Using a mobility assistance dog reduces upper limb effort during manual wheelchair ramp ascent in an individual with spinal cord injury
Bibliographic record
Abstract
OBJECTIVE: To compare the mechanical and muscular efforts generated in the non-dominant upper limb (U/L) when ascending a ramp with and without the use of a mobility assistance dog (AD(Mob)) in a manual wheelchair user with a spinal cord injury. METHOD: The participant ascended a ramp at natural speed using his personal wheelchair with (three trials) and without (three trials) his AD(Mob). Movement parameters of the wheelchair, head, trunk, and non-dominant U/L (i.e. hand, forearm, and arm segments) were recorded with a motion analysis system. The orthogonal force components applied on the hand rims by the U/Ls were computed with instrumented wheels. Muscular activity data of the clavicular fibers of the pectoralis major, the anterior fibers of the deltoid, the long head of the biceps brachii, and the long head of the triceps brachii were collected at the non-dominant U/L. RESULTS: During uphill propulsion with the AD(Mob), the total and tangential forces applied at the non-dominant handrim, along with the rate of rise of force, were reduced while mechanical efficiency was improved compared to uphill propulsion without the AD(Mob). Similarly, the resultant net joint movements (wrist, elbow, and shoulder) and the relative muscular demands (biceps, triceps, anterior deltoid, pectoralis major) decreased during uphill propulsion with an AD(Mob) versus without an AD(Mob). CONCLUSION: Propelling uphill with the assistance of an AD(Mob) reduces U/L efforts and improves efficiency compared to propelling uphill without its assistance in a manual wheelchair user with a spinal cord injury.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".