目的通过对肌肉疲劳过程中非诱发表面肌电(surface electromyography,sEMG)信号和诱发表面肌电信号的研究分析,寻找有效评价肌肉疲劳的分析测量方法。方法对7名受试者进行自主运动和电刺激两种致肌疲劳的实验,并在两组实验中分别记录电刺激诱发与非诱发肌电信号,然后对每组信号进行傅里叶变换求取功率谱和近似熵。结果随着疲劳的产生,两组实验诱发信号的频谱曲线左移效果优于非诱发信号,近似熵分析中电刺激组诱发信号出现先上升后下降的变化,自主运动组诱发信号则呈现单调递减的趋势。结论低频电刺激诱发表面肌电信号更适于测量肌疲劳的动态变化。相对于传统功率谱,近似熵分析方法更适于处理电刺激诱发的表面肌电信号。
Objective To establish an effective method for evaluating muscular fatigue by using surface electromyography (sEMG) signals under electrical stimulation or rest condition. Methods Both sEMG signals under electrical stimulation conditions and rest condition were recorded during the experiments of muscular fatigue indicated by motion contraction and electrical stimulation. Power spectrum by Fourier transform and approximation entropy were extracted to analyze the signals. Results There were left shifts found on the curves of power spectrum in both voluntary and evoked sEMG signals on occurrence of fatigue ,whereas no obvious shift on the curves of the resting ones. In the entropy analysis,there was a monotonous decrease in voluntary signal and an up and down tendency in electrical stimulation signal. Conclusions Both methods are good measures to indicate muscular fatigue, and are more indicative in active (i. e. voluntary and electrical stimulation ) conditions than in rest conditions. And approximation entropy is more suitable to indicate fatigue of sEMG signals evoked by electrical stimulation.