Open AccessThe State of the Art in Feature Extraction Methods for EEG Classification
Author(s) -
Mokhtar Mohammad,
Hoger Mahmud Hussen
Publication year - 2019
Publication title -
uhd journal of science and technology
Language(s) - English
Resource type - Journals
eISSN - 2521-4217
pISSN - 2521-4209
DOI - 10.21928/uhdjst.v3n2y2019.pp16-23
Subject(s) - electroencephalography , epileptic seizure , epilepsy , neuroscience , feature (linguistics) , feature extraction , computer science , pattern recognition (psychology) , psychology , artificial intelligence , medicine , linguistics , philosophy
Epileptic seizure is a neurological disease that is common around the world and there are many types (e.g. Focal aware seizures and atonic seizure) that are caused by synchronous or abnormal neuronal activity in the brain. A number of techniques are available to detect the brain activities that lead to Epileptic seizures; one of the most common one is Electroencephalogram (EEG) that uses visual scanning to measure brain activities generated by nerve cells in the cerebral cortex. The techniques make use of different features detected by EEG to decide on the occurrence and type of seizures. In this paper we review EEG features proposed by different researches for the purpose of Epileptic seizure detection, also analyze, and compare the performance of the proposed features.