4.7 Article

System for adaptive extraction of non-invasive fetal electrocardiogram

期刊

APPLIED SOFT COMPUTING
卷 113, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.asoc.2021.107940

关键词

Adaptive filtration; Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN); Extraction algorithms; Fast transversal filter (FTF); Fetal electrocardiography; Fetal heart rate (fHR); Hybrid system; Independent component analysis (ICA); Non-invasive fetal monitoring

资金

  1. Ministry of Education of the Czech Republic [SP2021/32, SP2021/24]
  2. European Regional Develop-ment Fund in the Research Centre of Advanced Mechatronic Sys-tems project within the Operational Programme Research, Development and Education [CZ.02.1.01/0.0/0.0/16_019/0000867]

向作者/读者索取更多资源

This study identified an effective method for extracting non-invasive fetal electrocardiogram (NI-fECG) from signals recorded from the mother's abdomen, combining independent component analysis (ICA), fast transversal filter (FTF), and complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Testing on two patient databases demonstrated that this combined method is capable of accurately extracting fECG with lower computational complexity.
This study aimed to find the most suitable combination of adaptive and non-adaptive methods for extraction of non-invasive fetal electrocardiogram (NI-fECG) using signals recorded from the mother's abdomen. Among the nine methods considered, the combination of independent component analysis (ICA), fast transversal filter (FTF), and complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) proved to be the most effective for the extraction of fECG from abdominal recordings. This combined method was suitable due to both being effective in extracting fECG and being less computationally complex. Further, so far, FTF and CEEMDAN methods have not been extensively tested for fECG extraction, and in particular, have not been examined as a hybrid method. The ICA-FTF-CEEMDAN hybrid algorithm was tested on two patient databases: Fetal Electrocardiograms, Direct and Abdominal with Reference Heartbeats Annotations (FECGDARHA) and PhysioNet Challenge 2013. The evaluation of the accuracy of fQRS complexes detection was performed using the following parameters: accuracy (ACC), sensitivity (SE), positive predictive value (PPV), and F1 score. The fetal heart rate (fHR) determination accuracy was evaluated using Bland-Altman plots and fHR traces. When testing on the FECGDARHA database, average values of ACC = 92.98%, SE = 95.33%, PPV = 96.4% and F1 = 95.86% for detection fQRS were achieved. The error in estimating the fHR was -1.02 +/- 7.02 (mu +/- 1.96 sigma) bpm. When testing on the Challenge 2013 database, average values of ACC = 78.47%, SE = 82.06%, PPV = 87.90% and F1 = 84.62% for fQRS detection were achieved, and the error in estimating the fHR was -6.62 +/- 10.33 (mu +/- 1.96 sigma) bpm. In addition, a non-invasive morphological analysis (ST analysis) was performed on the records from the FECGDARHA database, which was accurate in 7 of 12 records with values of mu < 0.03 and values of +/- 1.96 sigma < 0.04. (C) 2021 The Author(s). Published by Elsevier B.V.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据