Transmission of Acceleration From a Synchronous Vibration Exercise Platform to the Head During Dynamic Squats
Bibliographic record
Abstract
Many research studies have evaluated the effects of whole-body vibration exercise on muscular strength, standing balance, and bone density, but relatively few reports have evaluated safety issues for vibration exercises. Knee flexion reduces acceleration transmission to the head during static exercise. However, few studies have evaluated dynamic exercises. The purpose of this investigation was to evaluate the transmission of acceleration to the head during dynamic squats. Twelve participants performed dynamic squats (0°-40° of knee flexion) on a synchronous vertical whole-body vibration platform. Platform frequencies from 20 to 50 Hz were tested at a peak-to-peak nominal displacement setting of 1 mm. Transmissibilities from the platform to head varied depending on platform frequency and knee flexion angle. We observed amplification during 20 and 25 Hz platform vibration when knee flexion was <20°. Vibration from exercise platforms can be amplified as it is transmitted through the body to the head during dynamic squats. Similarly, this vibration energy contributes to observed injuries such as retinal detachment. It is recommended that knee flexion angles of at least 20° and vibration frequencies above 30 Hz are used when performing dynamic squat exercises with whole-body vibration.
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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 | 0.000 | 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) | 0.002 | 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".