• DocumentCode
    3642114
  • Title

    Neonatal seizure detection using blind multichannel information fusion

  • Author

    Huaying Li;Aleksandar Jeremić

  • Author_Institution
    Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
  • fYear
    2011
  • fDate
    5/1/2011 12:00:00 AM
  • Firstpage
    649
  • Lastpage
    652
  • Abstract
    Seizure is the result of excessive electrical discharges of neurons, which usually develops synchronously and happens suddenly in the central nervous system. Clinically, it is difficult for physician to identify neonatal seizures visually, while EEG seizures can be recognized by the trained experts. By extending our previous results on multichannel information fusion, we propose an automated distributed detection system consisting of the existing detectors and a fusion center to detect the seizure activities in the newborn EEG. The advantage of this proposed technique is that it does not require any priori knowledge of the hypotheses and the detector performances, which are often unknown in real applications. Therefore, this proposed technique has the potential to improve the performances of the existing neonatal seizure detectors.
  • Keywords
    "Detectors","Electroencephalography","Pediatrics","Error probability","Algorithm design and analysis","Maximum likelihood estimation","Discharges"
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4577-0538-0
  • Electronic_ISBN
    2379-190X
  • Type

    conf

  • DOI
    10.1109/ICASSP.2011.5946487
  • Filename
    5946487