Počet záznamů: 1  

Classification of brain activities during language and music perception

  1. 1.
    SYSNO ASEP0533472
    Druh ASEPJ - Článek v odborném periodiku
    Zařazení RIVZáznam nebyl označen do RIV
    Poddruh JČlánek ve WOS
    NázevClassification of brain activities during language and music perception
    Tvůrce(i) Besedová, P. (CZ)
    Vyšata, O. (CZ)
    Mazurová, R. (CZ)
    Kopal, Jakub (UIVT-O) RID, ORCID, SAI
    Ondráková, J. (CZ)
    Vališ, M. (CZ)
    Procházka, A. (CZ)
    Zdroj.dok.Signal Image and Video Processing - ISSN 1863-1703
    Roč. 13, č. 8 (2019), s. 1559-1567
    Jazyk dok.eng - angličtina
    Země vyd.GB - Velká Británie
    Klíč. slovaeeg ; speech ; plasticity ; benefits ; behavior ; signal ; time ; Multichannel signal analysis ; Computational intelligence ; Cognitive science ; Linguistics ; Machine learning
    UT WOS000509671800011
    EID SCOPUS85067257869
    DOI10.1007/s11760-019-01505-5
    AnotaceAnalysis of brain activities in language perception for individuals with different musical backgrounds can be based upon the study of multichannel electroencephalograhy (EEG) signals acquired in different external conditions. The present paper is devoted to the study of the relationship of mental processes and the perception of external stimuli related to the previous musical education. The experimental set under study included 38 individuals who were observed during perception of music and during listening to foreign languages in four stages, each of which was 5 min long. The proposed methodology is based on the application of digital signal processing methods, signal filtering, statistical methods for signal segment selection and active electrode detection. Neural networks and support vector machine (SVM) models are then used to classify the selected groups of linguists to groups with and without a previous musical education. Our results include mean classification accuracies of 82.9% and 82.4% (with the mean cross-validation errors of 0.21 and 0.22, respectively) for perception of language or music and features based upon EEG power in the beta and gamma EEG frequency bands using neural network and SVM classification models.
    PracovištěÚstav informatiky
    KontaktTereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
    Rok sběru2021
Počet záznamů: 1  

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