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Comparison of four classification methods for brain-computer interface

SYSNO ASEP	0359738
Document Type	J - Journal Article
R&D Document Type	Journal Article
Subsidiary J	Článek ve WOS
Title	Comparison of four classification methods for brain-computer interface
Author(s)	Frolov, A. (RU) Húsek, Dušan (UIVT-O)_{RID, SAI, ORCID} Bobrov, P. (RU)
Source Title	Neural Network World. - : Ústav informatiky AV ČR, v. v. i. - ISSN 1210-0552 Roč. 21, č. 2 (2011), s. 101-115
Number of pages	15 s.
Language	eng - English
Country	CZ - Czech Republic
Keywords	brain computer interface ; motor imagery ; visual imagery ; EEG pattern classification ; Bayesian classification ; Common Spatial Patterns ; Common Tensor Discriminant Analysis
Subject RIV	IN - Informatics, Computer Science
R&D Projects	1M0567 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
	GA201/05/0079 GA ČR - Czech Science Foundation (CSF)
	GAP202/10/0262 GA ČR - Czech Science Foundation (CSF)
CEZ	AV0Z10300504 - UIVT-O (2005-2011)
UT WOS	000290838300001
EID SCOPUS	79957872178
DOI	10.14311/NNW.2011.21.007
Annotation	Four classifiers effectiveness, for Brain Computer Interface (BCI) based on multichannel EEG with aim to distinguish EEG patterns corresponding to performance of several mental tasks, is compared. Basic Bayesian classifier (BC) exploits only inter-channel covariance matrices. The second one based on Bayesian approach exploits inter-channel covariance matrices estimated separately for several frequency bands (Multiband Bayesian Classifier, MBBC). The third one based on Multiclass Common Spatial Patterns (MSCP) method exploits only inter-channel covariance matrices as BC. The fourth one based on Common Tensor Discriminant Analysis (CTDA) takes EEG frequency structure into account. The MBBC and CTDA classifiers perform significantly better than the two other methods. Classifiers computational complexity analysis shows that an increase in the classifying quality is always accompanied by a significant increase of computational complexity.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2012

Number of the records: 1