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

Abstract

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.