Comparison of two methods in the estimation of vertical jump height
Bibliographic record
Abstract
Vertical jumps are vital aspects in many sports. Many technologies are available to determine and calculate jump height. One such portable and easy-to-use technology is an Inertial Measurement Unit (IMU) that uses accelerometers, gyroscopes and magnetometers. The purpose of this study was to compare vertical jump heights calculated from the data captured with an IMU versus true jump height calculated using a gold standard 3-Dimensional Motion Capture system. Ten subjects completed five jumps for six different conditions including vertical counter-movement jumps and jumps involving rotations on the ground and using a trampoline. An average Pearson correlation coefficient of 0.87 was found between the IMU and motion capture for all conditions. Condition correlations ranged from 0.76 to 0.94. Bland-Altman analyses showed that the IMU underestimated the vertical jump height compared to the motion capture by 5.0 to 9.2 cm across all conditions. Results suggest an IMU can be used to measure jump height in a laboratory setting with a reasonable accuracy, even during vertical jumps that include rotations.
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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 | 0.009 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".