A treatment of EEG data by underdetermined blind source separation for motor imagery classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F12%3A00380079" target="_blank" >RIV/67985556:_____/12:00380079 - isvavai.cz</a>
Alternative codes found
RIV/46747885:24220/12:#0002020
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
A treatment of EEG data by underdetermined blind source separation for motor imagery classification
Original language description
Brain-Computer Interfaces (BCI) controlled through imagined movements cannot work properly without a correct classification of EEG signals. The difficulty of this problem consists in low signal-to-noise ratio, because EEG may contain strong signal components that are not related to motor imagery. In this paper, these artifact components are to be suppressed using a recently proposed underdetermined blind source separation method and a novel MMSE beamformer. We use these tools to remove unwanted components of EEG to increase the classification accuracy of the BCI system. In our experiments with several datasets, the classification is improved by up to 10%.
Czech name
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Czech description
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Project
<a href="/en/project/GAP103%2F11%2F1947" target="_blank" >GAP103/11/1947: Methods of Latent Variable Analysis in Blind Speech and Audio Processing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
20th European Signal Processing Conference (EUSIPCO 2012)
ISBN
978-1-4673-1068-0
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
1484-1488
Publisher name
EURASIP
Place of publication
Bucharest
Event location
Bukurešť
Event date
Aug 27, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000310623800298

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