Key result
The db5 wavelet maximizes signal-to-noise ratio and achieves ~98% signal reconstruction in denoising phonocardiograms.
Why the study?
Existing hard-thresholding and soft-thresholding methods for denoising heart sound signals have limitations such as discontinuous functions and permanent bias.
A novel adaptive wavelet-based denoising method improves noise cancellation in heart sound signals compared to traditional thresholding techniques.
Adaptive thresholding may enhance signal preprocessing; leaves open validation in clinical cardiovascular datasets.
This paper presents a novel wavelet-based denoising method using coefficient thresholding technique.The proposed method uses the adaptive thresholding which overcome the shortcomings of discontinuous function in hard-thresholding and also can eliminate the permanent bias in soft-thresholding.The qualitative evaluation of the denoising performance has shown that the proposed method cancels noises more effectively than the other examined techniques.The introduced method can be used as preprocessor stage in all fields of phonocardiography, including the recording of fetal heart sounds on the maternal abdominal surface.
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Gyanaprava Mishra . (2013) studied Heart sound (PCG) signal noise. Wavelet transform denoising (db5) vs. Other wavelet functions was evaluated on Signal to Noise Ratio (SNR) and Percentage of Reconstruction (PR). The db5 wavelet at level 5 decomposition provided the maximum Signal to Noise Ratio for denoising phonocardiogram signals, while db5 at level 2 produced the maximum percentage of reconstruction (98.19%).
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