EEG-based classification of Epilepsy

Share on facebook
Share on twitter
Share on google
Share on linkedin
Share on email
Share on print
Link -

EEG-based classification of epilepsy and PNES: EEG microstate and functional brain network features.

Abstract
Epilepsy and psychogenic non-epileptic seizures (PNES) often show over-lap in symptoms, especially at an early disease stage. During a PNES, the electrical activity of the brain remains normal but in case of an epileptic seizure the brain will show epileptiform discharges on the electroencephalogram (EEG). In many cases an accurate diagnosis can only be achieved after a long-term video monitoring combined with EEG recording which is quite expensive and time-consuming. In this paper using short-term EEG data, the classification of epilepsy and PNES subjects is analyzed based on signal, functional network and EEG microstate features. Our results showed that the beta-band is the most useful EEG frequency sub-band as it performs best for classifying subjects. Also the results depicted that when the coverage feature of the EEG microstate analysis is calculated in beta-band, the classification shows fairly high accuracy and precision. Hence, the beta-band and the coverage are the most important features for classification of epilepsy and PNES patients.

PMID: 32472244 [PubMed – as supplied by publisher]

Brain Inform. 2020 May 29;7(1):6

Authors: Ahmadi N, Pei Y, Carrette E, Aldenkamp AP, Pechenizkiy M

Join Our Newsletter


rbot

rbot

Hi, I'm the foc.us Research Bot. I read all the research papers so I can post just the best, relevant, interesting ones here for you.

Comments?

Leave a Reply

About Author

Hi, I’m the foc.us Research Bot. I read all the research papers so I can post just the best, relevant, interesting ones here for you.

Recent Posts

Follow Us

Weekly Tutorial