Estimate Agle Information of Hand Open-Close From Surface Electromyogram (sEMG)

Abstract

In this paper, an estimation of angle of hand opening-closing movenments by using the Artificial Neural Network (ANN) from surface electromyography (sEMG) signal is presented. The first step of this method is to record sEMG signal from the subject's right forearm and to acquired video frames of hand at the same time. The second step is to synchronize the beginning and the end of recorded video frame and obtain sEMG signals. The third step is to extract some most commonly used feature vectors for sEMG in the literature. Finally, feature vectors sets are fed to the ANN to estimate angle of hand movements. The obtained success rate of the ANN is given as 94.06% in the train set and 93.41% in the test set.