Time–frequency based newborn EEG seizure detection using low and high frequency signatures.
Hamid Hassanpour, Mostefa Mesbah and Boualem Boashash
Laboratory of Signal Processing Research, Queensland University of Technology,
GPO Box 2434, Brisbane, QLD 4001, Australia
Received 8 January 2004, accepted for publication 28 June 2004
Published 22 July 2004
Online at stacks.iop.org/PM/25/935
doi:10.1088/0967-3334/25/4/012
Abstract
The nonstationary and multicomponent nature of newborn EEG seizures tend
to increase the complexity of the seizure detection problem. In dealingwith this
type of problem, time–frequency based techniques were shown to outperform
classical techniques. Neonatal EEG seizures have signatures in both low
frequency (lower than 10 Hz) and high frequency (higher than 70 Hz) areas.
Seizure detection techniques have been proposed that concentrate on either
low frequency or high frequency signatures of seizures. They, however, tend
to miss seizures that reveal themselves only in one of the frequency areas.
To overcome this problem, we propose a detection method that uses time–
frequency seizure features extracted from both low and high frequency areas.
Results of applying the proposed method on five newborn EEGs are very
encouraging.
Keywords: EEG seizure detection, spike detection, time–frequency, singular
vector
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