Feature Selection and Fuzzy Rule Mining for Epileptic Patients from Clinical EEG Data

摘要

In this paper, we create EEG data derived signatures for differentiating epileptic patients from normal individuals. Epilepsy is a neurological condition of human beings, mostly treated based on a patient's seizure symptoms. Clinicians face immense difficulty in detecting epileptic patients. Here we define brain region-connection based signatures from EEG data with help of various machine learning techniques. These signatures will help the clinicians in detecting epileptic patients in general. Moreover, we define separate signatures by taking into account a few demographic features like gender and age. Such signatures may aid the clinicians along with the generalized epileptic signature in case of complex decisions.