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Comparison of four classification methods for brain-computer interface
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SYSNO ASEP 0359738 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Comparison of four classification methods for brain-computer interface Tvůrce(i) Frolov, A. (RU)
Húsek, Dušan (UIVT-O) RID, SAI, ORCID
Bobrov, P. (RU)Zdroj.dok. Neural Network World. - : Ústav informatiky AV ČR, v. v. i. - ISSN 1210-0552
Roč. 21, č. 2 (2011), s. 101-115Poč.str. 15 s. Jazyk dok. eng - angličtina Země vyd. CZ - Česká republika Klíč. slova brain computer interface ; motor imagery ; visual imagery ; EEG pattern classification ; Bayesian classification ; Common Spatial Patterns ; Common Tensor Discriminant Analysis Vědní obor RIV IN - Informatika CEP 1M0567 GA MŠMT - Ministerstvo školství, mládeže a tělovýchovy GA201/05/0079 GA ČR - Grantová agentura ČR GAP202/10/0262 GA ČR - Grantová agentura ČR CEZ AV0Z10300504 - UIVT-O (2005-2011) UT WOS 000290838300001 EID SCOPUS 79957872178 DOI 10.14311/NNW.2011.21.007 Anotace 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. Pracoviště Ústav informatiky Kontakt Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Rok sběru 2012
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