Reduction of heart sounds from lung sound recordings by automated gain control and adaptive filtering techniques

Auscultation is an attractive, simple, and noninvasive method for the diagnosis of cardiovascular and pulmonary disorders. However, heart sounds contaminates severely lung sound recordings. The results of our previous researches indicated that the Laplacian electrocardiographic signal (LECG) could be used as a reference for adaptive filtering to reduce heart sounds. In this paper, an integrated platform including an electronic stethoscope, an automated gain control (AGC), and an adaptive algorithm, has been developed to process the signal in real time. The AGC algorithm allows amplifying the LECG signal in different scales to solve the problem of relatively weak LECG signals at the right chest. The experimental result shows that the heart-noise reduction at the right chest is improved from 43% reported early to 75%. The overall heart sound reduction by our new scheme ranges from 75% to 83% at different chest locations.