• DocumentCode
    3020249
  • Title

    Epilepsy detection using Detrended Fluctuation Analysis

  • Author

    Shalbaf, Reza ; Hosseini, Pegah Tayaranian ; Analoui, Morteza

  • Author_Institution
    Dept. of Electr. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    235
  • Lastpage
    240
  • Abstract
    Epilepsy is a disorder of the central nervous system characterized by the loss of consciousness and convulsions. If some early warning signal of an upcoming seizure (diagnosis of preictal period) could be detected, proper treatment could be applied to the patient to help prevent the seizure. In this articles, detrended fluctuation analysis (DFA) has been introduced and used to extract the DFA feature from EEG signal. DFA is a scaling analysis method that provides a simple quantitative parameter to represent the correlation properties of a signal, we come to 100% separation of Normal, Preictal, and Ictal states of the brain.
  • Keywords
    electroencephalography; medical signal detection; patient treatment; EEG signal; brain; central nervous system disorder; detrended fluctuation analysis; epilepsy detection; patient treatment; quantitative parameter; scaling analysis method; signal detection; Epilepsy; Fluctuations; Pattern analysis; Pattern recognition; Wavelet analysis; Detrended fluctuation analysis; linear discriminant analysis; seizure detection; standard deviation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition, 2009. ICWAPR 2009. International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3728-3
  • Electronic_ISBN
    978-1-4244-3729-0
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2009.5207454
  • Filename
    5207454