Human interface using surface electromyography signals

Abstract

Abstract We have been working toward the construction of a forward model arm employing a neural network model with electromyographic signals as the control input. We have succeeded in estimating 1) the joint torque during isometric contraction in a plane from the electromyographic signals, 2) the path of motion from the degree of joint acceleration as well as 3) the path of motion from the joint torque and 4) the position in three‐dimensional space. In this paper, we present a new human interface employing a model of an arm, robot control of an artifical hand, and the learning of motion capability. In addition, based on the fact that we can estimate the position of the arm in three‐dimensional space, we discuss as an example of the human interface the results of generating motion from electromyographic signals in a hypothetical arm using a neural network model.