Newborn EEG seizure detection based on interspike space distribution in the time-frequency domain

Hassanpour, H. and Mesbah, M. (2007) Newborn EEG seizure detection based on interspike space distribution in the time-frequency domain. International Journal of Engineering, 20 2: 137-146.


Author Hassanpour, H.
Mesbah, M.
Title Newborn EEG seizure detection based on interspike space distribution in the time-frequency domain
Journal name International Journal of Engineering
ISSN 1025-2495
Publication date 2007-06-01
Sub-type Article (original research)
Volume 20
Issue 2
Start page 137
End page 146
Total pages 10
Language eng
Subject 090609 Signal Processing
0903 Biomedical Engineering
Abstract This paper presents a new time-frequency based EEG seizure detection method. This method uses the distribution of interspike intervals as a criterion for discriminating between seizure and nonseizure activities. To detect spikes in the EEG, the signal is mapped into the time-frequency domain. The high instantaneous energy of spikes is reflected as a localized energy in time-frequency domain. Histogram of successive spikes intervals is then used as a feature for seizure detection. In the presented technique the EEG data are segmented into 4-second epochs. A k-nearest neighbor algorithm is employed to classify the EEG epochs into seizure and nonseizure groups. The performance of the presented technique is evaluated using the EEG data of five neonates. The results indicate that the proposed technique is superior to the other existing methods with 92.4 % good detection rate and 4.9 % false detection rate.
Q-Index Code C1
Additional Notes from Transactions A Basics

Document type: Journal Article
Sub-type: Article (original research)
Collections: Faculty of Engineering, Architecture and Information Technology Publications
Excellence in Research Australia (ERA) - Collection
 
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Created: Wed, 25 Mar 2009, 18:52:44 EST by Paul Rollo on behalf of Faculty Of Health Sciences