Testing the generation of speed-dependent gait trajectories to control a 6DoF overground exoskeleton

Abstract

Nowadays wearable rehabilitation exoskeletons are one of the most studied gait rehabilitation tool from a technological point of view. Current devices use prerecorded healthy gait patterns. This leads to potentially non-natural imposed gait patterns, and to solve this issue, we propose the use of regression-based methods to reconstruct speed dependent angular trajectories. Results suggest that the proposed method can lead to a more natural gait. Consequently, a naive user may more easily learn to walk under the presence of a robot guidance.