Abstract

This paper presents a multilayer Monte Carlo model of a healthy human neck to investigate the light-tissue interaction during different perfusion states within its dermal layer. Whilst there is great interest in advancing wearable technologies for medical applications, and non-invasive techniques like photoplethysmography (PPG) have been studied in detail, research has focused on more conventional body regions like the finger, wrist, and ear. Alternatively, the neck could offer access to additional physiological parameters which other body regions are unsuitable for. The aim of this work was to investigate the effects of several factors that would influence the optimum design of a reflectance PPG sensor for the neck. These included the source-detector separation on the optical path, penetration depth, and light detection efficiency. The results were generated from a static multilayer model in a reflectance mode geometry at two wavelengths, 660 nm and 880 nm, containing different blood volume fractions with a fixed oxygen saturation. Simulations indicated that both wavelengths penetrated similar depths, where optimal source-detector separation should not exceed 3 mm or 2.4 mm, for red and infrared respectively. Within this range, light interrogates the dermal-fat boundary corresponding to the last neck tissue layer positively contributing to a neck PPG acquisition.

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