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Air seal performance of personalized and statistically shaped 3D-printed face masks compared with market-available surgical and FFP2 masks

The ongoing COVID-19 pandemic has revealed alarming shortages of personal protective equipment for frontline healthcare professionals and the general public. Therefore, a 3D-printable mask frame was developed, and its air seal performance was evaluated and compared. Personalized masks (PM) based on...

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Detalles Bibliográficos
Autores principales: Nold, Julian, Metzger, Marc C., Schwarz, Steffen, Wesemann, Christian, Wemken, Gregor, Pieralli, Stefano, Kernen, Florian, Weingart, Julia, Schirmeister, Carl G., Schumann, Stefan, Schlager, Stefan, Spies, Benedikt C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8481495/
https://www.ncbi.nlm.nih.gov/pubmed/34588584
http://dx.doi.org/10.1038/s41598-021-98963-0
Descripción
Sumario:The ongoing COVID-19 pandemic has revealed alarming shortages of personal protective equipment for frontline healthcare professionals and the general public. Therefore, a 3D-printable mask frame was developed, and its air seal performance was evaluated and compared. Personalized masks (PM) based on individual face scans (n = 8) and a statistically shaped mask (SSM) based on a standardized facial soft tissue shape computed from 190 face scans were designed. Subsequently, the masks were additively manufactured, and in a second step, the PM and SSM were compared to surgical masks (SM) and FFP2 masks (FFP2) in terms of air seal performance. 3D-printed face models allowed for air leakage evaluation by measuring the pressure inside the mask in sealed and unsealed conditions during a breathing simulation. The PM demonstrated the lowest leak flow (p < 0.01) of inspired or expired unfiltered air of approximately 10.4 ± 16.4%, whereas the SM showed the highest (p < 0.01) leakage with 84.9 ± 7.7%. The FFP2 and SSM had similar values of 34.9 ± 18.5% leakage (p > 0.68). The developed framework allows for the time- and resource-efficient, on-demand, and in-house production of masks. For the best seal performance, an individually personalized mask design might be recommended.