Innovation in Respirator Design, Research, & Protection: A model of predictive fit for occupational safety and health.

Linsey Griffin, Minji Yu, Susan Sokolowski, Susan Arnold, William K. Durfee

Research output: Contribution to journalConference articlepeer-review

Abstract

Improving the fit of a half-mask respirator can be achieved by developing a design, fit, and sizing strategy to fit the faces of the general population or a specific group such as race, age group, or occupation. The purpose of this study was to define respirator fit based on the body product relationship and to develop a new set of facial landmarks and measurements for half-mask respirator design. 3D scan data and quantitative fit factor scores from 47 healthcare workers and 9 researchers in healthcare-related fields were utilized to investigate the relationship of new anthropometry measurements to respirator fit. A mask fit association model was validated through logistic regression. The respirator fit prediction model incorporating highly correlated face measurements opens the possibility of developing a system for judging respirator fit success and failure based on face dimensions; it can be integrated with automated measuring technologies and machine learning.

Original languageEnglish (US)
Pages (from-to)821
Number of pages1
JournalProceedings of the Human Factors and Ergonomics Society
Volume67
Issue number1
DOIs
StatePublished - 2023
Event67th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2023 - Columbia, United States
Duration: Oct 23 2023Oct 27 2023

Bibliographical note

Publisher Copyright:
© 2023 Human Factors and Ergonomics Society.

Keywords

  • anthropometry
  • Personal Protective Equipment
  • PPE
  • respirator fit

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