Recognition of outer muscle's EMG and Inner muscle's EMG using support vector machine (recognition of abduction and external rotation movements of shoulder joint)

There have been some studies of exoskeletal robots to support upper limb motion. However, it is difficult to support internal/external rotation, one of 3 DOF in the shoulder joint. This is because the internal/external rotation is performed by the activities of the rotator cuff, which consists of deep layer muscles. In other words, it is difficult to recognize the surface electromyogram (SEMG) signals, which are generated at muscles far from the skin. In this paper, our aim is to quantify the different characteristics in the SEMG between the surface layer and deep layer muscles and apply different characteristics to the discrimination of the external rotation under the experimental evaluation with twelve young subjects. Three kinds of parameters, such as Zero Crossing, MPF and coefficient of the approximate function, were selected to express the characteristic of high frequency component in the EMG signal. Specifically, the classification was shown to be 97% successful by applying two features to Support Vector Machine (SVM). Hence, it is almost possible to assume that either the deep or the surface muscle is active and discriminate the motions which their muscles involve.