Fixed foot balance training increases rectus femoris activation during landing and jump height in recreationally active women.
Bibliographic record
Abstract
The objective of this study was to determine the effects of fixed foot and functionally directed balance training on static balance time, muscle activation during landing, vertical jump height and sprint time. Twenty-four recreationally active females were tested pre- and post-training (fixed foot balance training, n= 11, functionally directed balance training, n = 7 and control group, n = 6). Experimental subjects completed either fixed foot or functionally directed balance exercises 4 times/week for 6 weeks. Surface electromyography (EMG) was used to assess preparatory and reactive muscle activity of the rectus femoris (RF), biceps femoris (BF), and the soleus during one- and two-foot landings following a jump. Maximum vertical jump height, static balance and 20-meter sprint times were also examined. The fixed foot balance-training group showed a 33% improvement (p < 0.05) in static balance time and 9% improvement in jump height. Neither type of training improved sprint times. Further analysis revealed significant (p < 0.05) overall (data collapsed over groups and legs) increases in reactive RF activity when landing. Independently, the fixed foot balance group showed a 33% increase in reactive RF activity (p < 0.01). Overall, there was also significantly less reactive co-activation following training (p < 0.05). It appears that fixed foot balance training for recreationally active women may provide greater RF activity when landing and increased countermovement jump height. Key pointsBalance training increased rectus femoris EMG activity upon landing from a stride.Fixed foot balance training improved countermovement jump height.Neither fixed foot nor functionally directed balance training elicited changes in sprint times.
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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 | 0.000 |
| 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 | 0.000 |
| 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".