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Thesis

French

ID: <

http://hdl.handle.net/20.500.11794/67369

>

Where these data come from
Design/validation of an electronic arterial pressure measuring device and evaluation of the performance of algorithms for estimating systemolic and diastolic pressure values

Abstract

Hypertension is taking an increasingly prominent place in our society. In fact, almost 1 in 4 Canadians are suffering from hypertension in 2019 according to Statistics Canada and constitutes the main risk factor that leads to cardiovascular diseases if left uncontrolled. In 2008, the World Health Organization (WHO) reported that 33% of deaths worldwide were due to cardiovascular disease and 55% of them were directly attributable to complications caused by hypertension. Still according to the WHO, effective cardiovascular diseases prevention involves promoting healthy lifestyles and an effective hypertension screening strategy. This strategy necessarily implies the measurement of blood pressure, which is mainly carried out using the oscillometric method. Recently, studies have shown that ambulatory measurements over a 24-hour period can better diagnose hypertension. These ambulatory measurements are done by specialized devices known as ambulatory blood pressure monitors (ABPM). However, these devices use proprietary algorithms that estimate the systolic and diastolic pressure and does not allow to obtain the raw oscillometric signal. Thus, those devices can’t be used to build a signal database in a way that blood pressure estimation algorithms found in literature can be assessed. We therefore propose the design of a light, ergonomic and compact ambulatory blood pressure measurement device whose characteristics makes it ideal for use in ambulatory contexts. The device can be installed directly on the cuff and the oscillometric signal is sent to a base station through a Bluetooth Low Energy link. Whether it is a smartphone, a tablet, a laptop or a specialized device, the base station can save the data and build a database of oscillometric signals in order to qualitatively assess systolic and diastolic blood pressure estimation algorithms proposed by the literature.

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