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dc.creatorLavanga, M. 
dc.creatorDe Wel, O 
dc.creatorCaicedo Dorado, Alexander 
dc.creatorHeremans, E 
dc.creatorJansen, K 
dc.creatorDereymaeker, A 
dc.creatorNaulaers, G 
dc.creatorVan Huffel, S 
dc.date.accessioned2020-08-28T15:50:07Z
dc.date.available2020-08-28T15:50:07Z
dc.date.created2017-09-14
dc.identifier.issnISBN: 978-1-5090-2810-8
dc.identifier.issnEISBN: 978-1-5090-2809-2
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/28923
dc.description.abstractThis study investigates the multifractal formalism framework for quiet sleep detection in preterm babies. EEG recordings from 25 healthy preterm infants were used in order to evaluate the performance of multifractal measures for the detection of quiet sleep. Results indicate that multifractal analysis based on wavelet leaders is able to identify quiet sleep epochs, but the classifier performances seem to be highly affected by the infant's age. In particular, from the developed classifiers, the lowest area under the curve (AUC) has been obtained for EEG recordings at very young age (? 31 weeks post-menstrual age), and the maximum at full-term age (? 37 weeks post-menstrual age). The improvement in classification performances can be due to a change in the multifractality properties of neonatal EEG during the maturation of the infant, which makes the EEG sleep stages more distinguishable.
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.relation.ispartof39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), ISBN: 978-1-5090-2810-8;EISBN: 978-1-5090-2809-2 (2017); pp. 2010-2013
dc.relation.urihttps://ieeexplore.ieee.org/document/8037246
dc.source2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
dc.titleAutomatic quiet sleep detection based on multifractality in preterm neonates: effects of maturation
dc.typebookPart
dc.publisherIEEE
dc.subject.keywordFractals
dc.subject.keywordPediatrics
dc.subject.keywordSleep
dc.subject.keywordElectroencephalography
dc.subject.keywordEntropy
dc.subject.keywordTraining
dc.subject.keywordBrain modeling
dc.rights.accesRightsinfo:eu-repo/semantics/restrictedAccess
dc.type.spaparte de Libro
dc.rights.accesoRestringido (Acceso a grupos específicos)
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doihttps://doi.org/10.1109/EMBC.2017.8037246
dc.title.TranslatedTitleDetección automática del sueño silencioso basada en la multifractalidad en recién nacidos prematuros: efectos de la maduración
dc.relation.citationEndPage2013
dc.relation.citationStartPage2010
dc.relation.citationTitle2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)


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