A
phonocardiogram apparatus and related method for diagnosis of cardiac pathologies through advanced sound recording and analysis. This apparatus utilizes a grid of microphones embedded in a fabric and positioned over the patient's chest and back to capture heart,
lung, and neck sounds from multiple locations. An
artificial intelligence (AI) based
algorithm is employed to determine the most relevant microphones based on the patient's unique
anatomy, thereby optimizing sound collection for diagnostic purposes. The collected sounds undergo a series of pre-
processing and
machine learning analyses to diagnose cardiac abnormalities such as aortic
stenosis, murmurs, and extra systoles, create cardiac auscultatory signatures and allow longitudinal monitoring by clinicians or patients themselves for comparison over time.