基于样本熵的肌电信号起始点检测研究

摘要

该文提出了一种基于样本熵的动作肌电信号起始点检测方法，为肌电信号应用于智能假肢控制、人机交互，以及临床疾病诊断和评估等领域提供重要前提。首先利用固定长度的滑动窗对动作肌电信号分帧，然后计算每帧信号的样本熵值，之后设定自适应阈值确定动作肌电信号的起始点。实验结果表明，样本熵能够有效表征动作肌电信号的开启模式，对较短时间的肌肉收缩松弛有很好的连续性，较之于其他常见的几类检测算法具有更好的抗噪声性能，特别是对肌肉不自主收缩产生的尖锐毛刺信号具有优异的抑制性能。%Onset detection of action surface electromyography (sEMG)signals is important since it has great impact on the accuracy of subsequent sEMG analysis such as in prosthetic control,human computer interaction and clinical diagnosis and assessment,etc.This study presents a segment onset detection method based on sample entropy.Firstly,sEMG signals are framed by a fixed-length sliding window and the sample entropy of each frame is calculated.Afterwards,adaptive thresh-old is set to determine the starting point.Experimental results demonstrate the feasibility of sample entropy to characterize the switching property of action sEMG signals.Meanwhile,compared to moving average and Teager-Kaiser energy operator,the proposed method has advantages in better anti-jamming ability,not only in suppressing short muscular contraction relaxation intervals,but also in suppressing involuntary background spikes.