Method and system for providing digitally based musculoskeletal rehabilitation therapy

Abstract

In order to solve the above problem, a method for providing digital-based musculoskeletal rehabilitation treatment provided by an application may include the steps of: selecting an exercise plan to be provided to the patient based on prescription information including an exercise plan for the patient being assigned from a doctor terminal; executing the application on a user terminal to which the patient account is logged in; providing an exercise list according to the exercise plan to the user terminal on which the application is executed; playing exercise videos corresponding to the multiple exercise items constituting the exercise list on the user terminal; providing an evaluation page for making an evaluation related to the exercise items based on the degree to which the exercise videos are played back meeting a preset criterion; and updating the exercise plan based on the evaluation information received via the evaluation page.

Description

[Technical Field]

[0001] The present invention relates to a method and system for providing digitally based musculoskeletal rehabilitation therapy. [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.

[0011] 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]

[0012] The present invention relates to a method and system for providing digital-based musculoskeletal rehabilitation therapy, which can provide digital-based rehabilitation therapy for musculoskeletal disorders.

[0013] Furthermore, the present invention relates to a method and system for providing digital-based musculoskeletal rehabilitation therapy that can provide customized digital therapeutics suited to a patient's indication.

[0014] Furthermore, the present invention relates to a method and system for providing digital-based musculoskeletal rehabilitation therapy that can provide cognitive behavioral therapy in conjunction with rehabilitation therapy. [Means for solving the problem]

[0015] In order to solve the above problem, a method for providing digital-based musculoskeletal rehabilitation therapy provided by an application may include the steps of selecting an exercise plan to be provided to the patient based on the assignment of prescription information including an exercise plan corresponding to the patient's indications from a doctor's terminal; executing the application on a user terminal to which the patient account is logged in; providing an exercise list according to the exercise plan to the user terminal on which the application is executed; playing exercise videos corresponding to each of the multiple exercise items constituting the exercise list on the user terminal; providing an evaluation page for making an evaluation related to the exercise items based on the degree to which the exercise videos are played back meeting a predetermined standard; and updating the exercise plan based on the evaluation information received via the evaluation page.

[0016] In one example, the exercise plan may include exercise items related to the patient's indications included in the patient's prescription information, with at least some of the exercise items assigned to each of a plurality of different days that make up a predetermined rehabilitation period.

[0017] In one example, the step of providing the exercise list may provide the exercise list including the plurality of exercise items assigned to specific days on which the exercise video is played, based on a reference date on which the user terminal started counting the preset rehabilitation period, and the evaluation page may be provided to the user terminal for each specific day if the playback level of the exercise video meets the preset standard, in order to perform an evaluation related to the plurality of exercise items provided to the patient for each specific day.

[0018] In one example, the evaluation page includes at least one of a first evaluation area for evaluating the exercise difficulty of the plurality of exercise items assigned to the particular day, a second evaluation area for selecting a high-difficulty exercise from the plurality of exercise items, and a third evaluation area for evaluating exercise pain associated with the plurality of exercise items, and in the step of updating the exercise plan, the difficulty of the exercise plan may be changed or at least some of the exercise items constituting the exercise plan may be changed based on evaluation information received through at least one of the first evaluation area, the second evaluation area, and the third evaluation area.

[0019] In one example, exercise items according to the updated exercise plan may be provided to the user terminal from the day after the specific day has passed.

[0020] In one example, the second evaluation area displays the plurality of exercise items assigned to the particular day, and in the step of updating the exercise plan, when at least one of the plurality of exercise items is selected from the user terminal, the selected exercise item may be excluded from the exercise plan, and another exercise item that has an effect corresponding to the selected exercise item and induces less pain than the selected exercise item may be included in the exercise plan.

[0021] The method may further include a step of assigning a cognitive behavioral treatment plan to the patient account in conjunction with the exercise plan, wherein the step of assigning the cognitive behavioral treatment plan may include a step of receiving questionnaire response data for multiple questionnaire data via the user terminal, a step of detecting condition information of the pain patient related to the pain duration and degree of cognitive distortion of the pain patient based on the questionnaire response data, a step of identifying a user group corresponding to the condition information of the pain patient from multiple user groups classified according to the pain duration and degree of cognitive distortion, a step of determining an initial treatment protocol corresponding to the user group from multiple treatment protocols, and a step of providing multiple specific treatment programs included in the initial treatment protocol in sequence during a predetermined rehabilitation period.

[0022] The method may further include a step of providing an initial screen page in response to the application being executed on the user terminal, the initial screen page including at least one of a first menu item for accessing an exercise list according to the exercise plan, a second menu item for accessing the evaluation page, a third menu item for accessing the cognitive behavioral treatment plan assigned along with the exercise plan, and a fourth menu item for accessing a page for conducting a functional evaluation for specific movements of the patient, and if the playback level of the exercise video does not meet the preset standard, even if the second menu item is selected on the user terminal, provision of the evaluation page to the user terminal may be restricted.

[0023] In one example, the functional assessment for the specific movement is performed at predetermined day intervals during a predetermined rehabilitation period to which the exercise plan is assigned, and the fourth menu item is configured to be included on the initial screen page on a specific day corresponding to the predetermined day interval, and may not be included on the initial screen page if it is not the specific day during the rehabilitation period.

[0024] Furthermore, the digital-based musculoskeletal rehabilitation treatment provision system 100 according to the present invention includes a communication unit that receives prescription information including an exercise plan for the patient from a doctor's terminal, and a control unit that provides an exercise list according to the exercise plan to the user terminal in response to the application being executed on the user terminal to which the patient account is logged in. The control unit plays exercise videos corresponding to each of the exercise items constituting the exercise list on the user terminal, provides an evaluation page for evaluating the exercise items based on whether the playback level of the exercise videos meets a predetermined standard, and updates the exercise plan based on the evaluation information received via the evaluation page.

[0025] Furthermore, the program may be executed by one or more processes in an electronic device and stored on a computer-readable recording medium, and may include instructions to perform the following steps: determine an exercise plan to be provided to the patient based on prescription information including an exercise plan for the patient being assigned from a doctor terminal; execute the application on a user terminal to which the patient account is logged in; provide an exercise list according to the exercise plan to the user terminal on which the application is executed; play, on the user terminal, exercise videos corresponding to each of the exercise items constituting the exercise list; provide an evaluation page for evaluating the exercise items based on whether the playback level of the exercise video meets a predetermined criterion; and update the exercise plan based on the evaluation information received via the evaluation page.

[0026] Meanwhile, a method for providing exercise therapy according to the present invention may include the steps of receiving prescription information regarding exercise for a patient from a doctor terminal, assigning an exercise plan including at least one prescribed exercise to the patient account based on the prescription information, receiving exercise video of the exercise corresponding to the prescribed exercise from the patient terminal, extracting key points corresponding to a plurality of pre-set joint points from the exercise video using an AI posture estimation model, analyzing the relative positional relationship between the key points using an AI motion analysis model, and analyzing the patient's exercise movements for the prescribed exercise based on the analysis of the positional relationship, and transmitting the analysis results of the patient's exercise movements to the patient terminal.

[0027] Furthermore, the exercise therapy provision estimation method according to the present invention may further include the steps of: outputting the exercise video to the patient terminal in real time in conjunction with the exercise video being captured on the patient terminal; and providing a graphic object corresponding to the extracted key point by superimposing it on an area in the exercise video where a subject corresponding to the patient is located so that the patient can recognize the joint points at which analysis is performed on the patient's exercise movement.

[0028] In one example, the step of extracting the key points may include identifying visible joint points of the subject that are visible in the motion video from among the plurality of pre-set joint points, and extracting the identified visible joint points as the key points.

[0029] In one example, the motion analysis model may predict invisible joint points of the subject that are not visible in the motion video among the plurality of pre-set joint points based on the learning data, and analyze the patient's motion based on the visible joint points and the invisible joint points.

[0030] In this case, the key points may include key points corresponding to the visible joint points and the invisible joint points.

[0031] In one example, the training data may include a first data group in which position information of training target visible joint points of a subject included in a training target video and training target invisible joint points estimated based on the visible joint points are listed in order, and a second data group including data values ​​indicating whether the training target visible joint points and the training target invisible joint points are visible or not.

[0032] In this case, the data values ​​included in the second data group may be listed in the same order as the order in which the training target visible joint points and the training target invisible joint points are listed.

[0033] In one example, the step of analyzing the patient's exercise motion may analyze the relative positional relationship between the key points based on rule information regarding the prescribed exercise, and analyze the patient's exercise motion by determining whether the relative positional relationship between the key points satisfies the rule information.

[0034] In one example, the visual appearance of the graphic object superimposed on the motion image may differ depending on whether the relative positional relationship between the extracted key points satisfies the rule information.

[0035] In one example, the analysis results for the patient's exercise movements may include a first analysis result in which the graphic objects corresponding to the key points are superimposed on the exercise video in real time with different visual appearances based on the rule information while the exercise video is being shot on the patient terminal, and a second analysis result including the patient's evaluation score for the prescribed exercise based on key points extracted from each of a plurality of frames constituting the exercise video.

[0036] In this case, the first analysis result may be generated by a behavior analysis model of an application installed on the patient terminal, the second analysis result may be generated by a cloud server linked to the application, and both the first analysis result and the second analysis result may be transmitted to the doctor terminal. Furthermore, the exercise therapy providing system according to the present invention includes a communication unit that receives prescription information regarding exercises for a patient from a doctor's terminal, and a control unit that assigns an exercise plan including at least one prescribed exercise to the patient account based on the prescription information. The control unit may receive exercise video of the exercise corresponding to the prescribed exercise from the patient's terminal, extract key points corresponding to a plurality of pre-set joint points from the exercise video, analyze the relative positional relationships between the key points through an artificial intelligence motion analysis model, analyze the patient's exercise movements for the prescribed exercise based on the analysis of the positional relationships, and transmit the analysis results of the patient's exercise movements to the patient's terminal.

[0037] Furthermore, the exercise therapy provision system of the present invention includes a communication unit that receives prescription information regarding exercise for a patient from a doctor terminal, and a control unit that assigns an exercise plan including at least one prescribed exercise to the patient account based on the prescription information, and the control unit receives exercise video of the exercise corresponding to the prescribed exercise from the patient terminal, analyzes the patient's exercise movements for the prescribed exercise from the exercise video using an artificial intelligence motion analysis model, and transmits the analysis results of the patient's exercise movements to the patient terminal.

[0038] 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: receiving prescription information regarding exercise for a patient from a doctor terminal; allocating an exercise plan including at least one prescribed exercise to the patient account based on the prescription information; receiving exercise video of the exercise corresponding to the prescribed exercise from the patient terminal; extracting key points corresponding to a plurality of predetermined joint points from the exercise video; analyzing the relative positional relationships between the key points through an artificial intelligence motion analysis model; analyzing the patient's exercise movements for the prescribed exercise based on the analysis of the positional relationships; and transmitting the analysis results of the patient's exercise movements to the patient terminal.

[0039] Meanwhile, the exercise posture estimation method of the present invention includes the steps of receiving an exercise video from a user terminal, analyzing an exercise movement related to a specific exercise movement of the user included in the exercise video based on posture estimation information extracted from a posture estimation model trained using a training dataset 400 including position information of joint points, and providing an analysis result of the exercise movement of the user related to the specific exercise movement to the user terminal based on completion of the analysis, wherein the position information of the joint points included in the training dataset is position information of each of a plurality of pre-specified training target joint points among joint points of a subject included in the training target exercise video, and the training dataset may be composed of data extracted from the training target exercise video.

[0040] In one example, the learning data set may be composed of a plurality of data groups each corresponding to a different information attribute, a first data group among the plurality of data groups including position information of each of the plurality of learning target joint points, and the position information included in the first data group may include coordinate information of each of the pre-specified plurality of learning target joint points in the learning target movement video in a mutually paired form.

[0041] In one example, the position information included in the first data group may be defined as different types of information depending on whether the plurality of training target joint points are visible in the training target image, and the type of the position information may be defined according to a data value of data included in a second data group different from the first data group.

[0042] In one example, the pose estimation model may set different learning weights for each position information of the plurality of training target joint points included in the first data group based on the data values ​​included in the second data group.

[0043] In one example, the first data group may be arranged such that the position information of each of the plurality of training joint points is sequentially arranged in the first data group based on a predefined order among the plurality of training joint points, and the data values ​​included in the second data group may be arranged in the same order as the predefined order in which the position information of each of the plurality of training joint points is arranged, so as to indicate whether each of the plurality of training joint points is visible.

[0044] In one example, the training data set may further include a third data group including data values ​​related to the shooting direction of the object, and 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 relative to the camera that captured the object.

[0045] In this case, the posture estimation model is configured to be learned taking into account the shooting direction of the subject through the learning dataset having different data values ​​depending on the shooting direction of the subject, and the result of the exercise / motion analysis of the user may be a result of analyzing a specific exercise / motion of the user based on posture estimation information extracted in the posture estimation model taking into account the shooting direction of the user included in the exercise video.

[0046] In one example, the exercise video received from the user terminal and the training target exercise video correspond to the specific exercise movements having the same exercise code, and the training dataset may include a fourth data group including an exercise code matched to the specific exercise movement performed by the subject in the training target exercise video.

[0047] Furthermore, the training object motion video may be a video, and the training dataset 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 the training object motion video, with a focus on the subject included in the training object motion video.

[0048] The motion posture estimation system according to the present invention includes: a posture estimation model that extracts posture estimation information using a training data set including position information of joint points; a motion analysis model that analyzes a motion movement related to a specific motion of a user included in a motion video to be analyzed using the posture estimation information; and a service server that provides a motion movement analysis result of the user related to the specific motion to the user terminal based on completion of the analysis. The position information of the joint points included in the training data set may be position information of each of a plurality of pre-designated training target joint points among joint points of a subject included in the training target motion video, and the training data set may be composed of data extracted from the training target motion video.

[0049] Furthermore, a program executed by one or more processes in an electronic device and stored in a computer-readable recording medium includes instructions for performing the following steps: receiving a motion video from a user terminal; analyzing a motion movement related to a specific motion of the user included in the motion video based on posture estimation information extracted from a posture estimation model trained using a training dataset including position information of joint points; and providing an analysis result of the user's motion movement related to the specific motion to the user terminal based on completion of the analysis. The position information of the joint points included in the training dataset may be position information of each of a plurality of pre-designated training target joint points among joint points of a subject included in a training target motion video, and the training dataset may be composed of data extracted from the training target motion video.

[0050] On the other hand, a cognitive behavioral therapy providing method according to the present invention may include the steps of providing a plurality of questionnaire data for diagnosing the condition of a pain patient on a user terminal, receiving questionnaire response data for the plurality of questionnaire data via the user terminal, detecting condition information of the pain patient related to the pain duration and degree of cognitive distortion of the pain patient based on the questionnaire response data, identifying a user group corresponding to the condition information of the pain patient from a plurality of user groups classified according to the pain duration and degree of cognitive distortion, determining an initial treatment protocol corresponding to the user group from a plurality of treatment protocols, and sequentially providing a plurality of specific treatment programs included in the initial treatment protocol to the user terminal according to the treatment week set for each of the plurality of specific treatment programs.

[0051] The treatment protocol of the present invention can be understood as a treatment process consisting of multiple treatment programs, each matched to a different topic. A specific treatment program may include at least one treatment module related to a specific topic matched to the specific treatment program. Here, a treatment module can be understood as a detailed category for cognitive-behavioral treatment of a pain patient for a specific topic. In one example, a server stores multiple treatment programs, each matched to a different topic, each including at least one treatment module related to the topic matched to the multiple treatment programs. Each of the multiple treatment protocols may be composed of at least one different treatment program or treatment module depending on the characteristics of the pain duration and the degree of cognitive distortion of the user group matched to the multiple treatment protocol.

[0052] In this case, the multiple user groups may include a first user group having acute pain and high cognitive distortion in relation to the characteristics of pain duration and degree of cognitive distortion, a second user group having acute pain and low cognitive distortion in relation to the characteristics of pain duration and degree of cognitive distortion, a third user group having chronic pain and high cognitive distortion in relation to the characteristics of pain duration and degree of cognitive distortion, and a fourth user group having chronic pain and low cognitive distortion in relation to the characteristics of pain duration and degree of cognitive distortion, and the criterion for distinguishing between acute pain and chronic pain may be determined based on whether the pain duration exceeds a reference period, and the criterion for distinguishing between high cognitive distortion and low cognitive distortion may be determined based on whether a score (SCORE) collected based on multiple questions related to cognitive distortion exceeds a reference score.

[0053] In one example, the step of sequentially providing to the user terminal includes a step of sequentially providing to the user terminal specific treatment modules constituting the plurality of specific treatment programs according to the treatment week set for each of the plurality of specific treatment programs, and a step of collecting treatment response data from the user terminal using the specific treatment modules, and may further include a step of updating the initial treatment protocol using the treatment response data.

[0054] In one example, the step of updating the initial treatment protocol is performed by updating the initial treatment protocol using initial treatment response data obtained from treatment modules provided for each treatment week of a predetermined initial treatment period during a predetermined overall treatment period during which the plurality of specific treatment programs are to be provided to the user terminal, and the updating of the initial treatment protocol may be performed by changing at least one of the remaining treatment programs assigned to the remaining treatment periods of the overall treatment period excluding the initial treatment period and the treatment modules constituting the remaining treatment programs.

[0055] In one example, the step of updating the initial treatment protocol may include the steps of: using the initial treatment response data to analyze the pain patient's condition for each of a plurality of different analysis categories related to at least one of emotion, pain, insomnia, cognitive distortion, and stress; using the analysis results to identify a category among the plurality of analysis categories in which the pain patient's problem symptoms meet predetermined criteria; and modifying the remaining treatment program assigned to the remaining treatment period and at least one of the treatment modules that make up the remaining treatment program so as to be related to the identified category.

[0056] In one example, as a result of updating the initial treatment protocol, at least some of the example sentences provided by the treatment modules that make up the remaining treatment program may be modified to relate to the identified category.

[0057] In one example, the step of updating the initial treatment protocol includes a step of determining whether to maintain a preset total treatment period for providing the plurality of specific treatment programs to the user terminal based on the treatment response data, and a step of updating the preset total treatment period based on the determination result, wherein the updating of the preset total treatment period may include shortening the total treatment period to a period shorter than the total treatment period or extending the total treatment period to a period longer than the total treatment period. In one example, each of the plurality of specific treatment programs may include a worksheet module for checking at least one of the pain patient's pain level, pain duration, mental health state, and physical health state, and the step of sequentially providing the plurality of specific treatment programs to the user terminal may prioritize providing user response information to a worksheet module provided in a treatment week prior to the current treatment week before providing a treatment program corresponding to the current treatment week among the plurality of specific treatment programs to allow the pain patient to recognize the pain patient's past condition.

[0058] Furthermore, the cognitive behavioral therapy provision system of the present invention includes a communication unit that communicates with a user terminal, a storage unit that stores multiple treatment programs that are each matched to different topics, and a control unit that provides multiple questionnaire data for diagnosing the condition of a pain patient on the user terminal, wherein the control unit receives response data to the multiple questionnaire data from the user terminal via the communication unit, detects condition information of the pain patient related to the pain duration and degree of cognitive distortion of the pain patient based on the response data, identifies a user group corresponding to the condition information of the pain patient from multiple user groups classified according to the pain duration and degree of cognitive distortion, determines an initial treatment protocol corresponding to the user group from multiple treatment protocols, and provides multiple specific treatment programs included in the initial treatment protocol to the user terminal in sequence according to the treatment week set for each of the multiple specific treatment programs.

[0059] 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: providing a plurality of questionnaire data for diagnosing the condition of a pain patient on a user terminal; receiving response data to the plurality of questionnaire data via the user terminal; detecting condition information of the pain patient related to the pain duration and degree of cognitive distortion of the pain patient based on the response data; identifying a user group corresponding to the condition information of the pain patient from a plurality of user groups classified according to the pain duration and degree of cognitive distortion; determining an initial treatment protocol corresponding to the user group from a plurality of treatment protocols; and sequentially providing a plurality of specific treatment programs included in the initial treatment protocol to the user terminal according to the treatment week set for each of the plurality of specific treatment programs. [Effects of the Invention]

[0060] As described above, the method and system for providing digital-based musculoskeletal rehabilitation therapy according to the present invention can provide a patient with an exercise plan for musculoskeletal rehabilitation therapy through an application based on prescription information including an exercise plan assigned to the patient from a doctor's terminal.

[0061] In particular, the method and system for providing digital-based musculoskeletal rehabilitation treatment according to the present invention can play exercise videos corresponding to each of a plurality of exercise items constituting an exercise list on a user terminal running an application. As a result, even if a doctor and a patient do not meet in person for rehabilitation treatment of a musculoskeletal disorder, the doctor can prescribe the treatment to the patient, and the patient can undergo rehabilitation through an exercise plan according to the doctor's prescription. This eliminates spatial, time, and financial constraints on musculoskeletal rehabilitation treatment and improves accessibility to exercise treatment.

[0062] Furthermore, the method and system for providing digital-based musculoskeletal rehabilitation therapy according to the present invention can provide an evaluation page for evaluating exercise items based on whether the playback level of an exercise video satisfies a preset standard, and can update the exercise plan based on the evaluation information received through the evaluation page. This allows patients to perform exercise plans, provide appropriate feedback, and receive customized rehabilitation therapy with the feedback applied. In particular, patients can receive customized rehabilitation exercise therapy by adjusting the difficulty of exercise items according to their own condition and excluding exercise items that are difficult for the patient.

[0063] Furthermore, the digital-based musculoskeletal rehabilitation treatment delivery method and system of the present invention can provide patients with cognitive behavioral treatment plans in conjunction with rehabilitation exercise plans, thereby providing treatment for not only the rehabilitation area but also mental health.

[0064] In particular, the digital-based musculoskeletal rehabilitation therapy providing method and system according to the present invention can receive questionnaire response data for multiple questionnaires via a user terminal and detect patient condition information related to the patient's pain duration and the degree of cognitive distortion based on the questionnaire response data. Furthermore, a treatment protocol for cognitive behavioral therapy customized for the patient can be provided based on the patient's condition information. As a result, rather than providing a patient with a uniform cognitive behavioral therapy for a musculoskeletal disorder, the rehabilitation therapy providing method and system according to the present invention can provide a patient with a behavioral treatment program customized for the same musculoskeletal disorder, taking into account the patient's pain duration and the degree of cognitive distortion. Furthermore, patients can receive cognitive behavioral therapy customized to their own condition.

[0065] Furthermore, the digital-based musculoskeletal rehabilitation therapy delivery method and system according to the present invention can sequentially deliver multiple treatment programs in conjunction with exercise plans during the rehabilitation period, allowing patients to systematically receive cognitive behavioral therapy along with rehabilitation exercises and complete the rehabilitation therapy without interruption.

[0066] Furthermore, the digital-based musculoskeletal rehabilitation treatment provision method and system according to the present invention updates the treatment program to be useful for the patient's cognitive behavioral treatment based on treatment response data collected during the progress of the cognitive behavioral treatment. This makes it possible to provide an updated cognitive behavioral treatment that takes into account the patient's improvement status, rather than continuously providing the patient with an initially determined cognitive behavioral treatment method. [Brief explanation of the drawings]

[0067] [Figure 1] 1 is a conceptual diagram illustrating a digital-based musculoskeletal rehabilitation treatment delivery system according to the present invention. [Figure 2a] 1 is a conceptual diagram for explaining a digital-based musculoskeletal rehabilitation treatment method according to the present invention. FIG. [Figure 2b]1 is a conceptual diagram for explaining a digital-based musculoskeletal rehabilitation treatment method according to the present invention. FIG. [Figure 2c] 1 is a conceptual diagram for explaining a digital-based musculoskeletal rehabilitation treatment method according to the present invention. FIG. [Figure 3] 1 is a flow chart illustrating a method for providing digital-based musculoskeletal rehabilitation therapy according to the present invention. [Figure 4] FIG. 1 is a conceptual diagram illustrating a method for providing musculoskeletal rehabilitation therapy and cognitive behavioral therapy in cooperation with each other in the present invention. [Figure 5a] This is a concept to explain how the present invention provides patients with a customized exercise plan for musculoskeletal rehabilitation therapy. [Figure 5b] This is a concept to explain how the present invention provides patients with a customized exercise plan for musculoskeletal rehabilitation therapy. [Figure 5c] This is a concept to explain how the present invention provides patients with a customized exercise plan for musculoskeletal rehabilitation therapy. [Figure 5d] This is a concept to explain how the present invention provides patients with a customized exercise plan for musculoskeletal rehabilitation therapy. [Figure 6] This is a concept to explain how the present invention provides patients with a customized exercise plan for musculoskeletal rehabilitation therapy. [Figure 7] This is a concept to explain how the present invention provides patients with a customized exercise plan for musculoskeletal rehabilitation therapy. [Figure 8a] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8b] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8c] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8d]1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8e] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8f] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8g] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8h] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8i] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8j] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8k] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8l] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 8m] 1 is a concept for illustrating a method of providing cognitive behavioral therapy in accordance with the present invention. [Figure 9a] This is a concept for explaining a method for providing an AI function evaluation service in the present invention. [Figure 9b] This is a concept for explaining a method for providing an AI function evaluation service in the present invention. [Figure 10] 1 is a concept for explaining a rehabilitation treatment report provided by 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

[0068] 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.

[0069] 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.

[0070] 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.

[0071] The singular expression includes the plural expression unless the context clearly dictates otherwise.

[0072] 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.

[0073] The present invention relates to a method and system for providing digital-based rehabilitation therapy and cognitive behavioral therapy linked to the rehabilitation therapy to patients with musculoskeletal disorders, and in particular to a method and system for providing customized rehabilitation therapy according to the patient's indications. According to the present invention, a doctor (or medical staff) provides an exercise plan corresponding to the patient's indications, and the user can perform the exercise plan and provide feedback to the system of the present invention. The system of the present invention can appropriately update the exercise plan to reflect the patient's feedback, thereby guiding the system to maximize the therapeutic effect according to the patient's indications.

[0074] Here, an indication is a symptom or clinical situation that requires a specific treatment or examination, and can be understood as a patient's disease or symptom, etc. Furthermore, an indication can be understood as a patient's disease or symptom that requires treatment or rehabilitation.

[0075] The present invention can provide at least one of rehabilitation therapy and cognitive behavioral therapy for rehabilitation treatment of musculoskeletal patients.

[0076] For the sake of convenience, the present invention will be described mainly with reference to "musculoskeletal disorders," but is not necessarily limited to this. That is, the rehabilitation treatment described in the present invention can include treatment for patients with various diseases (e.g., cancer, diabetes, hypertension, etc.) as well as patients who require rehabilitation treatment due to musculoskeletal disorders.

[0077] Hereinafter, a method and system for providing a digitally-based customized rehabilitation therapy method for musculoskeletal patients will be specifically discussed with reference to the accompanying drawings. Figure 1 is a conceptual diagram for explaining a digitally-based musculoskeletal rehabilitation therapy delivery system according to the present invention. Figures 2a, 2b, and 2c are conceptual diagrams for explaining a digital-based musculoskeletal rehabilitation treatment method according to the present invention, Figure 3 is a flowchart for explaining a method for providing digital-based musculoskeletal rehabilitation treatment according to the present invention, Figure 4 is a conceptual diagram for explaining a method for providing musculoskeletal rehabilitation treatment and cognitive behavioral treatment in collaboration according to the present invention, Figures 5a, 5b, 5c, 5d, 6, and 7 are concepts for explaining a method for providing a patient with a customized exercise plan for musculoskeletal rehabilitation treatment according to the present invention, Figures 8a, 8b, 8c, 8d, 8e, 8f, 8g, 8h, 8i, 8j, 8k, 8l, and 8m are concepts for explaining a method for providing cognitive behavioral treatment according to the present invention, Figures 9a and 9b are concepts for explaining a method for providing an AI functional assessment service according to the present invention, and Figure 10 is a concept for explaining a rehabilitation treatment report provided by the present invention.

[0078] As shown in FIG. 1, a digital-based musculoskeletal rehabilitation therapy delivery system (hereinafter referred to as "rehabilitation therapy delivery system") 100 according to the present invention can be embodied as an application or software.

[0079] In accordance with software implementations of the rehabilitation therapy delivery system 100 of the present invention, the sequences, functions, and other aspects described herein may be implemented as separate software therapy modules, each capable of performing one or more of the functions and operations described herein.

[0080] The rehabilitation treatment providing system 100 implemented as software may be downloaded to the user terminal 10 through a program (e.g., a Play Store) that allows applications to be downloaded, or may be implemented by an initial installation program on the user terminal 10. In this case, the communication unit 110, the storage unit 120, and the control unit 130 according to the present invention may be utilized as components of the user terminal 10.

[0081] In the present invention, the terminal 10 is also named a "mobile terminal" or an "electronic device", and the terminals described in this specification may include mobile phones, smartphones, laptop computers, digital broadcasting terminals, personal digital assistants (PDAs), portable multimedia players (PMPs), navigation systems, slate PCs, tablet PCs, ultrabooks, wearable devices such as smart watches, smart glasses, and head mounted displays (HMDs).

[0082] Meanwhile, the rehabilitation treatment delivery system 100 may exist within a server (hereinafter referred to as the server) constructed separately from the user terminal 10 for a specific purpose (e.g., a function related to the provision of rehabilitation treatment), or may exist as a system separate from the server. When the rehabilitation treatment delivery system 100 exists within the server, musculoskeletal rehabilitation treatment services can be provided by at least one of the components of the communication unit 110, storage unit 120, and control unit 130 located within the server, or by a component module performing a function similar to each of the components. In this case, an application can communicate with the server to provide services related to musculoskeletal rehabilitation treatment on the user terminal 10 on which the application is installed. Furthermore, the rehabilitation treatment delivery system 100 according to the present invention can provide the rehabilitation treatment delivery method according to the present invention to the user terminal 10 in conjunction with an external server.

[0083] Meanwhile, the rehabilitation treatment provision system 100 according to the present invention can provide rehabilitation treatment and cognitive behavioral treatment services to a patient based on a doctor's prescription for the patient, and can provide customized rehabilitation treatment to the patient based on the patient's feedback on the rehabilitation treatment.

[0084] As shown in FIG. 2(a), the present invention can receive prescription information prescribed by doctor D for rehabilitation treatment of a musculoskeletal patient from a doctor terminal 20. In the present invention, rehabilitation treatment and cognitive behavioral treatment services can be provided via a user terminal 10 on which an application is installed, based on the prescription information received from the doctor terminal 20. A patient U can receive cognitive behavioral treatment by running the application on the user terminal 10 and performing rehabilitation exercises while watching the provided exercise video (see FIG. 2(b)). Furthermore, the present invention can provide an evaluation service that allows a patient U who has completed rehabilitation treatment to evaluate the rehabilitation treatment and an analysis service of the patient's exercise movements (see FIG. 2(c)). Furthermore, the present invention can provide a patient with customized rehabilitation treatment by updating the rehabilitation treatment provided to the patient based on the patient's feedback on the rehabilitation treatment (see FIG. 2(d)).

[0085] In this way, the rehabilitation treatment delivery system 100 according to the present invention can provide customized musculoskeletal rehabilitation treatment services to patients by continuously updating the rehabilitation treatment provided to the patients based on the patients' feedback.

[0086] Therefore, the rehabilitation treatment provision system 100 of the present invention may be named a "digital rehabilitation treatment solution," a "digital rehabilitation exercise solution," a "non-face-to-face rehabilitation treatment solution," a "non-face-to-face rehabilitation exercise solution," a "mobile rehabilitation treatment program," a "mobile rehabilitation exercise program," and an "application for digital treatment purposes for skeletal system patients," etc.

[0087] Meanwhile, patient U can perform rehabilitation exercises according to the exercise plan prescribed by the doctor through the application or web page provided by the rehabilitation treatment provision system 100 of the present invention, and can evaluate the exercise plan after the rehabilitation exercises.

[0088] At this time, the patient U may have a user account registered in the rehabilitation treatment providing system 100 according to the present invention. For convenience of explanation, in this specification, the account of a patient user will be referred to as a "patient account (or user account)."

[0089] As described above, an "account" may be created through a page associated with the rehabilitation therapy delivery system 100. Alternatively, an "account" may be created in at least one other system associated with the rehabilitation therapy delivery system 100 of the present invention.

[0090] Therefore, in this specification, regardless of the system to which the account is issued, any account based on the rehabilitation treatment provision system 100 of the present invention will be referred to as an "account pre-registered in the rehabilitation treatment provision system 100 of the present invention."

[0091] Meanwhile, a doctor (Doctor) can prescribe rehabilitation treatment to a musculoskeletal patient U via the doctor terminal 20. In this case, the doctor D may have a user account registered in the rehabilitation treatment providing system 100 according to the present invention. For the sake of convenience, the account of a doctor user will be referred to as a "doctor account" in this specification. Furthermore, the user terminal logged in with the doctor's account will be referred to as the doctor terminal 20 in the following description.

[0092] Hereinafter, a rehabilitation treatment providing system 100 according to the present invention will be described with reference to an embodiment in which the system is implemented as an application on a user terminal 10.

[0093] 1, a digital-based musculoskeletal rehabilitation therapy delivery system 100 according to the present invention may be configured to include at least one of a communication unit 110, a storage unit 120, and a control unit 130. In this case, the rehabilitation therapy delivery system 100 according to the present invention is not limited to the above-mentioned components, and may further include components that perform the same functions as the devices described in this specification.

[0094] The communication unit 110 may include one or more communication modules that enable wireless or wired communication between the rehabilitation therapy delivery system 100 and the user terminal 10, or between the rehabilitation therapy delivery system 100 and an external server. The communication unit 110 may also include one or more communication modules that connect the rehabilitation therapy delivery system 100 to one or more networks.

[0095] Specifically, the communication unit 110 can receive an exercise plan assigned to a patient account so that the patient U can perform rehabilitation exercises according to the exercise plan assigned to the patient. The communication unit 110 can also receive patient evaluation data for the exercise plan based on the patient's rehabilitation exercises according to the exercise plan. The communication unit 110 can also receive a customized exercise plan updated based on the patient's evaluation data and provide the updated exercise plan to the user terminal 10.

[0096] The storage unit 120 may also be referred to as a database (DB) and may be configured to store exercise plan history information, including exercise plans assigned to patients, patient evaluation data for the exercise plans, and exercise plans updated with the evaluation data.

[0097] Furthermore, the storage unit 120 may be configured to store matching information 700 in which exercise movements, difficulty information of the exercise movements, and exercise videos are matched for each rehabilitation part (e.g., shoulder, elbow, wrist & hand, hip & pelvis, knee, ankle & foot, neck, back, waist, abdomen) for the treatment of an indication (see FIG. 7).

[0098] Furthermore, the rehabilitation treatment providing system 100 according to the present invention can utilize data stored in an external storage device separate from the storage unit 120, and such external storage device can also be expressed as a "database."

[0099] Meanwhile, the control unit 130 can control the overall operation of the rehabilitation treatment providing system 100 according to the present invention.

[0100] 1, the control unit 130 can control to output a page (or service page 300) for providing musculoskeletal rehabilitation treatment services via a display unit (or touch screen) provided in the user terminal 10. Such page 300 can be output on the user terminal 10 via an application or web page installed on the user terminal 10.

[0101] The page 300 is a page linked to the rehabilitation treatment delivery system 100 according to the present invention, and is configured to be controlled by the rehabilitation treatment delivery system 100 according to the present invention.

[0102] Furthermore, if the page 300 is provided in the form of an application, the page 300 can be controlled by a CPU (Central Processing Unit) of the user terminal 10 in which the application is installed. In this case, the CPU of the user terminal 10 can provide the patient with services related to musculoskeletal rehabilitation therapy based on information provided by the musculoskeletal rehabilitation therapy system 100 according to the present invention.

[0103] The components of the rehabilitation therapy delivery system 100 according to the present invention have been discussed above. A method for providing customized musculoskeletal rehabilitation therapy services to patients based on the above components will now be described.

[0104] As shown in FIG. 3, the method for providing rehabilitation therapy according to the present invention can perform a process of determining an exercise plan to be provided to a patient based on prescription information including an exercise plan for the patient being assigned from a doctor terminal (S310).

[0105] In the present invention, as shown in FIG. 2b, an exercise prescription page (or exercise assignment page) 21 including a prescription function for rehabilitation exercises for musculoskeletal patients can be provided on a doctor terminal 20 logged in with a doctor account.

[0106] The exercise prescription page 21 may be controlled by a server configured to provide rehabilitation therapy services. The rehabilitation therapy delivery system 100 according to the present invention may exist inside the server, or may exist as a separate system 100 from the server and be connected via communication. That is, the present invention will be described as being performed in the rehabilitation exercise therapy delivery system 100 without separating the physical space in which the process for providing musculoskeletal rehabilitation therapy services is performed. Furthermore, the process for providing musculoskeletal rehabilitation therapy services will be described as being performed by the communication unit 110, storage unit 120, and control unit 130 according to the present invention.

[0107] Meanwhile, the control unit 130 can provide an exercise prescription page 21 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.

[0108] For example, in the present invention, it is assumed that a first patient account (e.g., patient account of "Song Jin-gyu") and a second patient account (e.g., patient account of "Kim So-hee") are matched with a specific doctor D account. The control unit 130 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 "Song Jin-gyu") from the doctor terminal 20.

[0109] The control unit 130 can allocate 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.

[0110] The prescription information may include various information related to providing a rehabilitation exercise plan to a musculoskeletal patient. For example, the prescription information may include at least one of: i) information about indications (e.g., information about pain disorders), ii) information about the rehabilitation site of the musculoskeletal patient (e.g., shoulder, elbow, wrist and hand, hip and pelvis, knee, ankle and foot, neck, back, waist, and abdomen), iii) rehabilitation period information (e.g., 1 week, 4 weeks, or 8 weeks), iv) rehabilitation exercise items that the musculoskeletal patient should perform for rehabilitation (e.g., "stretch your calves with your hands against the wall" or "sit and roll a ball to massage the soles of your feet"), vi) difficulty information about the rehabilitation exercise items, vi) duration information about the rehabilitation exercise items (e.g., maintain for 10 seconds), vii) number of repetitions of the rehabilitation exercise items (e.g., repeat 5 times), viii) information about the number of repetition sets of the rehabilitation exercise items, ix) precaution information (e.g., "please apply ice after exercise"), and x) exercise equipment information (see FIG. 4).

[0111] Furthermore, the prescription information may further include information about a digital therapeutic. As shown in FIG. 2b, exercise prescription page 21 may include items 22, 23, and 24 representing digital therapeutics corresponding to different indications (e.g., patellofemoral pain syndrome, patellofemoral arthritis, chronic lower back pain, etc.). In the present invention, a specific digital therapeutic may be selected from physician terminal 20 according to the patient's indication. In the present invention, a digital therapeutic may also be understood as an "exercise plan" for the indication corresponding to the digital therapeutic. A plurality of different exercise plans may be stored in storage unit 120 according to the present invention, and each exercise plan may correspond to a digital therapeutic matched to a different indication. In other words, a digital therapeutic in the present invention may refer to an exercise plan for treating an indication. Therefore, selecting a digital therapeutic item 22 for treating a specific indication (e.g., a digital therapeutic item for treating patellofemoral pain syndrome) on exercise prescription page 21 may mean that an exercise plan for treating patellofemoral pain syndrome is selected as a prescription for the patient.

[0112] 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.

[0113] Meanwhile, the control unit 130 can select (or identify) an exercise plan to be provided to the patient based on the prescription information assigned to the patient from the doctor terminal 20. That is, as described above, the control unit 130 can select an exercise plan corresponding to the digital therapeutic agent selected from the doctor terminal 20 as the exercise plan to be provided to the patient.

[0114] Meanwhile, an exercise plan corresponding to each digital therapeutic may have at least one exercise item assigned to each of the days or weeks constituting the rehabilitation period. That is, an exercise plan corresponding to a digital therapeutic may have predetermined exercise items for treating an indication for which the digital therapeutic is used. The exercise items constituting each exercise plan may be selected by an expert, a group of experts, or an artificial intelligence algorithm as being effective for treating an indication targeted by the digital therapeutic according to the respective exercise plan. The rehabilitation period may be preset and stored in the system 100, or may be included in prescription information received from the doctor terminal 20. For convenience of explanation, the following description will be given assuming that a rehabilitation period of "8 weeks" is set.

[0115] The exercise plan may be composed of at least one different rehabilitation exercise item for each of multiple days that make up the rehabilitation period. For example, the first day of the exercise plan may be composed of a first exercise item and a second exercise item, and the second day may be composed of a first exercise item and a third exercise item.

[0116] Furthermore, the exercise plan may be composed of at least one different rehabilitation exercise item for each of the multiple weeks that make up the rehabilitation period. In this case, the exercise plan may include the same rehabilitation exercise item on multiple days (e.g., Monday to Sunday) that make up the same week. For example, the first week of the exercise plan (Monday to Sunday of the first week) may be composed of the first exercise item and the second exercise item, and the second week (Monday to Sunday of the second week) may be composed of the first exercise item and the third exercise item.

[0117] Meanwhile, the control unit 130 may assign a cognitive behavioral treatment plan 220 to the patient account during a pre-set rehabilitation period in conjunction with the exercise plan 210 so that cognitive behavioral treatment is provided in conjunction with the rehabilitation treatment for the musculoskeletal patient.

[0118] For example, as shown in Fig. 4, the control unit 130 can assign a weekly exercise plan 210 and a cognitive behavioral treatment plan 220 to each of a plurality of treatment weeks constituting a rehabilitation period. During the first week of the rehabilitation period, the control unit 130 can implement the exercise plan 211 and the cognitive behavioral treatment plan 221 assigned to the first week in conjunction with each other, and during the second week of the rehabilitation period, the control unit 130 can implement the exercise plan 212 and the cognitive behavioral treatment plan 222 assigned to the second week in conjunction with each other. Cognitive behavioral treatment will be described in detail below.

[0119] In this manner, the control unit 130 can set the cognitive behavioral treatment plan 220 to correspond to the preset rehabilitation period corresponding to the exercise plan 210. For example, if the preset rehabilitation period corresponding to the exercise plan 210 is eight weeks, the treatment period according to the cognitive behavioral treatment plan 220 may also be set to eight weeks. Conversely, if the preset rehabilitation period corresponding to the exercise plan 210 is six weeks, the treatment period according to the cognitive behavioral treatment plan 220 may also be set to six weeks. Meanwhile, the control unit 130 can configure the preset rehabilitation period corresponding to the exercise plan 210 and the treatment period according to the cognitive behavioral treatment plan 220 independently of each other depending on the situation. For example, the rehabilitation period according to the exercise plan 210 may be set to six weeks, and the treatment period according to the cognitive behavioral treatment plan 220 may be set to eight weeks.

[0120] Meanwhile, in the present invention, the process of executing the application can be performed on the user terminal where the patient account is logged in (S320, see FIG. 3).

[0121] The control unit 130 may check whether the exercise plan assigned to the patient account is activated based on the execution of the application. The exercise plan assigned to the patient account may be an exercise plan corresponding to the digital therapeutic agent selected on the doctor terminal 20.

[0122] Here, "activating an exercise plan" can be understood as a state in which rehabilitation exercise services can be provided according to an exercise plan.

[0123] If the exercise plan assigned to the patient account is in an inactive state, the control unit 130 may control the exercise plan to be activated based on the execution of the application.

[0124] For example, the control unit 130 may control the activation of an exercise plan assigned to a patient account based on the patient account being logged in through the executed application. As another example, the control unit 130 may provide an icon (e.g., "Kim Ji-seok, would you like to start rehabilitation exercises?") associated with the activation of an exercise plan assigned to a patient account on the screen of the user terminal 10 through the executed application. In addition, the control unit 130 may control the activation of an exercise plan assigned to a patient account based on the selection of the icon.

[0125] Meanwhile, as shown in FIG. 2c, the patient can check the digital therapeutic prescribed to them through the executed application. Information 31 and 32 about the digital therapeutic prescribed to the patient may be provided on page 30 of the application. Meanwhile, if multiple digital therapeutics are selected for the patient, the patient can select the digital therapeutic for which they wish to receive rehabilitation treatment. In this case, the control unit 130 can provide the user terminal 10 with an exercise plan that matches the selected digital therapeutic.

[0126] Meanwhile, the control unit 130 may count the rehabilitation period matched to the exercise plan based on the activation of the exercise assigned to the patient account.

[0127] In the present invention, the day when the rehabilitation period begins to be counted may be referred to as the "start date" or "baseline date" of the rehabilitation exercise. For example, in the present invention, the baseline date may be counted as the first day, and the day after the baseline date may be counted as the second day. As another example, in the present invention, the seven days including the baseline date may be referred to as the first week, and the seven days following the first week may be referred to as the second week.

[0128] Meanwhile, as shown in FIG. 5a (a), the control unit 130 can provide an initial screen page 300 on the user terminal 10 based on the execution of an application.

[0129] The initial screen page 300 may be configured to include at least one of a plurality of first to fourth menu items 310 to 340 associated with the provision of different services.

[0130] The first menu item 310 may be configured to link to a rehabilitation exercise information page 600 that provides rehabilitation exercise services according to an exercise plan assigned to the patient account.

[0131] 5a(b), the control unit 130 can provide a rehabilitation exercise information page 600 including an exercise list 610 according to the exercise plan on the user terminal 10 based on the selection of the first menu item 310 on the user terminal 10. Therefore, in the present invention, the first menu item 310 can be understood as being associated with a function of accessing the exercise list according to the exercise plan.

[0132] The second menu item 320 may be configured to be linked to an access function to an evaluation page (see reference numerals 710 to 730 in FIG. 5b) that provides an evaluation service for the exercise plan assigned to the patient account. The control unit 130 may control so that the second menu item 320 is activated based on whether the patient's rehabilitation exercise execution level (or exercise video playback level) satisfies a preset criterion. Meanwhile, the control unit 130 may be configured so that, even if the second menu item 320 is selected on the user terminal 10, provision of the evaluation pages 710 to 730 on the user terminal 10 is limited (i.e., deactivated) if the patient's rehabilitation exercise execution level (or exercise video playback level) does not satisfy the preset criterion.

[0133] The third menu item 330 may be configured to link to a cognitive behavioral treatment page (see FIG. 8a, reference numeral 800) that provides the cognitive behavioral treatment plan assigned to the patient account. Cognitive behavioral treatment plans are described in more detail below.

[0134] Furthermore, the fourth menu item 340 may be configured to link with a function evaluation page (or a movement analysis page, see reference numeral 900 in FIG. 9 ) that performs a function evaluation for a specific movement of the patient. In the present invention, an artificial intelligence model trained from learning data can be used to analyze the patient's posture and movement for a specific movement movement from the patient's exercise video. Therefore, in the present invention, the functional evaluation that evaluates the patient's posture and movement for a movement item can be named "AI (Artificial Intelligence) functional evaluation."

[0135] On the other hand, in the present invention, in order to confirm the patient's improvement in response to rehabilitation exercise (or the effect of rehabilitation exercise), the patient can be guided to undergo AI functional evaluation for a specific movement.

[0136] The control unit 130 can control the inclusion of the fourth menu item 340 on the initial screen page 300 on a specific day corresponding to a preset interval of days (e.g., "2 weeks") so that AI function evaluation for a specific movement is performed at preset intervals of days (e.g., "2 weeks") during a preset rehabilitation period (e.g., "8 weeks") to which an exercise plan is assigned.

[0137] In this way, in the present invention, various services provided by the present invention can be provided on the user terminal 10 based on the selection of any one of the multiple menu items 310 to 340 that make up the initial screen page 300.

[0138] Meanwhile, in the present invention, a process of providing an exercise list according to an exercise plan to a user terminal on which an application is executed can be performed (S330, see FIG. 3).

[0139] The control unit 130 can provide a rehabilitation exercise information page 600 including an exercise list 610 on the user terminal 10 based on the selection of the first menu item 310 on the initial screen page 300 .

[0140] 5a(b), the exercise list 610 may include multiple rehabilitation exercise items 611-616 assigned to specific days for which the exercise list 610 is provided, based on a reference date on which counting of the rehabilitation period began. For example, if the patient's rehabilitation exercise execution date corresponds to "day 23" based on the reference date, the exercise list 610 may include exercise items 611-616 assigned to "day 23" among the multiple days that make up the exercise plan matched to the patient account.

[0141] Furthermore, based on the exercise plan assigned to the patient account, the control unit 130 can arrange a specific exercise item repeatedly by the number of sets on the exercise list 610. For example, if three sets of the "Straight Leg Raise 1" exercise item are assigned to the exercise plan, the control unit 130 can arrange three exercise items 611, 612, and 613 corresponding to "Straight Leg Raise 1" on the exercise list 610.

[0142] Furthermore, the control unit 130 can arrange multiple exercise items 611 to 616 in order on the exercise list 610 based on the exercise plan assigned to the patient account. The control unit 130 can arrange the first exercise items 611 to 613 corresponding to the highest priority exercise order in the upper row of the exercise list 610, and arrange the second exercise item 614 corresponding to the next exercise order below the first exercise item.

[0143] Meanwhile, in the present invention, a process of playing back exercise videos corresponding to a plurality of exercise items, respectively, according to a plurality of exercise items constituting an exercise list can be performed on the user terminal (S340, see FIG. 3).

[0144] Based on the patient's request to start rehabilitation exercise, the control unit 130 can sequentially play back on the user terminal 10 exercise videos corresponding to each of the exercise items 611 to 616 in accordance with the order of the exercise items 611 to 616 arranged in the exercise list 610. For example, as shown in (b) of FIG. 5a, based on the user's selection of the "Start Exercise" icon included in the rehabilitation exercise information page 600, the control unit 130 can play back on the user terminal 10 exercise videos corresponding to each of the multiple exercise items 611 to 616.

[0145] 7, exercise videos 710b, 720b, 730b, and 740b corresponding to each exercise item may be stored in the storage unit 120. The control unit 130 may load the exercise videos corresponding to the exercise items from the storage unit 120 and output them on the user terminal 10.

[0146] Meanwhile, in the present invention, a process of providing an evaluation page for evaluating the exercise item based on whether the playback level of the exercise video meets a preset standard can be performed (S350, see FIG. 3).

[0147] As described above, the present invention can receive feedback from the patient regarding the exercise plan, and update and provide the exercise plan based on the feedback, so that a customized exercise plan can be provided for each patient.

[0148] The control unit 130 can monitor whether the patient has performed the rehabilitation exercises in order to receive feedback on the exercise plan from the patient who has actually performed the rehabilitation exercises according to the exercise plan assigned to the patient account. Furthermore, if the control unit 130 determines as a result of monitoring that the patient has actually performed the rehabilitation exercises, it can provide evaluation pages 710 to 730 for receiving evaluation information on the rehabilitation exercises performed by the patient.

[0149] Specifically, when exercise videos corresponding to the plurality of exercise items 611 to 616 included in the exercise list 610 are played on the user terminal 10, the control unit 130 can monitor the playback level of the exercise videos to determine the patient's rehabilitation exercise execution rate (or rehabilitation exercise execution level). Furthermore, the control unit 130 can provide evaluation pages 710 to 730 on the user terminal 10 based on whether the playback level of the exercise videos meets a preset standard.

[0150] The control unit 130 may determine the playback level of the exercise video and whether to provide an evaluation page based on at least one of the playback time of the exercise video and the number of exercise items corresponding to the played exercise video.

[0151] The control unit 130 can determine whether to provide the evaluation pages 710 to 730 depending on whether the playback time of the exercise video exceeds a preset reference playback time.

[0152] The control unit 130 may decide to provide the evaluation pages 710 to 730 (or activate the evaluation pages) if the playback time of the exercise video exceeds a preset reference playback time, and may decide not to provide the evaluation pages 710 to 730 (or deactivate the evaluation pages) if the playback time of the exercise video does not exceed a preset reference playback time.

[0153] In this case, the control unit 130 may set the reference playback time, which is the basis for providing the evaluation pages 710, 720, and 730, to be different from each other based on the overall playback time (or total playback time) of the exercise videos corresponding to the multiple exercise items 611 to 616 included in the exercise list.

[0154] Specifically, the control unit 130 may set the reference playback time to a time corresponding to a certain range (or ratio) of the overall playback time so that the reference playback time is proportional to the overall playback time (or total playback time) of the exercise videos corresponding to the multiple exercise items 611 to 616 included in the exercise list.

[0155] Meanwhile, the control unit 130 may determine whether to provide the evaluation pages 710 to 730 depending on whether the number of exercise items corresponding to the played exercise video (hereinafter referred to as the "number of played exercise items") exceeds a predetermined reference number of plays.

[0156] The control unit 130 may decide to provide the evaluation pages 710 to 730 (or activate the evaluation pages) if the number of played exercise items exceeds a predetermined reference number of plays, and may decide not to provide the evaluation pages 710 to 730 (or deactivate the evaluation pages) if the number of played exercise items does not exceed a predetermined reference number of plays.

[0157] In this case, the control unit 130 may set the reference number of plays, which is the criterion for providing the evaluation pages 710 to 730, to be different from each other based on the total number (or total number) of the multiple exercise items 611 to 616 included in the exercise list.

[0158] Specifically, the control unit 130 may set the reference number of plays to a number corresponding to a certain range (or ratio) of the total number of the multiple exercise items 611 to 616 included in the exercise list, so that the reference number of plays is proportional to the total number (or total number) of the multiple exercise items 611 to 616 included in the exercise list.

[0159] That is, the control unit 130 may set different evaluation page provision criteria (standard playback time or standard number of playbacks) for each specific day corresponding to the patient's rehabilitation exercise execution date based on the multiple exercise items assigned to the specific day.

[0160] Meanwhile, when it is determined that the evaluation pages 710 to 730 are to be provided, the control unit 130 may control the second area 320 associated with the evaluation pages to be activated on the initial screen page 300 (see (a) of FIG. 5a). For example, the control unit 130 may display the second area 320 on the initial screen page 300 based on the determination that the evaluation pages are to be provided.

[0161] 5a(c), a pop-up 602 associated with the evaluation page may be provided on the user terminal 10 based on a decision to provide the evaluation pages 710-730. For example, the control unit 130 may provide the pop-up 620 on the user terminal 10 based on the completion of playback of all videos corresponding to the plurality of exercise items 611-616 included in the exercise list 610. Furthermore, the control unit 130 may provide the evaluation pages 710-730 on the user terminal 10 based on the selection of an icon (e.g., "Go to self-check") 620a included in the pop-up 620.

[0162] On the other hand, the evaluation pages 710 to 730 may be configured with a plurality of evaluation areas so that evaluations are made for a plurality of evaluation categories for a plurality of exercise items assigned to a specific day.

[0163] Here, the "evaluation category" refers to a category that is the subject of evaluation for an exercise plan so that a customized rehabilitation exercise plan can be provided taking into account the condition of the musculoskeletal patient, and may include, for example, at least one of the exercise difficulty for the exercise item, high-difficulty exercise items (difficult exercise items), and pain after rehabilitation exercise.

[0164] The control unit 130 can configure the evaluation page to include evaluation areas corresponding to each of a plurality of evaluation categories. In this case, the plurality of evaluation areas may be arranged on the same page, or may be arranged on different evaluation pages 710, 720, and 730, as shown in FIG. 5b. Therefore, the terms "evaluation page" and "evaluation area" in the present invention may be used interchangeably. In the present invention, the "evaluation areas" are described using the same reference numerals "710 to 730" as the "evaluation page."

[0165] The control unit 130 may configure the first evaluation area 710 so that the exercise difficulty levels for the multiple exercise items assigned to a specific day are evaluated.

[0166] As shown in (a) of Figure 5b, the control unit 130 may include, in the first evaluation area 710, question information asking about the exercise difficulty (e.g., "How was the exercise intensity today?"), guidance information informing the user that the exercise plan will be updated based on the exercise difficulty evaluation information (e.g., "The exercise structure and difficulty will be adjusted based on the information you have entered"), and an evaluation information input area (hereinafter referred to as the "first input area") 710a for receiving the exercise difficulty evaluation information.

[0167] The control unit 130 may include a slider corresponding to a preset exercise difficulty scale in the first input area 710a. In addition, the control unit 130 may control the output of an emotion graphic object and emotion information corresponding to the exercise difficulty specified by the slider in the first evaluation area 710 in conjunction with the slider.

[0168] For example, when the exercise difficulty level specified by the slider is the "lowest difficulty level (e.g., 0 points)," the control unit 130 may output a "smile" emotional graphic object and emotional information of "it feels like I didn't exercise" on the first evaluation area 710. As another example, when the exercise difficulty level specified by the slider is the "highest difficulty level (e.g., 9 points)," the control unit 130 may output a "frown" emotional graphic object and emotional information of "it was difficult to imitate the exercise" on the first evaluation area 710.

[0169] The patient can intuitively recognize the range of exercise difficulty scores from the lowest to the highest using the slider in the first evaluation area 710. In addition, the patient can input evaluation information while visually checking the difficulty of the rehabilitation exercise as perceived by the patient through the graphic objects and emotional information displayed in conjunction with the slider.

[0170] Furthermore, the control unit 130 can receive exercise difficulty level evaluation information from the first evaluation area 710 based on the evaluation information being input to the first evaluation area 710.

[0171] On the other hand, as shown in (b) of Figure 5b, the control unit 130 may include, in the second evaluation area 720, question information asking about exercise items of high difficulty exercise (e.g., "Please tell us which movements are painful or inconvenient"), guidance information informing the user that the exercise plan will be updated based on the evaluation information of the exercise items of high difficulty exercise (e.g., "The exercise structure and difficulty will be adjusted based on the information you have entered"), and an input area for selecting high difficulty exercise items (hereinafter referred to as the "second input area").

[0172] Furthermore, the control unit 130 can control the second input area of ​​the second evaluation area 720 to include multiple check items 721a to 726a for inputting the user's selection for a highly difficult exercise item (a difficult exercise item) among the multiple exercise items 611 to 616 assigned to a specific day (e.g., "the 23rd day").

[0173] The control unit 130 may associate one of the multiple check items (e.g., "There were no inconvenient movements") 721a with an option that does not select any of the multiple exercise items 611-616 assigned to a specific day (e.g., "23rd day") as a high-difficulty exercise item. The control unit 130 may also associate the remaining check items 722a-726a with the multiple exercise items 611-616 assigned to a specific day (e.g., "23rd day"), and display information about the multiple exercise items 611-616 (e.g., thumbnails of videos corresponding to the exercise items or names of the exercise items).

[0174] The control unit 130 may receive evaluation information on the highly difficult exercise items according to the user's selection of the checkboxes included in the second evaluation area 720 .

[0175] 5b(c), the control unit 130 may include, in the third evaluation area 730, question information inquiring about exercise pain (e.g., "How much pain do you feel after the rehabilitation exercise?"), guidance information informing the user that the exercise plan will be updated based on the exercise pain evaluation information (e.g., "The exercise structure and difficulty will be adjusted based on the information you entered"), and an evaluation information input area (hereinafter referred to as the "third input area") 730a for receiving exercise pain evaluation information. The third evaluation area 730 may be configured similarly to the first evaluation area 710 except for the question information. Therefore, a detailed description will be omitted.

[0176] The control unit 130 can receive evaluation information on exercise pain through the third evaluation area 730.

[0177] On the other hand, in the present invention, an updated exercise plan can be provided to a patient by making changes such as changing the difficulty level of the exercise plan or excluding or adding at least some of the exercise items that make up the exercise plan based on the patient's evaluation information. Below, a method for updating an exercise plan based on evaluation information will be specifically described.

[0178] Based on the evaluation information for the highly difficult exercise items received from the second evaluation area 720 (hereinafter referred to as "second evaluation information"), the control unit 130 can update the exercise plan by changing (or replacing) the exercise items, such as excluding at least some of the exercise items included in the exercise plan assigned to the patient account or adding new exercise items.

[0179] In this case, the exercise items to be excluded or replaced may correspond to the exercise items assigned to the day after ("day 24 or later") a specific day ("day 23") among the multiple days (e.g., "8 weeks") that make up the rehabilitation period. That is, the control unit 130 can exclude or replace at least some of the exercise items from the day after the specific day based on the evaluation information for the specific day (especially the second evaluation information).

[0180] The control unit 130 may exclude a specific exercise item selected as a high-difficulty exercise from among the exercise items assigned to a specific day from the exercise plan for the day after the specific day. Furthermore, the control unit 130 may add (include) another exercise item in place of the excluded exercise item. Alternatively, the control unit 130 may exclude a specific exercise item selected as a high-difficulty exercise from among the exercise items assigned to a specific day from the exercise plan for another specific day (which may be the day after the specific day or another day) that is to be performed next after the specific day. In this case, too, the control unit 130 may add (include) another exercise item in place of the excluded exercise item.

[0181] More specifically, the control unit 130 may replace a specific exercise item selected as a high-difficulty exercise in the second evaluation area with another exercise item having the same difficulty level among the exercise items matched to the same rehabilitation part. Here, the other exercise item may be an exercise having the same or similar effect (e.g., rehabilitation effect) as the selected specific exercise item. Furthermore, the other exercise item may be an exercise that induces less pain than the selected specific exercise item. In this case, the effect and pain level of each exercise item may be determined based on information matched to each exercise item.

[0182] 7, a plurality of exercise items 710 to 750 may be stored in the storage unit 120, matched into the same group for each rehabilitation part (e.g., shoulder, elbow, wrist & hand, hip & pelvis, knee, ankle & foot, neck, back, waist, abdomen) or for each indication (e.g., patellofemoral pain syndrome, patellofemoral arthritis, chronic lower back pain, etc.). The exercise items included in the same group matched for each rehabilitation part may correspond to exercise items for the rehabilitation of a specific rehabilitation part.

[0183] Furthermore, the matching information 700 may include difficulty level information (e.g., "difficulty level 1 to difficulty level 3") 710a-750a of each exercise item matched to a specific rehabilitation part (e.g., "shoulder") 701, and different exercise duration information (or exercise repetition number information) for each exercise item. Also, the matching information 700 may include multiple exercise videos 711-714 that correspond to different exercise duration information (or exercise repetition number information) for each specific exercise item (e.g., "stand up and raise your arms to the sides and flip over") 710.

[0184] For example, the exercise duration information may include one of "5 seconds duration," "10 seconds duration," "15 seconds duration," or "20 seconds duration," and the exercise repetition count information may include one of "5 repetitions," "10 repetitions," "15 repetitions," or "20 repetitions." For convenience of explanation, the exercise duration will be used as an example below.

[0185] As shown in (a) of Figure 5c, assume that multiple exercise items 611 to 616 are assigned to a specific day ("Day 23"), and among these, the first exercise item (e.g., "Stand up and flip over with arms raised to the sides") 611 is selected as a high-difficulty exercise.

[0186] 7, the matching information 700 may include a specific exercise item 710 selected as a high-difficulty exercise, and other exercise items 720 to 750 that are matched to the same rehabilitation body part (e.g., "shoulder") 701. The control unit 130 can identify, among the other exercise items 720 to 750, another exercise item (e.g., "standing and raising both arms to the sides") 720 that has the same difficulty level information (e.g., level 1) 720a as the difficulty level information (e.g., level 1) 710a of the specific exercise item 710, as an alternative exercise item.

[0187] The control unit 130 can update the exercise plan assigned to the patient account by excluding exercise items selected as high-difficulty exercise and adding (or including new) alternative exercise items from the day after a certain date has passed (e.g., "day 24").

[0188] Also, as shown in (b) of FIG. 5c, the control unit 130 can provide the user terminal 10 with an exercise list 620 including exercise items 621 to 626 according to the updated exercise plan from the day after a specific day has passed (e.g., "the 24th day").

[0189] On the other hand, the control unit 130 may set the exercise intensity of the alternative exercise item to be the same as that of the specific exercise item selected as the high-difficulty exercise.

[0190] Here, "exercise intensity" may refer to exercise duration information (or exercise repetition number information) and the number of sets.

[0191] For example, if the exercise intensity of the exercise item 611 selected as a high-difficulty exercise is "10-second maintenance, 1 set," the control unit 130 may set the exercise intensity of the alternative exercise item 621 to "10-second maintenance, 1 set."

[0192] Meanwhile, the control unit 130 can update the exercise plan by adjusting (or changing) the difficulty level of each exercise item included in the exercise plan assigned to the patient account based on the evaluation information received from either the first evaluation area 710 or the third evaluation area 730.

[0193] In this case, the exercise items that are the subject of difficulty level adjustment may refer to the exercise items that are assigned to the day after ("day 24 or later") a specific day ("day 23") out of the multiple days that make up the rehabilitation period (e.g., "8 weeks"). In other words, the control unit 130 can change the difficulty level of the exercise items from the day after the specific day based on the evaluation information for the specific day.

[0194] The control unit 130 can determine one of decreasing the difficulty level (Down), maintaining the difficulty level, and increasing the difficulty level (Up) based on the evaluation information received from either the exercise difficulty evaluation information received from the first evaluation area 710 (hereinafter referred to as the first evaluation information) or the exercise pain evaluation information received from the third evaluation area 730 (hereinafter referred to as the third evaluation information).

[0195] The control unit 130 may determine a change in the difficulty level of an exercise item constituting an exercise plan based on either the first evaluation information or the third evaluation information. For example, the control unit 130 may determine a change in the difficulty level of an exercise item using the first evaluation information. The control unit 130 may also determine a change in the difficulty level of an exercise item using the third evaluation information. The control unit 130 may also determine a change in the difficulty level of an exercise item using an evaluation score (SCORE) calculated by summing or averaging the first evaluation information and the third evaluation information. For convenience of explanation, an example of determining a change in the difficulty level of an exercise item based on exercise difficulty evaluation information will be described below.

[0196] The control unit 130 can check whether the exercise difficulty evaluation information for the exercise item assigned to a specific day (e.g., "the 23rd") corresponds to one of the difficulty change criteria, such as decreasing the difficulty level, maintaining the difficulty level, increasing the difficulty level, or updating the exercise, and can decide whether to change the difficulty level of the exercise item assigned from the day after the specific day.

[0197] Specifically, the control unit 130 can decide to lower the difficulty level (Down) if the exercise difficulty evaluation information corresponds to the first difficulty level change criterion, decide to maintain the difficulty level if it corresponds to the second difficulty level change criterion, and decide to increase the difficulty level (Up) if it corresponds to the third difficulty level change criterion.

[0198] For example, assume that the exercise difficulty evaluation information is a difficulty score (SCORE) consisting of a scale of "0 to 9 (natural numbers)." If the difficulty scores of the exercise items assigned to a specific day are "9," "8," "7," or "6," the control unit 130 can determine to lower the difficulty of the exercise items assigned from the day after the specific day. Furthermore, if the difficulty scores of the exercise items assigned to a specific day are "5," "4," or "3," the control unit 130 can determine to maintain the difficulty of the exercise items assigned from the day after the specific day. Furthermore, if the difficulty scores of the exercise items assigned to a specific day are "2," "1," or "0," the control unit 130 can determine to increase the difficulty of the exercise items assigned from the day after the specific day.

[0199] Meanwhile, when the control unit 130 determines that the difficulty level of the exercise items assigned on or after the day following a specific day is to be either lowered (Down) or increased (Up), it can change the exercise difficulty by changing at least one of the number of times the exercise action is maintained (or the number of times the exercise action is repeated) and the number of sets for each exercise item assigned on the specific day.

[0200] As shown in (a) of FIG. 5c, it is assumed that a plurality of exercise items 611-616 are assigned to a specific day ("23rd day"). When a change in difficulty level is determined based on the exercise difficulty evaluation information for the exercise items 611-616 assigned to the specific day ("23rd day"), the control unit 130 can change the difficulty level of the exercise items 611-616. For convenience of explanation, the following describes a method for changing the difficulty level of a specific exercise item (e.g., "standing with shoulders straight") 612 as an example. The method for changing the difficulty level of a specific exercise item 612 can be similarly applied to other exercise items.

[0201] The control unit 130 can change the difficulty level of a specific exercise item by referring to the matching information 700 stored in the storage unit 120 and changing at least one of the duration of the exercise action (or the number of repetitions of the exercise action) and the number of sets of the specific exercise item (standing and straightening the shoulders) 730.

[0202] Each exercise item may be matched with a minimum exercise action duration (e.g., 5 seconds), a maximum exercise action duration (e.g., 20 seconds), a minimum number of sets (e.g., 1 set), and a maximum number of sets (e.g., 3 sets). Meanwhile, in the present invention, for the sake of convenience, "exercise action duration" will be used as an example, but depending on the type of exercise item, it may also be described as "number of exercise action repetitions."

[0203] Based on the determination of increasing the difficulty level of the exercise item, the control unit 130 may increase the exercise action duration of the specific exercise item 730. For example, if the current exercise duration of the specific exercise action 730 is "5 seconds (731)", the control unit 130 may increase the exercise duration of the specific exercise item 730 to "10 seconds (732)".

[0204] The control unit 130 may increase the current number of sets of a specific exercise item when the current exercise duration of the specific exercise action 730 is the maximum. For example, when the current exercise duration of the specific exercise action 730 is "20 seconds" and the current number of sets is "1 set," the control unit 130 may increase the number of sets of the specific exercise item 730 to "2 sets."

[0205] On the other hand, if both the current exercise duration and the current number of sets of a specific exercise item are maximum, the control unit 130 may replace the specific exercise item with another exercise item having a difficulty level higher than the difficulty level of the specific exercise item. For example, if the difficulty level of the specific exercise item 730 is "2," the control unit 130 may replace (or substitute) the specific exercise item 730 with another exercise item 740 having a difficulty level of "3." In this case, the control unit 130 may determine the exercise duration and the number of sets of the other exercise item 740 as the maximum exercise duration and the maximum number of sets matched to the other exercise item 740.

[0206] Meanwhile, based on the determination of the difficulty level of the exercise item, the control unit 130 may reduce the exercise action duration of the specific exercise item 730. For example, if the current exercise duration of the specific exercise action 730 is 15 seconds (733), the control unit 130 may reduce the exercise duration of the specific exercise item 730 to 10 seconds (732).

[0207] The control unit 130 may reduce the current number of sets of a specific exercise item when the current exercise duration of the specific exercise action 730 is the shortest. For example, when the current exercise action duration of the specific exercise action 730 is "5 seconds" and the current number of sets is "2 sets," the control unit 130 may reduce the number of sets of the specific exercise item 730 to "1 set."

[0208] On the other hand, if both the current exercise duration and the current number of sets of a specific exercise item are minimum, the control unit 130 may replace the specific exercise item with another exercise item having a difficulty level lower than the difficulty level of the specific exercise item. For example, if the difficulty level of the specific exercise item 730 is "2," the control unit 130 may replace (or substitute) the specific exercise item 730 with another exercise item 720 having a difficulty level of "1." In this case, the control unit 130 may determine the exercise duration and the number of sets of the other exercise item 730 as the maximum exercise duration and the maximum number of sets matched to the other exercise item 730.

[0209] On the other hand, the control unit 130 can update the exercise plan by changing at least one of the exercise type and difficulty level of the exercise item assigned on or after the day after the specific day (e.g., "the 23rd day") based on the evaluation information of the exercise item assigned on the specific day (e.g., "the 23rd day").

[0210] The control unit 130 can provide, on the user terminal 10, an exercise list including exercise items according to the updated exercise plan from the day after the specific day onwards.

[0211] Meanwhile, when the exercise plan is updated based on the patient's evaluation information, the control unit 130 can provide the user terminal 10 with information instructing the user to update the exercise plan.

[0212] The timing and method of notifying the user of an exercise plan update may vary. For example, the control unit 130 may notify the user of an exercise plan update when the application is executed the day after a specific day. As another example, when the first menu item 310 is selected on the initial screen page 300 the day after a specific day, the control unit 130 may provide an exercise plan update notification page 600' on the user terminal 10 before providing an exercise list based on the exercise items included in the updated exercise plan.

[0213] In this case, at least one of information regarding the reason for updating the exercise plan and information regarding the update items of the exercise plan may be displayed on the exercise plan update information page 600'.

[0214] For example, as shown in (a) of FIG. 6, based on the evaluation information of the exercise items assigned to a specific day, the difficulty level of the exercise items assigned to the day after the specific day has been changed, the control unit 130 can display information about the reason for the change in difficulty level (e.g., "Hong Gil-dong, yesterday was tough" or "Your pain index has worsened, so we will adjust the program you previously implemented and proceed with the plan") and information about the change in difficulty level (e.g., "Program with difficulty level 2 → Program with difficulty level 1") on the exercise plan update information page 600'.

[0215] As another example, as shown in (b) of FIG. 6, based on the evaluation information of the exercise items assigned to a specific day, if at least some of the exercise items assigned to the day after the specific day are excluded, the control unit 130 can display information on the reason for changing the type of exercise item (e.g., "It has been determined that the difficult exercise will make it difficult to improve pain and progress in the plan, so from today onwards the exercise will be excluded") and information on the changes to the exercise item (e.g., "Passive ankle dorsiflexion 2 has been excluded") on the exercise plan update information page 600.

[0216] Meanwhile, the method and system 100 for providing musculoskeletal rehabilitation therapy according to the present invention can provide cognitive behavioral therapy in conjunction with rehabilitation exercise therapy to patients suffering from pain due to musculoskeletal disorders.

[0217] In particular, the present invention provides a plurality of different programs in sequence during a rehabilitation period set for rehabilitation exercise, thereby enabling comprehensive cognitive behavioral therapy to be provided as the musculoskeletal patient progresses with their rehabilitation exercise.

[0218] As described above, the cognitive behavioral treatment plan 220 may be set to correspond to the preset rehabilitation period corresponding to the exercise plan 210. For example, if the preset rehabilitation period corresponding to the exercise plan 210 is eight weeks, the treatment period according to the cognitive behavioral treatment plan 220 may also be set to eight weeks. Conversely, if the preset rehabilitation period corresponding to the exercise plan 210 is six weeks, the treatment period according to the cognitive behavioral treatment plan 220 may also be set to six weeks. Meanwhile, the control unit 130 may configure the preset rehabilitation period corresponding to the exercise plan 210 and the treatment period according to the cognitive behavioral treatment plan 220 independently depending on the situation. For example, the rehabilitation period according to the exercise plan 210 may be set to six weeks, and the treatment period according to the cognitive behavioral treatment plan 220 may be set to eight weeks.

[0219] Meanwhile, the rehabilitation therapy delivery system 100 according to the present invention may be named a cognitive behavioral therapy delivery system 100.

[0220] The present invention relates to a method and system for providing a customized behavioral treatment protocol for each pain patient, taking into account the duration of pain and the degree of cognitive distortion of the pain patient, and in particular to a method and system for providing cognitive behavioral treatment for patients with pain caused by musculoskeletal disorders.

[0221] For the sake of convenience, the present invention will be described mainly with reference to "musculoskeletal disorders," but is not necessarily limited thereto. That is, the cognitive behavioral therapy of the present invention can include not only patients with pain due to musculoskeletal disorders, but also patients with pain due to various diseases (e.g., cancer, diabetes, hypertension, etc.).

[0222] In the present invention, the term "pain patient" refers to a patient who is experiencing pain due to a disease, and may be used interchangeably with "patient" or "user."

[0223] On the other hand, in the case of pain patients, even if they have the same disease (or illness), the duration of pain and the degree of cognitive distortion may differ from patient to patient. Therefore, the present invention can provide a cognitive behavioral treatment protocol customized for each pain patient, reflecting the duration of pain and the degree of cognitive distortion of the patient.

[0224] Meanwhile, the rehabilitation treatment provision system 100 according to the present invention can use the user terminal 10 to diagnose the duration of pain and the degree of cognitive distortion of the "patient" U, and provide a customized behavioral treatment protocol taking this into consideration.

[0225] "Cognitive distortion" refers to a cognitive error that leads to incorrect assumptions or incorrect concepts about pain, surrounding circumstances, events, etc., and "degree of cognitive distortion" can be understood as a term that indicates the degree to which a patient's cognition is distorted. In the present invention, "degree of cognitive distortion" can be used interchangeably with "cognitive distortion state" and can be quantified as a "cognitive distortion score" or "cognitive distortion score."

[0226] Meanwhile, as shown in (a) of Figure 8a, patient U can receive the cognitive behavioral treatment plan assigned to his / her patient account by selecting the third menu item 330 on the initial screen page 300. As shown in (b) and (c) of Figure 8a, through the cognitive behavioral treatment page 800 provided by the rehabilitation treatment delivery system 100 according to the present invention, the patient can diagnose the duration of his / her own pain and the degree of cognitive distortion, and manage his / her mental health condition by receiving counseling services according to a customized cognitive behavioral treatment protocol.

[0227] Below, we describe a method for providing a customized cognitive behavioral treatment protocol to pain patients.

[0228] Hereinafter, a cognitive behavioral therapy providing system 100 according to the present invention will be described with reference to an embodiment in which the system is implemented as an application on a user terminal 10.

[0229] Cognitive behavioral therapy delivery system 100 for pain patients according to the present invention may be configured to include at least one of communication unit 110, storage unit 120, and control unit 130. In this case, cognitive behavioral therapy delivery system 100 according to the present invention is not limited to the above-mentioned components, and may further include components that perform the same functions as the devices described in this specification.

[0230] The communication unit 110 may include one or more treatment modules that enable wireless or wired communication between the cognitive behavioral therapy delivery system 100 and the user terminal 10, or between the cognitive behavioral therapy delivery system 100 and an external server. The communication unit 110 may also include one or more communication modules that connect the cognitive behavioral therapy delivery system 100 to one or more networks.

[0231] Specifically, the communication unit 110 can collect, from at least one source, questionnaire response data for diagnosing the patient's pain duration and the degree of cognitive distortion via the user terminal 10. In addition, the communication unit 110 can provide, via the user terminal 10, a cognitive behavioral therapy service customized according to the pain duration and the degree of cognitive distortion of the pain patient.

[0232] The storage unit 120, also called a database (DB), is configured to store various information (or data) related to cognitive behavioral treatment of pain patients, such as collected questionnaire response data, diagnosis results based on the questionnaire response data, and cognitive behavioral treatment protocols based on the diagnosis results.

[0233] Furthermore, the cognitive behavioral therapy providing system 100 according to the present invention can utilize data stored in external storage separate from the storage unit 120, and such external storage can also be expressed as a "database."

[0234] Meanwhile, the control unit 130 can control the overall operation of the cognitive behavioral therapy providing system 100 according to the present invention.

[0235] 1, the control unit 130 can control to output a page (or service page) for providing cognitive behavioral therapy services via a display unit (or touch screen) provided in the user terminal 10. Such a page can be output on the user terminal 10 via an application or web page installed on the user terminal 10.

[0236] The page is linked to the cognitive behavioral therapy providing system 100 according to the present invention, and is configured to be controlled by the cognitive behavioral therapy providing system 100 according to the present invention.

[0237] Furthermore, if the page is provided in the form of an application, the page 300 can be controlled by a CPU (Central Processing Unit) of the user terminal 10 in which the application is installed. In this case, the CPU of the user terminal 10 can provide services related to cognitive behavioral therapy to the pain patient based on information provided by the cognitive behavioral therapy providing system 100 according to the present invention.

[0238] The components of the cognitive behavioral therapy delivery system 100 according to the present invention have been discussed above. A method for providing a customized cognitive behavioral therapy protocol to a pain patient based on the above components will now be described.

[0239] As shown in FIG. 8b, the method for providing cognitive behavioral therapy according to the present invention may include a step of providing a plurality of questionnaire data for diagnosing the condition of a pain patient on a user terminal (S210).

[0240] The control unit 130 can perform control so as to provide a page including multiple pieces of questionnaire data on the user terminal 10. In this case, the page including multiple pieces of questionnaire data can be output via the touch screen (or display) of the user terminal 10.

[0241] Here, the plurality of questionnaire (or question, or problem, or item, or test) data may include a questionnaire for assessing the status of factors related to pain.

[0242] In the present invention, pain-related factors may be diverse. For example, pain-related factors may refer to various elements for evaluating a patient's pain-related condition, such as pain level, pain duration, mental health, and physical health. However, the above-mentioned factors are merely examples, and it is clear that the pain-related factors described in the present invention refer to all elements for evaluating a patient's condition.

[0243] Such pain-related factors may include reliable questionnaire data that is actually used in psychiatric medicine to diagnose a patient's condition. In addition, the control unit 130 can update the questionnaire data as needed or periodically by downloading additional questionnaires for diagnosing a patient's condition via an external server or website.

[0244] A user interface through which questionnaire data is provided will be described below, as shown in Fig. 8c. As shown in Fig. 8c, a page including a questionnaire area 401 for displaying at least one of a plurality of questionnaires and an answer area 402 for receiving the patient's answer to the displayed questionnaire may be output on the user terminal 10. In this case, the answer area 402 may include answer graphic objects 402a, 402b corresponding to each of a plurality of different answers corresponding to the questionnaire displayed in the questionnaire area 401.

[0245] This allows the pain patient to select as the questionnaire response data the candidate answer that is considered to be most suitable (or appropriate, or accurate) for the user's condition from the candidate answers output in answer area 402 as an answer to any of the displayed questionnaires.

[0246] Meanwhile, in the present invention, a process of receiving survey response data for a plurality of survey data can be performed via the user terminal (S220, see FIG. 8b).

[0247] The control unit 130 can receive survey response data from the user terminal 10 based on the user's selection (or user's input) in the response area 402 of the user terminal 10.

[0248] For example, as shown in (a) of FIG. 8c, based on the selection of one of the plurality of answer graphic objects 402a, 402b corresponding to a first questionnaire regarding the pain duration of a pain patient (e.g., "When did Jang Hye-ryong's knee pain start?"), the answer corresponding to the selected answer graphic object 402a (e.g., "One week ago") can be received as questionnaire response data for the first questionnaire. Meanwhile, the first questionnaire may include a plurality of questionnaires. In this case, the user terminal 10 may be provided with a plurality of questionnaires necessary to detect condition information regarding the patient's pain duration. Furthermore, the answers to the plurality of questionnaires can be received from the user terminal as questionnaire response data.

[0249] As another example, as shown in (b) of Figure 8c, based on the selection of any one of multiple answer graphic objects corresponding to a second questionnaire related to the degree of cognitive distortion of the patient (How much have you felt negative emotions such as anxiety when you felt pain in the past two weeks?), an answer (e.g., "3") corresponding to the selected answer graphic object can be received as questionnaire response data for the second questionnaire.

[0250] On the other hand, the second questionnaire may include multiple questionnaires. In this case, the user terminal 10 may be provided with multiple questionnaires necessary for detecting condition information regarding the degree of cognitive distortion of the pain patient. Furthermore, responses to the multiple questionnaires may be received from the user terminal as questionnaire response data. Examples of the second questionnaire include questionnaires related to at least one of the Pain Catastrophizing Scale and Fear (or Risk) Avoidance Beliefs, such as: i) I'm always worried that the pain will never go away; ii) I feel like I can't bear it any longer; iii) The pain is so bad that I worry it will never get better; iv) My pain is caused by physical activity; v) My pain gets worse due to physical activity; and vi) My pain is caused by work or an accident at work. Furthermore, unlike the above, the multiple questionnaire data for diagnosing the condition of the pain patient may further include questionnaires for assessing depression, insomnia, etc.

[0251] Meanwhile, in the present invention, a process of detecting condition information of a pain patient related to the duration of pain and the degree of cognitive distortion of the pain patient can be performed based on the questionnaire response data (S230, see FIG. 8b).

[0252] As shown in FIG. 8d, the control unit 130 can compare the pain duration 450 extracted (acquired or detected) from the pain patient's questionnaire response data with a first criterion (e.g., "3 months") 450a to detect the condition information of the pain patient.

[0253] Here, the first criterion 450a can be understood as a predefined reference period (e.g., "3 months") for classifying (or dividing) the pain duration (or the nature of the pain according to the pain duration) into either "first type of pain duration (e.g., acute pain) 451" or "second type of pain duration (e.g., chronic pain) 452."

[0254] If the comparison result shows that the pain duration 450 of the pain patient is shorter than the predefined reference period 450a (i.e., equal to or shorter than the predefined reference period), the control unit 130 can classify (categorize, identify, or determine) the pain duration of the pain patient as a "first type of pain duration (e.g., acute pain) 451." On the other hand, if the pain duration 450 of the pain patient is longer than the predefined reference period 450a (i.e., exceeds the predefined reference period), the control unit 130 can classify the pain duration of the pain patient as a "second type of pain duration (e.g., chronic pain) 452."

[0255] The control unit 130 can classify the pain duration of the pain patient into either acute pain or chronic pain depending on whether the pain duration 450 exceeds the reference period 450a.

[0256] Furthermore, the control unit 130 can compare the degree of cognitive distortion 460 extracted (acquired or detected) from the questionnaire response data of the pain patient with a second criterion 460a.

[0257] Here, the degree of cognitive distortion in a pain patient can be related to either the Pain Catastrophizing Scale or Fear (or danger) Avoidance Beliefs, as described above.

[0258] Here, the second criterion 460a can be understood as a predefined standard score (e.g., "24 points") for classifying (or dividing) the degree of cognitive distortion of a pain patient into either "degree of first type of cognitive distortion (e.g., high cognitive distortion) 461" or "degree of second type of cognitive distortion (e.g., low cognitive distortion) 462."

[0259] The control unit 130 can calculate (derive or compute) a cognitive distortion score (SCORE) of the pain patient based on the questionnaire response data to compare the degree of cognitive distortion 460 of the pain patient with a predefined standard score 460a.

[0260] A plurality of selection items for a questionnaire for determining the degree of cognitive distortion (e.g., "I always worry that the pain will never go away") may be matched with different scores (e.g., "I don't agree at all": 0 points, "I agree a little": 1 point, "I agree often": 2 points, "I agree very much": 3 points, "I agree all the time": 4 points). The response data is a selection signal for any one of the plurality of selection items, and the control unit 130 can calculate (derive or calculate) the cognitive distortion score (SCORE) of the pain patient using the score matched to the selection item according to the received selection signal.

[0261] Meanwhile, the control unit 130 can calculate the cognitive distortion score of the pain patient from the questionnaire response data using various methods. For example, the control unit 130 can calculate the cognitive distortion score of the pain patient using the sum or average of the questionnaire response data corresponding to a plurality of questionnaire data. In this case, the control unit 130 can calculate the cognitive distortion score of the pain patient by assigning (giving) a different weight to each questionnaire response data.

[0262] The control unit 130 can compare the calculated cognitive distortion score with a predefined reference score 460a.

[0263] If the comparison result shows that the pain patient's cognitive distortion score is higher than the predefined standard score 460a (i.e., exceeds the predefined score), the control unit 130 can classify (categorize, identify, or determine) the degree of cognitive distortion of the pain patient as "degree of first type of cognitive distortion (high cognitive distortion) 461." On the other hand, if the pain patient's cognitive distortion score is lower than the predefined standard score 460a (i.e., equal to or lower than the predefined cognitive distortion score), the control unit 130 can classify the degree of cognitive distortion of the pain patient as "degree of second type of cognitive distortion (low cognitive distortion) 462."

[0264] That is, the control unit 130 can determine the degree of cognitive distortion of the pain patient as either high cognitive distortion or low cognitive distortion depending on whether the cognitive distortion score exceeds the reference score.

[0265] Meanwhile, in the present invention, a process can be performed to identify a user group corresponding to the condition information of a pain patient from among a plurality of user groups classified according to the duration of pain and the degree of cognitive distortion (S240, see FIG. 2).

[0266] As shown in Fig. 8d, in the present invention, a plurality of user groups 410, 420, 430, and 440 can be classified according to pain duration 450 and cognitive distortion level 460. For convenience of explanation, an example will be described in which there are four different user groups according to pain duration 450 and cognitive distortion level 460. The user groups in the present invention may be named first user group 410, second user group 420, third user group 430, and fourth user group 440. However, it is clear that the number and conditions for classifying the user groups can be set in various ways in the present invention.

[0267] Meanwhile, classification criteria information for classifying the plurality of user groups may be matched and exist for each of the plurality of user groups 410, 420, 430, and 440. Such classification criteria information may be predefined and exist in the storage unit 120 or an external server.

[0268] Specifically, in the first user group 410, a first type of pain duration (e.g., acute pain) 451 and a first type of cognitive distortion degree (e.g., high cognitive distortion) 461 may be matched as classification criteria information.

[0269] In the second user group 420, a first type of pain duration (e.g., acute pain) 451 and a second type of cognitive distortion degree (e.g., low cognitive distortion) 462 may be matched and present as classification criterion information.

[0270] In the third user group 430, the duration of pain of the second type (e.g., chronic pain) 452 and the degree of cognitive distortion of the first type (e.g., high cognitive distortion) 461 may be matched as classification criteria information.

[0271] Additionally, in the fourth user group 440, a second type of pain duration (e.g., chronic pain) 452 and a second type of cognitive distortion degree (e.g., low cognitive distortion) 462 may be matched and present as classification criteria information.

[0272] The control unit 130 may determine a specific user group from among the plurality of user groups 410, 420, 430, and 440, to which classification criterion information corresponding to the condition information of the pain patient is matched.

[0273] Specifically, if the condition information of a first pain patient (e.g., "Patient Kim Cheol-soo") includes a first type of pain duration (e.g., acute pain) 451 and a first type of cognitive distortion degree (e.g., high cognitive distortion) 461, the control unit 130 can identify (or classify) the first pain patient as a pain patient belonging to a first user group 410 among multiple user groups.

[0274] Furthermore, if the condition information detected from the questionnaire response data of a second pain patient (e.g., "Patient Lee Yeon-sook") includes the duration of pain of the first type (e.g., acute pain) 451 and the degree of cognitive distortion of the second type (e.g., low cognitive distortion) 462, the control unit 130 can identify (or classify) the second pain patient as a pain patient belonging to a second user group 420 among multiple user groups.

[0275] Furthermore, if the condition information of a third pain patient (e.g., "Patient Choi Min-cheol") includes the duration of pain of the second type (e.g., chronic pain) 452 and the degree of cognitive distortion of the first type (e.g., high cognitive distortion) 461, the control unit 130 can identify (or classify) the third pain patient as a pain patient belonging to a third user group 430 among multiple user groups.

[0276] Furthermore, if the condition information of a fourth pain patient (e.g., "Patient Bang Minji") includes a second type of pain duration (e.g., chronic pain) 452 and a second type of cognitive distortion degree (e.g., low cognitive distortion) 462, the control unit 130 can identify (or classify) the fourth pain patient as a pain patient belonging to a fourth user group 440 among multiple user groups.

[0277] Meanwhile, in the present invention, a process of determining an initial treatment protocol corresponding to a user group from among a plurality of treatment protocols can be performed (S250, see FIG. 8b).

[0278] As shown in Figures 8e and 8f, the treatment protocol according to the present invention may be composed of multiple treatment programs 510-580, each of which is matched to a different topic 510a-580a. That is, each treatment program refers to a program for providing treatment according to the topic matched to that treatment program.

[0279] Here, the "topics 510a to 580a" correspond to a plurality of programs 510 to 580 for cognitive behavioral treatment of pain patients, respectively. For example, as shown in FIGS. 8g and 8h, i) motivation enhancement (hereinafter referred to as the first topic) 510a corresponds to the first program (or the first treatment program) 510, ii) emotion confirmation (hereinafter referred to as the second topic) 520a corresponds to the second program (or the second treatment program) 520, iii) behavioral strategy (hereinafter referred to as the third topic) 530a corresponds to the third program (or the third treatment program) 530, and iv) attention shifting (hereinafter referred to as the fourth topic) 540a corresponds to the fourth program (or the third treatment program) 540. v) Changing Mindset (hereinafter, fifth topic) 550a can correspond to the fifth program (or fifth treatment program) 550, vi) Thought Record (hereinafter, sixth topic) 560a can correspond to the sixth program (or sixth treatment program) 560, vii) Management Strategies (hereinafter, seventh topic) 570a can correspond to the seventh program (or seventh treatment program) 570, and viii) Future Me (hereinafter, eighth topic) 580a can correspond to the eighth program (or eighth treatment program) 580.

[0280] The first topic (enhancing motivation) is a process for understanding cognitive behavioral therapy and cognitive schemas regarding pain, and for pain patients to set their own goals and increase their motivation for treatment, and can be composed of related treatment modules.

[0281] The second topic (emotional identification) is intended to examine pain, emotions, and the pain patient's own coping strategies, and may consist of a treatment module to explore the pain patient's negative emotions, physical reactions, and behaviors related to pain and to discover the pain patient's own coping strategies.

[0282] The third topic (behavioral strategies) is treatment for pain patients to set activity goals, establish new coping behavior methods, and use breathing techniques and progressive relaxation techniques to cope with pain, and can be composed of treatment modules for this purpose.

[0283] The fourth topic (attention shifting) is a treatment for dealing with pain using attention shifting methods that utilize activities, emotions, the five senses, etc., and can be composed of treatment modules for this purpose.

[0284] The fifth topic (changing thinking) involves exploring negative automatic thoughts related to pain and identifying the emotions and behaviors that result from these thoughts. This involves the process of finding evidence to refute the automatic thoughts, and can consist of a treatment module for this purpose.

[0285] The sixth topic (thought recording) is the process of exploring pain patients' own irrational thinking patterns and finding cognitive flexibility, and can be composed of a treatment module for this purpose.

[0286] The seventh topic (Management Strategies) is using positive self-talk and practicing pain management strategies, which may consist of a treatment module to use positive self-talk to deal with pain and understand the "Stop-Think-Assess-Act Method."

[0287] The eighth topic (future me) could consist of a treatment module to organize the coping strategies learned so far in relation to jumping over stones (treatment resistance) and developing a positive self-image, to create the pain patient's own recipe for dealing with pain (pain coping recipe), and to identify ways of dealing with anticipated difficulties.

[0288] Meanwhile, in the present invention, the topics 510a to 580a may be predefined and stored in the storage unit 120. Meanwhile, in the present invention, it goes without saying that the number and content (or type) of topics are not limited to the above example and can be defined in various ways.

[0289] A specific treatment program may be configured to include at least one treatment module related to a specific topic that is matched to the specific treatment program. For example, a first treatment program 510 may be configured with multiple treatment modules 511-515 related to a first topic (e.g., "motivation enhancement") 510a.

[0290] Here, a "treatment module" may refer to content related to a specific category (or subtopic) for cognitive behavioral treatment of pain patients for a specific topic. For example, the multiple treatment modules 511-515 related to a first topic (e.g., "Motivation Enhancement") 510a may include a "What Pain Means to Me Treatment Module 511," a "Pain Cognitive Schema Treatment Module 512," a "Pain Questionnaire Treatment Module 513," a "Goal Setting Treatment Module 514," and a "Pain Record Exercise Treatment Module 515" (see FIG. 8e). In the present invention, a treatment module included in a treatment program related to a specific topic may be referred to as a "treatment module corresponding to a specific topic." In the present invention, the term "treatment module" may be used interchangeably with "chapter."

[0291] Meanwhile, as shown in FIG. 8d, a plurality of user groups 410, 420, 430, and 440 may each be matched with different treatment protocols 410a, 420a, 430a, and 440a.

[0292] The multiple treatment protocols 410a, 420a, 430a, 440a matched to each of the multiple user groups 410, 420, 430, 440 may consist of at least one different treatment program or treatment module depending on the characteristics of the pain duration 450 and the degree of cognitive distortion 460 of the user groups 410, 420, 430, 440.

[0293] For example, the first treatment protocol 410a matched to the first user group 410 and the third treatment protocol 430a matched to the third user group 430 may be configured to include all treatment modules (full modules) stored in the server. In this case, all treatment modules may include all of the treatment modules matched to each of the first to eighth topics, and cognitive behavioral therapy may be performed on pain patients belonging to the first user group using all of the treatment modules included in each of the first to eighth topics.

[0294] As another example, the treatment protocols matched to the second user group 420 and the fourth user group 440 may be configured to include only some of the treatment modules stored in the server (full modules). The treatment protocols matched to the second user group 420 and the fourth user group 440 may be configured with only some of the treatment modules matched to each of the first to eighth topics, and cognitive behavioral therapy may be performed on pain patients belonging to the second user group 420 and the fourth user group 440 using some of the treatment modules constituting the first to eighth topics.

[0295] As one example, a second treatment protocol 420a matched to a second user group 420 may be configured to emphasize modules related to coping strategies, breathing techniques, and disease education. As another example, a fourth treatment protocol 440a matched to a fourth user group 440 may be configured to emphasize modules related to acceptance commitment.

[0296] On the other hand, as shown in Figures 8e and 8f, each of the multiple treatment programs 510 to 580 may include worksheet modules 515, 522, 531, 541, 551, 561, 571, 581 for checking at least one of the pain level, pain duration, mental health status, and physical health status of a pain patient.

[0297] In this case, each worksheet module may be input with user response information for checking at least one of the pain level, pain duration, mental health condition, and physical health condition of the pain patient in relation to a specific topic of the treatment program to which the worksheet module is included. Furthermore, each worksheet module may be input with various user response information for checking at least one of the pain level, pain duration, mental health condition, and physical health condition of the pain patient in addition to content related to a specific topic of the treatment program.

[0298] For example, a worksheet module 515 included in the first treatment program 510 may receive input of user response information related to a first topic ("Motivation Enhancement") 510a to check at least one of a pain patient's pain level, pain duration, mental health status, and physical health status.

[0299] As another example, a worksheet module 522 included in the second treatment program 520 may receive input of user response information related to a second topic ("Emotional Verification") 520a to check at least one of the pain level, pain duration, mental health status, and physical health status of a pain patient.

[0300] The worksheet module may be provided at various points in each treatment program. For example, the worksheet module may be located at the end or middle of each treatment program. The location at which the worksheet module is included in each treatment program may vary depending on the condition of the pain patient.

[0301] Alternatively, the worksheet module may be provided as the final module in each treatment program. The worksheet module may be arranged as the final module among the treatment modules constituting each treatment program, and may be configured so that the pain patient proceeds to the worksheet module after completing all of the treatment modules of the treatment program. This may include the purpose of receiving the pain patient's feedback on the treatment program, objectification, or treatment effect.

[0302] Furthermore, the worksheet module included in each treatment program may be configured so that the pain patient can score (select, input, etc.) the severity of pain, the mood when experiencing pain, the degree of negative emotions related to pain, the degree of stress related to pain, etc. The control unit 130 can use the score received in the worksheet module to determine whether the treatment program including the corresponding worksheet module was helpful or effective for the pain patient.

[0303] For example, if there is a treatment program that has obtained a low pain score, the control unit 130 can determine that the treatment program is useful to the user. In this case, the treatment program can be reflected in updating the treatment protocol, which will be described later.

[0304] Meanwhile, in the present invention, a process can be performed in which multiple specific treatment programs included in the initial treatment protocol are sequentially provided to the user terminal 10 according to the treatment week set for each of the multiple specific treatment programs (S260, see Figure 8b).

[0305] Here, a "treatment week" can be understood as the order (or period) in which a treatment program is provided (or activated) via the user terminal 10 so that the patient undergoes cognitive behavioral therapy in accordance with the treatment program. In the present invention, the "total number" of treatment weeks and the "weekly treatment period" corresponding to each treatment week may be preset. Also, in the present invention, the "total treatment period" can be understood as being predefined. The total treatment period may be determined as the product of the preset total number of treatments and the preset weekly treatment period. For example, if the total number is "8" and the weekly treatment period is one week (7 days), the preset total treatment period is "8 weeks."

[0306] For ease of explanation, the following describes an example in which eight different treatment weeks occur within each one-week treatment period. That is, in the present invention, the first treatment week occurs in the first treatment session, and the second treatment week occurs in the second treatment session. Therefore, in the present invention, the term "treatment week" may be used interchangeably with "treatment session," "treatment number," "treatment period," and "treatment sequence."

[0307] The control unit 130 may set at least one treatment week for each of the multiple treatment programs included in the initial treatment protocol. Furthermore, the control unit 130 can provide a treatment program for which a specific treatment week is set for a specific treatment week.

[0308] As previously mentioned, in the present invention, the total number of treatment weeks (e.g., "8") can be predefined.

[0309] When the multiple treatment programs included in the initial treatment protocol correspond to a predefined number of treatment weeks, the control unit 130 may set different treatment weeks for each of the multiple treatment programs. For example, when the first to eighth treatment programs are selected for the initial treatment protocol, the control unit 130 may set any one of the first to eighth treatment weeks for each of the first to eighth treatment programs.

[0310] Meanwhile, the first to eighth treatment programs may correspond to the first to eighth topics described above, respectively. That is, i) the first treatment program may be for training or treatment related to the first topic (motivation enhancement), ii) the second treatment program may be for training or treatment related to the second topic (emotion validation), iii) the third treatment program may be for training or treatment related to the third topic (behavioral strategies), iv) the fourth treatment program may be for training or treatment related to the fourth topic (attention shifting), v) the fifth treatment program may be for training or treatment related to the fifth topic (thinking shifting), vi) the sixth treatment program may be for training or treatment related to the sixth topic (thought recording), vii) the seventh treatment program may be for training or treatment related to the seventh topic (management strategies), and viii) the eighth treatment program may be for training or treatment related to the eighth topic (future self).

[0311] On the other hand, if the multiple treatment programs included in the initial treatment protocol do not meet the predefined number of treatment weeks (shortfall), the control unit 130 may set multiple treatment weeks for at least some of the multiple treatment programs. The control unit 130 may repeatedly assign the same topic to different weeks so that treatment is performed according to the predefined treatment weeks. For example, if the predefined treatment weeks are 8 weeks and the initial treatment protocol includes 7 treatment programs, the control unit 130 may repeatedly assign one of the 7 treatment programs to a specific number of weeks. For example, the control unit 130 may repeatedly set the same topic (e.g., thought recording) 560a in the 6th and 7th weeks.

[0312] Meanwhile, the control unit 130 can sequentially provide the plurality of specific treatment programs to the user terminal 10 in accordance with the treatment week set for each of the plurality of specific treatment programs based on the initial treatment protocol.

[0313] The control unit 130 can activate the state of a specific treatment program based on the initial treatment protocol so that a specific treatment program set for a specific treatment week is provided to the user terminal 10 during a treatment period corresponding to the specific treatment week. In the following, to avoid confusion in terms, the state of a specific treatment program will be referred to as the "mode" of the specific treatment program.

[0314] In the present invention, the "treatment program active mode" can be understood as a mode in which at least some of the treatment modules included in the treatment program can be viewed (or used), while the "treatment program inactive mode" can be understood as a mode in which none of the treatment modules included in the treatment program can be viewed (or used).

[0315] For example, as shown in Fig. 8e, the control unit 130 can activate a mode of the first treatment program 510 in which the first treatment week is set based on the arrival of the first treatment week (first week). Also, the control unit 130 can activate a mode of the second treatment program 520 in which the second treatment week is set based on the arrival of the second treatment week (second week).

[0316] Thus, patients can receive cognitive behavioral treatment systematically, using multiple treatment programs in sequence according to the treatment weeks set out in the initial treatment protocol.

[0317] Meanwhile, the control unit 130 can sequentially provide the specific treatment modules constituting the multiple specific treatment programs to the user terminal 10 according to the treatment weeks set for each of the multiple specific treatment programs.

[0318] The control unit 130 can sequentially provide the plurality of treatment modules 511 to 515 that make up the first treatment program 510 to the user terminal 10 during the first treatment week (see FIG. 8e).

[0319] Here, the term "treatment module sequence" can be understood as the order in which multiple treatment modules included in a particular treatment program are delivered.

[0320] Furthermore, the "active mode of the treatment module" can be understood as a mode in which the treatment module can be viewed (or used), while the "inactive mode of the treatment module" can be understood as a mode in which the treatment module cannot be viewed (or used).

[0321] The control unit 130 can change (or switch) the mode of the treatment module corresponding to the next order in the specific order from the inactive mode to the active mode based on the completion of cognitive behavioral treatment by the treatment module corresponding to the specific order in accordance with the treatment module order.

[0322] For example, as shown in Fig. 8e, the first treatment program 510 is composed of first to fifth treatment modules 511 to 515. The control unit 130 can switch the mode of the second treatment module 512 from the inactive mode to the active mode based on the completion of the cognitive behavioral treatment of the first treatment module 511.

[0323] On the other hand, based on the activation of the mode of a specific treatment program, the control unit 130 can switch the mode of the treatment module that is earliest in order among the multiple treatment modules that make up the specific treatment program from inactive mode to active mode.

[0324] For example, based on the activation of the first treatment program 510, the control unit 130 can switch the mode of the first treatment module 511 corresponding to the highest priority (first order) of the multiple treatment modules 511 to 515 included in the first treatment program 510 from a deactivated mode to an activated mode.

[0325] In this case, the highest priority treatment module in the second week's treatment program to the eighth week's treatment program 520-580, excluding the first week's treatment program 510, may be the first treatment module corresponding to the highest priority order, which is the previous worksheet check module containing the user's response information to the worksheet module provided in the previous treatment week.

[0326] In order to allow the pain patient to recognize the pain patient's past condition, the control unit 130 may preferentially provide the user's response information to the worksheet module provided in a treatment week prior to the current treatment week before providing the treatment program corresponding to the current treatment week among multiple specific treatment programs.

[0327] For example, the control unit 130 may provide the user's response information for the worksheet module provided in the first week of the treatment program to the user terminal 10 preferentially before providing the second week of the treatment program. Furthermore, the user's response information for the worksheet module provided in the previous treatment week may be provided at various times.

[0328] On the other hand, in the present invention, "a specific treatment program is activated" can be understood as switching the mode of the previous worksheet module corresponding to the highest priority (e.g., first order) among the multiple treatment modules constituting the specific treatment program from inactive mode to active mode.

[0329] Meanwhile, the control unit 130 can collect treatment response data from the user terminal 10 by a specific treatment module.

[0330] The control unit 130 may provide the user terminal 10 with a page corresponding to a specific treatment module based on the selection of the specific treatment module activated via the user terminal 10.

[0331] A page corresponding to a particular treatment module may include cognitive-behavioral therapy content related to a particular topic. For example, a page corresponding to a treatment module 511 included in a first treatment program 510 may include cognitive-behavioral therapy content (e.g., "What does pain mean to me?") related to a first topic (e.g., "Motivational Enhancement") 510a. For convenience of explanation, a page corresponding to a particular treatment module will be referred to below as a "page related to a particular topic."

[0332] The control unit 130 may collect treatment response data based on the cognitive behavioral performance of a pain patient related to a specific treatment module through a page related to a specific topic provided to the user terminal 10.

[0333] In addition, the control unit 130 may match the treatment response data collected through a page corresponding to a specific treatment module with a specific topic and store the matched treatment response data in the storage unit 120. In this case, the specific topic matched with the treatment response data may refer to a topic related to a specific treatment module.

[0334] For example, suppose that a page (e.g., a pain record exercise page) corresponding to a specific treatment module is provided on the user terminal 10 based on the selection of a specific module (one of 511 to 515) included in the first program (or first treatment program) 510. The control unit 130 can match the treatment response data input via the page with a first topic (e.g., "motivation enhancement") 510a and store it in the storage unit 120 (see FIG. 8e).

[0335] As another example, suppose that a page corresponding to a specific module 521 or 522 included in the second program (or second treatment program) 520 is provided on the user terminal 10 based on the selection of the specific module. The control unit 130 can match the treatment response data input via the page with a second topic (e.g., "emotion confirmation") 520a and store it in the storage unit 120 (see FIG. 8e).

[0336] Meanwhile, the control unit 130 can configure a page so that the pain patient inputs treatment response data required from a particular treatment module on a page corresponding to the particular treatment module.

[0337] For example, to collect treatment response data related to a pain patient's perception of pain intensity, the control unit 130 may display question data asking about pain intensity (e.g., "How is your pain today?") in one area of ​​the page, and display graphic objects corresponding to multiple pain intensities (e.g., "Pain Intensity 1 to Pain Intensity 5") in another area. The control unit 130 may also collect treatment response data for the patient's pain intensity based on the selection of a specific graphic object on the page.

[0338] As another example, the control unit 130 may provide an input field (Text Input Field) in an area of ​​the page in which the pain patient can input the emotion switching method they wish to try, in order to collect treatment response data for the emotion switching method of the pain patient. The control unit 130 may collect treatment response data related to the emotion switching method input in the input field.

[0339] Meanwhile, the control unit 130 can provide a page including various cognitive behavioral therapy contents other than the above examples for cognitive behavioral therapy of a pain patient on the user terminal 10. Furthermore, the control unit 130 can collect various treatment response data necessary for cognitive behavioral therapy through the page.

[0340] On the other hand, in the present invention, the corresponding treatment program (or treatment modules constituting the treatment program) can be changed after a specific week of treatment based on the results (particularly, initial treatment response data) of cognitive behavioral treatment of a pain patient conducted based on an initial treatment protocol.

[0341] Therefore, the "initial treatment protocol" described in this invention means a treatment protocol determined based on questionnaire response data, and the "updated treatment protocol" can be understood as a protocol in which at least one of the initial treatment program and initial treatment module included in the initial treatment protocol has been changed based on the initial treatment response data.

[0342] Meanwhile, various information other than information collected from the treatment module can be used for updating the initial treatment protocol. For example, in the present invention, after starting treatment according to the initial treatment protocol, a survey (information collection) may be conducted (information collection) regarding at least one of i) the patient's pain level, ii) the degree of negative emotions (depression), iii) the presence or absence of insomnia, iv) the degree of cognitive distortion (catastrophizing, risk aversion), v) the degree of stress caused by pain, vi) the most inconvenient thing in daily life (work, interpersonal relationships, etc.), and vii) sense of competence regarding pain management, through questions asked once a day during a predetermined initial treatment period (e.g., the first four weeks).

[0343] For example, in the present invention, after starting treatment according to the initial treatment protocol, a survey (information collection) may be conducted once a week during a preset initial treatment period regarding the treatment module or method that the patient subjectively considers to be most useful for managing pain. The control unit 130 can update the initial treatment protocol based on an analysis of the surveyed information.

[0344] Furthermore, to collect the information, the control unit 130 may provide the user with an information collection alarm in various ways (e.g., an application push message, etc.), and may provide an additional alarm if a response to the information collection is not made within a preset time. In this case, the time required for the information collection may be limited, and the control unit 130 may provide a preset evaluation time so that an evaluation for at least one of the above items i) to viii) is made within the evaluation time.

[0345] The information input by the user for the above items i) to viii) can be utilized as the "treatment response data" described in the present invention. Meanwhile, the frequency and intervals for collecting the treatment response data can, of course, be varied in various ways.

[0346] The following describes in detail how to update a treatment protocol.

[0347] For the sake of convenience, the following description will be given assuming the total treatment period to be eight weeks. However, this is merely an example for the sake of convenience, and it goes without saying that the treatment period can be set and changed in various ways by the patient and the system administrator.

[0348] Meanwhile, the control unit 130 can collect treatment response data related to cognitive behavioral treatment according to the initial treatment protocol, and update the initial treatment protocol using the collected initial treatment response data based on the passage of a preset initial treatment period (e.g., "4 weeks") within a preset overall treatment period (e.g., "8 weeks").

[0349] The control unit 130 can analyze the condition of the pain patient for at least one analysis category based on the initial treatment response data to update the initial treatment protocol.

[0350] As used herein, an "analysis category" refers to a category that is the subject of analysis of treatment response data for cognitive behavioral treatment of pain patients, and may include, for example, at least one of emotion, pain, insomnia, cognitive distortion, stress, competence, and inconvenience.

[0351] The control unit 130 can use the initial treatment response data to obtain (or derive or calculate or compute) a condition analysis result for at least one of: i) the pain level of the pain patient (associated with the pain analysis category), ii) the degree of negative emotions (associated with the emotion analysis category), iii) the degree of insomnia (associated with the insomnia category), iv) the degree of stress related to pain (associated with the stress analysis category), v) the degree of sense of competence in dealing with pain (competence category), vi) the degree of inconvenience in daily life, and vii) the degree of cognitive distortion.

[0352] The control unit 130 can derive the analysis result of the condition of the pain patient for each analysis category using various methods.

[0353] For example, the control unit 130 can acquire a condition analysis result of the pain patient for each analysis category using an artificial intelligence model that has performed machine learning to analyze the condition of the pain patient. In this case, the condition analysis result acquired using the artificial intelligence model may include information identifying a specific analysis category (e.g., "insomnia") among multiple analysis categories in which the problem symptom of the pain patient meets a preset criterion. Alternatively, the condition analysis result acquired using the artificial intelligence model may include an analysis score for each of multiple analysis categories.

[0354] As another example, the control unit 130 can compare whether the analysis scores for each of a plurality of analysis categories satisfy a preset standard, and identify, from among the plurality of analysis categories, an analysis category in which the pain patient's problem symptoms satisfy the preset standard. The control unit 130 can calculate (or compute) an analysis score for each analysis category based on treatment response data. For example, the control unit 130 can calculate an analysis score using (or compute) initial treatment response data corresponding to an objective formula. Furthermore, the control unit 130 can calculate an analysis score for initial response data consisting of text by performing an artificial intelligence analysis on the initial response data consisting of text. The control unit 130 can compare each of the calculated analysis scores for each category with a problem score preset for each category, and identify an analysis category in which the analysis score exceeds the preset problem score as a category in which the pain patient's problem symptoms exist.

[0355] Meanwhile, the control unit 130 can use the results of the condition analysis of the pain patient based on the initial treatment response data to update the initial treatment program so that at least one of the treatment programs and treatment modules related to the identified category is included in the treatment program.

[0356] As shown in FIG. 8i, the control unit 130 can change at least some of the programs 550, 560 of the fifth to eighth treatment programs 550-580 set for the fifth to eighth treatment weeks, respectively, to new programs 550', 560' based on treatment response data from the first to fourth treatment programs 510-540 set for the first to fourth treatment weeks, respectively.

[0357] In this case, the control unit 130 may change the remaining treatment programs assigned to the remaining treatment periods (5 weeks to 8 weeks) excluding the pre-set initial treatment period (e.g., 1 week to 4 weeks), and at least one of the treatment modules constituting the remaining treatment programs, so that they are associated with the identified analysis category (e.g., "insomnia").

[0358] Assume that an initial treatment protocol 810 exists, as shown in FIG. 8j. The initial treatment protocol 810 may be composed of first through eighth initial treatment programs 811-818, each of which relates to a different topic for each of the first through eighth weeks. Each of the initial treatment programs 811-818 may include a treatment module corresponding to each topic. For example, the fifth initial treatment program 815 may include multiple initial treatment modules 815a-815f related to the fifth topic, and the sixth initial treatment program 816 may include multiple initial treatment modules 816a-816f related to the sixth topic.

[0359] 8k, the control unit 130 may exclude at least some 815d-815f and 816d-816f of the treatment modules 815a-815f and 816a-816f included in the remaining treatment programs 815-816 based on the results of the pain patient's condition analysis of the initial treatment response data. The remaining treatment programs 815-816 of the updated treatment protocol 820 may include at least some of the treatment modules 815a-815c and 816a-816c that have not been excluded. In this case, the treatment modules 815a-815c and 816a-816c that have not been excluded may be those associated with the identified analysis category.

[0360] Furthermore, the control unit 130 may reset a specific treatment program set for a preset initial treatment period (or initial treatment week) to at least a part of the remaining treatment period (remaining treatment week) based on the result of analyzing the pain patient's condition with respect to the initial treatment response data. That is, the control unit 130 can reallocate (or reset or relocate) a treatment program related to a specific topic matched to the preset initial treatment period (or initial treatment week) to the remaining treatment period (or remaining treatment week) to update the initial treatment protocol.

[0361] For example, as shown in Figure 8l, the control unit 130 may reset the third treatment program 813 set in the third week to the fifth week, and reset the fourth treatment program 814 set in the fourth week to the sixth week. The updated treatment program 830 may include overlapping (or repeated) treatment programs 813 and 814 that have already been performed in different weeks. That is, in the present invention, the initial treatment program can be updated based on the initial treatment response data so that a treatment program that has already been performed is performed again.

[0362] The overlapping or repeated treatment programs may be modules determined to be most useful for pain patients. Such determination can be made through analysis of evaluation information for the treatment programs received from pain patients, changes in numerical values ​​(e.g., numerical values ​​(scores) for pain severity, mood when experiencing pain, degree of negative feelings about pain, and degree of stress about pain) received through the worksheet module, frequency of use of pain management strategies created in a particular treatment program, duration of use, etc. Such analysis can be performed using various artificial intelligence algorithms.

[0363] In this case, the reassigned treatment program 813, 814 may be one related to the identified analysis category.

[0364] Furthermore, the control unit 130 may update the initial treatment protocol 810 so that a treatment program made up of treatment modules corresponding to different topics is set for the remaining treatment period (remaining treatment week).

[0365] For example, as shown in Figure 8m, the updated protocol 830 may include a treatment program 841 that combines treatment modules corresponding to multiple topics. The treatment program 841 may include treatment modules 813a-813c related to a third topic and treatment modules 814a-814c related to a fourth topic, and may be set for a fifth treatment week. In other words, at least some of the treatment programs 841 set for the remaining treatment period (remaining treatment weeks) may include some of the treatment modules provided in the preset initial treatment period (or initial treatment week).

[0366] Furthermore, although not shown, the control unit 130 can update the initial treatment program by adding new modules different from the modules set in the initial protocol for the remaining treatment period (remaining treatment weeks).

[0367] For example, assume that the fifth treatment program 815 constituting the initial treatment protocol 810 includes six fifth-topic treatment modules 815a to 815f (see FIG. 8j). The control unit 130 can update the initial treatment protocol 815 by adding a new fifth-topic treatment module that was not included in the already included fifth-topic treatment modules 815a to 815f to the fifth treatment program 815.

[0368] In this case, the control unit 130 can remove at least some of the already included fifth topic treatment modules 815a-815f and add a new treatment module. Alternatively, the control unit 130 may include a new treatment module while leaving the already included fifth topic treatment modules 815a-815f as they are. That is, the control unit 130 may include a completely new treatment module that is different from the already included treatment modules. In this case, the already included treatment modules may be removed, maintained, or modified in various ways.

[0369] Meanwhile, based on the results of updating the initial treatment protocol, the control unit 130 may modify at least some of the example sentences provided by the treatment modules that make up the remaining treatment program so that they relate to the identified category.

[0370] As described above, the control unit 130 can identify, from among a plurality of analysis categories, a category in which the problem symptom of the pain patient meets a preset criterion.

[0371] In this case, the control unit 130 can identify a preset number (e.g., two) of the multiple analysis categories. For example, the control unit 130 can identify the "depression" and "analysis" categories with the highest analysis scores from the categories of emotion, pain, insomnia, cognitive distortion, stress, competence, and inconvenience.

[0372] The storage unit 120 may contain example sentence information corresponding to at least one category that meets preset criteria. The control unit 130 may match a patient account with at least one of information about a category that meets preset criteria and example sentence information included in the category that meets preset criteria, and store the matched information. Furthermore, the matching information may store information about selected example sentences selected by the pain patient from example sentences provided by a treatment module that the pain patient has already undergone, in addition to the category that meets preset criteria. Furthermore, the example sentences stored as matching information for the category that meets the preset criteria may also be composed of selected example sentences selected by the pain patient.

[0373] The control unit 130 can control the treatment programs 550 to 580 matched for the remaining treatment weeks to include example sentences related to the identified analysis category based on the example sentence information present in the storage unit 120. The control unit 130 can change (replace) at least a portion of the example sentences preset for the treatment modules constituting the treatment programs matched for the remaining treatment weeks with selected example sentences stored in the example sentence information corresponding to the user history.

[0374] For example, assuming that the category of depression is identified, the control unit 130 may include an example sentence such as, "Jang Hye-ryeong, do you think that 'my depressed mood will never improve'" in a specific treatment module constituting the fifth treatment program set for the fifth week.

[0375] As another example, assume that the insomnia category has been identified. The control unit 130 may include an example sentence such as, "Jang Hye-ryeong, do you think, 'I can never sleep deeply when I'm in pain?'" in a specific treatment module constituting the sixth treatment program set for the sixth week. In this way, the control unit 130 may objectify the user's perception of example sentences by continuously exposing example sentences previously selected by the pain patient or example sentences of a specific category to the pain patient.

[0376] On the other hand, in the present invention, it is possible to determine whether to maintain or change the initial treatment protocol based on the results (particularly, initial treatment response data) of cognitive behavioral treatment of a pain patient conducted based on the initial treatment protocol.

[0377] The control unit 130 can determine whether to maintain the total treatment period preset in accordance with the initial treatment protocol based on the results of the cognitive behavioral treatment of the pain patient. Furthermore, based on the determination result, the control unit 130 can update the total treatment period. Here, updating the total treatment period may include extending or shortening the total treatment period. The control unit 130 can determine whether to shorten (or suspend or shorten) the total treatment period, maintain the total treatment period, or extend the treatment period to a period longer than the total treatment period.

[0378] The control unit 130 can make the above-mentioned judgment based on various criteria, and can, for example, make a judgment as to whether to interrupt, maintain, or extend treatment for a pain patient depending on whether the results of the pain patient's cognitive behavioral treatment satisfy predetermined criteria (e.g., criteria respectively set for interrupting, maintaining, or extending treatment).

[0379] For example, the control unit 130 can quantify the results of the cognitive behavioral treatment of the pain patient into a score or the like, and can determine whether to suspend, maintain, or extend the treatment for the pain patient depending on which of a plurality of intervals the corresponding score falls within. For example, if the cognitive behavioral treatment result score of the pain patient falls within the first interval (suspended interval), the control unit 130 can suspend (or reduce) the cognitive behavioral treatment for the pain patient.

[0380] For example, if the result of cognitive behavioral treatment for a pain patient is positive, the result of the cognitive behavioral treatment may belong to the score of the first section. In this case, the control unit 130 may shorten the overall treatment period, and in this case, the control unit 130 may determine the shortened period. The control unit 130 may update the initial treatment protocol so that only the initial treatment is performed up to the time of monitoring and no subsequent treatment is performed. In this case, the cognitive behavioral treatment for the pain patient may be discontinued.

[0381] As another example, if the cognitive behavioral treatment result score of the pain patient falls within the second interval (maintenance interval), the control unit 130 may maintain the cognitive behavioral treatment for the pain patient. In this case, the treatment period (e.g., 8 weeks) set in the initial protocol may be maintained as is. If the result of the cognitive behavioral treatment of the pain patient is normal, the result of the cognitive behavioral treatment may belong to the score of the second interval. In this case, the control unit 130 may maintain the entire treatment period as is. Meanwhile, in this case, an update to the initial protocol may be performed, and the update to the initial protocol may be performed as described above in Figures 8j to 8m, so the detailed description will be replaced with the above description.

[0382] As another example, if the pain patient's cognitive behavioral treatment result score falls within the third section (maintenance section), the control unit 130 may extend the treatment period of the cognitive behavioral treatment for the pain patient. In this case, the treatment period (e.g., 8 weeks) set in the initial protocol may be further extended (e.g., 12 weeks, etc.). If the pain patient's cognitive behavioral treatment result is negative, the cognitive behavioral treatment result may belong to the score of the third section. In this case, the control unit 130 may further extend the entire treatment period. The control unit 130 may determine the extension period. The control unit 130 may determine the range of the extension period depending on the condition of the pain patient. The worse the patient's condition, the longer the extension period may be. If the treatment period is extended, the control unit 130 may determine a treatment program to be performed during the extended treatment period and update the initial treatment program so that the determined treatment program is further assigned to the extended treatment period. Of course, updating the initial treatment protocol may include not only determining a program for the extended treatment period but also updating an already assigned treatment program.

[0383] Meanwhile, the control unit 130 may determine which treatment program to further allocate to the extended treatment period using feedback from the pain patient regarding the treatment program. Furthermore, to allocate a treatment program to the extended treatment period, the control unit 130 may utilize the pain patient's condition information for each analysis category analyzed based on initial treatment response data for the treatment program already administered. The control unit 130 may determine a category for which further treatment should be administered to the pain patient based on the pain patient's condition information for each analysis category for at least one of emotion, pain, insomnia, cognitive distortion, stress, competence, and inconvenience, and further allocate a treatment program for the corresponding category to the extended treatment period. Meanwhile, there may be various methods for determining the treatment program to be allocated to the extended treatment period. For example, the control unit 130 may receive the patient's intention regarding the extension of the treatment program. The timing for receiving the patient's intention may vary. For example, the control unit 130 may receive the patient's intention regarding whether to extend the treatment period at the completion of a preset treatment period or at the start of a preset treatment program. The control unit 130 may provide an interface for receiving information from the patient using a pop-up page or various other methods. If the control unit 130 receives a patient's intention to extend the treatment period, it may extend the treatment program. The patient may also select the extension period. Furthermore, the user may select at least one of the topics or treatment modules of the extended treatment program. This allows the patient to select a treatment program or treatment module that is useful to them, thereby enabling more effective treatment. As described above, the method and system for providing cognitive behavioral therapy for a pain patient according to the present invention may receive questionnaire response data for a plurality of questionnaire data via a user terminal and detect condition information of the pain patient related to the duration of pain and the degree of cognitive distortion of the pain patient based on the questionnaire response data.Furthermore, a treatment protocol for cognitive behavioral therapy customized for a pain patient can be provided based on the condition information of the pain patient. As a result, the cognitive behavioral therapy providing method and system according to the present invention can provide a behavioral treatment program customized for a pain patient, taking into account the duration of pain and the degree of cognitive distortion of the pain patient, even if the pain patient has the same disease, rather than providing a uniform cognitive behavioral therapy depending on the pain patient's illness. Furthermore, pain patients can receive cognitive behavioral therapy customized to their own condition.

[0384] Furthermore, the method and system for providing cognitive behavioral therapy for pain patients according to the present invention can sequentially provide multiple specific treatment programs according to the treatment week, thereby allowing pain patients to receive cognitive behavioral therapy systematically and complete the treatment without interruption.

[0385] Furthermore, the method and system for providing cognitive behavioral therapy for pain patients according to the present invention updates the treatment program to be useful for treating pain patients based on treatment data collected during the progress of cognitive behavioral therapy, thereby making it possible to provide updated cognitive behavioral therapy taking into account the improvement status of pain patients without having to continuously provide the initial treatment program.

[0386] 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).

[0387] Meanwhile, as shown in FIG. 9a(a), the patient can select the fourth menu item 340 on the initial screen page 300 to receive an AI function evaluation service based on an artificial intelligence model for his or her exercise movements.

[0388] 9a(b), the control unit 130 can provide a function evaluation page 900 including a plurality of pre-set exercise items (e.g., "stretch arms out to the side," "raise arms in front of you," and "sit and straighten and bend your knees") on the user terminal 10 based on the selection of the fourth menu item 340. The exercise items that are the subject of the AI ​​function evaluation service can be set and changed by the system 100 administrator.

[0389] Meanwhile, when any one of a plurality of preset exercise items is selected, the control unit 130 may control the camera provided in the user terminal 10 to capture an exercise video of the patient U in order to evaluate the patient's exercise motion for the selected exercise item. Hereinafter, the exercise video of the patient will be referred to as a "video to be analyzed for functional evaluation."

[0390] As shown in (a) of Figure 9b, the control unit 130 can output a guidance message (e.g., "Please stand within the screen") on the user terminal 10 so that the patient's entire body is included within a specific area of ​​the functional evaluation analysis image (or user terminal display) in order to detect a subject U corresponding to the patient from the functional evaluation analysis image captured by the camera.

[0391] The control unit 130 can detect the object U from the image to be analyzed for functional evaluation 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.

[0392] The control unit 130 can use various object detection algorithms. For example, the exercise therapy application 100 can use an algorithm (Weighted Box Fusion, WBF) that ensembles multiple bounding boxes. However, it goes without saying that the control unit 130 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 video image to be analyzed for functional evaluation.

[0393] Furthermore, based on the detection of a subject U corresponding to the patient's entire body within a specific area, the control unit 130 can use a camera to capture video of the subject of functional evaluation analysis, including the patient performing exercise movements according to pre-set exercise items.

[0394] In addition, the control unit 130 can extract key points P1 and P2 corresponding to pre-set joint points from the video to be analyzed for functional evaluation in real time in conjunction with the video to be analyzed for functional evaluation being captured by the user terminal 10.

[0395] In this case, the control unit 130 can extract key points P1 and P2 corresponding to predetermined joint points from the video based on an artificial intelligence model (artificial intelligence posture estimation model) that has learned learning data including position information of the joint points.

[0396] In addition, the control unit 130 can provide the extracted key points P1 and P2 on the user terminal 10 in real time so that the patient can intuitively recognize the joint points at which analysis is performed on the exercise movement.

[0397] 9b (b) and (c), the control unit 130 may output the video to be analyzed for functional evaluation in real time on the user terminal 10 in conjunction with the video being captured by the user terminal 10. In addition, the control unit 130 may provide by overlapping or rendering graphic objects corresponding to the extracted key points P1 and P2 in a region of the subject U corresponding to a predetermined joint point.

[0398] In addition, when the position of a preset joint point is changed as the patient performs an exercise, the control unit 130 may provide a key point graphic object by superimposing it on an area of ​​the subject U corresponding to the changed joint point. That is, the control unit 130 may superimpose a key point graphic object on an area corresponding to the joint point in the image to be analyzed for functional evaluation so that the position of the joint point, which is changed in real time, is reflected.

[0399] Meanwhile, the control unit 130 may analyze the exercise movements corresponding to the exercise items performed by the patient using the image to be analyzed for functional evaluation and at least one of the key points P1 and P2.

[0400] In this case, the control unit 130 can analyze the patient's exercise movements based on at least one of an artificial intelligence model (artificial intelligence movement analysis model) that has undergone machine learning for analyzing exercise movements and predefined rules (or rule information).

[0401] On the other hand, analysis of the patient's movement can be performed not only on the range of motion of the joints, but also on at least one of the following: the distance of movement of the joints, the speed (or acceleration) of movement of the joints, the 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 being analyzed.

[0402] As described above, the present invention not only provides rehabilitation exercises to patients, but also provides cognitive behavioral therapy in conjunction with rehabilitation exercises, thereby monitoring information on the patient's pain level, pain duration, and mental health status. Furthermore, the present invention analyzes the patient's exercise movements using the above-mentioned AI functional assessment, thereby extracting information on the patient's exercise performance ability, body parts where the patient's exercise ability is lacking (e.g., body parts with weak muscles), etc.

[0403] Therefore, in the present invention, the patient's exercise plan can be updated using at least one of the results of the patient's cognitive behavioral therapy and the results of exercise analysis, rather than relying solely on the patient's evaluation information. In this case, the update of the patient's exercise plan may include various adjustments or changes related to the update of the exercise plan, such as adjusting the difficulty level of the patient's exercise or changing the type of exercise.

[0404] For example, during the cognitive behavioral treatment process, the control unit 130 may update the exercise plan based on the patient's pain feedback (example 1: negative pain feedback (e.g., my legs can no longer function), example 2: positive pain feedback (e.g., I feel like I can run)) based on the cognitive behavioral assessment results (or feedback, e.g., which may be received through a worksheet module or another module) received from the patient. As an example, if negative feedback is received as a result of the cognitive behavioral assessment, the control unit 130 may lower the difficulty of the exercise in the patient's exercise plan or change the type of exercise. The change in the type of exercise may be changing the type of exercise performed before the patient's pain feedback was received to another exercise. As another example, if positive feedback is received as a result of the cognitive behavioral assessment, the control unit 130 may increase the difficulty of the exercise in the patient's exercise plan or change the type of exercise. The change in the type of exercise may be changing to an exercise that is more difficult than the type of exercise performed before the patient's pain feedback was received.

[0405] As another example, the control unit 130 may analyze the patient's exercise movements based on the AI ​​functional evaluation, thereby extracting information regarding the patient's exercise performance ability, body parts with weak muscles, etc. Furthermore, based on the extracted information, the control unit 130 may update the exercise plan to strengthen the body parts with weak motor abilities, or update the exercise plan to prevent overwork of the body parts with weak motor abilities. For example, if the functional evaluation results indicate that a specific body part (e.g., left leg muscles) of the patient is weak, the control unit 130 may analyze whether the current exercise plan includes exercises that are excessive for the specific body part of the patient. The control unit 130 may analyze whether the current exercise plan includes exercises that are excessive for the specific body part of the patient based on information (e.g., description information) about each type of exercise. Furthermore, if the analysis results indicate that an exercise is excessive for a specific body part of the patient, the control unit 130 may exclude the exercise from the exercise plan. Furthermore, the control unit 130 may update the patient's exercise plan by extracting exercise items that can strengthen the specific body part of the patient from the storage unit and including them in the patient's exercise plan.

[0406] In this way, the control unit 130 can update the patient's exercise plan based on at least one of the patient's condition information obtained through the cognitive behavioral therapy and the evaluation information obtained through the functional assessment. Furthermore, the control unit 130 can update the patient's exercise plan based on at least one of the patient's condition information obtained through the cognitive behavioral therapy and the evaluation information obtained through the functional assessment, and the patient's evaluation information obtained through the evaluation page.

[0407] Meanwhile, as shown in FIG. 10, the control unit 130 can provide a summary page 1000 including the results of the service provided by the present invention on the user terminal 10.

[0408] The control unit 130 can display at least one of the following on the summary page 1000: i) rehabilitation exercise information according to the exercise plan, ii) evaluation information for the exercise plan, iii) AI function evaluation information based on an AI function evaluation, and iv) result information of cognitive behavioral treatment according to the cognitive behavioral treatment plan.

[0409] As shown in (a) of Figure 10, the control unit 130 can display, on the summary page 1000, at least one of the exercise execution rate information for each of the multiple days that make up the rehabilitation period and the average exercise execution rate information during the rehabilitation period as rehabilitation exercise information in accordance with the exercise plan.

[0410] Furthermore, as shown in (b) of Figure 10, the control unit 130 can display, on the summary page 1000, at least one of evaluation information (e.g., pain score, etc.) for each of the multiple days that make up the rehabilitation period and information on changes in the evaluation information (e.g., comparison information between the initial pain score and the most recent pain score) as evaluation information for the exercise plan.

[0411] 10(c), the control unit 130 may display, on the summary page 1000, information on the results of the AI ​​function assessment performed at predetermined intervals during the rehabilitation period. In this case, the control unit 130 may display, on the summary page 1000, at least one of the number of times (or the time required) for each of a plurality of predetermined exercise items and the average number of times (or the average time required) for each of the predetermined exercise items.

[0412] 10(d), the control unit 130 may provide a calendar on the summary page 1000 that allows the user to check the progress of the cognitive behavioral treatment according to the cognitive behavioral treatment plan. The calendar may also display whether a worksheet module provided in the cognitive behavioral treatment plan has been performed. The control unit 130 may display visually different graphic objects for days on which a worksheet module has been performed and days on which a worksheet module has not been performed.

[0413] As described above, the method and system for providing digital-based musculoskeletal rehabilitation therapy according to the present invention can provide a patient with an exercise plan for musculoskeletal rehabilitation therapy through an application based on prescription information including an exercise plan assigned to the patient from a doctor's terminal.

[0414] In particular, the method and system for providing digital-based musculoskeletal rehabilitation treatment according to the present invention can play exercise videos corresponding to each of a plurality of exercise items constituting an exercise list on a user terminal running an application. As a result, even if a doctor and a patient do not meet in person for rehabilitation treatment for a musculoskeletal disorder, the doctor can prescribe the treatment to the patient, and the patient can receive rehabilitation through an exercise plan according to the doctor's prescription. This eliminates spatial, time, and financial constraints on musculoskeletal rehabilitation treatment and improves accessibility to exercise treatment.

[0415] Furthermore, the method and system for providing digital-based musculoskeletal rehabilitation therapy according to the present invention can provide an evaluation page for evaluating exercise items based on whether the playback level of an exercise video satisfies a preset standard, and can update the exercise plan based on the evaluation information received through the evaluation page. This allows patients to perform exercise plans, provide appropriate feedback, and receive customized rehabilitation therapy with the feedback applied. In particular, patients can receive customized rehabilitation exercise therapy by adjusting the difficulty of exercise items according to their own condition and excluding exercise items that are difficult for the patient.

[0416] Furthermore, the digital-based musculoskeletal rehabilitation treatment delivery method and system of the present invention can provide patients with cognitive behavioral treatment plans in conjunction with rehabilitation exercise plans, thereby providing treatment for not only the rehabilitation area but also mental health.

[0417] In particular, the digital-based musculoskeletal rehabilitation therapy providing method and system according to the present invention can receive questionnaire response data for multiple questionnaires via a user terminal and detect patient condition information related to the patient's pain duration and the degree of cognitive distortion based on the questionnaire response data. Furthermore, a treatment protocol for cognitive behavioral therapy customized for the patient can be provided based on the patient's condition information. As a result, rather than providing a patient with a uniform cognitive behavioral therapy for a musculoskeletal disorder, the rehabilitation therapy providing method and system according to the present invention can provide a patient with a behavioral treatment program customized for the same musculoskeletal disorder, taking into account the patient's pain duration and the degree of cognitive distortion. Furthermore, patients can receive cognitive behavioral therapy customized to their own condition.

[0418] Furthermore, the digital-based musculoskeletal rehabilitation therapy delivery method and system according to the present invention can sequentially deliver multiple treatment programs in conjunction with exercise plans during the rehabilitation period, allowing patients to systematically receive cognitive behavioral therapy along with rehabilitation exercises and complete the rehabilitation therapy without interruption.

[0419] Furthermore, the digital-based musculoskeletal rehabilitation treatment provision method and system according to the present invention updates the treatment program to be useful for the patient's cognitive behavioral treatment based on treatment response data collected during the progress of the cognitive behavioral treatment. This makes it possible to provide an updated cognitive behavioral treatment that takes into account the patient's improvement status, rather than continuously providing the patient with an initially determined cognitive behavioral treatment method.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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."

[0424] 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.

[0425] 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."

[0426] 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.

[0427] 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.

[0428] 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)."

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] Doctor D can prescribe medication to patient U by referring to user DB 30 that contains user information about patient U.

[0434] 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.

[0435] 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 motion analysis model and provide the results on the patient terminal 10.

[0436] 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.

[0437] 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.

[0438] 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).

[0439] 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."

[0440] 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.

[0441] Here, "joint points" may refer to multiple joints of patient U (or a part of patient U's body that includes joints).

[0442] 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.

[0443] 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.

[0444] 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."

[0445] 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.

[0446] Here, in the third data processing method, the exercise therapy application 100 and the artificial intelligence server 200 may process data sequentially or simultaneously.

[0447] 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.

[0448] 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.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] 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.

[0453] 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."

[0454] 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.

[0455] 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 .

[0456] 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.

[0457] 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.

[0458] 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.

[0459] 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."

[0460] 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.

[0461] 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.

[0462] 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."

[0463] 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.

[0464] 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.

[0465] 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").

[0466] 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.

[0467] 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.

[0468] 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)).

[0469] 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.

[0470] 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.

[0471] 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.

[0472] 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."

[0473] 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.

[0474] 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.

[0475] 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.

[0476] 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.

[0477] 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).

[0478] 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).

[0479] 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.

[0480] 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.

[0481] 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.

[0482] 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.

[0483] 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.

[0484] 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).

[0485] 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.

[0486] The exercise motion analysis process performed by the exercise treatment provision system 1000 will be described in more detail below.

[0487] 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).

[0488] 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."

[0489] 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.

[0490] 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.

[0491] 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).

[0492] 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).

[0493] 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).

[0494] 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.

[0495] 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."

[0496] 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.

[0497] As shown in (b) of Figure 15, the exercise page may include an exercise list L, and the exercise list L may include items V1 to V6 corresponding to exercise guide images 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.

[0498] 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").

[0499] 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.

[0500] 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).

[0501] 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.

[0502] 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.

[0503] 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.

[0504] 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.

[0505] 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.

[0506] 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.

[0507] 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.

[0508] 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.

[0509] 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).

[0510] 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.

[0511] 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.

[0512] Here, "joint points" may refer to multiple joints of patient U (or a part of patient U's body that includes joints).

[0513] 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.

[0514] 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.

[0515] 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.

[0516] 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).

[0517] 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.

[0518] 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.

[0519] 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.

[0520] 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 .

[0521] 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.

[0522] 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.

[0523] 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.

[0524] Additionally, the exercise therapy delivery system 1000 can extract the identified visible joint points as key points.

[0525] 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.

[0526] 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".

[0527] 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.

[0528] 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.

[0529] 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.

[0530] 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".

[0531] 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.

[0532] 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.

[0533] 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.

[0534] 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.

[0535] 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.

[0536] 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.

[0537] 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.

[0538] 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.

[0539] 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.

[0540] 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.

[0541] 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.

[0542] 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."

[0543] 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.

[0544] 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.

[0545] 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.

[0546] 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.

[0547] 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.

[0548] 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.

[0549] The therapeutic exercise provision system 1000 can analyze a patient's exercise movements by determining whether the relative positional relationships between key points satisfy the rule information. A method for analyzing a joint range of motion based on the relative positional relationships between key points and the rule information will be described below as an example. However, the content described below is merely one embodiment for analyzing a patient's movements based on the relative positional relationships between key points and the rule information, and various patient movements can be analyzed based on the relative positional relationships between key points and the rule information in the present invention.

[0550] 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.

[0551] 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.

[0552] 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.

[0553] 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.

[0554] 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.

[0555] 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.

[0556] 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.

[0557] 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.

[0558] 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.

[0559] The exercise therapy delivery system 1000 can extract key points in each of the first and second frames under analysis.

[0560] A first group of key points to be analyzed corresponding to each of the plurality of joint points can be extracted from the first frame to be analyzed, and a second group of key points to be analyzed corresponding to each of the plurality of joint points can be extracted from the second frame to be analyzed.

[0561] 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.

[0562] 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.

[0563] 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.

[0564] 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.

[0565] 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.

[0566] 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.

[0567] 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.

[0568] 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).

[0569] 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.

[0570] 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).

[0571] 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.

[0572] 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.

[0573] 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.

[0574] 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.

[0575] 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.

[0576] 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.

[0577] 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.

[0578] 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.

[0579] 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.

[0580] 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.

[0581] 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.

[0582] 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.

[0583] The training data used to train the posture estimation model of the present invention will be specifically described below.

[0584] 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.

[0585] 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.

[0586] Database 40 may store training data for training pose estimation model 52 as a training data set.

[0587] 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.

[0588] 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.

[0589] 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."

[0590] Meanwhile, the "exercise video 300" described in the present invention may include an "analysis target exercise video" and a "learning target exercise video."

[0591] 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.

[0592] 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 training data to train the posture estimation model.

[0593] 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.

[0594] 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.

[0595] 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.

[0596] 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.

[0597] 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.

[0598] 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.

[0599] 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.

[0600] 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.

[0601] 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.

[0602] 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.

[0603] 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.

[0604] 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.

[0605] 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.

[0606] 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).

[0607] 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.

[0608] 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.

[0609] 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).

[0610] 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.

[0611] 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).

[0612] 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.

[0613] 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.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] 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.

[0618] 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.

[0619] 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.

[0620] 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.

[0621] 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 range of motion information 221 of a specific joint point P1 around the specific joint point P1.

[0622] 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.

[0623] 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.

[0624] 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).

[0625] 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.

[0626] The learning data set 400 used for estimating the user's exercise posture will be described in more detail below.

[0627] 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.

[0628] 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.

[0629] 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.

[0630] 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.

[0631] 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.

[0632] 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.

[0633] 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.

[0634] 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.

[0635] 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.

[0636] 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.

[0637] 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.

[0638] 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.

[0639] 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.

[0640] The following specifically describes the multiple data groups and the relationships between each group.

[0641] 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.

[0642] 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.

[0643] 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.

[0644] 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.

[0645] 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.

[0646] 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.

[0647] 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.

[0648] 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.

[0649] 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.

[0650] 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.

[0651] 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.

[0652] 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.

[0653] 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.

[0654] 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.

[0655] 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.

[0656] 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.

[0657] 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.

[0658] 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.

[0659] 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.

[0660] 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.

[0661] 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.

[0662] 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.

[0663] 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.

[0664] 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.

[0665] 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."

[0666] 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.

[0667] 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]".

[0668] 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.

[0669] 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.

[0670] As described above, the database 40 may contain a plurality of training target joint points P1 and P2 in a predefined order.

[0671] 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.

[0672] 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.

[0673] 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.

[0674] 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.

[0675] 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."

[0676] 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.

[0677] 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.

[0678] 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."

[0679] 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.

[0680] 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 exp...

Claims

1. A digitally based musculoskeletal rehabilitation treatment delivery system: Executing the application on a user terminal where the patient account is logged in; providing an exercise list according to the exercise plan to the user terminal on which the application is executed; a step of playing, on the user terminal, exercise videos corresponding to the plurality of exercise items, respectively, according to the plurality of exercise items constituting the exercise list; providing an evaluation page to the user terminal to receive an evaluation of the exercise plan from the patient based on whether the playback level of the exercise video meets a preset standard; updating the exercise plan based on evaluation information received via the evaluation page and exercise matching information present in a storage unit, The evaluation information is First evaluation information in which the patient evaluates the difficulty of the exercise plan; and second evaluation information in which at least one exercise item among the plurality of exercise items is selected as a high-difficulty exercise, The exercise matching information includes: For each indication, exercise items for treating the indication are matched to a group; Each of the exercise items for treating the indication is matched with exercise difficulty level information; In the step of updating the exercise plan, changing the difficulty levels of the exercise items constituting the exercise plan based on the first evaluation information and the exercise matching information; A method for providing digital-based musculoskeletal rehabilitation therapy, characterized in that, based on the second evaluation information and the exercise matching information, the exercise item selected as the high-difficulty exercise is excluded from the exercise plan, and other exercise items that are matched to the same group as the selected exercise item and have the same difficulty level information are included in the exercise plan.

2. The exercise plan includes:

2. The method for providing digital-based musculoskeletal rehabilitation therapy according to claim 1, wherein at least a portion of the exercise items related to the patient's indications included in the patient's prescription information are assigned to each of a plurality of different days constituting a predetermined rehabilitation period.

3. In the step of providing the exercise list, providing the exercise list including the plurality of exercise items assigned to specific days on which the exercise video is played based on a reference date on which counting of the preset rehabilitation period is started in the user terminal; The evaluation page includes:

3. The method for providing digital-based musculoskeletal rehabilitation therapy according to claim 2, wherein the exercise video is provided to the user terminal on the specific day if the playback level of the exercise video meets the preset criteria in order to perform an evaluation related to the plurality of exercise items provided to the patient on the specific day.

4. The evaluation page includes: a first evaluation area for evaluating the difficulty levels of the plurality of exercise items assigned to the specific day; A second evaluation area for selecting a highly difficult exercise from the plurality of exercise items; a third evaluation area for evaluating exercise pain associated with the plurality of exercise items; In the step of updating the exercise plan, 4. The method for providing digital-based musculoskeletal rehabilitation therapy according to claim 3, characterized in that the difficulty levels of the exercise items constituting the exercise plan are changed or at least some of the exercise items constituting the exercise plan are replaced with the other exercise items based on the evaluation information received through at least one of the first evaluation area, the second evaluation area, and the third evaluation area.

5. The method for providing digital-based musculoskeletal rehabilitation therapy according to claim 4, characterized in that exercise items according to the updated exercise plan are provided to the user terminal from the day after the specific day has passed.

6. further comprising assigning to the patient account a cognitive behavioral treatment plan to be performed in conjunction with the exercise plan; The step of assigning the cognitive behavioral treatment plan includes: receiving, via the user terminal, questionnaire response data for a plurality of questionnaire data; Detecting condition information of the patient related to the duration of pain and the degree of cognitive distortion of the patient based on the questionnaire response data; Identifying a user group corresponding to the patient's condition information from among a plurality of user groups classified according to pain duration and degree of cognitive distortion; determining an initial treatment protocol corresponding to the user group from among a plurality of treatment protocols; and providing a plurality of specific treatment programs included in the initial treatment protocol in sequence during a predetermined rehabilitation period.

7. providing an initial screen page in response to the application being executed on the user terminal; The initial screen page is a first menu item for accessing a list of exercises according to said exercise plan; a second menu item for accessing the rating page; a third menu item for accessing the cognitive behavioral treatment plan assigned along with the exercise plan; a fourth menu item for accessing a page for performing a functional assessment for a specific movement of the patient; 7. The method for providing digital-based musculoskeletal rehabilitation therapy of claim 6, characterized in that if the playback level of the exercise video does not meet the preset standard, provision of the evaluation page to the user terminal is restricted even if the second menu item is selected on the user terminal.

8. The functional assessment for the specific movement is performed at predetermined intervals of days during a predetermined rehabilitation period to which the exercise plan is assigned; The fourth menu item is: The initial screen page is configured to be included on a specific day according to the preset day interval, The method of claim 7, wherein the initial screen page does not include any day other than the specific day during the rehabilitation period.

9. A communication unit that receives prescription information including an exercise plan corresponding to an indication of a patient from a doctor terminal; a storage unit storing exercise matching information in which, for each of the indications, exercise items for treating the indications are matched to groups, and difficulty level information of exercise is matched to each of the exercise items for treating the indications; a control unit that, in response to an application being executed on a user terminal to which a patient account is logged in, provides the user terminal with an exercise list according to the exercise plan; The control unit On the user terminal, exercise videos corresponding to the plurality of exercise items are played back in accordance with the plurality of exercise items constituting the exercise list; providing an evaluation page to the user terminal so that the patient can evaluate the exercise plan based on whether the playback level of the exercise video satisfies a predetermined standard; updating the exercise plan based on the evaluation information received via the evaluation page and the exercise matching information stored in the storage unit; The evaluation information is First evaluation information in which the patient evaluates the difficulty of the exercise plan; and second evaluation information in which at least one exercise item among the plurality of exercise items is selected as a high-difficulty exercise, The control unit changing the difficulty levels of the exercise items constituting the exercise plan based on the first evaluation information and the exercise matching information; A digital-based musculoskeletal rehabilitation treatment provision system, characterized in that, based on the second evaluation information and the exercise matching information, the exercise item selected as the high-difficulty exercise is excluded from the exercise plan, and other exercise items that are matched to the same group as the selected exercise item and have the same difficulty level information are included in the exercise plan.

10. A program executed by one or more processes in an electronic device and stored on a computer-readable recording medium, The computer, Selecting an exercise plan to be provided to the patient based on prescription information including an exercise plan corresponding to the patient's indications being assigned from a doctor terminal; Executing the application on a user terminal where the patient account is logged in; providing an exercise list according to the exercise plan to the user terminal on which the application is executed; a step of playing, on the user terminal, exercise videos corresponding to the plurality of exercise items, respectively, according to the plurality of exercise items constituting the exercise list; providing an evaluation page to the user terminal so that the patient can evaluate the exercise plan based on whether the playback level of the exercise video satisfies a preset standard; updating the exercise plan based on the evaluation information received via the evaluation page and the exercise matching information stored in the storage unit; The evaluation information is First evaluation information in which the patient evaluates the difficulty of the exercise plan; and second evaluation information in which at least one exercise item among the plurality of exercise items is selected as a high-difficulty exercise, The exercise matching information includes: For each of the indications, exercise items for treating the indication are matched to a group; Each of the exercise items for treating the indication is matched with exercise difficulty level information; In the step of updating the exercise plan, changing the difficulty levels of the exercise items constituting the exercise plan based on the first evaluation information and the exercise matching information; A program stored on a computer-readable recording medium, comprising instructions to exclude from the exercise plan an exercise item selected as the high-difficulty exercise based on the second evaluation information and the exercise matching information, and to include in the exercise plan other exercise items that are matched to the same group as the selected exercise item and have the same difficulty level information.

Images