City Research Online

Abstract

Photoplethysmography (PPG) has been hailed as a non-invasive and low-cost optical measurement technique. It is used for a wide range of applications in clinical settings and wearable devices by monitoring the pulsations associated with changes in blood volume in a peripheral vascular bed. However, one unresolved limitation of PPG is the effect of skin pigmentation on the signal and its impact on pulse oximetry. While this phenomenon was first revealed in the 1980s, numerous publications since the COVID-19 pandemic have led this topic to resurface. The causes of discrepancies found in oxygen saturation measurement by pulse oximetry (SpO2), specifically its overestimation of true SaO2 in individuals with darker skin, are still unclear and require further research.

The interchangeable relationship between in vivo and in-silico studies supports the utilisation of Monte Carlo (MC) models, a computational tool which has been extensively used to predict and analyse the optical interactions within multiple tissue layers. Hence, this thesis focuses on presenting several novel MC models, which simulate different skin pigmentations in the finger. Different optical parameters are predicted and used to quantify the effect of skin pigmentation on the PPG output. The first model examines melanin concentration in the visible range in the epidermis, which is then expanded to include a multilayer finger model in both reflectance and transmittance modes. The third model evaluates the impact of melanin on simulated pulse oximeter calibration algorithms, and finally, simulations of PPG signals are presented. Overall, the computational results show that skin pigmentation may influence a range of optical parameters, with some more significantly than others. Most importantly, the simulations qualitatively reproduced the overestimation of SaO2 as pigmentation increased, highlighting that a one-algorithm-fits-all approach may not be suitable. Software-based corrective measures may be required to minimise SpO2 bias between populations.

Publication Type:	Thesis (Doctoral)
Subjects:	Q Science > QA Mathematics > QA76 Computer software Q Science > QH Natural history > QH301 Biology R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Departments:	School of Science & Technology > Department of Engineering School of Science & Technology > School of Science & Technology Doctoral Theses Doctoral Theses

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