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

M. Lavanga; O. De Wel; A. Caicedo; E. Heremans; K. Jansen; A. Dereymaeker; G. Naulaers; S. Van Huffel

doi:10.1109/EMBC.2017.8037246

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

M. Lavanga
, O. De Wel
, A. Caicedo
, E. Heremans
, K. Jansen
, A. Dereymaeker
, G. Naulaers
, S. Van Huffel

Research output: Chapter in Book/Inform › Conference contribution

7 Scopus citations

Abstract

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.

Original language	English (US)
Title of host publication	2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publication	Smarter Technology for a Healthier World, EMBC 2017 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2010-2013
Number of pages	4
ISBN (Electronic)	9781509028092
DOIs	https://doi.org/10.1109/EMBC.2017.8037246
State	Published - Sep 13 2017
Externally published	Yes
Event	39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of Duration: Jul 11 2017 → Jul 15 2017

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)	1557-170X

Conference

Conference	39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
Country/Territory	Korea, Republic of
City	Jeju Island
Period	7/11/17 → 7/15/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 1 No Poverty

All Science Journal Classification (ASJC) codes

Signal Processing
Biomedical Engineering
Computer Vision and Pattern Recognition
Health Informatics

Access to Document

10.1109/EMBC.2017.8037246

Cite this

Lavanga, M., De Wel, O., Caicedo, A., Heremans, E., Jansen, K., Dereymaeker, A., Naulaers, G., & Van Huffel, S. (2017). Automatic quiet sleep detection based on multifractality in preterm neonates: Effects of maturation. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Smarter Technology for a Healthier World, EMBC 2017 - Proceedings (pp. 2010-2013). Article 8037246 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2017.8037246

Lavanga, M. ; De Wel, O. ; Caicedo, A. et al. / Automatic quiet sleep detection based on multifractality in preterm neonates : Effects of maturation. 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Smarter Technology for a Healthier World, EMBC 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 2010-2013 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

@inproceedings{53c34542e940439fa57cb413d2b6c758,

title = "Automatic quiet sleep detection based on multifractality in preterm neonates: Effects of maturation",

abstract = "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.",

author = "M. Lavanga and \{De Wel\}, O. and A. Caicedo and E. Heremans and K. Jansen and A. Dereymaeker and G. Naulaers and \{Van Huffel\}, S.",

note = "Funding Information: VI. ACKNOWLEDGEMENTS This research is supported by Bijzonder Onderzoeksfonds KU Leuven (BOF): The effect of perinatal stress on the later outcome in preterm babies (\# C24/15/036); iMinds Medical Information Technologies (SBO-2016); Belgian Federal Science Policy Office, IUAP \# P7/19/ (DYSCO, {\textquoteleft}Dynamical systems, control and optimization{\textquoteright}, 2012-2017); Belgian Foreign Affairs-Development Cooperation (VLIR UOS programs (2013-2019)); ERC Advanced Grant: BIOTENSORS (n◦ 339804). A.C. is a post-doc fellow at Fonds voor We-tenschappelijk Onderzoek-Vlaanderen (FWO), supported by Flemish government. M.L. is a SB PhD fellow at Fonds voor Wetenschappelijk Onderzoek-Vlaanderen (FWO), supported by Flemish government. Publisher Copyright: {\textcopyright} 2017 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 ; Conference date: 11-07-2017 Through 15-07-2017",

year = "2017",

month = sep,

day = "13",

doi = "10.1109/EMBC.2017.8037246",

language = "English (US)",

series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2010--2013",

booktitle = "2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society",

address = "United States",

}

Lavanga, M, De Wel, O, Caicedo, A, Heremans, E, Jansen, K, Dereymaeker, A, Naulaers, G & Van Huffel, S 2017, Automatic quiet sleep detection based on multifractality in preterm neonates: Effects of maturation. in 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Smarter Technology for a Healthier World, EMBC 2017 - Proceedings., 8037246, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Institute of Electrical and Electronics Engineers Inc., pp. 2010-2013, 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017, Jeju Island, Korea, Republic of, 7/11/17. https://doi.org/10.1109/EMBC.2017.8037246

Automatic quiet sleep detection based on multifractality in preterm neonates: Effects of maturation. / Lavanga, M.; De Wel, O.; Caicedo, A. et al.
2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Smarter Technology for a Healthier World, EMBC 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 2010-2013 8037246 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

Research output: Chapter in Book/Inform › Conference contribution

TY - GEN

T1 - Automatic quiet sleep detection based on multifractality in preterm neonates

T2 - 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017

AU - Lavanga, M.

AU - De Wel, O.

AU - Caicedo, A.

AU - Heremans, E.

AU - Jansen, K.

AU - Dereymaeker, A.

AU - Naulaers, G.

AU - Van Huffel, S.

N1 - Funding Information: VI. ACKNOWLEDGEMENTS This research is supported by Bijzonder Onderzoeksfonds KU Leuven (BOF): The effect of perinatal stress on the later outcome in preterm babies (# C24/15/036); iMinds Medical Information Technologies (SBO-2016); Belgian Federal Science Policy Office, IUAP # P7/19/ (DYSCO, ‘Dynamical systems, control and optimization’, 2012-2017); Belgian Foreign Affairs-Development Cooperation (VLIR UOS programs (2013-2019)); ERC Advanced Grant: BIOTENSORS (n◦ 339804). A.C. is a post-doc fellow at Fonds voor We-tenschappelijk Onderzoek-Vlaanderen (FWO), supported by Flemish government. M.L. is a SB PhD fellow at Fonds voor Wetenschappelijk Onderzoek-Vlaanderen (FWO), supported by Flemish government. Publisher Copyright: © 2017 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.

PY - 2017/9/13

Y1 - 2017/9/13

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/85031932125

UR - https://www.scopus.com/pages/publications/85031932125#tab=citedBy

U2 - 10.1109/EMBC.2017.8037246

DO - 10.1109/EMBC.2017.8037246

M3 - Conference contribution

C2 - 29060290

AN - SCOPUS:85031932125

T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

SP - 2010

EP - 2013

BT - 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 11 July 2017 through 15 July 2017

ER -

Lavanga M, De Wel O, Caicedo A, Heremans E, Jansen K, Dereymaeker A et al. Automatic quiet sleep detection based on multifractality in preterm neonates: Effects of maturation. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Smarter Technology for a Healthier World, EMBC 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. p. 2010-2013. 8037246. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC.2017.8037246

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

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this