Pulse Wave Monitoring Based on Remote Photoplethysmography

Atherosclerosis plays a major role in cardiovascular diseases. Traditional detection methods such as vascular ultrasound and angiography are quite accurate. However, they need costly equipment and specialized staff. This limits their use in home health monitoring. This study aims to come up with a non-invasive and low-cost way to detect carotid artery atherosclerosis. It makes use of remote photoplethysmography (rPPG) technology. Through non-contact optical methods, it collects cardiovascular-related physiological parameters. Then it calculates carotid pulse wave velocity (PWV) as an indication of arterial stiffness. The study analyzes grayscale video data and sample points from dual laser light sources. MATLAB is used for signal processing and PWV calculation. The initial results indicate that the PWV measured by rPPG has a good correlation with traditional methods. This confirms its effectiveness. There are challenges. One is to extract the subtle variations in skin luminance. How to measure the time and distance that the pulse wave travels is also an important issue to discuss in this study. Approaches like grayscale transformation, zero-phase filtering, and cross-correlation analysis, along with interpolation algorithms can possibly be solutions to the measurements. The use of rPPG to examine the carotid regions that are susceptible to noise is what makes this study novel. Cross-correlation functions are also employed to deal with precise image data. This technology may prove to be valuable for evaluating risks and preventing atherosclerosis at an early stage, which can contribute to treating cardiovascular diseases.