000187951 001__ 187951
000187951 005__ 20190316235700.0
000187951 0247_ $$2doi$$a10.1088/1741-2560/10/5/056007
000187951 022__ $$a1741-2552
000187951 02470 $$2ISI$$a000324862400007
000187951 037__ $$aARTICLE
000187951 245__ $$aAn online EEG BCI based on covert visuospatial attention in absence of exogenous stimulation
000187951 269__ $$a2013
000187951 260__ $$bIop Publishing Ltd$$c2013$$aBristol
000187951 300__ $$a8
000187951 336__ $$aJournal Articles
000187951 520__ $$aObjective. In this work we present—for the first time—the online operation of an electroencephalogram (EEG) brain–computer interface (BCI) system based on covert visuospatial attention (CVSA), without relying on any evoked responses. Electrophysiological correlates of pure top-down CVSA have only recently been proposed as a control signal for BCI. Such systems are expected to share the ease of use of stimulus-driven BCIs (e.g. P300, steady state visually evoked potential) with the autonomy afforded by decoding voluntary modulations of ongoing activity (e.g. motor imagery). Approach. Eight healthy subjects participated in the study. EEG signals were acquired with an active 64-channel system. The classification method was based on a time-dependent approach tuned to capture the most discriminant spectral features of the temporal evolution of attentional processes. The system was used by all subjects over two days without retraining, to verify its robustness and reliability. Main results. We report a mean online accuracy across the group of 70.6 ± 1.5%, and 88.8 ± 5.8% for the best subject. Half of the participants produced stable features over the entire duration of the study. Additionally, we explain drops in performance in subjects showing stable features in terms of known electrophysiological correlates of fatigue, suggesting the prospect of online monitoring of mental states in BCI systems. Significance. This work represents the first demonstration of the feasibility of an online EEG BCI based on CVSA. The results achieved suggest the CVSA BCI as a promising alternative to standard BCI modalities.
000187951 6531_ $$aBrain-computer Interface
000187951 6531_ $$acovert visuospatial attention
000187951 6531_ $$aEEG
000187951 6531_ $$aOnline operations
000187951 700__ $$0242175$$g190240$$aTonin, Luca
000187951 700__ $$0242179$$g192497$$aLeeb, Robert
000187951 700__ $$g220790$$aSobolewski, Aleksander$$0246009
000187951 700__ $$aMillán, José del R.$$g149175$$0240030
000187951 773__ $$j10$$tJournal of Neural Engineering$$k5$$q056007
000187951 8564_ $$uhttps://infoscience.epfl.ch/record/187951/files/1741-2552_10_5_056007%20%281%29.pdf$$zPublisher's version$$s450046$$yPublisher's version
000187951 909C0 $$xU12103$$0252018$$pCNBI
000187951 909C0 $$pCNP$$xU12599$$0252517
000187951 909CO $$qGLOBAL_SET$$pSTI$$particle$$ooai:infoscience.tind.io:187951
000187951 917Z8 $$x190240
000187951 917Z8 $$x190240
000187951 937__ $$aEPFL-ARTICLE-187951
000187951 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000187951 980__ $$aARTICLE