Prediction of Cardiovascular Diseases from Radial Pulse Wave Analysis

This study investigates the efficacy of radial pulse wave analysis in predicting cardiovascular diseases (CVD), specifically diabetes and hypertension. Using a novel low-pressure sensor system, pulse waveforms from 140 participants were analysed through multiple feature extraction methods: time domain fiducial points, frequency domain analysis, and pulse rate variability measures. The results demonstrate high classification accuracy, achieving 96% for diabetes using pulse rate variability features and 92% for hypertension using frequency domain features. The findings suggest that radial pulse wave analysis could serve as a viable non-invasive alternative for cardiovascular disease screening and monitoring.