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EEG in Neurorehabilitation: A Bibliometric Analysis and Content Review.

Athanasia TsiamalouEfthimios DardiotisKonstantinos PaterakisGeorge FotakopoulosIoannis N LiampasMarkos SgantzosVasileios SiokasAlexandros G Brotis
Published in: Neurology international (2022)
EEG constitutes the most significant input in brain-computer interfaces (BCIs) and can be successfully used in the neurorehabilitation of patients with stroke symptoms, amyotrophic lateral sclerosis, and traumatic brain and spinal injuries. EEG-based BCI facilitates the training, communication, and control of wheelchair and exoskeletons. However, research is limited to specific scientific groups from developed countries. Evidence is expected to change with the broader availability of BCI and improvement in EEG-filtering algorithms.
Keyphrases
  • resting state
  • functional connectivity
  • amyotrophic lateral sclerosis
  • working memory
  • spinal cord injury
  • machine learning
  • deep learning
  • atrial fibrillation
  • multiple sclerosis
  • sleep quality
  • high density