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Open AccessArticle

Decomposition of a Multiscale Entropy Tensor for Sleep Stage Identification in Preterm Infants

1
Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, 3001 Leuven, Belgium
2
Department of Applied Mathematics and Computer Science, Universidad del Rosario, Bogotá 111711, Colombia
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Department of Development and Regeneration, Neonatal Intensive Care Unit, University Hospitals Leuven, 3000 Leuven, Belgium
4
Department of Development and Regeneration, Child Neurology, University Hospitals Leuven, 3000 Leuven, Belgium
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(10), 936; https://doi.org/10.3390/e21100936
Received: 10 August 2019 / Revised: 12 September 2019 / Accepted: 23 September 2019 / Published: 25 September 2019
(This article belongs to the Special Issue Multiscale Entropy Approaches and Their Applications)
Established sleep cycling is one of the main hallmarks of early brain development in preterm infants, therefore, automated classification of the sleep stages in preterm infants can be used to assess the neonate’s cerebral maturation. Tensor algebra is a powerful tool to analyze multidimensional data and has proven successful in many applications. In this paper, a novel unsupervised algorithm to identify neonatal sleep stages based on the decomposition of a multiscale entropy tensor is presented. The method relies on the difference in electroencephalography(EEG) complexity between the neonatal sleep stages and is evaluated on a dataset of 97 EEG recordings. An average sensitivity, specificity, accuracy and area under the receiver operating characteristic curve of 0.80, 0.79, 0.79 and 0.87 was obtained if the rank of the tensor decomposition is selected based on the age of the infant. View Full-Text
Keywords: CPD; EEG; multiscale entropy; sleep staging; tensor decomposition; preterm neonate CPD; EEG; multiscale entropy; sleep staging; tensor decomposition; preterm neonate
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MDPI and ACS Style

De Wel, O.; Lavanga, M.; Caicedo, A.; Jansen, K.; Naulaers, G.; Van Huffel, S. Decomposition of a Multiscale Entropy Tensor for Sleep Stage Identification in Preterm Infants. Entropy 2019, 21, 936.

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