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.
|Journal Article Type||Article|
|Publication Date||Jul 1, 2016|
|Peer Reviewed||Peer Reviewed|
|Institution Citation||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|
|Keywords||Offshore workers; Window egress; Binary logistic regression; 3D scanning|
STEWART 2016 The ability of UK offshore workers of different
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