Skip to main content

A Mixed Approach for Fetal QRS Complex Detection

  • Conference paper
  • First Online:
  • 925 Accesses

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 528))

Abstract

Non-invasive fetal electrocardiogram (NI-FECG) plays an important role in detecting and diagnosing fetal diseases. Fetal electrocardiogram (FECG) is used to know the information of the fetal health. In this paper, we propose a mixed approach for extracting FECG from maternal abdominal ECG (AECG) recording. The proposed method is based on a combination of the wavelet transform and Support Vector Machines (SVM). As a first tier, the wavelet transform is used to detect maternal QRS complex from abdominal ECG recording. Then, a coherent averaging method was using to construct MECG and remove MECG from AECG recording. After removing MECG, SVM is used to locate fetal QRA complex from residual signal. The accuracy (84.53%) and Positive predictive value (PPV) (89.6%) in this study are much higher than other method.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. H.-B. Li, S.-Y. Fang, Development of internet-based home telemonitoring system for fetus. Chin. Med. Equip. J. 2, 17–19 (2006)

    Google Scholar 

  2. N. Ivanushkina, K. Ivanko E. Lysenko, et al., Fetal Electrocardiogram Extraction from Maternal Abdominal Signals (Kyiv, 2014) pp. 334–338

    Google Scholar 

  3. S.B. Barnett, D. Maulik, Guidelines and recommendations for safe use of doppler ultrasound in perinatal applications. J. Matern. Fetal Med. 10(2), 75–84 (2001)

    Article  Google Scholar 

  4. M. Sato, Y. Kimura, S. Chida et al., A novel extraction method of fetal electrocardiogram from the composite abdominal signal. IEEE Trans. Biomed. Eng. 1, 49–58 (2007)

    Article  Google Scholar 

  5. F. Andreotti, J. Behar, S. Zaunseder, J. Oster, G.D. Clifford, An open-source framework for stress-testing non-invasive foetal ecg extraction algorithms. Physiol. Meas. 37(5), 627 (2016)

    Article  Google Scholar 

  6. B. Widrow, J.R. Glover, J. McCool, J. Kaunitz, C. Williams, R. Hearn, J. Zeidler, J. Eugene Dong, R. Goodlin, Adaptive noise cancelling: principles and applications. Proc. IEEE 63, 1692–1696 (1975)

    Article  Google Scholar 

  7. J. Behar, A. Johnson, G.D. Clifford, J. Oster, A comparison of single channel foetal ECG extraction methods Ann. Biomed. Eng. 42, 1340–1353 (2014)

    Google Scholar 

  8. R. Bhoker, J.P Gawande, Fetal ECG extraction using wavelet transform. ITSI Trans. Electr. Electron. Eng. (1), 19–22 (2013)

    Google Scholar 

  9. M. Akay, E. Mulder, Examining fetal heart-rate variability using matching pursuits. IEEE Eng. Med. Biol. 15, 64–72 (1996)

    Google Scholar 

  10. C.J. James, C.W. Hesse, Independent component analysis for biomedical signals. Physiol. Meas. 26, 15–39 (2005)

    Article  Google Scholar 

  11. C. Di Maria, W.F. Duan, M. Bojarnejad, F. Pan, S. King, D.C. Zheng, A. Murray, P. Langley, An algorithm for the analysis of foetal ECGs from 4-channel non-invasive abdominal recordings. Proc. Comput. Cardiol 4, 305–308 (2013)

    Google Scholar 

  12. P.P. Kanjilal, S. Palit, G. Saha, Fetal ECG extraction from single-channel maternal ECG using singular value decomposition. IEEE Trans. Biomed 44 51–3 (1997)

    Google Scholar 

  13. R. Sameni, Extraction of fetal cardiac signals from an array of maternal abdominal recordings. Ph.D. Thesis, Sharif University of Technology—Institute National Polytechnique deGrenoble, 2008, www.sameni.info/Publications/Thesis/PhDThesis.pdf

  14. J. Behar, J. Oster, G.D. Clifford, Combining and comparing benchmarking methods of foetal ECG extraction without maternal or scalp electrode data. Physiol. Meas. 35, 1569–89 (2014)

    Google Scholar 

  15. P. Podziemski, J. Gierałtowski, Fetal heart rate discovery: algorithm for detection of fetal heart rate from noisy. Comput. Cardiol. 40, 333–336 (2013)

    Google Scholar 

  16. J. Behar, J. Oster, G.D. Clifford, Non-invasive FECG extraction from a set of abdominal sensors. Comput. Cardiol. 297–300 (2013)

    Google Scholar 

  17. P. Quan, D. Zhang, D. Guanzhong, Z. Hongcai, Two denoising methods by wavelet transform. IEEE Trans. Signal Proces. 47, 3401–6 (1999)

    Google Scholar 

  18. C. Liu, P. Li, C. Di Maria, L. Zhao, H. Zhang, Z. Chen, 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. 35, 1665–1683 (2014)

    Article  Google Scholar 

  19. C.Y. Liu, P. Li, L.N. Zhao, F.F. Liu, R.X. Wang, Real-time signal quality assessment for ECGs collected using mobile phones. Proc. Comput. Cardiol. 38 357–60 (2011)

    Google Scholar 

  20. S. Banerjee, R. Gupta, M. Mitra, Delineation of ECG characteristic features using multiresolution wavelet analysis method. Measurement 45, 474–487 (2012)

    Article  Google Scholar 

  21. R. Kahankova, R. Martinek.et al. Fetal ECG Extraction from Abdominal ECG Using RLS based Adaptive Algorithms, in 2017 18th International Carpathian Control Conference (ICCC) (IEEE Conferences, 2017)

    Google Scholar 

  22. W. Zhong, L. Liao, X. Guo, G. Wang, A deep learning approach for fetal QRS complex detection. Physiol. Meas. (9), 045004 (2018)

    Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of P. R. China under Grant No. 61375080, and the Key Program of Natural Science Foundation of Guangdong, China under Grant No. 2015A030311049. The Guangzhou science and technology project under Grant Nos. 201510010017, 201604010101.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guoli Wang .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Liao, L., Zhong, W., Guo, X., Wang, G. (2019). A Mixed Approach for Fetal QRS Complex Detection. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2018 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering, vol 528. Springer, Singapore. https://doi.org/10.1007/978-981-13-2288-4_38

Download citation

Publish with us

Policies and ethics