Motion state identification of human hand
Xiaoyong Wang · Computer Engineering and Applications Journal · 2010
A novel classifier that uses wavelet transform and Lyapunov exponent to construct feature vectors is presented.Using the advantage of back propagation in area of non-linear modeling,construct neural network to classify.It is efficient to classify motion states of the hands which include hand grasping,hand opening,wrist inner spinning and wrist outer spinning through disposal of four routes SEMG gathering from antbrachium extensor,flexor and pronator.The result indicates that the classifier has more higher recognize exactitude and stable reappearance.