Virtual Reality-Based Robot-Assisted Method for Gait Training Showing Retention of Anticipatory Motor Responses

Abstract

The recent increase in attention toward robotic assistance in gait therapy has prompted a clear need for useful paradigms that can interface with such devices. This is especially true for post-stroke rehabilitation, for which impairments in walking are particularly debilitating and notoriously difficult to overcome. Until recently, robot-assisted gait training methods tended to target only a single aspect of the human sensorimotor system, usually proprioception. To address this limitation, a virtual reality (VR) system is united with the unique robotic rehabilitation platform, the Variable Stiffness Treadmill (VST), in order to understand the complex interactions between visual and proprioceptive feedback in gait. This work proposes a new type of intervention that directly results in significant anticipatory responses to stiffness perturbations, even when those anticipated perturbations may not occur, showing that using a VR system can lead to the retention of training provided. The results show relevant and repeatable responses, which can lay the foundation for more effective protocols that can be used for a wider array of robotic systems and sensory modalities.