Abstract:
A biomechanics analyzing system and a biomechanics computerized analyzing method for analyzing an organism when the organism performs an act by himself are provided. The biomechanics analyzing system includes an accelerometer, a low-pass filter, and a processing unit. The accelerometer is configured to be disposed on a surface of a muscle of the organism and is further configured to detect an acceleration signal. The low-pass filter is connected to the accelerometer and is configured for receiving the acceleration signal from the accelerometer and filtering the acceleration signal to produce a low-frequency signal. The processing unit is connected to the low-pass filter, and is configured for receiving the low-frequency signal from the low-pass filter and analyzing a frequency of a motion state of the organism according to the low-frequency signal.

Description:
[0001]    This is a continuation-in-part application of application Ser. No. 12/842,244, filed on Jul. 23, 2010 which claims the benefit of Taiwan application Serial No.099121749, filed Jul. 1, 2010, the subject matter of which is incorporated herein by reference. 
     
    
     TECHNICAL FIELD 
       [0002]    The disclosure relates in general to a biomechanics analyzing system and a biomechanics analyzing method. 
       BACKGROUND 
       [0003]    Recently, the progress in the technology makes a lot of manpower be replaced with the mechanical power so that life becomes more convenient. However, the exercising opportunity of the human body is relatively gradually decreased. This causes the unbalanced enhancement in the physical fitness ability, and also degrades the training effect. The weakness of muscular fitness during exercise further causes frequently seen lifestyle diseases. For example, the low back pain is frequently caused by the muscular problem (i.e., the muscle weakness or muscle tightness) in the motion. At present, many references have proved that the enhancement of the strength of the muscle is advantageous to the maintenance of the health-related physical fitness of the non-athlete and the prevention of the modern lifestyle diseases. 
       SUMMARY 
       [0004]    According to an exemplary embodiment of the present disclosure, a biomechanics analyzing system for analyzing a motion state of an organism when the organism performs an act by himself is provided. The biomechanics analyzing system includes an accelerometer, a low-pass filter, and a processing unit. The accelerometer is configured to be disposed on a surface of a muscle of the organism and is further configured to detect an acceleration signal. The low-pass filter is connected to the accelerometer and is configured for receiving the acceleration signal from the accelerometer and filtering the acceleration signal to produce a low-frequency signal. The processing unit is connected to the low-pass filter, and is configured for receiving the low-frequency signal from the low-pass filter and analyzing a frequency of a motion state of the organism according to the low-frequency signal. 
         [0005]    According to an exemplary embodiment of the present disclosure, a biomechanics computerized analyzing method for analyzing a motion state of an organism when the organism performs an act by himself is provided. The biomechanics computerized analyzing method includes the following steps. An acceleration signal is detected on a surface of a muscle of the organism by an accelerometer. The acceleration signal is filtered to produce a low-frequency signal. A frequency of the motion state of the organism is analyzed according to the low-frequency signal. 
         [0006]    The above and other aspects of the disclosure will become better understood with regard to the following detailed description of the non-limiting embodiment(s). The following description is made with reference to the accompanying drawings. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0007]      FIG. 1  is a block diagram showing a biomechanics analyzing system according to an embodiment of the disclosure. 
           [0008]      FIGS. 2A to 3B  are schematic illustrations showing a user wearing a detecting unit to do exercise. 
           [0009]      FIG. 4  is a flow chart showing a biomechanics computerized analyzing method according to an embodiment of the disclosure. 
           [0010]      FIG. 5  shows a low-frequency signal. 
           [0011]      FIG. 6A  shows a low-frequency signal. 
           [0012]      FIG. 6B  shows an acceleration signal. 
           [0013]      FIG. 7  shows a relationship between the time and the median of the frequency of the motion state. 
           [0014]      FIG. 8  shows a flowchart of detail steps for analyzing the muscle fatigue extent according to the frequency of the motion state. 
           [0015]      FIG. 9  shows a flowchart of detail steps for analyzing the muscle endurance according to the muscle fatigue extent of the organism. 
       
    
    
     DETAILED DESCRIPTION 
       [0016]    The disclosure is directed to a biomechanics analyzing system and a biomechanics analyzing method for analyzing the mechanomyography (MMG) according to the acceleration signal detected by a detecting unit. Thus, the information, such as the posture and the frequency of the motion state of the user, can be obtained. 
         [0017]      FIG. 1  is a block diagram showing a biomechanics analyzing system  100  according to an embodiment of the disclosure. Referring to  FIG. 1 , the biomechanics analyzing system  100  is for detecting a motion state of an organism. The organism may be an animal, such as the human, cat, dog, horse or fish. The biomechanics analyzing system  100  includes a detecting unit  110 , a low-pass filter  120 , a processing unit  140  and a providing unit  150 . The detecting unit  110  detects an acceleration signal A 0 . For example, the detecting unit  10  may be a mechanical accelerometer, a piezoelectric voltage-type accelerometer, a charge-type accelerometer or a capacitive accelerometer. The low-pass filter  120  filters an electronic signal, and then lets the low-frequency components pass. The processing unit  140  analyzes various signals to obtain the associated information. The low-pass filter  120  and the processing unit  140  may be, for example, a chip, a firmware circuit or a computer readable recording medium for storing a plurality of sets of program codes. The providing unit  150 , such as a hard disk, a memory card, a keyboard, a mouse or a transmission cable, provides a lot of required information. 
         [0018]      FIGS. 2A to 3B  are schematic illustrations showing a user  200  wearing the detecting unit  110  to do exercise. In  FIG. 2A , the user  200  stands and lift his/her foot. The detecting unit  110  is worn on a thigh  210  of the user  200 . The biomechanics analyzing system  100  (see  FIG. 1 ) of this embodiment can analyze the angle of the thigh  210  with respect to the horizontal plane L to obtain the posture of the thigh  210  of the user  200 . If the user  200  repeats the same motion, the biomechanics analyzing system  100  of this embodiment may also analyze its frequency of the motion state. 
         [0019]    In  FIG. 2B , the user  200  performs the semi-crouch motion. In  FIGS. 2A and 2B , the angles of the thigh  210  with respect to the horizontal plane L are similar, but the strength of the muscle of the thigh  210  of  FIG. 2B  is greater than the strength of the muscle of the thigh  210  of  FIG. 2A . 
         [0020]    In  FIG. 3A , the user  200  performs the hill climbing motion. The biomechanics analyzing system  100  (see  FIG. 1 ) of this embodiment can analyze the angle of the thigh  210  with respect to the horizontal plane L to obtain the posture of the thigh  210  of the user  200 . If the user  200  repeats the same motion, the biomechanics analyzing system  100  of this embodiment may also analyze its frequency of the motion state. 
         [0021]    In  FIG. 3B , the user  200  also performs the hill climbing motion, but the loading in  FIG. 3B  is greater than the loading in  FIG. 3A , so that the strength of the muscle of the thigh  210  in  FIG. 3B  is greater than that in FIG. 
         [0022]      3 A. 
         [0023]    Of course, in addition to the thigh  210 , the detecting unit  110  may also be disposed on other extremities, the head, the breast, the waist, and the position thereof does not intend to restrict the disclosure. 
         [0024]      FIG. 4  is a flow chart showing a biomechanics computerized analyzing method according to an embodiment of the disclosure. As shown in  FIGS. 1 and 4 , the biomechanics computerized analyzing method of this embodiment will be clearly described with reference to an actual measurement example. In one actual measurement example, the detecting unit  110  is attached to the thigh of the user. Those skilled in the art may easily understand that the biomechanics analyzing system  100  of this embodiment is not particularly restricted to this flow chart, and the order and the contents of the steps may be properly adjusted. 
         [0025]    First, in step S 401 , the detecting unit  110  is disposed on the surface of the muscle of the organism to detect an acceleration signal A 0 . 
         [0026]    Next, in step S 403 , the low-pass filter  120  filters the acceleration signal A 0  to produce a low-frequency signal A 1 .  FIG. 5  shows the low-frequency signal A 1 . 
         [0027]    Next, in step S 407 , the processing unit  140  analyzes a frequency of the motion state of the organism according to the low-frequency signal Al and analyzes a posture of the motion state of the organism according to the acceleration signal A 0 . 
         [0028]    In one example, the frequency of the motion state of the organism can be analyzed according to the low-frequency signal A 1  by the following steps. Please refer to  FIG. 6A , which shows a low-frequency signal A 1 ′. One organism wears an accelerometer when he is walking. The number of the local minimum of the low-frequency signal A 1 ′ or the number of the local maximum of the low-frequency signal A 1 ′ during a cycle time is deemed as the frequency of the walking steps. 
         [0029]    In one example, the posture of the motion state of the organism can be analyzed according to an acceleration signal A 0 ′ by the following steps. 
         [0030]    Please refer to  FIG. 6B , which shows the acceleration signal A 0 ′. One organism wears the accelerometer on his thigh. The acceleration signal A 0 ′ includes a X-axis acceleration a x  and a Z-axis acceleration a z . The angle θ with respect to the horizontal plane L can be calculated by θ=tan −1 (a x /a z ) Therefore, the angle of the thigh of the organism can be obtained. Then, the posture of the motion state of the organism can be obtained according to the angle of the thigh of the organism. 
         [0031]    Next, in step S 411 , the processing unit  140  further analyzes a muscle fatigue extent of the organism according to the frequency of the motion state. 
         [0032]    In one example, the muscle fatigue extent can be analyzed according to the frequency of the motion state by the following steps. Please refer to  FIG. 7 , which shows a relationship between the time and the median of the frequency of the motion state. Please refer to  FIG. 8 , which shows a flowchart of detail steps for analyzing the muscle fatigue extent according to the frequency of the motion state. Firstly, in step S 801 , at the begin of the motion, the frequency of the motion state is obtained according to a MMG signal during a time period. For example, the time period is 30 seconds. Then, in step S 802 , an initial reference value of the median of the frequency of the motion state is obtained according to the MMG signal. Next, in step S 803 , the initial reference value of the median of the frequency of the motion state is recorded. Then, in step S 804 , after performing the motion for a long time, the frequency of the motion state is obtained according to the MMG signal during another time period. Next, in step S 805 , a current value of the median of the frequency of the motion state is obtained according to the MMG signal. Then, in step S 806 , whether the difference between the current value of the median of the frequency of the motion state and the initial reference value of the median of the frequency of the motion state is larger than a predetermined value is determined. If the difference is larger than the predetermined value, then the process proceeds to the step S 807 . In step S 807  the muscle is deemed as being fatigued. 
         [0033]    Then, in step S 412 , the processing unit  140  further analyzes a muscle endurance of the organism according to the muscle fatigue extent of the organism. 
         [0034]    In one example, the muscle endurance can be analyzed according to the muscle fatigue extent of the organism by the following steps. Please refer to  FIG. 9 , which shows a flowchart of detail steps for analyzing the muscle endurance according to the muscle fatigue extent of the organism. Firstly, in step S 901 , a previous value of time when the muscle is fatigued is obtained. The previous value of time may be obtained before. Next, in step S 902 , a current value of time when the muscle is fatigued is obtained. Then, in step S 903 , whether the current value of time is larger than the previous value of time is determined. If the current value of time is larger than the previous value of time, then the process proceeds to step S 904 ; otherwise, the process proceeds to step S 905 . In step S 904 , the muscle endurance becomes large. In step S 905 , the muscle endurance becomes small. 
         [0035]    While the disclosure has been described by way of example and in terms of the exemplary embodiment(s), it is to be understood that the disclosure is not limited thereto. On the contrary, it is intended to cover various modifications and similar arrangements and procedures, and the scope of the appended claims therefore should be accorded the broadest interpretation so as to encompass all such modifications and similar arrangements and procedures.