Seizure detection via Empirical Mode Decomposition

Epilepsy is a neurological disorder that affects a serious number of people all around the world. Detection of epileptic seizures using EEG signals occupies an important part in the diagnosis of epilepsy. The aim of this study is to develop a method for seizure detection based on Empirical Mode Decomposition. In this method, EEG signals are decomposed to their Intrinsic Mode Functions and first 4 IMFs's maximum, minimum, mean, standart deviation and energy values are used for classification. This method was tested on 123 minutes of iktal data and 200 minutes of inter-iktal data using 3 different classifiers. For all clasifiers, over %80 sensitivity and over %95 specificity were otained. These results show that epileptic seizure detection in EEG records via EMD is very promising.