Analysis of terrain effects on the interfacial force distribution at the hand and forearm during crutch gait
Bibliographic record
Abstract
Forces transferred to the upper body during crutch use can lead to both short-term and long-term injuries, including joint pain, crutch palsy, and over-use injuries. While this force transmission has been studied in controlled laboratory settings, it is unclear how these forces are affected by irregular terrains commonly encountered during community ambulation. The purpose of this study was to determine the effects of walking speed and uneven terrain on the load magnitude, distribution, and rate of loading at the human-crutch contact surfaces. Our results show that the rates of loading were significantly increased with higher walking speeds and while negotiating certain irregular terrains, despite there being no apparent effect on the peak force transmission, suggesting load rate may be a more appropriate metric for assessing terrain effects on crutch gait. Furthermore, irrespective of the type of terrain and walking condition, the largest compressive forces were found to reside in the carpal-tunnel region of the hand, and may therefore be a primary contributor to carpal-tunnel injury.
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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) | 0.000 | 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".