Simulation System of Upper-limb Rehabilitation Training Exoskeleton Controlled by Mechanomyography Signals

Abstract

A novel simulation system of upper-limb rehabilitation training exoskeleton controlled by pattern recognition of mechanomyography (MMG) signals is developed in this study. Aiming at the upper-limb rehabilitation training of hemiplegia patients, this system is divided into two parts: one part includes 3 classes of shoulder and elbow movements, and another part includes 6 classes of wrist movements. After collecting multi-channel MMG for upper-limb movements and designing a 7 degrees of freedom (DoF) upper-limb exoskeleton model, the system can generate instructions to control the exoskeleton to assist the patients to do upper-limb (hemiplegia) rehabilitation training according to the pattern recognition results of upper-limb (normal side) movements. The simulation system makes that is possible to assist hemiplegia patients to do passive training for upper-limbs according to the pattern recognition of upper limb movements based on MMG, and the bilateral movements are more benefit to rehabilitation from a medical standpoint.