• DocumentCode
    3039798
  • Title

    7.6: Presentation session: Poster session and reception: “Seizure prediction: One step closer. Graphical user interface for fast EEG review and statistical validation of PSDM”

  • Author

    Hofmeister, Lucas H.

  • Author_Institution
    Capstone Design, Biomedical Engineering, University of Tennessee Knoxville
  • fYear
    2010
  • fDate
    25-26 May 2010
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    Epilepsy is one of the most widely occurring and costly neurological disorders. The CDC has named developing a prediction method for seizures as its top priority in epileptic research because the unpredictability of seizures causes immense psychological stress on persons with lifetime epilepsy. In order to reduce these stresses, Hively et al have designed an algorithm to provide forewarning of epileptic events from scalp EEG data. To help in the development of this algorithm for clinical application, we have designed a graphical user interface (GUI) to allow experts to rapidly characterize electroencephalogram (EEG) datasets to be used to train the forewarning algorithm. We have also performed a statistical validation of the forewarning results to date. Both of these aspects of this project contribute to the overall goal of realizing reliable seizure prediction for people with epilepsy
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Sciences and Engineering Conference (BSEC), 2010
  • Conference_Location
    Oak Ridge, TN, USA
  • Print_ISBN
    978-1-4244-6713-6
  • Electronic_ISBN
    978-1-4244-6714-3
  • Type

    conf

  • DOI
    10.1109/BSEC.2010.5510819
  • Filename
    5510819