Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/83569
Title: Complex dynamics of epileptic EEG
Authors: Kannathal, N.
Puthusserypady, S.K. 
Min, L.C.
Keywords: Correlation dimension
Fractal dimension
Hurst exponent
Kalmogorov entropy
Largest Lyapunov exponent
Issue Date: 2004
Source: Kannathal, N.,Puthusserypady, S.K.,Min, L.C. (2004). Complex dynamics of epileptic EEG. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings 26 I : 604-607. ScholarBank@NUS Repository.
Abstract: Electroencephalogram (EEG) - the recorded representation of electrical activity of the brain contain useful information about the state of the brain. Recent studies indicate that nonlinear methods can extract valuable information from neuronal dynamics. In this work, we compare the dynamical properties of EEG signals of healthy subjects with epileptic subjects using nonlinear time series analysis techniques. Chaotic invariants like correlation dimension (D2), largest Lyapunov exponent (λ1), Hurst exponent (H) and Kolmogorov entropy (K) are used to characterize the signal. Our study showed clear differences in dynamical properties of brain electrical activity of the normal and epileptic subjects with a confidence level of more than 90%. Furthermore to support this claim fractal dimension (FD) analysis is performed. The results indicate reduction in value of FD for epileptic EEG indicating reduction in system complexity.
Source Title: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/83569
ISSN: 05891019
Appears in Collections:Staff Publications

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