Brain-machine interfaces for rehabilitation of poststroke hemiplegia

Junichi Ushiba, S. R. Soekadar

Research output: Contribution to journalArticle

16 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
JournalProgress in Brain Research
DOIs
Publication statusAccepted/In press - 2016

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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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