Automatic quiet sleep detection based on multifractality in preterm neonates: effects of maturation
| Autor: | E Heremans, Gunnar Naulaers, Alexander Caicedo, Mario Lavanga, S. Van Huffel, Anneleen Dereymaeker, Katrien Jansen, O De Wel |
|---|---|
| Přispěvatelé: | Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM) |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
medicine.medical_specialty
Neonatal eeg Speech recognition Multifractal formalism 02 engineering and technology Audiology Electroencephalography 03 medical and health sciences 0302 clinical medicine 0202 electrical engineering electronic engineering information engineering medicine Humans ComputingMilieux_MISCELLANEOUS Biological Phenomena medicine.diagnostic_test SISTA [SCCO.NEUR]Cognitive science/Neuroscience Infant Newborn Infant Multifractal system Infant newborn 3. Good health Young age Quiet sleep 020201 artificial intelligence & image processing Psychology Sleep Sleep eeg 030217 neurology & neurosurgery Infant Premature |
| Zdroj: | 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Jul 2017, Seogwipo, France. pp.2010-2013, ⟨10.1109/EMBC.2017.8037246⟩ EMBC |
| Popis: | 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. no issn/isbn ispartof: pages:2010-2013 ispartof: Proc. 39th Annual International Conference of the IEEE Engineering in Medicine & Biology Society vol:2017 pages:2010-2013 ispartof: EMBC 2017 location:Jeju Island, South Korea date:Jul - Jul 2017 status: published |
| Databáze: | OpenAIRE |
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