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QRS Complexes Detection in Electrocardiogram Signals Based on Multiresolution Analysis

  • Kil-sang YooEmail author
  • Won-hyung Lee
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 179)

Abstract

In this paper, an electrocardiogram signal-processing scheme is proposed. The proposed algorithm involves morphological processing of a sampled ECG signal using Daubechies’ wavelet transform. The wavelet filter with scaling function conforms more closely to the shape of the ECG signal. QRS complexes are detected, and each complex is used to locate the peaks of the individual waves. By using this method, the detection rate of QRS complexes is close to 99.77% for the MIT/BIH arrhythmia database. The results show that the proposed method is effective, simple, suitable and accurate for practical application.

Keywords

QRS detection wavelet electrocardiogram 

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References

  1. 1.
    Zheng, X., Li, Z., Shen, L., Ji, Z.: Detection Of QRS Complexes Based On Biorthogonal Spline Wavelet. In: IEEE Computer Society International Symposium on Information Science and Engieering, Shanghai, China, December 20-22, pp. 502–506 (2008)Google Scholar
  2. 2.
    Mahmoodabadi, S.Z., Ahmadian, A., Abolhasani, M.D.: ECG Feature Extraction Using Daubechies’ Wavelets. In: Proc. of ISTEAD VIIP, pp. 343–348 (2005)Google Scholar
  3. 3.
    Li, C.W., Zheng, C.X., Tai, C.F.: Detection of ECG characteristic points using wavelet transforms. IEEE Transaction on Biomedical Eng. 42(1), 22–28 (1995)Google Scholar
  4. 4.
    Qiu, Y.Z., Ding, X.F., Feng, J.: QRS complexes detection based on Mexican-hat wavelet. Journal of Biomedical Engineering 23(6), 1347–1349 (2006)Google Scholar
  5. 5.
    Zhen, J., Zheng, X.Y., Luo, J., Li, Z.: Detection of QRS complexes based on biorthogonal spline wavelet. Journal of Shenzhen University Science and Engineering 25(2), 167–172 (2008)Google Scholar
  6. 6.
    Daubechies, I.: The wavelet transform, time-frequency localization and signal analysis. IEEE Trans. Inform. Theory, 961–1005 (1990)Google Scholar
  7. 7.
    Schluter, P., Peterson, S., Moody, G., Siegal, L., Jackson, C., Perry, D., Acarturk, E., Aumiller, J., Blake, S., Blaustein, A., Conrad, C., Heller, G., Malagold, M., Mark, R., Miklozek, C.: MIT-BIH arrhythmia database directory, Online database (1987), http://www.physionet.org/physiobank/database/html/mitdbdir/mitdbdir.html
  8. 8.
    Chen, S.-W., Chen, H.-C., Chan, H.-L.: A real-time QRS detection method based on moving-averaging incorporating with wavelet denoising. Comput. Meth. Prog. Biomed. 82(3), 187–195 (2006)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  1. 1.Chung-Ang UniversitySeoulKorea

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