Detection of Arterial Stenosis Based on Synchronized Signals from Wearable Pulse and Blood Flow Velocity Sensors.

Atherosclerosis is the main cause of ischemic stroke. It occurs as a condition that leads to thickening of the arterial blood vessel walls and narrowing of the blood vessels, which can seriously affect the normal flow of blood. Currently, the detection of arterial stenosis relies on large-scale hospital equipment like computed tomography (CT) and magnetic resonance imaging (MRI), which require specialized technicians to operate and are not convenient for daily use. In addition, stenosis affects multiple parameters of hemodynamics in the blood flow field, and relying on a single physical quantity is not sufficient to understand the blood flow field localized in the stenotic vessel. Here, we demonstrated combined sensors of pulse wave and blood flow velocity (CSPB) based on photoelectric plethysmography and an ultrasonic Doppler device. We found that when the stenosis rate increased by 30%, the amplitude difference of the pulse wave curve between the two sides of the stenosis increased by over 11%, the amplitude of the blood flow curve decreased by 8%, and the blood flow resistance increased by 11%. We also prepared silicone-based models of blood stenosis vessels to build in vitro blood flow systems and achieve more accurate simulation of vascular stenosis diseases. Based on this, we studied the pulse wave and blood flow velocity curves of CSPB under different stenosis parameters. Meanwhile, we used the finite element analysis method of fluid-structure interactions to study the pulse wave and blood flow velocity changes under different arterial stenosis conditions. This study is expected to provide theoretical and technical references for achieving noninvasive detection of cardiovascular and cerebrovascular diseases based on multisensor fusion.