Adaptive Artifact Cancelation Based on Bacteria Foraging Optimization for ECG Signal

Agya Ram Verma, Yashvir Singh
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引用次数: 2

Abstract

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.

Abstract Image

基于细菌觅食优化的心电信号自适应伪影消除
本文提出了一种利用细菌觅食优化(BFO)算法设计自适应伪影消除器(AAC)滤波器的方法。在损坏的心电信号上测试了所提出的AAC滤波器的性能。基于仿真结果,与文献中报道的其他算法相比,采用BFO技术设计的AAC滤波器在信噪比、NRMSE和NRME等保真度参数方面取得了显著提高。与最近报道的基于ABC-SF算法的AAC滤波器相比,基于BFO技术的AAC过滤器在输出SNR方面提供了6dB的改善,在NRMSE方面降低了85%,并且在NRME方面降低了90%。此外,使用BFO技术的AAC滤波器增强了纯ECG信号和重构ECG信号之间的相干性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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