Abstract：Muscle fatigue is a phenomenon that the maximum voluntary contraction force of muscle is reduced due to muscular movement. If the fatigue is not treated properly it will harm the muscle. In this study we used a designed ultrasonic image entropy testing system to detect the muscle tissue, and used the image entropy to characterize the gray scale distribution characteristic of muscle ultrasonic image texture, trying to evaluate characteristics of the muscle fatigue process. We collected the ultrasound images of biceps brachii of ten subjects with different loads (20%MVC、30%MVC、40%MVC、50%MVC), and linearly fitted their estimated ultrasound image entropy. A statistical analyze method of ANOVA of the random group was applied to study the down slope of muscle fatigue image entropy. It is shown that the slope between different subjects over time are different significantly(P=0.000 0), the slope under different loads of same subjects are also different (P=0.0400). However, the difference of the linear fitted slope of ultrasonic image entropy under different loads to the same subject is far less than that of the same loads to different subjects, which illustrates that the personal muscles characteristics play a major role. This study provides a quantitative evaluation method to the muscle fatigue process.
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