Abstract

Info

Title:: Lung sound denoising algorithm based on variational mode decomposition

Author(s):: SUN Wenhui1; 2; ZHANG Yipeng1; 2; LIN Dongmei3; CHEN Fuming2; 1. School of Information Engineering, Gansu University of Chinese Medicine, Lanzhou 730000, China 2. Medical Security Center, the 940th Hospital of Joint Logistics Support Force of Chinese Peoples Liberation Army, Lanzhou 730050, China 3. College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China

Keywords:: Keywords: lung sound denoising variational mode decomposition empirical mode decomposition

Abstract:: Abstract: 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.