which displays it to the user.

[0892] Input: Adjusted plan

[0893] Output: Adjusted plan display screen

[0894] (Application example 1)

[0895] 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."

[0896] Conventional personal training systems have had difficulty individually examining a user's exercise form and dietary habits and providing feedback based on that. Furthermore, the generation of training and meal plans for achieving goals is based on general algorithms, which do not adequately reflect the user's individual circumstances. This makes it difficult to achieve effective training and health management.

[0897] 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.

[0898] In this invention, the server includes means for acquiring basic information and goal data of a user, means for generating an appearance image of the user after achieving the goal, means for generating an individual training menu based on the goal data and the user's fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and the user's individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, means for using a generative AI model to generate a training plan based on the user's goal settings, and means for generating prompts for the generative AI model, thereby enabling effective training and health management based on the user's individual conditions.

[0899] "User basic information" refers to personal information provided by a user, including name, email address, password, height, weight, etc.

[0900] "Goal data" refers to specific fitness or health goals set by the user, such as "lose 5 kilograms in 3 months."

[0901] An "appearance image" is an image generated to visually display the body shape and appearance of a user after achieving the goal set by the user.

[0902] "Fitness level" refers to the user's current physical strength and athletic ability, and is evaluated based on past training results and physical condition.

[0903] An "individual training menu" is an exercise plan that is optimized for each individual user and is generated based on the user's goal data and fitness level.

[0904] "Exercise footage" refers to video data taken by a user while they are training, and is used to analyze their exercise form.

[0905] "Exercise form" refers to the movements and postures that a user performs during training, and their accuracy and efficiency are evaluated.

[0906] "Feedback" refers to the evaluation and advice for improvement that the system provides to the user regarding their exercise form.

[0907] "Individual conditions" refers to information about the user's own health and lifestyle, such as the user's allergy information, favorite ingredients, and dietary restrictions.

[0908] A "meal plan" is a specific meal plan proposed based on the user's goal data and individual conditions to help the user achieve their goals.

[0909] "Progress" refers to the current exercise and dietary details, changes in weight and body shape, and the like, relative to the goal set by the user.

[0910] A "generative AI model" is an artificial intelligence model that uses deep learning and machine learning techniques to generate training plans and meal plans from user data.

[0911] A "prompt" is a document that provides instructions and input information to a generative AI model, and is created based on the user's current situation and goals.

[0912] The present invention is a personal training system that collects basic information and goal data of a user, generates an individual training menu and meal plan based on the collected information, and supports the user in maintaining their health and achieving their goals. This system is implemented as follows.

[0913] Initial Setup

[0914] The server obtains the user's basic information (such as name, email address, password, height, and weight) and stores it in a database. A user profile is created based on this information. The device (smartphone or household robot) displays a form and sends the data entered by the user to the server. The server also manages authentication information and generates an appropriate authentication token when the user logs in and sends it to the device.

[0915] goal setting

[0916] Users set fitness goals in an application on their device. For example, they can set a specific goal like "lose 5 kg in 3 months." The server receives this goal data and stores it in a database. Based on this, it generates a personalized training menu.

[0917] Training menu generation

[0918] The server generates a personalized training menu based on the user's goal data and fitness level. It uses a generative AI model and inputs prompts. These prompts contain information needed to help the user achieve their goals. For example,

[0919] To help users achieve their goals, please propose a personal training plan based on the following information:

[0920] Username: Example

[0921] Age: 35

[0922] Current weight: 75kg

[0923] Goal: Lose 5kg in 3 months

[0924] Fitness Level: Beginner

[0925] Allergies: None

[0926] This generated training menu is sent from the server to the terminal and displayed to the user.

[0927] Exercise form analysis

[0928] During exercise, users record their own training videos and upload them to a server via their device. The server receives the video data and runs an exercise form analysis algorithm (e.g., a deep learning model using Keras) to accurately evaluate their exercise form and provide feedback to the user.

[0929] Meal plan suggestions

[0930] The server generates an optimal meal plan based on the user's goals and individual conditions (allergy information, dietary preferences, etc.). This data is also processed using a generative AI model. The generated meal plan is sent from the server to the device and presented to the user.

[0931] Progress management

[0932] The user inputs their daily progress (exercise, diet, weight change, etc.) on the device. The server receives this progress data and stores it in a database. If necessary, the server adjusts the training menu and meal plan and provides the user with the latest plan.

[0933] This allows users to easily receive personal training at home and efficiently achieve their goals based on individual training and dietary advice.

[0934] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0935] Step 1: User Registration

[0936] The server receives basic information from the user (such as name, email address, password, height, and weight) and stores it in a database. The terminal displays the basic information entered by the user in a form and sends the information entered by the user to the server. The input is the user's basic information, and the output is the user's profile stored in the database.

[0937] Step 2: Log in

[0938] The server receives the authentication information (email address, password) entered by the user and checks it in the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. The terminal displays the generated authentication token and notifies the user that login was successful. The input is authentication information and the output is the authentication token.

[0939] Step 3: Goal Setting

[0940] A user sets a fitness goal (e.g., "lose 5 kg in 3 months") in an application on their device. This information is sent from the device to a server, which stores the goal data in a database. The input is the goal data, and the output is the goal data stored in the database.

[0941] Step 4: Create a training menu

[0942] The server uses a generative AI model to create prompts based on the user's goal data and fitness level. The generative AI model generates a training menu based on the prompts, and the server stores the generated menu in a database and sends it to the terminal. The terminal displays the training menu to the user. The input is the goal data and fitness level, and the output is the generated training menu.

[0943] Step 5: Analyze your exercise form

[0944] The user takes a video of themselves training on their device and uploads it to the server. The server receives the video data and runs an exercise form analysis algorithm (using Keras) to generate an analysis of their exercise form. The server stores the results in a database, generates feedback, and sends it to the device. The device displays the feedback to the user. The input is the exercise video, and the output is the feedback results.

[0945] Step 6: Meal plan suggestions

[0946] The server uses a generative AI model to generate a meal plan based on the user's goal data and individual conditions (allergy information, likes and dislikes, etc.), and stores it in a database. The server then sends the generated meal plan to the device, which displays it to the user. The input is the goal data and individual conditions, and the output is the generated meal plan.

[0947] Step 7: Track progress

[0948] The user inputs progress data, such as daily exercise, diet, and weight changes, into the device. The server receives this data, stores it in a database, and analyzes the progress. If necessary, the server adjusts the training menu and meal plan and sends the updated plan to the device. The device displays the adjusted plan to the user. The input is progress data, and the output is the adjusted training menu and meal plan.

[0949] 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.

[0950] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle, and further combines it with an emotion engine that recognizes the user's emotions. This system acquires the user's basic information and goal data, generates training plans and meal plans, analyzes exercise form, manages progress, and adjusts these plans and feedback based on the user's emotions. Specific embodiments for implementing the present invention are described below.

[0951] Initial Setup

[0952] User Registration

[0953] User: Launch the app and click the "New Registration" button.

[0954] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[0955] User: Enter the required information and press the send button.

[0956] Terminal: Sends the entered data to the server.

[0957] Server: Stores the received user information in a database and creates a user profile.

[0958] Log in

[0959] User: Enter your email address and password and click the login button.

[0960] Terminal: Sends the entered data to the server.

[0961] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[0962] Terminal: Save the received authentication token and display the dashboard.

[0963] goal setting

[0964] Goal Input

[0965] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[0966] Terminal: Sends the data from the target input form to the server.

[0967] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[0968] Image generation

[0969] Morphing

[0970] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[0971] Terminal: Sends the request to the server.

[0972] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[0973] Server: Sends the generated image to the terminal.

[0974] Terminal: displays the generated image to the user.

[0975] Training menu generation

[0976] Plan creation

[0977] Server: Creates personalized training menus based on the user's goals, current fitness level, and previous training data.

[0978] Server: Sends the generated training menu to the terminal.

[0979] Terminal: Displays the training menu to the user.

[0980] Exercise form analysis

[0981] Video Analysis

[0982] User: Records exercise during training and uploads the video.

[0983] Device: Upload the captured video to the server.

[0984] Server: Receives uploaded video data and executes analysis algorithms.

[0985] Server: Evaluates the accuracy of exercise form and generates feedback.

[0986] Server: Sends feedback data to the device.

[0987] Terminal: displays the feedback results to the user.

[0988] Meal plan suggestions

[0989] Plan Generation

[0990] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[0991] Server: Sends the generated meal plan to the device.

[0992] Terminal: Display the meal plan to the user.

[0993] emotion recognition

[0994] Introducing the Emotion Engine

[0995] Terminal: The emotion engine analyzes the user's facial expressions, voice tone, and text input.

[0996] Server: Receives the recognized emotion data and determines the user's current emotional state.

[0997] Server: Based on the emotional state, the training menu and feedback provided are adjusted appropriately.

[0998] Progress management

[0999] Data Entry and Management

[1000] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[1001] Terminal: Sends the entered progress data to the server.

[1002] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[1003] Server: Sends the adjusted plan to the device.

[1004] Device: Display the adjusted plan to the user.

[1005] Specific examples

[1006] For example, if a user sets a goal of "lose 5 kg in 3 months," the system operates as follows:

[1007] 1. After registering and logging in, enter "Lose 5 kg in 3 months" on the goal setting screen.

[1008] 2. The server retrieves the goal data and generates a personalized training menu based on it. The initial training menu includes 30 minutes of cardio and 15 minutes of strength training three times a week.

[1009] 3. The user takes a video of themselves training with a camera and uploads the video to the system.

[1010] 4. The server analyzes the uploaded video, evaluates whether the exercise form is correct, and provides necessary feedback.

[1011] 5. Furthermore, the server generates and presents a meal plan that takes into account calorie restriction and nutritional balance to help the user achieve their goals.

[1012] 6. The emotion engine recognizes the user's emotions, and if it determines that motivation is declining, it provides encouraging feedback and makes adjustments to increase motivation.

[1013] 7. The user enters daily progress data (e.g., diet, exercise, weight changes), and the server evaluates the progress based on this and adjusts the individual plan if necessary.

[1014] In this way, the system of the present invention allows users to always receive appropriate and personalized health management and training guidance, and the introduction of an emotion engine helps maintain and improve motivation, enabling users to make effective progress toward their goals.

[1015] The processing flow will be explained below.

[1016] Step 1: User Registration

[1017] User: Launch the app and click the "New Registration" button.

[1018] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[1019] User: Enter the required information and press the send button.

[1020] Terminal: Sends the entered data to the server.

[1021] Server: Stores the received user information in a database and creates a user profile.

[1022] Step 2: Log in

[1023] User: Enter your email address and password and click the login button.

[1024] Terminal: Sends the entered data to the server.

[1025] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[1026] Terminal: Save the received authentication token and display the dashboard.

[1027] Step 3: Goal Setting

[1028] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[1029] Terminal: Sends the data from the target input form to the server.

[1030] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[1031] Step 4: Image generation (morphing)

[1032] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[1033] Terminal: Sends the request to the server.

[1034] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[1035] Server: Sends the generated image to the terminal.

[1036] Terminal: displays the generated image to the user.

[1037] Step 5: Create a training menu

[1038] Server: Generates a personalized training menu based on the user's goals, current fitness level, and past training data.

[1039] Server: Sends the generated training menu to the terminal.

[1040] Terminal: Displays the training menu to the user.

[1041] Step 6: Analyze your exercise form

[1042] User: Records exercise during training and uploads the video.

[1043] Device: Upload the captured video to the server.

[1044] Server: Receives uploaded video data and executes analysis algorithms.

[1045] Server: Evaluates the accuracy of exercise form and generates feedback.

[1046] Server: Sends feedback data to the device.

[1047] Terminal: displays the feedback results to the user.

[1048] Step 7: Meal Plan Suggestion

[1049] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[1050] Server: Sends the generated meal plan to the device.

[1051] Terminal: Display the meal plan to the user.

[1052] Step 8: Emotion Recognition

[1053] Terminal: The emotion engine analyzes the user's facial expressions, voice tone, and text input.

[1054] Server: Receives the recognized emotion data and determines the user's current emotional state.

[1055] Server: Based on the emotional state, the training menu and feedback provided are adjusted appropriately.

[1056] Step 9: Track progress

[1057] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[1058] Terminal: Sends the entered progress data to the server.

[1059] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[1060] Server: Sends the adjusted plan to the device.

[1061] Device: Display the adjusted plan to the user.

[1062] Example 2

[1063] 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."

[1064] Conventional personal training systems lack the ability to generate personalized training and meal plans to help users achieve their goals, making progress management difficult, and they also lack the ability to adjust feedback based on the user's emotional state, making it difficult to maintain user motivation.

[1065] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring basic information and goal data of the user, means for generating an appearance image of the user after achieving the goal based on the goal data, means for generating an individual training menu based on the goal data and fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, and emotion recognition means for analyzing the user's facial expression, voice tone, and text input and adjusting the training menu and feedback content based on the results. This allows the user to receive individualized health management and training guidance, and makes it easier to maintain motivation through feedback adjustment based on the user's emotional state.

[1066] "User" means any individual or collective entity that uses this system.

[1067] "Basic information" is data for identifying a user, such as the user's name, email address, password, height, and weight.

[1068] "Goal Data" refers to specific fitness-related goals set by a user. An example would be "lose 5 kilograms in 3 months."

[1069] The "means for generating an appearance image" is a technical means for generating an appearance image after the user has achieved the goal based on the user's current body type data and goal data.

[1070] The "means for generating a training menu" refers to a technical means for creating an optimal training plan or exercise program for a user based on the goal data and the user's fitness level.

[1071] The "means for analyzing exercise video" refers to a technical means for analyzing the exercise video taken and uploaded by the user, and for evaluating and providing feedback on the accuracy of the exercise form.

[1072] The "means for proposing a meal plan" refers to a technical means for generating and proposing an optimal meal plan based on the user's goal data and individual conditions.

[1073] "Means for recording progress" refers to technical means for recording and managing a user's progress data, such as daily exercise, diet, and weight changes.

[1074] The "adjustment means" refers to a technical means for changing the training menu and meal plan as needed based on progress data, and providing the user with an optimal program.

[1075] "Emotion recognition means" refers to a technical means for analyzing a user's facial expressions, voice tone, text input, etc., and determining the user's emotional state based on the results, and adjusting the training menu and feedback content.

[1076] MODE FOR CARRYING OUT THE INVENTION

[1077] This invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle, and is also combined with an emotion engine that recognizes the user's emotions. This system acquires the user's basic information and goal data, generates training and meal plans, analyzes exercise form, manages progress, and adjusts these plans and feedback based on the user's emotions.

[1078] 1. User Registration

[1079] When a user launches the app and clicks the "New Registration" button, the device displays a form for the user to enter basic information such as name, email address, password, height, and weight. When the user enters the required information and presses the submit button, the data is sent to the server. The server stores the received user information in a database and creates a user profile.

[1080] 2. Log in

[1081] When a user enters their email address and password and presses the login button, the device sends the entered data to the server. The server checks the user information in the database, and if it matches, it generates an authentication token and sends it to the device. The device saves the received authentication token and displays the dashboard.

[1082] 3. Goal setting

[1083] When a user enters specific fitness goals into the app's "Goal Setting" screen and presses the submit button, the device sends the data from the goal entry form to the server, which stores the received goal data in a database and generates an optimal training plan based on it.

[1084] 4. Image Generation

[1085] When the user clicks the "Generate Image" button to check what they will look like after achieving their goal, the device sends the request to the server. The server uses an image generation algorithm to generate an image of what they will look like after achieving their goal based on the user's current body shape data and goal data. The generated image is sent to the device, which then displays it to the user.

[1086] 5. Training menu generation

[1087] The server creates a personalized training menu based on the user's goals, current fitness level, and previous training data, and sends the created training menu to the device, which then displays it to the user.

[1088] 6. Analysis of exercise form

[1089] When a user films their workout with a camera and uploads the video, the device uploads the video to a server. The server receives the uploaded video data and runs an analysis algorithm to evaluate the accuracy of the workout form and generate feedback. The feedback data is sent to the device, which displays it to the user.

[1090] 7. Meal plan suggestions

[1091] The server generates an optimal meal plan based on the user's goals, current condition, allergy information, etc. The generated meal plan is sent to the device, which then displays it to the user.

[1092] 8. Emotion recognition

[1093] Using the emotion engine, the device analyzes the user's facial expressions, voice tone, and text input. The server receives the recognized emotion data and determines the user's current emotional state. Based on the emotional state, the device appropriately adjusts the training menu and feedback provided.

[1094] 9. Progress Management

[1095] When the user enters progress data such as daily exercise, diet, and weight changes into the app, the device sends the entered progress data to the server. The server stores the received progress data in a database and evaluates the user's progress. If necessary, it adjusts the training menu and meal plan and sends it to the device. The device then displays the adjusted plan to the user.

[1096] Prompt Sentence Examples

[1097] "Please explain in detail the steps for user registration."

[1098] "Please provide a concrete example of how to lose 5 kg in 3 months."

[1099] "Please tell me more about how you analyze your exercise form and provide feedback."

[1100] "Please explain how you propose a meal plan."

[1101] These specific steps and functions enable the system of the present invention to provide the user with personalized health management and training guidance, as well as provide feedback and adjust plans that take into account the user's emotional state.

[1102] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1103] Program processing flow

[1104] Step 1: User Registration

[1105] Input: Basic information such as user name, email address, password, height, and weight

[1106] Processing: The user launches the app and clicks the "New Registration" button. The device displays a form for the user to enter basic information, and after filling it in, the user presses the submit button. The device sends the entered data to the server.

[1107] Data processing: The server stores the received user information in a database and creates a user profile.

[1108] Output: The user's basic information is saved in a database and a profile is created.

[1109] Specific operation: When the app is launched, a "New Registration" button is displayed on the main screen. When the user clicks this, a form requesting name, email address, password, etc. is displayed. When the user enters the required information and presses the submit button, the data is sent to the server.

[1110] Step 2: Log in

[1111] Input: Email address, Password

[1112] Process: The user enters their email address and password and presses the login button. The device sends the entered data to the server.

[1113] Data processing: The server compares the user information with that in the database, and if there is a match, generates an authentication token and sends it to the terminal.

[1114] Output: An authentication token is generated and sent to the device.

[1115] How it works: When a user enters their email address and password on the login screen and presses the "Login" button, the device sends this data to the server. The server compares the input information with existing user data in its database, and if there is a match, it generates an authentication token and sends it to the device.

[1116] Step 3: Goal Setting

[1117] Input: Fitness goal (e.g. lose 5 kg in 3 months)

[1118] Processing: The user enters specific fitness goals into the app's "Goal Setting" screen and presses the submit button. The device then sends the data from the goal entry form to the server.

[1119] Data processing: The server stores the received goal data in a database and generates an optimal training plan.

[1120] Output: Goal data is stored in a database and a training plan is generated.

[1121] Specific operation: The user enters specific goals on the "Goal Setting" screen and presses the send button. This data is sent to the server via the device. The server generates a training plan based on the received goal data.

[1122] Step 4: Image generation

[1123] Input: Current body shape data, goal data

[1124] Processing: The user clicks the "Generate Image" button to see what the image will look like after achieving the goal. The device sends the request to the server.

[1125] Data processing: The server uses an image generation algorithm to generate an image of what the user will look like after achieving their goal, based on the user's current body shape data and goal data.

[1126] Output: An image of the appearance after the goal is achieved is generated and sent to the device.

[1127] Specific operation: When the user clicks the "Generate Image" button, the device sends the request to the server, which then uses an image generation algorithm to generate an image based on the user's body shape data and target data.

[1128] Step 5: Create a training menu

[1129] Input: Goal data, Fitness level, Past training data

[1130] Processing: The server creates a personalized training menu based on the user's goals, fitness level, and previous training data.

[1131] Data processing: The server uses AI algorithms to generate the optimal training plan for the user.

[1132] Output: A training menu is generated and sent to the device.

[1133] How it works: The server uses an AI algorithm to generate a training menu based on your goals, fitness level, and past training data, and sends it to your device.

[1134] Step 6: Analyze your exercise form

[1135] Input: Exercise footage during training

[1136] Processing: The user takes a video of their workout with a camera and uploads the video. The device then uploads the video to the server.

[1137] Data processing: The server analyzes the uploaded video data using an analysis algorithm to evaluate the accuracy of the exercise form.

[1138] Output: Generate feedback and send it to the device.

[1139] How it works: The user takes a video of themselves training and uploads it to the system. The server then uses an analysis algorithm to evaluate the video and sends feedback to the device.

[1140] Step 7: Meal Plan Suggestion

[1141] Input: goal data, allergy information, food preferences

[1142] Processing: The server generates an optimal meal plan based on the user's goals, current condition, allergy information, food preferences, etc.

[1143] Data processing: Using AI algorithms to generate meal plans that take into account calorie restriction and nutritional balance.

[1144] Output: A meal plan is generated and sent to the device.

[1145] Specific operation: The server uses an AI algorithm to generate a meal plan taking into account goals, allergy information, food preferences, etc., and sends it to the device.

[1146] Step 8: Emotion Recognition

[1147] Input: Facial expressions, voice tone, text input

[1148] Processing: Using the emotion engine, the device analyzes the user's facial expressions, voice tone, and text input.

[1149] Data processing: The server receives the recognized emotion data and determines the user's current emotional state.

[1150] Output: Adjust the training menu and feedback content.

[1151] Specific operation: The device analyzes the user's emotions using an emotion engine, and the server adjusts the training menu and feedback based on the results.

[1152] Step 9: Track progress

[1153] Input: Progress data such as daily exercise, diet, and weight changes

[1154] Process: The user enters daily progress data into the app, and the device sends it to the server.

[1155] Data processing: The server stores the received progress data in a database and evaluates the progress using an AI algorithm.

[1156] Output: Adjust your training menu and meal plan as needed and send it to your device.

[1157] What it does: The user enters their daily progress into the app, and the server evaluates their progress based on that information, adjusts the plan as necessary, and sends it to the device.

[1158] (Application example 2)

[1159] 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."

[1160] While interest in fitness and health management is growing in modern society, providing personal training requires a lot of time and effort, and costs and resources are limited, especially when providing services at physical stores. Furthermore, it is difficult to provide feedback and support tailored to each user's emotional state and progress, making it difficult to maintain motivation. Furthermore, there is a demand for a unified service that covers everything from confirming proper exercise form to managing dietary habits when users receive training and instruction at physical stores.

[1161] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring basic information and goal data of the user, means for generating an appearance image of the user after achieving the goal based on the goal data, means for generating an individual training menu based on the goal data and the user's fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and the user's individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, means for analyzing the user's emotions and adjusting the training menu and feedback content based on the user's emotional state, and means for installing the system on a smart device (smart glasses or tablet) optimized for use in a physical store. This enables feedback and training adjustments based on emotions in real time in a physical store, enabling efficient maintenance of user motivation and comprehensive health management.

[1162] "Basic user information" refers to information necessary for creating training and meal plans, such as the user's name, height, weight, age, and gender.

[1163] "Goal Data" refers to specific fitness or health goals set by the user, such as "lose 5 kilograms in 3 months."

[1164] The "appearance image" is an image that visually shows the future body shape after the user achieves the goal, generated based on the user's current body shape data and goal data.

[1165] A "training menu" is an exercise program customized based on a user's goals and fitness level, including specific exercises, exercise frequency, and duration.

[1166] "Exercise video" is video data taken by a user while they are training, and is used to evaluate the accuracy of their exercise form.

[1167] "Exercise form" refers to the physical movements and posture of the user when exercising, and maintaining correct form leads to improved safety and effectiveness.

[1168] A "meal plan" is a meal menu suggested based on the user's goals and physical condition, taking into consideration nutritional balance and calorie restrictions.

[1169] "Progress" is data recorded by the user regarding daily exercise, diet, weight fluctuations, etc., and is used to evaluate progress toward goals.

[1170] "Emotional state" refers to the user's current emotions, analyzed based on the user's facial expressions, voice tone, text input, etc.

[1171] "Feedback content" refers to advice and encouraging messages provided based on the user's exercise form, progress, and emotional state.

[1172] A "smart device" is a device for use by a user, and in the present invention particularly refers to smart glasses or tablets.

[1173] This invention relates to a personal training system that helps users maintain their health, lose weight, and build muscle. The system acquires basic information and goal data from the user and generates individual training and meal plans. It can also recognize the user's emotions and adjust the plans and feedback accordingly.

[1174] Hardware and software used

[1175] Hardware: Smart glasses, tablets, cameras

[1176] Software: Emotion recognition engine (EmotionRecognition), training plan generation engine (TrainingRecommendation), database management system

[1177] Specific explanation of the process

[1178] 1. User Registration and Login:

[1179] The user uses a tablet to enter basic information and send it to the server, which stores it in a database.

[1180] If the user is already registered, they enter their email address and password on the login screen, and the server checks the information against the database.

[1181] 2. Goal Setting:

[1182] Users input their fitness goals using a tablet in the physical store, and the server generates an optimal training plan based on this goal data and displays it on the tablet.

[1183] 3. Training and meal plans provided:

[1184] The server generates personalized training and meal plans based on the user's goals and fitness level, which are displayed on a tablet or smart glasses.

[1185] 4. Real-time analysis of athletic form:

[1186] Cameras and smart glasses installed in the store capture footage of the workout, which is then sent to a server where an algorithm is run to assess the accuracy of the workout form, providing real-time feedback on the tablet or smart glasses.

[1187] 5. Emotion-aware feedback regulation:

[1188] An emotion recognition engine analyzes the user's emotional state based on camera footage, audio, and text input. The server then adjusts the training menu and feedback content based on the recognized emotions, providing encouraging messages as needed.

[1189] 6. Progress Management and Data Entry:

[1190] Users enter their daily exercise routines, dietary habits, weight fluctuations, etc. into a tablet, and this data is sent to a server, where progress is evaluated and the plan is adjusted as necessary.

[1191] Specific examples

[1192] For example, if a user sets a goal of "losing 5 kg in 3 months," the system will generate optimal training and meal plans based on this goal. Footage captured by the camera during training is used to analyze exercise form. Furthermore, if the system determines through an emotion recognition engine that the user's motivation is declining, appropriate feedback and encouraging messages will be displayed on the tablet or smart glasses.

[1193] Example prompt for a generative AI model:

[1194] "Given the user's current body shape data and goal data, generate an image of what they will look like after achieving their goal."

[1195] The above processing makes it possible to provide real-time feedback and adjust training according to emotions in a physical store, thereby maintaining user motivation and efficiently managing overall health.

[1196] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1197] Step 1:

[1198] A user launches the application using a tablet and clicks the "New Registration" button. They enter basic information such as their name, email address, password, height, and weight, and then presses the submit button. This input data is sent from the device to the server. The server stores the received user information in a database and creates a user profile.

[1199] Step 2:

[1200] The user logs in from the tablet using the registered email address and password. The device sends the entered authentication information to the server, which checks it against the user information in the database. If authentication is successful, the server generates an authentication token, sends it to the device, and displays the dashboard to the user.

[1201] Step 3:

[1202] The user opens the "Goal Setting" screen on the tablet and enters their specific fitness goals. The entered goal data is sent from the device to the server, which stores this information in a database. Based on the received goal data, the server generates an optimal training plan and sends it to the tablet.

[1203] Step 4:

[1204] During training, the user uses smart glasses or a camera to capture video of their exercise. This video data is then uploaded to a server via the device. The server receives the uploaded video data and runs an analysis algorithm to evaluate the accuracy of the exercise form. The server generates an evaluation result and appropriate feedback, which it then sends to the device. The device then displays the feedback to the user in real time.

[1205] Step 5:

[1206] The server proposes a customized meal plan based on the user's preset fitness goals and current health status. Taking into account the user's individual conditions (allergies, preferences, etc.), the server generates an optimal meal plan and sends it to the tablet. The device then displays the meal plan and allows the user to view the proposal.

[1207] Step 6:

[1208] The emotion engine analyzes the user's facial expressions, voice tone, and input text through a tablet or smart glasses to determine the user's emotional state. The server receives the analysis results and adjusts the training menu and feedback content according to the user's emotional state. Based on this, feedback messages and encouraging messages that interest the user are displayed on the device.

[1209] Step 7:

[1210] The user enters progress data, such as daily exercise, diet, and weight fluctuations, into a tablet, and the device sends the data to a server. The server stores the received progress data in a database and evaluates the user's progress. Based on the evaluation results, the training menu and meal plan are adjusted as necessary, and a new plan is generated. The new plan is then sent to the device and displayed to the user.

[1211] Through the above process, the system provides comprehensive support for users when receiving personal training at a physical store, and can flexibly adapt to the user's emotional state and progress.

[1212] 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.

[1213] 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.

[1214] 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.

[1215] [Third embodiment]

[1216] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1217] 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.

[1218] 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).

[1219] 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.

[1220] 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.

[1221] 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).

[1222] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[1223] 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.

[1224] 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.

[1225] 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.

[1226] 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.

[1227] 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."

[1228] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle strength. This system acquires basic information and goal data about the user, and comprehensively generates training and meal plans, analyzes exercise form, and manages progress. Specific embodiments for implementing the present invention are described below.

[1229] Initial Setup

[1230] User Registration

[1231] User: After launching the app, enter basic information such as name, email address, password, height, and weight.

[1232] Terminal: Displays this information as a form and sends the input data to the server.

[1233] Server: Stores the received user information in a database and creates a user profile.

[1234] Log in

[1235] User: Enter your email address and password to log in.

[1236] Terminal: Sends authentication information to the server and displays the dashboard if authentication is successful.

[1237] Server: If authentication is successful, generate an authentication token and send it to the device.

[1238] goal setting

[1239] Goal Input

[1240] User: Enters fitness goal (e.g., lose 5 kg in 3 months) in the in-app goal setting screen.

[1241] Terminal: Sends target data to the server.

[1242] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[1243] Image generation

[1244] Morphing

[1245] User: Makes a request to see what it will look like after achieving the goal.

[1246] Terminal: Sends the request to the server.

[1247] Server: Based on the current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving the goal, and this is sent to the device.

[1248] Terminal: displays the generated image to the user.

[1249] Training menu generation

[1250] Plan creation

[1251] Server: Creates personalized training menus based on the user's goals, current fitness level, and previous training data.

[1252] Server: Sends the generated training menu to the terminal.

[1253] Terminal: Displays the training menu to the user.

[1254] Exercise form analysis

[1255] Video Analysis

[1256] User: Takes video of exercise during training and uploads the video.

[1257] Terminal: Sends the captured video to the server.

[1258] Server: Receives video data and runs exercise form analysis algorithms to evaluate accurate form and generate feedback.

[1259] Server: Sends feedback to the device.

[1260] Terminal: displays the feedback results to the user.

[1261] Meal plan suggestions

[1262] Plan Generation

[1263] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[1264] Server: Sends the generated meal plan to the device.

[1265] Terminal: Display the meal plan to the user.

[1266] Progress management

[1267] Data Entry and Management

[1268] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[1269] Terminal: Sends the entered progress data to the server.

[1270] Server: Stores the received progress data in a database, analyzes the user's progress, and adjusts training menus and meal plans as needed.

[1271] Server: Sends the adjusted plan to the device.

[1272] Device: Display the adjusted plan to the user.

[1273] Specific examples

[1274] For example, if a user sets a goal of "lose 5 kg in 3 months," the system operates as follows:

[1275] 1. After registering and logging in, enter "Lose 5 kg in 3 months" on the goal setting screen.

[1276] 2. The server retrieves the goal data and generates a personalized training menu based on it. The initial training menu includes 30 minutes of cardio and 15 minutes of strength training three times a week.

[1277] 3. The user takes a video of themselves training with a camera and uploads the video to the system.

[1278] 4. The server analyzes the uploaded video, evaluates whether the exercise form is correct, and provides necessary feedback.

[1279] 5. Furthermore, the server generates and presents a meal plan that takes into account calorie restriction and nutritional balance to help the user achieve their goals.

[1280] 6. The user enters daily progress data (e.g., diet, exercise, weight changes), and the server evaluates the progress based on this and adjusts the individual plan if necessary.

[1281] In this way, the system of the present invention allows users to always receive appropriate and personalized health management and training guidance, enabling them to progress efficiently toward their goals.

[1282] The processing flow will be explained below.

[1283] Step 1: User Registration

[1284] User: Launch the app and click the "New Registration" button.

[1285] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[1286] User: Enter the required information and press the send button.

[1287] Terminal: Sends the entered data to the server.

[1288] Server: Stores the received user information in a database and creates a user profile.

[1289] Step 2: Log in

[1290] User: Enter your email address and password and click the login button.

[1291] Terminal: Sends the entered data to the server.

[1292] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[1293] Terminal: Save the received authentication token and display the dashboard.

[1294] Step 3: Goal Setting

[1295] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[1296] Terminal: Sends the data from the target input form to the server.

[1297] Server: The received goal data is stored in a database and used as the basis for generating optimal training plans.

[1298] Step 4: Image generation

[1299] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[1300] Terminal: Sends requests to the server.

[1301] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[1302] Server: Sends the generated image to the terminal.

[1303] Terminal: displays the generated image to the user.

[1304] Step 5: Create a training menu

[1305] Server: Generates an individual training menu based on the user's goals, current fitness level, and past training data.

[1306] Server: Sends the generated training menu to the terminal.

[1307] Terminal: Displays the training menu to the user.

[1308] Step 6: Analyze your exercise form

[1309] User: Records exercise during training and uploads the video.

[1310] Device: Upload the captured video to the server.

[1311] Server: Receives uploaded video data and executes analysis algorithms.

[1312] Server: Evaluates the accuracy of the exercise form and generates the necessary feedback.

[1313] Server: Sends feedback data to the device.

[1314] Terminal: displays the feedback results to the user.

[1315] Step 7: Meal Plan Suggestion

[1316] Server: Generates an optimal meal plan based on the user's goals, current condition, allergy information, etc.

[1317] Server: Sends the generated meal plan to the device.

[1318] Terminal: Display the meal plan to the user.

[1319] Step 8: Track progress

[1320] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[1321] Terminal: Sends the entered progress data to the server.

[1322] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[1323] Server: Sends the adjusted plan to the device.

[1324] Device: Display the adjusted plan to the user.

[1325] Example 1

[1326] 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."

[1327] Conventional fitness and diet systems have problems in that they do not adequately propose detailed training menus and meal plans tailored to the user's individual needs, nor do they adequately analyze and provide feedback on exercise form. In particular, there is a demand for systems that can efficiently approach the goals set by the user. Without such systems, users may not receive appropriate guidance or adjustments to achieve their goals, which can result in a loss of motivation. Another issue is the lack of a function that reflects the user's progress data in real time and provides appropriate advice.

[1328] 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.

[1329] In this invention, the server includes: means for acquiring a user's basic information and goal data; means for generating an image of the user's appearance after achieving their goal based on the goal data; means for generating an individual training menu based on the goal data and the user's fitness level; means for analyzing exercise video data uploaded by the user and evaluating and providing feedback on accurate exercise form; means for proposing an optimal meal plan based on the goal data and the user's individual conditions; means for acquiring and recording the user's daily progress data and adjusting the training menu and meal plan as needed; and means for verifying authentication information and displaying the app's dashboard screen. This allows users to receive individually optimized training guidance and dietary advice, helping them efficiently achieve their goals. Furthermore, real-time feedback and plan adjustments based on the user's progress make it easier for them to maintain motivation.

[1330] "User" refers to an individual who uses the System.

[1331] "Basic information" refers to initial setting data such as the user's name, email address, password, height, and weight.

[1332] "Goal data" refers to the specific fitness or diet goal values ​​and details that a user wants to achieve.

[1333] The "appearance image" refers to image data that represents the virtual appearance of the user after achieving the goal.

[1334] "Fitness level" refers to information that indicates the user's current athletic ability and health condition.

[1335] A "training menu" refers to a plan that indicates the specific exercises and training content that a user will perform to achieve their goal.

[1336] "Exercise video data" refers to video data captured by a user while they are training.

[1337] "Form analysis" refers to the process of evaluating a user's exercise form and analyzing its accuracy based on their exercise video data.

[1338] "Feedback" refers to assessment and advice provided to a user regarding exercise form and progress.

[1339] "Meal Plan" refers to a meal plan suggested based on a user's goals and individual requirements.

[1340] "Progress data" refers to continuously recorded data such as a user's exercise, diet, and weight changes.

[1341] "Token" refers to a digital identifier used to identify an authenticated user's session.

[1342] "Dashboard" refers to a screen where users can check their progress and plans in one place through the app.

[1343] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle strength. This system acquires basic information and goal data about the user, and comprehensively generates training and meal plans, analyzes exercise form, and manages progress. Specific embodiments are described below.

[1344] Initial Setup

[1345] User Registration

[1346] The user launches the app and enters information such as name, email address, password, height, and weight on the input screen.

[1347] The device temporarily stores the user's input data and sends it to the server in JSON format.

[1348] The server validates the received data, stores it in a database (MySQL), creates a new user profile, and returns a success message to the terminal.

[1349] Log in

[1350] The user enters their email address and password on the login screen.

[1351] The terminal transmits the entered authentication information to the server.

[1352] The server verifies the user information in the database and, if authentication is successful, generates a JWT (JSON Web Token).

[1353] The server returns the generated JWT to the terminal, which saves it and displays the dashboard screen.

[1354] goal setting

[1355] Goal Input

[1356] The user enters "lose 5 kg in 3 months" into the app's goal setting screen.

[1357] The device sends the entered goal data to the server in JSON format.

[1358] The server stores the received goal data in a database and generates a personalized training plan for the user based on the goals.

[1359] The server returns the generated training plan to the terminal, which displays it to the user.

[1360] Image generation

[1361] Morphing

[1362] The user makes a request to see what it will look like after achieving the goal.

[1363] The terminal sends a request to the server.

[1364] The server reads the current body shape data and runs the image generation algorithm using TensorFlow along with the target data.

[1365] The server sends the generated image to the terminal, which displays the image to the user.

[1366] Training menu generation

[1367] Plan creation

[1368] The server obtains the user's goals, current fitness level, and past training data, and uses an algorithm to generate a personalized training menu.

[1369] The server transmits the generated training menu to the terminal.

[1370] The terminal displays a training menu to the user.

[1371] Exercise form analysis

[1372] Video Analysis

[1373] Users can record their workouts with a camera and upload the videos.

[1374] The device sends the captured video to the server.

[1375] The server receives the video data and runs a motion form analysis algorithm using OpenPose.

[1376] The server evaluates the user's exercise form based on the analysis results and generates feedback.

[1377] The server sends the feedback to the terminal, which displays the results to the user.

[1378] Meal plan suggestions

[1379] Plan Generation

[1380] The server takes the user's goals, current condition, and allergy information and uses an algorithm to generate an optimal meal plan.

[1381] The server transmits the generated meal plan to the terminal.

[1382] The terminal displays the meal plan to the user.

[1383] Progress management

[1384] Data Entry and Management

[1385] Users enter progress data such as daily exercise, diet, and weight changes into the app.

[1386] The terminal transmits the input data to the server.

[1387] The server stores the received progress data in a database and analyzes the progress using an algorithm.

[1388] The server will adjust your training menu and meal plan as needed based on your progress data.

[1389] The server sends the adjusted plan to the terminal, which displays it to the user.

[1390] Prompt Sentence Examples

[1391] "Generate what your goal will look like after you achieve it."

[1392] "Create a training plan to lose 5 kg in 3 months."

[1393] This system allows users to always receive appropriate and personalized health management and training guidance, enabling them to progress efficiently toward their goals.

[1394] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1395] Step 1:

[1396] User Registration

[1397] The user launches the app and enters information such as name, email address, password, height, and weight on the input screen.

[1398] Input: Name, email address, password, height, weight

[1399] The device temporarily stores the user's input data and sends it to the server in JSON format.

[1400] Output: User registration data in JSON format

[1401] The server validates the received data, stores it in a database (MySQL), creates a new user profile, and returns a success message to the terminal.

[1402] Input: JSON format user registration data

[1403] Output: Success message

[1404] Step 2:

[1405] Log in

[1406] The user enters their email address and password on the login screen.

[1407] Input: Email address, password

[1408] The terminal transmits the entered authentication information to the server.

[1409] Output: Credentials in JSON format

[1410] The server verifies the user information in the database and, if authentication is successful, generates a JWT (JSON Web Token).

[1411] Input: JSON formatted credentials

[1412] Output: JWT (JSON Web Token)

[1413] The server returns the generated JWT to the terminal, which saves it and displays the dashboard screen.

[1414] Input: JWT (JSON Web Token)

[1415] Output: Dashboard screen

[1416] Step 3:

[1417] Goal Input

[1418] The user enters "lose 5 kg in 3 months" into the app's goal setting screen.

[1419] Input: Goal data (e.g., "lose 5 kg in 3 months")

[1420] The device sends the entered goal data to the server in JSON format.

[1421] Output: Goal data in JSON format

[1422] The server stores the received goal data in a database and generates a personalized training plan for the user based on the goals.

[1423] Input: Goal data in JSON format

[1424] Data processing: Create a plan using a training plan generation algorithm

[1425] Output: Training Plan

[1426] The server returns the generated training plan to the terminal, which displays it to the user.

[1427] Input: Training plan

[1428] Output: Training plan display screen

[1429] Step 4:

[1430] Morphing Request

[1431] The user makes a request to see what it will look like after achieving the goal.

[1432] Input: Request data (check appearance after goal achievement)

[1433] The terminal sends the request to the server.

[1434] Output: Request data

[1435] The server reads the current body shape data and runs the image generation algorithm using TensorFlow along with the target data.

[1436] Input: Current body shape data, goal data

[1437] Data Computation: Morphing with Image Generation Algorithms

[1438] Output: Generated image

[1439] The server sends the generated image to the terminal, which displays the image to the user.

[1440] Input: Generated appearance image

[1441] Output: Image display screen

[1442] Step 5:

[1443] Creating a training menu

[1444] The server obtains the user's goals, current fitness level, and past training data, and uses an algorithm to generate a personalized training menu.

[1445] Input: Goal data, Fitness level, Training history

[1446] Data processing: Create a plan using a training menu generation algorithm

[1447] Output: Training menu

[1448] The server transmits the generated training menu to the terminal.

[1449] Input: Training Menu

[1450] Output: Training menu display screen

[1451] Step 6:

[1452] Exercise form analysis

[1453] Users can record their workouts with a camera and upload the videos.

[1454] Input: Exercise video data

[1455] The device sends the captured video to the server.

[1456] Output: Video data

[1457] The server receives the video data and runs a motion form analysis algorithm using OpenPose.

[1458] Input: Video data

[1459] Data processing: Form evaluation using exercise form analysis algorithms

[1460] Output: Evaluation results and feedback data

[1461] The server sends the feedback to the terminal, which displays the results to the user.

[1462] Input: Feedback data

[1463] Output: Feedback display screen

[1464] Step 7:

[1465] Meal plan suggestions

[1466] The server takes the user's goals, current condition, and allergy information and uses an algorithm to generate an optimal meal plan.

[1467] Input: goal data, current condition, allergy information

[1468] Data processing: Meal plan generation algorithm

[1469] Output: Meal plan

[1470] The server transmits the generated meal plan to the terminal.

[1471] Input: meal plan

[1472] Output: Meal plan display screen

[1473] Step 8:

[1474] Progress management

[1475] Users enter progress data such as daily exercise, diet, and weight changes into the app.

[1476] Input: Progress data (exercise, diet, weight changes)

[1477] The terminal transmits the input data to the server.

[1478] Output: Progress data

[1479] The server stores the received progress data in a database and uses an algorithm to analyze the progress.

[1480] Input: Progress data

[1481] Data Computing: Evaluation with Progress Data Analysis Algorithms

[1482] Output: Analysis results

[1483] The server will adjust your training menu and meal plan as needed based on your progress data.

[1484] Input: Analysis results

[1485] Output: Adjusted plan

[1486] The server sends the adjusted plan to the terminal, which displays it to the user.

[1487] Input: Adjusted plan

[1488] Output: Adjusted plan display screen

[1489] (Application example 1)

[1490] 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."

[1491] Conventional personal training systems have had difficulty individually examining a user's exercise form and dietary habits and providing feedback based on that. Furthermore, the generation of training and meal plans for achieving goals is based on general algorithms, which do not adequately reflect the user's individual circumstances. This makes it difficult to achieve effective training and health management.

[1492] 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.

[1493] In this invention, the server includes means for acquiring basic information and goal data of a user, means for generating an appearance image of the user after achieving the goal, means for generating an individual training menu based on the goal data and the user's fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and the user's individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, means for using a generative AI model to generate a training plan based on the user's goal settings, and means for generating prompts for the generative AI model, thereby enabling effective training and health management based on the user's individual conditions.

[1494] "User basic information" refers to personal information provided by a user, including name, email address, password, height, weight, etc.

[1495] "Goal data" refers to specific fitness or health goals set by the user, such as "lose 5 kilograms in 3 months."

[1496] An "appearance image" is an image generated to visually display the body shape and appearance of a user after achieving the goal set by the user.

[1497] "Fitness level" refers to the user's current physical strength and athletic ability, and is evaluated based on past training results and physical condition.

[1498] An "individual training menu" is an exercise plan that is optimized for each individual user and is generated based on the user's goal data and fitness level.

[1499] "Exercise footage" refers to video data taken by a user while they are training, and is used to analyze their exercise form.

[1500] "Exercise form" refers to the movements and postures that a user performs during training, and their accuracy and efficiency are evaluated.

[1501] "Feedback" refers to the evaluation and advice for improvement that the system provides to the user regarding their exercise form.

[1502] "Individual conditions" refers to information about the user's own health and lifestyle, such as the user's allergy information, favorite ingredients, and dietary restrictions.

[1503] A "meal plan" is a specific meal plan proposed based on the user's goal data and individual conditions to help the user achieve their goals.

[1504] "Progress" refers to the current exercise and dietary details, changes in weight and body shape, and the like, relative to the goal set by the user.

[1505] A "generative AI model" is an artificial intelligence model that uses deep learning and machine learning techniques to generate training plans and meal plans from user data.

[1506] A "prompt" is a document that provides instructions and input information to a generative AI model, and is created based on the user's current situation and goals.

[1507] The present invention is a personal training system that collects basic information and goal data of a user, generates an individual training menu and meal plan based on the collected information, and supports the user in maintaining their health and achieving their goals. This system is implemented as follows.

[1508] Initial Setup

[1509] The server obtains the user's basic information (such as name, email address, password, height, and weight) and stores it in a database. A user profile is created based on this information. The device (smartphone or household robot) displays a form and sends the data entered by the user to the server. The server also manages authentication information and generates an appropriate authentication token when the user logs in and sends it to the device.

[1510] goal setting

[1511] Users set fitness goals in an application on their device. For example, they can set a specific goal like "lose 5 kg in 3 months." The server receives this goal data and stores it in a database. Based on this, it generates a personalized training menu.

[1512] Training menu generation

[1513] The server generates a personalized training menu based on the user's goal data and fitness level. It uses a generative AI model and inputs prompts. These prompts contain information needed to help the user achieve their goals. For example,

[1514] To help users achieve their goals, please propose a personal training plan based on the following information:

[1515] Username: Example

[1516] Age: 35

[1517] Current weight: 75kg

[1518] Goal: Lose 5kg in 3 months

[1519] Fitness Level: Beginner

[1520] Allergies: None

[1521] This generated training menu is sent from the server to the terminal and displayed to the user.

[1522] Exercise form analysis

[1523] During exercise, users record their own training videos and upload them to a server via their device. The server receives the video data and runs an exercise form analysis algorithm (e.g., a deep learning model using Keras) to accurately evaluate their exercise form and provide feedback to the user.

[1524] Meal plan suggestions

[1525] The server generates an optimal meal plan based on the user's goals and individual conditions (allergy information, dietary preferences, etc.). This data is also processed using a generative AI model. The generated meal plan is sent from the server to the device and presented to the user.

[1526] Progress management

[1527] The user inputs their daily progress (exercise, diet, weight change, etc.) on the device. The server receives this progress data and stores it in a database. If necessary, the server adjusts the training menu and meal plan and provides the user with the latest plan.

[1528] This allows users to easily receive personal training at home and efficiently achieve their goals based on individual training and dietary advice.

[1529] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1530] Step 1: User Registration

[1531] The server receives basic information from the user (such as name, email address, password, height, and weight) and stores it in a database. The terminal displays the basic information entered by the user in a form and sends the information entered by the user to the server. The input is the user's basic information, and the output is the user's profile stored in the database.

[1532] Step 2: Log in

[1533] The server receives the authentication information (email address, password) entered by the user and checks it in the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. The terminal displays the generated authentication token and notifies the user that login was successful. The input is authentication information and the output is the authentication token.

[1534] Step 3: Goal Setting

[1535] A user sets a fitness goal (e.g., "lose 5 kg in 3 months") in an application on their device. This information is sent from the device to a server, which stores the goal data in a database. The input is the goal data, and the output is the goal data stored in the database.

[1536] Step 4: Create a training menu

[1537] The server uses a generative AI model to create prompts based on the user's goal data and fitness level. The generative AI model generates a training menu based on the prompts, and the server stores the generated menu in a database and sends it to the terminal. The terminal displays the training menu to the user. The input is the goal data and fitness level, and the output is the generated training menu.

[1538] Step 5: Analyze your exercise form

[1539] The user takes a video of themselves training on their device and uploads it to the server. The server receives the video data and runs an exercise form analysis algorithm (using Keras) to generate an analysis of their exercise form. The server stores the results in a database, generates feedback, and sends it to the device. The device displays the feedback to the user. The input is the exercise video, and the output is the feedback results.

[1540] Step 6: Meal plan suggestions

[1541] The server uses a generative AI model to generate a meal plan based on the user's goal data and individual conditions (allergy information, likes and dislikes, etc.), and stores it in a database. The server then sends the generated meal plan to the device, which displays it to the user. The input is the goal data and individual conditions, and the output is the generated meal plan.

[1542] Step 7: Track progress

[1543] The user inputs progress data, such as daily exercise, diet, and weight changes, into the device. The server receives this data, stores it in a database, and analyzes the progress. If necessary, the server adjusts the training menu and meal plan and sends the updated plan to the device. The device displays the adjusted plan to the user. The input is progress data, and the output is the adjusted training menu and meal plan.

[1544] 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.

[1545] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle, and further combines it with an emotion engine that recognizes the user's emotions. This system acquires the user's basic information and goal data, generates training plans and meal plans, analyzes exercise form, manages progress, and adjusts these plans and feedback based on the user's emotions. Specific embodiments for implementing the present invention are described below.

[1546] Initial Setup

[1547] User Registration

[1548] User: Launch the app and click the "New Registration" button.

[1549] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[1550] User: Enter the required information and press the send button.

[1551] Terminal: Sends the entered data to the server.

[1552] Server: Stores the received user information in a database and creates a user profile.

[1553] Log in

[1554] User: Enter your email address and password and click the login button.

[1555] Terminal: Sends the entered data to the server.

[1556] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[1557] Terminal: Save the received authentication token and display the dashboard.

[1558] goal setting

[1559] Goal Input

[1560] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[1561] Terminal: Sends the data from the target input form to the server.

[1562] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[1563] Image generation

[1564] Morphing

[1565] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[1566] Terminal: Sends the request to the server.

[1567] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[1568] Server: Sends the generated image to the terminal.

[1569] Terminal: displays the generated image to the user.

[1570] Training menu generation

[1571] Plan creation

[1572] Server: Creates personalized training menus based on the user's goals, current fitness level, and previous training data.

[1573] Server: Sends the generated training menu to the terminal.

[1574] Terminal: Displays the training menu to the user.

[1575] Exercise form analysis

[1576] Video Analysis

[1577] User: Records exercise during training and uploads the video.

[1578] Device: Upload the captured video to the server.

[1579] Server: Receives uploaded video data and executes analysis algorithms.

[1580] Server: Evaluates the accuracy of exercise form and generates feedback.

[1581] Server: Sends feedback data to the device.

[1582] Terminal: displays the feedback results to the user.

[1583] Meal plan suggestions

[1584] Plan Generation

[1585] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[1586] Server: Sends the generated meal plan to the device.

[1587] Terminal: Display the meal plan to the user.

[1588] emotion recognition

[1589] Introducing the Emotion Engine

[1590] Terminal: The emotion engine analyzes the user's facial expressions, voice tone, and text input.

[1591] Server: Receives the recognized emotion data and determines the user's current emotional state.

[1592] Server: Based on the emotional state, the training menu and feedback provided are adjusted appropriately.

[1593] Progress management

[1594] Data Entry and Management

[1595] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[1596] Terminal: Sends the entered progress data to the server.

[1597] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[1598] Server: Sends the adjusted plan to the device.

[1599] Device: Display the adjusted plan to the user.

[1600] Specific examples

[1601] For example, if a user sets a goal of "lose 5 kg in 3 months," the system operates as follows:

[1602] 1. After registering and logging in, enter "Lose 5 kg in 3 months" on the goal setting screen.

[1603] 2. The server retrieves the goal data and generates a personalized training menu based on it. The initial training menu includes 30 minutes of cardio and 15 minutes of strength training three times a week.

[1604] 3. The user takes a video of themselves training with a camera and uploads the video to the system.

[1605] 4. The server analyzes the uploaded video, evaluates whether the exercise form is correct, and provides necessary feedback.

[1606] 5. Furthermore, the server generates and presents a meal plan that takes into account calorie restriction and nutritional balance to help the user achieve their goals.

[1607] 6. The emotion engine recognizes the user's emotions, and if it determines that motivation is declining, it provides encouraging feedback and makes adjustments to increase motivation.

[1608] 7. The user enters daily progress data (e.g., diet, exercise, weight changes), and the server evaluates the progress based on this and adjusts the individual plan if necessary.

[1609] In this way, the system of the present invention allows users to always receive appropriate and personalized health management and training guidance, and the introduction of an emotion engine helps maintain and improve motivation, enabling users to make effective progress toward their goals.

[1610] The processing flow will be explained below.

[1611] Step 1: User Registration

[1612] User: Launch the app and click the "New Registration" button.

[1613] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[1614] User: Enter the required information and press the send button.

[1615] Terminal: Sends the entered data to the server.

[1616] Server: Stores the received user information in a database and creates a user profile.

[1617] Step 2: Log in

[1618] User: Enter your email address and password and click the login button.

[1619] Terminal: Sends the entered data to the server.

[1620] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[1621] Terminal: Save the received authentication token and display the dashboard.

[1622] Step 3: Goal Setting

[1623] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[1624] Terminal: Sends the data from the target input form to the server.

[1625] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[1626] Step 4: Image generation (morphing)

[1627] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[1628] Terminal: Sends the request to the server.

[1629] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[1630] Server: Sends the generated image to the terminal.

[1631] Terminal: displays the generated image to the user.

[1632] Step 5: Create a training menu

[1633] Server: Generates a personalized training menu based on the user's goals, current fitness level, and past training data.

[1634] Server: Sends the generated training menu to the terminal.

[1635] Terminal: Displays the training menu to the user.

[1636] Step 6: Analyze your exercise form

[1637] User: Records exercise during training and uploads the video.

[1638] Device: Upload the captured video to the server.

[1639] Server: Receives uploaded video data and executes analysis algorithms.

[1640] Server: Evaluates the accuracy of exercise form and generates feedback.

[1641] Server: Sends feedback data to the device.

[1642] Terminal: displays the feedback results to the user.

[1643] Step 7: Meal Plan Suggestion

[1644] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[1645] Server: Sends the generated meal plan to the device.

[1646] Terminal: Display the meal plan to the user.

[1647] Step 8: Emotion Recognition

[1648] Terminal: The emotion engine analyzes the user's facial expressions, voice tone, and text input.

[1649] Server: Receives the recognized emotion data and determines the user's current emotional state.

[1650] Server: Based on the emotional state, the training menu and feedback provided are adjusted appropriately.

[1651] Step 9: Track progress

[1652] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[1653] Terminal: Sends the entered progress data to the server.

[1654] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[1655] Server: Sends the adjusted plan to the device.

[1656] Device: Display the adjusted plan to the user.

[1657] Example 2

[1658] 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."

[1659] Conventional personal training systems lack the ability to generate personalized training and meal plans to help users achieve their goals, making progress management difficult, and they also lack the ability to adjust feedback based on the user's emotional state, making it difficult to maintain user motivation.

[1660] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring basic information and goal data of the user, means for generating an appearance image of the user after achieving the goal based on the goal data, means for generating an individual training menu based on the goal data and fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, and emotion recognition means for analyzing the user's facial expression, voice tone, and text input and adjusting the training menu and feedback content based on the results. This allows the user to receive individualized health management and training guidance, and makes it easier to maintain motivation through feedback adjustment based on the user's emotional state.

[1661] "User" means any individual or collective entity that uses this system.

[1662] "Basic information" is data for identifying a user, such as the user's name, email address, password, height, and weight.

[1663] "Goal Data" refers to specific fitness-related goals set by a user. An example would be "lose 5 kilograms in 3 months."

[1664] The "means for generating an appearance image" is a technical means for generating an appearance image after the user has achieved the goal based on the user's current body type data and goal data.

[1665] The "means for generating a training menu" refers to a technical means for creating an optimal training plan or exercise program for a user based on the goal data and the user's fitness level.

[1666] The "means for analyzing exercise video" refers to a technical means for analyzing the exercise video taken and uploaded by the user, and for evaluating and providing feedback on the accuracy of the exercise form.

[1667] The "means for proposing a meal plan" refers to a technical means for generating and proposing an optimal meal plan based on the user's goal data and individual conditions.

[1668] "Means for recording progress" refers to technical means for recording and managing a user's progress data, such as daily exercise, diet, and weight changes.

[1669] The "adjustment means" refers to a technical means for changing the training menu and meal plan as needed based on progress data, and providing the user with an optimal program.

[1670] "Emotion recognition means" refers to a technical means for analyzing a user's facial expressions, voice tone, text input, etc., and determining the user's emotional state based on the results, and adjusting the training menu and feedback content.

[1671] MODE FOR CARRYING OUT THE INVENTION

[1672] This invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle, and is also combined with an emotion engine that recognizes the user's emotions. This system acquires the user's basic information and goal data, generates training and meal plans, analyzes exercise form, manages progress, and adjusts these plans and feedback based on the user's emotions.

[1673] 1. User Registration

[1674] When a user launches the app and clicks the "New Registration" button, the device displays a form for the user to enter basic information such as name, email address, password, height, and weight. When the user enters the required information and presses the submit button, the data is sent to the server. The server stores the received user information in a database and creates a user profile.

[1675] 2. Log in

[1676] When a user enters their email address and password and presses the login button, the device sends the entered data to the server. The server checks the user information in the database, and if it matches, it generates an authentication token and sends it to the device. The device saves the received authentication token and displays the dashboard.

[1677] 3. Goal setting

[1678] When a user enters specific fitness goals into the app's "Goal Setting" screen and presses the submit button, the device sends the data from the goal entry form to the server, which stores the received goal data in a database and generates an optimal training plan based on it.

[1679] 4. Image Generation

[1680] When the user clicks the "Generate Image" button to check what they will look like after achieving their goal, the device sends the request to the server. The server uses an image generation algorithm to generate an image of what they will look like after achieving their goal based on the user's current body shape data and goal data. The generated image is sent to the device, which then displays it to the user.

[1681] 5. Training menu generation

[1682] The server creates a personalized training menu based on the user's goals, current fitness level, and previous training data, and sends the created training menu to the device, which then displays it to the user.

[1683] 6. Analysis of exercise form

[1684] When a user films their workout with a camera and uploads the video, the device uploads the video to a server. The server receives the uploaded video data and runs an analysis algorithm to evaluate the accuracy of the workout form and generate feedback. The feedback data is sent to the device, which displays it to the user.

[1685] 7. Meal plan suggestions

[1686] The server generates an optimal meal plan based on the user's goals, current condition, allergy information, etc. The generated meal plan is sent to the device, which then displays it to the user.

[1687] 8. Emotion recognition

[1688] Using the emotion engine, the device analyzes the user's facial expressions, voice tone, and text input. The server receives the recognized emotion data and determines the user's current emotional state. Based on the emotional state, the device appropriately adjusts the training menu and feedback provided.

[1689] 9. Progress Management

[1690] When the user enters progress data such as daily exercise, diet, and weight changes into the app, the device sends the entered progress data to the server. The server stores the received progress data in a database and evaluates the user's progress. If necessary, it adjusts the training menu and meal plan and sends it to the device. The device then displays the adjusted plan to the user.

[1691] Prompt Sentence Examples

[1692] "Please explain in detail the steps for user registration."

[1693] "Please provide a concrete example of how to lose 5 kg in 3 months."

[1694] "Please tell me more about how you analyze your exercise form and provide feedback."

[1695] "Please explain how you propose a meal plan."

[1696] These specific steps and functions enable the system of the present invention to provide the user with personalized health management and training guidance, as well as provide feedback and adjust plans that take into account the user's emotional state.

[1697] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1698] Program processing flow

[1699] Step 1: User Registration

[1700] Input: Basic information such as user name, email address, password, height, and weight

[1701] Processing: The user launches the app and clicks the "New Registration" button. The device displays a form for the user to enter basic information, and after filling it in, the user presses the submit button. The device sends the entered data to the server.

[1702] Data processing: The server stores the received user information in a database and creates a user profile.

[1703] Output: The user's basic information is saved in a database and a profile is created.

[1704] Specific operation: When the app is launched, a "New Registration" button is displayed on the main screen. When the user clicks this, a form requesting name, email address, password, etc. is displayed. When the user enters the required information and presses the submit button, the data is sent to the server.

[1705] Step 2: Log in

[1706] Input: Email address, Password

[1707] Process: The user enters their email address and password and presses the login button. The device sends the entered data to the server.

[1708] Data processing: The server compares the user information with that in the database, and if there is a match, generates an authentication token and sends it to the terminal.

[1709] Output: An authentication token is generated and sent to the device.

[1710] How it works: When a user enters their email address and password on the login screen and presses the "Login" button, the device sends this data to the server. The server compares the input information with existing user data in its database, and if there is a match, it generates an authentication token and sends it to the device.

[1711] Step 3: Goal Setting

[1712] Input: Fitness goal (e.g. lose 5 kg in 3 months)

[1713] Processing: The user enters specific fitness goals into the app's "Goal Setting" screen and presses the submit button. The device then sends the data from the goal entry form to the server.

[1714] Data processing: The server stores the received goal data in a database and generates an optimal training plan.

[1715] Output: Goal data is stored in a database and a training plan is generated.

[1716] Specific operation: The user enters specific goals on the "Goal Setting" screen and presses the send button. This data is sent to the server via the device. The server generates a training plan based on the received goal data.

[1717] Step 4: Image generation

[1718] Input: Current body shape data, goal data

[1719] Processing: The user clicks the "Generate Image" button to see what the image will look like after achieving the goal. The device sends the request to the server.

[1720] Data processing: The server uses an image generation algorithm to generate an image of what the user will look like after achieving their goal, based on the user's current body shape data and goal data.

[1721] Output: An image of the appearance after the goal is achieved is generated and sent to the device.

[1722] Specific operation: When the user clicks the "Generate Image" button, the device sends the request to the server, which then uses an image generation algorithm to generate an image based on the user's body shape data and target data.

[1723] Step 5: Create a training menu

[1724] Input: Goal data, Fitness level, Past training data

[1725] Processing: The server creates a personalized training menu based on the user's goals, fitness level, and previous training data.

[1726] Data processing: The server uses AI algorithms to generate the optimal training plan for the user.

[1727] Output: A training menu is generated and sent to the device.

[1728] How it works: The server uses an AI algorithm to generate a training menu based on your goals, fitness level, and past training data, and sends it to your device.

[1729] Step 6: Analyze your exercise form

[1730] Input: Exercise footage during training

[1731] Processing: The user takes a video of their workout with a camera and uploads the video. The device then uploads the video to the server.

[1732] Data processing: The server analyzes the uploaded video data using an analysis algorithm to evaluate the accuracy of the exercise form.

[1733] Output: Generate feedback and send it to the device.

[1734] How it works: The user takes a video of themselves training and uploads it to the system. The server then uses an analysis algorithm to evaluate the video and sends feedback to the device.

[1735] Step 7: Meal Plan Suggestion

[1736] Input: goal data, allergy information, food preferences

[1737] Processing: The server generates an optimal meal plan based on the user's goals, current condition, allergy information, food preferences, etc.

[1738] Data processing: Using AI algorithms to generate meal plans that take into account calorie restriction and nutritional balance.

[1739] Output: A meal plan is generated and sent to the device.

[1740] Specific operation: The server uses an AI algorithm to generate a meal plan taking into account goals, allergy information, food preferences, etc., and sends it to the device.

[1741] Step 8: Emotion Recognition

[1742] Input: Facial expressions, voice tone, text input

[1743] Processing: Using the emotion engine, the device analyzes the user's facial expressions, voice tone, and text input.

[1744] Data processing: The server receives the recognized emotion data and determines the user's current emotional state.

[1745] Output: Adjust the training menu and feedback content.

[1746] Specific operation: The device analyzes the user's emotions using an emotion engine, and the server adjusts the training menu and feedback based on the results.

[1747] Step 9: Track progress

[1748] Input: Progress data such as daily exercise, diet, and weight changes

[1749] Process: The user enters daily progress data into the app, and the device sends it to the server.

[1750] Data processing: The server stores the received progress data in a database and evaluates the progress using an AI algorithm.

[1751] Output: Adjust your training menu and meal plan as needed and send it to your device.

[1752] What it does: The user enters their daily progress into the app, and the server evaluates their progress based on that information, adjusts the plan as necessary, and sends it to the device.

[1753] (Application example 2)

[1754] 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."

[1755] While interest in fitness and health management is growing in modern society, providing personal training requires a lot of time and effort, and costs and resources are limited, especially when providing services at physical stores. Furthermore, it is difficult to provide feedback and support tailored to each user's emotional state and progress, making it difficult to maintain motivation. Furthermore, there is a demand for a unified service that covers everything from confirming proper exercise form to managing dietary habits when users receive training and instruction at physical stores.

[1756] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring basic information and goal data of the user, means for generating an appearance image of the user after achieving the goal based on the goal data, means for generating an individual training menu based on the goal data and the user's fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and the user's individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, means for analyzing the user's emotions and adjusting the training menu and feedback content based on the user's emotional state, and means for installing the system on a smart device (smart glasses or tablet) optimized for use in a physical store. This enables feedback and training adjustments based on emotions in real time in a physical store, enabling efficient maintenance of user motivation and comprehensive health management.

[1757] "Basic user information" refers to information necessary for creating training and meal plans, such as the user's name, height, weight, age, and gender.

[1758] "Goal Data" refers to specific fitness or health goals set by the user, such as "lose 5 kilograms in 3 months."

[1759] The "appearance image" is an image that visually shows the future body shape after the user achieves the goal, generated based on the user's current body shape data and goal data.

[1760] A "training menu" is an exercise program customized based on a user's goals and fitness level, including specific exercises, exercise frequency, and duration.

[1761] "Exercise video" is video data taken by a user while they are training, and is used to evaluate the accuracy of their exercise form.

[1762] "Exercise form" refers to the physical movements and posture of the user when exercising, and maintaining correct form leads to improved safety and effectiveness.

[1763] A "meal plan" is a meal menu suggested based on the user's goals and physical condition, taking into consideration nutritional balance and calorie restrictions.

[1764] "Progress" is data recorded by the user regarding daily exercise, diet, weight fluctuations, etc., and is used to evaluate progress toward goals.

[1765] "Emotional state" refers to the user's current emotions, analyzed based on the user's facial expressions, voice tone, text input, etc.

[1766] "Feedback content" refers to advice and encouraging messages provided based on the user's exercise form, progress, and emotional state.

[1767] A "smart device" is a device for use by a user, and in the present invention particularly refers to smart glasses or tablets.

[1768] This invention relates to a personal training system that helps users maintain their health, lose weight, and build muscle. The system acquires basic information and goal data from the user and generates individual training and meal plans. It can also recognize the user's emotions and adjust the plans and feedback accordingly.

[1769] Hardware and software used

[1770] Hardware: Smart glasses, tablets, cameras

[1771] Software: Emotion recognition engine (EmotionRecognition), training plan generation engine (TrainingRecommendation), database management system

[1772] Specific explanation of the process

[1773] 1. User Registration and Login:

[1774] The user uses a tablet to enter basic information and send it to the server, which stores it in a database.

[1775] If the user is already registered, they enter their email address and password on the login screen, and the server checks the information against the database.

[1776] 2. Goal Setting:

[1777] Users input their fitness goals using a tablet in the physical store, and the server generates an optimal training plan based on this goal data and displays it on the tablet.

[1778] 3. Training and meal plans provided:

[1779] The server generates personalized training and meal plans based on the user's goals and fitness level, which are displayed on a tablet or smart glasses.

[1780] 4. Real-time analysis of athletic form:

[1781] Cameras and smart glasses installed in the store capture footage of the workout, which is then sent to a server where an algorithm is run to assess the accuracy of the workout form, providing real-time feedback on the tablet or smart glasses.

[1782] 5. Emotion-aware feedback regulation:

[1783] An emotion recognition engine analyzes the user's emotional state based on camera footage, audio, and text input. The server then adjusts the training menu and feedback content based on the recognized emotions, providing encouraging messages as needed.

[1784] 6. Progress Management and Data Entry:

[1785] Users enter their daily exercise routines, dietary habits, weight fluctuations, etc. into a tablet, and this data is sent to a server, where progress is evaluated and the plan is adjusted as necessary.

[1786] Specific examples

[1787] For example, if a user sets a goal of "losing 5 kg in 3 months," the system will generate optimal training and meal plans based on this goal. Footage captured by the camera during training is used to analyze exercise form. Furthermore, if the system determines through an emotion recognition engine that the user's motivation is declining, appropriate feedback and encouraging messages will be displayed on the tablet or smart glasses.

[1788] Example prompt for a generative AI model:

[1789] "Given the user's current body shape data and goal data, generate an image of what they will look like after achieving their goal."

[1790] The above processing makes it possible to provide real-time feedback and adjust training according to emotions in a physical store, thereby maintaining user motivation and efficiently managing overall health.

[1791] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1792] Step 1:

[1793] A user launches the application using a tablet and clicks the "New Registration" button. They enter basic information such as their name, email address, password, height, and weight, and then presses the submit button. This input data is sent from the device to the server. The server stores the received user information in a database and creates a user profile.

[1794] Step 2:

[1795] The user logs in from the tablet using the registered email address and password. The device sends the entered authentication information to the server, which checks it against the user information in the database. If authentication is successful, the server generates an authentication token, sends it to the device, and displays the dashboard to the user.

[1796] Step 3:

[1797] The user opens the "Goal Setting" screen on the tablet and enters their specific fitness goals. The entered goal data is sent from the device to the server, which stores this information in a database. Based on the received goal data, the server generates an optimal training plan and sends it to the tablet.

[1798] Step 4:

[1799] During training, the user uses smart glasses or a camera to capture video of their exercise. This video data is then uploaded to a server via the device. The server receives the uploaded video data and runs an analysis algorithm to evaluate the accuracy of the exercise form. The server generates an evaluation result and appropriate feedback, which it then sends to the device. The device then displays the feedback to the user in real time.

[1800] Step 5:

[1801] The server proposes a customized meal plan based on the user's preset fitness goals and current health status. Taking into account the user's individual conditions (allergies, preferences, etc.), the server generates an optimal meal plan and sends it to the tablet. The device then displays the meal plan and allows the user to view the proposal.

[1802] Step 6:

[1803] The emotion engine analyzes the user's facial expressions, voice tone, and input text through a tablet or smart glasses to determine the user's emotional state. The server receives the analysis results and adjusts the training menu and feedback content according to the user's emotional state. Based on this, feedback messages and encouraging messages that interest the user are displayed on the device.

[1804] Step 7:

[1805] The user enters progress data, such as daily exercise, diet, and weight fluctuations, into a tablet, and the device sends the data to a server. The server stores the received progress data in a database and evaluates the user's progress. Based on the evaluation results, the training menu and meal plan are adjusted as necessary, and a new plan is generated. The new plan is then sent to the device and displayed to the user.

[1806] Through the above process, the system provides comprehensive support for users when receiving personal training at a physical store, and can flexibly adapt to the user's emotional state and progress.

[1807] 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.

[1808] 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.

[1809] 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.

[1810] [Fourth embodiment]

[1811] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1812] 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.

[1813] 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).

[1814] 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.

[1815] 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.

[1816] 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).

[1817] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[1818] 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.

[1819] 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.

[1820] 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.

[1821] 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.

[1822] 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.

[1823] 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."

[1824] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle strength. This system acquires basic information and goal data about the user, and comprehensively generates training and meal plans, analyzes exercise form, and manages progress. Specific embodiments for implementing the present invention are described below.

[1825] Initial Setup

[1826] User Registration

[1827] User: After launching the app, enter basic information such as name, email address, password, height, and weight.

[1828] Terminal: Displays this information as a form and sends the input data to the server.

[1829] Server: Stores the received user information in a database and creates a user profile.

[1830] Log in

[1831] User: Enter your email address and password to log in.

[1832] Terminal: Sends authentication information to the server and displays the dashboard if authentication is successful.

[1833] Server: If authentication is successful, generate an authentication token and send it to the device.

[1834] goal setting

[1835] Goal Input

[1836] User: Enters fitness goal (e.g., lose 5 kg in 3 months) in the in-app goal setting screen.

[1837] Terminal: Sends target data to the server.

[1838] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[1839] Image generation

[1840] Morphing

[1841] User: Makes a request to see what it will look like after achieving the goal.

[1842] Terminal: Sends the request to the server.

[1843] Server: Based on the current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving the goal, and this is sent to the device.

[1844] Terminal: displays the generated image to the user.

[1845] Training menu generation

[1846] Plan creation

[1847] Server: Creates personalized training menus based on the user's goals, current fitness level, and previous training data.

[1848] Server: Sends the generated training menu to the terminal.

[1849] Terminal: Displays the training menu to the user.

[1850] Exercise form analysis

[1851] Video Analysis

[1852] User: Takes video of exercise during training and uploads the video.

[1853] Terminal: Sends the captured video to the server.

[1854] Server: Receives video data and runs exercise form analysis algorithms to evaluate accurate form and generate feedback.

[1855] Server: Sends feedback to the device.

[1856] Terminal: displays the feedback results to the user.

[1857] Meal plan suggestions

[1858] Plan Generation

[1859] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[1860] Server: Sends the generated meal plan to the device.

[1861] Terminal: Display the meal plan to the user.

[1862] Progress management

[1863] Data Entry and Management

[1864] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[1865] Terminal: Sends the entered progress data to the server.

[1866] Server: Stores the received progress data in a database, analyzes the user's progress, and adjusts training menus and meal plans as needed.

[1867] Server: Sends the adjusted plan to the device.

[1868] Device: Display the adjusted plan to the user.

[1869] Specific examples

[1870] For example, if a user sets a goal of "lose 5 kg in 3 months," the system operates as follows:

[1871] 1. After registering and logging in, enter "Lose 5 kg in 3 months" on the goal setting screen.

[1872] 2. The server retrieves the goal data and generates a personalized training menu based on it. The initial training menu includes 30 minutes of cardio and 15 minutes of strength training three times a week.

[1873] 3. The user takes a video of themselves training with a camera and uploads the video to the system.

[1874] 4. The server analyzes the uploaded video, evaluates whether the exercise form is correct, and provides necessary feedback.

[1875] 5. Furthermore, the server generates and presents a meal plan that takes into account calorie restriction and nutritional balance to help the user achieve their goals.

[1876] 6. The user enters daily progress data (e.g., diet, exercise, weight changes), and the server evaluates the progress based on this and adjusts the individual plan if necessary.

[1877] In this way, the system of the present invention allows users to always receive appropriate and personalized health management and training guidance, enabling them to progress efficiently toward their goals.

[1878] The processing flow will be explained below.

[1879] Step 1: User Registration

[1880] User: Launch the app and click the "New Registration" button.

[1881] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[1882] User: Enter the required information and press the send button.

[1883] Terminal: Sends the entered data to the server.

[1884] Server: Stores the received user information in a database and creates a user profile.

[1885] Step 2: Log in

[1886] User: Enter your email address and password and click the login button.

[1887] Terminal: Sends the entered data to the server.

[1888] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[1889] Terminal: Save the received authentication token and display the dashboard.

[1890] Step 3: Goal Setting

[1891] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[1892] Terminal: Sends the data from the target input form to the server.

[1893] Server: The received goal data is stored in a database and used as the basis for generating optimal training plans.

[1894] Step 4: Image generation

[1895] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[1896] Terminal: Sends requests to the server.

[1897] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[1898] Server: Sends the generated image to the terminal.

[1899] Terminal: displays the generated image to the user.

[1900] Step 5: Create a training menu

[1901] Server: Generates an individual training menu based on the user's goals, current fitness level, and past training data.

[1902] Server: Sends the generated training menu to the terminal.

[1903] Terminal: Displays the training menu to the user.

[1904] Step 6: Analyze your exercise form

[1905] User: Records exercise during training and uploads the video.

[1906] Device: Upload the captured video to the server.

[1907] Server: Receives uploaded video data and executes analysis algorithms.

[1908] Server: Evaluates the accuracy of the exercise form and generates the necessary feedback.

[1909] Server: Sends feedback data to the device.

[1910] Terminal: displays the feedback results to the user.

[1911] Step 7: Meal Plan Suggestion

[1912] Server: Generates an optimal meal plan based on the user's goals, current condition, allergy information, etc.

[1913] Server: Sends the generated meal plan to the device.

[1914] Terminal: Display the meal plan to the user.

[1915] Step 8: Track progress

[1916] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[1917] Terminal: Sends the entered progress data to the server.

[1918] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[1919] Server: Sends the adjusted plan to the device.

[1920] Device: Display the adjusted plan to the user.

[1921] Example 1

[1922] 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."

[1923] Conventional fitness and diet systems have problems in that they do not adequately propose detailed training menus and meal plans tailored to the user's individual needs, nor do they adequately analyze and provide feedback on exercise form. In particular, there is a demand for systems that can efficiently approach the goals set by the user. Without such systems, users may not receive appropriate guidance or adjustments to achieve their goals, which can result in a loss of motivation. Another issue is the lack of a function that reflects the user's progress data in real time and provides appropriate advice.

[1924] 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.

[1925] In this invention, the server includes: means for acquiring a user's basic information and goal data; means for generating an image of the user's appearance after achieving their goal based on the goal data; means for generating an individual training menu based on the goal data and the user's fitness level; means for analyzing exercise video data uploaded by the user and evaluating and providing feedback on accurate exercise form; means for proposing an optimal meal plan based on the goal data and the user's individual conditions; means for acquiring and recording the user's daily progress data and adjusting the training menu and meal plan as needed; and means for verifying authentication information and displaying the app's dashboard screen. This allows users to receive individually optimized training guidance and dietary advice, helping them efficiently achieve their goals. Furthermore, real-time feedback and plan adjustments based on the user's progress make it easier for them to maintain motivation.

[1926] "User" refers to an individual who uses the System.

[1927] "Basic information" refers to initial setting data such as the user's name, email address, password, height, and weight.

[1928] "Goal data" refers to the specific fitness or diet goal values ​​and details that a user wants to achieve.

[1929] The "appearance image" refers to image data that represents the virtual appearance of the user after achieving the goal.

[1930] "Fitness level" refers to information that indicates the user's current athletic ability and health condition.

[1931] A "training menu" refers to a plan that indicates the specific exercises and training content that a user will perform to achieve their goal.

[1932] "Exercise video data" refers to video data captured by a user while they are training.

[1933] "Form analysis" refers to the process of evaluating a user's exercise form and analyzing its accuracy based on their exercise video data.

[1934] "Feedback" refers to assessment and advice provided to a user regarding exercise form and progress.

[1935] "Meal Plan" refers to a meal plan suggested based on a user's goals and individual requirements.

[1936] "Progress data" refers to continuously recorded data such as a user's exercise, diet, and weight changes.

[1937] "Token" refers to a digital identifier used to identify an authenticated user's session.

[1938] "Dashboard" refers to a screen where users can check their progress and plans in one place through the app.

[1939] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle strength. This system acquires basic information and goal data about the user, and comprehensively generates training and meal plans, analyzes exercise form, and manages progress. Specific embodiments are described below.

[1940] Initial Setup

[1941] User Registration

[1942] The user launches the app and enters information such as name, email address, password, height, and weight on the input screen.

[1943] The device temporarily stores the user's input data and sends it to the server in JSON format.

[1944] The server validates the received data, stores it in a database (MySQL), creates a new user profile, and returns a success message to the terminal.

[1945] Log in

[1946] The user enters their email address and password on the login screen.

[1947] The terminal transmits the entered authentication information to the server.

[1948] The server verifies the user information in the database and, if authentication is successful, generates a JWT (JSON Web Token).

[1949] The server returns the generated JWT to the terminal, which saves it and displays the dashboard screen.

[1950] goal setting

[1951] Goal Input

[1952] The user enters "lose 5 kg in 3 months" into the app's goal setting screen.

[1953] The device sends the entered goal data to the server in JSON format.

[1954] The server stores the received goal data in a database and generates a personalized training plan for the user based on the goals.

[1955] The server returns the generated training plan to the terminal, which displays it to the user.

[1956] Image generation

[1957] Morphing

[1958] The user makes a request to see what it will look like after achieving the goal.

[1959] The terminal sends a request to the server.

[1960] The server reads the current body shape data and runs the image generation algorithm using TensorFlow along with the target data.

[1961] The server sends the generated image to the terminal, which displays the image to the user.

[1962] Training menu generation

[1963] Plan creation

[1964] The server obtains the user's goals, current fitness level, and past training data, and uses an algorithm to generate a personalized training menu.

[1965] The server transmits the generated training menu to the terminal.

[1966] The terminal displays a training menu to the user.

[1967] Exercise form analysis

[1968] Video Analysis

[1969] Users can record their workouts with a camera and upload the videos.

[1970] The device sends the captured video to the server.

[1971] The server receives the video data and runs a motion form analysis algorithm using OpenPose.

[1972] The server evaluates the user's exercise form based on the analysis results and generates feedback.

[1973] The server sends the feedback to the terminal, which displays the results to the user.

[1974] Meal plan suggestions

[1975] Plan Generation

[1976] The server takes the user's goals, current condition, and allergy information and uses an algorithm to generate an optimal meal plan.

[1977] The server transmits the generated meal plan to the terminal.

[1978] The terminal displays the meal plan to the user.

[1979] Progress management

[1980] Data Entry and Management

[1981] Users enter progress data such as daily exercise, diet, and weight changes into the app.

[1982] The terminal transmits the input data to the server.

[1983] The server stores the received progress data in a database and analyzes the progress using an algorithm.

[1984] The server will adjust your training menu and meal plan as needed based on your progress data.

[1985] The server sends the adjusted plan to the terminal, which displays it to the user.

[1986] Prompt Sentence Examples

[1987] "Generate what your goal will look like after you achieve it."

[1988] "Create a training plan to lose 5 kg in 3 months."

[1989] This system allows users to always receive appropriate and personalized health management and training guidance, enabling them to progress efficiently toward their goals.

[1990] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1991] Step 1:

[1992] User Registration

[1993] The user launches the app and enters information such as name, email address, password, height, and weight on the input screen.

[1994] Input: Name, email address, password, height, weight

[1995] The device temporarily stores the user's input data and sends it to the server in JSON format.

[1996] Output: User registration data in JSON format

[1997] The server validates the received data, stores it in a database (MySQL), creates a new user profile, and returns a success message to the terminal.

[1998] Input: JSON format user registration data

[1999] Output: Success message

[2000] Step 2:

[2001] Log in

[2002] The user enters their email address and password on the login screen.

[2003] Input: Email address, password

[2004] The terminal transmits the entered authentication information to the server.

[2005] Output: Credentials in JSON format

[2006] The server verifies the user information in the database and, if authentication is successful, generates a JWT (JSON Web Token).

[2007] Input: JSON formatted credentials

[2008] Output: JWT (JSON Web Token)

[2009] The server returns the generated JWT to the terminal, which saves it and displays the dashboard screen.

[2010] Input: JWT (JSON Web Token)

[2011] Output: Dashboard screen

[2012] Step 3:

[2013] Goal Input

[2014] The user enters "lose 5 kg in 3 months" into the app's goal setting screen.

[2015] Input: Goal data (e.g., "lose 5 kg in 3 months")

[2016] The device sends the entered goal data to the server in JSON format.

[2017] Output: Goal data in JSON format

[2018] The server stores the received goal data in a database and generates a personalized training plan for the user based on the goals.

[2019] Input: Goal data in JSON format

[2020] Data processing: Create a plan using a training plan generation algorithm

[2021] Output: Training Plan

[2022] The server returns the generated training plan to the terminal, which displays it to the user.

[2023] Input: Training plan

[2024] Output: Training plan display screen

[2025] Step 4:

[2026] Morphing Request

[2027] The user makes a request to see what it will look like after achieving the goal.

[2028] Input: Request data (check appearance after goal achievement)

[2029] The terminal sends the request to the server.

[2030] Output: Request data

[2031] The server reads the current body shape data and runs the image generation algorithm using TensorFlow along with the target data.

[2032] Input: Current body shape data, goal data

[2033] Data Computation: Morphing with Image Generation Algorithms

[2034] Output: Generated image

[2035] The server sends the generated image to the terminal, which displays the image to the user.

[2036] Input: Generated appearance image

[2037] Output: Image display screen

[2038] Step 5:

[2039] Creating a training menu

[2040] The server obtains the user's goals, current fitness level, and past training data, and uses an algorithm to generate a personalized training menu.

[2041] Input: Goal data, Fitness level, Training history

[2042] Data processing: Create a plan using a training menu generation algorithm

[2043] Output: Training menu

[2044] The server transmits the generated training menu to the terminal.

[2045] Input: Training Menu

[2046] Output: Training menu display screen

[2047] Step 6:

[2048] Exercise form analysis

[2049] Users can record their workouts with a camera and upload the videos.

[2050] Input: Exercise video data

[2051] The device sends the captured video to the server.

[2052] Output: Video data

[2053] The server receives the video data and runs a motion form analysis algorithm using OpenPose.

[2054] Input: Video data

[2055] Data processing: Form evaluation using exercise form analysis algorithms

[2056] Output: Evaluation results and feedback data

[2057] The server sends the feedback to the terminal, which displays the results to the user.

[2058] Input: Feedback data

[2059] Output: Feedback display screen

[2060] Step 7:

[2061] Meal plan suggestions

[2062] The server takes the user's goals, current condition, and allergy information and uses an algorithm to generate an optimal meal plan.

[2063] Input: goal data, current condition, allergy information

[2064] Data processing: Meal plan generation algorithm

[2065] Output: Meal plan

[2066] The server transmits the generated meal plan to the terminal.

[2067] Input: meal plan

[2068] Output: Meal plan display screen

[2069] Step 8:

[2070] Progress management

[2071] Users enter progress data such as daily exercise, diet, and weight changes into the app.

[2072] Input: Progress data (exercise, diet, weight changes)

[2073] The terminal transmits the input data to the server.

[2074] Output: Progress data

[2075] The server stores the received progress data in a database and uses an algorithm to analyze the progress.

[2076] Input: Progress data

[2077] Data Computing: Evaluation with Progress Data Analysis Algorithms

[2078] Output: Analysis results

[2079] The server will adjust your training menu and meal plan as needed based on your progress data.

[2080] Input: Analysis results

[2081] Output: Adjusted plan

[2082] The server sends the adjusted plan to the terminal, which displays it to the user.

[2083] Input: Adjusted plan

[2084] Output: Adjusted plan display screen

[2085] (Application example 1)

[2086] 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."

[2087] Conventional personal training systems have had difficulty individually examining a user's exercise form and dietary habits and providing feedback based on that. Furthermore, the generation of training and meal plans for achieving goals is based on general algorithms, which do not adequately reflect the user's individual circumstances. This makes it difficult to achieve effective training and health management.

[2088] 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.

[2089] In this invention, the server includes means for acquiring basic information and goal data of a user, means for generating an appearance image of the user after achieving the goal, means for generating an individual training menu based on the goal data and the user's fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and the user's individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, means for using a generative AI model to generate a training plan based on the user's goal settings, and means for generating prompts for the generative AI model, thereby enabling effective training and health management based on the user's individual conditions.

[2090] "User basic information" refers to personal information provided by a user, including name, email address, password, height, weight, etc.

[2091] "Goal data" refers to specific fitness or health goals set by the user, such as "lose 5 kilograms in 3 months."

[2092] An "appearance image" is an image generated to visually display the body shape and appearance of a user after achieving the goal set by the user.

[2093] "Fitness level" refers to the user's current physical strength and athletic ability, and is evaluated based on past training results and physical condition.

[2094] An "individual training menu" is an exercise plan that is optimized for each individual user and is generated based on the user's goal data and fitness level.

[2095] "Exercise footage" refers to video data taken by a user while they are training, and is used to analyze their exercise form.

[2096] "Exercise form" refers to the movements and postures that a user performs during training, and their accuracy and efficiency are evaluated.

[2097] "Feedback" refers to the evaluation and advice for improvement that the system provides to the user regarding their exercise form.

[2098] "Individual conditions" refers to information about the user's own health and lifestyle, such as the user's allergy information, favorite ingredients, and dietary restrictions.

[2099] A "meal plan" is a specific meal plan proposed based on the user's goal data and individual conditions to help the user achieve their goals.

[2100] "Progress" refers to the current exercise and dietary details, changes in weight and body shape, and the like, relative to the goal set by the user.

[2101] A "generative AI model" is an artificial intelligence model that uses deep learning and machine learning techniques to generate training plans and meal plans from user data.

[2102] A "prompt" is a document that provides instructions and input information to a generative AI model, and is created based on the user's current situation and goals.

[2103] The present invention is a personal training system that collects basic information and goal data of a user, generates an individual training menu and meal plan based on the collected information, and supports the user in maintaining their health and achieving their goals. This system is implemented as follows.

[2104] Initial Setup

[2105] The server obtains the user's basic information (such as name, email address, password, height, and weight) and stores it in a database. A user profile is created based on this information. The device (smartphone or household robot) displays a form and sends the data entered by the user to the server. The server also manages authentication information and generates an appropriate authentication token when the user logs in and sends it to the device.

[2106] goal setting

[2107] Users set fitness goals in an application on their device. For example, they can set a specific goal like "lose 5 kg in 3 months." The server receives this goal data and stores it in a database. Based on this, it generates a personalized training menu.

[2108] Training menu generation

[2109] The server generates a personalized training menu based on the user's goal data and fitness level. It uses a generative AI model and inputs prompts. These prompts contain information needed to help the user achieve their goals. For example,

[2110] To help users achieve their goals, please propose a personal training plan based on the following information:

[2111] Username: Example

[2112] Age: 35

[2113] Current weight: 75kg

[2114] Goal: Lose 5kg in 3 months

[2115] Fitness Level: Beginner

[2116] Allergies: None

[2117] This generated training menu is sent from the server to the terminal and displayed to the user.

[2118] Exercise form analysis

[2119] During exercise, users record their own training videos and upload them to a server via their device. The server receives the video data and runs an exercise form analysis algorithm (e.g., a deep learning model using Keras) to accurately evaluate their exercise form and provide feedback to the user.

[2120] Meal plan suggestions

[2121] The server generates an optimal meal plan based on the user's goals and individual conditions (allergy information, dietary preferences, etc.). This data is also processed using a generative AI model. The generated meal plan is sent from the server to the device and presented to the user.

[2122] Progress management

[2123] The user inputs their daily progress (exercise, diet, weight change, etc.) on the device. The server receives this progress data and stores it in a database. If necessary, the server adjusts the training menu and meal plan and provides the user with the latest plan.

[2124] This allows users to easily receive personal training at home and efficiently achieve their goals based on individual training and dietary advice.

[2125] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2126] Step 1: User Registration

[2127] The server receives basic information from the user (such as name, email address, password, height, and weight) and stores it in a database. The terminal displays the basic information entered by the user in a form and sends the information entered by the user to the server. The input is the user's basic information, and the output is the user's profile stored in the database.

[2128] Step 2: Log in

[2129] The server receives the authentication information (email address, password) entered by the user and checks it in the database. If authentication is successful, the server generates an authentication token and sends it to the terminal. The terminal displays the generated authentication token and notifies the user that login was successful. The input is authentication information and the output is the authentication token.

[2130] Step 3: Goal Setting

[2131] A user sets a fitness goal (e.g., "lose 5 kg in 3 months") in an application on their device. This information is sent from the device to a server, which stores the goal data in a database. The input is the goal data, and the output is the goal data stored in the database.

[2132] Step 4: Create a training menu

[2133] The server uses a generative AI model to create prompts based on the user's goal data and fitness level. The generative AI model generates a training menu based on the prompts, and the server stores the generated menu in a database and sends it to the terminal. The terminal displays the training menu to the user. The input is the goal data and fitness level, and the output is the generated training menu.

[2134] Step 5: Analyze your exercise form

[2135] The user takes a video of themselves training on their device and uploads it to the server. The server receives the video data and runs an exercise form analysis algorithm (using Keras) to generate an analysis of their exercise form. The server stores the results in a database, generates feedback, and sends it to the device. The device displays the feedback to the user. The input is the exercise video, and the output is the feedback results.

[2136] Step 6: Meal plan suggestions

[2137] The server uses a generative AI model to generate a meal plan based on the user's goal data and individual conditions (allergy information, likes and dislikes, etc.), and stores it in a database. The server then sends the generated meal plan to the device, which displays it to the user. The input is the goal data and individual conditions, and the output is the generated meal plan.

[2138] Step 7: Track progress

[2139] The user inputs progress data, such as daily exercise, diet, and weight changes, into the device. The server receives this data, stores it in a database, and analyzes the progress. If necessary, the server adjusts the training menu and meal plan and sends the updated plan to the device. The device displays the adjusted plan to the user. The input is progress data, and the output is the adjusted training menu and meal plan.

[2140] 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.

[2141] The present invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle, and further combines it with an emotion engine that recognizes the user's emotions. This system acquires the user's basic information and goal data, generates training plans and meal plans, analyzes exercise form, manages progress, and adjusts these plans and feedback based on the user's emotions. Specific embodiments for implementing the present invention are described below.

[2142] Initial Setup

[2143] User Registration

[2144] User: Launch the app and click the "New Registration" button.

[2145] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[2146] User: Enter the required information and press the send button.

[2147] Terminal: Sends the entered data to the server.

[2148] Server: Stores the received user information in a database and creates a user profile.

[2149] Log in

[2150] User: Enter your email address and password and click the login button.

[2151] Terminal: Sends the entered data to the server.

[2152] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[2153] Terminal: Save the received authentication token and display the dashboard.

[2154] goal setting

[2155] Goal Input

[2156] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[2157] Terminal: Sends the data from the target input form to the server.

[2158] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[2159] Image generation

[2160] Morphing

[2161] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[2162] Terminal: Sends the request to the server.

[2163] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[2164] Server: Sends the generated image to the terminal.

[2165] Terminal: displays the generated image to the user.

[2166] Training menu generation

[2167] Plan creation

[2168] Server: Creates personalized training menus based on the user's goals, current fitness level, and previous training data.

[2169] Server: Sends the generated training menu to the terminal.

[2170] Terminal: Displays the training menu to the user.

[2171] Exercise form analysis

[2172] Video Analysis

[2173] User: Records exercise during training and uploads the video.

[2174] Device: Upload the captured video to the server.

[2175] Server: Receives uploaded video data and executes analysis algorithms.

[2176] Server: Evaluates the accuracy of exercise form and generates feedback.

[2177] Server: Sends feedback data to the device.

[2178] Terminal: displays the feedback results to the user.

[2179] Meal plan suggestions

[2180] Plan Generation

[2181] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[2182] Server: Sends the generated meal plan to the device.

[2183] Terminal: Display the meal plan to the user.

[2184] emotion recognition

[2185] Introducing the Emotion Engine

[2186] Terminal: The emotion engine analyzes the user's facial expressions, voice tone, and text input.

[2187] Server: Receives the recognized emotion data and determines the user's current emotional state.

[2188] Server: Based on the emotional state, the training menu and feedback provided are adjusted appropriately.

[2189] Progress management

[2190] Data Entry and Management

[2191] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[2192] Terminal: Sends the entered progress data to the server.

[2193] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[2194] Server: Sends the adjusted plan to the device.

[2195] Device: Display the adjusted plan to the user.

[2196] Specific examples

[2197] For example, if a user sets a goal of "lose 5 kg in 3 months," the system operates as follows:

[2198] 1. After registering and logging in, enter "Lose 5 kg in 3 months" on the goal setting screen.

[2199] 2. The server retrieves the goal data and generates a personalized training menu based on it. The initial training menu includes 30 minutes of cardio and 15 minutes of strength training three times a week.

[2200] 3. The user takes a video of themselves training with a camera and uploads the video to the system.

[2201] 4. The server analyzes the uploaded video, evaluates whether the exercise form is correct, and provides necessary feedback.

[2202] 5. Furthermore, the server generates and presents a meal plan that takes into account calorie restriction and nutritional balance to help the user achieve their goals.

[2203] 6. The emotion engine recognizes the user's emotions, and if it determines that motivation is declining, it provides encouraging feedback and makes adjustments to increase motivation.

[2204] 7. The user enters daily progress data (e.g., diet, exercise, weight changes), and the server evaluates the progress based on this and adjusts the individual plan if necessary.

[2205] In this way, the system of the present invention allows users to always receive appropriate and personalized health management and training guidance, and the introduction of an emotion engine helps maintain and improve motivation, enabling users to make effective progress toward their goals.

[2206] The processing flow will be explained below.

[2207] Step 1: User Registration

[2208] User: Launch the app and click the "New Registration" button.

[2209] Terminal: Presents a form for the user to enter basic information such as name, email address, password, height, and weight.

[2210] User: Enter the required information and press the send button.

[2211] Terminal: Sends the entered data to the server.

[2212] Server: Stores the received user information in a database and creates a user profile.

[2213] Step 2: Log in

[2214] User: Enter your email address and password and click the login button.

[2215] Terminal: Sends the entered data to the server.

[2216] Server: Compares the user information with that in the database, and if it matches, generates an authentication token and sends it to the terminal.

[2217] Terminal: Save the received authentication token and display the dashboard.

[2218] Step 3: Goal Setting

[2219] User: Enter a specific fitness goal (e.g., lose 5 kg in 3 months) on the "Goal Setting" screen within the app and press the submit button.

[2220] Terminal: Sends the data from the target input form to the server.

[2221] Server: Stores the received goal data in a database and generates an optimal training plan based on it.

[2222] Step 4: Image generation (morphing)

[2223] User: Clicks the "Generate Image" button to see what it will look like once the goal is achieved.

[2224] Terminal: Sends the request to the server.

[2225] Server: Based on the user's current body shape data and goal data, an image generation algorithm is used to generate an image of what the user will look like after achieving their goal.

[2226] Server: Sends the generated image to the terminal.

[2227] Terminal: displays the generated image to the user.

[2228] Step 5: Create a training menu

[2229] Server: Generates a personalized training menu based on the user's goals, current fitness level, and past training data.

[2230] Server: Sends the generated training menu to the terminal.

[2231] Terminal: Displays the training menu to the user.

[2232] Step 6: Analyze your exercise form

[2233] User: Records exercise during training and uploads the video.

[2234] Device: Upload the captured video to the server.

[2235] Server: Receives uploaded video data and executes analysis algorithms.

[2236] Server: Evaluates the accuracy of exercise form and generates feedback.

[2237] Server: Sends feedback data to the device.

[2238] Terminal: displays the feedback results to the user.

[2239] Step 7: Meal Plan Suggestion

[2240] Server: Generates the optimal meal plan based on the user's goals, current condition, allergy information, etc.

[2241] Server: Sends the generated meal plan to the device.

[2242] Terminal: Display the meal plan to the user.

[2243] Step 8: Emotion Recognition

[2244] Terminal: The emotion engine analyzes the user's facial expressions, voice tone, and text input.

[2245] Server: Receives the recognized emotion data and determines the user's current emotional state.

[2246] Server: Based on the emotional state, the training menu and feedback provided are adjusted appropriately.

[2247] Step 9: Track progress

[2248] User: Enter progress data such as daily exercise, diet, and weight changes within the app.

[2249] Terminal: Sends the entered progress data to the server.

[2250] Server: Stores the received progress data in a database, evaluates the user's progress, and adjusts training and meal plans as needed.

[2251] Server: Sends the adjusted plan to the device.

[2252] Device: Display the adjusted plan to the user.

[2253] Example 2

[2254] 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."

[2255] Conventional personal training systems lack the ability to generate personalized training and meal plans to help users achieve their goals, making progress management difficult, and they also lack the ability to adjust feedback based on the user's emotional state, making it difficult to maintain user motivation.

[2256] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring basic information and goal data of the user, means for generating an appearance image of the user after achieving the goal based on the goal data, means for generating an individual training menu based on the goal data and fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, and emotion recognition means for analyzing the user's facial expression, voice tone, and text input and adjusting the training menu and feedback content based on the results. This allows the user to receive individualized health management and training guidance, and makes it easier to maintain motivation through feedback adjustment based on the user's emotional state.

[2257] "User" means any individual or collective entity that uses this system.

[2258] "Basic information" is data for identifying a user, such as the user's name, email address, password, height, and weight.

[2259] "Goal Data" refers to specific fitness-related goals set by a user. An example would be "lose 5 kilograms in 3 months."

[2260] The "means for generating an appearance image" is a technical means for generating an appearance image after the user has achieved the goal based on the user's current body type data and goal data.

[2261] The "means for generating a training menu" refers to a technical means for creating an optimal training plan or exercise program for a user based on the goal data and the user's fitness level.

[2262] The "means for analyzing exercise video" refers to a technical means for analyzing the exercise video taken and uploaded by the user, and for evaluating and providing feedback on the accuracy of the exercise form.

[2263] The "means for proposing a meal plan" refers to a technical means for generating and proposing an optimal meal plan based on the user's goal data and individual conditions.

[2264] "Means for recording progress" refers to technical means for recording and managing a user's progress data, such as daily exercise, diet, and weight changes.

[2265] The "adjustment means" refers to a technical means for changing the training menu and meal plan as needed based on progress data, and providing the user with an optimal program.

[2266] "Emotion recognition means" refers to a technical means for analyzing a user's facial expressions, voice tone, text input, etc., and determining the user's emotional state based on the results, and adjusting the training menu and feedback content.

[2267] MODE FOR CARRYING OUT THE INVENTION

[2268] This invention is a personal training system that effectively supports users in maintaining their health, dieting, and building muscle, and is also combined with an emotion engine that recognizes the user's emotions. This system acquires the user's basic information and goal data, generates training and meal plans, analyzes exercise form, manages progress, and adjusts these plans and feedback based on the user's emotions.

[2269] 1. User Registration

[2270] When a user launches the app and clicks the "New Registration" button, the device displays a form for the user to enter basic information such as name, email address, password, height, and weight. When the user enters the required information and presses the submit button, the data is sent to the server. The server stores the received user information in a database and creates a user profile.

[2271] 2. Log in

[2272] When a user enters their email address and password and presses the login button, the device sends the entered data to the server. The server checks the user information in the database, and if it matches, it generates an authentication token and sends it to the device. The device saves the received authentication token and displays the dashboard.

[2273] 3. Goal setting

[2274] When a user enters specific fitness goals into the app's "Goal Setting" screen and presses the submit button, the device sends the data from the goal entry form to the server, which stores the received goal data in a database and generates an optimal training plan based on it.

[2275] 4. Image Generation

[2276] When the user clicks the "Generate Image" button to check what they will look like after achieving their goal, the device sends the request to the server. The server uses an image generation algorithm to generate an image of what they will look like after achieving their goal based on the user's current body shape data and goal data. The generated image is sent to the device, which then displays it to the user.

[2277] 5. Training menu generation

[2278] The server creates a personalized training menu based on the user's goals, current fitness level, and previous training data, and sends the created training menu to the device, which then displays it to the user.

[2279] 6. Analysis of exercise form

[2280] When a user films their workout with a camera and uploads the video, the device uploads the video to a server. The server receives the uploaded video data and runs an analysis algorithm to evaluate the accuracy of the workout form and generate feedback. The feedback data is sent to the device, which displays it to the user.

[2281] 7. Meal plan suggestions

[2282] The server generates an optimal meal plan based on the user's goals, current condition, allergy information, etc. The generated meal plan is sent to the device, which then displays it to the user.

[2283] 8. Emotion recognition

[2284] Using the emotion engine, the device analyzes the user's facial expressions, voice tone, and text input. The server receives the recognized emotion data and determines the user's current emotional state. Based on the emotional state, the device appropriately adjusts the training menu and feedback provided.

[2285] 9. Progress Management

[2286] When the user enters progress data such as daily exercise, diet, and weight changes into the app, the device sends the entered progress data to the server. The server stores the received progress data in a database and evaluates the user's progress. If necessary, it adjusts the training menu and meal plan and sends it to the device. The device then displays the adjusted plan to the user.

[2287] Prompt Sentence Examples

[2288] "Please explain in detail the steps for user registration."

[2289] "Please provide a concrete example of how to lose 5 kg in 3 months."

[2290] "Please tell me more about how you analyze your exercise form and provide feedback."

[2291] "Please explain how you propose a meal plan."

[2292] These specific steps and functions enable the system of the present invention to provide the user with personalized health management and training guidance, as well as provide feedback and adjust plans that take into account the user's emotional state.

[2293] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2294] Program processing flow

[2295] Step 1: User Registration

[2296] Input: Basic information such as user name, email address, password, height, and weight

[2297] Processing: The user launches the app and clicks the "New Registration" button. The device displays a form for the user to enter basic information, and after filling it in, the user presses the submit button. The device sends the entered data to the server.

[2298] Data processing: The server stores the received user information in a database and creates a user profile.

[2299] Output: The user's basic information is saved in a database and a profile is created.

[2300] Specific operation: When the app is launched, a "New Registration" button is displayed on the main screen. When the user clicks this, a form requesting name, email address, password, etc. is displayed. When the user enters the required information and presses the submit button, the data is sent to the server.

[2301] Step 2: Log in

[2302] Input: Email address, Password

[2303] Process: The user enters their email address and password and presses the login button. The device sends the entered data to the server.

[2304] Data processing: The server compares the user information with that in the database, and if there is a match, generates an authentication token and sends it to the terminal.

[2305] Output: An authentication token is generated and sent to the device.

[2306] How it works: When a user enters their email address and password on the login screen and presses the "Login" button, the device sends this data to the server. The server compares the input information with existing user data in its database, and if there is a match, it generates an authentication token and sends it to the device.

[2307] Step 3: Goal Setting

[2308] Input: Fitness goal (e.g. lose 5 kg in 3 months)

[2309] Processing: The user enters specific fitness goals into the app's "Goal Setting" screen and presses the submit button. The device then sends the data from the goal entry form to the server.

[2310] Data processing: The server stores the received goal data in a database and generates an optimal training plan.

[2311] Output: Goal data is stored in a database and a training plan is generated.

[2312] Specific operation: The user enters specific goals on the "Goal Setting" screen and presses the send button. This data is sent to the server via the device. The server generates a training plan based on the received goal data.

[2313] Step 4: Image generation

[2314] Input: Current body shape data, goal data

[2315] Processing: The user clicks the "Generate Image" button to see what the image will look like after achieving the goal. The device sends the request to the server.

[2316] Data processing: The server uses an image generation algorithm to generate an image of what the user will look like after achieving their goal, based on the user's current body shape data and goal data.

[2317] Output: An image of the appearance after the goal is achieved is generated and sent to the device.

[2318] Specific operation: When the user clicks the "Generate Image" button, the device sends the request to the server, which then uses an image generation algorithm to generate an image based on the user's body shape data and target data.

[2319] Step 5: Create a training menu

[2320] Input: Goal data, Fitness level, Past training data

[2321] Processing: The server creates a personalized training menu based on the user's goals, fitness level, and previous training data.

[2322] Data processing: The server uses AI algorithms to generate the optimal training plan for the user.

[2323] Output: A training menu is generated and sent to the device.

[2324] How it works: The server uses an AI algorithm to generate a training menu based on your goals, fitness level, and past training data, and sends it to your device.

[2325] Step 6: Analyze your exercise form

[2326] Input: Exercise footage during training

[2327] Processing: The user takes a video of their workout with a camera and uploads the video. The device then uploads the video to the server.

[2328] Data processing: The server analyzes the uploaded video data using an analysis algorithm to evaluate the accuracy of the exercise form.

[2329] Output: Generate feedback and send it to the device.

[2330] How it works: The user takes a video of themselves training and uploads it to the system. The server then uses an analysis algorithm to evaluate the video and sends feedback to the device.

[2331] Step 7: Meal Plan Suggestion

[2332] Input: goal data, allergy information, food preferences

[2333] Processing: The server generates an optimal meal plan based on the user's goals, current condition, allergy information, food preferences, etc.

[2334] Data processing: Using AI algorithms to generate meal plans that take into account calorie restriction and nutritional balance.

[2335] Output: A meal plan is generated and sent to the device.

[2336] Specific operation: The server uses an AI algorithm to generate a meal plan taking into account goals, allergy information, food preferences, etc., and sends it to the device.

[2337] Step 8: Emotion Recognition

[2338] Input: Facial expressions, voice tone, text input

[2339] Processing: Using the emotion engine, the device analyzes the user's facial expressions, voice tone, and text input.

[2340] Data processing: The server receives the recognized emotion data and determines the user's current emotional state.

[2341] Output: Adjust the training menu and feedback content.

[2342] Specific operation: The device analyzes the user's emotions using an emotion engine, and the server adjusts the training menu and feedback based on the results.

[2343] Step 9: Track progress

[2344] Input: Progress data such as daily exercise, diet, and weight changes

[2345] Process: The user enters daily progress data into the app, and the device sends it to the server.

[2346] Data processing: The server stores the received progress data in a database and evaluates the progress using an AI algorithm.

[2347] Output: Adjust your training menu and meal plan as needed and send it to your device.

[2348] What it does: The user enters their daily progress into the app, and the server evaluates their progress based on that information, adjusts the plan as necessary, and sends it to the device.

[2349] (Application example 2)

[2350] 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."

[2351] While interest in fitness and health management is growing in modern society, providing personal training requires a lot of time and effort, and costs and resources are limited, especially when providing services at physical stores. Furthermore, it is difficult to provide feedback and support tailored to each user's emotional state and progress, making it difficult to maintain motivation. Furthermore, there is a demand for a unified service that covers everything from confirming proper exercise form to managing dietary habits when users receive training and instruction at physical stores.

[2352] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring basic information and goal data of the user, means for generating an appearance image of the user after achieving the goal based on the goal data, means for generating an individual training menu based on the goal data and the user's fitness level, means for analyzing exercise videos uploaded by the user and evaluating and providing feedback on accurate exercise form, means for proposing an optimal meal plan based on the goal data and the user's individual conditions, means for recording progress and adjusting the training menu and meal plan as necessary, means for analyzing the user's emotions and adjusting the training menu and feedback content based on the user's emotional state, and means for installing the system on a smart device (smart glasses or tablet) optimized for use in a physical store. This enables feedback and training adjustments based on emotions in real time in a physical store, enabling efficient maintenance of user motivation and comprehensive health management.

[2353] "Basic user information" refers to information necessary for creating training and meal plans, such as the user's name, height, weight, age, and gender.

[2354] "Goal Data" refers to specific fitness or health goals set by the user, such as "lose 5 kilograms in 3 months."

[2355] The "appearance image" is an image that visually shows the future body shape after the user achieves the goal, generated based on the user's current body shape data and goal data.

[2356] A "training menu" is an exercise program customized based on a user's goals and fitness level, including specific exercises, exercise frequency, and duration.

[2357] "Exercise video" is video data taken by a user while they are training, and is used to evaluate the accuracy of their exercise form.

[2358] "Exercise form" refers to the physical movements and posture of the user when exercising, and maintaining correct form leads to improved safety and effectiveness.

[2359] A "meal plan" is a meal menu suggested based on the user's goals and physical condition, taking into consideration nutritional balance and calorie restrictions.

[2360] "Progress" is data recorded by the user regarding daily exercise, diet, weight fluctuations, etc., and is used to evaluate progress toward goals.

[2361] "Emotional state" refers to the user's current emotions, analyzed based on the user's facial expressions, voice tone, text input, etc.

[2362] "Feedback content" refers to advice and encouraging messages provided based on the user's exercise form, progress, and emotional state.

[2363] A "smart device" is a device for use by a user, and in the present invention particularly refers to smart glasses or tablets.

[2364] This invention relates to a personal training system that helps users maintain their health, lose weight, and build muscle. The system acquires basic information and goal data from the user and generates individual training and meal plans. It can also recognize the user's emotions and adjust the plans and feedback accordingly.

[2365] Hardware and software used

[2366] Hardware: Smart glasses, tablets, cameras

[2367] Software: Emotion recognition engine (EmotionRecognition), training plan generation engine (TrainingRecommendation), database management system

[2368] Specific explanation of the process

[2369] 1. User Registration and Login:

[2370] The user uses a tablet to enter basic information and send it to the server, which stores it in a database.

[2371] If the user is already registered, they enter their email address and password on the login screen, and the server checks the information against the database.

[2372] 2. Goal Setting:

[2373] Users input their fitness goals using a tablet in the physical store, and the server generates an optimal training plan based on this goal data and displays it on the tablet.

[2374] 3. Training and meal plans provided:

[2375] The server generates personalized training and meal plans based on the user's goals and fitness level, which are displayed on a tablet or smart glasses.

[2376] 4. Real-time analysis of athletic form:

[2377] Cameras and smart glasses installed in the store capture footage of the workout, which is then sent to a server where an algorithm is run to assess the accuracy of the workout form, providing real-time feedback on the tablet or smart glasses.

[2378] 5. Emotion-aware feedback regulation:

[2379] An emotion recognition engine analyzes the user's emotional state based on camera footage, audio, and text input. The server then adjusts the training menu and feedback content based on the recognized emotions, providing encouraging messages as needed.

[2380] 6. Progress Management and Data Entry:

[2381] Users enter their daily exercise routines, dietary habits, weight fluctuations, etc. into a tablet, and this data is sent to a server, where progress is evaluated and the plan is adjusted as necessary.

[2382] Specific examples

[2383] For example, if a user sets a goal of "losing 5 kg in 3 months," the system will generat...

Claims

1. A means for obtaining basic information and goal data of a user; means for generating an appearance image of the user after achieving the goal based on the goal data; means for generating an individual training menu based on the goal data and the user's fitness level; A means for analyzing exercise videos uploaded by users and evaluating and providing feedback on accurate exercise form; means for proposing an optimal meal plan based on the target data and the user's individual conditions; A way to track your progress and adjust your training and meal plans as needed; A system including:

2. 2. The system of claim 1, wherein the data input by the user as initial settings includes height and weight.

3. 2. The system of claim 1, wherein the means for generating the post-goal appearance image uses an image of the user's current body shape.

Images