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Is motor-imagery brain-computer interface feasible in stroke rehabilitation ?

TEO WP; CHEW E
PM & R , 2014, vol. 6, n° 8, p. 723-728
Doc n°: 171095
Localisation : Documentation IRR

D.O.I. : http://dx.doi.org/DOI:10.1016/j.pmrj.2014.01.006
Descripteurs : AF21 - ACCIDENTS VASCULAIRES CEREBRAUX, AL - NEUROREEDUCATION

In the past 3 decades, interest has increased in brain-computer interface (BCI)
technology as a tool for assisting, augmenting, and rehabilitating sensorimotor
functions in clinical populations. Initially designed as an assistive device for
partial or total body impairments, BCI systems have since been explored as a
possible adjuvant therapy in the rehabilitation of patients who have had a
stroke. In particular, BCI systems incorporating a robotic manipulanda to
passively manipulate affected limbs have been studied. These systems can use a
range of invasive (ie, intracranial implanted electrodes) or noninvasive
neurophysiologic recording techniques (ie, electroencephalography [EEG],
near-infrared spectroscopy, and magnetoencephalography) to establish
communication links between the brain and the BCI system. Trials are most
commonly performed on EEG-based BCI in comparison with the other techniques
because of its high temporal resolution, relatively low setup costs, portability,
and noninvasive nature. EEG-based BCI detects event-related
desynchronization/synchronization in sensorimotor oscillatory rhythms associated
with motor imagery (MI), which in turn drives the BCI. Previous evidence suggests
that the process of MI preferentially activates sensorimotor regions similar to
actual task performance and that repeated practice of MI can induce plasticity
changes in the brain. It is therefore postulated that the combination of MI and
BCI may augment rehabilitation gains in patients who have had a stroke by
activating corticomotor networks via MI and providing sensory feedback from the
affected limb using end-effector robots. In this review we examine the current
literature surrounding the feasibility of EEG-based MI-BCI systems in stroke
rehabilitation. We also discuss the limitations of using EEG-based MI-BCI in
patients who have had a stroke and suggest possible solutions to overcome these
limitations.
CI - Copyright (c) 2014 American Academy of Physical Medicine and Rehabilitation.
Published by Elsevier Inc. All rights reserved.

Langue : ANGLAIS

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