KR-102962198-B1 - METHOD AND SYSTEM FOR PROVIDING EXERCISE GUIDES BASED ON GENERATIVE MODEL

KR102962198B1KR 102962198 B1KR102962198 B1KR 102962198B1KR-102962198-B1

Abstract

The present invention relates to a method and system for providing exercise guidance based on a generative model. The method for providing exercise guidance based on a generative model according to the present invention may include the steps of: receiving sensing information from at least one sensor in response to an activation event of an application; generating a prompt using user-related information of a user account logged into the application and the sensing information while the application is active; inputting the prompt to an agent while the application is active; and obtaining a user exercise guide corresponding to the prompt from the agent and providing the obtained user exercise guide through the application.

Inventors

김병훈
정형진
윤찬

Assignees

에버엑스 주식회사

Dates

Publication Date: 20260511
Application Date: 20250219

Claims (18)

A step of activating an agent including a Large Language Model (LLM) in response to an activation event of an application, and providing a visual indicator on a display unit of a user terminal indicating that the agent has been activated; A step of providing an exercise video based on an exercise program related to the user's indication while the agent is activated, so that the user performs an exercise related to the indication using the application; A step of receiving voice information of the user through an activated microphone while the exercise video is being played in the above application; A step of generating a prompt for user feedback related to at least one of the user’s exercise movements according to the indication and the exercise video in the agent by using text corresponding to at least a portion of the user’s voice information through analysis of the user’s voice information; A step of inputting the prompt into the large language model while the above application is active; In the above large language model, the step of generating user feedback related to at least one of the user's exercise movements according to the indication and the exercise video; and A generative model-based exercise guide provision method characterized by including the step of providing a user exercise guide corresponding to the user feedback generated through the large language model in the agent above through the application above.
In paragraph 1, In a user terminal where the above application is activated, the camera is activated based on the activation of the above application, and A method for providing exercise guidance based on a generative model, characterized in that at least a portion of the video received through the camera is input into the large language model.
In paragraph 2, A generative model-based exercise guide provision method characterized by the agent acquiring the exercise guide corresponding to the user's voice information and at least some of the images by linking with the large language model.
In paragraph 1, The agent configures the prompt to include at least some of the user-related information related to the user so that a customized exercise guide for the user is generated, and The above user-related information is, It includes at least one of user account information and prescription information, and The above user account information is, It includes at least one of the user's ID, name, date of birth, and gender information, and The above prescription information is, A method for providing an exercise guide based on a generative model, characterized by including information on the above indications and information on a treatment plan prescribed by a medical institution for the above indications.
In paragraph 4, The above exercise guide is, A generative model-based exercise guide provision method characterized by including at least one of information related to an exercise video, exercise plan, exercise schedule, exercise movement, exercise method, exercise difficulty, number of exercises, exercise time, timing of exercise, and exercise description related to the exercise that the user must perform in relation to the above indication.
In paragraph 3, The above prompt is, A method for providing exercise guidance based on a generative model, characterized by including a first request to the agent to analyze the user's actions included in at least some of the above images.
In paragraph 6, The above prompt is, A method for providing an exercise guide based on a generative model, characterized by further including a second request to generate a comment on the indication included in the prescription information as a result of analyzing the action of the user.
In paragraph 5, The above prompt is, A method for providing an exercise guide based on a generative model, characterized by further including a third request to generate the exercise guide by reflecting user requests based on the voice information of the user.
In paragraph 8, In the step of generating the above prompt, A generative model-based exercise guide providing method characterized by converting the user's voice information into text based on a STT (Speech-to-Text) algorithm and including the converted text in the prompt.
In Paragraph 9, In the step of generating the above prompt, A generative model-based exercise guide provision method characterized by extracting text of a pre-set topic related to the generation of the exercise guide from the converted text and including the text of the pre-set topic in the prompt.
In Paragraph 10, The previously established topic above is, It relates to at least one of adjusting the difficulty of an exercise, selecting the type of exercise, and changing the type of exercise, and In the above agent, Based on the above third request, check the exercise plan information previously provided to the user account, and A method for providing an exercise guide based on a generative model, characterized by generating the exercise guide based on the confirmed exercise plan to reflect the user request.
In paragraph 5, The above agent is configured to be linked with a database in which exercise videos corresponding to each of a plurality of different exercise items are stored, and The above agent is, Based on the above prompt, at least one exercise item related to the above indication is extracted from the above database, and A generative model-based exercise guide provision method characterized by generating an exercise guide that enables the user to perform exercises according to the extracted exercise items.
In Paragraph 12, The above agent is, Generate the exercise plan composed of at least one exercise item, and The above application is, A method for providing an exercise guide based on a generative model, characterized by controlling a user terminal to sequentially play exercise videos according to at least one exercise item according to the above exercise plan.
In Paragraph 12, In the above database, exercise videos corresponding to each of the above exercise items are stored linked to the identifier (ID) of the above exercise item, and The extraction of exercise items from the above agent is, Corresponds to extracting an identifier corresponding to at least one exercise item related to the above indication, and A generative model-based exercise guide provision method characterized by the application receiving an identifier corresponding to the extracted exercise item from the agent and playing an exercise video corresponding to the identifier corresponding to the extracted exercise item on a user terminal.
In Paragraph 13, While the exercise video is being played on the user terminal, the camera and microphone of the user terminal are maintained in an active state, and A step of acquiring user feedback information through at least one of the camera and microphone while the exercise video is being played on the user terminal; A step of generating a feedback prompt to update the exercise guide using the above user feedback information; A generative model-based exercise guide provision method characterized by further including the step of inputting the above feedback prompt to the agent, obtaining an updated exercise guide from the agent, and providing the updated exercise guide to the user terminal.
In Paragraph 13, While the exercise video is being played on the user terminal, an image received from an activated camera is displayed in real time in one area of the user terminal, and A generative model-based exercise guide provision method characterized by displaying feedback information regarding the user's exercise movements included in the video in at least a portion of the video.
A control unit that activates an agent including a Large Language Model (LLM) in response to an activation event of an application, and provides a visual indicator on a display unit of a user terminal that indicates that the agent has been activated. The above control unit is, In order for the user to perform exercises related to the indication using the above application, the agent provides an exercise video based on an exercise program related to the user's indication while the agent is activated, and While the exercise video is being played in the above application, voice information of the user is received through an activated microphone, and By analyzing the voice information of the user, the agent generates a prompt for user feedback related to at least one of the user's exercise movements according to the indication and the exercise video using text corresponding to at least a portion of the user's voice information. With the above application active, input the above prompt into the large language model, and A generative model-based exercise guide providing system characterized by providing user feedback related to at least one of the user's exercise movements according to the indication and exercise video generated through the large language model through the application.
It is executed by one or more processes on an electronic device and can be read by a computer. As a program stored on an existing recording medium, The above program is, A step of activating an agent including a Large Language Model (LLM) in response to an activation event of an application, and providing a visual indicator on a display unit of a user terminal indicating that the agent has been activated; A step of providing an exercise video based on an exercise program related to the user's indication while the agent is activated, so that the user performs an exercise related to the indication using the application; A step of receiving voice information of the user through an activated microphone while the exercise video is being played in the above application; A step of generating a prompt for user feedback related to at least one of the user’s exercise movements according to the indication and the exercise video in the agent by using text corresponding to at least a portion of the user’s voice information through analysis of the user’s voice information; A step of inputting the prompt into the large language model while the above application is active; In the above large language model, the step of generating user feedback related to at least one of the user's exercise movements according to the indication and the exercise video; and A program stored on a computer-readable recording medium characterized by including instructions that perform the step of providing a user exercise guide corresponding to the user feedback generated through the large language model in the agent through the application.

Description

Method and System for Providing Exercise Guides Based on Generative Model The present invention relates to a method and system for providing exercise guidance based on a generative model. Recently, with the rapid advancement of artificial intelligence (AI) technology, generative models capable of natural conversation with humans (e.g., ChatGPT) have emerged. In particular, generative models that include a Large Language Model are demonstrating innovation in the AI market by showcasing technological capabilities that allow them to communicate naturally, almost like humans, and provide fast and accurate information, unlike traditional chatbots that are manually built and provide only limited answers. Furthermore, the utilization of artificial intelligence (AI) technology in the medical industry is rapidly expanding. In particular, there is growing interest in AI technology that uses generative models to provide personalized, non-face-to-face care to patients requiring consistent management and rehabilitation during treatment. For example, generative models can be effectively utilized for the management and rehabilitation of musculoskeletal disorders. Musculoskeletal disorders refer to pain or injury occurring in the musculoskeletal system, including muscles, nerves, tendons, ligaments, bones, and surrounding tissues. As a principle, the treatment of musculoskeletal disorders should begin with less invasive procedures; non-pharmacological conservative treatments (e.g., exercise therapy and education, cognitive therapy, or relaxation therapy) should be implemented first, followed by pharmacological treatment and surgical treatment in sequence. Treatment guidelines strongly recommend non-pharmacological conservative treatment for musculoskeletal disorders, and active research on methods for implementing such treatments is being conducted, primarily in the United States and Europe. However, since continuous treatment and rehabilitation are crucial for non-pharmacological conservative treatment, the need for patients to visit the hospital frequently poses a significant burden. To address these issues and facilitate the consistent management and rehabilitation of specific diseases, there is a need to provide non-face-to-face exercise guidance services using generative models. FIG. 1 is a conceptual diagram illustrating a generative model-based exercise guide providing system according to the present invention. FIG. 2 is a conceptual diagram for explaining the operation of an agent according to the present invention in general. FIG. 3 is a flowchart illustrating a method for providing exercise guidance based on a generative model according to the present invention. FIGS. 4a and FIGS. 4b are conceptual diagrams for explaining a prompt generation method according to the present invention. FIG. 4c is a conceptual diagram illustrating an exercise plan included in an exercise guide according to the present invention. FIG. 5 is a conceptual diagram illustrating the operation process of an agent according to the present invention. FIGS. 6a, FIGS. 6b, and FIGS. 7 are conceptual diagrams for explaining the process of providing an exercise guide by analyzing image data according to the present invention. FIG. 8 is a conceptual diagram illustrating the process of performing user authentication according to the present invention. FIGS. 9a and 9b are conceptual diagrams illustrating the process of updating an exercise guide based on user feedback according to the present invention. Hereinafter, embodiments disclosed in this specification will be described in detail with reference to the attached drawings. Identical or similar components are assigned the same reference number regardless of the drawing symbols, and redundant descriptions thereof will be omitted. The suffixes "module" and "part" used for components in the following description are assigned or used interchangeably solely for the ease of drafting the specification and do not have distinct meanings or roles in themselves. Furthermore, in describing the embodiments disclosed in this specification, if it is determined that a detailed description of related prior art could obscure the essence of the embodiments disclosed in this specification, such detailed description will be omitted. Additionally, the attached drawings are intended only to facilitate understanding of the embodiments disclosed in this specification; the technical concept disclosed in this specification is not limited by the attached drawings, and it should be understood that they include all modifications, equivalents, and substitutions that fall within the spirit and technical scope of the present invention. Terms including ordinal numbers, such as first, second, etc., may be used to describe various components, but said components are not limited by said terms. These terms are used solely for the purpose of distinguishing one component from another. When it is stated that one component is "connected"