Newborn EEG seizure detection using t-f distance measure

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Newborn EEG seizure detection using t-f distance measure

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Title: Newborn EEG seizure detection using t-f distance measure
Author: Zarjam, P; Azemi, G; Mesbah, M; Boashash, B
Abstract: In this research, a time-frequency (TF) based method for detecting seizure patterns in newborn’s Electroencephalogram (EEG) signals is proposed. In this approach, the discrimination between seizure and non-seizure states is based on the TF distance between the consequent segments in the EEG signal. Three different TF measures and three different reduced timefrequency distributions (TFD) are used in this study. The proposed method is tested on the EEG data acquired from three neonates with ages under two weeks. The empirical results validate the suitability of the proposed method in automated newborns’ seizure detection. The performance of the distance measures are then compared for the used TFDs. The results present an average seizure detection rate of 96% and false alarm rate of 5% using Kullback- Leibler measure which outperforms the other two distance measures.
Description: This paper use time-frequency distance measures with Quadratic TFDs to detect seizure activities in newborns’ EEGs with improved performance. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated).
URI: http://hdl.handle.net/10576/10779
Date: 2005-11

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