Abstract
Continuous blood pressure monitoring is essential for persons at risk of hypertension and cardiovascular disease. This work presents the analysis of different temporal features of photoplethysmogram (PPG) useful for estimating cuffless blood pressure by utilizing several statistical test approaches to identify the features’ contribution to this estimation and their correlation with a target mean arterial pressure values. The regression is performed using a random forest regressor to estimate mean arterial pressure (MAP) with temporal features, and statistical analysis with a ranking of features is done after estimation using p-value, correlation, and z-test. The significant ranking temporal features are selected and used to estimate MAP, DBP, and SBP.