INVESTIGATION OF DISCRETE WAVELET TRANSFORM DOMAIN OPTIMAL PARAMETRIC APPROACH FOR DENOISING OF PHONOCARDIOGRAM SIGNAL

Phonocardiogram (PCG) signals are contaminated with various noise signals, which hinders the accurate diagnostic interpretation of the signal. Discrete wavelet transform (DWT) is a well-known technique used to remove noise from PCG signals and improve signal quality. The performance of DWT-based den...

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Bibliographic Details
Published inJournal of mechanics in medicine and biology Vol. 22; no. 6
Main Authors GHOSH, SAMIT KUMAR, PONNALAGU, R. N.
Format Journal Article
LanguageEnglish
Published Singapore World Scientific Publishing Company 01.08.2022
World Scientific Publishing Co. Pte., Ltd
Subjects
Decomposition
Discrete Wavelet Transform
Heart valves
Noise reduction
Optimization
Parametric statistics
Performance evaluation
Phonocardiography
Process parameters
Root-mean-square errors
Signal quality
Signal to noise ratio
Wavelet transforms
denoising
thresholding
Discrete wavelet transform
phonocardiogram signal
decomposition level
signal-to-noise ratio
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Summary:Phonocardiogram (PCG) signals are contaminated with various noise signals, which hinders the accurate diagnostic interpretation of the signal. Discrete wavelet transform (DWT) is a well-known technique used to remove noise from PCG signals and improve signal quality. The performance of DWT-based denoising depends upon several parameters involved in the process, such as mother wavelets used for decomposition, the number of decomposition levels (DLs), thresholding technique used and the threshold estimation rule followed. In this work, an investigative study is carried out to select the optimal parameter values which give the best denoising performance. The metrics such as mean-square error (MSE), normalized-mean-square error (NMSE), root-mean-square error (RMSE), percentage root-mean-square difference (PRD) and signal-to-noise ratio (SNR) are used to evaluate the performance of the denoising in this study. The results obtained show that the fifth-order Coiflet wavelet is best suited for denoising PCG signals when applied with the soft thresholding (ST) function and rigrsure threshold selection rule. Also, the optimum number of DLs resulting in better performance is level 6. SNR value obtained from the studies shows the efficacy of the parameters selected for denoising. The denoised PCG signals provide accurate information to determine various kinds of heart valve-related disorders (HVDs).
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ISSN:0219-5194
1793-6810
DOI:10.1142/S0219519422500464