title: Entropy-based multichannel measure of stationarity for characterization of motor imagery patterns.
abstract: We propose a novel approach for measuring the stationarity level of multichannel time-series. This measure is based on stationarity definition over time-varying spectra and aims to quantify the relationship between local (single-channel dynamics) and global (multichannel dynamics) stationarity. With the purpose of separate among several motor/imagery tasks, we asssume that movement imagination implies an increase on the EEG variability, consequently, as discriminant features, we first compute the non-stationary components of input signals, and we further obtain its stationary level throughout the proposed measure. To assess the separability level of the proposed features, we employ the t-student test. Obtained results evidence that our measure is able to accurately detect brain areas projected on the scalp where motor tasks are performed.
authors.forename: J D
authors.initials: JD
authors.lastname: Martínez-Vargas
authors.forename: C
authors.initials: C
authors.lastname: Castro-Hoyos
authors.forename: G
authors.initials: G
authors.lastname: Castellanos-Dominguez
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D062207:Brain-Computer Interfaces; D004569:Electroencephalography; D019277:Entropy; D006801:Humans; D007092:Imagination; D009068:Movement; D059906:Neuroimaging; D012815:Signal Processing, Computer-Assisted