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Denoising of ECG Signals Using FIR & IIR Filter: a Performance Analysis

8 pagesPublished: October 23, 2018

Abstract

Electrocardiogram (ECG) signal is a bio-electrical activity of the heart. It is a common routine and important cardiac diagnostic tool where in electrical signals are measured and recorded to know the functional status of heart, but ECG signal can be distorted with noise as, various artifacts corrupt the original ECG signal and reduces it quality. Therefore, there is a need to remove such artifacts from the original signal and improve its quality for better interpretation. Digital filters are used to remove noise error from the low frequency ECG signal and improve the accuracy the signal. Noise can be any interference due to motion artifacts or due to power equipment that are present where ECG had been taken. Thus, ECG signal processing has become a prevalent and effective tool for research and clinical practices. This paper presents the comparative analysis of FIR and IIR filters and their performances from the ECG signal for proper understanding and display of the ECG signal.

Keyphrases: Baseline Noises, ECG, FIR filters, IIR filters, noise

In: Vinay K Chandna, Vijay Singh Rathore and Shikha Maheshwari (editors). Proceedings on International Conference on Emerging Trends in Expert Applications & Security (2018), vol 2, pages 51--58

Links:
BibTeX entry
@inproceedings{ICETEAS2018:Denoising_of_ECG_Signals,
  author    = {Chhavi Saxena and Vivek Upadhyaya and Hemant Kumar Gupta and Avinash Sharma},
  title     = {Denoising of ECG Signals Using FIR \textbackslash{}\& IIR Filter: a Performance Analysis},
  booktitle = {Proceedings on International Conference on Emerging Trends in Expert Applications \textbackslash{}\& Security (2018)},
  editor    = {Vinay K Chandna and Vijay Singh Rathore and Shikha Maheshwari},
  series    = {Kalpa Publications in Engineering},
  volume    = {2},
  pages     = {51--58},
  year      = {2018},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1770},
  url       = {https://easychair.org/publications/paper/XPR3},
  doi       = {10.29007/tgtg}}
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