Počet záznamů: 1  

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

  1. 1.
    0380079 - ÚTIA 2013 RIV RO eng C - Konferenční příspěvek (zahraniční konf.)
    Koldovský, Zbyněk - Phan, A. H. - Tichavský, Petr - Cichocki, A.
    A treatment of EEG data by underdetermined blind source separation for motor imagery classification.
    20th European Signal Processing Conference (EUSIPCO 2012). Bucharest: EURASIP, 2012, s. 1484-1488. ISBN 978-1-4673-1068-0. ISSN 2076-1465.
    [20th European Signal Processing Conference (EUSIPCO 2012). Bukurešť (RO), 27.08.2012-31.08.2012]
    Grant ostatní: GA ČR(CZ) GAP103/11/1947
    Program: GA
    Institucionální podpora: RVO:67985556
    Klíčová slova: electroencephalogram * brain-computer Interface * underdetermined blind source separation
    Kód oboru RIV: FH - Neurologie, neurochirurgie, neurovědy
    http://library.utia.cas.cz/separaty/2012/SI/tichavsky-a treatment of eeg data by underdetermined blind source separation for motor imagery classification.pdf

    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%.
    Trvalý link: http://hdl.handle.net/11104/0210892

     
     
Počet záznamů: 1  

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