A wheelchair modified for leg propulsion using voluntary activity or elecrical stimulation
Bibliographic record
Abstract
A commercially available wheelchair has been modified for propulsion by movements of the lower legs. The feet are attached securely to a foot rest that can rotate around the knee joint. Movement is generated either with residual voluntary activation of the quadriceps (knee extensor) and hamstring (knee flexor) muscles, or with electrical stimulation of these muscles, if voluntary control is absent. Either a chain or a lever can couple the movements through a gearbox to the wheel to propel the wheelchair forward. Control of a wheelchair with the legs is more efficient than using the arms and has the potential to increase the mobility and whole-body fitness of many wheelchair users, but there is considerable variability between subjects. To address this variability, we measured for individual subjects the passive properties of the legs and foot at rest (effective stiffness and viscosity), the length-tension (torque-angle) properties of the active muscle groups, as well as their force-velocity curve and their activation and fatigue rates. The measured values were then inserted into a model of the leg-propelled wheelchair. The purpose of this paper is to test whether the model could predict the performance of individual subjects accurately and could be used, for example, to optimize the speed of the wheelchair for a given subject.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".