Exploring the potential utility of a wearable accelerometer for estimating impact forces in ballet dancers
Bibliographic record
Abstract
Excessive forces and/or loading rates during landing may place ballet dancers at risk for overuse injury. The ability to estimate and monitor the landing forces of ballet dancers could help to improve injury prevention and rehabilitation; however, force platforms are not conducive to testing outside of a laboratory. Fortunately, it may be possible to indirectly assess landing forces via a wearable accelerometer. The purposes of this study were to examine the relationship between impact accelerations, recorded via a pelvis-worn accelerometer, and the peak forces and loading rates during performance of a common ballet manoeuvre, and to examine if a wearable accelerometer is sensitive to fatigue-related changes in landing forces. Fifteen ballet dancers continuously performed a ballet manoeuvre until self-determined exhaustion while impact accelerations and landing forces were simultaneously recorded using an accelerometer and force platforms. We observed very strong, positive relationships between the impact accelerations and the peak forces and loading rates during the landings. In addition, the changes in impact accelerations with fatigue paralleled the changes in the peak forces and loading rates. As a result, it appears that a wearable accelerometer could be used to estimate and monitor landing forces in ballet dancers.
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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 | 0.002 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".