Abstract
By analyzing electroencephalograms taken from healthy subjects and epilepsy patients, we investigated whether the complexity of the electroencephalogram (EEG) could be characterized by a multifractal. Our results showed that the EEGs from the two sets exhibit higher complexity than monofractal 1/f scaling. A significant finding was the observation that the dynamics of the epileptic EEGs exhibited anticorrelated, correlated, and uncorrelated behaviors. In conclusion, multifractal formalism based on the wavelet transform modulus maxima (WTMM) may be a good tool to characterize the various dynamics of the two sets.
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Song, IH., Lee, SM., Kim, IY., Lee, DS., Kim, S.I. (2005). Mutifractal Analysis of Electroencephalogram Time Series in Humans. In: Cabestany, J., Prieto, A., Sandoval, F. (eds) Computational Intelligence and Bioinspired Systems. IWANN 2005. Lecture Notes in Computer Science, vol 3512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11494669_113
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DOI: https://doi.org/10.1007/11494669_113
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26208-4
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