An overview of heart-noise reduction of lung sound using wavelet transform based filter

Auscultation of the lung sound is a simple and noninvasive method to obtain some instant but useful informations to detect various respiratory diseases. However, one of the main problems in lung sound analysis is the interference of heart sounds, which is unavoidable during lung sound recording. Wavelet transformation based adaptive denoising technique has been proposed for heart sound reduction from lung sound. In the wavelet transform (WT) based filter it has been shown that the multiresolution representation of the lung sound signal in the WT domain combined with hard thresholding can separate the nonstationary part of the input signal (heart sound) from the stationary one (lung sound). This study investigated the spectral characteristics of the lung sound signals before and after WT based filtering. WT based filtering has been applied to lung sound signals recorded from anterior-right chest locations of six healthy subjects at low (7.5 ml/s/kg) and medium (15 ml/s/kg) flow rates. The R-waves of simultaneously recorded ECG signals were used to detect the lung sound segments at defined flow rates with inclusion or exclusion of heart sounds. The power spectra of the filtered lung sound segments were compared with the power spectra of the original sound segments, including and excluding heart sounds, at different frequency bands from 20-2400 Hz. Results show that the WT based filtering reduces the lung sound average power greatly over the whole frequency range. This results in pronounced change in the spectrum of the original signal that are of interest. Therefore, further investigations on feasibility of using this method for heart-noise reduction of lung sound signal are necessary.