Power Line Interference Removal from ECG Signal Using Different IIR Filters

Rayhan Habib Jibon, Etu Podder, Abdullah Al-Mamun Bulbul

Abstract


Electrocardiogram (ECG) signal is widely and primarily used for diagnosis purpose of various cardiac diseases by the physicians. An ECG records the electrical impulses generated by the myocardium and describes the condition of the heart. A good quality ECG signal is always desirable for accurate diagnosis of a life-threatening patient. However, in real circumstances, these signals are corrupted by prominent noises, artifacts and interference like power line interference (PLI), electrode movement noise, white noise, muscle artifacts, etc., and these must be removed before diagnosis. From the above mentioned artifacts PLI is conspicuously prominent. Different IIR (Butterworth, Notch, and Chebyshev) filters are designed to remove PLI from ECG signal. Through the consecutive employment of these filters, ECG signal will become free from artifacts in a remarkable amount. After exploring the simulation results of both the output waveforms and the values of SNR, it is notified that the Notch filter is the best suited for the removal of PLI. In this paper, a comparative approach is presented for removing PLI from ECG signal using various digital filters.

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References


L. Cromewell, F. J. Weibell, and E. A. Pfeiffer, Biomedical instrumentation and measurements (Prentice Hall, 2004, pp.106107).

E.T. Gar, C. Thomas and M. Friesen, Comparison of noise sensitivity of QRS detection algorithms, IEEE Tran. Biomed. Eng., Vol. 37(Issue 1): 85-98, January 1990.

https://myhealth.alberta.ca/Health/pages/conditions.aspx?hwid=te 7147abc/ Alberta’s trusted Health Information Website. Available [online]: (viewed at 05.05.2019 at 8.00PM).

A. Doubell, The ECG atlas of cardiac rhythms, South African Medical Journal (SAMJ), vol. 107(Issue 8): 652-653, August 2017.

E. Braunwald, D. P. Zipes, P. Libby, and R.O. Bonow, Braunwald's heart disease e-book: a textbook of Cardiovascular medicine (Elsevier Health Sciences, 2014).

G. Walraven, Basic arrhythmias, (Pearson publication, 2011, pp. 1-11).

L.S. Lilly and E. Braunwald, Braunwald’s heart disease: a textbook of cardiovascular medicine, (Elsevier Health Sciences, 2012, pp. 108).

U. Biswas, A. Das, S. Debnath, and I. Oishee, ECG signal denoising by using least-mean-square and normalised-least-meansquare algorithm based Adaptive filter, International Conference on Informatics, Electronics & Vision (ICIEV), pp. 1-6, IEEE, May 2014.

H. Limaye, and V.V. Deshmukh, ECG noise sources and various noise removal techniques: a survey, International Journal of Application or Innovation in Engineering & Management, Vol. 5(Issue 2): 86-92, February 2016.

R. Panda, Removal of artifacts from Electrocardiogram using digital filter, Students Conference on Electrical, Electronics and Computer Science (SCEECS), pp. 1-4, IEEE, March 2012.

M.S. Chavan, R. Agarwala, M.D. Uplane, and M.S. Gaikwad, Design of ECG instrumentation and implementation of digital filter for noise reduction, World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin, USA, Vol. 1(Issue 157-474): 47-50, January 2004.

R. Limacher, Removal of power line interference from the ECG signal by an Adaptive digital filter, Proceedings of European Telemetry Conference, pp. 300-309, Garmisch, May 1996.

https://www.differencebetween.net/science/difference-betweeniir-and-fir-filters/ Scientific Differences Website. Available [online]: (viewed at 10.05.2019 at 9.00PM).

https://www.biopac.com/knowledge-base/iir-vs-fir-filters/ Data Acquisition, Loggers, Amplifiers, Transducers, Electrodes Website. Available [online]: (viewed at 10.05.2019 at 9.30PM).

E.C. Ifeachor and B.W. Jervis, Digital signal processing: a practical approach (Pearson Education, 2002, pp. 374-375).

http://www.physionet.org/physiobank/database/mitdb/ MIT-BIH Arrhythmia Database Website. Available [Online]: (viewed at 10.06.2019 at 11.00PM).

S. Rani, A. Kaur, and J.S. Ubhi, Comparative study of FIR and IIR filters for the removal of Baseline noises from ECG signal, 2011.

Y.W. Bai, W.Y. Chu, C.Y. Chen, Y.T. Lee, Y.C. Tsai, and C.H. Tsai, Adjustable 60Hz noise reduction by a notch filter for ECG signals, In Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference, Vol. 3, pp. 1706-1711, IEEE, May 2001.

M.A. Mneimneh, E.E. Yaz, M.T. Johnson, and R.J. Povinelli, An adaptive Kalman filter for removing baseline wandering in ECG signals, In Computers in Cardiology, IEEE, pp. 253-256, September 2006.

R.H. Jibon, E. Podder, A.A.M. Bulbul, R.N. Bairagi, M.S. Ahmed, I.A. Shohagh, Performance analysis of IIR filter in removing PLI from EEG signal, International Journal of Engineering & Technology, Vol. 7(Issue 4):5363-5367, December 2018.

C.M. Wang, and W.C. Xiao, Second-order IIR Notch Filter Design and implementation of digital signal processing system, In Applied Mechanics and Materials, Vol. 347, pp. 729-732, Trans Tech Publications.

J.G. Proakis, and D.G. Manolakis, Digital Signal Processing (PHI publication, 1998, pp.701-707).

R. Tandra, and A. Sahai, SNR walls for signal detection, IEEE Journal of selected topics in Signal Processing, Vol. 2(Issue 1): 4-17,November2008.


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