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Theses and Dissertations

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Browsing Theses and Dissertations by Subject "3D scanning"

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    Analysis of 3D facial anthropometric measurements for respirator fit outcomes
    (Colorado State University. Libraries, 2023) Hobbs-Murphy, Kayna, author; Rosecrance, John, advisor; Brazile, Bill, committee member; Anderson, Brooke, committee member; Morris, Kristen, committee member; Hess, Ann, committee member
    Anthropometry is central to the development of efficacious products and environments (i.e., personal protective equipment, clothing, sunglasses, chairs, interior spaces, etc.) used by humans. Three-dimensional (3D) scanning is increasingly common for collecting anthropometric data, as it is faster and less intrusive than traditional manual methods. Additionally, 3D anthropometric methods used to derive facial dimensions provide greater contextual application in the development of respirators and facemasks. More than 2,000 3D facial scans were analyzed to assess measurement reliability and the dimensions of 27 facial features. This research represents the largest sample of 3D facial anthropometrics assessed to date. The three specific aims of the research included: 1) to assess the intra- and inter-rater reliability of 3D facial measurement methods, 2) to compare the 3D facial anthropometric summary statistics from the present study to relevant summary statistics from manual facial measurements found in the literature, and 3) to assess the presence of differences in 3D facial anthropometrics related to respirator fit, based on demographic factors of gender, race/ethnicity, and age. Post hoc analyses were completed to quantify 3D facial measurement differences between demographic groups (within the larger demographic categories of gender, race/ethnicity, and age group). The most notable results of this research include a) high reliability in 3D measurement data collection methods, b) differences in measurement data summary statistics between 3D and manual methods, and c) significant differences in facial measurements between demographic categories of gender (Male and Female/Other), race/ethnicity (White, Black, LatinX, Asian, and Other), and age (18-34, 35-54, and 55-72).