Estimation of muscle forces and joint torque from EMG using SA process

This paper is motivated by works done in the area of robot-assisted stroke rehabilitation. The use of electromyographic (EMG) signal brings a new way of communication interface between user and robot. However, the EMG signal has to be transferred into useful information that serve as robot input. This paper presents a novel methodology for conversion of electromyographic (EMG) signal into estimated joint torque. Investigation of the proposed methodology covers human upper limb movement: shoulder flexion-extension, shoulder abduction-adduction, and elbow flexion-extension. Simulated annealing (SA) is implemented to obtain optimum model that maps EMG into estimated joint torque. General principle, design, and the implementation of SA for the problem are discussed in this paper. Experimentation was carried out to investigate the feasibility of the proposed algorithm. The results show that the algorithm is able to find optimum model that enables EMG to joint torque conversion.