Nonlinear Dynamical Aspects of the Human Sleep EEG

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Abstract
This article deals with the application of methods from the theory of nonlinear dynamical systems to EEG signals. Theoretical background, mathematical concepts and algorithms for the calculation of “nonlinear parameters” are reviewed and influences of the structure of reconstructed data sets on the calculations are pointed out. We present results for the estimation of the correlation dimension D2 and the principal Lyapunov-exponent λ1 for sleep EEG data respectively from 10 and 15 healthy subjects corresponding to different sleep stages. Essentially, we found a statistically significant decrease of both D2 and λ1 as sleep moves towards slow wave stages. The values for REM sleep lie between the values for stage I and II. Moreover, for one subject as an example we present calculations of the principal Lyapunov-exponent λ1 and the sum of the two largest Lyapunov-exponents λ1 + λ2 for EEG segments following subsequently during the night. Finally, we compare our results with investigations of other groups and discuss difficulties and opportunities of the nonlinear approach to human EEG signals.

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