Open Access   Article Go Back

Detection of Fetal Stress from Maternal Abdominal Electrocardiogram Signal

R. Tamilselvi1 , M. Parisa Beham2 , A. Merline3 , S.M.M.Roomi 4 , B. Saravanan5 , T. Ruba6

Section:Research Paper, Product Type: Journal Paper
Volume-06 , Issue-04 , Page no. 65-70, May-2018

Online published on May 31, 2018

Copyright © R. Tamilselvi, M. Parisa Beham, A. Merline, S.M.M.Roomi, B. Saravanan , T. Ruba . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: R. Tamilselvi, M. Parisa Beham, A. Merline, S.M.M.Roomi, B. Saravanan , T. Ruba, “Detection of Fetal Stress from Maternal Abdominal Electrocardiogram Signal,” International Journal of Computer Sciences and Engineering, Vol.06, Issue.04, pp.65-70, 2018.

MLA Style Citation: R. Tamilselvi, M. Parisa Beham, A. Merline, S.M.M.Roomi, B. Saravanan , T. Ruba "Detection of Fetal Stress from Maternal Abdominal Electrocardiogram Signal." International Journal of Computer Sciences and Engineering 06.04 (2018): 65-70.

APA Style Citation: R. Tamilselvi, M. Parisa Beham, A. Merline, S.M.M.Roomi, B. Saravanan , T. Ruba, (2018). Detection of Fetal Stress from Maternal Abdominal Electrocardiogram Signal. International Journal of Computer Sciences and Engineering, 06(04), 65-70.

BibTex Style Citation:
@article{Tamilselvi_2018,
author = {R. Tamilselvi, M. Parisa Beham, A. Merline, S.M.M.Roomi, B. Saravanan , T. Ruba},
title = {Detection of Fetal Stress from Maternal Abdominal Electrocardiogram Signal},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {06},
Issue = {04},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {65-70},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=359},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=359
TI - Detection of Fetal Stress from Maternal Abdominal Electrocardiogram Signal
T2 - International Journal of Computer Sciences and Engineering
AU - R. Tamilselvi, M. Parisa Beham, A. Merline, S.M.M.Roomi, B. Saravanan , T. Ruba
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 65-70
IS - 04
VL - 06
SN - 2347-2693
ER -

           

Abstract

In recent research, recognition of fetal stress is significant in fetal monitoring during pregnancy. In order to evaluate the health of the fetus, a non-invasive fetal monitoring method should be used for measuring the Fetal Heart Rate (FHR).Many methods are available for assessing the FHR. Among these methods, Cardiotocography (CTG) and Fetal Electrocardiogram (FECG) are common methods for monitoring FHR. The most important parameter for determining the fetal health is the FHR. Lot of algorithms are available extracting FECG signals from mothers abdomen. An algorithm is proposed to extract FECG from signals measured from the maternal abdomen. Wavelet transform technique is the most popular and efficient method for determining ECG characteristics. Independent Component Analysis (ICA) and Principle component Analysis (PCA) techniques are used in wavelet transform. This proposed work consists of three algorithms for finding out the fetal heart rate and stress. The proposed algorithm consists of three steps: 1) Abdominal ECG signal (AECG) is acquired from maternal abdomen i.e. Maternal ECG (MECG). 2) FECG signal is extracted by subtracting MECG signal from AECG signal by PCA method. 3) Then fetal R peaks are calculated in extracted FECG signal to detect fetal heart rate. Finally fetal stress is monitored from the measured FHR. The main contribution of our work is the fetal stress analysis from the fetal heart rate.

Key-Words / Index Term

Fetal Heart Rate, Cardiotocography, Fetal Electrocardiogram, PCA, ICA, ECG.

References

[1] J.Shamira and R.Tamilselvi, “Extraction of Fetal Heart Rate and Respiratory Rate from Abdominal Electrocardiogram”, Pak. J. Biotechnol. Volume 13 (special issue on Innovations in information Embedded and communication Systems) pp. 400- 404, 2016.
[2] Reza Sameni, Mohammad B. Shamsollahi, Christian Jutten and Gari D.Clifford, “A Nonlinear Bayesian Filtering Framework for ECG Denoising”, IEEE Transactions On Biomedical Engineering, Volume 54, Issue 12,2007.
[3] N P. Joshi, Shweta A.Tambe1, P.S. Topannavar, “Morphological &Dynamic Feature Based Heartbeat Classification”, International Journal of Engineering Research and General Science, Volume 2, Issue 3, 2014.
[4] RezaSameni, Christian Juttenand, Mohammad B.Shamsollahi, “Multichannel Electrocardiogram Decomposition Using Periodic Component Analysis”, IEEE Transactions on Biomedical Engineering. Volume 55, Issue 8, 2008.
[5] Camargo-Olivares J. L, R. Martin-Clemente, Hornillo-Mellado S, M. M.Elena, and I. Roman, “The Maternal Abdominal ECG as Input to MICA in the Fetal ECG Extraction Problem”, IEEE Signal Processing Letters, Volume 18,Issue 3,2011.
[6] C. Saritha,V. Sukanya,Y. Narasimha Murthy, “ ECG SignalAnalysis Using Wavelet Transforms”, Bulg. J. Phys. Volume 35 pp. 68–77,2008.
[7] Yatindra Kumar et al, “Performance Analysis of different Filters for Power Line Interface Reduction in ECG Signal” International Journal of Computer Applications ,Volume 3,Issue.7,pp.1-6, 2010.