Discriminating preictal and interictal brain states in intracranial EEG by sample entropy and extreme learning machine.
Journal:
Journal of neuroscience methods
Published Date:
Aug 31, 2015
Abstract
BACKGROUND: Epilepsy is one of the most common neurological disorders approximately one in every 100 people worldwide are suffering from it. Uncontrolled epilepsy poses a significant burden to society due to associated healthcare cost to treat and control the unpredictable and spontaneous occurrence of seizures. The objective of this research is to develop and present a novel classification framework that is utilised to discriminate interictal and preictal brain activities via quantitative analysis of electroencephalogram (EEG) recordings.