• DocumentCode
    1995544
  • Title

    Automatic detection of epileptiform discharges in EEG using a back-propagation network

  • Author

    Xie, Feng ; Yan, Zhuangzhi ; Liu, Shupeng

  • Author_Institution
    Dept. of Biomed. Eng., Shanghai Univ., China
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1781
  • Abstract
    This paper presents an automatic approach to detect epileptiform discharges (ED) in electroencephalogram (EEG). On the algorithm we utilized back-propagation artificial neural network (BPN) to detect ED. We train BPN respectively for each patient and induce parameter k to determine a threshold value. The result shows that the algorithm can determine presence or absence of ED automatically, and decrease the false determination in current automated approaches as well.
  • Keywords
    backpropagation; electroencephalography; medical signal processing; neural nets; pattern classification; signal classification; EEG; automatic detection; backpropagation neural network; cross recognition method; epileptiform discharges; output peak value distribution curve; power function curve; threshold value; Artificial neural networks; Biomedical engineering; Detection algorithms; Electroencephalography; Electronic mail; Epilepsy; Frequency; Intelligent networks; Pattern recognition; Scalp;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Print_ISBN
    0-7803-7211-5
  • Type

    conf

  • DOI
    10.1109/IEMBS.2001.1020565
  • Filename
    1020565