Stroke-volume-allocation model enabling wearable sensors for vascular age and cardiovascular disease assessment

Abstract

Frequent and unobtrusive monitoring of cardiovascular conditions with consumer electronics is a widely pursued goal, since it provides the most economic and effective way of preventing and managing cardiovascular diseases (CVDs) ─ the leading causes of death worldwide. However, most current wearable and flexible devices can only support the measurement of one or two types of vital signs, such as heart rate and blood oxygen level, due to the lack of physiological models to link the measured signals to cardiovascular conditions. Here, we report a stroke-volume allocation (SVA) model to quantify the cushioning function of arteries and empower nearly all existing cardiac sensors with new functions, including arterial stiffness evaluation, dynamic blood pressure tracking and classification of CVD-related heart damage. Large-scale clinical data testing involving a hybrid dataset taken from 6 hospitals/research institutes (9 open databases and 4 self-built databases from 878 subjects in total) and diverse measurement approaches was carried out to validate the SVA model. The results show that the SVA-based parameters correlate well with the gold-standard measurements in arterial stiffness and blood pressure and outperform the commonly used vital sign (e.g., blood pressure) alone in detecting abnormalities in cardiovascular systems.