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QRS Detection with Multiscale Product Using Wavelets with One and Two Vanishing Moments

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This paper proposes a performant method for R-wave detection. It is based on the analysis of ECG by the multiscale product (MP) using continuous wavelets with one and two vanishing moments. Adaptive thresholding and maxima detection allowed the localization of the QRS. The method can be applied for heart rate monitoring or being a part of a fetal ECG extraction process. Tests on real signals including abdominal ECG from pregnant women have shown that the proposed method can be effective with a preference to the one vanishing moment wavelet namely the first derivative of the Gaussian.
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ECG; Wavelet Transform; Vanishing Moments; Singularities Detection; Multiscale Product

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Nassiri, B., Latif, R., Toumanari, A., Elouaham, S., Maoulainine, F., ECG Signal De-Noising and Compression Using Discrete Wavelet Transform and Empirical Mode Decomposition Techniques, (2013) International Journal on Numerical and Analytical Methods in Engineering (IRENA), 1 (5), pp. 245-252.

M.L. Ahlstrom and W.J. Tompkins, “Automated high-speed analysis of holter tapes with microcomputers,” IEEE Trans. Biomed. Eng., vol. 30, pp. 651-657, Oct. 1983

M. Okada, “A digital filter for the QRS complex detection,” IEEE Trans. Biomed. Eng., vol. 26, pp. 700-703, Dec. 1979

B.C. Yu, S. Liu, M. Lee, C.Y. Chen, and B.N. Chiang, “A nonlinear digital filter for cardiac QRS complex detection,” J. Clin. Eng., vol. 10, pp. 193-201, 1985

Afonso VX, Tompkins WJ, Nguyen TQ, Luo S., ECG beat detection using filter banks, IEEE Trans Biomed Eng. 1999 Feb;46(2):192-202.

Benitez, D., Gaydecki, P., Zaidi, A. and Fitzpatrick, A.” The use of the Hilbert transform in ECG signal analysis”. Computers in Biology and Medicine, 2001

Y.H. Hu, W.J. Tompkins, J.L. Urrusti, and V.X. Afonso, “Applications of artificial neural networks for ECG signal detection and classification,” J. Electrocardiology, vol. 26 (Suppl.), pp. 66-73, 1993

Y. Suzuki, “Self-organizing QRS-wave recognition in ECG using neural networks,” IEEE Trans. Neural Networks, vol. 6, pp. 1469-1477, 1995

Jing- tian Tang,Xiao –li Yang, “The Algorithm of R peak detection in ECG based on empirical Mode Decompositio’, IEEE, 4th International Conference on Natural Computation, 2008

S. Z. Mahmoodabadi, A. Ahmadian, and M. D. Abolhasani, “ECG Feature Extraction using Daubechies Wavelets,” Proceedings of the fifth IASTED International conference on Visualization, Imaging and Image Processing, pp. 343-348, 2005

Addison, P. S. “Wavelet transforms and the ECG: a review”. Physiol Meas 26, R155−R199, 2005

Awadhesh Pachauri, and Manabendra Bhuyan, ‘Robust Detection of R Wave Using Wavelet Technique’, World Academy of Science, Engineering and Technology 32 2009

Sasikala P. and Wahidabanu R.S.D, “Robust R Peak and QRS detection in Electrocardiogram using Wavelet Transform”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 1,NO.6, pp.48-53,2010

R.J. Martis, U.R. Acharya, L.C. Min, “ECG beat classification using PCA, LDA, ICA and discrete wavelet transform”, Biomedical Signal Processing and Control 8 (5) 437–448 , 2013

Z. Huabin and W. Jiankang, “Real-time QRS detection method,” in Proceedings of the 10th International Conference on E-Health Networking, Applications and Services, 169–170,Singapore, July 2008.

F. Zhang and L. Yong, “Novel QRS detection by CWT for ECG sensor,” in Proceedings of the Biomedical Circuits and Systems Conference, Montreal, Canada, 2007.

Martinez J P, Almeida R, Olmos S, Rocha A P and Laguna P ”A wavelet-based ECG delineator: evaluation on standard data bases “ IEEE Trans. Biomed. Eng. 51 570–81,2004

R. Sameni and G. Clifford, “A review of fetal ECG signal processing; issues and promising directions,” The open pacing, electrophysiology & therapy journal, vol. 3, p. 4, 2010

Clifford G D, Silva I, Behar J and Moody G B “Noninvasive fetal ECG analysis” Physiol. Meas. 35 152, 2014

Y Xu, JB Weaver, DM Healy, J Lu, Wavelet transform domain filters: a spatially selective noise filtration technique. IEEE Trans Image Process 3(6), 747–758 , 1994

A Rosenfeld, A nonlinear edge detection. Proc IEEE 58, 814–816 ,1970

A. Bouzid and N. Ellouze Electroglottographic measures based on GCI and GOI detection using multiscale product, Int. J. Computer Communication, Control, vol. III, pp.21 -32 2008

R. Besrour, Z. Lachiri and N. Ellouze Using Multiscale Product for ECG Characterization in Research Letters in Signal Processing Volume 2009 Article ID 209395, 2009

S. Mallat and W. L. Hwang, “Singularity detection and processing with wavelets,” IEEE Transactions on Information Theory, vol. 38, no. 2, pp. 617–643, 1992

Massachusetts Institute of Technology, MIT-BIH ECG database,

Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New ResearchResource for Complex Physiologic Signals,


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