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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.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: 26995050Scopus ID: 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: 2017-05-02Bibliographically approved
In thesis
1. Bias and Precision in Biomechanical Exposure Assessment: Making the Most of our Methods
Open this publication in new window or tab >>Bias and Precision in Biomechanical Exposure Assessment: Making the Most of our Methods
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Background: Insufficient exposure assessment is a suggested contributing factor to the current lack of clearly characterised relationships between occupational biomechanical risk factors and musculoskeletal disorders. Minimal attention has been paid to the potential bias of measurement tools from expected true values (i.e. accuracy) or between measurement tools, and empirical data on the magnitudes of variance contributed by methodological factors for measurement tool precision are lacking.

Aim: The aim of this thesis was to quantify aspects of bias and precision in three commonly employed biomechanical risk factor assessment tools - inclinometry, observation, and electromyography (EMG) - and provide recommendations guiding their use. Methods: Upper arm elevation angles (UAEAs) were assessed using inclinometers (INC) and by computer-based posture-matching observation, and bias relative to true angles was calculated. Calibration models were developed for INC data, and their efficacy in correcting measurement bias was evaluated. The total variance of trapezius and erector spinae (ES) EMG recordings during cyclic occupational work was partitioned into biological and methodological sources, including the variance uniquely attributable to sub-maximal normalisation. Using algorithms to estimate the precision of a group mean, the efficacy of different trapezius EMG study designs was evaluated. Using precision criteria, the efficacy of different normalisation methods was assessed for ES EMG recordings.

Results and Discussion: Inclinometer measured UAEAs were biased from true angles, with increasing bias at higher angles. In contrast, computer based posture-matching observations were not biased from true angles. Calibration models proved effective at minimizing INC data bias. The dispersion of estimates between- and within- observers at any given set angle underlined the importance of repeated observations when estimating UAEAs. For EMG, a unique but relatively small component of the total variance was attributable to the methodological process of normalisation. Performing three repeats of the trapezius EMG normalisation task proved optimal at minimizing variance for one-day EMG studies, while two repeats sufficed for multi-day EMG studies. A prone normalisation task proved superior for maximizing normalised lumbar ES EMG precision.

Conclusion: Key aspects of measurement tool accuracy, bias between tools, and tool precision were quantified, and recommendations were made to guide future research study design.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2017. 90 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1329
Keyword
measurement strategy, accuracy, inclinometry, electromyography, EMG, upper arm, shoulder, low back, lumbar, thoracic
National Category
Environmental Health and Occupational Health
Identifiers
urn:nbn:se:hig:diva-23952 (URN)978-91-554-9902-0 (ISBN)
Public defence
2017-06-02, Krusenstjernasalen, Biblioteket, Kungsbäcksvägen 47, Gävle, 13:00 (English)
Opponent
Supervisors
Funder
Forte, Swedish Research Council for Health, Working Life and Welfare, 2009-1761
Available from: 2017-05-23 Created: 2017-05-02 Last updated: 2017-05-23Bibliographically approved

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