NDLI: Application of wavelet and EMD-based denoising to phonocardiograms

Content Provider	IEEE Xplore Digital Library
Author	Gavrovska, A. Slavkovic, M. Reljin, I. Reljin, B.
Copyright Year	2013
Description	Author affiliation: Sch. of Electr. Eng., Innovation Center, Univ. of Belgrade, Belgrade, Serbia (Gavrovska, A.; Slavkovic, M.; Reljin, B.) \|\| Dept. of Telecommun., Univ. of Belgrade, Belgrade, Serbia (Reljin, I.)
Abstract	Wavelet-based (WT) denoising has been frequently used as simple and efficient method enabling high signal-to-noise ratio. Moreover, by using second generation WT and lifting scheme, even better performance has been obtained. Besides the WT, empirical mode decomposition (EMD) is another efficient noise reduction technique, which enables adaptive decomposition based only on signal characteristics. Both WT and EMD denoising concepts find place in pre-processing of phonocardiograms (PCGs). Although these techniques are very effective in denoising, their inappropriate use can cause unwanted signal distortion. In this paper, we analyzed both denoising techniques and tested their influence to the degradation of PCGs, particularly regarding to some diagnostically relevant cardiac events, such as the first and second heart sound (S1 and S2) and clicks. It was shown that the morphology of S1, S2, and even the existence of subtle features (clicks) within the PCG, depend on the denoising method. Results of evaluation tests indicate which combination of denoising algorithm is the best choice for PCG signal pre-processing.
Starting Page	1
Ending Page	4
File Size	328250
Page Count	4
File Format	PDF
ISBN	9781479931934
e-ISBN	9781467361439
DOI	10.1109/ISSCS.2013.6651264
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-11
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Empirical mode decomposition Noise reduction Discrete wavelet transforms Phonocardiography Signal to noise ratio
Content Type	Text
Resource Type	Article

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