CN113303764A - System for detecting muscle health state of object of interest - Google Patents
System for detecting muscle health state of object of interest Download PDFInfo
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Abstract
The present application relates to a system for detecting the health status of a muscle to be measured of a subject of interest. The detection system comprises a motion indication module, a motion sensor, a data processing module and a judgment module. The action indication module indicates that the object of interest performs a predetermined action. Motion sensors placed at different locations on the object of interest obtain a plurality of sensor parameters when the object of interest performs a predetermined action. The data processing module obtains a first motion characteristic parameter for identifying a first sub-motion of the object of interest based on at least one first sensor parameter of the plurality of sensor parameters and obtains a second motion characteristic parameter for identifying a second sub-motion of the object of interest based on at least one second sensor parameter of the plurality of sensor parameters. The judging module determines the occurrence sequence of the first sub-actions and the second sub-actions according to the first action characteristic parameters and the second action parameters, and determines the health state of the muscle to be detected according to the determined sequence.
Description
Technical Field
The present invention relates to the technical field of detecting muscular problems of an object to be measured by means of a sensor worn by the object to be measured.
Background
Muscles are composed of muscle tissue, which is distributed throughout the body of a human and has a variety of important functions on the human body. The skeleton muscle wraps the skeleton, and when a human body is hit or collided by an external force, the strong muscle can effectively buffer the impact caused by the external force, so that the skeleton is protected from being damaged. In addition, skeletal muscles also support the body and help a person maintain various postures. Skeletal muscle is attached to the skeleton, and all the movements of the human body are performed by skeletal muscle contraction, and no movement occurs without skeletal muscle.
When problems occur with the muscles of the human body, problems may also occur with the movement of the human body. By enabling a person to wear the motion sensor, the information collected by the sensor can be used for obtaining the motion related information of the person to judge whether the motion of the person is abnormal or not, so that the health state of the muscle of the human body is judged, and the subsequent rehabilitation therapy aiming at the muscle is considered. Generally, in muscle health detection, whether the motor function is healthy or not is judged according to whether a detected user can complete an action or the degree of completing an action, so that whether relevant muscles are healthy or not is judged.
Disclosure of Invention
According to an embodiment of the invention, a system for detecting a health state of a muscle to be measured of a subject of interest is provided. The detection system comprises a motion indication module, a plurality of motion sensors, a data processing module and a judgment module. The action indication module indicates that the object of interest performs a predetermined action. A plurality of motion sensors to be placed at a plurality of locations on the object of interest, respectively, obtain a plurality of sensor parameters when the object of interest performs a predetermined action. The data processing module obtains a first motion characteristic parameter for identifying a first sub-motion performed by the object of interest for completing the predetermined motion according to at least one first sensor parameter of the plurality of sensor parameters, and obtains a second motion characteristic parameter for identifying a second sub-motion performed by the object of interest for completing the predetermined motion according to at least one second sensor parameter of the plurality of sensor parameters. The judging module determines first time of occurrence of the first sub-action according to the first action characteristic parameter, determines second time of occurrence of the second sub-action according to the second action characteristic parameter, compares the first time and the second time to determine the sequence of occurrence of the first sub-action and the second sub-action, and finally determines the health state of the muscle to be tested according to the determined sequence.
The inventors of the present invention have found that in some cases, it is not necessarily possible to detect all problematic muscles by merely detecting whether the user under test can perform a predetermined action for the test, but more details of the process of performing the predetermined action by the user under test are required to be detected and analyzed. The tested user unconsciously completes the preset action through a plurality of sub-actions of a plurality of parts of the body in the process of completing a specific preset action indicated by the detection system, and for certain preset actions and people with different muscle health states, the occurrence sequence of the sub-actions is different. When the object of interest completes the predetermined action indicated by the detection system, the detection system determines the occurrence sequence of the sub-actions by monitoring the action characteristic parameters of different sub-actions unconsciously performed by the object of interest when consciously performing the predetermined action, and then judges the health state of the muscle to be detected according to the occurrence sequence of the sub-actions. By the method, even if the tested user completes the preset action within the set time or adjusts the mode of completing the preset action by himself/herself consciously, the tested user does not know and can not control the involuntary sub-action of himself/herself, the detection system can still detect the health problem of the muscle to be detected, the missing of detection is avoided, and therefore the accuracy of the detection result is improved.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a schematic structural diagram of a system for detecting a health state of a muscle of an object of interest according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Fig. 1 is a schematic structural diagram of a system for detecting a health state of a muscle of an object of interest according to an embodiment of the present invention.
As shown in fig. 1, according to an embodiment of the invention, a system for detecting a health state of a muscle to be measured of a subject of interest is provided. A system for detecting the health status of a muscle to be measured of a subject of interest comprises an action indication module, a plurality of motion sensors, a data processing module and a decision module.
The object of interest is a tested user needing to detect whether the muscle has a problem, and the tested user can be an adult or a child. The muscle to be tested is any one or any combination of a certain muscle, a muscle at a certain position, a muscle at a certain body part or a certain muscle group on the tested user, such as the muscle on the back side of the thigh, the hip muscle, the muscle on the front side of the calf, the muscle on the inner side of the forearm and the like
The action indication module indicates that the object of interest performs at least one predetermined action. The predetermined movement is an action that the user under test can complete or can attempt to complete, such as squat with one leg, stepping forward or lifting an arm, etc. The motion indication module may select a predetermined motion from a pre-stored or established database of predetermined motions based on the muscle to be measured. For example, the muscle to be tested is a hip muscle, and the action indicating module selects a predetermined action corresponding to the hip muscle test from the predetermined action database. For another example, the detection system needs to detect the muscles of the whole body of the detected user, and the motion indication module sequentially selects different predetermined motions corresponding to different muscles from the predetermined motion database according to the detection sequence of the muscles of the whole body. In addition, the selection of the predetermined action can also take the health state known by the tested user into consideration, and the predetermined action with appropriate difficulty is selected from the predetermined action database.
The action indication module may be implemented in a variety of ways. For example, the action indicating module may be a display screen indicating the object of interest to perform the predetermined action by displaying a textual description, a picture or a video of the predetermined action. For another example, the action indication module may be a voice player, and the voice player indicates the object of interest to complete the predetermined action by means of voice prompt.
A plurality of motion sensors to be placed at different locations on the object of interest, respectively, and to obtain a plurality of sensor parameters when the object of interest performs a predetermined action. A motion sensor is a sensor that can measure motion related sensor parameters, such as an inertial sensor, a gyroscope or an accelerometer, etc. The sensor parameters include any one or any combination of velocity, angle, angular velocity, acceleration, angular acceleration, and the like.
In operation of the detection system, the subject of interest may wear the plurality of motion sensors at different locations or positions on the body, such as any combination of the legs, feet, waist, head, arms, etc. The motion sensor may be positioned at a location on the subject of interest in a variety of ways, such as by using a strap to secure the motion sensor to the lower leg of the subject of interest, and by using the subject of interest to hold the motion sensor by hand.
The data processing module obtains a first motion characteristic parameter for identifying a first sub-motion performed by the object of interest for completing the predetermined motion based on at least one first sensor parameter of the plurality of sensor parameters, and obtains a second motion characteristic parameter for identifying a second sub-motion performed by the object of interest for completing the predetermined motion based on at least one second sensor parameter of the plurality of sensor parameters.
The data processing module can be realized by a processor or an FPGA board and the like. The first sub-action and the second sub-action are two different sub-actions. The user under test may have several unintended sub-actions in order to consciously perform the predetermined action. For example, the user to be tested may intentionally lift his or her leg forward, but may unintentionally control sub-movements including knee bending or foot hooking of different parts of one leg during the process of lifting his or her leg. For another example, the user may intentionally jump upward, but may unintentionally control sub-movements including bending arms or bending down of various parts of the arms and various parts of the legs.
The motion characteristic parameter is a parameter that can represent a sub-motion performed unconsciously or subconsciously by the subject of interest in the process of consciously completing a predetermined motion, that is, a motion characteristic parameter of a certain body part of the subject of interest where the sub-motion occurs or is completed, such as a frequency of shaking of the certain body part of the subject of interest, a flexion and extension angle of the certain body part of the subject of interest, a motion acceleration of the certain body part of the subject of interest, an included angle between two adjacent body parts of the subject of interest, and the like.
The at least first sensor parameter may be any one or any combination of velocity, angle, angular velocity, acceleration, angular acceleration, and the like. The at least second sensor parameter may be any one or any combination of velocity, angle, angular velocity, acceleration, angular acceleration, and the like.
During the process of completing the predetermined action of the object of interest, the sensor parameters obtained by the motion sensor are a plurality of values within a measurement period, and the corresponding action characteristic parameters obtained according to the sensor parameters are a plurality of values within the same measurement period. The start time of the measurement time may be determined in a number of ways, such as by having the motion indication module indicate a time at which the object of interest has completed a predetermined motion as the start time, and such as by inputting the start time by an operator of the detection system. The end time of the measurement time may be determined in a number of ways, such as detecting the time to complete the predetermined action as the end time, such as entering the end time by an operator of the detection system, or such as indicating the time to complete the next predetermined action by the action indicating module as the end time.
Before the data processing module obtains the motion characteristic parameters for identifying the sub-motions according to the sensor parameters of the motion sensor or before the detection system works, the data processing module can calibrate the motion sensor in a manual or automatic mode, namely, the sensor parameters are calibrated to a coordinate system used by the data processing module for evaluating the motion state of the measured object. Calibration may be achieved in a number of ways. For example, the vertical, lateral horizontal and horizontal forward directions of the measured object can be calibrated by standing the measured object in a specified direction. As another example, calibration may be based on the obtained sensor parameters and the predetermined action. The basic calibration method using a motion sensor is well known to those skilled in the art and will not be described in detail herein.
The judging module determines first time of the first sub-action according to the first action characteristic parameter, determines second time of the second sub-action according to the second action characteristic parameter, compares the first time and the second time to determine the sequence of the first sub-action and the second sub-action, and finally determines the health state of the muscle to be tested according to the determined sequence.
The judging module can be realized by a processor or an FPGA board and the like. The judging module determines first time of occurrence of the first sub-action according to the first action characteristic parameter changing along with time, and determines second time of occurrence of the second sub-action according to the second sub-action parameter changing along with time.
The decision module may determine the time at which the sub-action occurs from the action characteristic parameter in a number of ways. In one embodiment, the action characteristic parameter may be compared with a predetermined sub-action threshold value, and the time when the value of the action characteristic parameter reaches the sub-action threshold value is the time when the sub-action occurs. In yet another embodiment, the time at which the maximum value of the motion characteristic parameter curve formed by the time-varying motion characteristic parameters occurs is the time at which the sub-motion occurs. In yet another embodiment, the time when the first peak appears in the motion characteristic parameter curve formed by the motion characteristic parameters changing with time is the time when the sub-motion occurs.
Muscle health status may be 0 or 1, with or without, healthy or unhealthy to indicate whether the muscle being tested is at a health problem or risk. According to the sequence of the first sub-action and the second sub-action, the muscle health state can be determined. For example, when the first sub-action occurs before the second sub-action, the determining module determines that the muscle to be tested does not have a muscle health problem; otherwise, namely when the first sub-action occurs after or simultaneously with the second sub-action, the judgment module determines that the muscle to be tested has the muscle health problem.
By monitoring the sequence of different sub-actions unconsciously performed by the tested user when the tested user consciously completes the test action, the muscle health problem of certain interested objects when certain preset actions are completed can be found, so that the problem of missing detection of muscle health detection caused by simply detecting whether the tested user completes the test action or the degree (such as speed, depth or distance) of completing the test action is avoided.
When the muscle to be tested is determined to have the health problem according to the determined sequence of the first sub-action and the second sub-action, the judging module is further used for determining the health risk degree of the muscle to be tested according to the length of the time difference between the first time and the second time.
The muscle health risk level may be 1 to 4 stars or mild, moderate, poor, severe to dangerous to indicate the degree or grade of muscle health risk. Also for example, the muscle health risk level may represent the degree or grade of the presence of a muscle health risk in terms of a percentage.
Determining the health risk level based on the length of the time difference between the first time and the second time may be accomplished in a variety of ways. In one embodiment, the length of the time difference is compared to one or more predetermined time difference thresholds, and a muscle health risk is determined based on whether the length of the time difference reaches the time difference threshold. In yet another embodiment, the degree or level of muscle health risk is determined based on a proportional relationship between the length of the time difference and a time difference threshold value. The time difference threshold may be generated from a database of time differences generated from a large sampling of the population.
When the sequence of the first sub-action and the second sub-action shows that the muscle to be detected has a health problem, the degree of the muscle to be detected having the health problem, namely the muscle health risk degree, can be further determined by analyzing the time difference of the two sub-actions, so that the subsequent more targeted rehabilitation treatment can be performed, and the over-treatment or the under-treatment can be avoided.
In an example of determining the occurrence time of the sub-motion, the determination module further detects a time of occurrence of a maximum value of the first motion characteristic parameter during the completion of the predetermined motion of the object of interest as a first time, and detects a time of occurrence of a maximum value of the second motion characteristic parameter during the completion of the predetermined motion of the object of interest as a second time.
In one example, the first motion characteristic parameter comprises a first angular velocity of flexion and extension of a first body part of the subject of interest, and the second motion characteristic parameter comprises a second angular velocity of flexion and extension of a second body part of the subject of interest. The first body part and the second body part are two different body parts of the object of interest. For example, the first body part is a thigh and the second body part is a calf. For another example, the first body part is a large arm and the second body part is a small arm. For another example, the first body part is a lower leg and the second body part is a foot. .
According to one embodiment of the present invention, the health status of the rear thigh muscle and the calf muscle can be detected.
The motion indication module indicates that the object of interest completes a preset action of 'deep squatting', and the deep squatting requires the tested user to squat to a limit state which can not be lowered any more.
The detection system includes a plurality of motion sensors for wearing on a thigh of a first body part and a calf of a second body part, respectively, of a user under test. After the user to be tested begins to squat deeply, the plurality of motion sensors measure a plurality of sensor parameters, wherein a first sensor parameter included in the plurality of sensor parameters is a thigh angular velocity value of the motion sensor worn on a thigh, which changes along with time, and a second sensor parameter included in the plurality of sensor parameters is a shank angular velocity value of the motion sensor worn on a shank, which changes along with time.
The data processing module obtains a first motion characteristic parameter of thigh flexion and extension of a first sub-action of the interested object for completing deep squatting according to the thigh angular velocity value of the first sensor parameter, namely the thigh flexion and extension angular velocity, namely the angular velocity of the thigh in the direction of the included angle between the front facing direction of the detected user and the horizontal ground. The data processing module obtains a second motion characteristic parameter of shank flexion and extension of a second sub-action of the interested object for completing deep squatting according to the shank angular velocity value of the second sensor parameter, which is the shank flexion and extension angular velocity, namely the angular velocity of the shank in the direction of the included angle between the front orientation direction of the detected user and the horizontal ground.
The judging module determines that the time when the thigh bending and stretching angular speed reaches the maximum value is the first time when the thigh bending and stretching occurs in the first sub-action according to the first motion characteristic parameter, and determines that the time when the shank bending and stretching angular speed reaches the maximum value is the second time when the shank bending and stretching occurs in the second sub-action according to the second motion characteristic parameter. Determining that the health status of the posterior thigh muscle and the calf muscle is healthy when the first time is before the second time; on the contrary, the health state of the muscles of the back side of the thigh and the muscles of the lower leg is determined to be a health problem.
When the first time is after the second time, namely the health state of the muscles on the back side of the thigh and the muscles on the lower leg is determined to be a health problem, the judging module compares the length of the time difference between the second time and the first time with a first flexion-extension time difference threshold value and a second flexion-extension time difference threshold value: if the length of the time difference is smaller than a first flexion-extension time difference threshold value, determining that the health risk degree of muscles on the back side of the thigh and the muscles of the shank is slight; if the length of the time difference is larger than the first flexion-extension time difference threshold value but smaller than the second flexion-extension time difference threshold value, determining that the health risk degree of muscles on the back side of the thigh and muscles of the shank is medium; and if the length of the time difference is larger than a second flexion-extension time difference threshold value, determining that the health risk of the muscles on the back side of the thigh and the muscles on the lower leg is serious.
In yet another embodiment of determining the occurrence time of the sub-action, the decision module further detects a time at which the first action characteristic parameter reaches a first threshold value as the first time and detects a time at which the second action characteristic parameter reaches a second threshold value as the second time.
In an embodiment the first motion characteristic parameter comprises a first angle of adjacent third and fourth body parts of the object of interest and the second motion characteristic parameter comprises a second angle of adjacent fourth and fifth body parts of the object of interest. The third body part and the fifth body part are two different body parts of the object of interest. For example, the first angle is the angle between the waist and the thigh, and the second angle is the angle between the thigh and the shank. For another example, the first angle is the angle between the shoulder and the large arm, and the second angle is the angle between the large arm and the small arm. The included angle of the adjacent parts can reflect the motion state of more body parts by only using one motion characteristic parameter, thereby being capable of determining the muscle health state of the adjacent parts and the middle joints of the adjacent parts.
According to one embodiment of the present invention, the health status of the posterior thigh muscles and the hip muscles can be detected.
The motion indication module indicates the interested object to complete the preset action of squatting, and the detected user only needs to move down the whole gravity center without squatting to the lowest state.
The detection system comprises a plurality of motion sensors which are respectively worn on the waist, the thigh and the calf of the third body part of the detected user. After the user to be tested begins to squat, the plurality of motion sensors measure a plurality of sensor parameters, the first sensor parameters included in the plurality of sensor parameters are a waist angle value of the motion sensor worn on the waist and a thigh angle value of the motion sensor worn on the thigh, the waist angle value of the motion sensor worn on the thigh and the thigh angle value of the motion sensor worn on the shank, the first sensor parameters are a thigh angle value of the motion sensor worn on the thigh and a shank angle value of the motion sensor worn on the shank, the shank angle value of the motion sensor changes along with time, and the second sensor parameters included in the plurality of sensor parameters are a shank angle value of the motion sensor worn on the thigh and the shank angle value of the motion sensor worn on the shank and the shank angle value of the motion sensor changes along with time.
The data processing module obtains a first motion characteristic parameter of the first sub-action of the interested object for bending the crotch to finish squatting according to the waist angle value and the thigh angle value of the first sensor parameter, wherein the first motion characteristic parameter is a waist and thigh included angle, namely the waist and thigh included angle in the front forward direction of the interested object. The data processing module obtains a second motion characteristic parameter of the knee bending of the second sub-action of the interested object for completing the squat according to the thigh angle value and the shank angle value of the second sensor parameter, wherein the second motion characteristic parameter is the included angle between the thigh and the shank, namely the included angle between the thigh and the shank in the front forward direction of the interested object.
The judgment module determines that the time when the included angle between the waist and the thigh reaches a first threshold value, namely the hip bending angle threshold value, is the first time when the first sub-action bends the hip according to the first motion characteristic parameter, and determines that the time when the included angle between the thigh and the shank reaches a second threshold value, namely the knee bending angle threshold value, is the second time when the second sub-action bends the knee according to the second motion characteristic parameter. Determining that the health status of the rear thigh muscles and the hip muscles is healthy when the first time is before the second time; on the contrary, the health state of the muscles of the back side of the thigh and the hip is determined as a health problem.
When the first time is after the second time, namely the health states of the muscles at the back side of the thighs and the buttocks are determined to be healthy, the judging module compares the length of the time difference between the second time and the first time with the hip-bending time difference threshold value: if the length of the time difference is smaller than the threshold value of the time difference of bending the hip and the knee, the health risk degree of the muscles at the back side of the thigh and the hip muscles is determined to be slight; if the length of the time difference is more than one time of the time difference threshold value of bending the hip and the knee and less than two times of the time difference threshold value of bending the hip and the knee, the health risk degree of muscles at the back side of the thigh and the muscles of the calf is determined to be medium; and if the length of the time difference is greater than two times of the threshold value of the time difference for bending the hip and the knee, determining that the health risk of the muscles at the back side of the thigh and the muscles of the lower leg is serious.
In yet another embodiment of determining the occurrence time of the sub-action, the decision module detects a time at which the first action characteristic parameter reaches the third threshold value as the first time, and detects a time at which the second action characteristic parameter occurs a maximum value as the second time.
In an embodiment, the first motion characteristic parameter comprises a number of peaks of the first acceleration of the sixth body part of the subject of interest within the time length T, and the second motion characteristic parameter comprises a second acceleration of the seventh body part of the subject of interest. The sixth body part and the seventh body part are two different body parts of the object of interest. For example, the sixth body part is the left leg and the seventh body part is the right leg. For another example, the sixth body part is the right foot and the seventh body part is the left foot.
According to one embodiment of the invention, the health status of the hip muscles can be detected.
The motion indication module indicates that the object of interest performs a predetermined action of "squat on one leg".
The detection system comprises a plurality of motion sensors which are respectively worn on thighs of a user to be detected. After the tested user starts to squat with one leg, the plurality of motion sensors measure a plurality of sensor parameters, a first sensor parameter included in the plurality of sensor parameters is a supporting leg acceleration value of the motion sensor worn on the supporting leg of the sixth body part, which changes along with time, and a second sensor parameter included in the plurality of sensor parameters is a lifting leg acceleration value of the motion sensor worn on the lifting leg of the seventh body part, which changes along with time.
The data processing module obtains a first motion characteristic parameter of shaking of a first sub-action supporting leg of the interested object for completing single-leg squatting according to the supporting leg acceleration value of the first sensor parameter, wherein the first motion characteristic parameter is the number of wave crests of the acceleration of the supporting leg in the time length T, namely the total number of the wave crests of the acceleration of the supporting leg in the vertical direction, the horizontal forward direction and the horizontal lateral direction in the time length T. The length of time T may be determined in a number of ways. For example, the time length T may be predetermined. For another example, the time length from the beginning of the predetermined action to the completion of the predetermined action of the user to be tested may be taken as the time length T. As another example, the time period T may be entered by the test operator.
The data processing module obtains a second motion characteristic parameter of single leg lifting of a second sub-action of the object of interest for completing single leg squatting according to the acceleration value of the lifting leg of the second sensor parameter, wherein the second motion characteristic parameter is the motion acceleration of the lifting leg, namely the acceleration of the lifting leg in the vertical direction.
The judgment module determines that the number of wave crests of the accelerated speed of the supporting leg in the time length T reaches a third threshold value according to the first motion characteristic parameter, namely the threshold value of the number of the wave crests, the time is the first time when the first sub-action supporting leg shakes, and the time when the accelerated speed of the lifting leg reaches the maximum value is determined according to the second motion characteristic parameter as the second time when the second sub-action lifting leg lifts. Determining that the health status of the hip muscles is healthy when the first time is after the second time; otherwise, the health state of the hip muscles is determined to be a health problem.
When the first time is before or the same as the second time, namely the health state of the hip muscles is determined to have a health problem, the judging module compares the length of the time difference between the first time and the second time with a time difference threshold value: if the length of the time difference is smaller than the time difference threshold value, determining that the buttock muscle health risk degree is slight; and if the length of the time difference is larger than the time difference threshold value, determining that the buttock muscle health risk degree is serious.
It is noted that, in this document, relational terms such as "first" and "second", and the like, may be used solely to distinguish one module, entity, parameter, or operation from another module, entity, parameter, or operation without necessarily requiring or implying any actual such relationship or order between such modules, entities, parameters, or operations. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Accordingly, the invention is not to be limited to the embodiments shown herein. It will be appreciated that those skilled in the art can make various changes or modifications to the embodiments without departing from the spirit and scope of the present application, and that such changes or modifications fall within the scope of the present application.
Claims (9)
1. A system for detecting the health status of a muscle to be tested of a subject of interest, comprising:
-an action indication module for indicating that the object of interest performs a predetermined action;
-a plurality of motion sensors to be placed at a plurality of locations on the object of interest, respectively, for obtaining a plurality of sensor parameters when the object of interest completes the predetermined action;
-a data processing module for:
-obtaining a first motion characteristic parameter for identifying a first sub-motion of the object of interest for completing the predetermined motion from at least one first sensor parameter of the plurality of sensor parameters;
-obtaining second motion characteristic parameters for identifying a second sub-motion of the object of interest for completing the predetermined motion from at least one second sensor parameter of the plurality of sensor parameters;
-a decision module for:
-determining a first time at which the first sub-action occurs from the first action characteristic parameter;
-determining a second time at which the second sub-action occurs from the second action characteristic parameter;
-comparing the first time and the second time to determine the precedence order in which the first sub-action and the second sub-action occur;
-determining the health status of the muscle to be tested according to the determined chronological order.
2. The system of claim 1, wherein the decision module is further configured to:
-determining the muscle health risk of the muscle to be tested according to the length of the time difference between the first time and the second time when the health status of the muscle to be tested is determined to be in health problems according to the determined precedence order.
3. The system of claim 1, wherein the decision module is further configured to:
-detecting as the first time a time of occurrence of a maximum value of the first motion characteristic parameter during the completion of the predetermined motion of the object of interest;
-detecting as the second time a time of occurrence of a maximum value of the second motion characteristic parameter during the completion of the predetermined motion of the object of interest.
4. The system of claims 1 and 3, wherein the first motion characteristic parameter comprises a first angular velocity of flexion and extension of a first body part of the subject of interest, and the second motion characteristic parameter comprises a second angular velocity of flexion and extension of a second body part of the subject of interest.
5. The system of claim 1, wherein the decision module is further configured to:
-detecting as the first time a time at which the first action characteristic parameter reaches a first threshold value;
-detecting as the second time a time at which the second motion characteristic parameter reaches a second threshold value.
6. The system according to claims 1 and 5, wherein the first motion characteristic parameter comprises a first angle of adjacent third and fourth body parts of the subject of interest, and the second motion characteristic parameter comprises a second angle of adjacent fourth and fifth body parts of the subject of interest.
7. The system of claim 1, wherein the decision module is further configured to:
-detecting a time at which the first action characteristic parameter reaches a third threshold value as the first time;
-detecting as the second time the time at which the second motion characteristic parameter occurs at a maximum value.
8. The system according to claims 1 and 7, wherein the first motion characteristic parameter comprises a number of peaks of a first acceleration of a sixth body part of the subject of interest over a time length T, and the second motion characteristic parameter comprises a second acceleration of a seventh body part of the subject of interest.
9. The system of claim 1, wherein the plurality of motion sensors are inertial sensors.
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