A Novel Technique for Denoising Explosive Lung Sounds Emnpirmical Mode Decompiosition and Fractal Dimension Foilter

In this paper, a novel denoising tool that enhances explosive lung sounds (ELS), such as crackles and squawks (SQs), so they can more accurately and reliably be interpreted by the physicians, has been presented. This approach combines empirical mode decomposition (EMD) with fractal dimension (FD) analysis, highlighting, simultaneously, the advantageous complementarities drawn from such bridging, through its application to experimental data. The results obtained show that this hybrid denoising scheme can achieve good discrimination between useful ELS and background noise. Finally, its adaptive performance and its low computational complexity make it applicable to other separation problems involving nonstationary transient signals contaminated by uncorrelated additive noise