Estimating fetal gestational age using cardiac valve intervals

Faezeh Marzbanrad, Ahsan H. Khandoker, Yoshitaka Kimura, Marimuthu Palaniswami, Gari D. Clifford

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

A new automated method for estimation of the gestational age is presented in this paper based on the intervals between fetal cardiac valve timings and the Q-wave of fetal electrocardiogram (fECG). The intervals were estimated automatically from one-dimensional Doppler Ultrasound and noninvasive fECG. Among the intervals, Isovolumic Contraction Time, Electromechanical Delay Time, Ventricular Filling Time and their interactions were selected in a stepwise regression process. Compared with Crown-Rump Length as gold standard, a mean absolute error of 3.8 weeks was obtained using leave-one-out cross validation. This method also outperformed a fetal heart rate based approach. Since valve intervals reflect the autonomic function, this method provides a novel measure ofthe development of fetal autonomic nervous system that may be growth curve independent.

Original languageEnglish
Title of host publicationComputing in Cardiology Conference, CinC 2016
EditorsAlan Murray
PublisherIEEE Computer Society
Pages109-112
Number of pages4
ISBN (Electronic)9781509008964
DOIs
Publication statusPublished - 2016 Mar 1
Event43rd Computing in Cardiology Conference, CinC 2016 - Vancouver, Canada
Duration: 2016 Sep 112016 Sep 14

Publication series

NameComputing in Cardiology
Volume43
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X

Other

Other43rd Computing in Cardiology Conference, CinC 2016
CountryCanada
CityVancouver
Period16/9/1116/9/14

ASJC Scopus subject areas

  • Computer Science(all)
  • Cardiology and Cardiovascular Medicine

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  • Cite this

    Marzbanrad, F., Khandoker, A. H., Kimura, Y., Palaniswami, M., & Clifford, G. D. (2016). Estimating fetal gestational age using cardiac valve intervals. In A. Murray (Ed.), Computing in Cardiology Conference, CinC 2016 (pp. 109-112). [7868691] (Computing in Cardiology; Vol. 43). IEEE Computer Society. https://doi.org/10.22489/cinc.2016.035-146