Confidence interval estimation for oscillometric blood pressure measurements using nonparametric bootstrap approach

Abstract

Blood pressure is an important vital sign for determining the health of an individual. Although estimation of average arterial blood pressure is possible using oscillometric methods, there are no established methods in the literature for obtaining confidence interval (CI) for systolic pressure (SBP) and diastolic pressure (DBP) estimates obtained from such measurements. This paper presents a nonparametric bootstrap methodology to obtain CI with a small sample set of measurements. The proposed methodology uses pseudo measurements using bootstrap principles to derive the pseudo maximum amplitudes (PMA) and the pseudo envelopes (PE). Then the SBP and DBP are derived using the new relationships between PMA and PE and the confidence intervals for such estimates. Application of the proposed methodology on an experimental dataset of 85 patients with 5 sets of measurements for each patient has yielded a tighter Cl than the conventional student t-method.