Biomechanical Analysis Methods to Assess Professional Badminton Players' Lunge Performance
Bibliographic record
Abstract
Under the condition of simulating a badminton court in the laboratory, this study used the injury mechanism model to analyze the maximal right lunge movements of eight professional badminton players and eight amateur players. The purpose of this protocol is to study the differences in kinematics and joint moment of the right knee and ankle. A motion capture system and force plate were used to capture data of the joint movements of the lower extremity and the vertical ground reaction force (vGRF). Sixteen young men who did not have any sports injuries in the past 6 months took part in the study. The subjects performed a maximal right lunge from the start position with their right foot, stepping on and fully contacting with the force plate, hit the shuttlecock with an underhand stroke to the designated position in the backcourt, and then returned to the start/end position. All subjects wore the same badminton shoes to avoid a difference in impact from different badminton shoes. The amateur players showed a greater range of ankle movement and reverse joint moment on the frontal plane, and a larger internal joint rotation moment on the horizontal plane. The professional badminton players exhibited greater knee moment on the sagittal and frontal planes. Therefore, these factors should be considered in the development of the training program to reduce the risk of sports injuries in knee and ankle joints. This study simulates the real badminton court and calibrates the range of activities of each movement of the subjects so that the subjects complete the experimental action in a natural state with high quality. A limitation of this study is that it does not combine joint load and muscle activity. Another limitation is that the sample size is small and should be expanded in future studies. This research method can be applied to the lower limb biomechanical research of other footwork in the badminton project.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".