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

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Abstract

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.

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Abbreviations

ANC:

Adaptive noise cancellation

CWT:

Continuous wavelet transform

ECG:

Electrocardiogram

EMG:

Electromyogram

FOS:

Fourth-order statistics

HS:

Heart sounds

HPF:

High pass filtering

LMS:

Least mean square

RLS:

Recursive least squares

ROKF:

Reduced order Kalman filtering

PSD:

Power spectral density

STFT:

Short-time Fourier transform

TF:

Time-frequency

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Pourazad, M.T., Moussavi, Z. & Thomas, G. Heart sound cancellation from lung sound recordings using time-frequency filtering. Med Bio Eng Comput 44, 216–225 (2006). https://doi.org/10.1007/s11517-006-0030-8

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