一种改进的基于信号能量阈值的表面肌电信号自动分割方法

Improved Automatic Segmentation Method of sEMG Based on Signals ’ Energy Value

表面肌电信号中连续动作信号的有效分段提取是对信号分析和处理的前提,提出了一种改进的肌电信号自动分割方法,为实现康复机器人信号全自动分析奠定了基础。该方法将表面肌电信号窗口能量作为肌肉动作始末点的判决标准,给出初始阈值计算公式。同时结合小波变换技术对非动作信号进行滤波,并根据分割点特征提出分割阈值自动调节方法。实验表明,该方法可以自动分割肌电信号,无需考虑测试者自身因素的影响,无需手工设定初值,分割结果准确,精度较高。

As effective stage extraction of surface electromyography （sEMG） is the premise of signals analysis and processing, an improved method has been proposed to realize sEMG segmented automatically which could lay a foundation for full automatic analysis of rehabilitation robot. In this paper the value of window energy has been taken as the judgment standard for the start--stop point of muscle action, and the formula of initial threshold has been given. The wavelet transform technique has been applied to filter the non--action signals, and the segmentation value has been adjusted automatically according to the characteristics of the split point. The experiments results show that this method can segment sEMG signals automatically, without regarding as the artificial factors of conner, without initialization, and the results are more accurate and the precision is higher.