Abstract

This project investigated and evaluated how to automatically generate a customized oronasal mask (PPE) model adapted to each user’s face, based on facial scanning data and a generic model designed for additive manufacturing using an elastic material. The work covered the characterization of the resulting point clouds and the development of a unique facial referencing algorithm, through to an automatic fitting procedure for the generic PPE model and its validation through physical fit tests. As a result, the entire process was integrated into a software application capable of generating, for each scanned face, a customized 3D model ready for printing.