Since this is just a design approach it would require followup with stroke leadership and strategy. That doesn't exist, so this research was totally useless.
A Robot-based Gait Training System for Post-Stroke Rehabilitation
Sharon Banh 1,
Emily Zheng 2,
Alyssa Kubota 1,
Laurel D. Riek 1
1 Computer Science and Engineering, University of California San Diego
2 Computing and Mathematical Sciences, California Institute of Technology
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.
ACM Reference Format:
Sharon Banh1
, Emily Zheng2
, Alyssa Kubota1
, Laurel D. Riek1
. 2021. A
Robot-based Gait Training System for Post-Stroke Rehabilitation. In Companion of the 2021 ACM/IEEE International Conference on Human-Robot
Interaction (HRI ’21 Companion), March 8–11, 2021, Boulder, CO, USA. ACM,
New York, NY, USA, 5 pages. https://doi.org/10.1145/3434074.3447212
1 Computer Science and Engineering, University of California San Diego
2 Computing and Mathematical Sciences, California Institute of Technology
ABSTRACT
As the prevalence of stroke survivors increases, the demand forrehabilitative 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.
ACM Reference Format:
Sharon Banh1
, Emily Zheng2
, Alyssa Kubota1
, Laurel D. Riek1
. 2021. A
Robot-based Gait Training System for Post-Stroke Rehabilitation. In Companion of the 2021 ACM/IEEE International Conference on Human-Robot
Interaction (HRI ’21 Companion), March 8–11, 2021, Boulder, CO, USA. ACM,
New York, NY, USA, 5 pages. https://doi.org/10.1145/3434074.3447212
No comments:
Post a Comment