基于排列组合熵的表面肌电信号特征分析

Feature Analysis of SEMG Based on Permutation Entropy

针对表面肌电信号的混沌特征、噪声强等特点,该文提出了基于排列组合熵的表面肌电信号特征分析方法。用肌电信号的相邻数据复杂度计算出排列组合熵,以尺侧腕伸肌和尺侧腕屈肌两路肌电信号对应的排列组合熵构成特征向量,对腕上翻、腕下翻、展拳和握拳四种动作信号进行区分,具有良好的区分度。

according to surface electromyography signal（SEMG） features with chaotic,noise characteristics,a analysis method of SEMG features based on permutation entropy is proposed.The paper uses SEMG data with the complexity of the adjacent to calculate permutation entropy,permutation entropy which corresponding two SEMG of the extensor carpi ulnaris and flexor carpi ulnaris constitute the feature vector,distinguish four actions（wrist flection,wrist extension,release and grasp）,achieves a good discrimination.