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Using EEG-based brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills: Theoretical background, applications and prospects

Abstract : Many Brain Computer Interface (BCI) and neurofeedback studies have investigated the impact of sensorimotor rhythm (SMR) self-regulation training procedures on motor skills enhancement in healthy subjects and patients with motor disabilities. This critical review aims first to introduce the different definitions of SMR EEG target in BCI/Neurofeedback studies and to summarize the background from neurophysiological and neuroplasticity studies that led to SMR being considered as reliable and valid EEG targets to improve motor skills through BCI/neurofeedback procedures. The second objective of this review is to introduce the main findings regarding SMR BCI/neurofeedback in healthy subjects. Third, the main findings regarding BCI/neurofeedback efficiency in patients with hypokinetic activities (in particular, motor deficit following stroke) as well as in patients with hyperkinetic activities (in particular, Attention Deficit Hyperactivity Disorder, ADHD) will be introduced. Due to a range of limitations, a clear association between SMR BCI/neurofeedback training and enhanced motor skills has yet to be established. However, SMR BCI/neurofeedback appears promising, and highlights many important challenges for clinical neurophysiology with regards to therapeutic approaches using BCI/neurofeedback
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https://hal.archives-ouvertes.fr/hal-01919018
Contributor : Camille Jeunet <>
Submitted on : Monday, November 12, 2018 - 10:30:54 AM
Last modification on : Friday, September 18, 2020 - 2:34:59 PM
Long-term archiving on: : Wednesday, February 13, 2019 - 1:09:41 PM

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Camille Jeunet, Bertrand Glize, Aileen Mcgonigal, Jean-Marie Batail, Jean-Arthur Micoulaud-Franchi. Using EEG-based brain computer interface and neurofeedback targeting sensorimotor rhythms to improve motor skills: Theoretical background, applications and prospects. Neurophysiologie Clinique/Clinical Neurophysiology, Elsevier Masson, 2019, 49 (2), pp.125-136. ⟨10.1016/j.neucli.2018.10.068⟩. ⟨hal-01919018⟩

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