System for recommending customized exercise program according to physical ability of user and operation method thereof

Abstract

A method for recommending a user-customized exercise program according to the present invention may comprise: a first step of providing a first exercise video for a first body area among a plurality of body areas of a user, and extracting a first exercise state evaluation score for each of one or more first detailed body areas included in the first body area on the basis of a joint position and muscle movement of the first body area of the user; a second step of determining a first detailed body area for which second exercise state evaluation information needs to be extracted from at least one of the first detailed body areas on the basis of the first exercise state evaluation score; a third step of recommending a second exercise video corresponding to the first detailed body area for which the second exercise state evaluation information needs to be extracted; and a fourth step of providing the recommended second exercise video and calculating a second exercise state evaluation score on the basis of the joint position and muscle movement of the first detailed body area of the user.

Description

Personalized exercise program recommendation system based on user's physical ability and method of operation thereof

[0001] The present invention relates to a customized exercise program recommendation system based on a user's physical ability and a method of operation thereof, and more specifically, to a device and method of operation thereof that recommends a customized exercise program suitable for body areas requiring exercise prescription based on the movement of a user's joints and muscles.

[0002] The elderly and frail adults, including the elderly and infirm, experience reduced muscle strength and flexibility compared to the general population, and are prone to weakened balance and cardiorespiratory function. Since these physical changes increase the risk of falls, musculoskeletal disorders, and the development of chronic diseases, appropriate exercise is essential to maintain independence in daily life and improve quality of life. Recently, with the rapid surge in the healthcare market for promoting the health of the elderly, there has been a significant increase in fitness centers and home training video content and applications designed to maintain and improve their health. However, for existing fitness centers, deploying specialized personnel for senior healthcare requires a substantial amount of time and cost to train. Furthermore, existing home training video content and applications often rely on following fixed exercise videos without considering the user's physical characteristics or fitness level. Consequently, users often struggle to keep up with the videos or lack the knowledge to identify exercises that can address their weaknesses, resulting in low efficiency.

[0003] Furthermore, it discloses only the feature of analyzing posture and movement based on balance for specific movements, but fails to disclose the feature of analyzing posture and movement in a complex manner by varying analysis conditions for each body region.

[0004] The present invention provides a customized exercise program recommendation system and a method of operation thereof that recommends a customized exercise program suitable for each body part based on a physical ability state measured based on the movement of joints and muscles for each body region of the user.

[0005] The objects of the present invention are not limited to those mentioned above, and other unmentioned objects and advantages of the present invention may be understood from the following description and will be more clearly understood by the embodiments of the present invention. Furthermore, it will be readily apparent that the objects and advantages of the present invention can be realized by the means and combinations thereof set forth in the claims.

[0006] A method for recommending a user-customized exercise program to achieve such an objective may include: a first step of providing a first exercise video for a first body region among a plurality of body regions of a user, and extracting a first exercise state evaluation score for at least one first detailed body region included in the first body region based on the joint position and muscle movement of the user's first body region; a second step of determining a first detailed body region among at least one first detailed body region from which second exercise state evaluation information needs to be extracted based on the first exercise state evaluation score; a third step of recommending a second exercise video corresponding to the first detailed body region from which second exercise state evaluation information needs to be extracted; and a fourth step of providing the recommended second exercise video and calculating a second exercise state evaluation score based on the joint position and muscle movement of the user's first detailed body region.

[0007] Additionally, the exercise program recommendation system includes a camera module that captures a 3D image of a user in real time; and at least one controller, wherein the at least one controller senses the joint position and muscle movement of the user from the captured 3D image to extract first image data, sequentially calculates a first exercise state evaluation score for each of the user's multiple body regions, and if the first exercise state evaluation score is less than a first threshold value, calculates a second exercise state evaluation score for at least one detailed body region included in the corresponding body region, extracts a physical ability state score based on the first exercise state evaluation score and the second exercise state evaluation score for the multiple body regions, and can recommend customized exercise suitable for the user's condition based on the physical ability state score.

[0008] According to the present invention as described above, by recommending a customized exercise program suitable for the body area requiring exercise prescription based on physical ability evaluated according to the movement of joints and muscles for each body area of ​​the user, effective exercise prescription for the user's health management can be provided.

[0009] In addition, by setting different analysis conditions for each body region, the user's physical condition can be diagnosed more precisely through a comprehensive analysis of muscle and joint movements, and effective customized exercises can be prescribed accordingly.

[0010] FIG. 1 is a drawing of a customized exercise program recommendation system based on a user's physical ability according to an embodiment of the present invention.

[0011] FIGS. 2a and 2b are drawings relating to image images corresponding to a chair squat exercise according to one embodiment of the present invention.

[0012] FIGS. 3 to 5 are drawings showing first evaluation motion information collected through a chair squat exercise according to an embodiment of the present invention, first target motion information that serves as a standard for the evaluation, and the first exercise state evaluation score.

[0013] FIG. 6 is a diagram showing a customized exercise list corresponding to a physical ability status score according to an embodiment of the present invention.

[0014] FIG. 7 is a drawing relating to a user-customized exercise recommendation method based on physical condition according to an embodiment of the present invention.

[0015] FIG. 8 is a drawing relating to a method for calculating a first exercise state evaluation score according to an embodiment of the present invention.

[0016] FIG. 9 is a diagram relating to a method for calculating a second motion state evaluation score according to an embodiment of the present invention.

[0017] FIG. 10 is a drawing relating to a method for calculating a user's physical ability status score according to an embodiment of the present invention.

[0018] The aforementioned objectives, signatures, and advantages are described in detail below with reference to the attached drawings, thereby enabling those skilled in the art to easily implement the technical concept of the present invention. In describing the present invention, detailed descriptions of known technologies related to the present invention are omitted if it is determined that such descriptions would unnecessarily obscure the essence of the invention. Hereinafter, preferred embodiments according to the present invention will be described in detail with reference to the attached drawings. In the drawings, the same reference numerals are used to indicate the same or similar components.

[0019] Figure 1 is a diagram of a customized exercise program recommendation system based on a user's physical ability.

[0020] As illustrated in FIG. 1, the customized exercise program recommendation system (1) may include a camera (10), a display unit (20), a memory (30), and a controller (40).

[0021] The above camera (10) is a component that captures the movements of a user performing first and second exercise videos provided through a customized exercise program recommendation system (1) from multiple angles, thereby capturing the user's appearance in three dimensions. The video / image captured through the above camera (10) can be stored in memory (30) and displayed on a display (20). There may be one or more cameras (10), and they may be electrically connected to a controller (40) or wirelessly connected outside the customized exercise program recommendation system (1).

[0022] The above display unit (20) can output a first exercise video and / or a second exercise video for evaluating the user's exercise state.

[0023] The above controller (40) may include an exercise evaluation control unit (41) and an exercise recommendation unit (42). The exercise evaluation control unit (41) may include a first exercise state evaluation unit (41A), a comparison unit (4B), a second exercise state evaluation unit (41C), and a physical ability state evaluation unit (41D).

[0024] The first exercise state evaluation unit (41A) may provide the user with a first exercise video corresponding to each of the user's multiple body regions in order to evaluate each of the user's multiple body regions. For example, the multiple body regions may include a first body region, a second body region, and a third body region. The first body region may include a lower body region, the second body region may include an upper body region, and the third body region may include a core region. Furthermore, the first exercise state evaluation unit (41A) may sequentially read the first exercise video corresponding to each of the first to third body regions stored in the memory (30) and provide it through the display. Here, the first exercise video corresponding to each body region may include a multi-joint exercise video. The multi-joint exercise is an exercise performed by simultaneously using multiple joints and major muscles of the body. For example, the lower body exercise corresponding to the first body area may include any one of chair squats (hips, legs), side steps (lower body, gluteal muscles), and seated leg raises (lower body). The upper body exercise corresponding to the second body area may include any one of wall push-ups (chest, arms, shoulders), arm rotations (shoulders), and band rows (back, arms). The core exercise corresponding to the third area may include any one of seated upper body twists (core, spine), seated knee pulls (abdomen, thigh muscles), and wall planks (abdomen, back). Hereinafter, for convenience of explanation, the chair squat exercise will be described as an example of the lower body exercise corresponding to the first body area.

[0025] Next, the first exercise state evaluation unit (41A) can collect first video data of the user performing an exercise movement following the first exercise video, and then sense joint positions and muscle movements in the first video data to extract first evaluation movement information. That is, in order to collect the first evaluation movement information from the first video data, the first exercise state evaluation unit (41A) can sense joint positions and muscle movements corresponding to the body area to be evaluated in the first video data. The method of sensing the joint positions and muscle movements can be to extract the first evaluation movement information by sensing the body area to be evaluated based on joint position and muscle movement information pre-set for each exercise video corresponding to the body area to be evaluated. The reason for collecting the first evaluation movement information is to evaluate similarity and exercise intensity by comparing the first target movement information corresponding to the first exercise video with the first evaluation movement information. The first video data may be composed of multiple frames. The first evaluation motion information may include at least one of joint angle information, information on changes in movement speed and acceleration, and the duration of the exercise motion. The joint angle information can be extracted by sensing the positions of multiple joints corresponding to at least one detailed body region included in the first body region, and by calculating the angle and distance between the joints. Through the joint angle information, the similarity of the user's exercise posture can be evaluated by determining whether the joint angle falls within a preset range. The movement speed information is information calculated by determining the positional change of the user's joint positions extracted from each frame of the first image data in chronological order. Additionally, the acceleration change information is information calculated based on the rate of change of speed over time, based on the movement speed information. That is, for each frame of the first image data, it can be calculated based on the position of the joints, changes in speed according to muscle movement, and time.

[0026] The duration of the exercise motion described above is information extracted by sensing the position of each joint and the movement of the muscles for each frame of the first video data and maintaining them continuously. In this way, the intensity of the exercise can be evaluated through the calculated information on changes in body speed and acceleration, and the duration of the exercise motion. That is, if the speed of the body's movement increases and the duration of the exercise motion is shorter than the first target motion information time, the first exercise video may be judged as high-intensity exercise for the user. Conversely, if the body's speed decreases or remains constant, or if the duration of the exercise falls within the target range, the first exercise video may be evaluated as low-intensity exercise for the user.

[0027] For example, referring to FIGS. 2a and 2b, the first exercise state evaluation unit (41A) may provide a chair squat exercise video to evaluate the lower body area of ​​the user and may collect first video data of the user performing the chair squat exercise.

[0028] Based on joint position and muscle movement information corresponding to the knee, ankle, and hip joints—which are pre-set detailed body regions to be evaluated—from the first collected video data, first evaluation motion information for the corresponding detailed body regions can be extracted through the chair squat exercise. For example, the joint angle information that can be collected when evaluating the chair squat exercise may include knee joint angles, ankle joint angles, and hip joint angles. The muscle activation information may include muscle activation information for the quadriceps, gluteal muscles, hamstrings, calf muscles, and core muscles. Additionally, information on movement speed and acceleration change may include information on descent speed, ascent speed, descent acceleration, and changes in ascent acceleration. Furthermore, the duration of the exercise motion may include the duration during descent, the duration at the lowest point of descent, and the duration during ascent.

[0029] Next, the first exercise evaluation control unit (41A) can compare the first evaluation motion information with the first target motion information of the first exercise video to evaluate whether the first evaluation motion information is included within the range of the first target motion information, and calculate a first exercise state evaluation score corresponding to each of at least one detailed body region included in the first body region. Here, the first target motion information of the first exercise video is information about a reference exercise posture generated based on the joint positions and muscle movements of a trainer or character who assumes a correct exercise posture in advance. For example, the first exercise evaluation control unit (41A) can calculate a first exercise state evaluation score by evaluating whether the first evaluation motion information corresponding to a chair squat exercise motion is included within the range of the first target motion information. Here, the explanation will be made with reference to FIGS. 3 to 5. FIGS. 3 to 5 are drawings showing first evaluation motion information collected through a chair squat exercise according to an embodiment of the present invention, first target motion information serving as a standard for the evaluation, and first exercise state evaluation score. The first evaluation motion information may include information related to the knee, ankle joint, and hip joint. A first exercise state evaluation score can be calculated by comparing the first evaluation motion information corresponding to each of the knee, ankle joint, and hip joint with the first target motion information corresponding to the first exercise video. It can be confirmed that the first exercise state evaluation score corresponding to the knee is 79 points, the first exercise state evaluation score corresponding to the ankle is 81 points, and the first exercise state evaluation score corresponding to the hip joint is 81 points.

[0030] Returning to FIG. 1, the comparison unit (41B) can determine the detailed body area requiring a second exercise state evaluation score by comparing each first exercise state evaluation score calculated for at least one detailed body area with a preset first threshold value (TH1). Here, the first threshold value (TH1) can be set differently for each exercise.

[0031] The comparison unit (41B) can determine that there are no detailed body evaluation areas for which a second exercise state evaluation score needs to be calculated if, as a result of comparing the first exercise state evaluation score calculated for each detailed body area with the first threshold value (TH1), there is no first exercise state evaluation score that is less than the first threshold value. Then, the first exercise evaluation control unit (41A) can identify a body area among the plurality of body areas for which a first exercise state evaluation score has not been calculated, and then provide a first exercise video corresponding to that body area to the user.

[0032] On the other hand, the comparison unit (41B) can determine that if there is a first exercise state evaluation score that is less than the first threshold value (TH1) when comparing the first exercise state evaluation score calculated for each detailed body area with the first threshold value (TH1), the detailed body area corresponding to the first exercise state evaluation score is a detailed body area requiring a second exercise state evaluation score. For convenience of explanation, the detailed body area requiring the second exercise state evaluation score is defined as a detailed body evaluation area. In order to calculate the second exercise state evaluation score for the detailed body evaluation area, the comparison unit (41B) may receive a recommendation for a second exercise video corresponding to the detailed body evaluation area from the exercise recommendation unit (42). That is, the comparison unit (41B) may transmit the first exercise state evaluation score corresponding to the detailed body evaluation area to the exercise recommendation unit (42) in order to receive a recommendation for a second exercise video corresponding to the detailed body evaluation area.

[0033] For example, if the first threshold value (TH1) corresponding to the chair squat exercise is 80 points, the comparison unit (41B) can compare the first exercise state evaluation score corresponding to the knee, ankle joint, and hip joint, respectively, with the first threshold value (TH1). As a result of the comparison, the score for the knee is 79 points, which is lower than the first threshold value (TH1), so the knee can be determined as a detailed body evaluation area.

[0034] And, the comparison unit (41B) can transmit the first exercise state evaluation score corresponding to the knee to the exercise recommendation unit (42).

[0035] The exercise recommendation unit (42) recommends a second exercise video by reflecting the first exercise state evaluation score corresponding to the detailed body evaluation area received from the comparison unit (41B) and transmits it to the second exercise state evaluation unit. The second exercise video may include a video related to a single joint. Additionally, the second exercise video may be determined according to the exercise intensity evaluated based on the movement speed and acceleration change included in the first exercise state evaluation score and the duration of the exercise movement. For example, looking at the movement speed and acceleration change related to the knee, it can be seen that the user's movement speed is 0.3 for descent and 0.3 for ascent, and the acceleration change is 1 for descent and 1 for ascent. It can be seen that the movement speed included in the first target movement information is 0.5 for descent and 0.5 for ascent, and the acceleration is 0 for descent and 0 for ascent. When comparing the first evaluation movement information with the first target movement information, it can be seen that the speed and acceleration have increased rapidly. Therefore, for the user, the chair squat exercise can be determined as a high-intensity exercise, and accordingly, a low-intensity exercise can be recommended in the second exercise video. The second exercise video corresponding to the knee-related low-intensity exercise may include any one of the following: sitting knee extension exercise, lying leg lift exercise, and stair climbing exercise. For example, the exercise recommendation unit (42) may recommend the knee extension exercise as the second exercise video.

[0036] The second exercise state evaluation unit (41C) provides the user with a second exercise video recommended by the exercise recommendation unit (42) and can calculate a second exercise state evaluation score based on the joint positions and muscle movements of the user's detailed body evaluation area. Specifically, the second exercise state evaluation unit (41C) collects second video data of the user performing an exercise movement following the second exercise video, and can collect second evaluation movement information by sensing the joint positions and muscle movements corresponding to the detailed body evaluation area to be evaluated in the second exercise video, which is pre-set in the second video data. For example, the second exercise state evaluation unit can collect a second video image of a user performing a knee extension exercise, and can extract the second evaluation movement information by reflecting the joint position and muscle movement information related to the knee from the second video image. That is, the major muscles considered when evaluating the knee extension exercise may include the quadriceps femoris, hamstrings, and gastrocnemius, and the joints may include the knee joint and hip joint. The major muscles and joints considered above can be pre-set, and second evaluation motion information can be extracted by sensing the corresponding joint positions and muscle movements.

[0037] For example, the joint angle information that can be collected when evaluating the above knee extension exercise may include knee angle and hip joint angle. The muscle activation information may include muscle activation information for the quadriceps, hamstrings, and gastrocnemius muscles. The information on changes in movement speed and acceleration may include speed and acceleration information for knee extension and flexion. The duration of the exercise movement may include the duration of maintenance after knee extension.

[0038] In addition, the second exercise state evaluation unit (41C) can compare the second evaluation motion information with the second target motion information of the second exercise video to evaluate whether the second evaluation motion information is included within the range of the second target motion information, and calculate a second exercise state evaluation score corresponding to the detailed body evaluation area. The second exercise state evaluation unit (41C) can transmit the calculated second exercise state evaluation score to the physical ability state evaluation unit (41D).

[0039] The above physical ability state evaluation unit (41D) checks whether the evaluation is completed for all of the plurality of body regions. If, as a result of the check, the evaluation is not completed for the plurality of body regions, the first exercise state evaluation unit (41A) can be repeated to calculate the first exercise state evaluation score for the unevaluated body regions among the plurality of body regions.

[0040] On the other hand, the physical ability state evaluation unit (41D) calculates a final exercise state evaluation score based on a first exercise state evaluation score and a second exercise state evaluation score corresponding to the inactive and functionally weakened body area among the plurality of body areas.

[0041] The physical ability status evaluation unit (41D) can calculate the user's physical ability status score based on the final exercise status evaluation score. Specifically, the physical ability status score can be calculated by assigning a high weight to Activities of Daily Living (ADL) items corresponding to the body area that is inactive or has weakened function among a plurality of body areas. The ADL may include basic activities for living as a human being, such as sitting and standing, using the toilet, dressing, showering, and moving.

[0042] For example, the physical ability status assessment unit (41D) may assign a higher weight to the two items of daily living activities (ADL) when the knee is a body area that is inactive or has weakened function among the multiple body areas, as it plays a more important role in sitting, standing, or movement activities. For example, the weights assigned to the ADL items may be 50% for sitting and standing, 30% for movement, 10% for dressing, 30% for using the toilet, and 5% for eating.

[0043] If the final exercise state evaluation score related to the knee calculated based on the first and second exercise state scores is 70 points, the physical ability state evaluation unit (41D) can calculate the following [Table 1] by applying weights according to each item of daily living activities related to the knee.

[0044] Item Weight Score Sitting and Standing 50% 70 x 50% = 35 points Movement 30% 70 x 30% = 21 points Dressing 10% 70 x 10% = 7 points Toilet Use 30% 70 x 30% = 21 points Eating 5% 70 x 5% = 3.5 points Physical Status Score 87.5

[0045] The above physical ability status evaluation unit (41D) can transmit the calculated physical ability status score to the exercise recommendation unit (42). The exercise recommendation unit (42) can recommend customized exercises corresponding to the physical ability status score to restore the user's body areas that are inactive or have weakened functions. The exercise recommendation unit (42) can determine the user's exercise level based on the physical ability status score and, accordingly, recommend exercises to strengthen the inactive or weakened body areas. For example, referring to FIG. 6, the exercise recommendation unit (42) can determine that the exercise level is advanced by checking the physical ability state score range containing the physical ability state score of 87.5 points in the knee strengthening exercise list stored in the memory, and can recommend at least one exercise among leg extension, step-up, walking lunge, and balance pad stand, which correspond to the physical ability state score range, to the user. FIG. 7 is a drawing of a user-customized exercise recommendation method according to physical condition according to an embodiment of the present invention.

[0046] As illustrated in FIG. 7, in step S701, the controller (40) can provide a first exercise video corresponding to a first body region among a plurality of body regions and calculate a first exercise state evaluation score based on joint position and muscle movement corresponding to the first body region.

[0047] Specifically, the controller (40) may provide the user with a first exercise video corresponding to the first body region. The first exercise video may include a multi-joint exercise video corresponding to the first body region. Here, the multi-joint exercise is an exercise performed by simultaneously using multiple joints and major muscles of the body. The first exercise video corresponding to the first body region may represent any one of an upper body exercise corresponding to the upper body region, a lower body exercise corresponding to the lower body region, and a core exercise corresponding to the core region. Next, the controller (40) may calculate a first exercise state evaluation score corresponding to at least one detailed body region included in the first body region based on the joint position and muscle movement of the user's first body region during the process of the user exercising through the first exercise video. This will be explained in detail in FIG. 8.

[0048] FIG. 8 is a drawing relating to a method for calculating a first exercise state evaluation score according to an embodiment of the present invention.

[0049] As illustrated in FIG. 8, in step S801, the controller (40) collects first video data of the user performing an exercise movement along the first exercise video, and can collect first evaluation movement information by sensing (extracting) joint positions and muscle movements corresponding to the first body region from the first video data. The reason for collecting the first evaluation movement information is to evaluate similarity and exercise intensity by comparing the first target movement information corresponding to the first exercise video with the first evaluation movement information. The first video data may be composed of multiple frames. The first evaluation movement information may include at least one of joint angle information, muscle activation grade, movement speed and acceleration change information, and the duration of the exercise movement. The joint angle information may be extracted by sensing the positions of multiple joints corresponding to at least one detailed body region included in the first body region, and by calculating the angle and distance between the joints. By determining whether the joint angle falls within a preset range using the joint angle information above, the similarity to the user's exercise posture can be evaluated.

[0050] The above muscle activation grade can be extracted by sensing pre-set muscle locations and muscle movements corresponding to the first exercise video from the above first video data, and the degree of activation and fatigue level of a specific muscle can be evaluated through EMG data or other physiological indicators. The controller (40) can evaluate muscle fatigue according to the muscle activation grade.

[0051] The above movement velocity information is information calculated by determining the positional change of the user's joint positions extracted from each frame of the first image data in chronological order. Additionally, the acceleration change information is information calculated based on the time rate of change of velocity, based on the above movement velocity information. That is, for each frame of the first image data, it can be calculated based on the velocity change and time according to the joint position and muscle movement.

[0052] The duration of the exercise motion described above is information extracted by sensing the position of each joint and the movement of the muscles for each frame of the first video data and maintaining them continuously. In this way, the intensity of the exercise can be evaluated through the calculated information on changes in body speed and acceleration, and the duration of the exercise motion. That is, if the speed of the body's movement increases and the duration of the exercise motion is shorter than the first target motion information time, the first exercise video may be judged as high-intensity exercise for the user. Conversely, if the body's speed decreases or remains constant, or if the duration of the exercise falls within the target range, the first exercise video may be evaluated as low-intensity exercise for the user.

[0053] In steps S803 and S805, the controller (40) can compare the first evaluation motion information with the first target motion information of the first exercise video to evaluate whether the first evaluation motion information is included within the range of the first target motion information and calculate a score for each item. Based on the calculated score for each item, a first exercise state evaluation score corresponding to each of at least one detailed body area included in the first body area can be calculated. Here, the first target motion information of the first exercise video is information about a reference exercise posture generated based on the joint positions and muscle movements of a trainer or character who assumes a correct exercise posture in advance.

[0054] Returning to FIG. 7, in steps S703 and S705, the controller (40) can determine the detailed body area requiring a second exercise state evaluation score by comparing each first exercise state evaluation score calculated for at least one detailed body area with a preset first threshold value (TH1). Here, the first threshold value (TH1) may be set differently for each exercise. If, as a result of comparing the first exercise state evaluation score calculated for each detailed body area with the first threshold value, there is no first exercise state evaluation score less than the first threshold value (TH1) (N0), the controller (40) determines that there is no detailed body evaluation area requiring a second exercise state evaluation score, and can repeat steps S701 through S705 to calculate the first exercise state evaluation score for the body area among the plurality of body areas for which evaluation has not been completed.

[0055] On the other hand, the controller (40) compares the first exercise state evaluation score calculated for each detailed body region with the first threshold value (TH1). If, among the at least one first exercise state evaluation score, there exists a first exercise state evaluation score that is less than the first threshold value (TH1), the controller recommends a second exercise video corresponding to the detailed body evaluation region so that a second exercise state evaluation score can be calculated for the detailed body region corresponding to the first exercise state evaluation score that is less than the first threshold value (TH1) (step S707). The second exercise video may include exercises related to single joints. Additionally, the second exercise video may be determined according to the exercise intensity evaluated based on the movement speed and acceleration change included in the first exercise state evaluation score and the duration of the exercise motion.

[0056] In step S709, the controller (40) provides the recommended second exercise video to the user and can calculate a second exercise state evaluation score based on the joint position and muscle movement of the user's detailed body evaluation area. This will be explained in detail through FIG. 9.

[0057] FIG. 9 is a diagram relating to a method for calculating a second motion state evaluation score according to an embodiment of the present invention.

[0058] Referring to FIG. 9, in step S901, the controller (40) collects second video data of the user performing an exercise movement along the second exercise video, and can collect second evaluation movement information by sensing (extracting) joint positions and muscle movements corresponding to the detailed body evaluation area from the second video data.

[0059] In steps S903 and S905, the controller (40) can compare the second evaluation motion information with the second target motion information of the second exercise video to evaluate whether the second evaluation motion information is included within the range of the second target motion information, and calculate a second exercise state evaluation score corresponding to the detailed body evaluation area. The second exercise state evaluation score may include one or more pieces of information such as joint angle, muscle activity grade, movement speed and acceleration, and exercise maintenance time.

[0060] Returning to Fig. 7, in step S711, it is checked whether the evaluation of all of the plurality of body regions is completed. If, as a result of the check, the evaluation of the plurality of body regions is not completed (NO), steps S701 to S711 are repeated for at least one unevaluated body region.

[0061] On the other hand, if the evaluation for each of the plurality of body regions is completed (YES), the user's physical ability state score can be calculated based on the first exercise state evaluation score and the second exercise state evaluation score corresponding to the body region that is inactive or has weakened function among the plurality of body regions. The physical ability state score can be calculated by assigning a high weight to the Activities of Daily Living (ADL) items corresponding to the body region that is inactive or has weakened function among the plurality of body regions. This will be explained with reference to FIG. 10.

[0062] Figure 10 above is a drawing relating to a method for calculating a user's physical ability status score according to an embodiment of the present invention.

[0063] Referring to FIG. 10, in step S1001, the controller (40) calculates a final exercise state evaluation score based on a first exercise state evaluation score and a second exercise state evaluation score corresponding to the inactive and functionally weakened body area among the plurality of body areas.

[0064] In step S1003, the controller (40) can calculate the user's physical ability status score based on the final exercise status evaluation score. Specifically, the physical ability status score can be calculated by assigning a high weight to Activities of Daily Living (ADL) items corresponding to a body area that is inactive or has weakened function among a plurality of body areas. The ADL may include basic activities for living as a human being, such as sitting and standing, using the toilet, dressing, showering, and moving.

[0065] In addition, the controller (40) can map the item with the highest degree of closeness among the daily life activity items for each body area.

[0066] In step S715, the controller (40) may recommend an exercise program corresponding to the physical ability status score to the user. The controller (40) may determine the user's exercise level based on the physical ability status score and, accordingly, may recommend exercises to strengthen the body parts that are inactive or have weakened functions.

[0067] Although the present invention has been described by the embodiments and drawings described above, the present invention is not limited to the above embodiments, and various modifications and variations are possible from this description by those skilled in the art to which the present invention pertains. Accordingly, the concept of the present invention should be understood only by the claims set forth below, and all equivalent or analogous variations thereof shall be considered to fall within the scope of the concept of the present invention.

Claims

1. A first step of providing a first exercise video for a first body region among a plurality of body regions of a user, and extracting a first exercise state evaluation score for at least one first detailed body region included in the first body region based on the joint position and muscle movement of the first body region of the user; A second step of determining a first detailed body area from at least one of the first detailed body areas for which second exercise state evaluation information needs to be extracted based on the first exercise state evaluation score; A third step of recommending a second exercise video corresponding to the first detailed body area from which second exercise state assessment information must be extracted; A fourth step of providing the recommended second exercise video and calculating a second exercise state evaluation score based on the joint position and muscle movement of the user's first detailed body region. A user-customized exercise program recommendation method including 2. In Paragraph 1, After the above fourth step, A step of repeating steps 1 through 4 until the first exercise state evaluation score or the first exercise state evaluation score and the second exercise state evaluation score are calculated for each of the plurality of body regions, and then extracting the user's physical ability state score based on the first exercise state evaluation score and the second exercise state evaluation score corresponding to each of the plurality of body regions; and A step of recommending customized exercises corresponding to the physical ability status score to the user. A user-customized exercise program recommendation method that includes more.

3. In Paragraph 1, The first step of calculating the above-mentioned first exercise state evaluation score is, A step of collecting first image data by providing the first movement video and sensing the position of a joint and the movement of a muscle corresponding to at least one first detailed body region included in the first body region; A step of analyzing the first image data based on pre-set joint position and muscle movement information corresponding to the first movement video to extract at least one first evaluation motion information; and A step of comparing and analyzing at least one first evaluation motion information collected above with the first target motion information of the first exercise video to extract the first exercise state evaluation score corresponding to at least one first detailed body area included in the first body area. A user-customized exercise program recommendation method including 4. In the above Paragraph 3, The above first evaluation operation information is, A method for recommending a user-customized exercise program that includes at least one of joint movement angle, muscle activation grade, changes in movement speed and acceleration, and duration of exercise movement.

5. In Paragraph 1 of the above, The above second step is, A user-customized exercise program recommendation method that determines a specific body area requiring a second exercise state evaluation score by comparing a first exercise state evaluation score calculated for at least one specific body area with a preset first threshold value (TH1).

6. In the above paragraph 5, The result of comparing the first exercise state evaluation score calculated for each detailed body area above with the first threshold value (TH1) above is, A user-customized exercise program recommendation method that, if there is no first exercise state evaluation score less than the first threshold value (TH1) (N0), determines that there is no detailed body evaluation area for which a second exercise state evaluation score needs to be calculated, and calculates the first exercise state evaluation score for a body area among the plurality of body areas for which evaluation has not been completed.

7. In the above Paragraph 5, As a result of comparing the first exercise state evaluation score calculated for each detailed body area above with the first threshold value (TH1), A user-customized exercise program recommendation method that recommends a second exercise video for calculating a second exercise state evaluation score for the detailed body area—detailed body evaluation area—corresponding to the first exercise state evaluation score that is less than the first threshold value (TH1) among at least one first exercise state evaluation score.

8. In the above paragraph 1, The above first exercise video may include a multi-joint related exercise video, and The above second exercise video is a method for recommending a user-customized exercise program that includes a single-joint exercise video.

9. In the above paragraph 1, The above second exercise state evaluation score calculation step is, A step of collecting second video data of the user performing an exercise movement following the second exercise video; A step of collecting second evaluation motion information by sensing (extracting) joint positions and muscle movements corresponding to the detailed body evaluation area in the second image data; A step of comparing the second evaluation motion information and the second target motion information of the second exercise video to evaluate whether the second evaluation motion information is included within the range of the second target motion information, and calculating a second exercise state evaluation score corresponding to the detailed body evaluation area. A user-customized exercise program recommendation method including 10. In the above paragraph 2, The step of extracting the physical ability status score of the above user is, A step of calculating a final exercise state evaluation score based on a first exercise state evaluation score and a second exercise state evaluation score corresponding to a body region that is inactive and has weakened function among the plurality of body regions; and A step of calculating the physical ability status score by assigning high weights to the Activities of Daily Living (ADL) items corresponding to the inactive or functionally weakened body areas among the plurality of body areas and the final exercise status evaluation score. User-customized exercise program recommendation method including, 11. In the above paragraph 2, The step of recommending an exercise program corresponding to the physical ability status score to the user A user-customized exercise program recommendation method that, in order to restore a body area that is inactive or has weakened function among the plurality of body areas, identifies a recommended exercise item corresponding to the user's physical ability status score from a pre-set list of exercises and then recommends the recommended exercise item to the user.

12. A camera module for capturing a 3D image of the user in real time; and Includes at least one controller, The above at least one controller An exercise program recommendation system that senses the joint positions and muscle movements of the user from the captured 3D image to extract first image data, sequentially calculates a first exercise state evaluation score for each of the user's multiple body regions, calculates a second exercise state evaluation score for at least one detailed body region included in the corresponding body region when the first exercise state evaluation score is less than a first threshold value, extracts a physical ability state score based on the first exercise state evaluation score and the second exercise state evaluation score for the multiple body regions, and recommends a customized exercise suitable for the user's condition based on the physical ability state score.

13. In Paragraph 12, The above controller is, A user-customized exercise program recommendation system that repeatedly performs for each of the above plurality of body regions until the first exercise state evaluation score or the first exercise state evaluation score and the second exercise state evaluation score are calculated.

14. In Paragraph 12, The above first exercise state evaluation score is, The controller provides the first exercise video to the user, senses the position of a joint and the movement of a muscle corresponding to at least one first detailed body region included in the first body region, and collects first video data. Based on pre-set joint position and muscle movement information corresponding to the first movement video, the first video data is analyzed to extract at least one first evaluation movement information, and By comparing and analyzing at least one first evaluation motion information collected above and the first target motion information of the first exercise video, the first exercise state evaluation score corresponding to at least one first detailed body area included in the first body area is extracted. User-customized exercise program system.

15. In the above Paragraph 14, The above first evaluation operation information is, A user-customized exercise program recommendation system including at least one of joint movement angle, muscle activation grade, change in movement speed and acceleration, and duration of exercise movement.

16. In Paragraph 12 of the above, The above controller A user-customized exercise program recommendation system that determines a specific body area requiring a second exercise state evaluation score by comparing a first exercise state evaluation score calculated for at least one specific body area with a preset first threshold value (TH1).

17. In the above Paragraph 16, The above controller is, A user-customized exercise program recommendation system that, as a result of comparing the first exercise state evaluation score calculated for each detailed body area with the first threshold value (TH1), if there is no first exercise state evaluation score less than the first threshold value (TH1) (N0), determines that there is no detailed body evaluation area for which a second exercise state evaluation score needs to be calculated, and calculates the first exercise state evaluation score for a body area among the plurality of body areas for which evaluation has not been completed.

18. In the above Paragraph 16, The above controller is, A user-customized exercise program recommendation method that recommends a second exercise video for calculating a second exercise state evaluation score for the detailed body area—detailed body evaluation area—corresponding to the first exercise state evaluation score that is less than the first threshold (TH1), when, as a result of comparing the first exercise state evaluation score calculated for each detailed body area with the first threshold (TH1), there exists a first exercise state evaluation score among at least one first exercise state evaluation score that is less than the first threshold.

19. In Clause 12 above, The above first exercise video may include a multi-joint related exercise video, and The above second exercise video is a method for recommending a user-customized exercise program that includes a single-joint exercise video.

20. In Clause 12 above, The above second motion state evaluation score is, A user-customized exercise program recommendation system in which the controller collects second video data of the user performing an exercise movement following the second exercise video, senses (extracts) joint positions and muscle movements corresponding to the detailed body evaluation area from the second video data to collect second evaluation movement information, compares the second evaluation movement information with the second target movement information of the second exercise video to evaluate whether the second evaluation movement information is included within the range of the second target movement information, and calculates a second exercise state evaluation score corresponding to the detailed body evaluation area.

21. In the above Clause 12, The physical ability status score of the above user is, A user-customized exercise program recommendation system in which the controller calculates a final exercise state evaluation score based on a first exercise state evaluation score and a second exercise state evaluation score corresponding to a body area that is inactive or has weakened function among the plurality of body areas, and calculates a physical ability state score by assigning a high weight to the final exercise state evaluation score and to Activities of Daily Living (ADL) items corresponding to the body area that is inactive or has weakened function among the plurality of body areas.

22. In the above Clause 12, The above controller is, A user-customized exercise program recommendation system that, in order to restore a body area that is inactive or has weakened function among the plurality of body areas, identifies a recommended exercise item corresponding to the user's physical ability status score from a pre-set list of exercises and recommends the recommended exercise item to the user.

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