In Silico Blood Pressure Models Comparison

In Silico Blood Pressure Models Comparison

Keywords: Arterial pressure waveform, continuous and noninvasive blood pressure (BP) measurement, hypertension monitoring, mathematical BP model, pulse pressure (PP), ultrasound (US) sensor

Hauptforschende*r

Dr. Ana Belén Amado Rey

Forschungsinstitut

Albert-Ludwigs-Universität Freiburg

Abstract

Abstract: As cardiovascular diseases (CVDs) are one of the most prominent illnesses, continuous, noninvasive, and comfortable monitoring of blood pressure (BP) is indispensable. This article investigates the best method for obtaining highly accurate BP values in noninvasive measurements through the extraction of hemodynamic variables from the arteries of young subjects. After the literature review, five state-of-the-art BP models were analyzed and qualitatively compared in a novel in silico study. Relevant arterial parameters such as luminal area, flow velocity, and pulse wave velocity (PWV) of 1458 subjects were extracted from a computer-simulated database and served as input parameters in the BP models’ simulation. The five models were calibrated to each arterial site. Contrary to the expected, the linear model (linear transformation of the distending diameter into BP) revealed more accuracy than the commonly used exponential transformation. In an ex vivo experimental setup, the linear model was used for the extraction of BP by using an ultrasound (US) sensor and validated with a commercial pressure sensor. The results showed an in silico pulse pressure (PP) correlation of 0.978 and a mean difference of (−2.845 ± 2.565) mmHg at the radial artery and an ex vivo PP correlation of 0.986 and a mean difference of (1.724 ± 3.291) mmHg. Thus, with the linear model, the US measurement complies with the Association for the Advancement of Medical Instrumentation (AAMI) standard with smaller deviations than ±5 mmHg.

Fördersumme

30.000 Euro (2019)

Publikationen

Beschreibung Dokument Link
In Silico Blood Pressure Models Comparison IEEE Sensors Journal;2022;22;23;10.1109/JSEN.2022.3215597
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