A new dissimilarity index of EEG signals for epileptic seizure detection

Epileptic seizures are generated by an abnormal synchronization of neurons. Since epileptic seizures are unforeseeable for the patients, epileptic seizures detection is an interesting issue in epileptology, that novel approaches to understand the mechanism of epileptic seizures. In this study we analyzed invasive electroencephalogram (EEG) recordings in patients suffering from medically intractable focal epilepsy with a nonlinear method called, dissimilarity index. In order to detect epileptic seizures Bhattacharyya distance between trajectory matrix of reference window during an interval quite distant in time from any seizure and trajectory matrix of present window is employed to measure dynamical dissimilarity index. The data were recorded during an invasive pre-surgical epilepsy monitoring at the “Epilepsy Center of the University Hospital of Freiburg”, Germany. Results show a significant increase in Bhattacharyya distance values between trajectory matrix of reference window and trajectory matrix of present window during seizure. Our results suggest that this technique is useful to detect changes due to epileptic seizures in the EEG.