Document Type: Original Research


1 PhD Candidate, Young Researchers and Elite Club, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 MSc, Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran

3 MSc, Department of Health Management and Economics, Tehran University of Medical Sciences, Tehran, Iran

4 PhD, Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran


Background: Fetal heart rate (FHR) extracted from abdominal electrocardiogram (ECG) is a powerful non-invasive method in appropriately assessing the fetus well-being during pregnancy. Despite significant advances in the field of electrocardiography, the analysis of fetal ECG (FECG) signal is considered a challenging issue which is mainly due to low signal to noise ratio (SNR) of FECG.
Objective: In this study, we present an approach for accurately locating the fetal QRS complexes in non-invasive FECG.
Materials and Methods: In this experimental study, the proposed method included 4 steps. In step 1, comb notching filter was employed to pre-process the abdominal ECG (AECG). Furthermore, low frequency noises were omitted using wavelet decomposition. In next step, principal component analysis (PCA) and signal quality assessment (SQA) were used to obtain an optimal AECG reference channel for maternal R-peaks detection. In step 3, maternal ECG (MECG) was removed from mixture signal and FECG was extracted. In final step, the extracted FECG was first decomposed by discrete wavelet transforms at level 10. Then, by employing details of levels 2, 3, 4, the new FECG signal was reconstructed in which various noises and artifacts were removed and FECG components whose frequency were close to the fetal QRS complexes remained which increased the performance of the method.
Results: For evaluation, 15 recordings of PhysioNet Noninvasive FECG database were used and the average F1 measure of 98.77% was obtained.
Conclusion: The results indicate that use of both an efficient analysis of major component of AECG along with a signal quality assessment technique has a promising performance in FECG analysis.


  1. Sameni R, Clifford GD. A Review of Fetal ECG Signal Processing; Issues and Promising Directions. Open Pacing Electrophysiol Ther J. 2010;3:4-20. doi: 10.2174/1876536x01003010004. PubMed PMID: 21614148. PubMed PMCID: 3100207.
  2. Wu S, Shen Y, Zhou Z, Lin L, Zeng Y, Gao X. Research of fetal ECG extraction using wavelet analysis and adaptive filtering. Comput Biol Med. 2013;43:1622-7. doi: 10.1016/j.compbiomed.2013.07.028. PubMed PMID: 24034754.
  3. Hasan MA, Reaz MB, Ibrahimy MI, Hussain MS, Uddin J. Detection and Processing Techniques of FECG Signal for Fetal Monitoring. Biol Proced Online. 2009;11:263-95. doi: 10.1007/s12575-009-9006-z. PubMed PMID: 19495912. PubMed PMCID: 3055800.
  4. Christov I, Simova I, Abacherli R. Extraction of the fetal ECG in noninvasive recordings by signal decompositions. Physiol Meas. 2014;35:1713-21. doi: 10.1088/0967-3334/35/8/1713. PubMed PMID: 25070127.
  5. Ghaffari A, Mollakazemi MJ, Atyabi SA, Niknazar M. Robust fetal QRS detection from noninvasive abdominal electrocardiogram based on channel selection and simultaneous multichannel processing. Australas Phys Eng Sci Med. 2015;38:581-92. doi: 10.1007/s13246-015-0381-2. PubMed PMID: 26462679.
  6. Ghaffari A, Atyabi S, Mollakazemi MJ, Niknazar M, Niknami M, Soleimani A, editors. PhysioNet/CinC Challenge 2013: a novel noninvasive technique to recognize fetal QRS complexes from noninvasive fetal electrocardiogram signals. Computing in Cardiology Conference; Zaragoza, Spain: IEEE; 2013.
  7. Liu C, Li P, Di Maria C, Zhao L, Zhang H, Chen Z. A multi-step method with signal quality assessment and fine-tuning procedure to locate maternal and fetal QRS complexes from abdominal ECG recordings. Physiol Meas. 2014;35:1665-83. doi: 10.1088/0967-3334/35/8/1665. PubMed PMID: 25069817.
  8. Goldberger AL, Amaral LA, Glass L, Hausdorff JM, Ivanov PC, Mark RG, et al. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation. 2000;101:E215-20. doi: 10.1161/01.CIR.101.23.e215. PubMed PMID: 10851218.
  9. American National Standard. ANSI/AAMI/ISO EC57 2012: Testing and reporting performance results of cardiac rhythm and ST segment. Available from:
  10. Karvounis EC, Tsipouras MG, Fotiadis DI, Naka KK. An automated methodology for fetal heart rate extraction from the abdominal electrocardiogram. IEEE Trans Inf Technol Biomed. 2007;11:628-38. doi: 10.1109/TITB.2006.888698. PubMed PMID: 18046938.
  11. Behar J, Oster J, Clifford GD, editors. Non-invasive FECG extraction from a set of abdominal sensors. Computing in Cardiology Conference; Zaragoza, Spain: IEEE; 2013.
  12. Di Maria C, Duan W, Bojarnejad M, Pan F, King S, Zheng D, Murray A, Langley Ph, editors. An algorithm for the analysis of fetal ECGs from 4-channel non-invasive abdominal recordings. Computing in Cardiology Conference; Zaragoza, Spain: IEEE; 2013.
  13. Martens SM, Rabotti C, Mischi M, Sluijter RJ. A robust fetal ECG detection method for abdominal recordings. Physiol Meas. 2007;28:373-88. doi: 10.1088/0967-3334/28/4/004. PubMed PMID: 17395993.
  14. Tompkins WJ. Biomedical digital signal processing: C-language Examples and Laboratory Experiments for the IBM PC. United States: Prentice-Hall, Inc; 1993.
  15. Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of biological signals. Phys Rev E Stat Nonlin Soft Matter Phys. 2005;71:021906. doi: 10.1103/PhysRevE.71.021906. PubMed PMID: 15783351.
  16. Pan J, Tompkins WJ. A real-time QRS detection algorithm. IEEE Transactions on Biomedical Engineering. 1985;BME-32(3):230-6. doi: 10.1109/TBME.1985.325532.
  17. Ibrahimy MI, Ahmed F, Mohd Ali MA, Zahedi E. Real-time signal processing for fetal heart rate monitoring. IEEE Trans Biomed Eng. 2003;50:258-62. doi: 10.1109/TBME.2002.807642. PubMed PMID: 12665042.
  18. Karvounis E, Papaloukas C, Fotiadis DI, Michalis L, et al. Fetal heart rate extraction from composite maternal ECG using complex continuous wavelet transform. Computers in Cardiology. 2004;31:737-40.
  19. Karvounis EC, Tsipouras MG, Fotiadis DI. Detection of fetal heart rate through 3-D phase space analysis from multivariate abdominal recordings. IEEE Trans Biomed Eng. 2009;56:1394-406. doi: 10.1109/TBME.2009.2014691. PubMed PMID: 19228552.
  20. Hasan M, Reaz M. Hardware prototyping of neural network based fetal electrocardiogram extraction. Measurement Science Review. 2012;12:52-5. doi: 10.2478/v10048-012-0007-8.
  21. Behar J, Johnson A, Clifford GD, Oster J. A comparison of single channel fetal ECG extraction methods. Ann Biomed Eng. 2014;42:1340-53. doi: 10.1007/s10439-014-0993-9. PubMed PMID: 24604619.