Alpha rebound improves on-line detection of the end of motor imageries

Cecilia Lindig-León 1 Laurent Bougrain 1 Sébastien Rimbert 1
1 NEUROSYS - Analysis and modeling of neural systems by a system neuroscience approach
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
Abstract : Limb movement execution or imagination induce sensorimotor rhythms that can be detected in electroencephalographic (EEG) recordings. This article presents the interest of considering not only the beta frequency band but also the alpha band to detect the elicited EEG rebound, i.e. the increasing of oscillatory power synchronization, at the end of motor imageries. From database 2a of the BCI competition IV, it is shown that this phenomenon can be stronger over the alpha than the beta band and it is experimentally demonstrated that the analysis on the alpha band improves the detection of the end of motor imageries. Moreover a variant method to compute the oscillatory power without referring to a baseline period is proposed; such capacity is useful for self-paced brain-computer interfaces (BCI) control.
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Cecilia Lindig-León, Laurent Bougrain, Sébastien Rimbert. Alpha rebound improves on-line detection of the end of motor imageries. IEEE EMBS Neural engineering conference , Apr 2015, Montpellier, France. ⟨hal-01092284v2⟩

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