Journals Proceedings

Abstract

Cardiovascular diseases (CVDs) are currently the leading cause of deaths worldwide. The traditional auscultation is cost-effective and time-saving for the public to diagnose CVDs early. While many approaches in analysis of the heart sound (HS) signal from auscultation have been utilized successfully, few studies are focused on acoustic perspective to interpret the HS signal. This paper creatively proposes a timbre model to interpret HS with much more attentions on feature extractions combined with medical knowledge. The timbre model based on multidimensional features has three dimensions, which are spectral centroid (SC), log attack time (LAT) and temporal centroid (TC). The simulation experiments indicate that the proposed model is of use in HS feature extraction and its following CVD diagnosis.