Newborn EEG seizure pattern characterisation using time-frequency analysis

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Newborn EEG seizure pattern characterisation using time-frequency analysis

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Title: Newborn EEG seizure pattern characterisation using time-frequency analysis
Author: Boashash, Boualem; Mesbah, M; Colditz, P
Abstract: Previous techniques for seizure detection in newborn babies are inefficient. The main reason for their relative poor performance resides in their assumption of stationarity of the EEG. To remedy this problem, we use time-frequency distributions (TFD) to analyse and characterise the newborn EEG seizure patterns as a first step toward a time-frequency (TF) based seizure detection and classification scheme. This paper presents the results of the analysis of these time-frequency patterns for two abnormal newborn EEGs. We demonstrate that the newborn EEG seizures are well described by a class of mono- and multi-component linear FM signals. This result is novel and contradicts the simplistic assumptions routinely made in the field.
Description: This is one of the earliest papers to show that new-born EEG seizures can be characterized by a piece-wise linear FM pattern in the time-frequency domain. A software package that calculates IF estimates and TFDs can be downloaded from the web site: www.time-frequency.net
URI: http://hdl.handle.net/10576/10691
Date: 2001

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