Phonocardiogram Signal Denoising Based on Nonnegative Matrix Factorization and Adaptive Contour Representation Computation

This letter introduces a new technique for phonocardiogram (PCG) signal denoising based on nonnegative matrix factorization (NMF) of its spectrogram and adaptive contour representation computation (ACRC) of its short-time Fourier transform (STFT). More precisely, NMFs on PCG and synchronous electroc...

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Veröffentlicht in:IEEE signal processing letters 2018-10, Vol.25 (10), p.1475-1479
Hauptverfasser: Duong-Hung Pham, Meignen, Sylvain, Dia, Nafissa, Fontecave-Jallon, Julie, Rivet, Bertrand
Format: Artikel
Sprache:eng
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Zusammenfassung:This letter introduces a new technique for phonocardiogram (PCG) signal denoising based on nonnegative matrix factorization (NMF) of its spectrogram and adaptive contour representation computation (ACRC) of its short-time Fourier transform (STFT). More precisely, NMFs on PCG and synchronous electrocardiogram spectrograms are first used to filter out high-energy noises from PCG. Then, ACRC is performed on a low-pass filtered version of the STFT of the resulting signal to identify relevant time-frequency components that are subsequently used for signal retrieval. Numerical experiments conducted on a real database of noisy PCG signals, Signal Separation Evaluation Campaign (SiSEC2016), illustrate the superiority of the proposed method over state-of-the-art techniques.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2018.2865253