With the rise in prevalence of cardiovascular (CV) disease, risk stratification is becoming increasingly important. Accurate characterization of the CV system is required, for which central aortic blood pressure (BP) parameters form an integral part. However, invasive measurement of central aortic BP parameters (aP) is difficult. Therefore, non-invasive methods to estimate aP from the radial pressure pulse (rPulse) have been proposed. To analyze accuracy of estimated aP (aPhat) and applicability in risk stratification and diagnosis, this study presents: (1) a novel representation of the rPulse with minimal loss of information, (2) a framework for strict definition and statistical analysis of aPhat, and (3) a dynamic analysis of effects of mean BP (MP) and heart rate (HR) in the rPulse shape. Methods: (1) 2671 rPulse s measured by applanation tonometry were represented using the first eight principal components (PC) scores after standard PC transformation. rPulse shapes were compared in three subpopulations. (2) The concept of &quotestimation option&quot (EO) for aP estimation was presented. A framework for strict definition of aPhat and the comparison of EOs was proposed, and 7 different EOs compared. (3) A sequence of rPulse s was analyzed during soft exhalation maneuver (SEM) %, a mild Valsalva type maneuver, in eight healthy subjects. Radial BP and respiration pressure were continuously measured. The effects of MP and HR in the rPulse parameters were analyzed by standard linear regression for each subject. Results: (1) PC representation of the rPulse improves accuracy of the estimation of aPhat compared with the simple use of rPulse parameters. Subpopulations have distinctive rPulse shapes. (2) No single EO was better for the estimation of all aPhat. Inclusion of MP improves estimation accuracy. Despite further improvement when rPulse is included, the general transfer function EO is a biased estimator. (3) The dynamic analysis of the rPulse provides information of the effects of MP and HR in the rPulse not available in static analysis. The effects were specific for each individual and different from the results obtained from a general population. Conclusions: For accurate CV risk stratification, future studies should include a dynamic measurement of calibrated radial pressure pulse during SEM maneuver. Risk analysis and diagnosis should be based on representations of the rPulse with minimum loss of information. aPhat should be used for better understanding of the underlying physiological principles.