A New ECG Denoising Technique Based on LWT and TVM
In: Circuits, Systems, and Signal Processing, Jg. 40 (2021-07-19), S. 6284-6300
Online
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Zugriff:
In this paper, we propose a new technique of Electrocardiogram ( $${\text{ECG}}$$ ) denoising based on Lifting Wavelet Transform ( $${\text{LWT}}$$ ) and Total Variation Minimization ( $${\text{TVM}}$$ ). The first step of this technique consists in applying the $${\text{LWT}}$$ to the noisy $${\text{ECG}}$$ signal for obtaining three wavelet sub-bands, $$cD_{1}$$ , $$cD_{2}$$ and $$cA_{2}$$ . The coefficients $$cD_{1}$$ and $$cD_{2}$$ are details coefficients, denoised by soft thresholding for obtaining two denoised coefficients, $$cDd_{1}$$ and $$cDd_{2}$$ . The coefficient $$cA_{2}$$ is an approximation coefficient, denoised by $${\text{TVM}}$$ based denoising method for obtaining a denoised coefficient $$cAd_{2}$$ . The last step of this technique consists in applying the inverse of $${\text{LWT}}$$ to $$cDd_{1}$$ , $$cDd_{2}$$ and $$cAd_{2}$$ for obtaining the denoised $${\text{ECG}}$$ signal. The proposed technique evaluation is by comparing it with three other denoising approaches discussed in the extant in literature. The TVM-based approach is the first, the second is $$1 - D$$ double-density complex Discrete Wavelet Transform denoising method, and the third is the $${\text{ECG}}$$ denoising technique based on Non-local Means. These four mentioned techniques are applied to various $${\text{ECG}}$$ signals taken from $${\text{MIT}} - {\text{BIH}}$$ database. Those signals are degraded by an additive White Gaussian Noise at different values of Signal to Noise Ratio ( $${\text{SNR}}i{\text{~}}\left( {{\text{dB}}} \right)$$ ). The results obtained from the calculation of $${\text{SNR}}$$ and the Mean Square Error, infer that the proposed technique outperforms the other denoising approaches selected for the comparative evaluation.
Titel: |
A New ECG Denoising Technique Based on LWT and TVM
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Autor/in / Beteiligte Person: | Talbi, Mourad |
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Zeitschrift: | Circuits, Systems, and Signal Processing, Jg. 40 (2021-07-19), S. 6284-6300 |
Veröffentlichung: | Springer Science and Business Media LLC, 2021 |
Medientyp: | unknown |
ISSN: | 1531-5878 (print) ; 0278-081X (print) |
DOI: | 10.1007/s00034-021-01781-y |
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