• DocumentCode
    573207
  • Title

    Calibration of time features and frequency features in the time-frequency domain for improved detection and classification of seizure in newborn EEG signals

  • Author

    Bahnasy, Yomna ; Saad, Noha ; Boubchir, Larbi ; Boashash, Boualem

  • Author_Institution
    Electr. Eng. Dept., Qatar Univ., Doha, Qatar
  • fYear
    2012
  • fDate
    2-5 July 2012
  • Firstpage
    1442
  • Lastpage
    1443
  • Abstract
    This paper presents new time-frequency features for seizure detection in newborn EEG signals. These features are obtained by calibrating relevant time features and frequency features in the joint time-frequency domain. The proposed features allow the possibility of improving the performance of the seizure detection and classification system based on multi-class SVM classifier.
  • Keywords
    diseases; electroencephalography; medical signal processing; signal classification; support vector machines; time-frequency analysis; calibration; classification system; improved detection; multiclass SVM classifier; newborn EEG signals; seizure detection; time features; time-frequency domain; time-frequency features; Calibration; Electroencephalography; Feature extraction; Joints; Pediatrics; Time frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science, Signal Processing and their Applications (ISSPA), 2012 11th International Conference on
  • Conference_Location
    Montreal, QC
  • Print_ISBN
    978-1-4673-0381-1
  • Electronic_ISBN
    978-1-4673-0380-4
  • Type

    conf

  • DOI
    10.1109/ISSPA.2012.6310531
  • Filename
    6310531