Video Based Heart

Video-based and audio-based remote heart monitoring is a rapidly developing field aiming to improve the accessibility and accuracy of cardiovascular assessments. Current research focuses on developing robust machine learning models, often employing deep learning architectures, to analyze video recordings of the face for heart rate and respiratory rate, and audio recordings of heart and lung sounds for diagnosing cardiac and pulmonary conditions. These methods are being refined to mitigate the impact of noise and variations in recording conditions, and are being integrated into robotic systems for autonomous auscultation. The ultimate goal is to provide accurate, convenient, and potentially life-saving remote diagnostic tools.