A Cloud-Based Assessment of Arterial Stiffness Through Contour Analysis of A Photoplethysmography

Abstract

Cardiovascular diseases (CVDs) are the leading cause of mortality globally. To effectively prevent CVDs, a variety of techniques have been employed to evaluate the mechanical properties of arteries, among which, aortic stiffness measured by aortic pulse wave velocity (PWV) has been proven to be an independent predictor of CVDs. However, the traditional way to measure PWV is complex and time consuming. Recent studies suggest the digital volume pulse (DVP) waveform to be an effective non-invasive method to obtain PWV. In this study, we present a cloud computing system that analyzes and calculates the relevant indices of arterial stiffness after receiving the measured DVP signals. The result of the analysis can be retrieved online for the user to view or download for further analysis. With this technique, arterial Stiffness Index (SI) for population can be obtained easily and inexpensively. This will help health authorities to do mass screening at population level and, hence, establish references of arterial SI for different cohorts by age, gender, ethnicity, and diseases.