Characterization of Inflationary and Deflationary Auscultatory Blood Pressure Measurements

This document is a paper-based dissertation. The dissertation is a collection of articles written by the author in the pursuit to develop a novel method to measure blood pressure (BP). The introduction chapter describes how the documents are interrelated. This work starts with the description of the development and design of a non-invasive medical device capable of measuring arterial BP with a combination of inflationary and deflationary procedures. In addition to the device, we conducted a human-based study to characterize the properties of the BP signal in the inflationary and deflationary curves. With the signals acquired, we focused on the uncertainty occurring when taking two consecutive BP measurements. The prototype was composed of 1) a modified off-the-shelf oscillometric BP system, 2) a contact microphone with an amplifier, and 3) a high-sensitivity pulse oximeter, and its control electronics. The device captured the cuff pressure signal, arterial skin-surface acoustics, and photoplethysmography (PPG). The captured signals were processed and analyzed. We focused our analysis on the characterization of the uncertainty of two consecutive BP measurements by studying the biosignals captured with the custom-made apparatus. Accurate non-invasive BP measurements are vital in preventing and treating many cardiovascular diseases. The ?gold standard? for non-invasive procedures is the auscultatory method, which is based on detecting Korotkoff sounds while deflating an arm cuff. Using this method as a ?gold standard? requires highly-trained technicians and has an intrinsic uncertainty in its BP predictions. In this document, we analyze and characterize the origins of BP uncertainty. By analyzing the captured bio signals we postulate an uncertainty model for two consecutive BP measurements. Our research group developed a computer-based simulation of auscultatory BP measurement uncertainty, and these modeled results were compared to a humansubject experiment with a group of 20 diverse-conditioned individuals. Uncertainties were categorized and quantified. The total computer-simulated uncertainty ranged between -8.4 mmHg to 8.4 mmHg in systolic BP and -8.4 mmHg to 8.3 mmHg in diastolic BP at a 95% confidence interval. The limits in the human-based study ranged from -8.3 mmHg to 8.3 mmHg in systolic BP and -16.7 mmHg to 4.2 mmHg in diastolic BP

Confidence interval estimation for oscillometric blood pressure measurements using bootstrap approaches

Although estimation of average blood pressure is commonly done with oscillometric measurements, confidence intervals (CIs) for systolic blood pressure (SBP) and diastolic blood pressure (DBP) are not usually estimated. This paper adopts bootstrap methodologies to build CI from a small sample set of measurements, which is a situation commonly encountered in practice. Three bootstrap methodologies, namely, nonparametric percentile bootstrap, standard bootstrap, and bias-corrected and accelerated bootstrap are investigated. A two-step methodology is pro