DOI QR코드

DOI QR Code

Characteristic wave detection in ECG using complex-valued Continuous Wavelet Transforms

  • Berdakh, Abibullaev (Department of Electronic Engineering, Graduate School, Yeungnam University) ;
  • Seo, Hee-Don (Department of Electronic Engineering, Graduate School, Yeungnam University)
  • Published : 2008.08.30

Abstract

In this study the complex-valued continuous wavelet transform (CWT) has been applied in detection of Electrocardiograms (ECG) as response to various signal classification methods such as Fourier transforms and other tools of time frequency analysis. Experiments have shown that CWT may serve as a detector of non-stationary signal changes as ECG. The tested signal is corrupted by short time events. We applied CWT to detect short-time event and the result image representation of the signal has showed us that one can easily find the discontinuity at the time scale representation. Analysis of ECG signal using complex-valued continuous wavelet transform is the first step to detect possible changes and alternans. In the second step, modulus and phase must be thoroughly examined. Thus, short time events in the ECG signal, and other important characteristic points such as frequency overlapping, wave onsets/offsets extrema and discontinuities even inflection points are found to be detectable. We have proved that the complex-valued CWT can be used as a powerful detector in ECG signal analysis.

Keywords

References

  1. Lilly LS, Pathophysiology of Heart Disease. 3rd Ed. Philadelphia, Lippincott Williams & Wilkins, pp.57-90, 2003
  2. L. Senhadji, G. Carrault, et al."Comparing Wavelet Transforms for Recognizing Cardiac Patterns", IEEE Eng Med Biol, vol.14, no.2, pp. 167-173, May 1995 https://doi.org/10.1109/51.376755
  3. Sahambi J.S, Tandon S.M and Bhatt R. K. P, "Using wavelet transforms for ECG characterization: An on-line digital signal processing system", IEEE Eng. Med. Biol. vol.16, no.1,pp.7783, Jan,1997
  4. Addison P.S., Watson J.N. et al. "Evaluating arrhythmias in ECG signals using wavelet transforms", IEEE Eng. Med. Biol., vol.19. pp.104-109. September/October 2000 https://doi.org/10.1109/51.870237
  5. S G Mallat, "A Theory for Multiresolution Signal Decomposition: The Wavelet Representation", IEEE Trans. Pattern Reco. and Machine Int., vol.11,no.7, pp.674-693, 1989 https://doi.org/10.1109/34.192463
  6. I. W. Selesnick, "The double-density dual-tree DWT," IEEE Trans. Signal Proc. 52, pp. 13041314, May. 2004
  7. K. Dubowik, and J. E. Larsson, "ECG Features Extraction - QRS Detection and Shape Recognition", Journal of Applied Computer Science, vol. 9, no. 1, pp 7-21, June 2002.
  8. S. Mallat and W. L. Hwang. "Singularity detection and processing with wavelets", IEEE Trans. Inf. Theory, vol.38, no.2, pp. 617643, March 1992
  9. S. Mallat, "A theory for multiresolution signal decomposition: the wavelet representation", IEEE Trans. Patt. Anal. Machine Intell., vol.11, no.7, pp. 674693, July 1989
  10. G.B. Moody and R.G. Mark, "The MIT-BIH arrhythmia database on CD-ROM and software for use with it", in Computers in Cardiology, IEEE Computer Society Press, pp.185-188, 1990