Remote heart-sound monitoring and biometric identification using laser-camera
Assessment of heart sounds is the cornerstone of cardiac examination, but it requires a stethoscope, skills and experience, and a direct contact with the patient. We developed a contactless, machine learning assisted method for heart-sound identification and quantification based on the remote measurement of the reflected laser speckle from the neck skin surface. We compare the performance of this method to standard digital stethoscope recordings on an example task of heart-beat sound biometric identification. We show that our method outperforms the stethoscope even allowing identification on the test data taken on different days/in different environments. This method might allow development of devices for remote monitoring of cardiovascular health in different settings.
