Heart sound cancellation from lung sound recordings using adaptive threshold and 2D interpolation in time-frequency domain

During lung sound recordings, an incessant noise source occurs due to heart sounds. The heart sound interference on lung sounds is significant especially at low flow rates. In this paper a new heart noise (HN) cancellation method is presented. This algorithm uses an image processing technique to detect HN segments in the spectrogram of the recorded lung sound signal. Afterwards the algorithm removes those segments and estimates the missing data employing a 2D interpolation in the time-frequency domain and finally reconstructs the signal in the time domain. The results show that the proposed method successfully cancels HN from lung sound signals while preserving the original fundamental components of the lung sound signal. The computational load and the speed of the proposed method were found to be much more efficient than other HN cancellation methods such as adaptive filtering.