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Journal ArticleDOI

Reduction of Heart Sounds from Lung Sounds by Adaptive Filterng

TLDR
It is shown how adaptive filtering can be used to reduce heart sounds without significantly affecting breath sounds and the technique is found to reduce the heart sounds by 50¿80 percent.
Abstract
Auscultation of the chest is an attractive diagnostic method used by physicians, owing to its simplicity and noninvasiveness. Hence, there is interest in lung sound analysis using time and frequency domain techniques to increase its usefulness in diagnosis. The sounds recorded or heard are, however, contaminated by incessant heart sounds which interfere in the diagnosis based on, and analysis of, lung sounds. A common method to minimize the effect of heart sounds is to filter the sound with linear high-pass filters which, however, also eliminates the overlapping spectrum of breath sounds. In this work we show how adaptive filtering can be used to reduce heart sounds without significantly affecting breath sounds. The technique is found to reduce the heart sounds by 50?80 percent.

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Citations
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Journal ArticleDOI

Analysis of Respiratory Sounds: State of the Art

TL;DR: The study includes a description of the various techniques that are being used to collect auscultation sounds, a physical description of known pathologic sounds for which automatic detection tools were developed, and a search for new markers to increase the efficiency of decision aid algorithms and tools.
Journal ArticleDOI

Localizing Heart Sounds in Respiratory Signals Using Singular Spectrum Analysis

TL;DR: Singular spectrum analysis (SSA), a powerful time series analysis technique, is used in this paper and the proposed method outperforms the wavelet-based method in terms of false detection and also correlation with the underlying heart sounds.
Journal ArticleDOI

Adaptive reduction of heart sounds from lung sounds using fourth-order statistics

TL;DR: An adaptive heart-noise reduction method, based on fourth-order statistics (FOS) of the recorded signal, without requiring recorded "noise-only" reference signal, is presented, which uses adaptive filtering to preserve the entire spectrum.
Journal ArticleDOI

A robust method for estimating respiratory flow using tracheal sounds entropy

TL;DR: A robust and novel method for estimating flow using entropy of the band pass filtered tracheal sounds is proposed, which requires only one breath for calibration and can estimate any flow rate even out of the range of calibration flow.
Journal ArticleDOI

A wavelet-based reduction of heart sound noise from lung sounds

TL;DR: Experimental results have shown that the implementation of this wavelet-based filter in lung sound analysis results in an efficient reduction of the superimposed heart sound noise, producing an almost noise-free output signal.
References
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Journal ArticleDOI

Adaptive noise cancelling: Principles and applications

TL;DR: It is shown that in treating periodic interference the adaptive noise canceller acts as a notch filter with narrow bandwidth, infinite null, and the capability of tracking the exact frequency of the interference; in this case the canceller behaves as a linear, time-invariant system, with the adaptive filter converging on a dynamic rather than a static solution.
Journal ArticleDOI

Spectral characteristics of normal breath sounds.

TL;DR: Breath sounds picked up over the trachea were characterized by power spectra typical to a broad spectrum sound with a sharp decrease of power at a cut-off frequency that varied between 850 and 1,600 Hz among the 10 healthy subjects studied.
Journal ArticleDOI

An accurate recording system and its use in breath sounds spectral analysis.

TL;DR: An accurate recording system was set up and used for analyzing normal and asthmatic breath-sound features and found that increasing the flow rate raises the high-frequency components of the spectra.
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