Author:
Jung Suhun,Bong Jae Hwan,Kim Seung-Jong,Park Shinsuk
Abstract
In this study, we proposed a novel machine-learning-based functional electrical stimulation (FES) control algorithm to enhance gait rehabilitation in post-stroke hemiplegic patients. The electrical stimulation of the muscles on the paretic side was controlled via deep neural networks, which were trained using muscle activity data from healthy people during gait. The performance of the developed system in comparison with that of a conventional FES control method was tested with healthy human subjects.
Funder
National Research Foundation of Korea
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
8 articles.
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