Abstract
Epilepsy is a neurological disorder characterized by the sudden abnormal discharging of brain neurons that can lead to encephalographic (EEG) abnormalities. In this study, data was obtained from epileptic patients with intracranial depth electrodes and analyzed using wavelet entropy algorithms in order to locate the epileptic foci. Significant increases in the wavelet entropy of the epileptic signals were identified during multiple episodes of clinical seizures. The results indicated that the algorithm was capable of identifying entropy changes in the epileptic sources. Furthermore, the correlations among the electrocorticogram (ECoG) signals of different channels determined using the amplitude-amplitude coupling method verified that the epileptic foci exhibited significantly higher coupling strengths. Thus, cross frequency coupling (CFC) could be an inspiration to energy and signal transitive mode of seizure and, thereby, improve diagnostic processes.