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Three-dimensional facial parameters and principal component scores: association with respirator fit.
Groce-D; Guffey-S; Viscusi-DJ; Lynch-S; Benson-S; Zhuang-Z
J Int Soc Respir Prot 2010 Jan; 27(1):1-15
Human facial dimensions play a significant role in the determination of respirator fit. Fit test "panels" intended to represent a range of wearer facial characteristics have been defined on the basis of specific facial dimensions such as face width and face length. The goal of this investigation was to identify facially-related variables that are worthy of further investigation. Specifically this investigation explored the extent to which facial parameters (such as angles and areas) or principal component analysis (PCA) scores derived from facial measurements of test subjects might be associated with the fit of four half-mask respirators. Thirty subjects were each evaluated for several facial parameters and PCA scores for facial size and facial shape. The facial parameter data were obtained by means of three-dimensional (3D) laser scanning technology and commercial computer software developed for the evaluation of the 3D scanned images. The same thirty subjects were each fit tested using the ambient aerosol quantitative technique while he or she wore each of four different models of half-mask respirators in small, medium, and large sizes. The fit test results and the derived facial parameters and PCA scores were analyzed by forward selection stepwise linear regression, with the derived facial parameters and PCA scores used as the independent variables. The resulting regression models had R(2) values ranging between 0.08 and 0.60 for individual models/sizes of respirators. Nose area was a significant contributor for 10 of the 12 regressions. The next closest variable (alare-sellion angle) contributed to 5 of the 12 regressions. PCA1 was a significant contributor for 8 of the 12 respirator model/size regressions, while PCA2 was a significant contributor for only 4 of the 12 regressions. The authors concluded that a non-linear 3-D parameter derived in this study (nose area) was found to be frequently correlated to respirator fit and the nose area may be more significant than other 3D parameters. The PCA score associated with overall face size (PCA1) was more important than the PCA score associated with facial shape (PCA2). The findings are significant in that they can potentially influence the composition of future respirator fit test panels.
Respirators; Respiratory-protective-equipment; Face-masks; Anthropometry; Humans; Human-factors-engineering; Measurement-equipment; Testing-equipment; Lasers; Scanning-techniques; Laboratory-testing; Aerosols; Quantitative-analysis; Mathematical-models; Author Keywords: respirator fit; facial dimensions; three-dimensional scan; principal component analysis; PCA; fit test panels
Ziqing Zhuang, National Institute for Occupational Safety and Health, National Personal Protective Technology Laboratory, 626 Cochrans Mill Road, P.O.Box 18070, Pittsburgh, PA 15236
Issue of Publication
Services: Public Safety
Journal of the International Society for Respiratory Protection
West Virginia University
Page last reviewed: April 12, 2019
Content source: National Institute for Occupational Safety and Health Education and Information Division