Abdullah, Johari Yap, Caggiari, Silvia, Keenan, Bethany ![]() ![]() ![]() |
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Abstract
N95/FFP3 respirators have been critical to protect healthcare workers and their patients from the transmission of COVID-19. However, these respirators are characterised by a limited range of size and geometry, which are often associated with fitting issues in particular sub-groups of gender and ethnicities. This study describes a novel methodology which combines magnetic resonance imaging (MRI) of a cohort of individuals (n = 8), with and without a respirator in-situ, and 3D registration algorithm which predicted the goodness of fit of the respirator. Sensitivity analysis was used to optimise a deformation value for the respirator-face interactions and corroborate with the soft tissue displacements estimated from the MRI images. An association between predicted respirator fitting and facial anthropometrics was then assessed for the cohort.
Item Type: | Article |
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Date Type: | Published Online |
Status: | Published |
Schools: | Engineering |
Publisher: | Public Library of Science |
ISSN: | 1932-6203 |
Date of First Compliant Deposit: | 14 November 2022 |
Date of Acceptance: | 30 October 2022 |
Last Modified: | 04 May 2023 16:15 |
URI: | https://orca.cardiff.ac.uk/id/eprint/154135 |
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