Estimating Workers’ Physical Effort during Isometric Contractions through sEMG
The Role of Feature Selection
Bibliographic Data
Work-related musculoskeletal disorders represent one main contributor to production workers absenteeism. In industry 5.0, exoskeletons have been proposed to mitigate risks of injury by supporting workers during repetitive tasks, with surface Electromyography (sEMG) showcasing their effects. Although existing studies have primarily evaluated exoskeletons by comparing muscle activity with and without the device, a systematic investigation of which sEMG features most effectively reflect muscle fatigue during prolonged arm elevation is still missing. This study aims to evaluate the effectiveness of different sEMG features in estimating perceived physical effort during an overhead bolting-unbolting task, performed by 10 participants both with and without a passive shoulder exoskeleton. It further assesses how the use of the exoskeleton influences the fatigue-related metrics identified. sEMG signals were collected from seven bilateral muscle groups, and 15 time-, frequency-, and spatial-domain features were extracted and correlated with two subjective effort perception models. Our results highlight strong correlations between time-domain features and perceived physical effort. Moreover, comparisons between conditions demonstrate that the exoskeleton provides a measurable fatigue-reducing effect. In contrast, spatial-domain features showed weak associations with perceived effort, suggesting limited suitability for low-intensity, long-duration tasks. These findings contribute to identifying the most informative sEMG features for fatigue estimation and provide evidence of the benefits of passive exoskeletons in industrial scenarios
Feature selection · Isometric exercise · Physical medicine and rehabilitation · Physical therapy · Computer Science · Ergonomics and Human Factors · Medicine · Muscle activation and electromyography studies · Musculoskeletal pain and rehabilitation · Artificial Intelligence
| Citation velocity | historical |
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| Highly cited | No |