Comparative performance of time-frequency based newborn EEG seizure detection using spike signatures

Hassanpour, H., Mesbah, Mostefa and Boashash, B. (2003). Comparative performance of time-frequency based newborn EEG seizure detection using spike signatures. In: Acoustics, Speech, and Signal Processing 2003 (ICASSP 2003). 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing 2003 (ICASSP 2003), Hong Kong, China, (389-392). 6-10 April 2003. doi:10.1109/ICASSP.2003.1202379


Author Hassanpour, H.
Mesbah, Mostefa
Boashash, B.
Title of paper Comparative performance of time-frequency based newborn EEG seizure detection using spike signatures
Conference name 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing 2003 (ICASSP 2003)
Conference location Hong Kong, China
Conference dates 6-10 April 2003
Convener Piscataway, NJ, U.S.A.
Proceedings title Acoustics, Speech, and Signal Processing 2003 (ICASSP 2003)   Check publisher's open access policy
Journal name 2003 Ieee International Conference On Acoustics, Speech, and Signal Processing, Vol Ii, Proceedings   Check publisher's open access policy
Place of Publication Piscataway, NJ, U.S.A.
Publisher IEEE - Institute of Electrical Electronics Engineers Inc.
Publication Year 2003
Sub-type Fully published paper
DOI 10.1109/ICASSP.2003.1202379
ISBN 0780376633
ISSN 1520-6149
Volume 2
Start page 389
End page 392
Total pages 4
Language eng
Abstract/Summary This paper investigates the performance of four nonparametric newborn EEG seizure detection methods. The authors recently proposed a time-frequency (TF) based technique suitable for nonstationarity of EEG signal. This method attempts to detect seizure activities through analysing the interspike intervals of the EEG in the TF domain. The performance of this method is compared to those of three nonparametric techniques for seizure detection. These methods are: autocorrelation, spectrum and singular spectrum analysis (SSA). The autocorrelation method performs analysis in the time domain and is based on the autocorrelation function of short epochs of EEG data. The spectrum technique is based on spectral analysis and is used to detect periodic discharges. The SSA technique employs singular spectrum analysis and information theoretic-based selection of the signal subspace. These three methods are based on the assumption that newborn EEG signal is quasi-stationary. The obtained results show the superior performance of the TF-based technique for detecting newborn EEG seizures.
Subjects 090609 Signal Processing
Keyword EEG seizure detection methods
Time-frequency (TF) based technique
Spectrum and singular spectrum analysis (SSA)
Autocorrelation method
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Unknown

 
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Created: Thu, 26 Mar 2009, 15:44:05 EST by Jason Parr on behalf of UQ Centre for Clinical Research