Quantification of Tissue Oxygenation Using an Intensity-Based Wearable Device and Machine Learning Approaches

Juan Pedro Cascales; Daniel A. Greenfield; Emmanuel Rousakis; Lilian Witthauer; Xiaolei Li; Avery Goss; Conor L. Evans

doi:10.1364/OMP.2021.OM3E.3

Biophotonics Congress 2021
OSA Technical Digest (Optica Publishing Group, 2021),
paper OM3E.3
•https://doi.org/10.1364/OMP.2021.OM3E.3

Quantification of Tissue Oxygenation Using an Intensity-Based Wearable Device and Machine Learning Approaches

Juan Pedro Cascales, Daniel A. Greenfield, Emmanuel Rousakis, Lilian Witthauer, Xiaolei Li, Avery Goss, and Conor L. Evans

Optical Molecular Probes, Imaging and Drug Delivery 2021

Washington, DC United States
12–16 April 2021
ISBN: 978-1-943580-85-9

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Instrumentation and Image Analysis (OM3E)

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J. P. Cascales, D. A. Greenfield, E. Rousakis, L. Witthauer, X. Li, A. Goss, and C. L. Evans, "Quantification of Tissue Oxygenation Using an Intensity-Based Wearable Device and Machine Learning Approaches," in Biophotonics Congress 2021, C. Boudoux, K. Maitland, C. Hendon, M. Wojtkowski, K. Quinn, M. Schanne-Klein, N. Durr, D. Elson, F. Cichos, L. Oddershede, V. Emiliani, O. Maragò, S. Nic Chormaic, N. Pégard, S. Gibbs, S. Vinogradov, M. Niedre, K. Samkoe, A. Devor, D. Peterka, P. Blinder, and E. Buckley, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper OM3E.3.

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Abstract

We report a lightweight, cost-efficient wearable device to measure phosphorescence of an oxygen-sensing dye, leading to an estimation of pO₂ through fit-based and machine learning approaches.

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