The Effect Of Hand-Held Tool Vibration On Reaching
Bibliographic record
Abstract
Handling power tools can expose users to hand-arm vibration frequencies between 10 Hz - 10 kHz [3]. Vibration in the range of physiological response for muscle sensory receptors (30-150 Hz) lead to illusions that affect the accuracy and precision of proprioception [14] and vibration up to 400 Hz may lead to disordered function [8]-[9]. The purpose of this study was to study how short-term exposure to hand-held tool vibration frequencies affects reaching accuracy and precision. Forty participants (Ps) made 20 cm planar arm reaching movements to two randomly-presented visual targets (60° and 120° relative to horizontal). Ps were alternately assigned to one of four groups and exposed to one of four vibration frequencies (40, 70, 100 or 115 Hz, .5 mm amplitude) while holding a custom pen-like pointing tool fitted with a vibration device. Each subject completed 30 trials in a no-vibration pre-exposure condition, a vibration-exposure condition, and a no-vibration post-exposure condition. Accuracy and precision of movement initial direction, distance, and end-point, and movement time and peak velocity were measured. Short-term vibration can immediately and detrimentally affect the speed, accuracy, and precision of reaching movements, especially multi-joint movements. Movement distance and direction accuracy and precision were affected by vibration, but Ps adapted to this exposure. The effect of vibration was larger for 120° than the 60° movement direction. Ps who received 100 Hz vibration were more likely to experience changes in their movement performance. These results suggest that tool vibration does influence limb movement performance and should be studied further to determine its effects on limb coordination.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".