Subjective Effects of Using a Passive Upper Limb Exoskeleton for Industrial Textile Workers
Bibliographic record
Abstract
Industrial wool textile production exposes workers mainly to the biomechanical loading of the shoulder joint. In this work context, which is characterized by poor machine ergonomics, exposure to biomechanical risk factors, and variable work organization, exoskeletons could facilitate work processes or could be a valuable means to protect workers from overuse injuries. Field evaluation is essential to verify the suitability of specific devices and their acceptance by users. As part of a pilot study, we examined the short-term subjective effects of a passive Arm-Support Exoskeleton (ASE) on workers performing repetitive overhead tasks. In a textile factory, eight workers participated in the study, answering questionnaires after carrying out a work session with (ASE) and without an exoskeleton (FREE). Participants had been using the Paexo exoskeleton for 4.2±5.8 months (min 0–max 12). Subjective evaluations were collected regarding the workload (NASA-TLX) and relief (Borg’s CR10 scale) obtained from the use of the exoskeleton, satisfaction (Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST)), usability (System Usability Scale (SUS)), and opinions on the ergonomics of the device (Ergonomics questionnaire). Workers reported a high workload (NASA 7.2±1.0) and assessed a 46% reduction in effort on the CR10 in ASE conditions compared to FREE. They expressed high satisfaction with most characteristics of the ASE (100% satisfied with durability and effectiveness), high level of usability (62% of scores above 80, out of a maximum score of 100), and ergonomics of the device (88±12, out of a maximum score of 110). In addition to the objective effects (electromyography (EMG) reduction) already demonstrated in a previous publication, these qualitative results demonstrate a positive perception by textile workers regarding the effectiveness, usability, and suitability of the exoskeleton. The adoption of ASE in the textile industry appears beneficial in the short term, but the impact associated with individual variables and long-term effects remains to be explored.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".