Adaptive Fourier decomposition approach for lung-heart sound separation

Interference often occurs between the lung sound (LS) and the heart sound (HS). Due to the overlap in their frequency spectrums, it is difficult to separate them. This paper proposes a novel separation method based on the adaptive Fourier decomposition (AFD) to separate the HS and the LS with the minimum energy loss. This AFD-based separation method is validated on the real HS signal from the University of Michigan Heart Sound and Murmur Library as well as the real LS signal from the 3M repository. Simulation results indicate that the proposed method is better than other extraction methods based on the recursive least square (RLS), the standard empirical mode decomposition (EMD) and various extensions of the EMD including the ensemble EMD (EEMD), the multivariate EMD (M-EMD) and the noise assisted M-EMD (NAM-EMD).