Brain–machine interfaces for rehabilitation of poststroke hemiplegia

J. Ushiba, S. R. Soekadar

Research output: Chapter in Book/Report/Conference proceedingChapter

25 Citations (Scopus)

Abstract

Noninvasive brain–machine interfaces (BMIs) are typically associated with neuroprosthetic applications or communication aids developed to assist in daily life after loss of motor function, eg, in severe paralysis. However, BMI technology has recently been found to be a powerful tool to promote neural plasticity facilitating motor recovery after brain damage, eg, due to stroke or trauma. In such BMI paradigms, motor cortical output and input are simultaneously activated, for instance by translating motor cortical activity associated with the attempt to move the paralyzed fingers into actual exoskeleton-driven finger movements, resulting in contingent visual and somatosensory feedback. Here, we describe the rationale and basic principles underlying such BMI motor rehabilitation paradigms and review recent studies that provide new insights into BMI-related neural plasticity and reorganization. Current challenges in clinical implementation and the broader use of BMI technology in stroke neurorehabilitation are discussed.

Original languageEnglish
Title of host publicationProgress in Brain Research
PublisherElsevier B.V.
Pages163-183
Number of pages21
DOIs
Publication statusPublished - 2016

Publication series

NameProgress in Brain Research
Volume228
ISSN (Print)0079-6123
ISSN (Electronic)1875-7855

Keywords

  • Brain–computer interface
  • Brain–machine interface
  • Corticospinal tract
  • Hemiplegia
  • Motor learning
  • Neural plasticity
  • Rehabilitation
  • Sensorimotor cortex

ASJC Scopus subject areas

  • Neuroscience(all)

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