Lung sound denoising algorithm based on variational mode decomposition
Objective To propose a lung sound denoising method based on variational mode decomposition(VMD)for effectively improving the quality of lung sound signals.Methods Empirical mode decomposition was utilized to decompose the noisy lung sound signal,and the optimal decomposition level was determined based on the intrinsic mode function features.Subsequently,the original noisy lung sound was processed with VMD according to the decomposition level,and the useful modes were then selected based on Pearson correlation coefficient.Finally,a threshold method was applied to the denoising of each mode function,and the lung sound signal without noise interference was obtained after reconstruction.Results Compared with Wiener filtering and finite impulse response filtering,the proposed method exhibited superior performance in perceptual evaluation of speech quality,short-time objective intelligibility,and signal-to-distortion ratio.Conclusion The proposed method can effectively remove the noise from lung sound signals.
NETL
NSTL
万方数据
维普
