Phonocardiogram Signal Denoising Based on Non-negative Matrix Factorization and Adaptive Contour Representation Computation

Abstract : —This letter introduces a new technique for phono-cardiogram (PCG) signal denoising based non-negative 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 (ECG) 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 (TF) components which are subsequently used for signal retrieval. Numerical experiments conducted on a real database of noisy PCG signals (SiSEC2016) illustrate the superiority of the proposed method over state-of-the-art techniques.
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IEEE Signal Processing Letters, Institute of Electrical and Electronics Engineers, 2018
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Duong-Hung Pham, Sylvain Meignen, Nafissa Dia, Julie Fontecave-Jallon, Bertrand Rivet. Phonocardiogram Signal Denoising Based on Non-negative Matrix Factorization and Adaptive Contour Representation Computation. IEEE Signal Processing Letters, Institute of Electrical and Electronics Engineers, 2018. 〈hal-01855855〉

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