Newborn EEG seizure detection using signal structural complexity

L. Rankine, M. Mesbah, B. Boashash

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A method for the automatic detection of seizure in newborns is presented. The proposed method is derived from the ability to detect changes in signal structure as the newborn EEG changes from the background state to the seizure state. Matching Pursuit decomposition technique, with an overcomplete time-frequency dictionary, is shown to be an adequate technique for detecting changes in signal structure. Changes are detected by using a new signal measure referred to as structural complexity, which is directly related to the dictionary being used for decomposition. The structural complexity measured is then incorporated in the proposed automatic newborn seizure detection algorithm.

Original languageEnglish
Title of host publication2004 12th European Signal Processing Conference, EUSIPCO 2004
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages2207-2210
Number of pages4
ISBN (Electronic)9783200001657
Publication statusPublished - Apr 3 2015
Externally publishedYes
Event12th European Signal Processing Conference, EUSIPCO 2004 - Vienna, Austria
Duration: Sept 6 2004Sept 10 2004

Publication series

NameEuropean Signal Processing Conference
Volume06-10-September-2004
ISSN (Print)2219-5491

Other

Other12th European Signal Processing Conference, EUSIPCO 2004
Country/TerritoryAustria
CityVienna
Period9/6/049/10/04

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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