Automated estimation of fetal cardiac timing events from doppler ultrasound signal using hybrid models

Faezeh Marzbanrad, Yoshitaka Kimura, Kiyoe Funamoto, Rika Sugibayashi, Miyuki Endo, Takuya Ito, Marimuthu Palaniswami, Ahsan H. Khandoker

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)

Abstract

In this paper, a new noninvasive method is proposed for automated estimation of fetal cardiac intervals from Doppler Ultrasound (DUS) signal. This method is based on a novel combination of empirical mode decomposition (EMD) and hybrid support vector machines - hidden Markov models (SVM/HMM). EMD was used for feature extraction by decomposing the DUS signal into different components (IMFs), one of which is linked to the cardiac valve motions, i.e. opening (o) and closing (c) of the Aortic (A) and Mitral (M) valves. The noninvasive fetal electrocardiogram (fECG) was used as a reference for the segmentation of the IMF into cardiac cycles. The hybrid SVM/HMM was then applied to identify the cardiac events, based on the amplitude and timing of the IMF peaks as well as the sequence of the events. The estimated timings were verified using pulsed doppler images. Results show that this automated method can continuously evaluate beat-to-beat valve motion timings and identify more than 91% of total events which is higher than previous methods. Moreover, the changes of the cardiac intervals were analyzed for three fetal age groups: 16-29, 30-35, and 36-41 weeks. The time intervals from Q-wave of fECG to Ac (Systolic Time Interval, STI), Ac to Mo (Isovolumic Relaxation Time, IRT), Q-wave to Ao (Preejection Period, PEP) and Ao to Ac (Ventricular Ejection Time, VET) were found to change significantly (p < 0.05) across these age groups. In particular, STI, IRT, and PEP of the fetuses with 36-41 week were significantly (p < 0.05) different from other age groups. These findings can be used as sensitive markers for evaluating the fetal cardiac performance.

Original languageEnglish
Article number6636069
Pages (from-to)1169-1177
Number of pages9
JournalIEEE Journal of Biomedical and Health Informatics
Volume18
Issue number4
DOIs
Publication statusPublished - 2014 Jul

Keywords

  • Doppler ultrasound (DUS)
  • empirical mode decomposition (EMD)
  • fetal cardiac intervals
  • fetal monitoring
  • hidden Markov models (HMM)
  • hybrid SVM/HMM
  • support vector machine (SVM)

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Health Information Management

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