Automatic Detection Of Seizure Activity From EEG Recordings Of Genetic Rat Model Of Absence Epilepsy

Abstract

Spike-and-wave discharge is a phenomenon that occurs during absence epilepsy. The detection of these wave-forms can provide an important tool for the different aspects of epilepsy. However, the manual detection of these seizures is not simple as it can take hours to be detected. In this study, we developed a promising tool to detect the spike and wave discharges automatically from a recorded EEG signal depending on the amplitude characteristics and frequency spectrum. The results are promising as the false and missed detection rates are less than 3%, whereas the time overlap between the manually and automatically detected wave-forms is greater than 96%.