Sparse representation of audio features for sputum detection from lung sounds

A medical staff needs to check sputum accumulation in patient´s respiratory tract by lung sounds auscultation at any time, and it is the big burden for the staff. This paper aims to develop a system which notifies appropriate timing for the tracheal suction for the medical staff by analyzing lung sounds of the patients. We present a novel framework about automatic sputum detection from lung sounds. We proposed the sparse representation of audio features to realize robust detection in real environment. We showed the effectiveness of our proposed method for three patients in an ICU of Gifu University Hospital, where the recorded lung sounds included electronic beeps, human voices, and other various noises.