Skip to main content
SpringerLink
Log in

Wavelet and Savitzky–Golay Filter-Based Denoising of Electrocardiogram Signal: An Improved Approach

  • Conference paper
  • First Online:
Emergent Converging Technologies and Biomedical Systems (ETBS 2022)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1040))

Abstract

Today, heart disease has reduced the chance of a human living. One of the main causes of morality is cardiovascular disease (CVD). The determination of the electrical activity of the signal is called an electrocardiogram. Different noises are present in the signal as it is being recorded. So, noise needs to be eliminated before ECG signal analysis. Various noises, including baseline wander, power line interference, and electromyogram, can be found in the ECG signal. In this article, develop a one-stage median filter to eliminate baseline wanders, Savitzky–Golay filtering (SG) and wavelet transform is employed for the elimination of artifacts from the electrocardiogram waveform is presented and the SNR (signal to noise ratio) measurements results have shown been calculated using MIT-BIH database for various records and contrasted these findings with earlier works. These suggested results outperform those found with the state of artworks.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Priya MS (2015) MATLAB based ECG signal noise removal and its analysis. Int Conf Recent Adv Eng Comput Sci IEEE

    Google Scholar 

  2. Pater C (2005) Methodological considerations in the design of trials for safety assessment of new drugs and chemical entities. Trials 6(1):1–13

    Article  Google Scholar 

  3. Jane R, Laguna P et al (1993) Adaptive baseline wander removal in the ECG: comparative analysis with cubic spline technique. In: Proceedings of computers in cardiology conference, USA, pp 143–146

    Google Scholar 

  4. Tsai T-H, Hong J-H, Wang L-H, Lee S-Y (2012) Low-power analog integrated circuits for wireless ECG acquisition systems. IEEE Trans Inf Technol Biomed 16(5):907–912

    Article  Google Scholar 

  5. Rahman MZU, Karthik GVS, Fathima SY, Lay-Ekuakille A (2013) An efficient cardiac signal enhancement using time–frequency realization of leaky adaptive noise cancelers for remote health monitoring systems. Measurement 46(10):3815–3835

    Google Scholar 

  6. Kang B, Yoo J, Park P (2013) Bias-compensated normalised LMS algorithm with noisy input. Electron Lett 49(8):538–539

    Article  Google Scholar 

  7. Taralunga DD, Gussi I, Strungaru R (2015) Fetal ECG enhancement: adaptive power line interference cancellation based on Hilbert Huang transform. Biomed Signal Process Control 19:77–84

    Article  Google Scholar 

  8. Awal MA, Mostafa SS, Ahmad M, Rashid MA (2014) An adaptive level dependent wavelet thresholding for ECG denoising. Biocybern Biomed Eng 34(4):238–249

    Article  Google Scholar 

  9. Yadav SK, Sinha R, Bora PK (2015) Electrocardiogram signal denoising using non-local wavelet transform domain filtering. IET Signal Process 9(1):88–96

    Google Scholar 

  10. Wang L-H, Chen T-Y, Lin K-H, Fang Q, Lee S-Y (2015) Implementation of a wireless ECG acquisition. IEEE J Biomed Health Informan 19(1):247–255

    Article  Google Scholar 

  11. Raheja N, Manoacha AK (2020) A study of telecardiology-based methods for detection of cardiovascular diseases. Adv Intell Syst Comput Book Ser 1124

    Google Scholar 

  12. Rahul K (2019) Signal processing techniques for removing noise from ECG signals. J Biomed Eng Res 3:101

    Google Scholar 

  13. Kumar A, Singh M (2015) Optimal selection of wavelet function and decomposition level for removal of ECG signal artifacts. J Med Imaging Health Inform 5:138–146

    Article  Google Scholar 

  14. Kumar A, Sing M (2016) Robust multiresolution wavelet analysis and window search based approach for electrocardiogram features delineation. J Med Imaging Health Inform 6:146–156

    Article  Google Scholar 

  15. Arun KS, Maheswari A, Bian G-B (2019) An intelligent learning approach for improving ECG signal classification and arrhythmia analysis. Artif Intell Med 103:101788

    Google Scholar 

  16. Amit K, Mandeep S (2016) Statistical analysis of ST segments in ECG signals for detection of ischemic episodes. In: Transactions of the institute of measurement and control, pp 1–12

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Maharaja Ranjit Singh Punjab Technical University, Bathinda, India

    Nisha Raheja & Amit Kumar Manoacha

Authors
  1. Nisha Raheja
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amit Kumar Manoacha
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amit Kumar Manoacha .

Editor information

Editors and Affiliations

  1. Jaypee University of Information Technology, Solan, India

    Shruti Jain

  2. University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, Haryana, India

    Nikhil Marriwala

  3. NITTTR Bhopal, Bhopal, India

    C. C. Tripathi

  4. Department of Electrical and Computer System Engineering, RMIT University, Melbourne, VIC, Australia

    Dinesh Kumar

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Raheja, N., Manoacha, A.K. (2023). Wavelet and Savitzky–Golay Filter-Based Denoising of Electrocardiogram Signal: An Improved Approach. In: Jain, S., Marriwala, N., Tripathi, C.C., Kumar, D. (eds) Emergent Converging Technologies and Biomedical Systems. ETBS 2022. Lecture Notes in Electrical Engineering, vol 1040. Springer, Singapore. https://doi.org/10.1007/978-981-99-2271-0_27

Download citation

Publish with us

Policies and ethics

Search

Navigation