On the Effects of Visual Anticipation of Floor Compliance Changes on Human Gait: Towards Model-based Robot-Assisted Rehabilitation

摘要

The role of various types of robot assistance in post-stroke gait rehabilitation has gained much attention in recent years. Furthermore, there is increased popularity to use more than one rehabilitation method in order to utilize the different advantages of each. Naturally, this results in the need to study how the different robot-assisted interventions affect the various underlying sensorimotor mechanisms involved in rehabilitation. To answer this important question, this paper combines a virtual reality experience with a unique robotic rehabilitation device, the Variable Stiffness Treadmill (VST), as a way of understanding interactions across different sensorimotor mechanisms involved in gait. The VST changes the walking surface stiffness in order to simulate real-world compliant surfaces while seamlessly interacting with a virtual environment. Through the manipulated visual and proprioceptive feedback, this paper focuses on the muscle activation patterns before, during, and after surface changes that are both visually informed and uninformed. The results show that there are predictable and repeatable muscle activation patterns both before and after surface stiffness changes, and these patterns are affected by the perceived visual and proprioceptive feedback. The interaction of feedback mechanisms and their effect on evoked muscular activation can be used in future robot-assisted gait therapies, where the intended muscle responses are informed by deterministic models and are tailored to a specific patient's needs.