Multiscale characteristics of human sleep EEG time series

Authors:
In-Ho Song;In-Young Kim;Doo-Soo Lee;Sun I. Kim
Affiliations:
Department of Electrical and Computer Engineering, Hanyang University, Seoul, South Korea;Department of Biomedical Engineering, College of Medicine, Hanyang University, Seoul, South Korea;Department of Electrical and Computer Engineering, Hanyang University, Seoul, South Korea;Department of Biomedical Engineering, College of Medicine, Hanyang University, Seoul, South Korea
Venue:
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
Year:
2006

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Abstract

We investigated the complexity of fluctuations in human sleep electroencephalograms (EEGs) by multifractals. We used human sleep EEG time series taken from normal, healthy subjects during the four stages of sleep and rapid eye movement (REM) sleep. Our findings showed that the fluctuation dynamics in human sleep EEGs could be adequately described by a set of scales and characterized by multifractals. Multifractal formalism, based on the wavelet transform modulus maxima, appears to be a good method for characterizing EEG dynamics.