Virtual fit and design improvements of a filtering half-mask for sub-adult wearers.

ABSTRACT

The recent pandemic has shown that protecting the general population from hazardous substances or pathogens can be a challenging and urgent task. The key element to adequate protection is appropriately sized, well-fitted and sufficiently distributed personal protective equipment (PPE). While these conditions are followed for adult PPE wearers, they are less considered when it comes to protecting subadults. In this study, the assessment of the fit and design improvements of a 3D-printed facial half mask for subadult wearers (4-18 years) is designed. The target population was represented by 1137 subadults, aged 4.06-18.94 years, for whom 3D face models were acquired. The half mask tested, which was originally provided in one subadult size, did not fit appropriately the target population. This finding prompted the creation of four size categories using the age-dependent distribution of the centroid size calculated from 7 facial landmarks. For each size category, a modified half-mask virtual design was created, including resizing and reshaping, and fit was evaluated visually and numerically using averaged and random 3D face representatives.Practitioner summary: The reason for this study was to describe procedures which led to design improvement of an existing half-mask and provide respiratory protection for subadults. To address this, fit was assessed using an innovative metric approach. Four sizes were then created based on centroid size, resulting in improved fit and design.Abbreviations CH cheilion landmark; CS centroid size; EX exocanthion landmark; GN gnathion landmark; N nasion landmark; PPE personal protective equipment; PR pronasale landmark; RPE respiratory protective equipment.

3D human face dataset was used for modifying and validating protective equipment for subadultsTo ensure optimal protection for subadults, four size categories were proposed based on 3D face landmarks and centroid sizeModified half-mask design fit was validated virtually using a visual and numerical approach.