Fluctuation dynamics in electroencephalogram time series

Authors:
In-Ho Song;Doo-Soo Lee
Affiliations:
Department of Electrical and Computer Engineering, Hanyang University, Seoul, Korea;Department of Electrical and Computer Engineering, Hanyang University, Seoul, Korea
Venue:
IWINAC'05 Proceedings of the First international conference on Mechanisms, Symbols, and Models Underlying Cognition: interplay between natural and artificial computation - Volume Part I
Year:
2005

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Abstract

We investigated the characterization of the complexity of electroencephalogram (EEG) fluctuations by monofractals and multifractals. We used EEG time series taken from normal, healthy subjects with their eyes open and their eyes closed, and from patients during epileptic seizures. Our findings showed that the fluctuation dynamics in EEGs could be adequately described by a set of scales, and characterized by multifractals, in both healthy and pathologic conditions. Multifractal formalism based on the wavelet transform modulus maxima (WTMM) appears to be a good method for characterizing EEG dynamics.