The Effects of EMG-Based Classification and Robot Control Method on User's Neuromuscular Effort during Real-Time Assistive Hand Exoskeleton Operation

EMG-based intention recognition and assistive device control are often developed separately, which can lead to the unintended consequence of requiring excessive muscular effort and fatigue during operation. In this paper, we address two important aspects of the performance of an integrated EMG-based assistive system. Firstly, we investigate the effects of muscular effort on EMG-based classification and robot control. Secondly, we propose a robot control solution that reduces muscular effort required in assisted dynamic daily tasks compared to the state-of-the-art control methods.