Training of a Artificial Intelligence Model to Detect Venous Diseases Using PPG Technology

The study investigates venous competence through three distinct exercises using photoplethysmography (PPG) technology to record blood flow in the leg veins of 20 subjects, split into two groups: those with chronic venous disease (CVD) and those without. The null hypothesis is that there will be no significant difference in venous filling times (VFT) and PPG trace variations between subjects with CVD and those without under different physical conditions. The alternative hypothesis suggests that individuals with CVD will show distinct PPG patterns, particularly shorter VFT and varied pressure changes, indicative of venous reflux or obstruction. This hypothesis is chosen based on prior evidence suggesting observable differences in venous function between affected and non-affected individuals.