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Optimal level and order detection in wavelet decomposition for PCG signal denoising
Mohamed Rouis1,2, Abdelkrim Ouafi1,2, Salim Sbaa1,2
1Department of Electrical Engineering, University of Biskra, Biskra, Algeria.
Biomedizinische Technik. Biomedical Engineering
|May 24, 2018
Summary
This study introduces a novel method for denoising phonocardiogram (PCG) signals by optimizing the discrete wavelet transform (DWT) through the selection of optimal mother wavelets and decomposition levels (DLs). The approach effectively reduces noise in PCG signals.
Area of Science:
- Biomedical Engineering
- Signal Processing
- Medical Informatics
Background:
- Phonocardiogram (PCG) signals are susceptible to noise, which can alter their diagnostic characteristics.
- Discrete Wavelet Transform (DWT) is a powerful tool for signal denoising, but its efficacy depends on the choice of mother wavelet and decomposition level (DL).
Purpose of the Study:
- To propose and evaluate a novel approach for selecting optimal mother wavelets and DLs for PCG signal denoising.
- To address noise and variability challenges in PCG acquisition across diverse patient populations.
Main Methods:
- Developed two algorithms to identify optimal DL and mother wavelet for PCG denoising.
- Utilized simulated noisy PCG signals for evaluation.
Main Results:
- The proposed method demonstrated effective noise reduction in PCG signals.
- Evaluated performance using coherence analysis (Coh), correlation coefficient (Corr), mean square error (MSE), and signal-to-noise ratio (SNR).
Conclusions:
- The developed approach successfully optimizes DWT parameters for enhanced PCG signal denoising.
- This method offers a robust solution for improving the quality of PCG signals in clinical settings.
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