EEG signal classification using frequency band analysis towards epileptic seizure prediction

Manoranjan Paul, Mohammad Parvez

Research output: Book chapter/Published conference paperConference paper

8 Citations (Scopus)

Abstract

Epilepsy is one of the most common and diverse set of chronic neurological disorders characterized by an abnormal excessive or synchronous neuronal activity in the brain that is termed 'seizure' affecting about 50 million individuals worldwide. Electroencephalogram (EEG) signal processing technique plays a significant role in detection and prediction of epileptic seizure. Recently, many research works have been devoted to detect/predict of epileptic seizure based on analysis of EEG signals. Even though remarkable works have been conducted on seizure detection/prediction, experimental results are not mature enough in terms of sensitivity, specificity, and accuracy. In this paper we present a new approach for seizure detection to analysis preictal (before seizure onset) and interictal (period between seizures) EEG signals by extracting different features from gamma frequency band by decomposing the signals using discrete wavelet transformation. Note that the detection of preictal and interictal EEG signals leads to predict the epileptic seizure. Experimental results demonstrate that the propose method outperforms the state-of-the-art method in terms of sensitivity, specificity and accuracy to classify seizure by analyzing EEG signals to the benchmark dataset in different brain locations.
Original languageEnglish
Title of host publicationProceedings of the 16th International Conference on Computer and Information Technology
Subtitle of host publicationICCIT 2013
EditorsRameswar Debnath
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages126-130
Number of pages5
ISBN (Electronic)9781479934980
Publication statusPublished - 2014
Event16th International Conference on Computer and Information Technology: ICCIT 2013 - Khulna University, Khulna, Bangladesh
Duration: 08 Mar 201410 Mar 2014
https://web.archive.org/web/20130409043745/http://www.iccit.org.bd/2013/

Conference

Conference16th International Conference on Computer and Information Technology
CountryBangladesh
CityKhulna
Period08/03/1410/03/14
Internet address

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  • Cite this

    Paul, M., & Parvez, M. (2014). EEG signal classification using frequency band analysis towards epileptic seizure prediction. In R. Debnath (Ed.), Proceedings of the 16th International Conference on Computer and Information Technology: ICCIT 2013 (pp. 126-130). IEEE, Institute of Electrical and Electronics Engineers. http://ieeexplore.ieee.org/document/6997315/