Time-frequency analysis of EEG asymmetry using bivariate empirical mode decomposition

C. Park, D. Looney, P. Kidmose, Michael Ungstrup, D.P. Mandic

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    81 Citationer (Scopus)

    Abstract

    A novel method is introduced to determine asymmetry, the lateralization of brain activity, using extension of the algorithm empirical mode decomposition (EMD). The localized and adaptive nature of EMD make it highly suitable for estimating amplitude information across frequency for nonlinear and nonstationary data. Analysis illustrates how bivariate extension of EMD (BEMD) facilitates enhanced spectrum estimation for multichannel recordings that contain similar signal components, a realistic assumption in electroencephalography (EEG). It is shown how this property can be used to obtain a more accurate estimate of the marginalized spectrum, critical for the localized calculation of amplitude asymmetry in frequency. Simulations on synthetic data sets and feature estimation for a brain-computer interface (BCI) application are used to validate the proposed asymmetry estimation methodology.
    OriginalsprogEngelsk
    TidsskriftI E E E Transactions on Neural Systems and Rehabilitation Engineering
    Vol/bind19
    Nummer4
    Sider (fra-til)366-373
    Antal sider8
    ISSN1534-4320
    DOI
    StatusUdgivet - 1 aug. 2011

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