Mechanical efficiency of two commercial lever-propulsion mechanisms for manual wheelchair locomotion
Bibliographic record
Abstract
The purpose of this study was to (1) evaluate the mechanical efficiency (ME) of two commercially available lever-propulsion mechanisms for wheelchairs and (2) compare the ME of lever propulsion with hand rim propulsion within the same wheelchair. Of the two mechanisms, one contained a torsion spring while the other used a roller clutch design. We hypothesized that the torsion spring mechanism would increase the ME of propulsion due to a passive recovery stroke enabled by the mechanism. Ten nondisabled male participants with no prior manual wheeling experience performed submaximal exercise tests using both lever-propulsion mechanisms and hand rim propulsion on two different wheelchairs. Cardiopulmonary parameters including oxygen uptake (VO2), heart rate (HR), and energy expenditure (En) were determined. Total external power (Pext) was measured using a drag test protocol. ME was determined by the ratio of Pext to En. Results indicated no significant effect of lever-propulsion mechanism for all physiological measures tested. This suggests that the torsion spring did not result in a physiological benefit compared with the roller clutch mechanism. However, both lever-propulsion mechanisms showed decreased VO2 and HR and increased ME (as a function of slope) compared with hand rim propulsion (p < 0.001). This indicates that both lever-propulsion mechanisms tested are more mechanically efficient than conventional hand rim propulsion, especially when slopes are encountered.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".