System and method for measuring rehabilitation muscle strength using image

Abstract

The present invention provides a system for measuring rehabilitation muscle strength using an image, the system enabling quantitative estimation of muscle strength of a subject by using a posture of the subject and an elastic band in an image photographed by a camera. The system comprises: a camera; a band detection unit for detecting an elastic band in an image photographed by the camera; a posture measurement unit for measuring a posture of the subject in the photographed image; and a muscle strength estimation unit for estimating a first muscle strength of the subject on the basis of an elastic force of the elastic band and a range of motion of an acting portion, the acting portion being a body portion acting on the elastic band in response to a posture change of the subject.

Description

System and method for measuring rehabilitation muscle strength using video

[0001] The present invention relates to a rehabilitation muscle strength measurement system and method that can quantitatively estimate the muscle strength of a subject using an image taken of the subject.

[0002] Rehabilitation treatment is a treatment that enables patients with impaired physical and mental functions after illness, injury, or surgery to lead as independent and active lives as possible. Among these, the recovery of physical functions is achieved by restoring the patient's muscle strength through various rehabilitation programs and exercises.

[0003] At this time, biomechanics, which analyzes the movement of the human body and the resulting force, plays an important role, and can enable effective rehabilitation treatment for patients by measuring the patient's muscle strength status or monitoring the progress of rehabilitation.

[0004] In the past, doctors qualitatively compared the patient's muscle strength status or monitored the progress of rehabilitation with the corresponding non-painful body part (e.g., arms, legs, etc.). However, the measurement results for the same subject varied among doctors, making it difficult to share or quantify the results.

[0005] To quantitatively measure muscle strength, a dynamometer can be used, as shown in Korean Patent Registration No. 10-1713239 or 10-1623575. However, because it must be connected to a power device such as a motor, the equipment becomes large and expensive, which reduces accessibility for general users. In other words, if a patient is performing rehabilitation exercises alone at home, it is impossible to measure muscle strength or monitor the progress of rehabilitation, so the accuracy of the posture cannot be confirmed, and if the exercise is repeated in an incorrect posture, effective rehabilitation treatment cannot be achieved.

[0006] Therefore, there is a need for necessary technologies to solve these problems.

[0007] The present invention provides a rehabilitation muscle strength measurement system and method that can quantitatively estimate the muscle strength of a subject by using the subject's posture and an elastic band in an image captured by a camera.

[0008] As a means for solving the above-mentioned technical problem, the present invention provides a rehabilitation muscle strength measurement system using an image, which includes a camera, a band detection unit for detecting an elastic band in an image captured using the camera, a posture measurement unit for measuring a posture of a subject in the image captured, and a muscle strength estimation unit for estimating a first muscle strength of the subject based on the elasticity of the elastic band and the range of motion of an action site, which is a body part that acts on the elastic band according to a change in the posture of the subject.

[0009] According to one embodiment, the posture measurement unit can measure the posture using characteristic points for each body part, including the joints of the subject.

[0010] According to one embodiment, the posture measurement unit can calculate accuracy by comparing the measured posture with a rehabilitation motion posture input by the user.

[0011] According to one embodiment, the muscle strength estimation unit can measure the first muscle strength of the subject based on the elastic coefficient of the elastic band, the amount of change in length of the elastic band, the angle formed by the action portion and the elastic band, and the length of the action portion.

[0012] According to one embodiment, the muscle strength estimation unit can measure the first muscle strength of the subject based on the elastic coefficient of the elastic band, the amount of change in length of the elastic band, the length of the action portion, and the angular velocity of the action portion based on the joint of the action portion that causes the change in length of the elastic band.

[0013] According to one embodiment, the muscle strength estimation unit estimates the first muscle strength using a measurement section image between a measurement start point and a measurement end point, wherein the measurement start point and the measurement end point can be set based on the shape of the elastic band detected using the band detection unit among the images captured by the camera.

[0014] According to one embodiment, the method may further include a recovery calculation unit that calculates a degree of recovery by comparing the second muscle strength estimated for a normal body part corresponding to the action part of the subject using the muscle strength estimation unit with the first muscle strength.

[0015] According to one embodiment, the type of elastic bands used in the first and second muscle strength estimation units may be the same or different.

[0016] According to one embodiment, the recovery calculation unit can use the muscle strength estimation unit to determine whether the subject's posture in each of the captured images is reversed left and right when estimating the first and second muscle strengths.

[0017] In addition, the present invention may include a step in which a band detection unit detects an elastic band in a captured image using a camera, a step in which a posture measurement unit measures a posture of a subject in the captured image, and a step in which a muscle strength estimation unit estimates a first muscle strength of the subject based on the elasticity of the elastic band and the range of motion of an action site, which is a body part that acts on the elastic band according to a change in the posture of the subject.

[0018] According to one embodiment, the recovery calculation unit may further include a step of calculating the degree of recovery by comparing the second muscle strength estimated for a normal body part corresponding to the action part of the subject using the muscle strength estimation unit with the first muscle strength.

[0019] The system and method for measuring rehabilitation muscle strength using video according to the present invention can quantitatively estimate the muscle strength of a subject using the subject's posture and elastic band in the video captured by the camera.

[0020] Additionally, the degree of recovery can be calculated by comparing it with the muscle strength measured for normal body parts.

[0021] Figure 1 is a schematic diagram of a rehabilitation muscle strength measurement system using an image according to one embodiment of the present invention.

[0022] Figure 2 is a configuration diagram of a rehabilitation muscle strength measurement system using an image according to one embodiment of the present invention.

[0023] Figure 3 is an example diagram showing the subject's posture and an elastic band in a filmed image according to one embodiment of the present invention.

[0024] Figure 4 is an example diagram showing the subject's application site tilting in the depth direction, which is the camera's line of sight, during the subject's rehabilitation exercise according to Figure 3.

[0025] FIG. 5 is a diagram illustrating a process for comparing and evaluating muscle strength estimates of a normal arm and an arm undergoing rehabilitation exercise according to one embodiment of the present invention.

[0026] FIG. 6 is a drawing for explaining a process in which a posture measurement unit according to one embodiment of the present invention measures a subject's posture.

[0027] Figure 7 is a step-by-step flow chart of a method for measuring rehabilitation muscle strength using an image according to one embodiment of the present invention.

[0028] Hereinafter, embodiments disclosed in this specification will be described in detail with reference to the attached drawings. Regardless of the drawing numbers, identical or similar components will be given the same reference numbers and redundant descriptions thereof will be omitted. The suffixes "unit" and "part" used for components in the following description are assigned or used interchangeably only for the convenience of writing the specification, and do not in themselves have distinct meanings or roles. In addition, when describing the embodiments disclosed in this specification, if it is determined that a specific description of a related known technology may obscure the gist of the embodiments disclosed in this specification, a detailed description thereof will be omitted. In addition, the attached drawings are only for easily understanding the embodiments disclosed in this specification, and the technical idea disclosed in this specification is not limited by the attached drawings, and it should be understood that they include all modifications, equivalents, and substitutes included in the spirit and technical scope of the present invention.

[0029] Terms including ordinal numbers, such as first, second, etc., may be used to describe various components, but the components are not limited by the terms.

[0030] The above terms are used solely to distinguish one component from another.

[0031] When a component is referred to as being "connected" or "connected" to another component, it should be understood that it may be directly connected or connected to that other component, but that there may be other components intervening. Conversely, when a component is referred to as being "directly connected" or "connected" to another component, it should be understood that there are no other components intervening.

[0032] Singular expressions include plural expressions unless the context clearly indicates otherwise.

[0033] In this specification, terms such as “include” or “have” are intended to specify the presence of a feature, number, step, operation, component, part or combination thereof described in the specification, but should be understood not to exclude in advance the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts or combinations thereof.

[0034]

[0035] Video-based rehabilitation muscle strength measurement system

[0036] FIG. 1 is a schematic diagram of a rehabilitation muscle strength measurement system using images according to one embodiment of the present invention, and FIG. 2 is a configuration diagram of a rehabilitation muscle strength measurement system using images according to one embodiment of the present invention.

[0037] As illustrated in FIG. 1, a rehabilitation muscle strength measurement system using images according to one embodiment of the present invention (hereinafter, abbreviated as “rehabilitation muscle strength measurement system”) (1) may include a camera (10), a processor (30) that performs an operation of estimating muscle strength of a subject (s) using images captured by the camera (10), and a memory (20) that stores various commands for performing operations related thereto. That is, the processor (30) serves as a means for controlling the overall operation of the rehabilitation muscle strength measurement system (1), and may perform an operation of estimating muscle strength of the subject (s) using images captured by the camera (10) by executing various commands stored in the memory (20).

[0038] Here, the camera (10) may be connected to the processor (30) and the memory (20) as independent devices so as to be communicatively connected to each other, but according to a preferred embodiment, the camera (10) may be implemented as an integral part of the processor (30) and the memory (20), so that the rehabilitation muscle strength measurement system (1) may be a single terminal, such as a mobile terminal, a smartphone, a laptop computer, a digital broadcasting terminal, a PDA (personal digital assistant), a PMP (portable multimedia player), a slate PC, a tablet PC, an ultrabook, etc.

[0039] The processor (30) may include, as illustrated in FIG. 2, a band detection unit (31) that detects elastic bands (b1, b2) in a captured image using a camera (10), classified according to function, a posture measurement unit (32) that measures the posture of the subject (s) in the captured image, and a muscle strength estimation unit (33) that estimates the first muscle strength of the subject (s) based on the elasticity of the elastic bands (b1, b2) and the range of motion of the action part, which is a body part that acts on the elastic bands (b1, b2) according to changes in the posture of the subject (s).

[0040] As described below, the processor (30) may further include a recovery calculation unit (34) that calculates the degree of recovery by comparing the second muscle strength estimated for the normal body part corresponding to the action part of the subject (s) using the muscle strength estimation unit (33) with the first muscle strength.

[0041] The captured image captured by the camera (10) may include a subject (s) and an elastic band (b1, b2) as identifiable objects. Here, the subject (s) may be a human object having a predetermined body structure, and the elastic band (b1, b2) is a band object made of a material such as rubber or silicone with elasticity of various strengths, which may be deformed or lengthened by an external force.

[0042] The camera (10) can capture images of the elastic bands (b1, b2) and the subject (s), specifically, the subject (s) holding the elastic bands (b1, b2). The images captured by the camera (10) can be temporarily still images or continuous images over time, but in a preferred embodiment, they are preferably continuous images.

[0043] The band detection unit (31) can detect elastic bands (b1, b2) using object recognition from the captured image of the camera (10). For example, the band detection unit (31) can recognize an object surrounding the subject (s) in the captured image of the camera (10) that is linear and at least part of which is stretchable along the length direction as an elastic band (b1).

[0044] At this time, the present invention is not particularly limited, but the band detection unit (31) can identify the type of elastic band (b1, b2) from a model learned based on image data on various types of elastic bands collected based on the color, shape (e.g., length, width, thickness, etc.), brand name, etc. of the elastic band (b1, b2) detected using object recognition.

[0045] The memory (20) can store the elastic coefficients of each type of elastic band (b1, b2), and the processor (30) (or the muscle force estimation unit (33)) can calculate the force (elastic force) applied to the elastic band (b1, b2) by using the elastic coefficients of the elastic band (b1, b2) and the change in length of the elastic band (b1, b2) due to an external force.

[0046] In contrast, the rehabilitation muscle strength measurement system (1) can, of course, receive input of the type of elastic band (b1, b2) and / or the elastic coefficient of the elastic band (b1, b2) according to user input through a user input means (not shown) such as a keyboard, mouse, or touch.

[0047] Here, the change in length of the elastic band (b1, b2) may be the difference between the first length of the elastic band (b1, b2) in the initial state in which it is straightened without bending, and the second length when it is stretched by a predetermined length greater than the first length in the straightened state, and the second length may be one of the average lengths of the elastic band (b1, b2) over a certain time period, a length measured in real time, a maximum length among the lengths measured within a predetermined arbitrary time period, a length when the accuracy is the highest, etc.

[0048] When the processor (30) calculates the length of the elastic band (b1, b2), the pixel distance of the elastic band (b1, b2) detected from the captured image captured by the camera (10), the focal length or sensor size of the camera (10), etc. may be used, but the present invention is not particularly limited thereto.

[0049] However, according to a preferred embodiment of the present invention, it is preferable that the processor (30) measure the change in length of the elastic bands (b1, b2) in the depth direction using augmented reality technology with respect to the captured image captured by the camera (10). For example, the processor (30) may recognize the elastic bands (b1, b2) as objects using ARKit or ArCore, track both ends of the elastic bands (b1, b2), and calculate the change in length of the elastic bands (b1, b2) having a depth component according to the viewing direction of the camera (10).

[0050] In this way, when the subject (s) is performing rehabilitation exercise in various postures with the elastic band (b1, b2), that is, even when performing rehabilitation exercise that pulls the elastic band (b1, b2) in the line of sight of the camera (10) or in the depth direction of the captured image, the processor (30) can calculate the exact change in length of the elastic band (b1, b2) with only one camera (10).

[0051] Meanwhile, the posture measurement unit (32) can measure the posture of the subject (s) in the image captured by the camera (10).

[0052] The posture measurement unit (32) can detect a subject (s) having a predetermined body structure using object recognition to measure the posture of the processor (30) in the captured image, and can measure the posture of the subject (s) using the characteristic points of the joints and / or the characteristic points of each body part of the detected subject (s).

[0053] FIG. 6 is a drawing for explaining a process in which a posture measurement unit according to one embodiment of the present invention measures a subject's posture. As shown in FIG. 6, the posture measurement unit (32) can measure the subject's (s) posture or posture change by setting the distal end (or the surrounding area thereof) and joints of each body part of the subject (s) as keypoints (p) and connecting these keypoints (p) for each body part to each other.

[0054] A rehabilitation muscle strength measurement system (1) according to one embodiment of the present invention can receive input of the type of rehabilitation exercise or posture of the subject (s) through the user input means (not shown), and the posture measurement unit (32) can compare the type of rehabilitation exercise or posture input by the user with the posture of the subject (s) according to the image captured by the camera (10) to calculate the accuracy thereof.

[0055] For example, as shown in Fig. 3(c), if the type of rehabilitation exercise or posture according to user input is a movement of straightening the right arm while standing upright and then lifting it straight up by 90°, the posture measurement unit (32) extracts characteristic points for each joint and body part of the subject (s) from the captured image, determines whether the extracted characteristic points follow the type of rehabilitation exercise or posture according to the user input, and calculates the accuracy according to the degree of following. Assuming that, as shown in Fig. 3(c), when the subject (s) in the above-described video is standing upright vertically and the angle at which the right arm is raised (for example, the angle θ1 formed by the side formed by the feature points PS3 and PS1 as the subject (s)'s upper body and the side formed by the feature points PS1 and PS2 as the right arm) reaches 90°, the accuracy can be judged to be 100%, and if it is 60°, which is less than this, the accuracy can be judged to be 80%, which is less than 100%.

[0056] The accuracy calculated by the posture measurement unit (32) in this way can be output so that it can be exposed to the subject (s) through a display means (not shown), and accordingly, the subject (s)'s re-activity can be induced to reach an accuracy of 100%.

[0057] Meanwhile, the muscle strength estimation unit (33) can estimate the first muscle strength of the subject (s) based on the elasticity of the elastic band (b1, b2) and the range of motion of the action part, which is the body part acting on the elastic band (b1, b2) according to the change in the posture of the subject (s).

[0058] At this time, the present invention is not particularly limited, but according to one embodiment of the present invention, it is preferable that the muscle strength estimation unit (33) estimate the first muscle strength only when the posture accuracy of the subject (s) measured by the posture measurement unit (32) is above a threshold value. In other words, the first muscle strength can be estimated only when the subject (s) is performing the rehabilitation exercise relatively accurately.

[0059] In addition, although the present invention is not particularly limited, according to one embodiment of the present invention, the muscle strength estimation unit (33) can estimate the first muscle strength of the subject (s) by determining the measurement start point and the measurement end point and using the measurement section image between the measurement start point and the measurement end point. According to one specific embodiment, the measurement start point and the measurement end point can be determined based on the shape of the elastic band (b1, b2) detected by the band detection unit (31) among the continuous images captured by the camera (10). For example, the muscle strength estimation unit (33) may set the first length of the elastic band (b1, b2) detected by the band detection unit (31) as the measurement start point when it is in the initial state of being straightened without bending, and may set the second length when the elastic band (b1, b2) is stretched by a predetermined length more than the first length in the straightened state as the measurement end point. Here, the second length may be one of the average lengths of the elastic band (b1, b2) per a certain time interval, or a length measured in real time, or a maximum length among the lengths measured within a predetermined arbitrary time period, or a length when the accuracy is the highest, etc.

[0060] Figure 3 is an example diagram showing the subject's posture and an elastic band in a filmed image according to one embodiment of the present invention.

[0061] As illustrated in FIG. 3, the posture of the subject (s) may change from FIG. 3(a) to 3(b) (for example, the subject (s)'s right arm may be raised forward in an extended state), and accordingly, the band detection unit (31) may detect an elastic band (b1) that is a yellow straight line that stretches or shrinks in the longitudinal direction as an object grasped by the subject (s) in the captured image by the camera (10). In this case, more preferably, the band detection unit (31) may detect the type of the elastic band (b1). Of course, as described above, the posture measurement unit (32) may calculate the accuracy of the subject (s)'s rehabilitation exercise posture.

[0062] Thereafter, the processor (30) (or the muscle strength estimation unit (33)) can calculate the elastic force based on the elastic coefficient and the change in length (= second length - first length) according to the type of the detected elastic band (b1).

[0063] Simultaneously with the band detection unit (31), the posture measurement unit (32) can detect the subject (s) in the captured image by the camera (10), and extract the characteristic points of the subject (s) to measure the posture or posture change of the processor (30). As described above, the posture measurement unit (32) can detect one side of the subject (s) in a state of standing as shown in FIG. 3(a), and then, as shown in FIG. 3(b), by detecting one side of the subject (s) in a state of raising the right arm forward, it can be determined that the posture change is occurring as a reactive action of the subject (s) raising the right arm forward. In addition, it goes without saying that the posture accuracy can be calculated according to one embodiment of the present invention.

[0064] In this way, the muscle strength estimation unit (33) can detect that the elastic band (b1) increases in length in a predetermined direction as the right arm, which is a body part of the subject (s), rotates forward by a predetermined angle centered on the shoulder, and the body part that acts to apply force to the elastic band (b1) is the right arm, where the posture of the subject (s) changes, and the first muscle strength of the subject (s) can be estimated based on the angle (for example, 90°) at which the right arm is raised forward, which is the range of motion, and the elastic force of the elastic band (b1) that has been calculated.

[0065] Specifically, the muscle strength estimation unit (33) can estimate the first muscle strength around the joint (PS1) around which the subject's (s) action portion rotates according to the rehabilitation exercise by using the learned model, based on the elastic force of the elastic band (b1) calculated based on the elastic coefficient and length change amount of the elastic band (b1) as described above, the length of the action portion of the subject (s) that applies force to the elastic band (b1) (for example, the length of the subject's (s') right arm in FIG. 3(c)), and the angle (θ2 in FIG. 3(c)) formed between the action portion of the subject (s) and the elastic band (b1).

[0066] In contrast, as another method, the muscle strength estimation unit (33) may estimate the first muscle strength around the joint (PS1) around which the action portion rotates according to the rehabilitation exercise of the subject (s) using a learned model based on the elasticity of the elastic band (b1), the length of the action portion of the subject (s) applying force to the elastic band (b1) (for example, the length of the right arm of the subject (s) in FIG. 3(c)), and the angular velocity of the action portion.

[0067] The unexplained drawing symbols Pb1 and Pb2 may be points indicating the ends of the elastic bands (b1, b2) detected by the band detection unit (31) in the image captured by the camera (10).

[0068] In addition, when the posture of the subject (s) changes from FIG. 3(a) to 3(b), the direction of movement of the working part of the subject (s) with respect to the elastic band (b1) (for example, when the right arm of the subject (s) is raised, the distal end of the arm may face inward, and in this case, the arm length measured on a plane in the photographed image may become shorter) may include a component in the depth direction along the line of sight of the camera (10) (see FIG. 4), so the processor (30) can measure the direction of movement of the working part in the depth direction using augmented reality technology with respect to the photographed image captured by the camera (10).

[0069] That is, the processor (30) can recognize the working part of the subject (s) and track both ends of the working part to calculate the degree to which the direction of movement of the working part moving according to the rehabilitation exercise is tilted in the depth direction, that is, the angle θ3 between A1 and A2 in FIG. 4, and accordingly, the muscle strength estimation unit (33) can estimate the first muscle strength around the joint (PS1) around which the working part of the subject (s) rotates by using a pre-learned model based on the degree to which the working part of the subject (s) is tilted in the depth direction, the elasticity of the elastic band (b1), the length of the working part of the subject (s), and the angle formed by the working part of the subject (s) and the elastic band (b1).

[0070] Of course, the muscle strength estimation unit (33) can estimate the first muscle strength around the joint (PS1) around which the subject's (s) action part rotates by using a model learned based on the degree (θ3) to which the subject's (s) action part is tilted in the depth direction, the elasticity of the elastic band (b1), the length of the subject's (s) action part, and the angular velocity of the action part.

[0071] Meanwhile, a rehabilitation muscle strength measurement system (1) according to one embodiment of the present invention may include a recovery degree calculation unit (34) that estimates a first muscle strength estimated using a muscle strength estimation unit (33) and a second muscle strength to be compared, as illustrated in FIG. 2, and calculates a degree of recovery by comparing the first muscle strength and the second muscle strength.

[0072] Here, the second muscle strength corresponds to the first muscle strength calculated by the muscle strength estimation unit (33), and may be an estimated value for another action site, which is a normal body part corresponding to the action site estimated during the rehabilitation exercise of the subject (s). For example, if the first muscle strength estimated by the muscle strength estimation unit (33) is for the right shoulder for rotating the right arm of the subject (s), the second muscle strength may be for the left shoulder for rotating the normal left arm of the subject (s).

[0073] Accordingly, the recovery calculation unit (34) can quantitatively calculate the degree of recovery by comparing the first and second muscle strengths and comparing the value of the first muscle strength with the value of the second muscle strength for a normal body part, and the calculated degree of recovery can be output through a display means or the like.

[0074] The recovery calculation unit (34) can compare the first and second muscle strengths estimated by the muscle strength estimation unit (33), but at this time, when the muscle strength estimation unit (33) estimates the first and second muscle strengths, the elastic bands (b1) may be the same, but may also be different. This is because the muscle strength estimation unit (33) according to one embodiment of the present invention can detect the elastic band (b1) when estimating the muscle strength, as well as identify the type of the elastic band (b1), so even if different elastic bands (b1) are used, the elastic force according to them can be calculated and the muscle strength for the subject (s) can be estimated.

[0075] In general, since the human body is bilaterally symmetrical, when the recovery degree calculation unit (34) according to one embodiment of the present invention estimates the first and second muscle strengths estimated by the muscle strength estimation unit (33) in order to calculate the degree of recovery, the processor (30) (or the recovery degree calculation unit (34)) can check whether the posture of the subject (s) in the captured image captured by the camera (10) is left-right inverted. Of course, at this time, the elastic bands (b1, b2) that stretch in the captured image captured by the camera (10) may also have left-right inverted shapes.

[0076] FIG. 5 is a diagram for explaining a process of comparing and evaluating the muscle strength estimates of a normal arm and an arm undergoing rehabilitation exercise according to one embodiment of the present invention, and as shown in FIGS. 5(a) and 5(b), the processor (30) (or the recovery calculation unit (34)) determines whether the posture of the subject (s) is reversed left and right in the image captured by the camera (10) when the first and second muscle strengths are estimated by the muscle strength estimation unit (33), and / or whether the elastic bands (b1, b2) are reversed left and right, thereby allowing the recovery calculation unit (34) to determine whether the calculation result is reliable when calculating the recovery degree.

[0077] If, when estimating the first and second muscle strengths, the subject's (s) posture is reversed left and right in the image captured by the camera (10), the processor (30) (or the recovery calculation unit (34)) can determine that the reliability is high, and conversely, if the subject's (s) posture is not reversed left and right in the image captured, the processor (30) (or the recovery calculation unit (34)) can determine that the reliability is low rather than high.

[0078]

[0079] Method for measuring rehabilitation muscle strength using video

[0080] Figure 7 is a step-by-step flow chart of a method for measuring rehabilitation muscle strength using an image according to one embodiment of the present invention.

[0081] As illustrated in FIG. 7, a method for measuring rehabilitation muscle strength according to an embodiment of the present invention may include a step (S10) in which a band detection unit (31) detects elastic bands (b1, b2) in a captured image using a camera, a step (S20) in which a posture measurement unit (32) measures the posture of a subject (s) in the captured image, and a step (S30) in which a muscle strength estimation unit (33) estimates first muscle strength of elastic bands (b1, b2) based on the elasticity of the elastic bands (b1, b2) and the range of motion of an action site, which is a body site acting on the elastic bands (b1, b2) according to a change in the posture of the subject (s).

[0082] At this time, the recovery calculation unit (34) may further include a step (S50) of calculating the degree of recovery by comparing the second muscle strength estimated for the normal body part corresponding to the action part of the subject (s) using the muscle strength estimation unit (33) with the first muscle strength.

[0083] Since the description of each step included in the method for measuring rehabilitation muscle strength using an image according to one embodiment of the present invention overlaps with the description described above, the description thereof will be omitted and replaced with that.

[0084]

[0085] computer-readable recording medium

[0086] The method for measuring rehabilitation muscle strength using an image according to one embodiment of the present invention described above can be implemented in the form of program commands that can be executed through various computer components and recorded on a computer-readable recording medium.

[0087] The computer-readable recording medium may include program commands, data files, data structures, etc., either singly or in combination. The program commands recorded on the computer-readable recording medium may be those specially designed and configured for the present invention, or may be those known and available to those skilled in the art of computer software. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and hardware devices specially configured to store and execute program commands, such as ROMs, RAMs, and flash memories. Examples of the program commands include not only machine language codes generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter, etc. The hardware devices may be configured to operate as one or more software modules to perform processing according to the present invention, and vice versa.

[0088] Preferred embodiments of the present invention have been described in detail above with reference to the drawings. The description of the present invention is provided for illustrative purposes only, and those skilled in the art will readily appreciate that modifications to other specific forms are possible without altering the technical spirit or essential characteristics of the present invention.

[0089] Accordingly, the scope of the present invention is indicated by the claims described below rather than the detailed description above, and all changes or modifications derived from the meaning, scope and equivalent concepts of the claims should be interpreted as being included in the scope of the present invention.

Claims

1. Camera; A band detection unit that detects an elastic band in a video captured using the above camera; A posture measurement unit that measures the posture of the subject in the above-mentioned video; and A muscle strength estimation unit that estimates the first muscle strength of the subject based on the elasticity of the elastic band and the range of motion of the body part that acts on the elastic band according to changes in the subject's posture; A rehabilitation muscle strength measurement system using video including .

2. In paragraph 1, The above posture measurement unit is a rehabilitation muscle strength measurement system using an image, characterized in that it measures posture using characteristic points for each body part including the joints of the subject.

3. In paragraph 2, A rehabilitation muscle strength measurement system using an image, characterized in that the posture measurement unit calculates accuracy by comparing the measured posture with a rehabilitation movement posture input by the user.

4. In paragraph 1, A rehabilitation muscle strength measurement system using video, characterized in that the muscle strength estimation unit measures the first muscle strength of the subject based on the elastic coefficient of the elastic band, the change in length of the elastic band, the angle formed by the action portion and the elastic band, and the length of the action portion.

5. In paragraph 1, A rehabilitation muscle strength measurement system using an image, characterized in that the muscle strength estimation unit measures the first muscle strength of the subject based on the elastic coefficient of the elastic band, the amount of change in length of the elastic band, the length of the working part, and the angular velocity of the working part based on the joint of the working part that causes the change in length of the elastic band.

6. In paragraph 1, The above muscle strength estimation unit estimates the first muscle strength using the measurement section image between the measurement start point and the measurement end point. A rehabilitation muscle strength measurement system using an image, characterized in that the measurement time point and the measurement end point are set based on the shape of the elastic band detected using the band detection unit among the images captured by the camera.

7. In paragraph 1, A recovery calculation unit that calculates the degree of recovery by comparing the second muscle strength estimated for the normal body part corresponding to the action part of the subject using the muscle strength estimation unit with the first muscle strength; A rehabilitation muscle strength measurement system using video, characterized in that it further includes.

8. In paragraph 7, The above muscle strength estimation unit is a rehabilitation muscle strength measurement system using an image, characterized in that the types of the elastic bands are the same or different when estimating the first and second muscle strengths.

9. In paragraph 7, A rehabilitation muscle strength measurement system using video, characterized in that the above recovery calculation unit uses the muscle strength estimation unit to check whether the subject's posture in each of the above-described images is reversed left and right when estimating the first and second muscle strengths.

10. The band detection unit is a step of detecting an elastic band in a captured image using a camera; The posture measurement unit comprises a step of measuring the posture of the subject in the above-described video; and The muscle strength estimation unit is a step of estimating the first muscle strength of the subject based on the elasticity of the elastic band and the range of motion of the action part, which is a body part that acts on the elastic band according to a change in the subject's posture; A method for measuring rehabilitation muscle strength using an image including:

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