All ETDs from UAB

Advisory Committee Chair

Cladiu Lungu

Advisory Committee Members

Jonghwa Oh

Kristina Zierold

Document Type

Thesis

Date of Award

2022

Degree Name by School

Master of Science in Public Health (MSPH) School of Public Health

Abstract

According to the National Institute of Occupational Health and Safety (NIOSH), each day nearly 2,000 workers sustain a job-related eye injury that requires medical treatment. It has been reported that the cause of these eye injuries is frequently due to workers not wearing eye protection because it does not fit properly on their faces. To improve the fit of eye protection, we are aiming to develop a fit matching application (app) which will identify the wearers’ better-fitting safety eyewear using 3D technology. We have successfully tested the feasibility of the use of commercially available 3D scanning apps using a mannequin head to integrate into the app we develop. However, such scanning apps need to be tested with actual human faces whose dimensions and texture are different from mannequin faces. The purpose of the present study was to validate the accuracy of 3D scanning apps for use in identification of better-fitting safety eyewear for the wearer to help reduce eye injuries. This study consisted of three steps: scanning of a participant’s head using two commercially available 3D scanning apps, scanning of participant’s head using a high precision scanner, and comparison of the app data with the scanner data. Fifteen participants representing four races/ethnicities, African American, Caucasian, Hispanic/Latino, and Asian, were recruited iii for the study. Approximately half (N=8) of them were women. Nineteen facial landmarks were located on the subjects’ face using a dermographic pen and eyeliner and each individual’s head was scanned with two 3D scanning smartphone applications, Polycam and Metascan, and one high precision 3D scanner. Seven facial dimensions were measured including bizygomatic breadth, nasal root breadth, morphological nose breadth, anatomical nose breadth, inner canthal distance, outer canthal distance, and maximum frontal breadth on images obtained from the scanning apps and scanner based on the landmarks in a computer aided design (CAD) program. Friedman’s Test for non-parametric repeated measure test was conducted on 15 individuals to examine the accuracy of 3D scanning apps in seven anthropometric measurements compared to the high precision 3D scanner. Results showed that the 3D scanning smartphone apps and the high precision 3D scanner showed no significant differences in all seven measurements (p=0.3679-0.9636), indicating that the 3D scanning apps provide similar results to the high precision scanner. We conclude that using the two smartphone 3D scanning apps to integrate into a fit-matching app we develop is feasible.

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