Assessing forearm exertion in manual tasks with surface EMG: A comparative analysis of through-forearm vs. muscle-specific EMG placements
研究比较了穿前臂与肌肉特定表面肌电图放置位置在评估手工作业中用力与感知用力的效果，发现穿前臂放置略优，模型拟合度高。
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. 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. All sEMG placements predicted exertion and force with strong fit (R 2 > 0.95) and high precision. Through-forearm sEMG slightly outperformed extensor and flexor placements and was closely correlated with their signals. 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. • We tested a novel EMG placement against other common ones in assessing hand exertion. • All sEMG placements predict exertion and force with strong model fit and low errors. • Through-forearm slightly outperforms extensor and flexor in predicting exertion and force. • Through-forearm sEMG is linearly correlated with a combination of extensor and flexor. • Moderate inter-subject and inter-task variability is observed across prediction models.