Automated measurement of fetal isovolumic contraction time from doppler ultrasound signals without using fetal electrocardiography

Faezeh Marzbanrad, Yoshitaka Kimura, Miyuki Endo, Marimuthu Palaniswami, Ahsan H Khandoker

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3 Citations (Scopus)


lsovolumic Contraction Time (ICT) is the interval from mitral closing to aorta opening. Fetal ICT can be noninvasively measured from Doppler Ultrasound (DUS) signal. Automated identification of opening and closing of mitral and aortic valves from DUS signal was proposed in recent studies. Fetal electrocardiogram (fECG) has a crucial role as a reference in automated methods by identifying the onset of each cardiac cycle. However simultaneous recording of abdominal ECG and DUS and separation of ECG from the noisy mixture of ECG complicate this technique. In this study the automated identification of valve motion events without using ECG was investigated. The DUS signal was decomposed by Empirical Mode Decomposition (EMD) to high and low frequency components linked to valve and wall motion,respectively. The peaks of the latter were used for segmentation of the high frequency component as a substitute for ECG. The mitral and aortic valve motion was then automatically identified by hybrid Support Vector Machine (SVM)-Hidden Markov Model (HMM). Results show a significant positive linear correlation between average ICT obtained with and without using ECG (r=O.90, p<0.0001) with the mean absolute difference of 1.4 msec.
Original languageEnglish
Title of host publicationComputing in Cardiology 2014
EditorsAlan Murray
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Electronic)9781479943470
ISBN (Print)9781479943463
Publication statusPublished - 2014
Externally publishedYes
EventComputing in Cardiology Conference 2014 - Cambridge, United States of America
Duration: 7 Sep 20149 Sep 2014
Conference number: 41st


ConferenceComputing in Cardiology Conference 2014
Abbreviated titleCINC 2014
CountryUnited States of America

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