A fatigue failure framework for the assessment of highly variable low back loading using inertial motion capture – a case study

Workers in manufacturing settings experience highly variable musculoskeletal loading, which current risk assessment methods often fail to fully capture. This study evaluated a Fatigue Failure-Based framework for estimating continuous lumbar loading from variable occupational loads. Worker movements and postures were recorded using Inertial Motion Capture technologies, and L5/S1 joint loading history was estimated through inverse dynamics. Stress cycles were analysed using Rainflow analysis, adjusted with Goodman's method, and summed using Palmgren-Miner rule to estimate cumulative damage. The framework was tested in live industrial settings with eight automotive workers across 108 trials. Logistic regression models demonstrated significant correlations between cumulative damage estimates and self-reported low-back pain (OR = 2.16, 95% CI: 1.30, 3.57). This framework provides a novel method for analysing highly variable loading to estimate cumulative exposure in ergonomics, offering a starting point for future research and potential applications in assessing low back injury risks in similar occupational settings.

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Publication Details

Journal
Ergonomics
Published
2025-02-16
DOI
https://doi.org/10.1080/00140139.2025.2460695
Citations
5
Primary Topic
Musculoskeletal pain and rehabilitation
Type
article
Field-Weighted Citation Impact
6.97

Funders

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article

A fatigue failure framework for the assessment of highly variable low back loading using inertial motion capture – a case study

Michael E. Zabala, Nathan Pool, Mark C. Schall, Iván Nail-Ulloa et al.
5 citations
Ergonomics
Musculoskeletal pain and rehabilitation
6.97
article

A fatigue failure framework for the assessment of highly variable low back loading using inertial motion capture – a case study

Michael E. Zabala, Nathan Pool, Mark C. Schall, Iván Nail-Ulloa, Matthew S. Thiese, Sean Gallagher, Richard Sesek, Robert Sesek
article en
5 citations

Abstract

Workers in manufacturing settings experience highly variable musculoskeletal loading, which current risk assessment methods often fail to fully capture. This study evaluated a Fatigue Failure-Based framework for estimating continuous lumbar loading from variable occupational loads. Worker movements and postures were recorded using Inertial Motion Capture technologies, and L5/S1 joint loading history was estimated through inverse dynamics. Stress cycles were analysed using Rainflow analysis, adjusted with Goodman's method, and summed using Palmgren-Miner rule to estimate cumulative damage. The framework was tested in live industrial settings with eight automotive workers across 108 trials. Logistic regression models demonstrated significant correlations between cumulative damage estimates and self-reported low-back pain (OR = 2.16, 95% CI: 1.30, 3.57). This framework provides a novel method for analysing highly variable loading to estimate cumulative exposure in ergonomics, offering a starting point for future research and potential applications in assessing low back injury risks in similar occupational settings.

ErgonomicsVol. 69(2)
University of Utah (US), Auburn University (US), Rocky Mountain University of Health Professions (US)
National Institute for Occupational Safety and Health
Climate action
Openalex Percentile: Top 3%
Musculoskeletal pain and rehabilitation
6.97
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A fatigue failure framework for the assessment of highly variable low back loading using inertial motion capture – a case study — Michael E. Zabala, Nathan Pool, et al. · Ergonomics (2025) | TGRS Research Map | TGRS