The ability of UK offshore workers of different body size and shape to egress through a restricted window space.
Stewart, Arthur; Ledingham, Robert; Furnace, Graham; Schranz, Natasha; Nevill, Alan
404 male offshore workers aged 41.4 (± 10.7 years) underwent 3D body scanning and an egress task simulating the smallest helicopter window emergency exit size. The 198 who failed were older (P < 0.01), taller (P < 0.05) and heavier (P < 0.0001) than the 206 who passed. Using all extracted dimensions from the scans, binary logistic regression identified a model (refined using backward elimination) which predicted egress outcome with 75.2% accuracy. Using only weight, bideltoid breadth and maximum chest depth, the model achieved ~70% accuracy. When anatomical dimensions categorise individuals for small window egress, 25% or more will be misclassified, with false positives (those predicted to fail, but pass) slightly outnumbering false negatives (those predicted to pass, but fail), highlighting the limitations of a predictive approach which treats the body as a rigid object. Differences in flexibility and technique may explain these observations, which may be important considerations for future research.
STEWART, A., LEDINGHAM, R., FURNACE, G., SCHRANZ, N. and NEVILL, A. 2016. The ability of UK offshore workers of different body size and shape to egress through a restricted window space. Applied ergonomics [online], 55, pages 226-233. Available from: https://doi.org/10.1016/j.apergo.2015.11.005
|Journal Article Type||Article|
|Acceptance Date||Nov 8, 2015|
|Online Publication Date||Nov 21, 2015|
|Publication Date||Jul 31, 2016|
|Deposit Date||Sep 9, 2016|
|Publicly Available Date||Nov 22, 2017|
|Peer Reviewed||Peer Reviewed|
|Keywords||Offshore workers; Window egress; Binary logistic regression; 3D scanning|
STEWART 2016 The ability of UK offshore workers of different
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