A nonlinear model of newborn EEG with nonstationary inputs

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dc.contributor.author Stevenson, Nathan J.
dc.contributor.author Mesbah, Mostefa
dc.contributor.author Boylan, Geraldine B.
dc.contributor.author Colditz, Paul B.
dc.contributor.author Boashash, Boualem
dc.contributor.editor McIntire, Larry V.
dc.date.accessioned 2012-07-11T14:06:27Z
dc.date.available 2012-07-11T14:06:27Z
dc.date.issued 2010-09
dc.identifier.citation Stevenson, NJ; Mesbah, M; Boylan, GB; Colditz, PB; Boashash, B; (2010) 'A nonlinear model of newborn EEG with nonstationary inputs'. Annals of Biomedical Engineering, 38 (9):3010-3021. doi: 10.1007/s10439-010-0041-3 en
dc.identifier.volume 38 en
dc.identifier.issued 9 en
dc.identifier.startpage 3010 en
dc.identifier.endpage 3021 en
dc.identifier.issn 0090-6964
dc.identifier.issn 1573-9686
dc.identifier.uri http://hdl.handle.net/10468/629
dc.identifier.doi 10.1007/s10439-010-0041-3
dc.description.abstract Newborn EEG is a complex multiple channel signal that displays nonstationary and nonlinear characteristics. Recent studies have focussed on characterizing the manifestation of seizure on the EEG for the purpose of automated seizure detection. This paper describes a novel model of newborn EEG that can be used to improve seizure detection algorithms. The new model is based on a nonlinear dynamic system; the Duffing oscillator. The Duffing oscillator is driven by a nonstationary impulse train to simulate newborn EEG seizure and white Gaussian noise to simulate newborn EEG background. The use of a nonlinear dynamic system reduces the number of parameters required in the model and produces more realistic, life-like EEG compared with existing models. This model was shown to account for 54% of the linear variation in the time domain, for seizure, and 85% of the linear variation in the frequency domain, for background. This constitutes an improvement in combined performance of 6%, with a reduction from 48 to 4 model parameters, compared to an optimized implementation of the best performing existing model. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Springer Verlag en
dc.relation.uri http://www.springerlink.com/content/15862x28m57q4373/
dc.rights ©2010, Biomedical Engineering Society. The original publication is available at www.springerlink.com en
dc.subject Newborn en
dc.subject Neonate en
dc.subject EEG en
dc.subject Modelling and simulation en
dc.subject Nonlinear en
dc.subject Duffing oscillator en
dc.subject Nonstationary en
dc.subject Seizure en
dc.subject Electroencephalogram en
dc.title A nonlinear model of newborn EEG with nonstationary inputs en
dc.type Article (peer-reviewed) en
dc.internal.authorurl http://research.ucc.ie/profiles/C005/nstevenson en
dc.internal.authorurl http://research.ucc.ie/profiles/C012/gboylan en
dc.internal.authorcontactother Nathan Stevenson, Paediatrics & Child Health, University College Cork, Cork, Ireland. +353-21-490-3000 Email: n.stevenson@ucc.ie en
dc.internal.authorcontactother Geraldine Boylan, Paediatrics & Child Health, University College Cork, Cork, Ireland. +353-21-490-3000 Email: g.boylan@ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2012-07-11T10:34:33Z
dc.description.version Accepted Version en
dc.internal.rssid 58462132
dc.internal.pmid 20405217
dc.description.status Peer reviewed en
dc.identifier.journaltitle Annals of Biomedical Engineering en
dc.internal.copyrightchecked No. CORA check Sherpa Romeo. Accepted version provided. en
dc.internal.licenseacceptance Yes en
dc.internal.IRISemailaddress n.stevenson@ucc.ie en

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