Noise Cancelation Using Adaptive Filter

  • Akhilesh Kumar RavatEmail author
  • Amit Dhawan
  • Manish Tiwari
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 587)


Adaptive filtering creates one of the core technologies in the field of the digital signal processing and finds various applications in the area of science and technology, viz., adaptive noise cancelation, echo cancelation, channel equalization, bio-medical signal processing, etc. The principal objective of the noise cancelation is based on elimination of noise from audio as well as ECG (Electrocardiogram) signals. In this paper, an adaptive ECG filter is introduced to reduce the noise originated by body artifacts and exterior systems. The type of noises include interference caused by power line, interference caused by other electronic equipment, noise from electrode contact, and removing of movement of patient by adaptive filter to produce best results.


Noise Adaptive algorithm Adaptive filter ANC LMS NLMS ECG 


  1. 1.
    Sahu, K., Sinha, R.: Simulation of NLMS adaptive filter for noise cancellation. Int. J. Eng. Appl. Sci. (IJEAS), ISSN: 2394-3661Google Scholar
  2. 2.
    He, Y., He, H., Li, L., Wu, Y., Pan, H.: The applications and simulation of adaptive filter in noise canceling. In: 2008 International Conference on Computer Science and Software Engineering, vol. 4, pp. 1–4. IEEE (2008)Google Scholar
  3. 3.
    Ardalan, S., Moghadami, S., Jaafari, S.: Motion noise cancelation in heartbeat sensing using accelerometer and adaptive filter. IEEE Embed. Syst. Lett. 7(4), 101–104 (2015)CrossRefGoogle Scholar
  4. 4.
    Ramos, R., Mànuel-Làzaro, A., Del Río, J., Olivar, G.: FPGA-based implementation of an adaptive canceller for 50/60-Hz interference in electrocardiography. IEEE Trans. Instrum. Meas. 56(6), 2633–2640 (2007)CrossRefGoogle Scholar
  5. 5.
    Haykin, S.S.: Adaptive Filter Theory. Pearson Education India (2008)Google Scholar
  6. 6.
    Proakis, J.G.: Digital Signal Processing: Principles Algorithms and Applications. Pearson Education India (2001)Google Scholar
  7. 7.
    Sehamby, R., Singh, B.: Noise Cancellation using Adaptive Filtering in ECG Signals: Application to Biotelemetry. Int. J. Bio-Sci. Bio-Technol. 8(2), 237–244 (2016)CrossRefGoogle Scholar
  8. 8.
    Zarzoso, V., Nandi, A.K.: Noninvasive fetal electrocardiogram extraction: blind separation versus adaptive noise cancellation. IEEE Trans. Biomed. Eng. 48(1), 12–18 (2001)CrossRefGoogle Scholar
  9. 9.
    Khamene, A., Negahdaripour, S.: A new method for the extraction of fetal ECG from the composite abdominal signal. IEEE Trans. Biomed. Eng. 47(4), 507–516 (2000)CrossRefGoogle Scholar
  10. 10.
    Li, C., Zheng, C., Tai, C.: Detection of ECG characteristic points using wavelet transforms. IEEE Trans. Biomed. Eng. 42(1), 21–28 (1995)CrossRefGoogle Scholar
  11. 11.
    Kanjilal, P.P., Palit, S., Saha, G.: Fetal ECG extraction from single-channel maternal ECG using singular value decomposition. IEEE Trans. Biomed. Eng. 44(1), 51–59 (1997)CrossRefGoogle Scholar
  12. 12.
    Moody, G.B., Mark, R.G.: QRS morphology representation and noise estimation using the Karhunen-Loeve transform. In: Computers in Cardiology 1989, Proceedings, pp. 269–272. IEEE (1989)Google Scholar
  13. 13.
    Barros, A.K., Mansour, A., Ohnishi, N.: Removing artifacts from electrocardiographic signals using independent components analysis. Neurocomputing 22(1–3), 173–186 (1998)CrossRefGoogle Scholar
  14. 14.
    He, T., Clifford, G., Tarassenko, L.: Application of independent component analysis in removing artefacts from the electrocardiogram. Neural Comput. Appl. 15(2), 105–116 (2006)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Akhilesh Kumar Ravat
    • 1
    Email author
  • Amit Dhawan
    • 1
  • Manish Tiwari
    • 1
  1. 1.Department of Electronics and Communication EngineeringMotilal Nehru National Institute of TechnologyAllahabadIndia

Personalised recommendations