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An automated quiet sleep detection approach in preterm infants as a gateway to assessing brain maturation

Abstract:

Sleep state development in preterm neonates can provide crucial information regarding functional brain maturation and give insight into neurological well being. However, visual labeling of sleep stages from EEG requires expertise and is very time consuming, prompting the need for an automated procedure. We present a robust method for automated detection of preterm sleep from EEG, over a wide postmenstrual age (PMA = gestational age + postnatal age) range, focusing first on Quiet Sleep (QS) as...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.1142/S012906571750023X

Authors


Dereymaeker, A More by this author
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Department:
Oxford, MPLS, Engineering Science
Vervisch, J More by this author
Van Huffel, S More by this author
Naulaers, G More by this author
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Grant:
098461/Z/12/Z (Sleep, Circadian Rhythms & Neuroscience Institute)
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Grant:
EP/G036861/1 (Oxford Centre for Doctoral Training in Healthcare Innovation)
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Grant:
Advanced Grant: BIOTENSORS (339804)
Publisher:
World Scientific Publishing Publisher's website
Journal:
International Journal of Neural Systems Journal website
Volume:
27
Issue:
6
Pages:
Article: 1750023
Publication date:
2017-05-02
Acceptance date:
2017-02-20
DOI:
EISSN:
1793-6462
ISSN:
0129-0657
Pubs id:
pubs:697603
URN:
uri:b72d6d76-61ca-4f71-9298-8dc3a87dec0a
UUID:
uuid:b72d6d76-61ca-4f71-9298-8dc3a87dec0a
Local pid:
pubs:697603

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