A Biomechanical Approach to Paralympic Cross-Country Sit-Ski Racing
Bibliographic record
Abstract
OBJECTIVE: To analyze the biomechanics of the double poling (DP) gesture in cross-country disabled sit-skiers in the field during competition. DESIGN: Cross-sectional research. SETTING: One-kilometer sprint race, Winter Paralympic Games, Vancouver 2010, Canada. PARTICIPANTS: Paralympic athletes: 35 men and 15 women, classified in all the 5 classes of the sit-skier category. INTERVENTION: Elite sit-skiers, with different disabilities, were recorded with a high-speed markerless stereophotogrammetric camera system. Reference points were semiautomatically tracked frame-by-frame on video images, according to a biomechanical model consisting of 7 anatomical and 4 technical points. MAIN OUTCOME MEASURES: Coordinates of anatomical and technical points were evaluated for 2-dimensional kinematic analysis of the push gesture both with reference to a ground-fixed frame and with respect to the athletes' seat on the sledges. RESULTS: Several graphical results represent the development of the DP gesture of each athlete with respect to both ground reference frame and sledge reference frame. The progression of the gesture is depicted by body and pole stick diagrams, trends of reference point positions and their gradients, and body joint trajectories in space. In addition, kinematic biomechanical parameters (eg, joints' range of motion) and technical parameters (eg, pole incline, sledge velocity) are reported. CONCLUSIONS: This research demonstrates the feasibility of a markerless kinematic analysis of the poling gesture on a contest field. Results point out a wide variability of the gesture due to the residual functional capabilities and sitting postures of each athlete. However, the poling cycles of subjects classified into different classes present similar features. An original segmentation of the DP gesture in a sequence of 3 phases is proposed in the article.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".