Using a quantitative assessment of propulsion biomechanics in wheelchair racing to guide the design of personalized gloves: a case study
Bibliographic record
Abstract
This study with a T-52 class wheelchair racing athlete aimed to combine quantitative biomechanical measurements to the athlete's perception to design and test different prototypes of a new kind of rigid gloves. Three personalized rigid gloves with various, fixed wrist extension angles were prototyped and tested on a treadmill in a biomechanics laboratory. The prototype with 45° wrist extension was the athlete's favourite as it reduced his perception of effort. Biomechanical assessment and user-experience data indicated that his favourite prototype increased wrist stability throughout the propulsion cycle while maintaining a very similar propulsion technique to the athlete's prior soft gloves. Moreover, the inclusion of an innovative attachment system on the new gloves allowed the athlete to put his gloves on by himself, eliminating the need for external assistance and thus significantly increasing his autonomy. This multidisciplinary approach helped to prototype and develop a new rigid personalized gloves concept and is clearly a promising avenue to tailor adaptive sports equipment to an athlete's needs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".