Effect of functional knee brace use on acceleration, agility, leg power and speed performance in healthy athletes
Bibliographic record
Abstract
OBJECTIVES: To investigate performance levels and accommodation period to functional knee brace (FKB) use in non-injured braced subjects while completing acceleration, agility, lower extremity power and speed tasks. DESIGN: A 2 (non-braced and braced conditions) × 5 (testing sessions) repeated-measures design. METHODS: 27 healthy male athletes were provided a custom fitted FKB. Each subject performed acceleration, agility, leg power and speed tests over 6 days; five non-braced testing sessions over 3 days followed by five braced testing sessions also over 3 days. Each subject performed two testing sessions (3.5 h per session) each day. Performance levels for each test were recorded during each non-braced and braced trial. Repeated measures analysis of variance, with a post hoc Tukey's test for any test found to be significant, were used to determine if accommodation to FKB was possible in healthy braced subjects. RESULTS: Initial performance levels were lower for braced than non-braced for all tests (acceleration p=0.106; agility p=0.520; leg power p=0.001 and speed p=0.001). However, after using the FKB for approximately 14.0 h, no significant performance differences were noted between the two testing conditions (acceleration non-braced, 0.53±0.04 s; braced, 0.53±0.04 s, p=0.163, agility non-braced, 9.80±0.74 s; braced, 9.80±0.85 s, p=0.151, lower extremity power non-braced, 58±7.4 cm; braced, 57±8.1 cm, p=0.163 and speed non-braced, 1.86±0.11 s; braced, 1.89±0.11 s, p=0.460). CONCLUSIONS: An initial decrement in performance levels was recorded when a FKB is used during an alactic performance task. After 12.0-14.0 h of FKB use, performance measures were similar between the two testing conditions.
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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) | 0.001 | 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 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".