超声图像熵特性的肌肉疲劳进程评估

Evaluation of Muscle Fatigue Process Based on Ultrasonic Image Entropy Characteristics

肌肉疲劳是一种由运动引起的肌肉最大随意收缩力减小的现象,处理不当,可能会产生严重的运动损伤。本研究利用自行设计的肌肉组织超声图像检测系统,以超声图像熵表征肌肉超声图像纹理灰度分布的空间特征,探讨肌肉组织疲劳过程中其超声图像熵的演变规律。采集10名受试者在不同负荷(20%MVC、30%MVC、40%MVC、50%MVC)时肱二头肌的超声图像,分别就每一负荷下图像熵随时间的变化进行直线拟合,并对其斜率进行随机区组方差分析。结果表明,不同的受试者之间其肌肉疲劳图像熵随时间变化的斜率差异显著(P=0.000 0);同一受试者不同负荷的超声图像熵随疲劳时间变化斜率也存在显著差异(P=0.040 0)。但是,同一受试者在不同负荷时超声图像熵随时间变化的拟合斜率的差异,远小于不同受试者在同一负荷水平拟合斜率值间的差异,提示个人的肌肉特性起到主要的作用。所进行的研究为肌肉疲劳进程的量化评估提供了依据。

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.