DocumentCode :
2480339
Title :
EEG seizure identification by using optimized wavelet decomposition
Author :
Pinzon-Morales, RD ; Orozco-Gutierrez, A. ; Castellanos-Dominguez, G.
Author_Institution :
Univ. Tecnol. de Pereira, Pereira, Colombia
fYear :
2011
fDate :
Aug. 30 2011-Sept. 3 2011
Firstpage :
2675
Lastpage :
2678
Abstract :
A methodology for wavelet synthesis based on lifting scheme and genetic algorithms is presented. Often, the wavelet synthesis is addressed to solve the problem of choosing properly a wavelet function from an existing library, but which may be not specially designed to the application in hand. The task under consideration is the identification of epileptic seizures over electroencephalogram recordings. Although basic classifiers are employed, results rendered that the proposed methodology is successful in the considered study achieving similar classification rates that had been reported in literature.
Keywords :
electroencephalography; genetic algorithms; medical signal processing; wavelet transforms; EEG seizure identification; electroencephalogram recordings; epileptic seizures; genetic algorithm; lifting scheme; optimized wavelet decomposition; wavelet synthesis; Electroencephalography; Feature extraction; Optimization; Principal component analysis; Vectors; Wavelet transforms; Electroencephalography; Humans; Seizures;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2011.6090735
Filename :
6090735
Link To Document :
بازگشت