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Symposium: Measuring posture in working life: Observation or inclinometry? [Mätning av arbetsställningar: observation eller inklinometri?]
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.
Institutet för miljömedicin, Karolinska institutet, Stockholm.
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: 0000-0002-5055-0698
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: 0000-0002-6561-5423
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2018 (Swedish)In: FALF KONFERENS 2018 Arbetet – problem eller potential för en hållbar livsmiljö?   10-12 juni 2018 Gävle: Program och abstracts / [ed] Lindberg, Per, Gävle: Gävle University Press , 2018, p. 38-40Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Quantifying postures during work is a key aspect of understanding the physical loads experienced by the body at work. Two commonly used tools to assess posture are observation and inclinometry. Observation can be performed in many ways, from real-time observations made at the worksite assessing gross body postures, to estimates of individual joint angles made by observers assessing still images taken from video recorded at the work site. Inclinometry is a direct technical measurement tool which typically uses tri-axial accelerometers to determine angles of specific body segments with respect to the line of gravity. Regardless of which tool is used, it will introduce some variability between repeated measurements of a same posture – this is called method-logical variability. Over the past ten years we have worked extensively in our Cost-efficient measurement of physical exposures research program to quantify the magnitude of error resulting from different measurement strategies – both in terms of bias (that is, the difference between the truth and the measured values) and precision (that is, how different repeated estimates of a same posture are). Further, we have compared the monetary costs and relative performances (in terms of measurement quality) of different measurement strategies. From these studies we have developed a set of recommendations to guide effective posture assessment.

We assessed bias in both observation and inclinometry to determine how close posture estimates were to the true body segment angles. Under ideal observation conditions, observers were not biased in estimating upper arm elevation angles (1). Conversely, we found a systematic underestimation of upper arm elevation angles made using inclino-metry, particularly for angles at or above 60° (2). We developed a simple, on-body incli-nometry calibration procedure, and determined it was effective at reducing inclinometer bias (2).

We investigated how data sampling should be distributed within and across days, and how much data was required to obtain a specific level of precision. Regardless of the tool, we found that efficiency was improved by distributing shorter sampling periods using a fixed-interval strategy across an entire day or days rather than collecting one longer period (3,4). Precision of inclinometer data is high and thus a single measurement of an event is sufficient. In contrast, observation requires repeated estimates of an image, even under ideal conditions (1, 5). For observation of still images from videos, we determined that efficiency was improved by assessing images extracted at set intervals across the recorded data (i.e. a work sampling approach) rather than making estimates based on continuously viewed intervals of video data (5). Further, repeated observations by one or more observers of a smaller number of frames of data improved the precision of angle estimates compared with a single observer rating a larger number of frames (6). In the case that a worker is obstructed from the camera view, additional frame analysis may be required and the uncertainty of the angle estimate may increase (7).

We developed models to assess the net cost of each method, including equipment acquisition, data collection and data analysis. While the initial expense may seem higher for inclinometers, cost gains are made during collection and analysis stages compared to the work-intensive post-collection efforts required for observation. We found that inclinometry was more cost efficient than observation in certain settings (8), but that uncertainty exists even in cost assessment models and thus that cost-efficiency is situation-dependent (9).

There are strengths and weaknesses to both tools and one must evaluate the goals of each data collection and the relative merits of each tool when determining the appropriate assessment method. Observation may be preferable for studies seeking a general impression of a working day, identifying the tasks comprising a working day, assessing twisting during work, or assessing whether anatomical segments are loaded or supported during work. Inclinometers may be preferred for studies requiring full day or multi-day assessments, a high degree of accuracy and precision in angle estimates, information on segmental movement velocities, and/or studies where workers cannot be adequately filmed. Rapid advances in inclinometer technology and smart phone analogues will serve to further minimise set-up times and acquisition costs, making direct technical measurement increasingly feasible.

1. Jackson, J. A., Mathiassen, S. E. & Liv, P. Observer performance in estimating upper arm elevation angles under ideal viewing conditions when assisted by posture matching software. Appl. Ergon. 55, 208–215 (2016).

2. Jackson, J. A., Mathiassen, S. E., Wahlström, J., Liv, P. & Forsman, M. Is what you see what you get? Standard inclinometry of set upper arm elevation angles. Appl. Ergon. 47, 242–252 (2015).

3. Liv, P., Mathiassen, S. E. & Svendsen, S. W. Theoretical and empirical efficiency of sampling strategies for estimating upper arm elevation. Ann. Occup. Hyg. 55, 436–449 (2011).

4. Liv, P., Mathiassen, S. E. & Svendsen, S. W. Accuracy and precision of variance components in occupational posture recordings: A simulation study of different data collection strategies. BMC Med. Res. Methodol. 12, 58–68 (2012).

5. Rezagholi, M., Mathiassen, S. E. & Liv, P. Cost efficiency comparison of four video-based techniques for assessing upper arm postures. Ergonomics 55, 350–360 (2012).

6. Liv, P., Mathiassen, S. E. & Wahlström, J. Statistical power and measurement requirements in studies comparing observed postures between groups. (PhD Thesis, Umeå University, 2012).

7. Trask, C., Mathiassen, S. E., Rostami, M. & Heiden, M. Observer variability in posture assessment from video recordings: The effect of partly visible periods. Appl. Ergon. 60, 275–281 (2017).

8. Trask, C., Mathiassen, S. E., Jackson, J.A. & Wahlström, J. Data processing costs for three posture assessment methods. BMC Med. Res. Methodol. 13, 124–137 (2013).

9. Waleh Åström, A., Heiden, M., Mathiassen, S. E. & Strömberg, A. Uncertainty in monetary cost estimates for assessing working postures using inclinometry, observation or self-report. in review, (2018).

Place, publisher, year, edition, pages
Gävle: Gävle University Press , 2018. p. 38-40
National Category
Occupational Health and Environmental Health
Identifiers
URN: urn:nbn:se:hig:diva-27077ISBN: 978-91-88145-28-4 (electronic)OAI: oai:DiVA.org:hig-27077DiVA, id: diva2:1219545
Conference
FALF 2018 konferens 'Arbetet - problem eller potential för en hållbar livsmiljö?', 10-12 juni 2018, Gävle
Note

Symposium contributors:

1. How can we measure posture? An introduction to observation and inclinometry.Jennie Jackson and Mikael Forsman

2. Is what you see what you get? Assessing bias in observation and inclinometry.Jennie Jackson

3. How much, when and how often? Designing efficient data collections. Svend Erik Mathiassen

4. What will it cost? Modelling costs to determine efficient data collection strategies.Marina Heiden and Amanda Waleh Åström

5. Which tool should I use? The future of observation and inclinometry.Mikael Forsman, Jennie Jackson and Svend Erik Mathiassen

Available from: 2018-06-16 Created: 2018-06-16 Last updated: 2018-12-17Bibliographically approved

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Jackson, JennieHeiden, MarinaWaleh Åström, AmandaMathiassen, Svend Erik

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