Adaptive filtering using PSO, MPSO and ABC algorithms for ECG signal. (2016)

• Record Type: Journal Article
• Authors: Verma, Agya Ram; Singh, Yashvir; Joshi, Vivek
• Is Part Of: International journal of biomedical engineering and technology. Volume 21:Number 4(2016)
• Page Start: 379
• Page End: 392
• Publication Date: 2016
• Subjects: ECG signals -- electrocardiograms -- ANC -- adaptive noise canceller -- particle swarm optimisation -- MPSO -- modified PSO -- ABC -- artificial bee colony -- SNR -- signal-to-noise ratio -- adaptive filtering -- simulation; Biomedical engineering -- Periodicals; 610.28
• Languages: English
• ISSNs: 1752-6418

Abstract

In this paper, the design of Adaptive Noise Canceller (ANC) filter using evolutionary algorithms such as Particle Swarm Optimisation (PSO), Modified PSO (MPSO) and Artificial Bee Colony (ABC) algorithms is presented. The performance of proposed ANC filter is tested on a corrupted ECG signal. Based on simulation results, it is observed that the ANC filter constructed using these evolutionary algorithms achieves significant improvement in fidelity parameters such as SNR, MSE, ME and correlation factor when compared with other reported techniques in literature. ANC filter based on ABC with scaling factor provides 78% improvement in output SNR, 76% and 87% reduction in MSE and ME, respectively, as compared to ANC filter based on PSO. Further, ANC filter designed using ABC technique enhances the correlation between output and pure ECG signal.