The effect of fatigue on lower limb coordination characteristics in badminton forehand smash: a functional principal component analysis
Bibliographic record
Abstract
The study of motor coordination explores how the central nervous system controls body movements. Using functional principal component analysis (FPCA), this study examined the impact of fatigue on limb coordination synergies and activity coefficients in 23 badminton players performing forehand smashes before and after fatigue. Kinematic data revealed that pre-fatigue, three coordination synergies effectively controlled all lower limb joints, while post-fatigue, four synergies were required, reflecting increased control complexity. Fatigue significantly altered synergy control: Synergy 2's control of the hip joint decreased, control of the right ankle increased (p < 0.05), and Synergy 3's control of the left ankle decreased (p < 0.05). Fatigue also shifted synergy activity, enhancing Synergy 3 control during landing while reducing Synergy 1 control in the follow-through. These findings highlight how fatigue modifies coordination strategies, increasing joint control complexity, with implications for training to enhance performance stability and reduce injury risks.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".