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. 2015 Aug:2015:1492-5.
doi: 10.1109/EMBC.2015.7318653.

Data-driven metric representing the maturation of preterm EEG

Ninah Koolen, Anneleen Dereymaeker, Okko Rasanen, Katrien Jansen, Jan Vervisch, Vladimir Matic, Maarten De Vos, Gunnar Naulaers, Sabine Van Huffel, Sampsa Vanhatalo

Data-driven metric representing the maturation of preterm EEG

Ninah Koolen et al. Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug.

Abstract

Essential information about early brain maturation can be retrieved from the preterm human electroencephalogram (EEG). This study proposes a new set of quantitative features that correlate with early maturation. We exploit the known early trend in EEG content from intermittent to continuous activity, which changes the line length content of the EEG. The developmental shift can be captured in the line length histogram, which we use to obtain 28 features; 20 histogram bins and 8 other statistical measurements. Using the mutual information, we select 6 features with high correlation to the infant's age. This subset appears promising to detect deviances from normal brain maturation. The presented data-driven index holds promise for developing into a computational EEG index of maturation that is highly needed for overall assessment in the Neonatal Intensive Care Units.

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