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Adaptive Fourier decomposition approach for lung-heart sound separation
Wang Z.; Nuno Da Cruz J.; Wan F.
2015
Conference NameIEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)
Source Publication2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, CIVEMSA 2015
Conference DateJUN 12-14, 2015
Conference PlaceShenzhen, PEOPLES R CHINA
Abstract

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).

KeywordAdaptive Fourier Decomposition Heart Sound Lung Sound
DOI10.1109/CIVEMSA.2015.7158631
URLView the original
Indexed BySCI
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Theory & Methods
WOS IDWOS:000380900900042
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Document TypeConference paper
CollectionDEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Wang Z.,Nuno Da Cruz J.,Wan F.. Adaptive Fourier decomposition approach for lung-heart sound separation[C],2015.
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