Automatic quiet sleep detection based on multifractality in preterm neonates: effects of maturation

This 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 analys...

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Detalles Bibliográficos
Autores Principales: Lavanga, M., De Wel, O, Caicedo, A, Heremans, E, Jansen, K, Dereymaeker, A, Naulaers, G, Van Huffel, S
Formato: Capítulo de libro (Book Chapter)
Lenguaje:Inglés (English)
Publicado: IEEE 2017
Materias:
Acceso en línea:https://repository.urosario.edu.co/handle/10336/28923
https://doi.org/10.1109/EMBC.2017.8037246
id ir-10336-28923
recordtype dspace
spelling ir-10336-289232020-08-28T15:50:40Z Automatic quiet sleep detection based on multifractality in preterm neonates: effects of maturation Detección automática del sueño silencioso basada en la multifractalidad en recién nacidos prematuros: efectos de la maduración Lavanga, M. De Wel, O Caicedo, A Heremans, E Jansen, K Dereymaeker, A Naulaers, G Van Huffel, S Fractals Pediatrics Sleep Electroencephalography Entropy Training Brain modeling This 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. 2017-09-14 2020-08-28T15:50:07Z info:eu-repo/semantics/bookPart info:eu-repo/semantics/publishedVersion ISBN: 978-1-5090-2810-8 EISBN: 978-1-5090-2809-2 https://repository.urosario.edu.co/handle/10336/28923 https://doi.org/10.1109/EMBC.2017.8037246 eng info:eu-repo/semantics/restrictedAccess application/pdf IEEE 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
institution EdocUR - Universidad del Rosario
collection DSpace
language Inglés (English)
topic Fractals
Pediatrics
Sleep
Electroencephalography
Entropy
Training
Brain modeling
spellingShingle Fractals
Pediatrics
Sleep
Electroencephalography
Entropy
Training
Brain modeling
Lavanga, M.
De Wel, O
Caicedo, A
Heremans, E
Jansen, K
Dereymaeker, A
Naulaers, G
Van Huffel, S
Automatic quiet sleep detection based on multifractality in preterm neonates: effects of maturation
description This 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.
format Capítulo de libro (Book Chapter)
author Lavanga, M.
De Wel, O
Caicedo, A
Heremans, E
Jansen, K
Dereymaeker, A
Naulaers, G
Van Huffel, S
author_facet Lavanga, M.
De Wel, O
Caicedo, A
Heremans, E
Jansen, K
Dereymaeker, A
Naulaers, G
Van Huffel, S
author_sort Lavanga, M.
title Automatic quiet sleep detection based on multifractality in preterm neonates: effects of maturation
title_short Automatic quiet sleep detection based on multifractality in preterm neonates: effects of maturation
title_full Automatic quiet sleep detection based on multifractality in preterm neonates: effects of maturation
title_fullStr Automatic quiet sleep detection based on multifractality in preterm neonates: effects of maturation
title_full_unstemmed Automatic quiet sleep detection based on multifractality in preterm neonates: effects of maturation
title_sort automatic quiet sleep detection based on multifractality in preterm neonates: effects of maturation
publisher IEEE
publishDate 2017
url https://repository.urosario.edu.co/handle/10336/28923
https://doi.org/10.1109/EMBC.2017.8037246
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score 12,111491