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Authors: Leah DeVos 1 ; Gennadi Saiko 2 and Alexandre Douplik 2 ; 3

Affiliations: 1 Department of Engineering, Toronto Metropolitan University, Toronto, Canada ; 2 Department of Physics, Toronto Metropolitan University, Toronto, Canada ; 3 iBest, Keenan Research Centre of the LKS Knowledge Institute, St. Michael’s Hospital, Canada

Keyword(s): Skin Tone, Melanin, Tissue Optics.

Abstract: Background: Skin colour is essential to skin and wound assessment as it brings valuable information about skin physiology and pathology. An approach, which can help deconvolute and isolate various mechanisms affecting skin colour, could be helpful to drive the rPPG utility beyond its current applications. Aim: The present work aims to create a framework that links skin colour with melanin content. Material and methods: The model consists of two parts. First, the model’s core connects tissue chromophore concentrations with changes in tissue reflectance. Seven-layer tissue models and Monte Carlo simulations were used to obtain the tissue reflectance spectra. In the second step, the tissue reflectance is convoluted with the responsivity of a sensor (tristimulus response in the case of the human eye) and the light source’s emission spectrum. Results: The model allows linking melanin content with skin colour. Conclusion: The model can be helpful for the interpretation of the amplitudes of various components of the rPPG signal. (More)

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Paper citation in several formats:
DeVos, L.; Saiko, G. and Douplik, A. (2023). Skin Tone via Device-Independent Colour Space. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOIMAGING; ISBN 978-989-758-631-6; ISSN 2184-4305, SciTePress, pages 124-128. DOI: 10.5220/0011748100003414

@conference{bioimaging23,
author={Leah DeVos. and Gennadi Saiko. and Alexandre Douplik.},
title={Skin Tone via Device-Independent Colour Space},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOIMAGING},
year={2023},
pages={124-128},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011748100003414},
isbn={978-989-758-631-6},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOIMAGING
TI - Skin Tone via Device-Independent Colour Space
SN - 978-989-758-631-6
IS - 2184-4305
AU - DeVos, L.
AU - Saiko, G.
AU - Douplik, A.
PY - 2023
SP - 124
EP - 128
DO - 10.5220/0011748100003414
PB - SciTePress

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