Model-based analysis of arterial pulse signals for tracking changes in arterial wall parameters: a pilot study

Arterial wall parameters (i.e., radius and viscoelasticity) are prognostic markers for cardiovascular diseases (CVD), but their current monitoring systems are too complex for home use. Our objective was to investigate whether model-based analysis of arterial pulse signals allows tracking changes in arterial wall parameters using a microfluidic-based tactile sensor. The sensor was used to measure an arterial pulse signal. A data-processing algorithm was utilized to process the measured pulse signal to obtain the radius waveform and its first-order and second-order derivatives, and extract their key features. A dynamic system model of the arterial wall and a hemodynamic model of the blood flow were developed to interpret the extracted key features for estimating arterial wall parameters, with no need of calibration. Changes in arterial wall parameters were introduced to healthy subjects ([Formula: see text]) by moderate exercise. The estimated values were compared between pre-exercise and post-exercise for significant difference ([Formula: see text]). The estimated changes in the radius, elasticity and viscosity were consistent with the findings in the literature (between pre-exercise and 1 min post-exercise: - 11% ± 4%, 55% ± 38% and 28% ± 11% at the radial artery; - 7% ± 3%, 36% ± 28% and 16% ± 8% at the carotid artery). The model-based analysis allows tracking changes in arterial wall parameters using a microfluidic-based tactile sensor. This study shows the potential of developing a solution to at-home monitoring of the cardiovascular system for early detection, timely intervention and treatment assessment of CVD.