A time-frequency approach for newborn seizure detection

Boashash, Boualem and Mesbah, Mostefa (2001) A time-frequency approach for newborn seizure detection. IEEE Engineering in Medicine and Biology Magazine, 20 5: 54-64. doi:10.1109/51.956820

Author Boashash, Boualem
Mesbah, Mostefa
Title A time-frequency approach for newborn seizure detection
Journal name IEEE Engineering in Medicine and Biology Magazine
ISSN 0278-0054
Publication date 2001-09
Sub-type Article (original research)
DOI 10.1109/51.956820
Volume 20
Issue 5
Start page 54
End page 64
Total pages 11
Place of publication New York
Publisher IEEE
Language eng
Subject 290903 Other Electronic Engineering
090609 Signal Processing
Abstract Techniques previously designed for seizure detection in newborns using the electroencephalogram (EEG) have been relatively inefficient due to their assumption of local stationarity of the EEG. To overcome the problem raised by the nonstationarity of the EEG signal, current methods are extended to a time-frequency approach. This allows the analysis and characterization of the different newborn EEG patterns that are intended to be the first step toward an automatic time-frequency seizure detection and classification. An in-depth analysis of both the autocorrelation and spectrum seizure detection techniques identified the detection criteria that can be extended to the time-frequency domain. The selected method uses a high-resolution reduced interference time-frequency distribution referred to as the B-distribution (BD). Here, the authors present the various patterns of observed time-frequency seizure signals and relate them to current knowledge of seizures. In particular, initial results indicate that a quasilinear instantaneous frequency (IF) can be used as a critical feature of the EEG seizure characteristics
Keyword electroencephalography
medical signal detection
time-frequency analysis
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
Collection: UQ Centre for Clinical Research Publications
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Citation counts: TR Web of Science Citation Count  Cited 37 times in Thomson Reuters Web of Science Article | Citations
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Created: Tue, 20 Jul 2010, 13:54:02 EST by Maria Campbell on behalf of The University of Queensland Library