Skip to main content

Advertisement

Log in

A novel approach to the extraction of fetal electrocardiogram based on empirical mode decomposition and correlation analysis

  • Scientific Paper
  • Published:
Australasian Physical & Engineering Sciences in Medicine Aims and scope Submit manuscript

Abstract

Fetal heart rate monitoring is the process of checking the condition of the fetus during pregnancy and it would allow doctors and nurses to detect early signs of trouble during labor and delivery. The fetal ECG (FECG) signal is so weak and also is corrupted by other signals and noises, mainly by maternal ECG signal. It is so hard to acquire a noise-free, precise and reliable FECG using the conventional methods. In this study, a combination of empirical mode decomposition (EMD) algorithms, correlation and match filtering is used for extracting FECG from maternal abdominal ECG signals. The proposed method benefits from match filtering ability to detect fetal signal and QRS complex to detect weak QRS peaks. The combined method, has been applied successfully on different signal qualities, even for signals that their analysis was hard and complicated for other methods. This method is able to detect R-R intervals with high accuracy. It was proved that the complete ensemble empirical mode decomposition method provides a better frequency resolution of modes and also requires less iterations that leads to a considerably less computational cost than EMD and ensemble empirical mode decomposition and can reconstruct the FECG completely from the calculated modes. We believe that this method opens a new field in non-invasive maternal abdominal signal processing so the FECG signal could be extracted with high speed and accuracy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Cunningham F, Leveno K, Bloom S, Spong CY, Dashe J (2014) Williams obstetrics, 24th edn. McGraw-Hill, New York

    Google Scholar 

  2. Zarzoso V, Nandi AK (2001) Noninvasive fetal electrocardiogram extraction: blind separation versus adaptive noise cancellation. IEEE Trans Biomed Eng 48(1):12–18

    Article  CAS  PubMed  Google Scholar 

  3. Groome LJ, Mooney DM, Holland SB, Smith LA, Atterbury JL, Loizou PC (1999) Human fetuses have nonlinear cardiac dynamics. J Appl Phys 87(2):530–537

    CAS  Google Scholar 

  4. Ghobadi Azbari P, Mohaqeqi S, Ghanbarzadeh Gashti N, Mikaili M (2016) Introducing a combined approach of empirical mode decomposition and PCA methods for maternal and fetal ECG signal processing. J Matern Fetal Neonatal Med 29(19):3104–3109

    Google Scholar 

  5. Yin Y, Ye M, Ren D, Zhu Y, Yang C (2010) FECG extraction using bayesian inference and neural networks approximation. J Comput Inf Syst 6(6):1769–1778

    Google Scholar 

  6. Ali MAS, Zeng X (2010) A novel technique for extraction foetal electrocardiogram using adaptive filtering and simple genetic algorithm. Am J Biostat 1(2):75

    Google Scholar 

  7. Kezi Selva Vijiila C, Kanagasabapathy P (2008) Intelligent technique of canceling maternal ECG in FECG extraction. Iran J Fuzzy Syst 5(1):27–45

    Google Scholar 

  8. Li Y, Yi Z (2008) An algorithm for extracting fetal electrocardiogram. Neurocomputing 71(7):1538–1542

    Article  Google Scholar 

  9. Nazarpour K, Ebadi S, Sanei S (2007) Fetal electrocardiogram signal modelling using genetic algorithm. In: 2007 IEEE international workshop on medical measurement and applications, 2007. IEEE, pp 1–4

  10. Lee J, Park K, Lee K (2005) Temporally constrained ICA-based foetal ECG separation. Electron Lett 41(21):1

    Article  Google Scholar 

  11. Pu X, Zeng X, Han L, Chen J (2009) Extraction of fetal electrocardiogram signal using least squares support vector machines. J Electron Inf Technol 31(12):2941–2947

    Google Scholar 

  12. Huang NE, Shen Z, Long SR, Wu MC, Shih HH, Zheng Q, Yen N-C, Tung CC, Liu HH (1998) The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. In: Proceedings of the Royal Society of London A: mathematical, physical and engineering sciences, 1998, vol 1971. The Royal Society, pp 903–995

  13. Wu Z, Huang NE (2009) Ensemble empirical mode decomposition: a noise-assisted data analysis method. Adv Adapt Data Anal 1(01):1–41

    Article  Google Scholar 

  14. Li N, Li P (2009) An improved algorithm based on EMD-wavelet for ECG signal de-noising. In: International joint conference on computational sciences and optimization, 2009. CSO 2009. IEEE, pp 825–827

  15. Torres ME, Colominas MA, Schlotthauer G, Flandrin P (2011) A complete ensemble empirical mode decomposition with adaptive noise. In: 2011 IEEE International conference on acoustics, speech and signal processing (ICASSP), 2011. IEEE, pp 4144–4147

  16. Jezewski J, Matonia A, Kupka T, Roj D, Czabanski R (2012) Determination of fetal heart rate from abdominal signals: evaluation of beat-to-beat accuracy in relation to the direct fetal electrocardiogram. Biomed Tech Biomed Eng 57(5):383–394

    Article  Google Scholar 

  17. Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE (2000) PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation [Online] 101(23):e215–e220

    Article  CAS  Google Scholar 

  18. Nimunkar AJ, Tompkins WJ (2007) EMD-based 60-Hz noise filtering of the ECG. In: 2007 29th annual international conference of the IEEE Engineering in Medicine and Biology Society, 2007. IEEE, pp 1904–1907

  19. Kotas M (1996) A new method of fetal QRS detection. Biocybern Biomed Eng 16(3–4):147–163

    Google Scholar 

  20. Xue Q, Hu YH, Tompkins WJ (1992) Neural-network-based adaptive matched filtering for QRS detection. IEEE Trans Biomed Eng 39(4):317–329

    Article  CAS  PubMed  Google Scholar 

  21. Sameni R, Clifford GD, Jutten C (2007) Shamsollahi MB (2007) multichannel ECG and noise modeling: application to maternal and fetal ECG signals. EURASIP J Appl Signal Process 1:94–94

    Google Scholar 

  22. http://www.physionet.org/physiobank/database/adfecgdb

  23. Karvounis EC, Tsipouras MG, Fotiadis DI, Naka KK (2007) An automated methodology for fetal heart rate extraction from the abdominal electrocardiogram. IEEE Trans Inf Technol Biomed 11(6):628–638

    Article  PubMed  Google Scholar 

  24. Azad KAK Fetal QRS (2000) complex detection from abdominal ECG: a fuzzy approach, In: Proceedings of IEEE nordic signal processing symposium. Kolmarden, Sweden, 2000. pp 275–278

  25. Pieri J, Crowe J, Hayes-Gill B, Spencer C, Bhogal K, James D (2001) Compact long-term recorder for the transabdominal foetal and maternal electrocardiogram. Med Biol Eng Comput 39(1):118–125

    Article  CAS  PubMed  Google Scholar 

  26. Ibrahimy MI, Ahmed F, Ali MM, Zahedi E (2003) Real-time signal processing for fetal heart rate monitoring. IEEE Trans Biomed Eng 50(2):258–261

    Article  PubMed  Google Scholar 

  27. Martens SM, Rabotti C, Mischi M, Sluijter RJ (2007) A robust fetal ECG detection method for abdominal recordings. Physiol Meas 28(4):373

    Article  PubMed  Google Scholar 

  28. Karvounis EC, Tsipouras MG, Fotiadis DI (2009) Detection of fetal heart rate through 3-D phase space analysis from multivariate abdominal recordings. IEEE Trans Biomed Eng 56(5):1394–1406

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Ethics declarations

Conflicts of interest

The authors declare that there is no conflict of interest regarding the publication of this article.

Ethical approval

This article does not contain any studies with human or animal subjects performed by any of the authors.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ghobadi Azbari, P., Abdolghaffar, M., Mohaqeqi, S. et al. A novel approach to the extraction of fetal electrocardiogram based on empirical mode decomposition and correlation analysis. Australas Phys Eng Sci Med 40, 565–574 (2017). https://doi.org/10.1007/s13246-017-0560-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13246-017-0560-4

Keywords

Navigation