Method and system for creating a customized therapeutic exercise program

Abstract

The present invention relates to a method and system for generating a customized therapeutic exercise program, which can customize an exercise program for therapeutic purposes and provide it to a patient. The method for generating a customized therapeutic exercise program according to the present invention may include the steps of: executing an exercise program generation mode on a terminal logged in with a specific medical staff account; selecting at least one exercise item to be included in the exercise program in the exercise program generation mode; setting program information corresponding to the exercise program; generating the exercise program including the exercise item and the program information; storing the exercise program in association with the specific medical staff account; and allocating the exercise program to the patient account based on receiving prescription information for the patient account from the specific medical staff account.

Description

[Technical Field]

[0001] The present invention relates to a method and system for generating a customized therapeutic exercise program, which can customize an exercise program for therapeutic purposes and provide it to a patient. [Background technology]

[0002] Musculoskeletal disorders refer to pain or injury that occurs in the musculoskeletal system, including muscles, nerves, tendons, ligaments, bones, and surrounding tissues. Musculoskeletal disorders can appear in various parts of the body, such as the neck, lower back, arms, and legs.

[0003] According to a report by the World Health Organization (WHO), the economic loss caused by musculoskeletal disorders is the fourth highest of all diseases, and musculoskeletal disorders are chronic pain conditions that affect not only daily life but also economic activity.

[0004] On the other hand, the treatment of musculoskeletal disorders should, as a rule, be performed with minimally invasive treatments first, with non-pharmacological conservative treatments (e.g., exercise therapy and education, cognitive therapy, or relaxation therapy) being performed first, followed by drug therapy and surgical treatment.

[0005] Treatment guidelines actively recommend non-drug conservative treatment for musculoskeletal disorders, and research into methods for non-drug conservative treatment of musculoskeletal disorders is actively being conducted, particularly in the United States and Europe.

[0006] Meanwhile, with the advancement of technology, electronic devices (e.g., smartphones, tablet PCs, etc.) have become increasingly popular, which has led to a gradual increase in dependency on the Internet in many aspects of daily life.

[0007] In this way, with the development of various technologies including the Internet, consumption patterns that were previously highly dependent on offline consumption have gradually shifted to online consumption, and online-centered consumption is now increasing dramatically.

[0008] In line with these changing trends, industries such as the medical industry, which are primarily offline due to the nature of their services, are increasingly providing medical services online.

[0009] Therefore, nowadays, various medical services are provided online, allowing patients, or users, to consult with medical staff about their illnesses with just a few clicks via electronic devices connected to the Internet.

[0010] As an example of such technology, Korean Patent Registration No. 10-2195512 discloses technology relating to a server and system that provides an online medical platform, providing patients with information about medical service locations that use online services. In line with this trend, there is a need for methods to provide non-pharmacological conservative treatment of musculoskeletal disorders online. Summary of the Invention [Problem to be solved by the invention]

[0011] The present invention relates to a method and system for generating a customized therapeutic exercise program, which can customize an exercise program and provide it to a patient. Furthermore, the present invention relates to a method and system for generating a customized therapeutic exercise program, which allows the customized exercise program to be shared among medical staff. In particular, the present invention relates to a method and system for generating a customized therapeutic exercise program that can provide an exercise program sharing environment on a hospital-by-hospital basis.

[0012] Furthermore, the present invention relates to a method and system for generating a customized therapeutic exercise program, which can provide a therapeutic exercise program to a patient based on the authority of medical staff. [Means for solving the problem]

[0013] In order to solve the above problem, the method for generating a customized exercise therapy program of the present invention may include the steps of executing an exercise program generation mode on a terminal logged in with a specific medical staff account, selecting at least one exercise item to be included in the exercise program in the exercise program generation mode, setting program information corresponding to the exercise program, generating the exercise program including the exercise item and the program information, storing the exercise program in association with the specific medical staff account, and assigning the exercise program to the patient account based on receiving prescription information for the patient account from the specific medical staff account.

[0014] In one example, the step of selecting the exercise item includes the steps of displaying on the terminal a plurality of exercise items registered in the exercise therapy provision service, selecting at least one of the plurality of exercise items from the specific medical staff account, and displaying on the terminal a list including the selected exercise items, and the exercise program may be composed of the exercise items included in the list.

[0015] Furthermore, the exercise program may be set to either a non-shareable state in which it is accessible only to the specific medical staff account, or a shareable state in which it is accessible to medical staff accounts other than the specific medical staff account.

[0016] In this case, the program information may include information identifying the target of sharing of the exercise program, and the other medical staff accounts that can access the exercise program may be determined based on the program information.

[0017] In one example, the information specifying the sharing target may be at least one of hospital information and medical staff information registered with the exercise treatment providing service.

[0018] In one example, if the exercise program is available for sharing, the exercise program may be assigned to the patient account based on prescription information received from the other medical staff account.

[0019] Furthermore, the specific medical staff account may be either a first type medical staff account that has unique prescription authority for the exercise program, or a second type medical staff account that does not have unique prescription authority for the exercise program, and the step of assigning the exercise program to the patient account may include a step of confirming the type of the specific medical staff account, and if the result of the confirmation is that the type of the specific medical staff account is the first type, a step of assigning the exercise program to the patient account.

[0020] Furthermore, the step of allocating the exercise program to the patient account may allocate the exercise program to the patient account based on the occurrence of an approval event for the exercise program prescription from a medical staff account of the first type when the confirmation result indicates that the particular medical staff account is of the second type.

[0021] Meanwhile, a customized exercise therapy program generation system according to the present invention may include a control unit that executes an exercise program generation mode on a terminal logged in with a specific medical staff account, a communication unit that receives a selection of at least one exercise item to be included in the exercise program in the exercise program generation mode, and a storage unit that stores the exercise program, wherein the control unit sets program information corresponding to the exercise program, generates the exercise program including the exercise item and the program information, stores the exercise program in the storage unit in cooperation with the specific medical staff account, and assigns the exercise program to the patient account based on receiving prescription information for the patient account from the specific medical staff account.

[0022] Furthermore, a program executed by one or more processes in an electronic device and stored on a computer-readable recording medium may include instructions to perform the following steps: executing an exercise program generation mode on a terminal logged in with a specific medical staff account; selecting at least one exercise item to be included in an exercise program in the exercise program generation mode; setting program information corresponding to the exercise program; generating the exercise program including the exercise item and the program information; storing the exercise program in association with the specific medical staff account; and allocating the exercise program to the patient account based on receiving prescription information for the patient account from the specific medical staff account. [Effects of the Invention]

[0023] As described above, the method and system for generating a customized therapeutic exercise program according to the present invention can provide a user environment in which medical staff can directly customize an exercise program by running an exercise program generation mode on a terminal logged in with a specific medical staff account.

[0024] Specifically, the method and system for generating a customized therapeutic exercise program according to the present invention generates an exercise program by selecting at least one exercise item to be included in the exercise program in an exercise program generation mode, allowing medical staff to generate an effective and optimal exercise program taking into consideration various factors such as the patient's characteristics such as disease, symptoms, age, age group, and exercise ability.

[0025] In particular, the method and system for generating a customized exercise treatment program according to the present invention stores the generated exercise program in association with a specific medical staff account, thereby enabling the exercise program generated by the specific medical staff account to be managed and the exercise program to be shared with other medical staff accounts.

[0026] Furthermore, the method and system for generating a customized therapeutic exercise program according to the present invention can assign the exercise program to a patient account based on receiving prescription information for the patient account from a specific medical staff account, thereby allowing a doctor to prescribe a customized exercise program for treatment purposes to a patient, and allowing the patient to receive an optimal exercise program and exercise effectively. [Brief explanation of the drawings]

[0027] [Figure 1] 1 is a conceptual diagram for explaining a customized exercise therapy providing system according to the present invention. [Figure 2a] FIG. 2 is a conceptual diagram for explaining a medical staff account and a patient account according to the present invention. [Figure 2b] FIG. 2 is a conceptual diagram for explaining a medical staff account and a patient account according to the present invention. [Figure 3] FIG. 1 is a conceptual diagram for explaining an exercise program provided by the present invention. [Figure 4a] FIG. 1 is a conceptual diagram for explaining an exercise program provided by the present invention. [Figure 4b] FIG. 1 is a conceptual diagram for explaining an exercise program provided by the present invention. [Figure 5] 1 is a flowchart illustrating a method for providing customized exercise therapy according to the present invention. [Figure 6a] FIG. 1 is a conceptual diagram for explaining a method for generating an exercise program according to the present invention. [Figure 6b] FIG. 1 is a conceptual diagram for explaining a method for generating an exercise program according to the present invention. [Figure 7] FIG. 1 is a conceptual diagram for explaining an exercise program prescription method according to the present invention. [Figure 8a] FIG. 1 is a conceptual diagram for explaining a method for sharing an exercise program in the present invention. [Figure 8b] FIG. 1 is a conceptual diagram for explaining a method for sharing an exercise program in the present invention. [Figure 9a] FIG. 1 is a conceptual diagram for explaining the exercise program prescription process according to the authority of a medical staff account in the present invention. [Figure 9b] FIG. 1 is a conceptual diagram for explaining the exercise program prescription process according to the authority of a medical staff account in the present invention. [Figure 9c] FIG. 1 is a conceptual diagram for explaining the exercise program prescription process according to the authority of a medical staff account in the present invention. [Figure 10] FIG. 10 is a conceptual diagram for explaining a change of workplace of a medical staff account in the present invention. [Figure 11] 1 is a conceptual diagram for explaining an exercise therapy providing system according to the present invention. [Figure 12]1 is a flowchart illustrating a method for providing exercise therapy according to the present invention. [Figure 13] 1 is a flowchart illustrating a method for providing exercise therapy according to the present invention. [Figure 14a] FIG. 1 is a conceptual diagram for explaining a doctor's prescription. [Figure 14b] FIG. 1 is a conceptual diagram for explaining a doctor's prescription. [Figure 15] FIG. 1 is a conceptual diagram illustrating a method for analyzing a patient's exercise motion from exercise video. [Figure 16] FIG. 1 is a conceptual diagram illustrating a method for analyzing a patient's exercise motion from exercise video. [Figure 17] FIG. 1 is a conceptual diagram for explaining an artificial intelligence posture estimation model. [Figure 18a] FIG. 1 is a conceptual diagram for explaining an artificial intelligence posture estimation model. [Figure 18b] FIG. 1 is a conceptual diagram for explaining an artificial intelligence posture estimation model. [Figure 18c] FIG. 1 is a conceptual diagram for explaining an artificial intelligence posture estimation model. [Figure 18d] FIG. 1 is a conceptual diagram for explaining an artificial intelligence posture estimation model. [Figure 18e] FIG. 1 is a conceptual diagram for explaining an artificial intelligence posture estimation model. [Figure 18f] FIG. 1 is a conceptual diagram for explaining an artificial intelligence posture estimation model. [Figure 19] FIG. 10 is a conceptual diagram illustrating an example of use in which the results of a user's behavior analysis are provided. [Figure 20] FIG. 10 is a conceptual diagram illustrating an example of use in which the results of a user's behavior analysis are provided. [Figure 21a] FIG. 1 is a conceptual diagram illustrating a user environment in which the results of a patient's exercise motion analysis are provided. [Figure 21b] FIG. 1 is a conceptual diagram illustrating a user environment in which the results of a patient's exercise motion analysis are provided. [Figure 21c] FIG. 1 is a conceptual diagram illustrating a user environment in which the results of a patient's exercise motion analysis are provided. DETAILED DESCRIPTION OF THE INVENTION

[0028] Hereinafter, the embodiments disclosed herein will be described in detail with reference to the accompanying drawings. Regardless of the reference numerals, identical or similar components are designated by the same reference numerals, and redundant descriptions thereof will be omitted. The suffixes "module" and "section" used in the following description are used solely for ease of description and do not have any distinct meanings or functions. Furthermore, when describing the embodiments disclosed herein, if a detailed description of related publicly known technology is deemed to obscure the gist of the embodiments disclosed herein, such detailed description will be omitted. Furthermore, the accompanying drawings are intended to facilitate understanding of the embodiments disclosed herein, and the technical concepts disclosed herein should not be limited by the accompanying drawings, and should be understood to include all modifications, equivalents, and alternatives within the concept and technical scope of the present invention.

[0029] Terms including ordinal numbers such as first, second, etc. may be used to describe various components, but the components are not limited by these terms. These terms are used only to distinguish one component from another.

[0030] When a component is described as being "coupled" or "connected" to another component, it should be understood that it may be directly coupled or connected to the other component, but that there may be other components between them. On the other hand, when a component is described as being "directly coupled" or "directly connected" to another component, it should be understood that there are no other components between them. The singular expression includes the plural expression unless the context clearly dictates otherwise.

[0031] In this application, the terms "comprise" or "have" and the like are intended to specify the presence of a specified feature, number, step, operation, component, part, or combination thereof, and are to be understood as not precluding the possible presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0032] The exercise therapy provision system 100 of the present invention can provide an exercise program (which may be called an "exercise plan" or "exercise therapy program") prescribed by medical staff U1 to a patient between the medical staff and the patient.

[0033] In particular, the exercise therapy delivery system 100 according to the present invention can provide patients with an exercise program that is directly customized and created by medical staff. Therefore, the exercise therapy delivery system 100 according to the present invention may be called an "exercise program generation system."

[0034] Meanwhile, the "medical staff" described in the present invention refers to those who work at the medical institution (for example, hospital) 1, and may include, for example, at least one of a doctor, a nurse, and a physical therapist.

[0035] For the sake of convenience, the present invention will be described with reference to examples of medical staff, such as doctors and physical therapists who can provide (or prescribe) an exercise program to patient U2. However, medical staff are not limited to these, and any user who works at a medical institution to provide exercise therapy services can be considered a medical staff member according to the present invention. The medical staff U1 can generate a treatment program including at least one treatment item according to the symptoms of the patient requiring treatment and the appropriate treatment method.

[0036] This invention will be described mainly on a method for generating an exercise program including at least one exercise item for exercise therapy (e.g., rehabilitation therapy, physical therapy, cognitive therapy, etc.). However, this invention is not limited to generating an exercise program for exercise therapy, and may also be used to generate a treatment program requested by a medical institution such as a hospital.

[0037] Meanwhile, medical staff U1 can customize at least one exercise item and an exercise method for the exercise item (for example, the number of exercises, the exercise time, the exercise sequence, etc.) to create various exercise programs.

[0038] Here, the "exercise item" can be understood as an exercise action or an exercise type, and in the present invention, the terms "exercise item," "exercise action," and "exercise type" may be used interchangeably.

[0039] In the present invention, an exercise program created by a specific medical staff member can be named a "unique exercise program (or unique program)," a "customized exercise program (or customized program)," a "customized type exercise program (or customized type program)," an "individual exercise program (or individual program)," or a "personal exercise program (or personal program)." Furthermore, the present invention can provide a user environment in which original exercise programs created by specific medical staff can be shared among medical staff. In the present invention, an exercise program shared among medical staff can be named a "shared exercise program (or shared program)."

[0040] Furthermore, the "recommended exercise program (or recommended program)" described in the present invention can be understood as a program that is registered in the exercise therapy providing service by the system administrator and provided to medical staff.

[0041] Meanwhile, medical staff U1 can prescribe an exercise program (or exercise plan) to patient U2 based on at least one of the original exercise program, the shared exercise program, and the recommended exercise program.

[0042] In the present invention, a service can be provided that enables medical staff U1 to create their own exercise program using a page (or screen) provided by the exercise therapy provision system 100. In addition, in the present invention, a user environment is provided in which medical staff U1 can prescribe an exercise program to patient U2, and information about the exercise program prescribed by medical staff U1 can be received. In addition, in the present invention, the prescribed exercise program received from medical staff U1 is provided to patient U2, thereby providing exercise therapy services to patient U2.

[0043]

[0019] Hereinafter, a method and system for generating a unique exercise program and providing a customized exercise therapy to a patient will be described in detail with reference to the accompanying drawings. Figure 1 is a conceptual diagram illustrating a customized exercise therapy providing system according to the present invention. Figures 2a and 2b are conceptual diagrams illustrating a medical staff account and a patient account according to the present invention. Figures 3, 4a, and 4b are conceptual diagrams illustrating an exercise program provided by the present invention. Figure 5 is a flowchart illustrating a method for providing a customized exercise therapy according to the present invention. Figures 6a and 6b are conceptual diagrams illustrating a method for generating an exercise program according to the present invention. Figure 7 is a conceptual diagram illustrating a method for prescribing an exercise program according to the present invention. Figures 8a and 8b are conceptual diagrams illustrating a method for sharing an exercise program according to the present invention. Figures 9a, 9b, and 9c are conceptual diagrams illustrating a process for prescribing an exercise program according to the authority of a medical staff account according to the present invention. Figure 10 is a conceptual diagram illustrating a change of workplace of a medical staff account according to the present invention. As shown in FIG. 1, an exercise therapy providing system 100 according to the present invention may be configured to communicate with user terminals 10 and 20.

[0044] The user terminals 10 and 20 in the present invention can be understood as electronic devices capable of using the exercise therapy provision service. For example, the user terminals 10 and 20 may include mobile phones, smartphones, notebook computers, laptop computers, slate PCs, tablet PCs, ultrabooks, desktop computers, digital broadcasting terminals, personal digital assistants (PDAs), portable multimedia players (PMPs), navigation systems, and wearable devices such as smart watches, smart glasses, and head-mounted displays (HMDs).

[0045] The medical staff member U1 can use his / her user terminal 10 to create and prescribe a therapeutic exercise program through a screen (or page) 400 provided by the exercise treatment delivery system 100. The patient U2 can use his / her own user terminal 20 to receive an exercise therapy service in accordance with the exercise program prescribed by the medical staff member U1 and undergo treatment.

[0046] Meanwhile, the "screen (or page) 400" described in the present invention can be understood to mean at least one piece of information (text, image, video, graphic object, etc.) displayed (or output) on the display of the user terminal 10, 20. Therefore, the "screen (or page)" in the present invention may be used interchangeably with "information."

[0047] On the other hand, in the present invention, information related to the exercise treatment service can be provided on the user terminals 10 and 20 logged in with the user account of the medical staff member U1 or the patient U2.

[0048] In this specification, for convenience of explanation, the medical staff U1 account is referred to as a "medical staff account," and a user terminal logged in with the medical staff account is referred to as a "medical staff terminal."

[0049] As shown in Figure 2b, an "account" can be created through pages (e.g., "membership registration pages") 200a, 200b provided by the exercise therapy provision system 100. Alternatively, an "account" can be created in at least one other system linked to the exercise therapy provision system according to the present invention. Details related to user accounts will be described later.

[0050] Meanwhile, as shown in FIG. 1, an exercise therapy providing system 100 according to the present invention may include at least one of a communication unit 110, a storage unit 120, and a control unit .

[0051] The communication unit 110 may be configured to perform communication with at least one of the medical staff terminal 10 and the patient terminal 20. For example, the communication unit 110 may be configured to support wireless LAN (WLAN), wireless fidelity (Wi-Fi), wireless fidelity (Wi-Fi) Direct, digital living network alliance (DLNA: registered trademark), wireless broadband (WiBro), world interoperability for microwave access (WiMAX), high speed downlink packet access (HSDPA), high speed uplink packet access (HSUPA), long term evolution (LTE), long term evolution-advanced (LTE-A), fifth generation mobile telecommunication (5G), Bluetooth (Bluetooth TMCommunication can be performed using at least one of the following technologies: WiFi (registered trademark), RFID (Radio Frequency Identification), Infrared Data Association (IrDA), UWB (Ultra-Wideband), ZigBee, NFC (Near Field Communication), Wi-Fi Direct, and Wireless USB (Wireless Universal Serial Bus).

[0052] The communication unit 110 can provide a screen (or page) 400 containing information about the unique exercise program to the medical staff terminal 10. The medical staff U1 can create a unique exercise program through the screen output on the medical staff terminal 10 and prescribe the unique exercise program that he or she created to the patient U2.

[0053] The communication unit 110 can provide a unique exercise program on the patient terminal 20 based on the unique exercise program prescribed by the medical staff terminal 10. The patient U2 can receive an exercise therapy service according to the exercise program prescribed by the medical staff U1 through the patient terminal 20.

[0054] Furthermore, the storage unit 120 may be configured to store various information related to the exercise therapy provision service. For example, the storage unit 120 may store a unique exercise program created by a specific medical staff member U1, matched with the specific medical staff member account U1.

[0055] In the present invention, the storage unit 120 can be understood as being sufficient as long as it is a space in which information related to the exercise therapy provision service is stored, and there are no physical space restrictions. Specifically, the storage unit 120 can exist in at least one of the inside and outside spaces (e.g., external server) of the exercise therapy provision system 100. That is, at least a part of the storage unit 120 can exist inside the exercise therapy provision system 100. Also, at least a part of the storage unit 120 can exist in database 2 in the external space (e.g., external server). In this case, the exercise therapy provision system 100 can use the information stored in database 2 in the external space. Furthermore, the control unit 130 can perform a series of controls related to the components included in the exercise treatment provision system 100 and the exercise treatment provision service.

[0056] In particular, the control unit 130 can provide a user environment in which the medical staff terminal 10 can generate a unique exercise program and prescribe the generated unique exercise program to a patient.

[0057] Furthermore, the control unit 130 can share a unique exercise program created in a specific medical staff account U1 with another medical staff account U3 based on the settings of the specific medical staff account U1.

[0058] Below, the concepts of "user account" and "exercise program" of the present invention will be explained, and then a service for creating, prescribing, and sharing a unique exercise program will be specifically described.

[0059] 2, the control unit 130 can separately manage medical staff accounts of medical staff U1, U3, U4, and U5 and a patient account of patient U2. For ease of explanation, the medical staff accounts will be denoted by the same reference numerals as the medical staff, "U1," "U3," "U4," and "U5," and the patient account will be denoted by the same reference numeral as the patient, "U2."

[0060] 2a(a), the control unit 130 can manage medical staff accounts U1, U3, U4, and U5 for each hospital 1a or 1b. The control unit 130 can match the medical staff accounts U1, U3, U4, and U5 with at least one hospital (or hospital information) 1a or 1b where the medical staff work (or belong), and store the matched results in the storage unit 120.

[0061] For example, the control unit 130 can match and manage medical staff accounts U1 and U3 of medical staff working at the first hospital 1a ("Doctor A" and "Therapist B") with the first hospital 1a, and can match and manage medical staff accounts U4 and U5 of medical staff working at the second hospital 1b ("Doctor B" and "Therapist B") with the second hospital 1b.

[0062] In order to manage medical staff accounts on a hospital-by-hospital basis, the control unit 130 may input hospital information of the medical staff's hospital where the medical staff works (or affiliated hospital, working hospital, associated hospital, or affiliated hospital) when creating the medical staff account.

[0063] For example, as shown in FIG. 2b(a), the control unit 130 may include, on a medical staff account registration page 210, an input area 211 for hospital information where the medical staff works.

[0064] Meanwhile, medical staff accounts in the present invention can be classified into a first type and a second type depending on whether they have the authority to independently prescribe exercise programs to patients.

[0065] A "first type of medical staff account" can be understood as a medical staff account that is authorized to independently prescribe exercise programs to patients.

[0066] In addition, a "second type medical staff account" can be understood as a medical staff account that can prescribe an exercise program to a patient based on the approval of the first type medical staff account. The control unit 130 can set the medical staff account to either the first type or the second type based on the occupational information of the medical staff.

[0067] For example, if the occupation of the medical staff is a first type of occupation (e.g., "doctor"), the control unit 130 can set the type of the medical staff account to a first type. On the other hand, if the occupation of the medical staff is a second type of occupation (e.g., "therapist"), the control unit 130 can set the type of the medical staff account to a second type.

[0068] In the present invention, an exercise program can be assigned to a patient through different processes depending on whether the medical staff account prescribing the exercise program to the patient is of the first type or the second type, as will be described in more detail below.

[0069] Meanwhile, as shown in (b) of Fig. 2a, a patient account U2 may exist in the storage unit 120. The patient account U2 may exist in a state matched with at least one of symptom information regarding the patient's symptoms, an exercise program assigned to the patient, medical staff information of the medical staff who assigned the exercise program, and hospital information of the hospital to which the medical staff belongs. The control unit 130 can provide a patient account registration page 220 configured differently from the page 210 for medical staff account registration.

[0070] For example, as shown in (b) of FIG. 2b, the control unit 130 can configure the patient account registration page 220 to allow for the input of at least one of the patient's name (first name) information 221, gender information 222, and mobile phone number information 223.

[0071] That is, the control unit 130 can generate a patient account even if the patient's occupation information and the hospital information of the associated hospital are not input, which is different from the medical staff account. Such a patient account registration page 210 may be provided on at least one of the medical staff terminal 10 and the patient terminal 20.

[0072] For example, when a patient visits a hospital, the control unit 130 can provide a patient account registration page 220 to the medical staff terminal 10. The medical staff can enter the patient information of the patient through the medical staff terminal 10 to create a patient account. As another example, a patient can directly create a patient account through a patient account registration page 220 provided on the patient terminal 20.

[0073] Meanwhile, as shown in FIG. 3, the exercise program 300 provided by the present invention may correspond to at least one of a unique exercise program (or a first attribute exercise program) 310, a shared exercise program (or a second attribute exercise program) 320, and a recommended exercise program (or a third attribute exercise program) 330 depending on the attribute. The unique exercise program 310 can be understood as an exercise program generated by a particular medical staff account U1.

[0074] A specific medical staff account U1 can select at least one exercise item from multiple exercise items registered in the exercise treatment provision service, and can create a unique exercise program 310 by setting the exercise method (e.g., number of exercise repetitions, exercise time, exercise sequence, exercise schedule, etc.) for the selected exercise item.

[0075] That is, a specific medical staff account U1 can create a unique exercise program 310 by customizing at least one exercise item and an exercise method for the exercise item.

[0076] Such a unique exercise program 310 is accessible to the particular medical staff account U1 that created the unique exercise program 310, and can be prescribed to patients by the particular medical staff account U1.

[0077] 4a, the control unit 130 may provide a unique exercise program entry page 400a to the terminal 10 logged in with a specific medical staff account U1. In this case, the unique exercise program entry page 400a may provide information 410, 420 about the exercise program created by the specific medical staff account U1.

[0078] The information 410 about the unique exercise program may include at least one of: i) information about the number of exercise items included in the exercise program (e.g., "12 movements") 411; ii) a shared graphic object 412 indicating whether the program can be shared; iii) a graphic object 413 indicating whether the program has been set as a favorite; iv) a thumbnail 414 of a video related to the exercise program; v) a title 415 of the exercise program; and vi) a date and time the exercise program was created 416. Here, the sharing graphic object 412 may be displayed to intuitively guide whether or not the unique exercise program 310 can be shared. In the present invention, the unique exercise program 310 may be set to either a non-sharable state or a sharable state. "Exercise program sharing" in the present invention may mean allowing access to and prescription of exercise programs.

[0079] In addition, the "non-sharing state" can be understood as a state in which the unique exercise program 310 can only be accessed by a specific medical staff account U1, and the unique exercise program information 410 can only be viewed by a specific medical staff account U1, and the unique exercise program can be assigned to a patient.

[0080] The "shareable state" can be understood as a state in which the unique exercise program can be accessed by other medical staff accounts U3 other than the specific medical staff account U1, and the other medical staff accounts U3 can also view the unique exercise program information 410 and assign the unique exercise program 310 to a patient.

[0081] The unique exercise program 310 may be determined to be either shareable or non-shareable based on the settings (or selections) of the particular medical staff account U1.

[0082] When the unique exercise program 310 is in a shareable state, the control unit 130 can display the shared graphic object 412 on the page 400a so that specific medical staff can intuitively recognize that the program is in a shareable state.

[0083] Meanwhile, if the unique exercise program 310 is in a non-shareable state, the control unit 130 can restrict the shared graphic object 412 from being displayed on the page 400a.

[0084] On the other hand, if a specific medical staff account U1 shares its own exercise program 310 with another medical staff account U3, the shared exercise program can be named "shared exercise program 320."

[0085] For example, assume that an exercise program created by a specific medical staff account U1 is shared with another medical staff account U3. In this case, the exercise program may be considered a unique exercise program 310 in the specific medical staff account U1 and a shared exercise program 320 in the other medical staff account U3.

[0086] 4b, the control unit 130 can provide a shared exercise program entry page 400b to the terminal 10 logged in with another medical staff account U3. In addition, the control unit 130 can display information 420 about the shared exercise program that was shared from a specific medical staff account U1 with another medical staff account U3 on the shared exercise program entry page 400b.

[0087] On the other hand, the recommended exercise program 330 is an exercise program provided by the exercise treatment provision system 100, and can be understood as an exercise program that can be accessed by all medical staff accounts registered in the exercise treatment provision system 100 (or some medical staff accounts set by the system administrator).

[0088] The control unit 130 can generate at least one recommended exercise program 330 based on settings by a system administrator, or can generate the recommended exercise program 330 based on prescription history information stored in the storage unit 120. For example, the control unit 130 can generate a "recommended exercise program for treating stiff neck" that includes at least one exercise item that is effective for treating stiff neck.

[0089] Medical staff can select one of the custom exercise programs 310, the shared exercise programs 320, and the recommended exercise programs 330 to prescribe a customized exercise plan for the patient.

[0090] The following describes in detail how to generate a unique exercise program so that medical staff can customize and prescribe their own exercise program.

[0091] In the present invention, a process of executing an exercise program generation mode can be performed on a terminal logged in with a specific medical staff account (S510, see FIG. 5).

[0092] The control unit 130 may control the exercise program generation mode to be executed on the terminal logged in with the specific medical staff account U1 based on receiving a request to execute the exercise program generation mode from the terminal logged in with the specific medical staff account U1.

[0093] Here, the "exercise program generation mode" can be understood as a mode in which an original exercise program can be generated, and may be used interchangeably with the "original exercise program generation mode" or the "new program generation mode."

[0094] 4a, the control unit 130 may provide a graphic object (e.g., "Create a new program") 430 associated with an exercise program generation mode execution function on a medical staff terminal logged in with a specific medical staff account U1. The control unit 130 may receive an exercise program generation mode execution request (or an exercise program generation mode execution event) from the specific medical staff account U1 based on the selection of the graphic object 430 by the specific medical staff account U1.

[0095] When the control unit 130 receives a request to execute the exercise program generation mode, the control unit 130 may control the execution of the exercise program generation mode on the terminal logged in with a specific medical staff account U1. That is, the control unit 130 may execute the exercise program mode based on the occurrence of an exercise program generation mode execution event.

[0096] Meanwhile, in the present invention, in the exercise program generation mode, a process of selecting at least one exercise item to be included in the exercise program can be performed (S520, see FIG. 5).

[0097] As shown in (a) of FIG. 6a, the control unit 130 can provide an exercise program creation page (or a unique exercise program creation page or exercise list configuration page) 600a on the terminal of a specific medical staff account U1.

[0098] The control unit 130 can be controlled to include a first area (also called a "selection area") 610 for selecting at least one exercise item included in a unique exercise program, and a second area (also called a "list area") 620 in which an exercise list composed of the selected exercise items is output.

[0099] The control unit 130 can display information on at least some of the multiple exercise items registered in the exercise therapy provision service on the first area 610 (e.g., information on the name (or title) of the exercise item, a representative image (e.g., a thumbnail of the video corresponding to the exercise item), information on the exercise part corresponding to the exercise item, etc.).

[0100] The control unit 130 can receive selection information for a specific medical staff account U1 from the medical staff terminal 10 based on the selection of any one of the exercise items displayed in the first area 610. For example, the control unit 130 can receive selection information for the selected exercise item based on the selection of information about the specific exercise item or an icon corresponding to the specific exercise item (e.g., "Add," "Select," or "Save") in the first area 610.

[0101] Furthermore, the control unit 130 can display information 611, 612 about at least one exercise program (original exercise program, shared exercise program, recommended exercise program) registered in the exercise therapy providing service on the first area 610. The information 611, 612 about the recommended exercise program may include at least one of information about the number of exercise items included in the recommended exercise program, information about the name (or title) of the exercise program, information about the exercise body part, and information about a representative image of the exercise item.

[0102] The control unit 130 can receive selection information (or a selection event) for a specific medical staff account U1 from the medical staff terminal 10 based on the selection of any one of the exercise programs displayed in the first area 610. For example, as shown in (a) of FIG. 6a, the control unit 130 can receive selection information for an exercise program based on the selection of information about a specific exercise program or an icon (e.g., "Add," "Select," or "Save") 611a corresponding to a specific exercise program in the first area 610.

[0103] In this case, the control unit 130 may determine that at least one exercise item included in the selected exercise program has been selected based on the selection of the exercise program (or the occurrence of a selection event) in the first area 610. For example, when an exercise program consisting of three exercise items (e.g., a first exercise item, a second exercise item, and a third exercise item) is selected, the control unit 130 may determine that all three exercise items have been selected.

[0104] In this way, when the unique exercise program generation mode is executed, the control unit 130 can provide a user environment to the terminal logged in with a medical staff account, in which the user can select at least one of the multiple exercise items registered in the exercise treatment provision service.

[0105] Meanwhile, as shown in (b) of Figure 6a, when at least one exercise item is selected in the first area 610, the control unit 130 can display the selected exercise items 621, 622 in the second area (also called the "list area") 620.

[0106] In this case, the control unit 130 may arrange the selected exercise items in order corresponding to the order in which they were selected, and display them in the second area 620. The control unit 130 may also generate an exercise program in order corresponding to the order in which the exercise items are arranged. Furthermore, the control unit 130 can provide an editing function through the second area 620 so that the selected exercise items 621 and 622 can be edited.

[0107] Here, the "editing function" can be understood as a function of performing at least one of the exercise method (exercise duration or number of exercise repetitions) for the selected exercise items 621, 622, the exercise order, and copying and deleting the selected exercise items 621, 622. For convenience of explanation, the editing function will be described below using a specific exercise item 621 as an example.

[0108] The control unit 130 may include an exercise method (exercise duration or number of exercise repetitions) setting area 621a for the exercise item 621 in the second area 620. The control unit 130 may display a plurality of exercise method option information (e.g., "maintain for 15 seconds," "maintain for 20 seconds," etc.) in the exercise method setting area 621a. Furthermore, the control unit 130 may set the selected exercise method option information as the exercise method for the exercise item based on the selection of any one of the plurality of exercise method option information (e.g., "maintain for 20 seconds"). Meanwhile, when no selection is made by the medical staff account for the exercise method option information, the control unit 130 may set the exercise method set as a basic value (or default value) as the exercise method for the exercise item.

[0109] Furthermore, the control unit 130 can display a graphic object 621b associated with a function for changing the arrangement of the exercise items 621 on the second area 620. The control unit 130 can change the arrangement of the exercise items 621 based on a selection by a medical staff account for the graphic object 621b associated with the arrangement change function. For example, the control unit 130 can change the arrangement of the exercise items 621 based on a user input of a medical staff account dragging the graphic object 621b, thereby moving the exercise items 621 from a first arrangement order (or a first position) to a second arrangement order (or a second position) different from the first arrangement order. In this case, the changed arrangement order of the exercise items 621 can correspond to the second arrangement order (or a second position).

[0110] Furthermore, the control unit 130 can display a check box 621c corresponding to the exercise item 621 on the second area 620. When a copy graphic object 623 displayed in the second area 620 is selected with the check box 621c corresponding to the exercise item selected, the control unit 130 can additionally display the copied exercise item 621 on the second area 620. Furthermore, when a delete graphic object 624 displayed in the second area 620 is selected with the check box 621c corresponding to the exercise item selected, the control unit 130 can delete the copied exercise item 621 from the second area 620.

[0111] In this way, the present invention provides a user environment in which a medical staff account can select at least some of the exercise items registered in the exercise treatment provision service and edit the selected exercise items, thereby enabling medical staff to customize and create a variety of exercise programs according to the patient's symptoms, characteristics of the patient (e.g., age group, age, exercise ability, etc.), and the patient's exercise environment. Meanwhile, in the present invention, a process of setting program information corresponding to an exercise program can be performed (S530, see FIG. 5).

[0112] As shown in FIG. 6b, the control unit 130 can provide program information setting pages (hereinafter also referred to as "information setting pages" or "exercise program information setting pages") 600b, 600c, 600d, and 600e for setting program information corresponding to an exercise program on a terminal logged in with a medical staff account.

[0113] The control unit 130 may provide the program information setting pages 600b, 600c, 600d, and 600e before or after the exercise list configuration page 600a (see FIG. 6a). That is, in the present invention, the order in which the exercise list configuration page 600a and the program information setting pages 600b, 600c, 600d, and 600e are provided may be configured in various ways.

[0114] The control unit 130 may input required information (exercise part information, exercise tool information) and selection information (program name information, disease and surgery name information, step information, precaution information, shared information) for generating an exercise program through the program information setting pages 600b, 600c, 600d, and 600e.

[0115] 6b(a), the control unit 130 can provide a program information setting page 600b for inputting exercise part information on a terminal logged in with a medical staff account. For example, the control unit 130 can display exercise part graphic objects 631, 632 corresponding to at least one exercise part (e.g., whole body, knee, etc.) on the program information setting page 600b. Based on the selection of at least one of the exercise part graphic objects 631, 632, the control unit 130 can match the exercise part (e.g., knee) information corresponding to the selected exercise part graphic object 632 to an exercise program to generate the exercise program.

[0116] 6b(b), the control unit 130 may provide a program information setting page 600c for inputting exercise equipment information on a terminal logged in with a medical staff account. For example, the control unit 130 may display exercise equipment graphic objects 641 and 642 corresponding to at least one exercise equipment (e.g., elastic band, mat, etc.) on the program information setting page 600c. The control unit 130 may also check exercise equipment information matched with exercise items included in the exercise program and automatically select (e.g., highlight) the exercise equipment graphic object (e.g., mat) 642 corresponding to the checked exercise equipment.

[0117] Exercise tool information may be matched for each exercise item and stored in the storage unit 120. The control unit 130 can automatically set (match) exercise tool information for an exercise program based on the exercise tool information matched to the exercise item.

[0118] In addition, based on the selection of at least one of the exercise tool graphic objects 641, 642, the control unit 130 can match the exercise part (e.g., knee) information corresponding to the selected exercise tool graphic object 632 to the exercise program to generate the exercise program.

[0119] Furthermore, a setting page for inputting at least one of the exercise program name information, disease and surgery name information, step information, and caution information can be provided on the terminal logged in with the medical staff account. For example, as shown in (c) of FIG. 6b, the control unit 130 can provide a program information setting page 600c including a caution input area 651 to the terminal logged in with the medical staff account. The medical staff can input caution information that should be noted when prescribing an exercise program in the caution input area 651. The control unit 130 can match the caution information input in the caution input area 651 to the exercise program to generate the exercise program.

[0120] Furthermore, as shown in FIG. 6b(d), the control unit 130 can provide a program information setting page (hereinafter also referred to as the "shared setting page") 600d for inputting shared information (or shared setting information) on a terminal logged in with a medical staff account.

[0121] As described above, the present invention allows a unique exercise program created by a specific medical staff account U1 to be restricted so that it is only accessible to the specific medical staff account U1, or allows a unique exercise program to be shared so that it is also accessible to other medical staff accounts U3. The medical staff can set sharing information for the exercise program on the sharing setting page 600d.

[0122] Here, the sharing information may include either sharing status information (or sharing setting information, information regarding whether the exercise program can be shared or not) and sharing target information (medical staff account information to which the exercise program is to be shared).

[0123] 6b(d), the control unit 130 may provide an icon 661 associated with a sharing status setting function on the sharing settings page 600d. Such an icon 661 may be displayed as a first visual appearance corresponding to a shareable status and a second visual appearance corresponding to a non-shareable status. The control unit 130 may set sharing status information for either shareable or non-shareable to match the exercise program based on the medical staff account's selection of the icon 661.

[0124] On the other hand, if there is no setting (or input or selection) of a medical staff account for the sharing information, the control unit 130 may match and set the sharing status (e.g., shareable) set as a basic value (or default value) to the exercise program.

[0125] Furthermore, although not shown, the control unit 130 may further include a sharing target setting area on the sharing setting page 600d. The control unit 130 may set another medical staff account U3 as a sharing target for the exercise program based on the selection (or input) of the medical staff account in the sharing target setting area. Details related to the sharing target setting will be described later.

[0126] Meanwhile, the present invention can perform a process of generating an exercise program including selected exercise items and set program information (S540, see FIG. 5). Furthermore, the present invention can perform a process of storing the generated exercise program in association with a specific medical staff account U1 (S550, see FIG. 5).

[0127] The control unit 130 can generate an exercise program composed of the selected exercise items. Specifically, the control unit 130 can generate a unique exercise program by matching at least some of the exercise order according to the arrangement of the selected exercise items, the exercise method set for each exercise item (exercise duration and number of exercise repetitions), exercise part information corresponding to the exercise program, exercise equipment information, program name information, disease and surgery name information, step information, caution information, and shared information.

[0128] That is, the unique exercise program created in the present invention may be configured so that exercise items selected by a specific medical staff account U1 are performed (or progressed) in a predetermined order according to an exercise method (exercise duration and number of exercise repetitions) based on the settings of the specific medical staff account U1. Furthermore, the created unique exercise program may be configured to be shared with another medical staff account U3 based on the settings of the specific medical staff account U1.

[0129] Furthermore, the control unit 130 can terminate the execution of the exercise program generation mode by storing the exercise program generated in cooperation with the specific medical staff account U1 in the storage unit 120.

[0130] Meanwhile, in the present invention, a process of assigning an exercise program to a patient account can be performed based on receiving prescription information for the patient account from a specific medical staff account U1 (S560, see FIG. 5). The control unit 130 can receive prescription information regarding exercise for the patient from the medical staff terminal 10.

[0131] As shown in FIG. 7(a), the control unit 130 can provide an exercise prescription page 700 including a prescription function for patient exercise on the medical staff terminal 10 logged in with a specific medical staff account U1.

[0132] The control unit 130 can provide an exercise prescription page 700 for each patient account on the medical staff terminal 10 so that prescriptions can be made for specific patient accounts among the patient accounts matched to a specific medical staff account U1.

[0133] For example, in the present invention, it is assumed that a first patient account (e.g., patient account "Kim Woo-young") and a second patient account (e.g., patient account "Kim So-hee") are matched with a specific medical staff account U1. Upon receiving an exercise prescription request for the first patient account (e.g., patient account "Kim Woo-young") from the medical staff terminal 10, the control unit 130 can provide an exercise prescription page 700 corresponding to the first patient account on the medical staff terminal 10.

[0134] The control unit 130 can display, on the exercise prescription page 700, information regarding at least some of the multiple exercise items registered in the exercise therapy provision service, or information regarding at least one exercise program registered in the exercise therapy provision service.

[0135] Specifically, the control unit 130 can display, on the exercise prescription page 700, information regarding at least one of a unique exercise program 710 linked to a specific medical staff account U1, a shared exercise program 720 shared with a specific medical staff account U1, and a recommended exercise program 730 provided by the exercise treatment provision service.

[0136] In this case, based on the fact that the unique exercise programs and shared exercise programs associated with each medical staff account are different from each other, the control unit 130 can display information about the different unique exercise programs or different shared exercise programs on the exercise prescription page 700 provided for each medical staff account.

[0137] The control unit 130 can receive selection information (or selection event) of a specific medical staff account U1 from the medical staff terminal 10 based on the selection of any one of the exercise programs displayed on the exercise prescription page 700.

[0138] 7(a), assume that information 711 corresponding to a unique exercise program linked to a specific medical staff account U1 and an icon (e.g., "Add," "Select," or "Save") 711a are displayed on an exercise prescription page 700. The control unit 130 can receive selection information for the exercise program based on the selection of the information 711 related to the exercise program or the icon 711a corresponding to the exercise program on the exercise prescription page 700.

[0139] Furthermore, the control unit 130 can assign the selected exercise program to the patient account based on receiving prescription information including the selected exercise program from the medical staff terminal 10.

[0140] The patient U2 can receive exercise treatment according to the exercise program assigned to the patient account using the patient terminal 20 logged in with the patient account.

[0141] Specifically, the control unit 130 can provide the exercise video corresponding to the exercise program assigned to the patient account on the patient terminal 20 logged in with the patient account so that the patient U2 can imitate the exercise treatment while watching the exercise video. That is, the control unit 130 can check the exercise program assigned to the patient account and the exercise items included in the exercise program, and provide the exercise video corresponding to the exercise items on the patient terminal 20.

[0142] Meanwhile, in the present invention, a unique exercise program created in a specific medical staff account U1 can be shared with another medical staff account U3. When the control unit 130 receives sharing information for the unique exercise program from the specific medical staff account U1, it can share the unique exercise program with the other medical staff account U3 based on the received sharing information.

[0143] Here, the sharing information may include either sharing status information (information about whether the exercise program can be shared or not) or sharing target information (information about the medical staff account to which the exercise program is to be shared).

[0144] As described above, when the exercise program generation mode is executed, the control unit 130 can receive sharing information of the unique exercise program from a specific medical staff account U1. The control unit 130 can set the sharing status and sharing target of the unique exercise program based on the sharing information received from the specific medical staff account U1.

[0145] Furthermore, when the exercise program generation mode is completed, the control unit 130 can receive sharing information of the unique exercise program from a specific medical staff account U1. Based on the received sharing information, the control unit 130 can change the sharing status and sharing targets of the unique exercise program.

[0146] In this way, when the exercise program generation mode is executed or terminated, the control unit 130 can receive sharing information of the unique exercise program from a specific medical staff account U1, and set the sharing status and sharing target of the unique exercise program based on the received sharing information.

[0147] For the sake of convenience, the following description will be given assuming that the sharing status and sharing target settings of a unique exercise program are performed after the exercise program generation mode is completed. However, the data processing described below is equally applicable even when the exercise program generation mode is running.

[0148] As shown in FIG. 8a, the control unit 130 can provide a page 800 including a sharing setting function for a unique exercise program on the medical staff terminal 10 logged in with a specific medical staff account U1.

[0149] The control unit 130 may provide the custom exercise program page 800 on the terminal logged in with the specific medical staff account U1 based on receiving a request to provide the custom exercise program page 800 from the specific medical staff account U1. In this case, the custom exercise program for which the page provision request is made may correspond to any one of the custom exercise programs associated with the specific medical staff account U1.

[0150] 4a, the control unit 130 can display information 410, 420 about at least one unique exercise program associated with a specific medical staff account U1 on a unique exercise program entry page 400a. Based on a selection of any one of the information 410, 420 displayed on the unique exercise program entry page 400a, the control unit 130 can receive a request from the specific medical staff account U1 to provide a unique exercise program page (hereinafter referred to as a "program page") 800 corresponding to the selected information.

[0151] Meanwhile, the control unit 130 may display on the program page 800 a first graphic object 810 associated with a shared activation setting function for a unique exercise program, and a second graphic object 820 associated with a shared target setting function.

[0152] The control unit 130 can set the sharing status of the unique exercise program to either shareable or non-shareable based on the input (or selection) of the medical staff account for the first graphic object 810.

[0153] For example, when the unique exercise program is set to "shareable," the control unit 130 can change the sharing status of the unique exercise program from "shareable" to "not shareable" based on an input from the user of the specific medical staff account U1 to the first graphic object 810. On the other hand, when the unique exercise program is set to "not shareable," the control unit 130 can change the sharing status of the unique exercise program from "not shareable" to "shareable" based on an input from the user of the specific medical staff account U1 to the first graphic object 810.

[0154] In this case, the control unit 130 may display the visual appearance of the first graphic object 810 differently and display different guidance information around the first graphic object 810 based on whether the sharing status of the unique exercise program corresponds to either shareable or non-shareable.

[0155] For example, when a unique exercise program is set to be shareable, the control unit 130 can display a first graphical object 810 having a first visual appearance on the program page 800. In addition, the control unit 130 can display a first guidance message (e.g., "The program will be shared with the hospital (your workplace) as a shared program") 811 around the first graphical object 810 to inform the user that the unique exercise program is shareable.

[0156] Meanwhile, when the user's own exercise program is set to be unshareable, the control unit 130 may display a first graphic object 810′ having a second visual appearance different from the first visual appearance on the program page 800. In addition, the control unit 130 may display a second notification message (e.g., “This program can only be viewed by the user”) 811′ around the first graphic object 810 to inform the user that the user's own exercise program is in a unshareable state.

[0157] Meanwhile, as shown in FIG. 8a, the control unit 130 can identify at least one other medical staff account that shares the unique exercise program based on input (or selection) of a particular medical staff account U1 to a second graphic object (e.g., “Select Medical Staff”) 820.

[0158] The control unit 130 can provide information 821, 822 about other medical staff accounts (e.g., “Physical Therapist / Kim Hyun-gi (1234)”, “Doctor / Lee Ji-eun (2222)”) other than the specific medical staff account U1 to the program page 800. For example, the control unit 130 can provide information 821, 822 about at least one other medical staff account to the program page 800 based on input (or selection) of the specific medical staff account U1 to the second graphic object (e.g., “Select Medical Staff”) 820.

[0159] The control unit 130 may identify at least one other medical staff account selected through the program page 800 as a target for sharing the unique exercise program. For example, based on the selection of information 821 about the medical staff account of medical staff "Lee Ji-eun," the control unit 130 may identify medical staff "Lee Ji-eun" as a target for sharing the unique exercise program.

[0160] Furthermore, the control unit 130 can provide information corresponding to all other medical staff accounts (e.g., "select all" or "share with all medical staff in the hospital") so that a specific medical staff account U1 can select all other medical staff accounts as targets for sharing its own exercise program.

[0161] The control unit 130 can identify all other medical staff accounts as targets for sharing the unique exercise program based on the selection of information corresponding to all other medical staff accounts (e.g., "Select all" or "Share with all medical staff in the hospital").

[0162] 8b, the control unit 130 may identify a sharing target of the unique exercise program based on at least one of the hospitals 1a and 1b and the individual medical staff members U3, U4, U5, and U6. That is, the control unit 130 may identify a sharing target of the exercise program on a hospital-by-hospital basis, or on a medical staff member-by-medical staff basis, for example, U3, U4, U5, and U6.

[0163] Specifically, the control unit 130 can identify at least some of a plurality of other medical staff members who work in the same hospital (e.g., "Hospital A") as the specific medical staff member, as the sharing targets of the unique exercise program.

[0164] The control unit 130 can refer to the storage unit 120 and provide information about other medical staff accounts U3 and U6 that are matched to the same hospital 1a as the specific medical staff account U1 to the program page 800. In addition, the control unit 130 can provide information corresponding to all other medical staff accounts that are matched to the same hospital 1a (e.g., "select all" or "share with all medical staff in the hospital") to the program page 800.

[0165] The control unit 130 can identify a target for sharing the unique exercise program based on the selection of a particular medical staff account U1 relative to at least one of the other medical staff account information provided on the program page 800.

[0166] For example, based on receiving a selection corresponding to "share all within the same hospital 910" from a specific medical staff account U1, the control unit 130 can identify all other medical staff accounts U3 and U6 that are matched with the same hospital 1a as the specific medical staff account U1 as sharing targets.

[0167] As another example, based on receiving a selection corresponding to "individual sharing within the same hospital 920" from a specific medical staff account U1, the control unit 130 can identify only the selected other medical staff account U3 from among other medical staff accounts U3 and U6 that are matched with the same hospital 1a as the specific medical staff account U1 as the sharing target.

[0168] As another example, the control unit 130 may set "total sharing within the same hospital 910" as a basic value (or default value) for the sharing target for a unique exercise program. In this case, if the control unit 130 does not receive setting information for the sharing target from a specific medical staff account U1, it may identify all other medical staff accounts U3 and U6 that are matched with the same hospital 1a as the specific medical staff account U1 as the sharing target.

[0169] That is, the control unit 130 can share a unique exercise program created by a particular medical staff member with at least some of the other medical staff members who work in the same hospital as the particular medical staff member account.

[0170] Furthermore, as shown in FIG. 8b, the control unit 130 may extend and share a unique program of a particular medical staff member working at a first hospital (e.g., "Hospital A") to a second hospital (e.g., "Hospital B") different from the first hospital.

[0171] In this case, other hospitals with which the unique program can be shared may be set in advance. For example, assume that a first hospital, a second hospital, and a third hospital, which are different from one another, are registered in the exercise therapy provision service. In this case, the control unit 130 may set the system so that the unique exercise program can be shared between the first hospital and the second hospital. On the other hand, the control unit 130 may set the system so that the sharing of the unique exercise program between the third hospital and the first hospital and the second hospital is restricted. Such setting for sharing the unique exercise program between hospitals may be made at the request of the hospital. The hospital may request the setting for sharing between hospitals based on a business agreement or the like between the hospitals.

[0172] As shown in Figure 8b, when the first hospital 1a and the second hospital 1b are configured to allow sharing of unique exercise programs, the control unit 130 can share a unique exercise program linked to a specific medical staff account U1 of the first hospital 1a with at least some of the medical staff accounts U4 and U5 of the second hospital 1b.

[0173] For example, the control unit 130 can identify all of the medical staff accounts U4 and U5 of the second hospital 1b as sharing targets based on receiving a selection corresponding to "share overall within other hospitals 930" from a particular medical staff account U1.

[0174] As another example, the control unit 130 can identify some medical staff accounts U4 of the second hospital 1b as sharing targets based on receiving a selection corresponding to "individual sharing within other hospitals 940" from a particular medical staff account U1.

[0175] Furthermore, in the present invention, unique exercise programs can be shared between different hospitals registered in the exercise therapy provision service of the present invention, or between medical staff belonging to different hospitals. In other words, the unique exercise programs of the present invention can be freely shared with any hospital or medical staff registered in the system of the present invention. As a result, the system of the present invention can serve as a medical platform that allows hospitals and medical staff to share and activate each other's treatment know-how.

[0176] Meanwhile, as mentioned above, medical staff accounts in the present invention can be divided into a first type and a second type based on whether or not they have the authority to independently prescribe exercise programs to patients. In the present invention, the "authority to independently prescribe an exercise program" can be understood as the authority to prescribe an exercise program without the approval of others.

[0177] As shown in FIG. 9a, a "first type medical staff account U1" can be understood as a medical staff account that has the authority to independently prescribe exercise programs to patients.

[0178] Such a first type medical staff account U1 may further have the authority to approve an exercise program prescribed by a second type medical staff account U3.

[0179] The "second type medical staff account U3" can be understood as a medical staff account that can prescribe an exercise program to a patient based on the approval of the first type medical staff account U1.

[0180] In other words, the "second type medical staff account U3" may be a medical staff account that does not have the authority to independently prescribe exercise programs to patients. Such second type medical staff account U3 may not even have the authority to approve exercise programs prescribed by other medical staff accounts. The control unit 130 can set the type of the medical staff account to either the first type or the second type based on the occupational information of the medical staff.

[0181] For example, if the occupation of the medical staff is a first type of occupation (e.g., "doctor"), the control unit 130 can set the type of the medical staff account to a first type. Also, if the occupation of the medical staff is a second type of occupation (e.g., "therapist"), the control unit 130 can set the type of the medical staff account to a second type.

[0182] Meanwhile, in the present invention, different exercise program prescription processes can be performed depending on whether the medical staff account that prescribed the exercise program to the patient is one of the first type and the second type.

[0183] In the present invention, a first exercise prescription process can be performed when the type of the medical staff account that prescribed the exercise program is a first type, and a second exercise prescription process can be performed when the type of the medical staff account that prescribed the exercise program is a second type.

[0184] To this end, when the control unit 130 receives prescription information from a medical staff account, it can check the type of the corresponding medical staff account and, depending on the check result, can perform either a first exercise prescription process or a second exercise prescription process.

[0185] Specifically, the control unit 130 can receive exercise program prescription information for the patient from the first type medical staff account U1 (S1010, see FIG. 9b).

[0186] The control unit 130 can assign the prescribed exercise program to the patient account U2 based on receiving exercise program prescription information for the patient from the first type medical staff account U1 (S1020, see FIG. 9b).

[0187] That is, when the control unit 130 receives prescription information from a first type of medical staff account, it can perform a first exercise prescription process to immediately assign an exercise program to a patient account based on the existence of authority in the first type of medical staff account to independently prescribe an exercise program.

[0188] Meanwhile, the control unit 130 can receive exercise program information for the patient from the second type medical staff account U3 (S1030, see FIG. 9b).

[0189] Based on receiving exercise program prescription information for the patient from the second type medical staff account U3, the control unit 130 can send approval request information for the prescribed exercise program to the first type medical staff account U1 (S1040, see Figure 9b).

[0190] In this case, the control unit 130 can identify the first type medical staff account U1 that is the target of a request for exercise program prescription approval based on the selection of the second type medical staff account U3 and one of the pre-set matching information.

[0191] The control unit 130 may request approval for prescription of the exercise program from a specific first-type medical staff account selected by the second-type medical staff account U3 that prescribed the exercise program among the multiple first-type medical staff accounts. In addition, the control unit 130 may request approval for prescription of the exercise program from a specific first-type medical staff account matched with the second-type medical staff account U3 that prescribed the exercise program among the multiple first-type medical staff accounts.

[0192] When the first type medical staff account U1 that received the prescription approval request approves the prescription for the exercise program (i.e., an exercise program prescription approval event occurs), the control unit 130 can receive approval information from the first type medical staff account U1 (S1040, see FIG. 9b).

[0193] The control unit 130 can assign the exercise program prescribed by the second type medical staff account U3 to the patient account U2 based on the approval of the exercise program prescription by the first type medical staff account U1 (or the occurrence of an exercise program prescription event) (S1050, see Figure 9b).

[0194] That is, when the control unit 130 receives prescription information from the second type medical staff account, it can send an exercise program prescription request to the first type medical staff account U1 that has approval authority based on the existence of authority in the second type medical staff account to independently prescribe an exercise program. Furthermore, the control unit 130 can perform a second exercise prescription process to assign an exercise program to a patient account based on the occurrence of an approval event for the exercise program prescription from the first type medical staff account.

[0195] Meanwhile, as shown in (a) of FIG. 9c, the control unit 130 can provide, on a terminal logged in with a second type medical staff account, a page 1000a including an area 1011 for identifying the first type medical staff account that approved the exercise program prescription.

[0196] The control unit 130 can display information about at least one first type medical staff account (e.g., "Yun Chang (5678)" and "Lee Yu-hyun (1234)") 1011, 1011 in the area 1010.

[0197] In this case, the control unit 130 can display information about the first type medical staff account that is matched with the same hospital as the second type medical staff account in the area 1010. That is, the control unit 130 can provide information about medical staff who have a first type occupation (e.g., doctor) among medical staff who work in the same hospital as the medical staff who have a second type occupation (e.g., therapist) in the first area 1010.

[0198] Based on the selection of a specific first type medical staff account (e.g., "Yun-Chan") through the area 1010, the control unit 130 can request approval from the selected first type medical staff account for the exercise program prescription of the second type medical staff account.

[0199] As shown in (b) of FIG. 9c, the control unit 130 can provide an exercise program approval page 1000b on the terminal logged in with the first type medical staff account U1.

[0200] The control unit 130 can display, on the exercise program approval page 1000b, at least one of second type medical staff account information 1021, exercise program prescribed date information 1022, exercise program information 1023, and patient information 1024 for which the exercise program is prescribed. The control unit 130 may also include, on the exercise program approval page 1000b, an approval graphic object 1025 associated with the exercise program approval function, and a rejection graphic object (or rejection graphic object) 1026 associated with the exercise program rejection (or non-approval) function.

[0201] The control unit 130 can assign the exercise program prescribed by the second type medical staff account U3 to the patient account U2 based on the selection of the approval graphic object 1025 on the exercise program approval page 1000b.

[0202] On the other hand, the control unit 130 can restrict the exercise program prescribed by the second type of medical staff account U3 from being assigned to the patient account U2 based on the selection of the rejection graphic object (or disapproval graphic object) 1026 on the exercise program approval page 1000b.

[0203] On the other hand, when the control unit 130 receives exercise program prescription information for a patient from the second type medical staff account U3, it can assign the prescribed exercise program to the patient account based on the automatic approval setting for the exercise program prescription.

[0204] That is, when automatic approval for an exercise program is set (or activated), the control unit 130 can restrict the request for prescription approval of an exercise program prescribed in a second type account from the first type medical staff account U1, and can immediately assign the prescribed exercise program to the patient account.

[0205] On the other hand, if automatic approval for the exercise program is not set (or is deactivated), the control unit 130 can request the first type medical staff account U1 to approve the prescription of the exercise program prescribed by the second type account.

[0206] To this end, as shown in (c) of Fig. 9c, the control unit 130 may provide a page 1000c including an icon 1030 associated with an automatic approval setting function for an exercise program prescription on a terminal logged in with the first type medical staff account U1. For example, the control unit 130 may include the automatic approval icon 1030 on the My Page 1000c.

[0207] The control unit 130 can set the automatic approval function for the exercise program to either activated or deactivated based on the input (or selection) of the first type medical staff account U1 to the automatic approval icon 1030.

[0208] For example, when the automatic approval function is set to "activated," the control unit 130 can change the automatic approval function from "activated" to "deactivated" based on an input by the user of the first type medical staff account U1 to the automatic approval icon 1030. On the other hand, when the automatic approval function is set to "deactivated," the control unit 130 can change the automatic approval function from "deactivated" to "activated" based on an input by the user of the first type medical staff account U1 to the automatic approval icon 1030.

[0209] This invention provides a user environment in which medical staff can share their own exercise programs with each other on a hospital basis. Therefore, if a medical staff member is transferred or changes hospitals where they work, it may become an issue as to whether the shared programs will continue to be shared among the medical staff members. Therefore, it is very important to update the hospital information of the changed medical staff members.

[0210] Therefore, the present invention can provide a function for changing the hospital where a medical staff member works. In the present invention, the hospital where a medical staff member works can refer to the hospital where the medical staff member works (or belongs to) or an affiliated hospital.

[0211] As shown in FIG. 10, the control unit 130 can provide a page 1100 for changing the hospital (or hospital information) where the medical staff member works on the terminal logged in with the medical staff member account. When a medical staff member is transferred from a first hospital to a second hospital, the medical staff member can change the hospital where he or she works from the first hospital to the second hospital through the page 1100 .

[0212] The control unit 130 can update the hospital information matched to the medical staff account from the first hospital to the second hospital based on the medical staff account inputting the second hospital as the medical staff's changed working hospital.

[0213] Meanwhile, when the hospital matched with the medical staff account is changed from the first hospital to the second hospital, the control unit 130 may suspend sharing so that the exercise program that was shared with other medical staff accounts working at the first hospital is no longer shared.

[0214] For example, assume that a unique program generated by a particular medical staff account U1 based on the fact that the particular medical staff member works at Hospital 1 is shared with Medical Staff Account U3 of another medical staff member working at Hospital 1.

[0215] When the work hospital information matched to the specific medical staff account U1 is changed from a first hospital to a second hospital, the control unit 130 can suspend sharing so that the exercise program of the specific medical staff account U1 is no longer shared with another medical staff account U3 matched to the first hospital.

[0216] Furthermore, when the hospital matched with a medical staff account is changed from a first hospital to a second hospital, the control unit 130 can suspend sharing of the exercise program that was shared with other medical staff accounts working at the first hospital so that it is no longer shared with the medical staff account that has been transferred to the second hospital.

[0217] As described above, the method and system for generating a customized therapeutic exercise program according to the present invention can provide a user environment in which medical staff can directly customize an exercise program by running an exercise program generation mode on a terminal logged in with a specific medical staff account.

[0218] Specifically, the method and system for generating a customized therapeutic exercise program according to the present invention generates an exercise program by selecting at least one exercise item to be included in the exercise program in an exercise program generation mode, allowing medical staff to generate an effective and optimal exercise program taking into consideration various factors such as the patient's characteristics such as disease, symptoms, age, age group, and exercise ability.

[0219] In particular, the method and system for generating a customized exercise treatment program according to the present invention stores the generated exercise program in association with a specific medical staff account U1, thereby enabling the exercise program generated by the specific medical staff account U1 to be managed and the exercise program to be shared with other medical staff accounts.

[0220] Furthermore, the method and system for generating a customized therapeutic exercise program according to the present invention can assign the exercise program to a patient account based on receiving prescription information for the patient account from a specific medical staff account U1, allowing a doctor to prescribe a customized therapeutic exercise program for the patient, and allowing the patient to receive the optimal exercise program and exercise effectively.

[0221] Meanwhile, the present invention described above can be embodied as a program that can be executed by one or more processes on a computer and stored on a computer-readable medium (or recording medium).

[0222] Furthermore, the present invention described above can be embodied as computer-readable code or instructions on a medium having a program recorded thereon, i.e., the present invention can be provided in the form of a program.

[0223] As described above, the present invention can provide therapeutic exercise for musculoskeletal disorders online, and the therapeutic exercise provision method and system will be discussed in more detail below. In particular, the following discusses a therapeutic exercise provision method and system that can analyze a patient's exercise movements performing prescribed exercises based on exercise video captured of the patient's exercise. In this way, the present invention can provide a therapeutic exercise provision method and system that can analyze a patient's exercise movements from exercise video based on an artificial intelligence model specialized for musculoskeletal disorders. Furthermore, the present invention can provide a therapeutic exercise provision method and system that can provide a user environment in which patients can easily access treatment for musculoskeletal disorders.

[0224] The present invention relates to a method for analyzing a patient's exercise movements contained in exercise videos received from a patient's terminal and providing analysis results. In particular, the present invention relates to a method for analyzing exercise movements based on a patient's joint points using an artificial intelligence model specialized for musculoskeletal disorders.

[0225] Although the present invention will be described focusing on the analysis of exercise movements in rehabilitation exercises for musculoskeletal disorders, it is not necessarily limited to this. That is, the motion analysis in the present invention may include not only the analysis of exercise movements but also the analysis of various movements such as movements in daily life and movements during stretching.

[0226] On the other hand, the "exercise action" described in this invention refers to a gesture (movement) performed in the process of exercising, and may be used interchangeably with terms such as bodily "movement," "action," "movement," and "gesture."

[0227] Furthermore, the "exercise video" is a video (image or video) that captures (includes) the process of the patient performing exercise, as shown in FIG. 16, and includes at least a part of the patient U's body.

[0228] In the present invention, a patient object included in an exercise video will be referred to as "subject U." In the present invention, "subject U" may refer to a patient exercising in the exercise video or a part of the patient's body. In the present invention, "subject" and "patient" may be used interchangeably, and will be described with the same reference numeral "U."

[0229] The following describes in detail the method and system for providing therapeutic exercise using an AI posture estimation model and a motion analysis model according to the present invention, with reference to the accompanying drawings. Figure 11 is a conceptual diagram illustrating the therapeutic exercise system according to the present invention. Figures 12 and 13 are flowcharts illustrating the therapeutic exercise method according to the present invention. Figures 14a and 14b are conceptual diagrams illustrating a doctor's prescription. Figures 15 and 16 are conceptual diagrams illustrating a method for analyzing a patient's exercise motion from an exercise video. Figures 17, 18a, 18b, 18c, 18d, 18e, and 18f are conceptual diagrams illustrating an AI posture estimation model. Figures 19 and 20 are conceptual diagrams illustrating an example of providing a user's motion analysis results. Furthermore, Figures 21a, 21b, and 21c are conceptual diagrams illustrating a user environment in which a patient's motion analysis results are provided.

[0230] As shown in FIG. 11 , the therapeutic exercise provision system 1000 according to the present invention analyzes a patient's exercise motions using an AI posture estimation and motion analysis model based on exercise video received from a patient terminal 10, and may include at least one of an application 100 installed on the patient terminal 10 and an AI server (or cloud server) 200. The therapeutic exercise provision system 1000 according to the present invention may also include a posture estimation model and a motion analysis model trained using training data. Of course, at least one of the components and functions of the therapeutic exercise provision system 1000 discussed below may be included as at least one of the components of the digital-based musculoskeletal rehabilitation treatment provision system described above. The digital-based musculoskeletal rehabilitation treatment provision system may be configured to include at least one of the functions or components described below.

[0231] The application 100 of the present invention is installed on a patient terminal 10 and can perform the function of analyzing the exercise movements of a patient U with a musculoskeletal disorder and providing feedback information based on the analysis results. Therefore, the application 100 of the present invention may be named a "digital exercise therapy solution," a "digital rehabilitation therapy solution," a "digital exercise evaluation solution," a "non-face-to-face exercise therapy solution," a "non-face-to-face rehabilitation therapy solution," a "non-face-to-face exercise evaluation solution," a "mobile exercise therapy program," a "mobile rehabilitation therapy program," a "mobile exercise evaluation program," and a "Mobile Orthopedic Rehabilitation Assistant (MORA)."

[0232] The application 100 according to the present invention is installed in a patient terminal 10 and can play a role in connecting a patient U with a musculoskeletal disorder with an orthopedic surgeon D, thereby supporting the rehabilitation of the patient U. For the sake of convenience, the application 100 installed in the patient terminal 10 will be referred to as a "therapeutic exercise application" below.

[0233] Meanwhile, the therapeutic exercise application 100 according to the present invention can be installed on a patient terminal 10. The patient terminal 10 described in the present invention refers to an electronic device logged in with a user account of a patient U, and the electronic device may include, for example, at least one of a smartphone, a mobile phone, a tablet PC, a kiosk, a computer, a laptop, a digital broadcast terminal, a PDA (Personal Digital Assistant), and a PMP (Portable Multimedia Player).

[0234] Here, the user account of patient U may refer to the account of patient U that is pre-registered in the exercise therapy providing system 1000 according to the present invention. Such a user account of patient U may be understood as a "patient account" or a "patient ID (identification, identification number)." In the present invention, the terms "patient," "patient account (or patient user account)," and "patient terminal" may be used interchangeably.

[0235] Meanwhile, a doctor can prescribe exercise to patient U via doctor terminal 20. Doctor terminal 20 in the present invention may refer to an electronic device logged in with doctor D's user account. Doctor D's user account is an account of doctor D registered in advance in exercise treatment provision system 1000 according to the present invention, and can be understood as a "doctor account" or a "doctor ID (identification, identification number)." In the present invention, the terms "doctor," "doctor account (or doctor's user account)," and "doctor terminal" may be used interchangeably. Doctor D can prescribe medication to patient U by referring to user DB 30 that contains user information about patient U.

[0236] The user DB 30 may contain user information (or patient information) of patient U matched to each patient account. The user information of patient U may include various information necessary for providing exercise therapy. For example, the user information of patient U may include at least one of the patient U's disease information, age information, gender information, surgical history information, exercise plan information, exercise execution information, height information, and weight information. However, the above-described patient user information is merely an example, and it goes without saying that the patient user information may include various information necessary for providing exercise therapy to the patient.

[0237] Meanwhile, the exercise therapy application 100 described in the present invention is installed on the patient terminal 10, and can analyze the exercise movements of a patient who has performed exercises according to the prescription of Doctor D through an AI posture estimation model and an AI movement analysis model and provide the results on the patient terminal 10.

[0238] In addition, the therapeutic exercise application 100 is configured to communicate with the artificial intelligence server 200, and can provide the patient's exercise and motion analysis results analyzed by the artificial intelligence server 200 on the patient terminal 10. The patient's exercise and motion analysis results analyzed by the artificial intelligence server 200 can be generated by at least one of the artificial intelligence motion analysis unit 212 and the rule-based motion analysis unit 213 included in the motion analysis unit 210.

[0239] The therapeutic exercise application 100 is configured to transmit and receive data to and from the artificial intelligence server 200 via wireless communication, and there is no limitation on the wireless communication method. The therapeutic exercise application 100 according to the present invention can communicate with the artificial intelligence server 200 using a communication module provided in the patient terminal 10. The communication module provided in the patient terminal 10 may be various.

[0240] For example, the communication module provided in the patient terminal 10 may be a WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Wi-Fi (Wireless Fidelity) Direct, DLNA (Digital Living Network Alliance: registered trademark), WiBro (Wireless Broadband), WiMAX (World Interoperability for Microwave Access), HSDPA (High Speed ​​Downlink Packet Access), HSUPA (High Speed ​​Uplink Packet Access), LTE (Long Term Evolution), LTE-A (Long Term Evolution-Advanced), 5G (5th Generation Mobile Telecommunication), Bluetooth (Bluetooth TMThe device may be configured to communicate with the artificial intelligence server 200 using at least one of the following technologies: QR Code (registered trademark), RFID (Radio Frequency Identification), Infrared Data Association (IrDA), UWB (Ultra-Wideband), ZigBee, NFC (Near Field Communication), Wi-Fi Direct, and Wireless Universal Serial Bus (Wireless USB).

[0241] Meanwhile, the artificial intelligence server 200 described in the present invention may be a cloud server that analyzes the exercise movements of patient U from exercise videos. Such an artificial intelligence server 200 can analyze the exercise movements of patient U using the exercise videos received from the exercise therapy application 100. The "artificial intelligence server" described in the present invention may be named an "artificial intelligence exercise therapy server," an "artificial intelligence rehabilitation therapy server," a "digital therapy server," etc. Hereinafter, for convenience of explanation, it will be referred to as the "artificial intelligence server."

[0242] Meanwhile, at least one of the therapeutic exercise application 100 and the artificial intelligence server 200 according to the present invention can analyze the relative positional relationship between key points P1 and P2 corresponding to a plurality of joint points of the patient U extracted from the exercise video 300 through a posture estimation model 52 (corresponding to the artificial intelligence posture estimation unit 121a in FIG. 11) trained using training data related to the joint points, as shown in FIG. 17. The analysis of the relative positions between the key points can be performed by the motion analysis units 120 and 210. In particular, the exercise motion can be analyzed by one of the artificial intelligence motion analysis units 122 and 212 and the rule-based motion analysis units 123 and 213 of the motion analysis unit. One of the artificial intelligence motion analysis units 122 and 212 or the rule-based motion analysis units 123 and 213 can be named an artificial intelligence motion analysis model. Here, "joint points" may refer to multiple joints of patient U (or a part of patient U's body that includes joints). Furthermore, the term "key point" may refer to an area in the motion video 300 that corresponds to each of a plurality of joint points of the subject U.

[0243] Therefore, in the present invention, the terms "joint point" and "key point" may be used interchangeably, and the same reference numerals "P1" and "P2" are used to denote the joint point and the key point, respectively.

[0244] The exercise therapy providing system 1000 can extract key points P1 and P2 corresponding to joint points from the patient's exercise video using the posture estimation model 52, and analyze the exercise movements of the patient U based on an analysis of the positional relationship between the extracted key points P1 and P2. In the present invention, a series of processes for analyzing the patient's exercise movements from the exercise video using the key points extracted through the artificial intelligence posture estimation model 52 can be named the "exercise movement analysis process."

[0245] Such an exercise motion analysis process can be performed by at least one of the exercise therapy application 100 and the artificial intelligence server 200. Specifically, the exercise motion analysis process may include at least one of i) a first data processing method performed by the exercise therapy application 100, ii) a second data processing method performed by the artificial intelligence server 200, and iii) a third data processing method performed by both the exercise therapy application 100 and the artificial intelligence server 200.

[0246] Here, in the third data processing method, the exercise therapy application 100 and the artificial intelligence server 200 may process data sequentially or simultaneously.

[0247] Therefore, in the present invention, the exercise analysis process will be described as being performed in the exercise therapy providing system 1000 without distinguishing between the physical space and the subject in which the exercise analysis process is performed.

[0248] 17, the motion analysis process may be performed using key points extracted from the AI ​​posture estimation model 52. The AI ​​posture estimation model 52 can identify or estimate the patient's joint points from the motion video through learning data specialized for the joint points, and extract the corresponding key points.

[0249] In the present invention, the training data used by AI pose estimation model 52 for training may be stored in database 40, which may be referred to as a "training data DB." Details of the training data will be described later.

[0250] As shown in Fig. 17, posture estimation server 50 may include at least one of learning unit 51 and posture estimation model 52. Posture estimation server 50 may be provided inside exercise therapy providing system 1000 according to the present invention, or may be formed as an external server. In other words, posture estimation server 50 according to the present invention performs the function of learning posture estimation, and can be understood as having no physical space constraints. Details of posture estimation server 50 will be described later together with learning data.

[0251] Meanwhile, as shown in FIG. 11, a therapeutic exercise application 100 according to the present invention may include at least one of a video receiving unit 110, a motion analyzing unit 120, a video processing unit 130, and a control unit 140.

[0252] The video receiving unit 110 of the therapeutic exercise application 100 may be configured to receive exercise video including the state of the patient's exercise from the patient terminal 10 on which the application 100 is installed. Such exercise video can be captured by a camera provided in the patient terminal 10. In the present invention, "receiving exercise video from the patient terminal 10" may mean that the video receiving unit 110 of the therapeutic exercise application 100 accesses the exercise video recorded in the memory of the patient terminal 10.

[0253] The motion analysis unit 120 of the exercise therapy application 100 can analyze the exercise motion (or exercise posture) of the patient based on the exercise video received from the patient terminal 10. For this purpose, the motion analysis unit 120 of the exercise therapy application 100 may be configured to include at least one of a key point extraction unit 121, an artificial intelligence motion analysis unit 122, and a rule-based motion analysis unit 123. The artificial intelligence motion analysis unit 122 or the rule-based motion analysis unit 123 may be named an "artificial intelligence motion analysis model."

[0254] The key point extraction unit 121 can extract key points P1 and P2, which are pairs of coordinate information on the x-axis and y-axis, from the motion video. In this case, the key point extraction unit 121 can extract key points from the video using an artificial intelligence model.

[0255] In the present invention, extraction of key points using an artificial intelligence model will be described as being performed by an artificial intelligence posture estimation unit 121 a included in key point extraction unit 121 .

[0256] The AI ​​posture estimation unit 121a may be referred to as an "AI posture estimation model" and may extract key points corresponding to the patient's joint points from the motion video using an AI model trained for object detection from video. The AI ​​posture estimation model may be a model based on object detection. For example, the AI ​​posture estimation unit 121a may extract key points from the motion video using an object detection AI model that ensembles multiple bounding boxes. Meanwhile, the AI ​​posture estimation unit 121a may use various object detection AI models, and the above-mentioned object detection AI model is one example.

[0257] Furthermore, in the present invention, the artificial intelligence motion analysis unit 122 and the rule-based motion analysis unit 123 can analyze the patient's exercise motion (or exercise posture) using at least one of the exercise video received from the patient terminal and the key points extracted by the key point extraction unit 120.

[0258] More specifically, the artificial intelligence motion analysis unit 122 and the rule-based motion analysis unit 123 can i) analyze the patient's motion based on the motion video, ii) analyze the patient's motion based on key points, or iii) analyze the patient's motion using both the motion video and key points.

[0259] For the sake of convenience, the following description will mainly focus on a method for analyzing a patient's exercise movements based on key points. However, it goes without saying that the AI ​​motion analysis unit 122 and the rule-based motion analysis unit 123 can receive exercise videos as input data instead of key points, and can directly analyze a patient's exercise movements from the exercise videos. Meanwhile, the AI ​​motion analysis unit 122 or the rule-based motion analysis unit 123 can also be expressed as the above-mentioned "AI motion analysis model."

[0260] Meanwhile, the artificial intelligence motion analysis unit 122 can classify (or identify) the type of exercise performed by the patient and determine the accuracy of the exercise based on an artificial intelligence model (or posture estimation model, see drawing reference number "52" in Figure 17) learned to analyze the patient's exercise (or exercise posture) from key points.

[0261] In addition, the rule-based motion analysis unit 123 can classify the type of exercise (or identify the type of exercise) performed by the patient and determine the accuracy of the exercise based on rule information defined for analyzing the patient's exercise.

[0262] Here, "rule information" refers to information that includes various rules used in analyzing exercise movements, and may include, for example, reference joint range of motion information for each exercise movement (or type of exercise). Such rule information may be used interchangeably with terms such as "reference information" and "standard information."

[0263] Furthermore, the rule information may include various rule information for analyzing at least one of the joint's movable range, joint's movable distance, joint movement speed (or acceleration), body balance, body equilibrium, and body alignment state (e.g., leg axis alignment state, spinal alignment state, etc.) of a subject (corresponding to a patient) included in the analysis target movement video, in addition to the joint's movable range. The rule-based motion analysis unit 123 can derive various analysis results from the analysis target movement video of the patient based on such rule information. In the present invention, the patient's exercise motion can be analyzed from the exercise video by at least one of the artificial intelligence motion analysis unit 122 and the rule-based motion analysis unit 123.

[0264] Specifically, in the present invention, i) the patient's exercise movements are analyzed by the artificial intelligence motion analysis unit 122 ("first analysis execution method"), ii) the patient's exercise movements are analyzed by the rule-based motion analysis unit 123 ("second analysis execution method"), or iii) the patient's exercise movements may be analyzed by both the artificial intelligence motion analysis unit 122 and the rule-based motion analysis unit 123 ("third analysis execution method").

[0265] Here, in the third analysis execution method, the AI ​​action analysis unit 122 and the rule-based action analysis unit 123 may process data sequentially or simultaneously.

[0266] Meanwhile, the image processor 130 of the therapeutic exercise application 100 may be configured to overlap and render graphic objects corresponding to the extracted key points P1 and P2 on the subject U of the patient included in the exercise image 300. This allows the patient to intuitively recognize the joint points where analysis is performed on their exercise movements.

[0267] The control unit 140 of the therapeutic exercise application 100 may be configured to perform overall control over the configuration included in the therapeutic exercise application 100. The control unit 140 of the therapeutic exercise application 100 can control the configuration of the therapeutic exercise application 100 using a CPU (Central Processing Unit) of the patient terminal 10, and can also control the configuration provided in the patient terminal 10 (e.g., a communication module, a camera module, a sensing module, an output module (e.g., a display, a speaker), and an input module (e.g., a touch screen, a microphone)).

[0268] On the other hand, as shown in FIG. 11, the artificial intelligence server 200 is a cloud server configured to analyze a patient's exercise posture using an artificial intelligence posture estimation model, and may be configured to include at least one of a motion analysis unit 210 and a control unit 220. The motion analysis unit 210 of the artificial intelligence server 200 can analyze the exercise motion (or exercise posture) of the patient based on the exercise video received from the patient terminal 10.

[0269] The motion analysis unit 210 of the artificial intelligence server 200 can receive the patient's exercise video from the exercise therapy application 100, and the exercise video may be received by a communication unit (or communication module) of the artificial intelligence server 200.

[0270] The motion analysis unit 210 of the artificial intelligence server 200 may be configured to include at least one of a key point extraction unit 211, an artificial intelligence motion analysis unit 212, and a rule-based motion analysis unit 213. The artificial intelligence motion analysis unit 212 or the rule-based motion analysis unit 213 may be named an "artificial intelligence motion analysis model."

[0271] The keypoint extraction unit 211, the AI ​​motion analysis unit 212, and the rule-based motion analysis unit 213 included in the AI ​​server 200 may perform the same functions as the keypoint extraction unit 121, the AI ​​motion analysis unit 122, and the rule-based motion analysis unit 123 of the above-described exercise therapy application 100. Therefore, detailed descriptions thereof will be omitted. The control unit 220 of the artificial intelligence server 200 may be configured to perform overall control over the components included in the artificial intelligence server 200.

[0272] Hereinafter, an exercise and motion analysis process will be described, in which the exercise and motion of the patient U is analyzed from an exercise video and an exercise and motion analysis result is provided using the above-described configuration of the exercise treatment providing system 1000 according to the present invention.

[0273] 12, the doctor terminal 20 may prescribe an exercise prescription for the patient U (S210). The exercise treatment provision system 1000 can receive prescription information for the exercise prescription from the doctor terminal 20 based on the exercise prescription for the patient being prescribed by the doctor terminal 20.

[0274] The exercise therapy delivery system 1000 can assign an exercise plan including at least one prescribed exercise according to the prescription information to the patient account based on the prescription information received from the doctor terminal 20. The assigned exercise plan can be transmitted to the patient terminal 10 (S220).

[0275] The exercise therapy providing system 1000 may include a communication unit that communicates with at least one of the patient terminal 10, the doctor terminal 20, the user DB 30, and the database 40. For example, the communication unit may be a wireless LAN (WLAN), a wireless fidelity (Wi-Fi), a wireless fidelity (Wi-Fi) Direct, a digital living network alliance (DLNA: registered trademark), a wireless broadband (WiBro), a world interoperability for microwave access (WiMAX), a high speed downlink packet access (HSDPA), a high speed uplink packet access (HSUPA), a long term evolution (LTE), a long term evolution-advanced (LTE-A), a fifth generation mobile telecommunication (5G), a Bluetooth (Bluetooth TM Communication can be performed using at least one of the following technologies: WiFi (registered trademark), RFID (Radio Frequency Identification), Infrared Data Association (IrDA), UWB (Ultra-Wideband), ZigBee, NFC (Near Field Communication), Wi-Fi Direct, and Wireless USB (Wireless Universal Serial Bus).

[0276] Meanwhile, the patient terminal 10 can capture an exercise video of the patient performing the prescribed exercise included in the exercise plan (S230). The exercise treatment application 100 can activate the camera provided in the patient terminal 10 and control it to capture the exercise video.

[0277] The exercise video captured by the patient terminal 10 can be used by the exercise treatment providing system 1000 as data to be analyzed (or exercise video to be analyzed) for the patient's exercise motion analysis.

[0278] As mentioned above, the exercise and motion analysis process may be performed by at least a part of the exercise therapy application 100 and the artificial intelligence server 200 installed on the patient terminal 10, and in the present invention, the exercise and motion analysis process is described as being performed in the exercise therapy provision system 1000 without separately distinguishing between the physical space and the entity in which the exercise and motion analysis process is performed.

[0279] Meanwhile, the therapeutic exercise providing system 1000 can extract key points P1 and P2 corresponding to a plurality of joint points from the exercise video. The extraction of the key points P1 and P2 can be performed by at least a part of the key point extraction unit 121 included in the therapeutic exercise application 100 and the key point extraction unit 221 included in the artificial intelligence server 200.

[0280] The exercise therapy provision system 1000 can analyze the relative positional relationship between the extracted key points P1 and P2 (S250). The exercise therapy provision system 1000 can also analyze the exercise motion of the patient U based on the analysis of the positional relationship between the key points P1 and P2 (S260). Such exercise motion analysis may be performed by at least a part of the motion analysis unit 120 of the application 100 and the motion analysis unit 210 of the artificial intelligence server 200.

[0281] Furthermore, the exercise treatment providing system 1000 can provide the results of the exercise motion analysis of the patient U to the patient terminal 10 as feedback information and to the doctor terminal 20 as monitoring information (S270).

[0282] In this way, the exercise therapy provision system 1000 can exercise overall control over the exercise motion analysis process, which in the present invention can be understood to be performed by the control unit of the exercise therapy provision system 1000. That is, the control unit of the exercise therapy provision system 1000 is a concept that includes the control unit 140 of the exercise therapy application 100 and the control unit 220 of the artificial intelligence server 200, and can exercise overall control over the exercise therapy provision system 1000. The exercise motion analysis process performed by the exercise treatment provision system 1000 will be described in more detail below.

[0283] In the present invention, a process of receiving prescription information regarding exercise for a patient from a doctor terminal can be performed (S310, see FIG. 3).

[0284] 14a and 14b, the exercise treatment provision system 1000 can provide an exercise prescription page (or exercise allocation page) including a prescription function for patient exercise on the doctor terminal 20 logged in with a doctor account. In the present invention, the term "exercise prescription" may be used interchangeably with "exercise allocation."

[0285] The exercise treatment provision system 1000 can provide an exercise prescription page for each patient account on the doctor terminal 20 so that a prescription can be made for a specific patient U account among the patient accounts matched with the doctor account.

[0286] For example, in the present invention, it is assumed that a first patient account (e.g., patient account of "Kim Woo-young") and a second patient account (e.g., patient account of "Kim So-hee") are matched with a specific doctor D account. The exercise treatment providing system 1000 can provide an exercise prescription page corresponding to the first patient account on the doctor terminal 20 based on receiving an exercise prescription request for the first patient account (e.g., patient account of "Kim Woo-young") from the doctor terminal 20.

[0287] The exercise therapy provision system 1000 can receive prescription information for a specific patient from the doctor terminal 20 based on a user selection (or user input) made on an exercise prescription page corresponding to the specific patient. The prescription information may include various information for prescribing exercise to the patient. For example, the prescription information may include at least one of the following: i) information on at least one exercise action to be included in the exercise plan (e.g., "Put your hands against the wall to stretch your calves" or "Sit and roll a ball to massage the soles of your feet"), ii) exercise action difficulty information, iii) exercise action duration information, iv) exercise action execution count information, v) exercise action execution schedule information, vi) physical information matched to the exercise action (e.g., "ankle" or "knee"), and vii) caution information (e.g., "Please apply ice after exercise") (see (a) of FIGS. 14a and 14b).

[0288] The exercise therapy providing system 1000 can receive prescription information for a specific patient U from the doctor terminal 20 based on the prescription information for the specific patient being input (or selected) on the exercise prescription page corresponding to the specific patient. In this case, guidance information informing the doctor that a prescription has been made for the specific patient may be output on the doctor terminal 20 (see (b) of FIG. 14).

[0289] Meanwhile, in the present invention, a process of assigning an exercise plan including at least one prescribed exercise to a patient account based on the prescription information can be performed (S320, see FIG. 13).

[0290] As shown in (a) of Figure 15, the exercise therapy provision system 1000 can assign an exercise plan E including at least one prescribed exercise to a specific patient account based on prescription information for the specific patient U, and provide the assigned exercise plan (e.g., "digital therapeutic agent for patellofemoral arthritis") E on the patient terminal 10 logged in with the specific patient account.

[0291] Here, the "prescribed exercise" can be understood as an exercise action that is identified based on prescription information and assigned to a patient account from among multiple exercise actions (or exercise types) included in the exercise treatment provision system 1000. Therefore, in the present invention, the "prescribed exercise" may be used interchangeably with the "exercise action." Also, in the present invention, the "exercise plan" may be used interchangeably with the "digital therapeutic agent."

[0292] The exercise treatment provision system 1000 can provide an exercise page linked to an exercise guide video provision function on the patient terminal 10 so that the patient can perform the prescribed exercises included in the exercise plan based on receiving a request for the provision of an exercise plan assigned to a specific patient account from the patient terminal 10 logged in with the specific patient account.

[0293] As shown in FIG. 1, the exercise page may include an exercise list L, which may include items V1 to V6 corresponding to exercise guide videos for each of multiple prescribed exercises (e.g., "straight leg raises," "standing and bending the knees") included in the exercise plan assigned to a specific account.

[0294] When the exercise plan includes a specific prescribed exercise (e.g., "straight leg raise") with multiple exercise sets, the exercise therapy provision system 1000 can control the exercise list L to include items V1 to V3 corresponding to the exercise guide video of the specific prescribed exercise for the number of sets (e.g., "3").

[0295] On the other hand, the exercise treatment provision system 1000 can control the patient terminal 10 to play multiple exercise guide videos in sequence based on the order of items V1 to V6 included in the exercise list L, based on receiving a request to start exercise from the patient terminal 10. Meanwhile, in the present invention, a process of receiving an exercise video of the exercise corresponding to the prescribed exercise from the patient terminal can be performed (S330, see FIG. 13).

[0296] As shown in FIG. 16, the exercise therapy provision system 1000 can control the camera provided on the patient terminal 10 to capture exercise video of patient U based on the exercise guide video being played on the patient terminal 10.

[0297] The exercise therapy application 100 installed on the patient terminal 10 can control the activation state of the camera provided on the patient terminal 10 from an inactive state to an active state, thereby controlling the camera to capture exercise footage of patient U performing exercise movements in accordance with the exercise guide video.

[0298] As shown in (a) of Figure 16, the exercise therapy application 100 may output a guidance message (e.g., "Please stand within the screen") on the patient terminal 10 so that the patient's entire body is included within a specific area of ​​the exercise video (or the display of the patient terminal) in order to detect a subject U corresponding to the patient from the exercise video captured by the camera.

[0299] The therapeutic exercise application 100 can detect the object U from the video 300 using an object detection algorithm, based on the fact that the object U corresponding to the patient's entire body is included in a specific region.

[0300] The therapeutic exercise application 100 can use various object detection algorithms. For example, the therapeutic exercise application 100 can use an algorithm (Weighted Box Fusion, WBF) that ensembles multiple bounding boxes. However, it goes without saying that the therapeutic exercise application 100 is not limited to the above-mentioned object detection algorithm, and can use various object detection algorithms that can detect an object corresponding to the subject U from the training target exercise video 300.

[0301] Furthermore, the exercise therapy application 100 can use a camera to capture exercise footage of the patient performing exercise movements according to the prescribed exercise, based on the detection of an object U corresponding to the patient's entire body within a specific area.

[0302] In this case, the exercise therapy application 100 can capture an image of the patient performing the prescribed exercise while playing back an exercise guide video corresponding to the prescribed exercise assigned to the patient.

[0303] In addition, the exercise therapy application 100 can match the exercise footage captured by the camera of the patient terminal 10 to the exercise plan (or each of the multiple prescribed exercises included in the exercise plan) and control it to be recorded in the memory of the patient terminal 10.

[0304] Meanwhile, in the present invention, a process of extracting key points corresponding to a plurality of pre-set joint points from a motion video can be performed (S340, see FIG. 13).

[0305] In the present invention, key points P1 and P2 corresponding to preset joint points P1 and P2 can be extracted from an exercise video by at least a part of the exercise therapy application 100 and the artificial intelligence server 200. As described above, the extraction of key points P1 and P2 may be performed i) by the exercise therapy application 100, ii) by the artificial intelligence server 200, or iii) by both the exercise therapy application 100 and the artificial intelligence server 200. In the following description, the extraction of key points P1 and P2 will be performed by the exercise therapy provision system 1000 without distinguishing between entities that perform the extraction.

[0306] The exercise therapy providing system 1000 can extract, from the exercise video 300, areas corresponding to predefined (or pre-set) joint points among a plurality of joint points of the patient, as key points P1 and P2. Here, "joint points" may refer to multiple joints of patient U (or a part of patient U's body that includes joints). Furthermore, the term "key point" may refer to an area in the motion video 300 that corresponds to each of a plurality of joint points of the subject U.

[0307] In the present invention, the terms "joint point" and "key point" may be used interchangeably, and the same reference numerals "P1" and "P2" are used to denote the joint point and the key point, respectively. On the other hand, the human body is made up of around 200 bones, and joints are the parts where bones connect, and the human body is made up of multiple joints.

[0308] In the present invention, joint points that are to be key points among a plurality of joint points that make up the human body are designated in advance and may exist as joint point definition information 500. For example, in the joint point definition information 500, a first joint point P1 corresponding to the head center 510 and a second joint point P2 corresponding to the neck center 520 may be defined in advance and exist (see FIG. 18d).

[0309] The exercise therapy provision system 1000 can extract key points P1 and P2 corresponding to joint points from the exercise video 300 based on a posture estimation model 52 trained using a training data set (Set) including position information of predetermined joint points.

[0310] In this case, the exercise therapy provision system 1000 can identify the positions of key points P1 and P2 in the exercise video 300 based on the fact that the position information of each joint point preset by the posture estimation model is extracted in pairs of coordinate information on the x-axis and y-axis.

[0311] Meanwhile, the exercise therapy provision system 1000 can extract (or identify) key points P1 and P2 corresponding to the joint points by either the first key point extraction process or the second key point extraction process based on whether the joint points are visible in the exercise video 300. In the present invention, whether a joint point is visible or not can be understood to mean whether the joint point is visible or not in the motion image 300 .

[0312] The therapeutic exercise providing system 1000 can determine that the joint points are visible in the exercise video 300 if the exercise video 300 includes a part of the subject U's body that corresponds to the joint points.

[0313] When a specific joint point is visible in the exercise video 300, the exercise therapy providing system 1000 can extract key points corresponding to the specific joint point through a first key point extraction process.

[0314] Specifically, the exercise therapy providing system 1000 can identify visible joint points of the subject U that are visible in the exercise video 300 from among a plurality of preset joint points. For example, if a first joint point and a second joint point from among a plurality of preset joint points are visible in the exercise video, the exercise therapy providing system 1000 can identify the first joint point and the second joint point as visible joint points. Additionally, the exercise therapy delivery system 1000 can extract the identified visible joint points as key points.

[0315] In this case, the exercise therapy providing system 1000 may extract position information of areas (or pixels) corresponding to visible joint points from the exercise video, and extract key points corresponding to the visible joint points. For example, the exercise therapy providing system 1000 may extract position information of visible joint points using an object detection algorithm, and extract key points corresponding to the visible joint points.

[0316] In the present invention, the position information of the visible joint points extracted by the first keypoint extraction process can be named and described as "first type information (first type position information)" or "actual position information".

[0317] On the other hand, if the exercise video 300 does not include a part of the subject U's body that corresponds to the joint point, the exercise therapy providing system 1000 can determine that the joint point is not visible in the exercise video 300.

[0318] When a specific joint point is not visible in the exercise video 300, the exercise therapy providing system 1000 can predict and extract a key point corresponding to the specific joint point using the posture estimation model 52 through a second key point extraction process.

[0319] The therapeutic exercise providing system 1000 can predict position information of invisible joint points of the subject U that are not visible in the exercise video 300, among a plurality of preset joint points, based on the posture estimation model 52. In this case, the posture estimation model 52 can predict position information of the invisible joint points based on position information of the visible joint points.

[0320] In the present invention, the position information of the articulation points extracted by the second keypoint identification process may be named and described as "second type information (second type position information)" or "predicted position information".

[0321] The therapeutic exercise provision system 1000 can extract (or identify) key points corresponding to invisible joint points by matching predicted position information of invisible joint points with key points corresponding to invisible joint points.

[0322] In this way, in the present invention, key points P1 and P2 corresponding to the joint points can be extracted (or identified) through different processes based on a posture estimation model that has been trained on the position information of the joint points depending on whether the predefined joint points are visible in the motion video 300. Therefore, in the present invention, invisible joint points that cannot be seen in the motion video can also be analyzed.

[0323] Meanwhile, the exercise therapy providing system 1000 can extract key points P1 and P2 from the exercise video in real time in conjunction with the exercise video being captured on the patient terminal 10. In addition, the exercise therapy providing system 1000 can provide the extracted key points P1 and P2 on the patient terminal 10 in real time so that the patient can intuitively recognize the joint points where the exercise motion is to be analyzed.

[0324] 16(b) and 16(c), the therapeutic exercise providing system 1000 can output the exercise video 300 on the patient terminal 10 in real time in conjunction with the exercise video 300 being captured by the patient terminal 10. In addition, the therapeutic exercise providing system 1000 can provide graphic objects corresponding to the extracted key points P1 and P2 by overlapping them in a region of the subject U corresponding to a predetermined joint point.

[0325] The data processing for overlaying the key point graphic objects on the exercise video 300 may be performed by the video processor 130 of the exercise therapy application 100. The video processor 130 may render each of the graphic objects corresponding to the extracted key points P1 and P2 on the area of ​​the subject U corresponding to the joint points P1 and P2 matched to the key points P1 and P2.

[0326] Furthermore, when the positions of preset joint points are changed as the patient performs an exercise, the image processor 130 may provide key point graphic objects by overlaying them on areas of the subject U corresponding to the changed joint points. That is, the image processor 130 may overlay key point graphic objects on areas corresponding to the joint points in the exercise image so that the positions of the joint points, which are changed in real time, are reflected.

[0327] Meanwhile, in the present invention, a process of analyzing the relative positional relationship between key points from key points extracted through a posture estimation model trained using training data related to joint points, and analyzing the patient's exercise motion for the prescribed exercise based on the analysis of the positional relationship can be performed (S350, see FIG. 13). The analysis of the relative position between key points can be performed by the motion analysis unit 120, 210. In particular, the exercise motion can be analyzed by one of the artificial intelligence motion analysis unit 122, 212 and the rule-based motion analysis unit 123, 213 of the motion analysis unit.

[0328] 16(d), the therapeutic exercise application 100 can guide the patient through the exercise / motion analysis by providing guidance information (e.g., "Calculating result values" or "Providing Kim Cheol-soo's exercise / motion analysis results") that guides the patient through the analysis of the exercise / motion on the patient terminal 10. The patient exercise / motion analysis method will be described in detail below.

[0329] The exercise therapy provision system 1000 can analyze the relative positional relationship between key points P1 and P2 corresponding to each of a plurality of pre-set joint points using key points extracted from a posture estimation model trained using training data.

[0330] The exercise therapy delivery system 1000 can analyze the relative positions between key points P1 and P2 corresponding to each of a plurality of pre-set joint points using both key points corresponding to visible joint points and key points corresponding to invisible joint points.

[0331] Here, the "relative position between keypoints" can be understood as the position of another keypoint (e.g., a second keypoint, "P2") relative to a specific keypoint (e.g., a first keypoint, "P1") between at least two keypoints P1 and P2.

[0332] In the following, for convenience of explanation, key points corresponding to visible joint points will be referred to as "first type key points" and key points corresponding to invisible joint points will be referred to as "second type key points."

[0333] The exercise therapy delivery system 1000 can perform analysis on at least one of i) the relative positional relationship between a plurality of first type key points, ii) the relative positional relationship between the first type key points and the second type key points, and iii) the relative positional relationship between a plurality of second type key points.

[0334] In this case, the exercise therapy providing system 1000 can analyze the relative positional relationship between some of the associated key points among the plurality of joint points based on the type of prescribed exercise performed by the patient.

[0335] For example, when a patient performs a prescribed exercise according to a first type of exercise, the exercise therapy provision system 1000 can analyze the relative positional relationship between key points corresponding to a first joint point and a second joint point among a plurality of joint points.

[0336] As another example, when a patient performs a prescribed exercise according to a second type of exercise different from the first type of exercise, the exercise therapy delivery system 1000 may analyze the relative positional relationship between key points corresponding to the first joint point and the third joint point among the plurality of joint points, and the relative positional relationship may be used for motion analysis.

[0337] The results of the motion analysis performed by the exercise therapy delivery system 1000 according to the present invention can be very diverse. For example, the exercise therapy delivery system 1000 can analyze at least one of the range of motion of a joint, the distance of motion, the speed (or acceleration) of joint movement, and the body balance, body equilibrium, and body alignment (e.g., leg alignment, spinal alignment, etc.) of a subject (corresponding to a patient) included in the exercise video to be analyzed from the extracted key points or video. Meanwhile, the exercise therapy delivery system 1000 according to the present invention can analyze the relative positional relationship between key points based on rule information regarding prescribed exercises. Here, the rule information can be understood as information in which rules are defined in advance for analyzing the relative positional relationship between key points. The exercise therapy delivery system 1000 can analyze the exercise motion of the patient by determining whether the relative positional relationship between the key points satisfies the rule information.

[0338] A method for analyzing a joint range of motion based on the relative positional relationship of key points and rule information will be described below as an example. However, the content described below is merely one embodiment for analyzing a patient's movement based on the relative positional relationship of key points and rule information, and various patient movements can be analyzed based on the relative positional relationship of key points and rule information in the present invention.

[0339] The range of joint motion analyzed by the therapeutic exercise provision system 1000 according to the present invention will be considered in more detail. The therapeutic exercise provision system 1000 can analyze the range of joint motion of a patient according to the relative positional relationship between key points based on rule information for the reference range of joint motion related to the prescribed exercise.

[0340] Furthermore, the exercise therapy delivery system 1000 can analyze the relative positional relationship between the key points based on rule information regarding prescribed exercise. Also, the exercise therapy delivery system 1000 can analyze the exercise motion of the patient by determining whether the relative positional relationship between the key points satisfies the rule information.

[0341] The exercise therapy delivery system 1000 can extract the relative positional relationship between associated key points matched to a specific prescribed movement from multiple consecutive frames related to the specific prescribed movement, and use the extracted relative positional relationship to obtain (or calculate) the patient's joint range of motion for the specific prescribed movement.

[0342] Specifically, assume that the motion video consists of a plurality of frames having a first type corresponding to a first prescribed motion, and a plurality of frames having a second type corresponding to a second prescribed motion.

[0343] When a patient's exercise motion analysis is performed for the first prescribed exercise among the first prescribed exercise and the second prescribed exercise, the exercise therapy provision system 1000 can analyze the patient's exercise motion using key points extracted from a plurality of frames having a first type.

[0344] Meanwhile, when a patient's exercise motion analysis is performed for the second prescribed exercise, the exercise therapy delivery system 1000 can analyze the patient's exercise motion using key points extracted from a plurality of frames having a second type.

[0345] That is, the exercise therapy delivery system 1000 can analyze the key point positional relationship for a series of movements (or postures) and obtain (or calculate) the patient's range of motion for a specific prescribed exercise.

[0346] In the following, for ease of explanation, consecutive frames (i.e., frames of a first type) corresponding to a particular prescribed motion (e.g., a first prescribed motion) will be referred to as the "first analyzed frame" and the "second analyzed frame" depending on the time before and after the frames are formed.

[0347] Here, the first frame to be analyzed can be understood as a frame formed before in time, and the second frame to be analyzed can be understood as a frame formed after in time. The exercise therapy delivery system 1000 can extract key points in each of the first and second frames under analysis.

[0348] A first analysis target keypoint group corresponding to each of the plurality of joint points can be extracted from the first analysis target frame, and a second analysis target keypoint group corresponding to each of the plurality of joint points can be extracted from the second analysis target frame.

[0349] The exercise treatment provision system 1000 can analyze a "first positional relationship" between key points included in a first analysis target key point group to perform a first motion analysis of the subject U included in the first analysis target frame. In addition, the exercise treatment provision system 1000 can analyze a "second positional relationship" between key points included in a second analysis target key point group to perform a second motion analysis of the subject U included in the second analysis target frame.

[0350] The exercise therapy delivery system 1000 can obtain (extract or calculate) the range of motion of the patient's joint for a specific prescribed exercise based on the first key point positional relationship and the second key point positional relationship.

[0351] In this case, the exercise therapy provision system 1000 can obtain the range of motion of the patient's joints by referring to the user DB30 and taking into consideration at least one of the patient's age information, gender information, height information, weight information, surgical history information, and musculoskeletal disease information.

[0352] Meanwhile, the exercise therapy providing system 1000 can determine whether the acquired range of motion of the patient satisfies the reference joint range of motion corresponding to the rule information for a specific prescribed exercise. In the present invention, the rule-based analysis of the range of motion of the patient may be performed by the rule-based motion analysis unit 213 of the artificial intelligence server 200 (see FIG. 11 ), but is not limited to the analysis by the rule-based motion analysis unit 213.

[0353] In the present invention, rule information for the reference joint range of motion may exist for each of a plurality of exercise types. Such rule information may include information on the reference joint range of motion that differs from one another for each age, gender, height, weight, and musculoskeletal disorder.

[0354] The exercise therapy provision system 1000 can compare the patient's joint range of motion for a specific prescribed exercise with the reference joint range of motion for the specific prescribed exercise included in the rule information to determine whether the patient's joint range of motion satisfies the reference joint range of motion.

[0355] Based on the judgment result, the exercise treatment provision system 1000 can provide the analysis result of the patient's exercise motion on the patient terminal 10 as feedback for the prescribed exercise. Meanwhile, in the present invention, a process of transmitting the analysis result of the patient's exercise motion to the patient terminal can be performed (S360, see FIG. 13).

[0356] The exercise therapy delivery system 1000 can provide the motion analysis results in various ways so that the patient can intuitively recognize the analysis results of the exercise motion and increase the patient's compliance with the exercise.

[0357] The exercise therapy providing system 1000 can provide graphic objects corresponding to key points P1 and P2 superimposed on the exercise video 300 in real time while the exercise video 300 is being captured by the patient terminal 10 (see FIG. 16). In this case, the therapeutic exercise provision system 1000 can arrange the patient's joint range of motion information around key points P1 and P2 related to the joint range of motion.

[0358] Furthermore, the exercise therapy provision system 1000 can provide key point graphic objects (or graphic objects corresponding to the positional relationships between key points) having different visual appearances superimposed on the exercise video so that the patient can recognize whether the patient's joint range of motion satisfies the reference joint range of motion.

[0359] Furthermore, the visual appearance of the graphic object superimposed on the motion image may be configured to differ depending on whether the relative positional relationship between the extracted key points satisfies the rule information.

[0360] For example, if the patient's joint range of motion satisfies the reference joint range of motion, a graphic object A having a first visual appearance may be superimposed on the exercise video 300. On the other hand, if the patient's joint range of motion does not satisfy the reference joint range of motion, a graphic object B having a second visual appearance different from the first visual appearance may be superimposed on the exercise video 300.

[0361] Furthermore, the exercise therapy provision system 1000 can provide the patient's evaluation score for the prescribed exercise (e.g., "Kim Woo-young's squat posture is 70 points") as a motion analysis result based on key points extracted from each of the multiple frames that make up the exercise video 300.

[0362] Meanwhile, in the present invention, the therapeutic exercise application 100 and the artificial intelligence server 200 installed in the patient terminal 10 can each analyze the exercise and motion and generate the exercise and motion analysis result.

[0363] For example, the exercise therapy application 100 may overlay graphic objects corresponding to the key points P1 and P2 on the exercise video in real time to generate the first analysis result.

[0364] As another example, the artificial intelligence server 200, which is a cloud server, can generate a patient's evaluation score for the prescribed exercise as a second analysis result based on key points extracted from each of the multiple frames that make up the exercise video.

[0365] The exercise therapy provision system 1000 can provide analysis results of the patient's exercise movements, including the first analysis result generated by the exercise therapy application 100 and the second analysis result generated by the artificial intelligence server 200, on the patient terminal 10.

[0366] Meanwhile, the exercise treatment providing system 1000 can transmit the patient's exercise motion analysis results to the doctor terminal 20. The doctor terminal 20 may be provided with both the first analysis result and the second analysis result.

[0367] In this way, the present invention provides various user environments related to the provision of analysis results so that the patient can intuitively recognize the analysis results of their exercise movements. Other embodiments related to the provision of analysis results will be described later.

[0368] 17, the present invention is directed to analyzing the exercise movements of a patient U included in the exercise video 300 based on the exercise video 300 received from the patient terminal 10, and providing the analysis results. In particular, the present invention relates to a method for processing a learning data set centered on important joint points and learning the data set in order to analyze the exercise movements of a patient based on artificial intelligence. The training data used to train the posture estimation model of the present invention will be specifically described below.

[0369] 17, database 40 is a storage in which a learning data set is stored, and may be provided in exercise therapy providing system 1000 according to the present invention itself, or may be formed as an external storage (or external DB). Database 40 according to the present invention can be understood as having no physical space restrictions as long as it is a space in which a learning data set is stored. The system may be configured to include at least one of the components of the database 40, the posture estimation server 50, and the exercise therapy providing system 1000. Database 40 may store training data for training pose estimation model 52 as a training data set.

[0370] 18b, the training data set 400 of the present invention may be composed of a plurality of data groups 410-450 corresponding to different information attributes 410a-450a, respectively. The information included in each of the plurality of data groups 410-450 may be extracted from an exercise video 300 including a subject U performing an exercise action.

[0371] Here, the "exercise video 300" is a video (image or video) that captures (includes) the process of the user performing an exercise, as shown in FIG. 18a, and may include at least a part of the user U's body.

[0372] In the present invention, a user object included in the exercise video 300 is referred to as a "subject U" in the following description. The "subject U" in the present invention may refer to the user exercising in the exercise video or a part of the user's body. Therefore, in the present invention, the terms "subject" and "user" may be used interchangeably and are described with the same reference numeral "U." Meanwhile, the "exercise video 300" described in the present invention may include an "analysis target exercise video" and a "learning target exercise video."

[0373] The "motion video to be analyzed" can be understood as a motion video that is the target of posture estimation analysis of the subject U, and the "motion video to be learned" can be understood as a motion video that is the target of machine learning for a posture estimation model. Here, posture estimation analysis can mean extracting key points from the video.

[0374] The learning unit 51 may be configured to perform learning for the posture estimation model based on the training object exercise video 300. The learning unit 51 can use the learning data to train the posture estimation model.

[0375] As shown in (a) of FIG. 18b, the learning unit 51 can detect a subject U from the training object exercise video 300 and extract various learning data to be used for exercise posture estimation from the detected subject U. Such learning data may be referred to interchangeably as "information," "data," "data value," or "data value." Meanwhile, extraction of learning data may be performed by other means instead of the learning unit 51.

[0376] The learning unit 51 can use various object detection algorithms to detect the subject U from the training target exercise video 300. For example, the learning unit 51 can use an algorithm (Weighted Box Fusion, WBF) that ensembles multiple bounding boxes. However, it goes without saying that the learning unit 51 is not limited to the above-mentioned object detection algorithms, and can use various object detection algorithms that can detect an object corresponding to the subject U from the training target exercise video 300.

[0377] The learning unit 51 can classify the extracted learning data into any one of a plurality of data groups 410 to 450 corresponding to each of a plurality of different information attributes 410a to 450a.

[0378] The plurality of mutually different information attributes 410a to 450a described in the present invention may be predefined and exist as shown in (b) of Fig. 18b. Furthermore, the plurality of data groups 410 to 450 corresponding to the plurality of information attributes 410a to 450a, respectively, may include learning data corresponding to the predefined information attributes.

[0379] For example, i) the data group 410 corresponding to the first information attribute 410a may include joint point position information of the subject U, ii) the data group 420 corresponding to the second information attribute 420a may include information indicating whether the joint points of the subject U are visible, iii) the data group 430 corresponding to the third information attribute 430a may include information regarding the shooting direction of the subject U, iv) the data group 440 corresponding to the fourth information attribute 440a may include exercise code information that classifies the exercise action (or type of exercise) performed by the subject U, and v) the data group 450 corresponding to the fifth information attribute 450a may include the size and center position information of a bounding box for the subject U. Here, the "joint points P1, P2" may refer to the user's joints or a region corresponding to the joints of the subject U in the motion image 300.

[0380] The learning unit 51 can link the multiple data groups 410-450 extracted from the training object exercise video 300 to each other, and generate (construct) a data set for the training object exercise video 300. The learning unit 51 can also store the generated training data set 400 in the database 40. The database 40 can be constructed as the database 40 for the posture estimation model 52 based on the storage of the training data set 400 generated by the learning unit 51.

[0381] Furthermore, the learning unit 51 can perform learning for the pose estimation model 52 based on a learning dataset 400 stored in the database 40. As described above, the learning dataset 400 may include position information of joint points.

[0382] The posture estimation model 52 is a posture estimation model trained using a training data set including position information of joint points, and is capable of estimating the motion posture of the subject U from the motion video to be analyzed.

[0383] Meanwhile, the posture estimation model 52 uses the learning dataset 400 generated by the learning unit 51 to extract key points corresponding to the joint points of the subject from the exercise video 300, and at least one of the artificial intelligence motion analysis units 122, 212 and the rule-based motion analysis units 123, 213 can analyze the exercise movements of the subject in the exercise video 300 using the extracted key points.

[0384] There may be various motion postures of the subject U that can be estimated from the analysis target motion video 300 using the key points estimated from the posture estimation model 52. For example, at least one of the artificial intelligence motion analysis units 122 and 212 and the rule-based motion analysis units 123 and 213 may estimate and analyze information regarding at least one of i) positions of joint points, ii) ranges of joint motion of the joint points, iii) movement paths of the joint points, iv) connection relationships between the joint points, and v) symmetry relationships between the joint points for the subject U.

[0385] In addition, the artificial intelligence motion analysis unit 122, 212 can analyze at least one of the joint movement distance, joint movement speed (or acceleration), body balance, body equilibrium, and body alignment (e.g., leg alignment, spinal alignment, etc.) of the subject (corresponding to the patient) included in the movement video 300 to be analyzed from the key points extracted from the movement video 300 to be analyzed or from the video 300.

[0386] In the present invention, posture estimation model 52 may be configured to include learning unit 51. Conversely, learning unit 51 may include posture estimation model 52, in which case posture estimation function can be achieved by having posture estimation model 52 learn in learning unit 51. Therefore, in the present invention, the functions performed by posture estimation model 52 can be described interchangeably with those performed by learning unit 51.

[0387] On the other hand, the user terminals 10, 20 may be configured to provide a posture analysis result service that provides the user terminals 10, 20 with a user's movement analysis result (or movement analysis report) that is analyzed based on key points extracted and estimated from the posture estimation model 52 (see FIG. 11). Here, the user terminals 10, 20 may be at least one of a patient terminal 10, a doctor terminal 20, and a third party terminal.

[0388] Such an exercise therapy provision system 1000 may be configured to communicate with user terminals 10 and 20. In the present invention, the communication of the exercise therapy provision system 1000 can also be understood as being performed by a communication unit of the exercise therapy provision system 1000.

[0389] For example, the communication unit of the exercise therapy provision system 1000 may be configured to support any of WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Wi-Fi (Wireless Fidelity) Direct, DLNA (Digital Living Network Alliance: registered trademark), WiBro (Wireless Broadband), WiMAX (World Interoperability for Microwave Access), HSDPA (High Speed ​​Downlink Packet Access), HSUPA (High Speed ​​Uplink Packet Access), LTE (Long Term Evolution), LTE-A (Long Term Evolution-Advanced), 5G (5th Generation Mobile Telecommunication), Bluetooth (Bluetooth TM The device may be configured to communicate with the user terminals 10, 20 using at least one of the following technologies: WiFi (registered trademark), RFID (Radio Frequency Identification), Infrared Data Association (IrDA), UWB (Ultra-Wideband), ZigBee, NFC (Near Field Communication), Wi-Fi Direct, and Wireless Universal Serial Bus (Wireless USB).

[0390] Meanwhile, the user terminals 10 and 20 described in the present invention refer to electronic devices and may include at least one of a smartphone, a mobile phone, a tablet PC, a kiosk, a computer, a laptop, a digital broadcasting terminal, a PDA (Personal Digital Assistant), and a PMP (Portable Multimedia Player). Furthermore, the user terminals 10 and 20 may be electronic devices to which a user account is logged in, connected, or registered.

[0391] Here, the user account may refer to an account that is registered in advance in the exercise treatment providing system 1000 according to the present invention. Such a user account may be understood as a user ID (identification, identification number).

[0392] Meanwhile, the present invention can perform a process of receiving exercise video from the user terminals 10 and 20. The exercise treatment providing system 1000 can receive exercise video 300, which is a video of a user performing exercise movements, through communication with the user terminals 10 and 20.

[0393] In this case, the exercise video 300 received by the exercise treatment providing system 1000 from the user terminals 10 and 20 can be understood as an exercise video to be analyzed, which is to be used to analyze the exercise motion of the user. The exercise treatment providing system 1000 can receive exercise videos to be analyzed from the user terminals 10 and 20 according to various time points and routes.

[0394] 11, the exercise therapy providing system 1000 can control the camera state to an activated state so that the camera 201 provided in the user terminal 10, 20 captures an exercise video to be analyzed based on the selection of a graphic object corresponding to "start exercise" from the user terminal 10, 20. In addition, the exercise therapy providing system 1000 can receive the exercise video to be analyzed captured by the camera 201 from the user terminal 10, 20 in real time or based on the completion of the user's exercise.

[0395] Next, in the present invention, a process of analyzing a movement associated with a specific movement of a user included in a movement video can be performed based on key points extracted from a posture estimation model trained using a training data set including position information of joint points.

[0396] When receiving the exercise video to be analyzed from the user terminal 10, 20, the learning unit 51 can extract key points corresponding to the joint points of the user U included in the exercise video to be analyzed based on the posture estimation model 52 learned using the exercise video to be analyzed 300. In addition, at least one of the artificial intelligence action analysis units 122, 212 and the rule-based action analysis units 123, 213 can analyze the exercise movements of the subject in the exercise video 300 using the extracted key points.

[0397] The posture estimation information of the user U estimated by the learning unit 51 may include various information. For example, the learning unit 51 can estimate i) position information of the joint points P1 and P2 of the subject U, and ii) joint movable range information (angle information) of the subject U.

[0398] Next, in the present invention, based on the completion of the analysis, a process of providing the user U's exercise motion analysis results related to a specific exercise motion to the user terminal 10, 20 can be performed.

[0399] The exercise treatment providing system 1000 can process the analysis results of the user's exercise motion to generate an exercise motion analysis report. The exercise treatment providing system 1000 can also provide the exercise motion analysis report on the user terminals 10 and 20.

[0400] 11, the therapeutic exercise provision system 1000 can provide by rendering joint point graphic objects corresponding to the joint points P1 and P2 of the user U at positions corresponding to the joint points P1 and P2 of the user U in the exercise video of the user. In addition, the therapeutic exercise provision system 1000 can display joint motion range information 221 of a specific joint point P1 around the specific joint point P1.

[0401] In this way, the exercise therapy providing system 1000 according to the present invention can perform learning for the posture estimation model 52 using the database 40 constructed based on the training object exercise video 300. In addition, the posture estimation model 52 can be used to estimate the user's exercise posture and provide an exercise motion analysis result service based on the estimated posture.

[0402] The analysis results may include a variety of information. For example, the analysis results may include analysis information on at least one of the range of motion of a joint, the distance of motion, the speed (or acceleration) of joint movement, the body balance, body equilibrium, and body alignment (e.g., leg alignment, spinal alignment, etc.) of a subject (corresponding to a patient) included in the movement video to be analyzed, analyzed from the extracted key points or video.

[0403] Furthermore, such analytical information may further include a score, which may be an analysis score of the user's exercise movement (or posture). Such an analysis score may be calculated based on various methods (e.g., rule-based analysis based on preset criteria or analysis using an artificial intelligence algorithm). The database 40 may store and exist a training data set 400 extracted and generated from the training object exercise video 300 by the training unit 51. The learning data set 400 used for estimating the user's exercise posture will be described in more detail below. As shown in FIG. 18 a, the training data set 400 may be configured to include data related to a subject U extracted from the training exercise video 300. The learning unit 51 can extract data for the subject U from the training object exercise video 300 to form a training data set 400.

[0404] Such a training dataset 400 may be made up of multiple sub-datasets 401 to 403. In the present invention, the training dataset 400 can be understood as a higher-level concept, and the sub-datasets 401 to 403 can be understood as datasets corresponding to lower-level concepts.

[0405] The learning unit 51 may extract data for the subject U from each of the reference frames 301 to 306 selected based on a preset criterion from among the multiple frames constituting the training object exercise video 300, and construct sub-data sets 401 to 403.

[0406] The learning unit 51 can select the reference frames 301 to 306 based on various criteria. The training exercise video 300 may be a moving image or a plurality of still images.

[0407] When the training object exercise video 300 is a video, the learning unit 51 may select reference frames 301 to 306 from among the multiple frames constituting the training object exercise video 300, based on a certain time interval T. As another example, when the amount of change in the motion of the subject included in the previous and next frames corresponds to a certain amount of change or more, the learning unit 51 may select the previous and next frames as the reference frames 301 to 306.

[0408] The training data included in the training dataset according to the present invention may be composed of training data extracted from each of reference frames selected based on a predetermined criterion from among a plurality of frames constituting a training motion video, with the subject included in the training motion video as the center.

[0409] For convenience of explanation, the following description will be based on the "training dataset 400" without distinguishing between the "training dataset 400" and the "sub-datasets 401 to 403." The information included in the training dataset 400 described below may be information included in the sub-datasets 401 to 403. In this case, the training dataset 400 according to the present invention can be understood as including multiple sub-datasets 401 to 403 each containing the information described below.

[0410] On the other hand, as shown in FIG. 18b(a), the learning data set 400 may be made up of a plurality of data groups 410 to 460 corresponding to a plurality of different information attributes, respectively.

[0411] The learning unit 51 can extract data corresponding to each of multiple information attributes from the training object exercise video, and classify (or match) the extracted data having the same information attribute into the same data group to generate a learning dataset 400.

[0412] Here, the information attributes 410a to 450a can be understood as criteria for distinguishing the types of information required for estimating the exercise posture of the subject U from the training exercise video 300. As shown in (b) of Fig. 18b, in the present invention, a plurality of different information attributes (first to fifth information attributes 410a to 450a) may be predefined and exist.

[0413] The learning unit 51 can extract learning data corresponding to each of the plurality of information attributes 410a to 450a from the training object exercise video, and classify the learning data corresponding to the same information attribute into the same data group to generate the learning data set 400.

[0414] Furthermore, the learning unit 51 can identify the association between each of the plurality of data groups 410 to 460 based on the association between the plurality of information attributes 410a to 450a, and perform learning on the learning data set 400 and the association between each of the groups. The following specifically describes the multiple data groups and the relationships between each group.

[0415] As shown in FIG. 18c, a first data group 410 among the plurality of data groups 410 to 450 may include position information 411 and 412 for joint points P1 and P2 of a subject U included in the exercise video 300.

[0416] As shown in (a) of Fig. 18c, the joint points P1 and P2 in the present invention may refer to an area of ​​the subject U corresponding to the user's joints in the training exercise video 300. Also, as shown in (b) of Fig. 18c, the position information 411 and 412 of the joint points may be understood as the positions of the areas in the training exercise video 300 where the joint points P1 and P2 are located. On the other hand, the human body is made up of around 200 bones, and joints are the parts where bones connect, and the human body is made up of multiple joints.

[0417] The learning unit 51 may have predefined joint points to be learned among the plurality of joint points of the subject U. That is, the "joint points to be learned" described in the present invention may be understood as joint points predefined for learning in the present invention among the plurality of joint points of the user.

[0418] 18d, in the database 40, among the plurality of joint points, training target joint points to be used as training targets for a pose estimation model may be specified in advance and may exist as reference information 500. Furthermore, the reference information 500 may exist with a predefined order of the plurality of training target joint points.

[0419] The first training joint point can be defined as the center of the head. More specifically, the first training joint point can be understood as a point that is analogous (predicted or corresponds) to the first cervical vertebra level.

[0420] The second training joint point can be defined as the center of the neck. More specifically, the second training joint point is the C3-C4 level, which is the center of the neck lordotic curve, and can be understood as the midpoint between the first and third levels when viewed from the front.

[0421] The third training joint point can be defined as the lower end of the neck. More specifically, the third training joint point is the C7-T1 level, which can be understood as the center point of the line connecting both clavicle levels.

[0422] The fourth training joint point may be defined as the shoulder center. More specifically, the fourth training joint point may be the humerus head center, which may be understood as a position corresponding to the center of rotation in a continuous rotational movement in which the arm is abducted to a position that is the central axis of the shoulder joint rotational movement. In an image that does not include a continuous rotational movement, a point corresponding to predicted position information of the shoulder center may correspond to the fourth training joint point. In addition, the fourth training joint point may exist at each of the left and right shoulder centers.

[0423] The fifth training joint point can be defined as the elbow center. More specifically, the fifth training joint point corresponds to the humerus medial-lateral epicondyle center and can be understood as the central point at the elbow level. The fifth training joint point can exist at either the left elbow center or the right elbow center.

[0424] The sixth training joint point can be defined as the wrist center. More specifically, the sixth training joint point is the radius-ulnar styloid process center, which can be understood as a central point at the wrist level. The sixth training joint point can exist at each of the left wrist center and the right wrist center.

[0425] The seventh training joint point can be defined as the hand center. More specifically, the seventh training joint point can be understood to correspond to the third metacarpal head, and can exist at both the left hand center and the right hand center.

[0426] The eighth training joint point may be defined as the hip joint center (femoral head center). More specifically, the eighth training joint point may be understood as the position of the central axis of the hip joint rotational movement, and as the position corresponding to the rotation center of a continuous movement in a rotational movement of abducting the leg. In an image that does not show a continuous rotational movement, a point corresponding to predicted position information of the hip joint center may be understood as the eighth training joint point. The eighth training joint point may exist at the left hip joint center and the right hip joint center.

[0427] The ninth training joint point can be understood as the knee center. More specifically, the ninth training joint point is the femoral medial-lateral epicondyle center, which can be understood as the central point at knee level. The ninth training joint point can exist at either the left knee center or the right knee center.

[0428] The tenth training joint point can be defined as the ankle center. More specifically, the tenth training joint point can be understood as the midpoint between the medial and lateral malleolus at ankle level. The tenth training joint point can be located at the left ankle center and the right ankle center, respectively.

[0429] The eleventh training joint point may be defined as the foot center. More specifically, the eleventh training joint point corresponds to the second metatarsal head and may be located at the left foot center and the right foot center.

[0430] The 12th training joint point can be defined as the heel. More specifically, the 12th training joint point can be located on each of the left and right heels at the level where the heels contact the floor. The 12th training joint point may not be visible when the subject U is standing completely forward in the image, but may become visible if the foot is twisted even slightly.

[0431] The 13th joint point to be learned can be defined as the beginning of the lumbar curve (SUP. END OF LORDOSIS). More specifically, the 13th joint point to be learned can be understood as the midpoint between the average level of the fourth and eighth spine on both sides, at the level of the xiphoid process of the sternum, approximately 8-10T spine.

[0432] The 14th training joint point can be defined as the center of lordosis. More specifically, the 14th training joint point is located at the level of approximately L2-4 of the spine, and can be understood as the midpoint between the 13th level and the average level of the 8th level on both sides.

[0433] The 15th training joint point can be defined as the end of the lumbar curve (INF. END OF LORDOSIS). More specifically, the 15th training joint point is at the level of approximately S1-2 spine, and can be understood as the midpoint between the 14th level and the average level of the 8th level on both sides.

[0434] Meanwhile, the first learning joint point P1 may be defined as the head center 510, and the second learning joint point P2 may be defined as the neck center 520. A first order having the highest priority may be defined for the first learning joint point P1, and a second order having a lower priority may be defined for the second learning joint point P2.

[0435] In this case, the order of the training joint points present corresponding to the left and right sides of the subject U may be such that the training joint point corresponding to the first side (e.g., left side) of the body has higher priority than the training joint point corresponding to the second side (e.g., right side) of the body. For example, a matching order may be defined in which the training joint point P3 corresponding to the left wrist center 530 has higher priority than the training joint point P4 corresponding to the right shoulder center 540.

[0436] The learning unit 51 can extract coordinate information as position information 411, 412 of each of a plurality of training target joint points P1, P2 designated in advance from the training target exercise video 300.

[0437] The coordinate information may include at least one of two-dimensional or three-dimensional coordinates. When two-dimensional coordinate information is extracted, the learning unit 120 can extract x- and y-axis coordinate information of each of the plurality of learning target joint points P1 and P2 from the learning target exercise video 300. In contrast, when two-dimensional coordinate information is extracted, the learning unit 120 can extract x-, y-, and z-axis coordinate information of each of the plurality of learning target joint points P1 and P2 from the learning target exercise video 300.

[0438] Coordinate information can be extracted by various methods. In particular, z-axis coordinate information can be extracted by a camera (e.g., an RGB camera) or various types of sensors (e.g., a distance measurement sensor). Furthermore, z-axis coordinate information can be extracted from the learning target image 300 through various types of artificial intelligence algorithms. When z-axis coordinate information is extracted through an artificial intelligence algorithm, it can be expressed as being "estimated" or "predicted."

[0439] On the other hand, the learning unit 51 classifies the position information 411, 412 of each of the multiple training target joint points P1, P2 into a first data group 410 based on the correspondence of the position information 411, 412 to the first information attribute 410a, and generates the first data group 410, and can generate a learning dataset 400 including the first data group 410.

[0440] Considering an example in which two-dimensional coordinate information (x, y coordinate information) is extracted, the learning unit 121 can extract position information 411, 412 of multiple training target joint points P1, P2, respectively, in the form of pairs of x-axis and y-axis coordinate information. The learning unit 51 can extract position information "[599, 463]" of the first training target joint point P1 and extract position information "[586, 545]" of the second training target joint point P2. In addition, the learning unit 51 can generate a training data set 400 configured from a first data group 410 including the "[599, 463]" and "[586, 545]".

[0441] The learning unit 51 can learn to estimate the positions of the joint points P1 and P2 of the subject U included in the training object exercise video 300 based on the position information 411 and 412 of the training object joint points P1 and P2 that constitute the first data group 410.

[0442] On the other hand, as shown in (b) of FIG. 18c, the learning unit 51 can configure (generate) a learning dataset 400 by sequentially arranging the position information 411, 412 of the multiple learning target joint points P1, P2 in a first data group 410 based on a predefined order between the multiple learning target joint points P1, P2. As described above, the database 40 may contain a predefined order of a plurality of training target joint points P1 and P2.

[0443] The learning unit 51 can refer to the database 40 and arrange the position information 411, 412 of the multiple training target joint points P1, P2 in the first data group 410 in the order corresponding to the training target joint points P1, P2, to generate the training data set 400. Furthermore, such training data set 400 can be stored in the database 40, and the database 40 for pose estimation can be constructed.

[0444] Specifically, as shown in (b) of FIG. 18c, the learning unit 51 can prioritize arranging the first position information 411 of the first learning target joint point P1 corresponding to the first order within the first data group 410, and arranging the second position information 412 of the second learning target joint point P2 corresponding to the second order following the first position information 411.

[0445] On the other hand, the learning unit 51 can extract (or identify) the position information 411, 412 of the learning target joint points P1, P2 by either the first process or the second process based on whether the learning target joint points P1, P2 are visible in the exercise video 300.

[0446] In the present invention, whether the training target joint points are visible or not can be understood to mean whether the training target joint points P1 and P2 are visible or not in the training target motion video 300.

[0447] In the present invention, visible joint points in the training motion video can be named "training target visible joint points," and invisible joint points in the training target motion video can be named "training target invisible joint points."

[0448] If the training object motion video 300 includes parts of the subject U's body corresponding to the training object joint points P1 and P2, the training unit 51 can determine that the training object joint points are visible in the training object motion video 300.

[0449] Based on the fact that the learning target joint points P1 and P2 are visible in the learning target exercise video 300, the learning unit 51 can extract position information of the actual positions where the learning target joint points P1 and P2 are located from the learning target exercise video 300 through the first process.

[0450] In the present invention, the position information of the learning joint points P1 and P2 extracted by the first process can be named and explained as "first type information (first type position information)" or "actual position information."

[0451] On the other hand, if the exercise video 300 does not include parts of the subject U's body corresponding to the learning joint points P1 and P2, the learning unit 51 can determine that the learning joint points P1 and P2 are not visible in the learning exercise video 300.

[0452] Based on the fact that the learning target joint points P1 and P2 are not visible in the exercise video 300, the learning unit 51 can predict the expected positions of the learning target joint points P1 and P2 through the second process and extract (or identify) the predicted position information.

[0453] In the present invention, the position information of the learning target joint points P1 and P2 extracted by the second process can be named and explained as "second type information (second type position information)" or "predicted position information."

[0454] In this manner, in the present invention, the plurality of position information 411, 412 included in the first data group 410 can be defined to have different extraction processes and type information depending on whether the plurality of training target joint points P1, P2 are visible in the training target exercise video 300. On the other hand, the second process may include various data processing steps for extracting (identifying) predicted position information of the training target joint points P1 and P2 that are not visible in the exercise video 300.

[0455] For example, the learning unit 51 that extracts predicted position information through the second process can predict predicted position information of the training target joint points P1 and P2 that are not visible in the exercise video 300 based on the actual position information of the training target joint points that are visible in the exercise video 300.

[0456] In this case, the learning unit 51 can identify predicted position information by assigning weights to the multiple learning target joint points P1 and P2 that are visible in the exercise video 300 based on their relevance to the learning target joint points P1 and P2 that are not visible in the exercise video 300.

[0457] For example, the closer the orders corresponding to the learning target joint points P1 and P2 are, the higher the relevance between the learning target joint points may be set. Regarding the relevance between the learning target joint points corresponding to the third order, the learning target joint point corresponding to the second order may be set higher than the learning target joint point corresponding to the first order.

[0458] As another example, the correlation between the learning target joint points P1 and P2 may be set to be highest between the learning target joint points P1 and P2 that exist corresponding to the left and right sides of the subject U. For example, the learning target joint point P3 corresponding to the center of the right wrist may be set to be highest in correlation with the learning target joint point P3 corresponding to the center of the left wrist (see (a) of FIG. 18c).

[0459] Furthermore, the learning unit 51 can extract predicted position information of the learning target joint points P1 and P2 that are not visible in the exercise video 300 based on motion information of the exercise action performed by the subject U in the exercise video 300. The database 40 may store motion information including the path of movement (e.g., the position and direction of movement) of the body (or joint points) during exercise.

[0460] The learning unit 51 can identify predicted position information of the training target joints that are not visible in the exercise video 300 by referring to the position information of the training target joint points P1 and P2 that are visible in the exercise video 300 and the motion information in the database 40.

[0461] Meanwhile, as shown in FIG. 18c, the second data group 420 among the plurality of data groups 410 to 450 may be composed of data values ​​421 and 422 indicating whether the learning target joint points P1 and P2 of the subject U included in the exercise video 300 are visible or not.

[0462] As shown in (b) of FIG. 18c, the data values ​​of the data 421, 422 included in the second data group 420 may be either a first data value (e.g., “1”) or a second data value (e.g., “2”), depending on whether the learning target joint points P1, P2 are visible or not.

[0463] Data having a first data value (e.g., “1”) is data indicating that the learning target joint points P1 and P2 are visible in the exercise video 300, and can be understood as information indicating that the position information included in the first data group 410 is of the first type (actual position information).

[0464] The learning unit 51 can extract first type position information (actual position information) of the learning target joint points when the learning target joint points P1 and P2 are visible in the exercise video 300. Based on the extraction of the first type position information (actual position information) from the exercise video 300, the learning unit 51 can generate (configure) the learning dataset 400 by including data having a first data value (e.g., “1”) in the second data group 420.

[0465] On the other hand, the second data value (e.g., "2") is data indicating that the learning target joint points P1 and P2 are not visible in the exercise video 300, and can be understood as information indicating that the position information included in the first data group 410 is of the second type (predicted position information).

[0466] The learning unit 51 can extract (or identify) the second type of position information (actual position information) of the learning target joint point when the learning target joint point is not visible in the exercise video 300. Based on the extraction (or identification) of the second type of position information (predicted position information) from the exercise video 300, the learning unit 51 can generate (configure) the learning dataset 400 by including data having a second data value (e.g., "2") in the second data group 420.

[0467] Meanwhile, as shown in (b) of FIG. 18c, the learning unit 51 can generate (configure) the learning dataset 400 by arranging the data (or data values) 421, 422 included in the second data group 420 in the same order as the predefined order in which the position information 411, 412 of each of the multiple training target joint points is arranged, so as to indicate whether each of the multiple training target joint points P1, P2 is visible or not.

[0468] The learning unit 51 can sequentially arrange the data 421, 422 indicating whether each of the multiple training target joint points is visible or not in the second data group 420 based on a predefined order between the multiple training target joint points P1, P2.

[0469] For example, as shown in (b) of Figure 18c, the learning unit 51 can arrange data 421 having a first data value (e.g., "1") in the second data group 420 in a first order corresponding to the first learning target joint point P1 based on the fact that the first learning target joint point P1 is visible in the exercise video 300.

[0470] 18c(a), the second learning target joint point P2 is shown as being visible in the movement video 300, but it is assumed that the second learning target joint point P2 is not visible in the movement video 300. Based on the fact that the second learning target joint point P2 is visible in the movement video 300, the learning unit 51 can arrange data 422 having a second data value (e.g., "2") in a second order corresponding to the second learning target joint point P2.

[0471] Meanwhile, in the present invention, it can be understood that the definition of the type of the location information included in the first data group 410 is performed according to the data value of the data included in the second data group 420.

[0472] As shown in (b) of Figure 18c, assume that in the second data group 420, data 421 arranged in a first order has a first data value (e.g., "1"), and data 422 arranged in a second order has a second data value (e.g., "2").

[0473] In the present invention, based on the fact that the data 421 arranged in a first order in the second data group 420 has a first data value (e.g., "1"), the type of the location information 411 arranged in a first order in the first data group 410 can be defined as a first type of location information (actual location information).

[0474] On the other hand, based on the fact that the data 422 arranged in the second order in the second data group 420 has a second data value (e.g., "2"), the type of the location information 411 arranged in the second order in the first data group 410 can be defined as a second type of location information (predicted location information).

[0475] Meanwhile, the posture estimation model 52 according to the present invention can perform learning by setting different learning weights for the position information 411, 412 of each of the plurality of training target joint points included in the first data group 410 based on the data values ​​included in the second data group 420.

[0476] Specifically, when data 421 arranged in a first order in second data group 420 has a first data value (e.g., "1"), posture estimation model 52 can set a first learning weight to position information 411 arranged in a first order in first data group 410 and perform learning.

[0477] On the other hand, if the data 422 arranged in the second order in the second data group 420 has a second data value (e.g., "2"), the posture estimation model 52 can set a second learning weight to the position information 412 arranged in the second order in the first data group 410 and perform learning.

[0478] That is, the posture estimation model 52 can perform learning by setting different learning weights for the first type of position information (actual position information) and the second type of position information (predicted position information) based on the data values ​​of the second data group 420. In this case, posture estimation model 52 may set the first learning weight higher than the second learning weight.

[0479] 18b, the plurality of data groups 410 to 450 may further include a third data group 430 including information related to the photographing direction of a subject included in the motion video 300. The third data group 430 may include a data value indicating the photographing direction in which a subject U included in the motion video 300 was photographed. As shown in FIG. 18e(a), the subject U may be photographed from different photographing directions (for example, "front" or "side").

[0480] Here, the "shooting direction" can be understood as the direction of the axis of the camera (see reference numeral "201" in FIG. 19) relative to the subject U. Here, the camera 201 can be understood as the camera 201 that captured the motion video 300 including the subject U. Such a camera 201 may include the camera 201 provided in the user terminal 10, 20.

[0481] The data values ​​included in the third data group 430 shown in Fig. 18e(b) correspond to the shooting direction of the object U and may have different data values ​​(e.g., "0" or "1"). The data values ​​included in the third data group may be configured to have different data values ​​depending on the shooting direction of the object U based on the camera that captured the object. In the following, to avoid confusion with the data values ​​included in the second data group 420, the data values ​​corresponding to the shooting direction will be referred to as "data object values."

[0482] Data having a first data object value (e.g., "0") can be understood as data indicating that the shooting direction of the training exercise video 300 is a first direction (e.g., forward direction) (see Figure 18e(b)).

[0483] The learning unit 51 can generate a learning dataset 400 by including data having a first data object value (e.g., "0") in the third data group 430 based on the fact that the shooting direction of the subject U included in the training exercise video 300 corresponds to a first direction (e.g., front direction).

[0484] On the other hand, the second data object value (e.g., “1”) can be understood as data indicating that the shooting direction for the motion image 300 is a second direction (e.g., a side direction) different from the first direction (see FIG. 18e(b)).

[0485] The learning unit 51 can generate a learning dataset 400 by including data having a second data object value (e.g., "1") in the third data group 430 based on the fact that the shooting direction of the subject U included in the exercise video 300 corresponds to the second direction (e.g., side direction).

[0486] Furthermore, although not shown, the third data object value (e.g., "2") can be understood as data indicating that the shooting direction for the motion image 300 is a third direction (e.g., diagonal direction) different from the first and second directions.

[0487] The learning unit 51 can store data having a third data object value (e.g., "2") in the third data group 430 in the database 40 based on the fact that the shooting direction of the subject U included in the training object video 300 corresponds to the third direction (e.g., diagonal direction).

[0488] On the other hand, the first to third directions described in the present invention can be understood as the cases where the angles formed by the axis of the subject U and the camera 201 based on a predetermined direction (e.g., clockwise) correspond to the first to third ranges, respectively.

[0489] For example, the first direction can be understood as the angle between the subject U and the axis of the camera 201 corresponding to a range from a first angle to a second angle that is larger than the first angle. The second direction can be understood as the angle between the subject U and the axis of the camera 201 corresponding to a range from the second angle to a third angle that is larger than the second angle. Furthermore, the third direction can be understood as the angle between the subject U and the axis of the camera 201 corresponding to a range from the third angle to a fourth angle that is larger than the third angle.

[0490] Meanwhile, the learning unit 51 may configure the angle (or angle value) formed between the object U and the axis of the camera 201 based on a preset direction (e.g., clockwise) as the data value of the data included in the third data group 430. For example, if the axis of the object U and the axis of the camera 201 form a right angle based on the clockwise direction, the learning unit 51 may configure the data value of “90” as the data of the third data group 430. Meanwhile, the learning unit 51 may perform learning for estimating the posture of the object U by linking the learning datasets 400 having different shooting direction information included in the third data group 430.

[0491] For example, it is assumed that the data included in the third data group 430 includes a first training data set having a first data object value (e.g., "0") and a second training data set having a second data object value (e.g., "1"). The training unit 51 can perform training for estimating the pose of the subject U by linking the position information of the first data group 410 included in the first data set with the position information of the first data group included in the second data set.

[0492] On the other hand, when the learning unit 51 estimates the exercise posture of the subject U from the exercise video to be analyzed filmed in the first direction, it can estimate the exercise posture of the subject U based on the posture estimation model learned from the exercise video 300 to be studied filmed in the first direction.

[0493] The exercise therapy provision system 1000 of the present invention can analyze the exercise movements of subject U based on key points extracted from a posture estimation model trained using a training dataset 400 including shooting direction information (data object values ​​or data values) corresponding to the shooting direction of the exercise video to be analyzed.

[0494] On the other hand, when the motion analysis units 120 and 210 estimate the exercise posture of the subject U from the exercise video 300 to be analyzed that was filmed in the first direction, they can analyze the exercise movements of the subject U using posture estimation information estimated from a posture estimation model that has been trained on the exercise video 300 to be studied that was filmed in each of the first and second directions.

[0495] That is, when the movement of subject U is captured in analysis target movement video 300 captured in a first imaging direction, motion analysis units 120 and 210 can analyze the movement of subject U using posture estimation information estimated from a posture estimation model trained on a first training data set including data object values ​​corresponding to the first imaging direction and a second training data set including data object values ​​corresponding to a second imaging direction different from the first imaging direction. In this case, posture estimation model 52 may correspond to a posture estimation model trained by setting a weight on the first training data set.

[0496] In this way, posture estimation model 52 may be configured to be trained by taking into account the shooting direction of the subject through the training data set having different data values ​​depending on the shooting direction of the subject included in the training video. Furthermore, the user's exercise / motion analysis result may be a result of analyzing a specific exercise / motion of the user based on posture estimation information extracted in the posture estimation model by taking into account the shooting direction of the user included in the exercise video.

[0497] Meanwhile, as shown in FIG. 18b, a fourth data group 440 of the plurality of data groups may include an exercise code matched to the exercise movement performed by the subject U included in the training exercise video 300.

[0498] As shown in FIG. 18f, in the database 40, a plurality of different exercise actions 710, 720, 730 may be matched with different exercise codes (for example, "502", "503", "504"), respectively.

[0499] The "exercise code" described in the present invention is a data value that distinguishes different exercise actions from each other, and may be used interchangeably with "exercise key," "action code," or "action key."

[0500] The learning unit 51 can generate a learning dataset 400 by including in the fourth data group 440 a specific exercise code ("502") that matches a specific exercise movement (e.g., "standing and extending one leg forward") 710 performed by the subject U included in the training exercise video 300. The learning unit 51 can perform learning for posture estimation by linking a plurality of learning data sets 400 including the same movement code.

[0501] For example, assume that there is a first training data set based on a first training object exercise video and a second training data set based on a second training object exercise video 300. The training unit 51 can link the first training data set and the second training data set based on the fact that the exercise code (e.g., "502") included in the first training data set and the second training data set is the same, and perform training for posture estimation.

[0502] Such exercise code may be included in the fourth data group 440 based on the exercise movement performed by the subject U being identified by at least one of information received from the user terminal 10, 20, a system administrator, or the learning unit 51.

[0503] The learning unit 51 can identify the exercise action performed by the subject U based on information received from the user terminals 10 and 20. For example, based on the selection of a graphic object corresponding to "start exercise" from the user terminals 10 and 20, the learning unit 51 can control the state of the camera 201 provided in the user terminals 10 and 20 to an activated state so that the camera 201 captures exercise footage.

[0504] In this case, the graphic object can correspond to a specific exercise action, and the learning unit 51 can determine that the subject U included in the exercise video 300 received from the user terminal 10, 20 has performed the specific exercise action. Furthermore, the learning unit 51 can identify the exercise and movement performed by the subject U based on the information input by the system administrator.

[0505] Furthermore, the learning unit 51 can identify the exercise and movement performed by the subject U based on the position information of the joints to be learned of the subject U included in the exercise video 300. In this case, the exercise and movement performed by the subject U can be identified by referring to the motion information of the exercise and movement stored in the database 40.

[0506] Meanwhile, the learning unit 51 may match a plurality of learning data sets 400 including the same exercise code with each other based on the exercise code included in the fourth data group 440 and store the matched data in the database 40 .

[0507] In this case, the learning unit 51 may divide and allocate the memory (or memory space) of the database 40 based on the learning code. In the present invention, dividing the memory (or memory space) of the database 40 may be understood as creating folders in the database 40 based on the exercise code. Furthermore, the learning unit 51 may store the learning data set 400 including a specific exercise code in a folder corresponding to the specific exercise code.

[0508] On the other hand, the motion analysis units 120 and 210 can analyze the exercise movements in the exercise video to be analyzed using posture estimation information estimated from a posture estimation model learned using a learning dataset including movement codes corresponding to specific exercise movements performed by the subject U.

[0509] Furthermore, the motion analysis unit 120, 210 can estimate the motion of the subject U for a specific motion using posture estimation information estimated from a posture estimation model learned based on the training target motion video 300 related to the same specific motion as the subject U included in the analysis motion target.

[0510] Meanwhile, as shown in FIG. 18c, the fifth data group 450 among the plurality of data groups 410 to 450 may include size information 451 of the bounding box 301 for the subject U included in the training exercise video 300, and position information 452 of the center of the bounding box 301. In the present invention, the "size information" of the bounding box 301 is sometimes confused with the "scale."

[0511] The learning unit 51 extracts size information 451 of the bounding box 301 corresponding to the subject U detected in the training object motion video 300, extracts center position information 452 of the bounding box 301, and includes this in a fifth data group 450 to generate a learning dataset 400.

[0512] As described above, the learning unit 51 can use various object detection algorithms to detect the subject U from the training target motion video 300. For example, the learning unit 51 can use an algorithm (Weighted Box Fusion, WBF) that ensembles multiple bounding boxes. However, it goes without saying that the learning unit 51 is not limited to the above-mentioned object detection algorithms, and can use various object detection algorithms that can detect an object corresponding to the subject U from the training target motion video 300.

[0513] The learning unit 51 can extract size information 451 and center position information 452 of the bounding box corresponding to the subject U from the learning target video 300 based on an object detection algorithm, and include the size information 451 and center position information 452 in a fifth data group 450 to generate a learning dataset 400. In this case, the learning unit 51 can extract the center position information 452 of the bounding box 301 in the form of a pair of coordinate information on the x-axis and y-axis. Meanwhile, the learning unit 51 can create a learning data set 400 including the video identification information of the training exercise video 300.

[0514] Here, "video identification information" refers to information for identifying the video 300 from which the information contained in the learning dataset was extracted, and may include, for example, file name information and file format type information (or extension information, e.g., "JPG", "TIF") of the training exercise video 300. In the present invention, the video identification information can be named a sixth data group corresponding to a sixth information attribute. The learning unit 51 can generate the learning data set 400 including the sixth data group made up of video identification information.

[0515] Meanwhile, in the present invention, the analysis of the user's exercise movements included in the exercise video to be analyzed is completed through posture estimation information extracted based on the posture estimation model 52, and the exercise movement analysis results can be provided to the user terminal 200 based on this.

[0516] 19(a), the control unit 130 can control the camera state to an activated state so that the camera 201 provided in the user terminal 200 captures an exercise video to be analyzed based on the selection of a graphic object 210 corresponding to "start exercise" from the user terminal 200. In addition, the control unit 130 can receive the exercise video to be analyzed captured by the camera 201 from the user terminal 200 in real time or based on the completion of the user's exercise.

[0517] 19(b), upon completing the analysis of the user's movement and motion included in the analysis target video based on the posture estimation model 52, the control unit 130 may provide the user terminal 200 with a movement and motion analysis result using the analysis result. The movement and motion analysis result provided on the user terminal 200 by the control unit 130 may include various information. For example, the control unit 130 may render graphic objects corresponding to joint points P1 and P2 for the subject U corresponding to the user and provide the graphic objects on the user terminal 200. In this case, the control unit 130 may also provide joint motion range information (angle information) 221 of the subject U.

[0518] 19(c), the control unit 130 can provide, on the user terminal 200, motion posture information 820 for each of a plurality of joint points of the subject U performing a specific motion posture (e.g., "stretching arms out to the side") 810. For example, the control unit 130 can provide, on the user terminal 200, the joint motion ranges of the joint points located on a first side (e.g., left side) of the user and the joint motion ranges of the joint points located on a second side (e.g., right side).

[0519] Meanwhile, the control unit 130 may prescribe (provide) an exercise plan (or exercise program) including at least one exercise movement to the user based on the movement analysis result for the specific exercise movement of the user.

[0520] For example, as shown in (a) of FIG. 20, the control unit 130 can add exercise actions to the exercise plan (or exercise program) based on the results of the exercise action analysis, and provide a service page 910 on the user terminal 200 that includes information on the exercise plan (or exercise program) including the added exercise actions.

[0521] As another example, as shown in (b) of Figure 20, the control unit 130 can adjust the difficulty of the exercise plan (or exercise program) based on the movement analysis posture results and provide a service page 920 on the user terminal 200 that includes the adjusted difficulty information.

[0522] As another example, as shown in (c) of Figure 20, the control unit 130 can exclude some of the exercise movements from the exercise plan (or exercise program) based on the results of the exercise movement analysis, and provide a service page 930 on the user terminal 200 informing the user that the exercise movements have been excluded.

[0523] Meanwhile, in the present invention, the exercise / motion analysis results can be provided to the patient terminal 10 after the analysis of the patient's exercise / motion is completed based on the above-mentioned motion analysis units 120 and 210. As shown in Figures 21a, 21b, and 21c, the exercise / motion analysis results can be provided through the therapeutic exercise application 100 installed on the patient terminal 10.

[0524] As shown in (a) of Fig. 21a, the exercise therapy application 100 can provide a service page configured to enable access to each of the multiple services provided by the present invention on the patient terminal 10. For example, the service page may be configured to enable access to at least one of i) an exercise guide page linked to an exercise guide information providing function for an exercise plan assigned to a patient account, ii) an exercise page related to the execution of an exercise plan assigned to a patient account (see (b) of Fig. 21a), iii) a function evaluation page linked to a function evaluation (see (c) of Fig. 21a), and iv) a plan evaluation page linked to an exercise plan evaluation function.

[0525] Furthermore, as shown in Fig. 21b, the exercise therapy application 100 can provide an exercise report page on the patient terminal 10 that provides an exercise report based on the exercise motion analysis results and the exercise execution results. For example, the exercise report page may include at least one of exercise execution rate information (see (a) and (b) in Fig. 21b) and exercise plan difficulty information (see (c) in Fig. 21b). Furthermore, as shown in FIG. 21c, the exercise therapy application 100 can provide the patient's exercise motion analysis results on the patient terminal 10.

[0526] 21c(a), the therapeutic exercise application 100 can provide exercise motion analysis information for each of a plurality of joint points of a subject U performing a specific prescribed exercise (e.g., "stretching arms out to the side") on the patient terminal 10. For example, the therapeutic exercise application 100 can provide, on the patient terminal 10, a graph of the joint motion ranges of joint points located on a first side (e.g., left side) of the patient and the joint motion ranges of joint points located on a second side (e.g., right side).

[0527] 21c(b), the therapeutic exercise application 100 can provide daily exercise motion analysis results for a patient who has performed prescribed exercises according to an exercise plan for a certain period of time. For example, the therapeutic exercise application 100 may provide joint range of motion information corresponding to a first exercise day and joint range of motion information corresponding to a second exercise day. The therapeutic exercise application 100 may also provide the average joint range of motion for the first exercise day and the second exercise day.

[0528] As shown in (c) of FIG. 21c, the therapeutic exercise application 100 may render graphic objects corresponding to key points P1 and P2 in the exercise video 300 and provide the rendered graphic objects on the patient terminal 10. In this case, the therapeutic exercise application 100 may also provide information on the patient's joint range of motion (angle information).

[0529] Meanwhile, the exercise treatment providing system 1000 according to the present invention can provide the exercise motion analysis results provided to the patient terminal 10 to the doctor terminal 20 so that the doctor can monitor the execution of the patient's exercise plan.

[0530] As described above, the system and method for providing therapeutic exercise using an AI posture estimation model and a motion analysis model according to the present invention can receive prescription information for patient exercise from a doctor's terminal and assign an exercise plan including at least one prescribed exercise to the patient's account based on the prescription information. This allows the doctor to prescribe exercise for the patient without having to meet in person for the exercise treatment for musculoskeletal disorders, and the patient can receive an exercise plan according to the doctor's prescription. This eliminates spatial, temporal, and financial constraints on therapeutic exercise and improves accessibility to therapeutic exercise.

[0531] Furthermore, the system and method for providing exercise therapy using the AI ​​posture estimation model and motion analysis model according to the present invention can analyze the user's exercise movements by extracting key points corresponding to a plurality of pre-set joint points from the exercise video, thereby focusing on the joints required for exercise therapy for musculoskeletal disorders.

[0532] Furthermore, the system and method for providing exercise therapy using an AI posture estimation model and a motion analysis model according to the present invention can analyze exercise movements related to specific exercise movements of a user included in an exercise video based on a posture estimation model trained using a training data set including position information of joint points. As a result, the present invention can accurately analyze a patient's posture from exercise videos, and in particular, obtain information on the patient's joint range of motion, alignment, and disengagement, thereby improving the quality of medical services.

[0533] Furthermore, the system and method for providing exercise therapy using the AI ​​posture estimation model and movement analysis model according to the present invention transmits the analysis results of the patient's exercise movements to the patient's terminal, so that the patient can receive feedback on the exercise video and improve the effectiveness of the exercise therapy without having to go directly to a hospital located far away.

[0534] On the other hand, computer-readable media includes any kind of recording device that stores data that can be read by a computer system, such as a hard disk drive (HDD), a solid state disk (SSD), a silicon disk drive (SDD), a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device.

[0535] Furthermore, the computer-readable medium may include a storage, and may be a server or cloud storage that can be accessed by the electronic device via communication. In this case, the computer can download the program according to the present invention from the server or cloud storage via wired or wireless communication.

[0536] Furthermore, in the present invention, the above-mentioned computer is an electronic device equipped with a processor, that is, a CPU (Central Processing Unit), and the type thereof is not particularly limited.

[0537] However, the above detailed description should not be construed as limiting in all respects, but should be considered as illustrative. The scope of the present invention should be determined by reasonable interpretation of the appended claims, and all modifications within the scope of the present invention are included in the scope of the present invention.

Claims

1. Executing an exercise program generation mode on a terminal logged in with a specific medical staff account; In the exercise program creation mode, at least one exercise item to be included in the exercise program is selected; setting program information corresponding to the exercise program; generating the exercise program including the exercise items and the program information; storing the exercise program in association with the particular medical staff account; assigning the exercise program to the patient account based on receiving prescription information for the patient account from the particular medical staff account; The specific medical staff account: Based on the occupational information of the specific medical staff, the account is set to either a first type of medical staff account in which the individual prescription authority for the exercise program exists (existence) or a second type of medical staff account in which the individual prescription authority for the exercise program does not exist (non-existence); If the type of the specific medical staff account is the first type, the patient account may play an exercise video corresponding to the exercise item based on receiving the prescription information from the specific medical staff account; When the type of the specific medical staff account is the second type, the patient account may play the exercise video corresponding to the exercise item based on the occurrence of an approval event for the prescription of the exercise program from the medical staff account of the first type; receiving a video including a subject of the patient from a terminal logged in with the patient account based on the exercise video being played back on the patient account; A method for generating a customized therapeutic exercise program, characterized in that an exercise motion analysis report of the patient is generated from the received video and provided to the specific medical staff account.

2. The step of selecting an exercise item includes: displaying, on the terminal, a plurality of exercise items registered in the exercise therapy provision service; selecting at least one exercise item from the plurality of exercise items from the specific medical staff account; and displaying a list including the selected exercise items on the terminal; The method of claim 1 , wherein the exercise program is composed of the exercise items included in the list.

3. The exercise program comprises:

3. The method for generating a customized therapeutic exercise program according to claim 2, wherein the customized therapeutic exercise program is set to either a non-shareable state in which the program is accessible only by the specific medical staff account, or a shareable state in which the program is accessible by medical staff accounts other than the specific medical staff account.

4. the program information includes information identifying a target to which the exercise program is to be shared; The method for generating a customized therapeutic exercise program according to claim 3, wherein the other medical staff accounts that can access the exercise program are determined based on the program information.

5. The information specifying the sharing target is:

5. The method for generating a customized therapeutic exercise program according to claim 4, wherein the customized therapeutic exercise program is generated based on at least one of hospital information and medical staff information registered in the therapeutic exercise provision service.

6. If the exercise program is in a shareable state, The method for generating a customized exercise therapy program according to claim 5, wherein the exercise program is assigned to the patient account based on prescription information received from the other medical staff account.

7. The step of assigning the exercise program to the patient account comprises: confirming the type of the particular medical staff account; 2. The method for generating a customized exercise therapy program according to claim 1, further comprising the step of: assigning the exercise program to the patient account if the type of the particular medical staff account is the first type as a result of the confirmation.

8. The step of assigning the exercise program to the patient account comprises:

8. The method for generating a customized exercise therapy program according to claim 7, wherein, if the confirmation result indicates that the specific medical staff account is of the second type, the exercise program is assigned to the patient account based on the occurrence of an approval event for the prescription of the exercise program from the medical staff account of the first type.

9. a control unit that executes an exercise program generation mode on a terminal logged in with a specific medical staff account; a communication unit that receives a selection for at least one exercise item to be included in the exercise program in the exercise program generation mode; a storage unit in which the exercise program is stored, The control unit setting program information corresponding to the exercise program; generating the exercise program including the exercise items and the program information; storing the exercise program in the storage unit in association with the specific medical staff account; assigning the exercise program to the patient account based on receiving prescription information for the patient account from the particular medical staff account; The specific medical staff account: Based on the occupational information of the specific medical staff, the account is set to either a first type of medical staff account in which the individual prescription authority for the exercise program exists (existence) or a second type of medical staff account in which the individual prescription authority for the exercise program does not exist (non-existence); If the type of the specific medical staff account is the first type, the patient account may play an exercise video corresponding to the exercise item based on receiving the prescription information from the specific medical staff account; When the type of the specific medical staff account is the second type, the patient account may play the exercise video corresponding to the exercise item based on the occurrence of an approval event for the prescription of the exercise program from the medical staff account of the first type; receiving a video including a subject of the patient from a terminal logged in with the patient account based on the exercise video being played back on the patient account; A system for generating a customized therapeutic exercise program, which generates an exercise motion analysis report for the patient from the received video and provides it to the specific medical staff account.

10. A program executed by one or more processes in an electronic device and stored on a computer-readable recording medium, The program Executing an exercise program generation mode on a terminal logged in with a specific medical staff account; In the exercise program creation mode, at least one exercise item to be included in the exercise program is selected; setting program information corresponding to the exercise program; generating the exercise program including the exercise items and the program information; storing the exercise program in association with the particular medical staff account; assigning the exercise program to the patient account based on receiving prescription information for the patient account from the particular medical staff account; The specific medical staff account: Based on the occupational information of the specific medical staff, the account is set to either a first type of medical staff account in which the individual prescription authority for the exercise program exists (existence) or a second type of medical staff account in which the individual prescription authority for the exercise program does not exist (non-existence); If the type of the specific medical staff account is the first type, the patient account may play an exercise video corresponding to the exercise item based on receiving the prescription information from the specific medical staff account; When the type of the specific medical staff account is the second type, the patient account may play the exercise video corresponding to the exercise item based on the occurrence of an approval event for the prescription of the exercise program from the medical staff account of the first type; A program stored on a computer-readable recording medium, characterized in that, based on the exercise video being played back in the patient account, video including the patient's subject is received from a terminal logged in with the patient account, and an exercise motion analysis report of the patient is generated from the received video and provided to the specific medical staff account.

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