Older workers spend less time in extreme trunk and upper-arm postures during order-picking tasks: Results from field testing

Order picking tasks require repetitive trunk and upper arms movements that may increase the risk of developing musculoskeletal disorders, particularly among older workers due to the decline of their physical capabilities with aging. We proposed an approach based on a limited number of wearable inertial sensors to assessed exposures to non-neutral trunk and upper arms postures among both older and young workers during their regular work-shifts. The obtained data were processed accordingly to international standards (ISO 11226 and EN 1005-4) to detect the existence of possible differences associated with age-specific working strategies. While the results indicate similar trunk and upper arms movement frequencies in both groups, older workers spend a significantly smaller percentage of time in the most demanding (>60°) postures for both districts. Such findings suggest the adoption of specific strategies to reduce the biomechanical risk which might be originated by a combination of awareness of physical limits and superior working experience. In this context, the instrumental monitoring of upper body in the logistic sector may result useful to highlight critical conditions potentially able to promote the onset of musculoskeletal disorders, thus supporting the decision processes pertaining to workers' health management and aging worker retainment.

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Publication Details

Journal
Applied Ergonomics
Published
2024-12-28
DOI
https://doi.org/10.1016/j.apergo.2024.104462
Citations
1
Primary Topic
Ergonomics and Musculoskeletal Disorders
Type
article
Field-Weighted Citation Impact
0.64

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article

Older workers spend less time in extreme trunk and upper-arm postures during order-picking tasks: Results from field testing

Maria Chiara Fastame, Massimiliano Pau, Giulia Casu, Micaela Porta et al.
1 citations
Applied Ergonomics
Ergonomics and Musculoskeletal Disorders
0.64
article

Older workers spend less time in extreme trunk and upper-arm postures during order-picking tasks: Results from field testing

Maria Chiara Fastame, Massimiliano Pau, Giulia Casu, Micaela Porta, Maury A. Nussbaum
article en
1 citations

Abstract

Order picking tasks require repetitive trunk and upper arms movements that may increase the risk of developing musculoskeletal disorders, particularly among older workers due to the decline of their physical capabilities with aging. We proposed an approach based on a limited number of wearable inertial sensors to assessed exposures to non-neutral trunk and upper arms postures among both older and young workers during their regular work-shifts. The obtained data were processed accordingly to international standards (ISO 11226 and EN 1005-4) to detect the existence of possible differences associated with age-specific working strategies. While the results indicate similar trunk and upper arms movement frequencies in both groups, older workers spend a significantly smaller percentage of time in the most demanding (>60°) postures for both districts. Such findings suggest the adoption of specific strategies to reduce the biomechanical risk which might be originated by a combination of awareness of physical limits and superior working experience. In this context, the instrumental monitoring of upper body in the logistic sector may result useful to highlight critical conditions potentially able to promote the onset of musculoskeletal disorders, thus supporting the decision processes pertaining to workers' health management and aging worker retainment.

Applied ErgonomicsVol. 125
University of Cagliari (IT), Virginia Tech (US)
Ministero degli Affari Esteri e della Cooperazione Internazionale
Decent work and economic growth
Openalex Percentile: Top 24%
Ergonomics and Musculoskeletal Disorders
0.64
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Older workers spend less time in extreme trunk and upper-arm postures during order-picking tasks: Results from field testing — Maria Chiara Fastame, Massimiliano Pau, et al. · Applied Ergonomics (2024) | TGRS Research Map | TGRS