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A Hybrid EMD-Kurtosis Method for Estimating Fetal Heart Rate from Continuous Doppler Signals

Overview of attention for article published in Frontiers in Physiology, August 2017
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Title
A Hybrid EMD-Kurtosis Method for Estimating Fetal Heart Rate from Continuous Doppler Signals
Published in
Frontiers in Physiology, August 2017
DOI 10.3389/fphys.2017.00641
Pubmed ID
Authors

Haitham M. Al-Angari, Yoshitaka Kimura, Leontios J. Hadjileontiadis, Ahsan H. Khandoker

Abstract

Monitoring of fetal heart rate (FHR) is an important measure of fetal wellbeing during the months of pregnancy. Previous works on estimating FHR variability from Doppler ultrasound (DUS) signal mainly through autocorrelation analysis showed low accuracy when compared with heart rate variability (HRV) computed from fetal electrocardiography (fECG). In this work, we proposed a method based on empirical mode decomposition (EMD) and the kurtosis statistics to estimate FHR and its variability from DUS. Comparison between estimated beat-to-beat intervals using the proposed method and the autocorrelation function (AF) with respect to RR intervals computed from fECG as the ground truth was done on DUS signals from 44 pregnant mothers in the early (20 cases) and late (24 cases) gestational weeks. The new EMD-kurtosis method showed significant lower error in estimating the number of beats in the early group (EMD-kurtosis: 2.2% vs. AF: 8.5%, p < 0.01, root mean squared error) and the late group (EMD-kurtosis: 2.9% vs. AF: 6.2%). The EMD-kurtosis method was also found to be better in estimating mean beat-to-beat with an average difference of 1.6 ms from true mean RR compared to 19.3 ms by using the AF method. However, the EMD-kurtosis performed worse than AF in estimating SNDD and RMSSD. The proposed EMD-kurtosis method is more robust than AF in low signal-to-noise ratio cases and can be used in a hybrid system to estimate beat-to-beat intervals from DUS. Further analysis to reduce the estimated beat-to-beat variability from the EMD-kurtosis method is needed.

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Mendeley readers

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The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 18%
Student > Ph. D. Student 4 18%
Other 3 14%
Researcher 2 9%
Lecturer 1 5%
Other 2 9%
Unknown 6 27%
Readers by discipline Count As %
Engineering 8 36%
Nursing and Health Professions 2 9%
Biochemistry, Genetics and Molecular Biology 1 5%
Mathematics 1 5%
Computer Science 1 5%
Other 3 14%
Unknown 6 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 August 2017.
All research outputs
#20,444,703
of 22,999,744 outputs
Outputs from Frontiers in Physiology
#9,473
of 13,760 outputs
Outputs of similar age
#275,674
of 315,743 outputs
Outputs of similar age from Frontiers in Physiology
#214
of 294 outputs
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