A Mobile App to Measure Facial Dimensions and Predict Respirator Size
Eric Elliott, Medhat Korna, Gregory Van Ermen, Daniel Barker, and John Lloyd
Technology Solutions Experts, Inc., 209 West Central Street, Suite 202, Natick, MA 01760, USA
Edgewood Chemical Biological Center, Research and Technology Directorate, ATTN: RDCB-DRP-R, Bldg. 3400, Aberdeen Proving Ground, MD 21010-5424, USA
The current workflow for sizing military respirators is time consuming, manually intensive, and tedious, but is necessary due to the critical need for respirators to fit properly, especially in operating environments when Warfighters may be exposed to chemical, biological, radiological, and nuclear threats. To reduce the time and resource cost of the fitting process, Technology Solutions Experts, Inc. developed a software application to rapidly generate a 3D model of a user’s face, accurately compute anthropometric measurements, and estimate the appropriate size of a respiratory protective mask. In this paper, we discuss implementing our 3D model generation and size prediction methodology in a mobile app, and collecting and analyzing data to measure the methodology’s predictive capability. Our verification and validation results show that our current method for fit prediction is insufficient to replace traditional fit tests. However, there is evidence to suggest that face measurements obtained from 3D models can produce fit predictions as accurate as hand measurements but in a fraction of the time, and without subject matter expertise.
Keywords: Respirator, mask, fit, 3D, model, prediction, face, images, measurements, anthropometry