A Rehabilitation Robot System to Enhance Proprioception with Physical and Virtual Simulation of Multi-terrain Scenarios

Abstract

Increasing evidence highlights the role of proprio-ceptive deficits in falls, emphasizing the need for targeted rehabilitation in populations with functional movement disorders. Despite advances in rehabilitation robots, movement constraints still hinder active engagement of the lower limb muscles, thereby limiting the effectiveness of proprioceptive training. In this work, We developed a neuro-rehabilitation robotic platform to address this need by physically and virtually simulating multi-terrain scenarios. The robot introduces common perturbations, such as uneven mountain trails, sandy beaches, and bumpy bus rides, to assess user stability and recovery, thereby assisting in the design of individualized training programs. The platform enhances neuromuscular responses across multiple directions and facilitates targeted muscle contraction through motor tasks that combine proprioceptive and visual feedback. Preliminary studies demonstrated that the robot successfully facilitated a complete range of ankle rotational movements. Electromyographic analysis revealed increased activation of specific muscle groups, changes in muscle loading and contraction patterns, suggesting that the system recruits multiple muscle groups while enhancing proprioceptive input to periarticular soft tissues. The proposed robot and control strategies established a feasible solution to enhance proprioception rehabilitation.