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Observer performance in estimating upper arm elevation angles under ideal viewing conditions when assisted by posture matching software
University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research. Department of Medical Sciences, Uppsala University, Uppsala.ORCID iD: 0000-0003-2939-0236
University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research.ORCID iD: 0000-0003-1443-6211
University of Gävle, Faculty of Health and Occupational Studies, Department of Occupational and Public Health Sciences, Occupational health science. University of Gävle, Centre for Musculoskeletal Research. Centre for Research and Development, Uppsala University/Region Gävleborg, Gävle.
2016 (English)In: Applied Ergonomics, ISSN 0003-6870, E-ISSN 1872-9126, Vol. 55, 208-215 p.Article in journal (Refereed) Published
Abstract [en]

Selecting a suitable body posture measurement method requires performance indices of candidate tools. Such data are lacking for observational assessments made at a high degree of resolution. The aim of this study was to determine the performance (bias and between- and within-observer variance) of novice observers estimating upper arm elevation postures assisted by posture matching software to the nearest degree from still images taken under ideal conditions. Estimates were minimally biased from true angles: the mean error across observers was less than 2°. Variance between observers was minimal. Considerable variance within observers, however, underlined the risk of relying on single observations. Observers were more proficient at estimating 0°and 90° postures, and less proficient at 60°. Thus, under ideal visual conditions observers, on average, proved proficient at high resolution posture estimates; further investigation is required to determine how non-optimal image conditions, as would be expected from occupational data, impact proficiency.

Place, publisher, year, edition, pages
2016. Vol. 55, 208-215 p.
Keyword [en]
measurement error, working postures, observation
National Category
Environmental Health and Occupational Health
Identifiers
URN: urn:nbn:se:hig:diva-19420DOI: 10.1016/j.apergo.2016.01.012ISI: 000374074600021PubMedID: 26995050ScopusID: 2-s2.0-84959471678OAI: oai:DiVA.org:hig-19420DiVA: diva2:815668
Funder
Forte, Swedish Research Council for Health, Working Life and Welfare, 2009-1761
Available from: 2015-06-01 Created: 2015-06-01 Last updated: 2017-01-10Bibliographically approved

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Jackson, Jennie A.Mathiassen, Svend ErikLiv, Per
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