A functional source separation algorithm to enhance error-related potentials monitoring in noninvasive brain-computer interface

•Semi Blind functional source separation (FSS) identify optimal spatial filter for BCI.•FSS algorithm is able to enhance error-related potential (ErrPs) monitoring in non-invasive BCI.•Bayesian linear classification shows higher accuracy for FSS respect to single EEG electrode.•Bayesian linear class...

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Vydané v:	Computer methods and programs in biomedicine Ročník 191; s. 105419
Hlavní autori:	Ferracuti, Francesco, Casadei, Valentina, Marcantoni, Ilaria, Iarlori, Sabrina, Burattini, Laura, Monteriù, Andrea, Porcaro, Camillo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Ireland Elsevier B.V 01.07.2020
Predmet:	Algorithms Bayes Theorem Brain computer interface (BCI) Brain-Computer Interfaces Electroencephalography (EEG) Electroencephalography - methods Error-related potential (ErrP) Event-Related Potentials, P300 Evoked Potentials Functional source separation (FSS) Humans P300, Spatial filter Signal Processing, Computer-Assisted CSP SSNR Functional source separation (FSS) C EEG ICA FSS ROC BCI ErrP Error-related potential (ErrP) P300, Spatial filter Brain computer interface (BCI) AUC Electroencephalography (EEG) FDR NC SNR BLDA EA
ISSN:	0169-2607, 1872-7565, 1872-7565
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