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Assessing forearm exertion in manual tasks with surface EMG: A comparative analysis of through-forearm vs.
Xuelong Fan1, Johan Rydgård2, Liyun Yang3
1Occupational and Environmental Medicine, Department of Medical Science, Uppsala University, Uppsala, Sweden.
Background:
Hand-intensive work is associated with musculoskeletal disorders (MSDs), highlighting the need to estimate external forearm loads. Surface electromyography (sEMG) with muscle-specific placements enables continuous load monitoring but has notable limitations. This study evaluated a novel through-forearm sEMG placement against traditional extensor and flexor placements for estimating force and perceived exertion during hand-intensive tasks.
Methods:
Sixteen participants performed four tasks at five exertion levels. sEMG signals, self-rated exertion, and exerted force were recorded. Polynomial mixed-effects models estimated self-rated exertion and exerted force, while correlations between sEMG placements were analyzed.
Results:
All sEMG placements predicted exertion and force with strong fit (R2 > 0.95) and high precision. Through-forearm sEMG slightly outperformed extensor and flexor placements and was closely correlated with their signals.
Conclusion:
Through-forearm sEMG offers marginally better performance for exertion estimation in manual tasks. Further research should explore individual calibration and task-specific methods for broader applications.
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