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
fDate :
5/1/2011 12:00:00 AM
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"
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Print_ISBN :
978-1-4577-0538-0
Electronic_ISBN :
2379-190X
DOI :
10.1109/ICASSP.2011.5946487