Estimating functional brain maturity in very and extremely preterm neonates using automated analysis of the electroencephalogram

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O'Toole , J M , Boylan , G B , Vanhatalo , S & Stevenson , N J 2016 , ' Estimating functional brain maturity in very and extremely preterm neonates using automated analysis of the electroencephalogram ' , Clinical Neurophysiology , vol. 127 , no. 8 , pp. 2910-2918 . https://doi.org/10.1016/j.clinph.2016.02.024

Title: Estimating functional brain maturity in very and extremely preterm neonates using automated analysis of the electroencephalogram
Author: O'Toole, J. M.; Boylan, G. B.; Vanhatalo, S.; Stevenson, N. J.
Contributor: University of Helsinki, Clinicum
University of Helsinki, Clinicum
Date: 2016-08
Language: eng
Number of pages: 9
Belongs to series: Clinical Neurophysiology
ISSN: 1388-2457
URI: http://hdl.handle.net/10138/224532
Abstract: Objective: To develop an automated estimate of EEG maturational age (EMA) for preterm neonates. Methods: The EMA estimator was based on the analysis of hourly epochs of EEG from 49 neonates with gestational age (GA) ranging from 23 to 32 weeks. Neonates had appropriate EEG for GA based on visual interpretation of the EEG. The EMA estimator used a linear combination (support vector regression) of a subset of 41 features based on amplitude, temporal and spatial characteristics of EEG segments. Estimator performance was measured with the mean square error (MSE), standard deviation of the estimate (SD) and the percentage error (SE) between the known GA and estimated EMA. Results: The EMA estimator provided an unbiased estimate of EMA with a MSE of 82 days (SD = 9.1 days; SE = 4.8%) which was significantly lower than a nominal reading (the mean GA in the dataset; MSE of 267 days, SD of 16.3 days, SE = 8.4%: p <0.001). The EMA estimator with the lowest MSE used amplitude, spatial and temporal EEG characteristics. Conclusions: The proposed automated EMA estimator provides an accurate estimate of EMA in early preterm neonates. Significance: Automated analysis of the EEG provides a widely accessible, noninvasive and continuous assessment of functional brain maturity. (C) 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Subject: Preterm neonate
Automated EEG analysis
Support vector regression
Clinical neurophysiology
Dysmaturity
SPONTANEOUS ACTIVITY TRANSIENTS
PREMATURE-INFANTS
MATURATIONAL CHANGES
CEREBRAL-PALSY
EEG ACTIVITY
SLEEP
INDEX
BIRTH
CONNECTIVITY
DYSMATURITY
3112 Neurosciences
3124 Neurology and psychiatry
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