SURFACE EMG SIGNAL CLASSIFICATON METHOD BASEDON COMPLEXITY MEASURE
基于复杂性度量的表面肌电信号分类方法

The feasibility of using complexity measure as surface EMG signal feature for motion classification was explored in this paper. By constructing feature vectors from complexity measures extracted from raw EMG data, four kinds of forearm motions were identified with a high accuracy. Experimental results proved that this measure, having a simple algorithm, is suitable for short data sets and capable of real time processing. It provides a new way for prothesis control and pathological diagnosis.