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Heart sound cancellation from lung sound recordings using time-frequency filtering.

机译:使用时频滤波从肺部录音中消除心音。

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摘要

During lung sound recordings, heart sounds (HS) interfere with clinical interpretation of lung sounds over the low frequency components which is significant especially at low flow rates. Hence, it is desirable to cancel the effect of HS on lung sound records. In this paper, a novel HS cancellation method is presented. This method first localizes HS segments using multiresolution decomposition of the wavelet transform coefficients, then removes those segments from the original lung sound record and estimates the missing data via a 2D interpolation in the time-frequency (TF) domain. Finally, the signal is reconstructed into the time domain. To evaluate the efficiency of the TF filtering, the average power spectral density (PSD) of the original lung sound segments with and without HS over four frequency bands from 20 to 300 Hz were calculated and compared with the average PSD of the filtered signals. Statistical tests show that there is no significant difference between the average PSD of the HS-free original lung sounds and the TF-filtered signal for all frequency bands at both low and medium flow rates. It was found that the proposed method successfully removes HS from lung sound signals while preserving the original fundamental components of the lung sounds.
机译:在肺部录音期间,心音(HS)会干扰低频分量上的肺部声音的临床解释,这在低流速下尤为重要。因此,希望消除HS对肺部声音记录的影响。本文提出了一种新的HS消除方法。该方法首先使用小波变换系数的多分辨率分解来定位HS片段,然后从原始肺部声音记录中删除那些片段,并通过时频(TF)域中的2D插值估计丢失的数据。最后,信号被重建到时域中。为了评估TF滤波的效率,计算了从20到300 Hz的四个频带上带有和不带有HS的原始肺部声音片段的平均功率谱密度(PSD),并将其与滤波后信号的平均PSD进行比较。统计测试表明,在低流量和中流量时,所有频段的无HS原始肺音的平均PSD与TF滤波信号之间没有显着差异。发现所提出的方法成功地从肺部声音信号中去除了HS,同时保留了肺部声音的原始基本成分。

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