Modular Design and Control System Optimisation of an Upper Limb Rehabilitation Robot

Stroke is one of the leading causes of disability and death worldwide, and upper limb dysfunction in particular seriously affects patients' daily life and self-care ability. Therefore, designing efficient and economical upper limb rehabilitation robots has become an urgent problem. In this paper, a modular and lightweight upper limb rehabilitation robot is proposed. The robot employs adaptive impedance control, model predictive control (MPC) and electromyogram (EMG)-based closed-loop control strategies to achieve personalized rehabilitation training support. Through simulation and experimentation, this paper verifies the significant effect of the robotic system in enhancing the upper limb function of stroke patients, especially in improving locomotor ability, enhancing the sense of active participation, and promoting the recovery of voluntary movement. The results show that the system has the ability of efficient and personalized rehabilitation training, and is expected to be widely applied in home and community rehabilitation to promote the popularity and development of upper limb rehabilitation technology. The analyses in this position can provide a reference for the development of upper limb rehabilitation robots.