Abstract
The automated detection of seizures in EEG is significant for epilepsy monitoring, diagnosis and rehabilitation. In this work, we evaluated the differences between epileptic EEG, interictal EEG and normal EEG by computing their Higuchi Fractal Dimension (HFD) and Approximate Entropy (ApEn). The calculated results show that there are significant differences between epileptic EEG and normal EEG in the variations of HFD and ApEn. HFD and ApEn have been shown to be useful to characterize normal and epileptic brain electrical activities, and the degree of complexity of epileptic EEG is lower than that of normal EEG even during interictal time. Our results could be helpful for interpreting the epileptic brain electrical activity and the normal brain electrical activity, and their neurodynamics.
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