Heart Sound Cancellation Based on Multiscale Products and Linear Prediction

This paper presents a novel method for Heart Sound (HS) cancellation from Lung Sound (LS) records. The method uses the multiscale product of the wavelet coefficients of the original signal to detect HS-included segments. Once the HS segments are identified, the method removes them from the wavelet coefficients at every level and estimates the created gaps by using a set of linear prediction filters. It is shown that if the segment to be predicted is stationary, a final record with no audible artifacts such as clicks can be reconstructed using this approach. The results were promising for HS removal from LS records and showed no hampering of the main components of the LS. The results were confirmed both qualitatively by listening to the reconstructed signal and quantitatively by spectral analysis

[1]  Armein Z. R. Langi,et al.  A wavelet-based measurement of signal fractal dimensions , 2002, IEEE CCECE2002. Canadian Conference on Electrical and Computer Engineering. Conference Proceedings (Cat. No.02CH37373).

[2]  강태원,et al.  [서평]「Chaos and Fractals : New Frontiers of Science」 , 1998 .

[3]  W. Etter,et al.  Restoration of a discrete-time signal segment by interpolation based on the left-sided and right-sided autoregressive parameters , 1996, IEEE Trans. Signal Process..

[4]  Zahra Moussavi,et al.  An overview of heart-noise reduction of lung sound using wavelet transform based filter , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[5]  Zahra Moussavi,et al.  Heart Sound Cancellation Based on Multiscale Products and Linear Prediction , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[6]  Hervé Carfantan,et al.  Time-invariant orthonormal wavelet representations , 1996, IEEE Trans. Signal Process..

[7]  Stéphane Mallat,et al.  Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  January Gnitecki,et al.  Recursive least squares adaptive noise cancellation filtering for heart sound reduction in lung sounds recordings , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[9]  John G. Proakis,et al.  Digital signal processing (3rd ed.): principles, algorithms, and applications , 1996 .

[10]  Y. Meyer.  Wavelets and Operators , 1993 .

[11]  C. Chui.  Wavelets: A Tutorial in Theory and Applications , 1992 .

[12]  Gabriel Thomas,et al.  Heart sound cancellation from lung sound recordings using adaptive threshold and 2D interpolation in time-frequency domain , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[13]  Zahra Moussavi,et al.  Qualitative and quantitative evaluation of heart sound reduction from lung sound recordings , 2005, IEEE Transactions on Biomedical Engineering.

[14]  Lei Zhang,et al.  Noise Reduction for Magnetic Resonance Images via Adaptive Multiscale Products Thresholding , 2003, IEEE Trans. Medical Imaging.