sEMG-based continuous estimation of grasp movements by long-short term memory network

Controlling a robotic hand or arm by surface Electromyographic signals (sEMG) is an important research direction. The present pattern-recognition-based control strategy can realize some myoelectric control but it is not as smooth as human hand. In this paper, we proposed a continuous estimation method for 6 daily grasp movements by Long-Short Term Memory Network (LSTM). In addition, we compared Sparse Gaussian Processes using Pseudo-inputs...