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Noise Reduction in ECG Signal Using Combined Ensemble Empirical Mode Decomposition Method with Stationary Wavelet Transform

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Abstract

The diagnostic study of electrocardiography (ECG) signals plays a vital role in the diagnosis of cardiac problems. But the powerline interference in ECG causes an artifact in the interpretation of the original signal. In this paper, a new method for the removal of such noise/artifact from the ECG signal by combining stationary wavelet transform with empirical mode decomposition (EMD-SWT) and ensemble empirical mode decomposition (EEMD-SWT) is proposed. SWT is applied after the decomposition of ECG signals into various intrinsic mode functions (IMFs) for further removal of noise. The proposed methods are tested for various datasets available in MIT-BIH Arrhythmia database, and the performance has been validated with existing methods. From the simulated results, it is found that combining SWT with EMD and EEMD yields better SNR enhancement when compared to the traditional methods.

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Authors and Affiliations

  1. School of Electronics Engineering, Vellore Institute of Technology, Vellore, 632014, India

    Atul Kumar Dwivedi, Himanshuram Ranjan, Advaith Menon & Prakasam Periasamy

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  1. Atul Kumar Dwivedi
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  2. Himanshuram Ranjan
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  3. Advaith Menon
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Correspondence to Prakasam Periasamy.

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Dwivedi, A.K., Ranjan, H., Menon, A. et al. Noise Reduction in ECG Signal Using Combined Ensemble Empirical Mode Decomposition Method with Stationary Wavelet Transform. Circuits Syst Signal Process 40, 827–844 (2021). https://doi.org/10.1007/s00034-020-01498-4

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