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Title: Opto-physiological modelling of pulse oximetry
Authors: Azorin-Peris, Vicente
Issue Date: 2008
Publisher: © Vicente Azorin Peris
Abstract: Since its conception decades ago, pulse oximetry-the non-invasive measurement of arterial blood oxygen saturation in real-time-has proven its worth by achieving and maintaining its rank as a compulsory standard of patient monitoring. However, the use of oversimplified models to describe and implement the technology has limited its applicability and has had its evolution at a near standstill for the past decade. Currently available technology relies on empirical calibrations that consist of the correlation between simultaneous measurements from pulse oximeters and invasively acquired arterial blood samples from test subjects, mainly because the mathematical models underlying the technology are not sufficiently descriptive and accurate. Advances in knowledge of human tissue optical properties, computing power and sensing technology all contribute to a new realm of expansion for pulse oximetry modelling. This research project aims to develop a methodology for improving optophysiological models of pulse oximetry through the use of a validated Monte Carlo simulation platform for optical propagation in arbitrary geometries. The platform aims to arrive at a model that can predict the widest range of empirical outcomes while maintaining the highest possible level of accuracy. To this end, an empirical platform and a corresponding experimental protocol is developed towards an increasingly repeatable standard, thus providing an empirical output for validation of simulated data. Subsequently, the parameters and coefficients of the optophysiological model at the core of the simulation platform are iterated until a high level of correlation is achieved in their outputs. This gives way to a new approach to the opto-physiological modelling of pulse oximetry.
Description: A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/22498
Appears in Collections:PhD Theses (Mechanical, Electrical and Manufacturing Engineering)

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