EMG-driven bilateral therapy for hand rehabilitation: Evaluation of the influence of an EMG-based visual biofeedback on the users’ performance

Abstract

Background: The development of rehabilitation robotic systems has experienced significant growth in recent years. Electromyography (EMG) is commonly used to drive this kind of robots. Although there are some studies that have assessed the effectiveness of EMG biofeedback in neurorehabilitation, none of them has applied this technique in combination with robotic platforms.Objectives: Our goal was to evaluate the influence of EMG biofeedback on the user performance, when individuals were asked to perform different hand gestures (open, rest and close) using an EMG-driven robotic hand exoskeleton rehabilitation platform. Methods: A total of 18 healthy subjects were enrolled in the study. The subjects were asked to perform 1-minute randomly generated sequences of hand gestures in four different conditions resulting from the combination of using or not (1) EMG-based visual biofeedback (2) kinesthetic feedback from the exoskeleton movement Results: The subject performance was statistical significantly better when the EMG-based visual feedback was present, while kinesthetic feedback did not improve their performance. The performance when both sources of feedback were present did not resulted in any enhancement, indicating that the kinesthetic feedback overrides the effect of the electromyographic one.Conclusion: The EMG-based visual feedback enables subjects to increase their control over the movement of the robotic platform by assessing their muscle activation in real-time. This type of feedback could benefit the patients in learning faster how to co-activate the motions of the rehabilitation robot, which may increase their motivation.