Assessing Increased Activities of the Forearm Muscles Due to Anti-Vibration Gloves: Construct Validity of a Refined Methodology
Bibliographic record
Abstract
Objective The primary aim was to test the construct validity of a surface electromyography (EMG) measurement protocol, indirectly assessing the effects of anti-vibration (AV) gloves on activities of the forearm muscles. Background AV gloves impose a relatively higher grip demand and thus a higher risk for musculoskeletal disorders. Consequently, activities of the forearm muscles should be considered when assessing AV glove performance. Method Effects of AV gloves on activities of the forearm muscles (ECR: extensor carpi radialis longus; ED: extensor digitorum; FCR: flexor carpi radialis; FDS: flexor digitorum superficialis) were measured via EMG, while gripping a handle with two grip force levels. Fifteen subjects participated with 11 glove conditions, including one with bare hand. Results Activities of ECR, FCR, mean of ECR and FCR (ECR_FCR), and mean of all four muscles were sensitive to wearing gloves. Compared with bare hand, combined ECR_FCR activities increased by 22%–78% (mean = 48%, SD = 28%) with gloves. The correlation coefficient ( r) of ECR_FCR activities with glove thickness and manual dexterity scores were 0.74 ( p < .05) and 0.90 ( p < .001), respectively. Conclusions A refined EMG methodology was the most sensitive to AV gloves with specific forearm muscles (ECR and FCR) and the 50-N handgrip force. Its construct validity was further substantiated by correlations with glove thickness and manual dexterity. Application Assessment of the effect of AV gloves on activities of the forearm muscles can yield design guidance for AV gloves to reduce grip exertion by the gloved hand.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".