Effects of Body Armor Fit on Encumbered Anthropometry Relative to Bulk and Coverage

Choi, Hyeg Joo; Garlie, Todd N.; Mitchell, K. Blake

doi:10.1007/978-3-319-94484-5_28

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…Static fit is most commonly defined through the anthropometric dimensions of users collected in a minimally clad configuration (traditional anthropometry) or in equipped configurations (encumbered anthropometry; Choi et al, 2019; Garlie & Choi, 2014; Jones et al, 2013). Anthropometry includes size data (i.e., linear dimensions) collected using standard anthropometers (e.g., calipers, tape measures) or extracted from three dimensional (3D) scan images, as well as 3D scan images themselves as shape data that provide information about a user’s external surface and contour (Hsiao, 2013; Hsiao et al, 2015; Jones et al, 2018; Margerum et al, 2010; Park et al, 2017).…”

Section: Resultsmentioning

confidence: 99%

“…Traditional anthropometric databases (Gordon et al, 2013, 2014; Harrison & Robinette, 2002) have been used to quantify anthropometric characteristics recorded in standardized postures, develop sizing systems, evaluate population accommodation rates, and generate digital human models for various target populations. Encumbered anthropometry studies include equipped size, weight, shape, and bulk in various ensemble configurations (Choi, Garlie et al, 2019; Garlie & Choi, 2014; Hsiao, 2013; Jones et al, 2013), as well as 3D surface coverage of a body within the geometry of equipment or a device (Choi et al, 2009; Hsiao et al, 2009; Jones et al, 2014, 2015; Li et al, 1999).…”

Section: Resultsmentioning

confidence: 99%

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Static, Dynamic, and Cognitive Fit of Exosystems for the Human Operator

et al. 2020

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Objective To define static, dynamic, and cognitive fit and their interactions as they pertain to exosystems and to document open research needs in using these fit characteristics to inform exosystem design. Background Initial exosystem sizing and fit evaluations are currently based on scalar anthropometric dimensions and subjective assessments. As fit depends on ongoing interactions related to task setting and user, attempts to tailor equipment have limitations when optimizing for this limited fit definition. Method A targeted literature review was conducted to inform a conceptual framework defining three characteristics of exosystem fit: static, dynamic, and cognitive. Details are provided on the importance of differentiating fit characteristics for developing exosystems. Results Static fit considers alignment between human and equipment and requires understanding anthropometric characteristics of target users and geometric equipment features. Dynamic fit assesses how the human and equipment move and interact with each other, with a focus on the relative alignment between the two systems. Cognitive fit considers the stages of human-information processing, including somatosensation, executive function, and motor selection. Human cognitive capabilities should remain available to process task- and stimulus-related information in the presence of an exosystem. Dynamic and cognitive fit are operationalized in a task-specific manner, while static fit can be considered for predefined postures. Conclusion A deeper understanding of how an exosystem fits an individual is needed to ensure good human–system performance. Development of methods for evaluating different fit characteristics is necessary. Application Methods are presented to inform exosystem evaluation across physical and cognitive characteristics.

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