ABSTRACT
In this work an experimental study is presented by verifying the performance of the FIR and IIR filters. These techniques have been used to eliminate the different types of intrinsic noise of the ECG signal. In order to measure the quality of the filters the MIT-BIH database and the metrics, percentage root mean square difference (PRD), signal to noise ratio (SNR) and mean square error (MSE) have been used. The results indicate that the filter IIR 7 has better quality to eliminate power line interference and base line wander.
- W. J. Tompkins, digital signal, in SpringerReference, Berlin/Heidelberg: Springer-Verlag, 2000.Google Scholar
- A. Irshad, A. D. Bakhshi, and S. Bashir, A bayesian filtering application for T-wave altemans analysis, 12th Int. Bhurban Conf. Appl. Sci. Technol. Islam. Pakistan, 13th - 17th January, pp. 222--227, 2015.Google Scholar
- S. Iravanian, U. B. Kanu, and D. J. Christini, A class of Monte-Carlo-based statistical algorithms for efficient detection of repolarization alternans, IEEE Trans. Biomed. Eng., vol. 59, no. 7, pp. 1882--1891, 2012.Google ScholarCross Ref
- S. Nemati, O. Abdala, V. Monasterio, S. Yim-Yeh, A. Malhotra, and G. D. Clifford, A nonparametric surrogate-based test of significance for T-wave alternans detection, IEEE Trans. Biomed. Eng., vol. 58, no. 5, pp. 1356--1364, 2011.Google ScholarCross Ref
- M. AlMahamdy and H. B. Riley, Performance study of different denoising methods for ECG signals, Procedia Comput. Sci., vol. 37, pp. 325--332, 2014.Google ScholarCross Ref
- U. Biswas, K. R. Hasan, B. Sana, and M. Maniruzzaman, Denoising ECG signal using different wavelet families and comparison with other techniques, 2nd Int. Conf. Electr. Eng. Inf. Commun. Technol. iCEEiCT 2015, no. May, pp. 21--23, 2015.Google ScholarCross Ref
- E. P. Haritha, C. Ganesan, M. Sumesh, A survey on modern trends in ECG noise removal techniques, 2016 Int. Conf. Circuit, Power Comput. Technol. {ICCPCT}, 2016.Google ScholarCross Ref
- M. M. Butt, U. Akram, and S. A. Khan, Denoising practices for electrocardiographic (ECG) signals: A survey, I4CT 2015 - 2015 2nd Int. Conf. Comput. Commun. Control Technol. Art Proceeding, no. I4ct, pp. 264--268, 2015.Google Scholar
- S. Thalkar, Various techniques for removal of power line interference from ECG signal, Int. J. Sci. Eng. Res., vol. 4, no. 12, pp. 12--23, 2013.Google Scholar
- A. Gacek, ECG signal processing,classification and interpretation, vol. 1. 2015. Google ScholarDigital Library
- S. Bashir, A. D. Bakhshi, and M. A. Maud, A template matched-filter based scheme for detection and estimation of t-wave alternans, Biomed. Signal Process. Control, vol. 13, no. 1, pp. 247--261, 2014.Google ScholarCross Ref
- N. Karaboga, A new design method based on artificial bee colony algorithm for digital IIR filters, J. Franklin Inst., vol. 346, no. 4, pp. 328--348, 2009.Google ScholarCross Ref
- S. Luo and P. Johnston, A review of electrocardiogram filtering, J. Electrocardiol., vol. 43, no. 6, pp. 486--496, 2010.Google ScholarCross Ref
- G. Gupta and R. Mehra, Design analysis of IIR filter for power line interference reduction in ECG signals gaurav gupta, rajesh mehra, Gaurav Gupta al Int. J. Eng. Res. Appl., vol. 3, no. 6, pp. 1309--1316, 2013.Google Scholar
- N. Karaboga, Digital IIR filter design using differential evolution algorithm, EURASIP J. Adv. Signal Process., vol. 2005, no. 8, pp. 1269--1276, 2005. Google ScholarDigital Library
- V. Kumar, S. C. Saxena, V. K. Giri, and D. Singh, Improved modified AZTEC technique for ECG data compression: Effect of length of parabolic filter on reconstructed signal, Comput. Electr. Eng., vol. 31, no. 4--5, pp. 334--344, 2005. Google ScholarDigital Library
- S. K. Mukhopadhyay, S. Mitra, and M. Mitra, A lossless ECG data compression technique using ASCII character encoding, Comput. Electr. Eng., vol. 37, no. 4, pp. 486--497, 2011. Google ScholarDigital Library
- J. A. Van Alsté and T. S. Schilder, Removal of base-line wander and power-line interference from the ECG by an efficient FIR filter with a reduced number of taps, IEEE Trans. Biomed. Eng., vol. BME-32, no. 12, pp. 1052--1060, 1985.Google ScholarCross Ref
- I. T. Rodríguez, Y. P. García, A. M. Mezher, and A. T. Crispi, Implementación de filtros FIR para procesar señales biomédicas con PSoC, no. June 2014, 2009.Google Scholar
- M. S. Chavan, R. A. Agarwala, and M. D. Uplane, Interference reduction in ECG using digital FIR filters based on rectangular window, WSEAS Trans. SIGNAL Process., vol. 4, no. 5, pp. 340--349, 2008. Google ScholarDigital Library
- N. Mbachu, C B, and N. Offor, K J, "Eduction of powerline noise in ECG signal using FIR digital filter implemented with hamming window, Int. J. Sci. Environ. Technol., vol. 2, no. 6, pp. 1380--1387, 2013.Google Scholar
- N. Singh, S. Ayub, and J. P. Saini, Design of digital IIR filter for noise reduction in ECG signal, Proc. - 5th Int. Conf. Comput. Intell. Commun. Networks, CICN 2013, pp. 171--176, 2013. Google ScholarDigital Library
- M. A. Al-Alaoui, Linear phase low-pass IIR digital differentiators, IEEE Trans. Signal Process., vol. 55, no. 2, pp. 697--706, 2007. Google ScholarCross Ref
- M. S. Chavan, R. Aggarwala, and M. Uplane, Suppression of baseline wander and power line interference in ECG Using digital IIR filter, Int. J. Circuits, Syst. Signal Process., vol. 2, no. 2, pp. 356--65, 2008.Google Scholar
- M. Choudhary and R. Narwaria, Suppression of noise in ECG signal using low pass IIR filters, Int. J. Electron. Comput. Sci. Eng., vol. 1, pp. 2238--2243, 2012.Google Scholar
- M. Kaur, Comparison of different approaches for removal of baseline wander from ECG signal comparisons of different approaches for removal of baseline wander from ECG signal, no. January 2011, 2015.Google Scholar
- O. Ondracek and J. Pucik, International Conference Trends in Biomedical Engineering, vol. 123, no. May 2014, pp. 3--9, 2005.Google Scholar
- G. Sreedevi and B. Anuradha, Using of Fir and IIR filters for noise removal from ecg signal: a performance analysis, Int. J. Electron. Commun. Eng. Technol., vol. 7, no. 4, pp. 91--99, 2016.Google Scholar
- S. H. Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, PhysioBank, physiotoolkit, and physionet components of a new research resource for complex physiologic signals, Circulation, vol. 101, no. 23, pp. 215--220, 2000.Google Scholar
Index Terms
- ECG Denoising by using FIR and IIR Filtering Techniques: An Experimental Study
Recommendations
Design of mixed IIR/FIR Two-channel QMF bank
A general family of mixed IIR/FIR two-channel QMF filter banks (FB) with near perfect reconstruction (NPR) is presented. The design method is general in the sense that all possible distortions (aliasing, imaging, amplitude and phase distortions) can be ...
Statistical Approach to Compare Image Denoising Techniques in Medical MR Images
AbstractIn medical image processing, magnetic resonance (MR) imaging techniques play an important role. The images acquired are usually affected from various noise such as gaussian noise, salt and pepper noise, speckle noise, periodic noise etc. Therefore,...
A correlative criterion for the stability of sigma-delta based IIR filter: application to an FIR-like bit-stream filter
ICECS'03: Proceedings of the 2nd WSEAS International Conference on Electronics, Control and Signal ProcessingRecently we have proposed a structure for single-bit filtering. This structure contains a ternary finite-impulse-response filter cascaded with a first-order infinite-impulse-response (IIR) filter. The recursive IIR filter contains a sigma-delta ...
Comments