A robot-based gait training system for post-stroke rehabilitation

Abstract

As the prevalence of stroke survivors increases, the demand for rehabilitative services will rise. While there has been considerable development in robotics to address this need, few systems consider individual differences in ability, interests, and learning. Robots need to provide personalized interactions and feedback to increase engagement, enhance human motor learning, and ultimately, improve treatment outcomes. In this paper, we present 1) our design process of an embodied, interactive robotic system for post-stroke rehabilitation, 2) design considerations for stroke rehabilitation technology and 3) a prototype to explore how feedback mechanisms and modalities affect human motor learning. The objective of our work is to improve motor rehabilitation outcomes and supplement healthcare providers by reducing the physical and cognitive demands of administering rehabilitation. We hope our work inspires development of human-centered robots to enhance recovery and improve quality of life for stroke survivors.