Adaptive Artifact Cancelation Based on Bacteria Foraging Optimization for ECG Signal
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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.
KeywordsAAC filter ABC BFO ECG MPSO PSO
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  for their study and did not collect data from any human participant or animal.
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