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Restoration of Lung Sound Signals Using a Hybrid Wavelet-Based Approach
A unique and ideal integration of wavelet-based total variation (WATV) and empirical Wiener denoising method is proposed in this article to significantly enhance the signal-to-noise ratio (SNR) while preserving the characteristics of a lung sound signal. While individual wavelet-based denoising filt...
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Published in: | IEEE sensors journal 2022-10, Vol.22 (20), p.19700-19712 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | A unique and ideal integration of wavelet-based total variation (WATV) and empirical Wiener denoising method is proposed in this article to significantly enhance the signal-to-noise ratio (SNR) while preserving the characteristics of a lung sound signal. While individual wavelet-based denoising filters based on a single basis function have been employed in the past, the outcome has been unsatisfactory because only significant (signal) wavelet coefficients are considered for denoising analysis. The new wavelet-based empirical Wiener (WATV-Wiener) hybrid technique, proposed here, takes into account both significant and insignificant (noise) wavelet coefficients of the noisy signal. An intensive analysis of selecting and fine-tuning the WATV-Wiener filter parameters is presented here through the simulation studies. The WATV-Wiener filter applied here onto different 1-D lung sound signals of different noise levels has led to an optimal root mean square error (RMSE) compared with seven other state-of-the-art filters reported in the literature. The optimal parameters achieved through our simulation studies led to a 3-20-dB improvement in SNR, and the average SNR was improved by 4-30 dB in our experiment. We also observed that the WATV-Wiener filter is less sensitive to the variation of SNR values of the input signal. Furthermore, the WATV-Wiener filter obtains similar SNR performance between continuous piecewise signal (wheeze) and noncontinuous piecewise signal (crackle) in both simulation and experimental studies. |
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ISSN: | 1530-437X 1558-1748 |
DOI: | 10.1109/JSEN.2022.3203391 |