Adaptive Artifact Cancelation Based on Bacteria Foraging Optimization for ECG Signal

  • Agya Ram VermaEmail author
  • Yashvir Singh


In this paper, the design of adaptive artifact canceler (AAC) filter using bacteria foraging optimization (BFO) algorithm is presented. The performance of proposed AAC filter is tested on a corrupted ECG signal. Based on simulation results, it is observed that the AAC filter designed with BFO technique achieves significant improvement in fidelity parameters such as SNR, NRMSE, and NRME when compared with other reported algorithms in the literature. AAC filter based on BFO technique provides 6 dB improvement in output SNR, 85% reduction in NRMSE, and 90% lower NRME as compared to recently reported AAC filter based on ABC-SF algorithm. Further, AAC filter using BFO technique enhances the coherence between pure and reconstructed ECG signals.





The author would like to thank Dr. G.S. Sandhu (M.D.), who is a Physician and Cardiologist as well as Medical officer at PDPM IIITDM, Jabalpur (INDIA), for their valuable clinical contribution and suggestions which improved the quality of article.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

Human and Animal Rights

Authors used the data available in [23] for their study and did not collect data from any human participant or animal.


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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Govind Ballabh Pant Engineering CollegePauriIndia

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