Skip to main content
SpringerLink
Log in

Cancellation of Powerline Interference from Biomedical Signals Using an Improved Affine Projection Algorithm

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

Powerline contamination of recorded signals represents a major source of noise in electrophysiology and impairs the use of recordings for research. Furthermore it degrades the signal quality and overwhelms tiny features that may be critical for clinical monitoring and diagnosis. During last years, notch filters and adaptive cancellers have been suggested to suppress this interference. In this article we present an improved adaptive canceller for the reduction of the fundamental powerline interference component and harmonics in electrocardiogram (ECG) and electrocardiograph (EEG) recordings. In this new ECG and EEG denoising approach is used an affine projection (AP) algorithm based on Gauss–Seidel method. The results show that the proposed method is able to reduce powerline interference from the noisy ECG and EEG signals more accurately and consistently in comparison to some of the state of-the-art methods. Furthermore, AP can be efficiently used with very low signal-to-noise ratios, while preserving original signal waveform.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. F. Albu, M. Bouchard, Y. Zakharov, Pseudo-affine projection algorithms for multichannel active noise control. IEEE Trans. Audio Speech Lang. Process. 15(3), 1044–1052 (2007)

    Article  Google Scholar 

  2. R. Barrett, M. Berry, T.F. Chan, J. Demmel, J.M. Donato, J. Dongarra, V. Eijkhout, R. Pozo, C. Romine, H.V. der Vorst, Templates for the Solutions of Linear Systems: Building Blocks for Iterative Methods, 2nd edn. (SIAM, Philadelphia, 1994)

    Book  Google Scholar 

  3. M. Bouchard, The gauss-seidel fast affine projection algorithm for multichannel active noise control and sound reproduction systems. IEEE Trans. Speech Audio Process. 11(1), 54–60 (2003)

    Article  Google Scholar 

  4. J. Bronzino, The Biomedical Engineering Handbook, 2nd edn. (CRC Press, Springer, 2000)

    Google Scholar 

  5. T. Degen, H. Jackel, Enhancing interference rejection of preamplified electrodes by automated gain adaption. IEEE Trans. Biomed. Eng. 51(11), 2031–2039 (2004)

    Article  Google Scholar 

  6. A.L. Goldberger, L.A.N. Amaral, L. Glass, J.M. Hausdorff, P.Ch. Ivanov, R.G. Mark, J.E. Mietus, G.B. Moody, C.-K. Peng, H.E. Stanley, PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation. (2000). 101(23):e215–e220 (June 13). Circulation electronic pages: http://circ.ahajournals.org/cgi/content/full/101/23/e215

  7. P.S. Hamilton, A comparison of adaptive and non-adaptive filters for reduction of power line interference in the ECG. IEEE Trans. Biomed. Eng. 43(1), 105–109 (1996)

    Article  Google Scholar 

  8. S. Haykin, Adaptive Filter Theory, 5th edn. (Prentice-Hall, Englewood Cliffs, 2013)

    Google Scholar 

  9. C.C. Huang, S.F. Liang, M.S. Young, F.Z. Shaw, A novel application of the s-transform in removing powerline interference from biomedical signals. Physiol. Meas. 30(1), 13–27 (2009)

    Article  Google Scholar 

  10. Y.Z. Ider, M.C. Saki, H. Alper Guer, Removal of power line interference in signal-averaged electrocardiography systems. IEEE Trans. Biomed. Eng. 42(7), 731–735 (1995)

    Article  Google Scholar 

  11. E. Laciar, R. Jané, D.H. Brooks, Improved alignment method for noisy high-resolution ecg and holter records using multiscale crosscorrelation. IEEE Trans. Biomed. Eng. 50(3), 344–353 (2003)

    Article  Google Scholar 

  12. J.M. Leski, N. Henzel, ECG baseline wander and powerline interference reduction using non-linear filter bank. Signal Process. 85(4), 781–793 (2005)

    Article  MATH  Google Scholar 

  13. W. Li, The convergence of the modified gauss-seidel methods for consistent linear systems. J. Comput. Appl. Math. 154(1), 97–105 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  14. G. Li, X. Zeng, X. Zhou, Y. Zhou, G. Liu, X. Zhou, Robust suppression of non-stationary power-line interference in electrocardiogram signals. Physiol. Meas. 33(7), 1151–1169 (2012)

    Article  Google Scholar 

  15. G. Luo, Wavelet notch filter design of spread-spectrum communication systems for high-precision wireless positioning. Circ. Syst. Signal Process. 31, 651–668 (2012)

    Article  Google Scholar 

  16. S.M.M. Martens, M. Mischi, S.G. Oei, J.W.M. Bergmans, An improved adaptive power line interference canceller for electrocardiography. IEEE Trans. Biomed. Eng. 53(11), 2220–2231 (2006)

    Article  Google Scholar 

  17. J. Mateo, A. Torres, M.A. García, C. Sánchez, R. Cervigon, Robust volterra filter design for enhancement of electroencephalogram signal processing. Circ. Syst. Signal Process. 32(1), 233–253 (2013)

    Article  Google Scholar 

  18. J. Mateo, A.M. Torres, M.A. García, Dynamic fuzzy neural network based learning algorithms for ocular artefact reduction in eeg recordings. Neural Process. Lett. 39(1), 45–67 (2014)

    Article  Google Scholar 

  19. S. Nikolić, G. Stancić, Design of IIR notch filter with approximately linear phase. Circ. Syst. Signal Process. 31(6), 2119–2131 (2012)

    Article  Google Scholar 

  20. K. Ozeki, T. Umeda, An adaptive filtering algorithm using an orthogonal projection to an affine subspace and its properties. Electron. Commun. Jpn. 67–A, 126–132 (1984)

    MathSciNet  Google Scholar 

  21. S.C. Pei, C.C. Tseng, Elimination of AC interference in electrocardiogram using IIR notch filter with transient suppression. IEEE Trans. Biomed. Eng. 42(11), 1128–1132 (1995)

    Article  Google Scholar 

  22. S. Poornachandra, N. Kumaravel, A novel method for the elimination of power line frequency in ECG signal using hyper shrinkage function. Digit. Signal Process. 18(2), 116–126 (2008)

    Article  Google Scholar 

  23. J.G. Proakis, D.G. Manolakis, Digital Signal Processing: Principles, Algorithms and Applications, 3rd edn. (Prentice-Hall, Englewood Cliffs, 1996)

    Google Scholar 

  24. R.M. Rangayyan, Biomedical Signal Analysis: A Case-Study Approach, IEEE Press Series in Biomedical Engineering (IEEE Press, Wiley, 2002)

    Google Scholar 

  25. R. Sameni, M.B. Shamsollahi, C. Jutten, G.D. Clifford, A nonlinear bayesian filtering framework for ECG denoising. IEEE Trans. Biomed. Eng. 54(12), 2172–2185 (2007)

    Article  Google Scholar 

  26. L. Sörnmo, P. Laguna, Bioelectrical Signal Processing in Cardiac and Neurological Applications (Elsevier Academic Press, Amsterdam, 2005)

    Google Scholar 

  27. C.C. Tseng, S.C. Pei, Stable IIR notch fiter design with optimal pole placement. IEEE Trans. Signal Process. 48(11), 2673–2681 (2001)

    Article  MathSciNet  Google Scholar 

  28. Y. Wu, R.M. Rangayyan, Y. Zhouc, S.C. Ngd, Filtering electrocardiographic signals using an unbiased and normalized adaptive noise reduction system. Med. Eng. Phys. 31(1), 17–26 (2009)

    Article  Google Scholar 

  29. L. Xu, Cancellation of harmonic interference by baseline shifting of wavelet packet decomposition coefficients. IEEE Trans. Signal Process. 53(1), 222–230 (2005)

    Article  MathSciNet  Google Scholar 

  30. A.K. Ziarani, A. Konrad, A nonlinear adaptive method of elimination of power line interferences in ECG signals. IEEE Trans. Biomed. Eng. 49(6), 540–547 (2002)

    Article  Google Scholar 

Download references

Acknowledgments

This work was sponsored by University of Castilla-La Mancha, the project PI10/01215 from Instituto de Salud Carlos III and Virgen de la Luz Hospital of Cuenca (Spain).

Author information

Authors and Affiliations

  1. Polytechnic School, University of Castilla-La Mancha, Cuenca, Spain

    A. M. Torres & J. Mateo

  2. Clinical Neurophysiology Service, Virgen de la Luz Hospital, Cuenca, Spain

    M. A. García

  3. Clinical Psychiatry Service, Virgen de la Luz Hospital, Cuenca, Spain

    J. L. Santos

Authors
  1. A. M. Torres
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. Mateo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. A. García
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. J. L. Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. M. Torres.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Torres, A.M., Mateo, J., García, M.A. et al. Cancellation of Powerline Interference from Biomedical Signals Using an Improved Affine Projection Algorithm. Circuits Syst Signal Process 34, 1249–1264 (2015). https://doi.org/10.1007/s00034-014-9890-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-014-9890-6

Keywords

Search

Navigation