ECG Signal Denoising with SavitzkyGolay Filter and Discrete Wavelet Transform (DWT)

ECG Signal Denoising with Savitzky-Golay Filter and Discrete Wavelet Transform (DWT)

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2016 by IJETT Journal
Volume-36 Number-5
Year of Publication : 2016
Authors : Harjeet Kaur, Rajni
DOI :  10.14445/22315381/IJETT-V36P249

Citation 

Harjeet Kaur, Rajni"ECG Signal Denoising with Savitzky-Golay Filter and Discrete Wavelet Transform (DWT)", International Journal of Engineering Trends and Technology (IJETT), V36(5),266-269 June 2016. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
Electrocardiogram (ECG) demonstrates the electrical activity of heart muscles over a period of time. The ECG is one of the extensively used physiological parameters for examination and diagnosis of cardiac diseases. The non-stationary ECG signal often gets contaminated with different noises. Hence, it is required to denoise the signal to provide accurate information to physicians. In this paper, Savitzky-Golay filter and Discrete Wavelet Transform (DWT) are being used to denoise ECG signal and a comparison is provided between two methods. The filter and DWT are applied on MITBIH arrhythmia database to check the robustness of proposed methods. Two parameters, signal to noise ratio (SNR) and mean squared error (MSE) are used for performance comparison.

 References

[1] P. Bhardwaj, R. K. Choudhary, and R. Dayama, ?Analysis and classification of cardiac arrhythmia using ECG signals, International Journal of Computer Applications, vol. 38, pp. 37-40, Jan. 2012.
[2] S. T. Prasad, and S. Varadarajan, ?ECG signal analysis: different approaches,” International Journal of Engineering Trends and Technology (IJETT), vol. 7, pp. 212-216, Jan. 2014.
[3] H. Y. Lin, S. Y. Liang, Y. L. Ho, Y. H. Lin, and H. P. Ma, ?Discrete wavelet transform based noise removal and feature extraction for ECG signals, IRBM, vol. 35, pp. 351-361, 2014.
[4] Rajni, and I. Kaur, ?Electrocardiogram signal analysis- an overview, International Journal of Computer Applications, vol. 84, pp. 22-25, Dec. 2013.
[5] H. Nagendra, S. Mukherjee, and V. Kumar, ?Application of wavelet techniques in ECG signal processing: an overview, International Journal of Engineering Science and Technology (IJEST), vol. 3, pp. 7432-7443, 2011.
[6] R. J. Martis, U. R. Acharya, and H. Adeli, ?Current methods in electrocardiogram characterization, Comput. Biol. Med., vol. 48, pp. 133-149, 2014.
[7] A. Josko, and R. J. Rak, ?Effective simulation of signals for testing ECG analyser, IEEE Trans. Instrum. Meas., vol. 54, pp. 1019-1024, June 2005.
[8] L. Scharmroth, An Introduction to Electrocardiography, 7th ed., Wiley:India, 2009.
[9] N. Sooma, J. Singh, and M. Tiwari, ?Feature extraction of ECG signal using HHT algorithm, International Journal of Engineering Trends and Technology (IJETT), vol. 8, pp. 454-460, Feb. 2014.
[10] D. Sadhukhan, and M. Mitra, ?R-peak detection algorithm for ECG using double difference and RR interval processing, Procedia Technology, vol. 4, pp. 873-877, 2012.
[11] Rajni, and H. Kaur, ?Methods of electrocardiogram signal analysis to detect arrhythmia - a review, in Proc. National Conference on Communication, Computing & Systems (NCCCS-2015), Aug. 2015, p. 1-5.
[12] B. Arvinti, M. Castache, D. Toader, M. Olten, and A. Isar, ?ECG statistical denoising in the wavelet domain in ISETC, Nov. 2010, p. 307-310.
[13] J. Oster, O. Pietquin, M. Kraemer, and J. Felblinger, “Nonlinear bayesian filtering for denoising of electrocardiograms acquired in a magnetic resonance environment, IEEE Trans. Biomed. Eng., Vol. 57, pp. 1628-1638, July 2010.
[14] M. V. R. Lele, and P. K. S. Holkar, ?Removal of baseline wander from ECG signal,” in Proc. international Conference on Recent Trends in engineering & Technology-2013, Feb. 2013, p. 60-65.
[15] I. kaur, and Rajni, ?Denoising of ECG signal using filters and wavelet transform, in Proc. International Conference on Recent Trends in Electronics, Data Communication and Computing (ICRTEDC-2014), 2014, p.28-31.
[16] http://www.physionet.org/
[17] A. L. Goldberger, L. A .N. Amaral, L. Glass, J. M. Hausdroff, P. C. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C. K. Peng, and E. H. Stanely, ?PhysioBank, Physio Toolkit and PhysioNet: components of a new research resource for complex physiologic signals, Circulation, vol. 101 pp. e215-e220, 2000.
[18] R. J. Martis, U. R. Acharya, C. M. Lim, J. S. Suri, ?Characterization of ECG beats from cardiac arrhythmia using discrete cosine transform in PCA framework, Knowl.- Based Syst., vol. 45, pp. 76-82, 2013.
[19] A. Savitzky, and M. J. E. Golay, ?Smoothing and differentiation of data by simplified least squares procedures, Anal. Chem., vol. 36, pp. 1627–1639, 1964.
[20] N. Rastogi, and R. Mehra, ?Analysis of Savitzky- Golay filter for baseline wander cancellation in ECG using Wavelets, International Journal of Engineering Sciences & Emerging Technologies (IJESET), vol. 6, pp. 15-23, 2013.
[21] K. Daqrouq, and A. R. Al-Qawasmi, ?ECG Enhancement using Wavelet Transform, WSEAS Transactions on Biology and Biomedicine, vol. 7, pp. 62–72, 2010.
[22] M. AlMahamdy, and H. R. Riley, ?Performance study of different denoising methods for ECG signals, Procedia Comput. Sci., vol. 37, pp. 325-332, 2014.
[23] S. Banerjee, R. Gupta, and M. Mitra, ?Delineation of ECG characteristics features using multiresolution wavelet analysis method, Measurement, vol. 45, pp. 474-487, 2012.
[24] I. Kaur, Rajni, and G. Sikri, ?Denoising of ECG signal with different wavelets, International Journal of Engineering Trends and Technology (IJETT), vol. 9, pp. 658-661, Mar. 2014.
[25] S. Patel, and D.A. Datar, ?ECG data compression using wavelet transform, International Journal of Engineering Trends and technology (IJETT), vol. 10, pp. 770-776, Apr. 2014.

Keywords
Electrocardiogram, Savitzky-Golay Filter, Discrete Wavelet Transform, SNR, MSE.