DocumentCode
650026
Title
Detection of absence epileptic seizures using support vector machine
Author
Reyes, C.F. ; Contreras, T.J. ; Tovar, Blanca ; Garay, L.I. ; Silva, Mario A.
Author_Institution
Maestria en Tecnol. Av., UPIITA, Mexico City, Mexico
fYear
2013
fDate
Sept. 30 2013-Oct. 4 2013
Firstpage
132
Lastpage
137
Abstract
An application of support vector machine is presented as a tool for events detection in the electroencephalogram recorded from a patient clinically diagnosed with absence epilepsy. A comparison of five kernels is shown (linear, quadratic, polynomial, RBP and MLP) evaluating their efficiency for the detection of this epileptic event occurrence. The kernel with the best performance is the quadratic, with 99.43% accuracy in this specific case.
Keywords
electroencephalography; patient diagnosis; MLP; RBP; absence epilepsy; absence epileptic seizures; electroencephalogram; epileptic event occurrence; events detection; linear kernel; patient diagnosis; polynomial kernel; quadratic kernel; support vector machine; EEG; SVM; epilepsy; kernels;
fLanguage
English
Publisher
ieee
Conference_Titel
Electrical Engineering, Computing Science and Automatic Control (CCE), 2013 10th International Conference on
Conference_Location
Mexico City
Print_ISBN
978-1-4799-1460-9
Type
conf
DOI
10.1109/ICEEE.2013.6676057
Filename
6676057
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