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Classification of Epileptic & Non Epileptic EEG Signal Using Matlab

Authors(2) :-Sanat Kumar, Dinesh Kumar Atal

Epilepsy is a typical incessant neurological issue. Epilepsy seizures are the consequence of the transient and surprising electrical aggravation of the cerebrum. Around 50 million individuals worldwide have epilepsy, and about two out of each three new cases are found in creating nations. Epilepsy will probably happen in youthful youngsters or individuals beyond 65 years old years; nonetheless, it can happen at any age. The identification of epilepsy is conceivable by investigating EEG signals. In this paper we are using a technique to classify normal & epileptic EEG signal using k-means clustering algorithm in MATLAB. Further the SVM & Discriminant classifier in MATLAB Machine learning toolbox is used to classify the epileptic and normal EEG signal & wavelet transform is used to process the EEG signal. After the implementation of the signals there is ~70% accuracy with SVM classifier and ~93% accuracy with discriminant classifier.
Sanat Kumar, Dinesh Kumar Atal
Epilepsy seizures, SVM Classifier, MATLAB, k-means clustering, wavelet transform, Discriminant Classifier.
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Publication Details
  Published in : Volume 2 | Issue 4 | July-August 2016
  Date of Publication : 2016-08-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 203-207
Manuscript Number : IJSRST162449
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
Sanat Kumar, Dinesh Kumar Atal, "Classification of Epileptic & Non Epileptic EEG Signal Using Matlab ", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 2, Issue 4, pp.203-207 , July-August-2016
URL : http://ijsrst.com/IJSRST162449