Deriving statistical fit contours and shape of an aerosol mask from 3D head scans

Abstract

This paper deals with mask shape design to ensure a statistical fit for a given population represented by tessellated 3D head scans. The mask rim curve should contact the face without gaps. This work identifies corresponding points on the mask and facial landmarks. The landmarks define a coordinate frame which helps extract rim contours (mask contours) and facial midline contours (profile contours) from the 3D model. Bilateral symmetrisation procedures are used to correct mild asymmetry in the mask contours. The statistical distribution induced by the contours on a grid is used to derive percentile contour geometries. Mask shapes generated by stacking elliptic cross sections, scaling and convex hull have been explored. 5th, 50th and 85th percentile masks are used for visual fit evaluation on a set of representative faces. The procedure establishes that the landmark-based approach provides a systematic method not only for design but also for fit evaluation.

A Novel Algorithm for Determining Contact Area Between a Respirator and a Headform

“…(3,7) In this study, a superimposed contact area and an average contact area of headform/N95 FFR combinations were developed for each of the five sizes of headforms. The superimposed contact area was the union of the contact areas that were generated from the combinations of the headform and three sizing systems of N95 FFRs, while the average contact area was the mean of the contact areas.…”

“…Krishnamurthy and Sen proposed an “ideal contact area” for a mask on the human face. (7) According to the mask user’s facial geometry, the ideal contact area of the half face mask was created as a 2D planar curve on the plane that was defined by three facial landmarks (sellion, menton, and pronasale). However, no experimental contact area from existing mask products justified the proposed contact area.…”

Use of 3D Printing to Support COVID-19 Medical Supply Shortages: A Review

“…N95 respirators masks are >95% efficient at filtering 0.3-μm airborne particles and require a fit test to ensure an adequate face seal [19][20][21][22][23][24][25][26][27][28][29][30]. The CDC currently recommends N95 masks for healthcare workers caring for COVID-19 patients [29].…”

“…Moreover, a personalized mask can be designed to account for the presence of facial hair length and density. Table 3 displays 3D-imaging technologies and key findings of several studies used to create N95 mask seals [19][20][21][22][23][24][25][26][27][28]. Han et al successfully developed respirator prototypes via digital face modeling and used rapid prototyping to print silicon respirators [21].…”

“…Thus, imaging technologies provide recommended construction of optimally fitted respirator seals and masks that can be worn by healthcare workers treating COVID-19 patients. 3D laser scanning method Used a high-precision hand scanner, zgHandScan H100 captured up to 480,000 points per second [27] 3D face scanner Created three differently face models (small, medium and large) using a 3D face scanner and developed three corresponding respirators through digital modeling; designed three silicon respirator models via rapid prototyping method [21] SPG Used to collect 3D images of subjects with and without wearing a molded, cup-shaped N95 FFRs; recorded geometric data from photographic images [23] 3D face scanner Used a minimal set of landmarks to derive contact area for a half-face mask on individual human faces [22] 3D real-time surface pressure mapping system…”