Abstract
Electrocardiogram (ECG) signal is the electrical recording of coronary heart activity. It is a common routine and vital cardiac diagnostic tool in which in electric signals are measured and recorded to recognize the practical status of heart, but ECG signal can be distorted with noise as numerous artifacts corrupt the unique ECG signal and decrease it quality. Consequently, there may be a need to eliminate such artifacts from the authentic signal and enhance its quality for better interpretation. ECG signals are very low-frequency signals of approximately 0.5–100 Hz, and digital filters are used as efficient approach for noise removal of such low-frequency signals. Noise may be any interference because of movement artifacts or due to power device that are present, wherein ECG has been taken. Consequently, ECG signal processing has emerged as a common and effective tool for research and clinical practices. This paper gives the comparative evaluation of FIR and IIR filters and their performances from the ECG signal for proper understanding and display of the ECG signal.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
R.S. Khandpur, Biomedical instrumentation hand book, in 11th reprint 2008 Tata McGraw—Hill publication company Limited (New Delhi, 2008). ISBN-13: 978-0-07-0473355-3
S.J. Chapman, MATLAB Programming for Engineers. 3rd Reprint Edn 2003 by Thomson Asia Pte Ltd. (Singapore, 2003). ISBN: 981-240-606-9
P. Malindi, Cancelling power line interference in electrophysiological signals. ECT Res. J. (2002)
B. Widrow, M.E. Hoff, Adaptive switching circuits, in IREWESCON Convention Record (New York, 1960), pp. 96–104
Z. Jiashu, T. Heng-Ming, Adaptive noise cancellation algorithm for speech processing. IEEE Trans. 2489–2492 (2007)
J.H. Shah, J.M. Joshi, Digital Signal Processing (University science press laxmi publication company Limited, New Delhi)
S.M.M. Martens, M. Mischi, S.G. Oei, An improved adaptive power line interference canceller for electrocardiography. IEEE Trans. Biomed. Eng. 53(11) Nov 2006
S.Z. Islam, S.Z. Islam, R. Jidin, M.A.M. Ali, Performance study of adaptive filtering algorithms for noise cancellation of ECG signal. IEEE (2009)
K. Buckley, ECE5251 Biomedical Signal Processing (2009)
K. Nishikawa, H. Kiya, Noval implementation technique of RLS algorithm for improving throughtput of adaptive filters (1999)
A.H. Sayed, Adaptive Filters (2008)
Hayes M.H., Statistical digital signal processing and modeling (Wiley, 1996)
S. Chandra, A. Sharma, A computationally efficient approach for ECG signal denoising and data compression, in 2017 IEEE 8th Control and System Graduate Research Colloquium (ICSGRC) (IEEE, 2017), pp. 22–27
A. Hashemi, M. Rahimpour, M.R. Merati, Dynamic Gaussian filter for muscle noise reduction in ECG signal. in 2015 23rd Iranian Conference on Electrial Engineering (ICEE) (IEEE, 2015), pp. 120–124
C. Lastre-Domínguez, Y.S. Shmaliy, O. Ibarra-Manzano, L.J. Morales-Mendoza, Unbiased FIR denoising of ECG signals. In: 2017 14th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE) (IEEE, 2017), pp. 1–6
H.D. Hesar, M. Mohebbi, ECG denoising using marginalized particle extended kalman filter with a automaticparticle weightingstrategy. IEEE J. Biomed. Health Inf. 21(3)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Saxena, C., Srivastava, R., Arora, D.P. (2022). Performance Analysis of FIR and IIR Filters Using ECG Signals. In: Pundir, A.K.S., Yadav, N., Sharma, H., Das, S. (eds) Recent Trends in Communication and Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-1324-2_34
Download citation
DOI: https://doi.org/10.1007/978-981-19-1324-2_34
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-1323-5
Online ISBN: 978-981-19-1324-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)