Assessing entropy and fractal dimensions as discriminants of seizures in EEG time series

In this paper, the performance of Higuichi´s algorithm for calculation of fractal dimension, Hurst exponents, and Shannon Entropy as discriminants for the detection of epileptic seizures in EEG signals are assessed. The proposed methods were applied to intracranial EEG recordings from epilepsy patients during the seizure free interval from within and from outside the seizure generating area as well as intracranial EEG recordings during epileptic seizures. Analysis was conducted using statistical hypothesis testing to determine the validity of the proposed seizure-identifying techniques.