Prediction of Human Elbow Torque from EMG Using SVM Based on AWR Information Acquisition Platformn **This work is partially supported by CNSF Grant #60505012,60575054 to Q. J. Song.

In this paper a novel prediction method of elbow torque from EMG signal using SVM is proposed. How to model the relations between EMG signals and various kinematical aspects of the movement behavior is a difficult problem in the researches of neurophysiology and biomechanies. Traditional prediction methods include using neural networks to model the relations. However, these methods suffer from several problems, such as local minima, the difficulty of the selection of the model, etc. To address these problems, support vector machine is adopted to construct the nonlinear model. The efficiency of our proposed method is proved by experiment results.