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Beer-Lambert law along non-linear mean light pathways for the rational analysis of Photoplethysmography

Rybynok, V. & Kyriacou, P. A. (2010). Beer-Lambert law along non-linear mean light pathways for the rational analysis of Photoplethysmography. Paper presented at the 13th IMEKO TC1-TC7 Joint Symposium, 01 Sep - 03 Sep 2010, London, UK. doi: 10.1088/1742-6596/238/1/012061


Photoplethysmography (PPG) is a technique that uses light to noninvasively obtain a volumetric measurement of an organ with each cardiac cycle. A PPG-based system emits monochromatic light through the skin and measures the fraction of the light power which is transmitted through a vascular tissue and detected by a photodetector. Part of thereby transmitted light power is modulated by the vascular tissue volume changes due to the blood circulation induced by the heart beating. This modulated light power plotted against time is called the PPG signal. Pulse Oximetry is an empirical technique which allows the arterial blood oxygen saturation (SpO2 – molar fraction) evaluation from the PPG signals. There have been many reports in the literature suggesting that other arterial blood chemical components molar fractions and concentrations can be evaluated from the PPG signals. Most attempts to perform such evaluation on empirical bases have failed, especially for components concentrations. This paper introduces a non-empirical physical model which can be used to analytically investigate the phenomena of PPG signal. Such investigation would result in simplified engineering models, which can be used to design validating experiments and new types of spectroscopic devices with the potential to assess venous and arterial blood chemical composition in both molar fractions and concentrations non-invasively.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: Published by IOP Publishing 2010
Subjects: Q Science > QC Physics
Departments: School of Science & Technology > Engineering
Text - Accepted Version
Available under License Creative Commons: Attribution 3.0.

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