EMG-based teleoperation of a robot arm in planar catching movements using ARMAX model and trajectory monitoring techniques

This paper presents a methodology of teleoperating a robot arm, using electromyographic (EMG) signals and a trajectory monitoring technique based on human motion analysis. EMG signals from the flexor and extensor muscles of the elbow joint are used to predict the human elbow joint angle, using an auto-regressive moving average with exogenous output (ARMAX) model. A position tracker is attached in the user upper arm, before the elbow joint. It has been identified from previous works on human physiology that the trajectory of the human hand during planar catching tasks lays on a straight line. This motion law is used in order to monitor and refine the trajectory of the human hand that is predicted through EMG and the ARMAX model. The experimental results show that the ARMAX model estimation for the elbow angle, in conjunction with the trajectory monitoring technique, is able to predict the user motion with high accuracy, within different target points unknown to the system, and various hand velocities