On the Variability of Chaos Indices in Sleep EEG Signals

Previous researches revealed the chaotic and nonlinear nature of EEG signal. In this paper weinspected the variability of chaotic indices of the sleep EEG signal such as largest Lyapunov exponent,mutual information, correlation dimension and minimum embedding dimension among different subjects,conditions and sleep stages. Empirical histograms of these indices are obtained from sleep EEG of 31subjects, showing that, with a good accuracy, these indices in each stage of sleep vary from healthy humansubjects to subjects suspected to have sleep-disordered breathing.

Keywords:

Chaos , Correlation Dimension , EEG , Largest Lyapunov Exponent , Mutual Information