Chaocity and Dimensional Complexity of Eeg-signal
نویسندگان
چکیده
We tested for nonlinearity 16-channels EEG-data of 21 healthy human subjects by surrogate data method using S-map forecasting as a discriminant statistics, showing that in most cases one may not reject the null hypothesis that the signal was generated by a linear stochastic process. We also demonstrated that fractal dimension of EEG-signal in time domain works as a relative index of signal’s dimensional complexity and may be useful for doctors, e.g. in semi-automatic differentiation of sleep stages.
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