• 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