A Wavelet Based Approach for the Detection of Coupling in EEG Signals

TitleA Wavelet Based Approach for the Detection of Coupling in EEG Signals
Publication TypeConference Paper
Year of Publication2005
AuthorsSaab, R., M. J. McKeown, L. J. Myers, and R. Abu-Gharbieh
Conference NameNeural Engineering, 2005. Conference Proceedings. 2nd International IEEE EMBS Conference on
Pagination616 -620
Date Publishedmar.
Keywordsbrainwave activity, Cognition, cognitive processing, coupling detection, electroencephalograms, electroencephalography, Fourier based coherence, medical signal detection, medical signal processing, motor processing, nonstationary EEG signals, single time-frequency coherence map, time-frequency analysis, wavelet based approach, wavelet coherence, wavelet transforms

Electroencephalograms (EEGs) provide a noninvasive way of measuring brainwave activity from sensors placed on the scalp. In this paper we present an approach to measure coupling, or synchrony, between various parts of the brain, critical for motor and cognitive processing, using wavelet coherence of EEG signals. We provide an argument, highlighting the benefits of using this approach as opposed to the regular Fourier based coherence, in the context of localizing short significant bursts of coherence between non-stationary EEG signals, to which regular coherence is insensitive. We further highlight the benefits of the wavelets approach by exploring how a single time-frequency coherence map can be controlled to yield various time and/or frequency resolutions


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