Epileptic source localization using high frequency interictal EEG signals

The records of scalp electroencephalogram (EEG) give many features of the epileptic region and its functionality. The process records using independent component analysis (ICA) will give enough information to the epileptologist, to go ahead with further investigation and decision for surgery. This paper presents the analysis of interictal high frequency events of a subject of Warsaw Memorial Child Hospital, Poland. Twenty interictal events of the patient was analyzed. For the cases analyzed, the focus had a standard deviation of 11.55%. K-mean clustering algorithm was used to classify the various interictal activities. The classification shows active centers at right frontal and right temporal regions. In addition to which the activities were seen at the motor regions corresponding to the right fist and left fist movements. The results match with the medical findings and pre-surgical evidences like Magnetic Resonance Imaging (MRI) and clinical history of the patient. The locations computed from the high frequency emissions have a good spatial and temporal resolution.