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The Value of Brain-Computer Interface in Stroke Upper Rehabilitation

Published: 09 December 2022 Publication History

Abstract

Stroke is a leading cause of acquired disability that can result in distal upper extremity functional motor impairments. As stroke mortality rates decrease due to advancements in medicine, there has been an increased number of disabled individuals. In recent years, brain-computer interface (BCI) based therapy has shown promising results for meeting the demands of rehabilitating the increasing amount of post-stroke patients. However, BCI has developed primarily in bottom-up, exercising-based intervention models which limits its potential application to patients with extreme disabilities. By stimulating upper body motor function, in which case can restore neural plasticity and motor function, BCI with motor feedback can help us discuss the importance of BCIs usage in top-down intervention. In this paper, we give a brief introduction to stroke upper rehabilitation technologies and the shortcomings of conventional treatment by discussing contemporary BCI systems and three main different types of technologies in signal acquisition. We conclude from a table of robotic EEG-based BCI system studies that treatment should be personalized for stroke patients who need upper limb rehabilitation. By utilizing BCI's customizability in signal acquisition technologies, there can be dozens of different possibilities for developing new novel top-down models.

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            ISAIMS '22: Proceedings of the 3rd International Symposium on Artificial Intelligence for Medicine Sciences
            October 2022
            594 pages
            ISBN:9781450398442
            DOI:10.1145/3570773
            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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            Published: 09 December 2022

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