Rear-impact neck protection devices for adult wheelchair users
Bibliographic record
Abstract
Many wheelchair users remain in their wheelchairs during transit. Safety research for wheelchair users has focused mainly on frontal impact. However, although they are generally less severe, rear-impact injuries are expensive and difficult to treat and whiplash injury protection for adult wheelchair users remains poorly understood. In this article, 10 g (16 km/h) rear-impact sled tests conducted with the Biofidelic Rear Impact Dummy II or BioRID-II (Denton ATD Inc and Chalmers University of Technology; Gothenburg, Sweden) seated in a rigid wheelchair with no head restraint showed that Abbreviated Injury Scale-score 1 neck injury risk evaluated with the neck injury criterion (NIC) and Nkm criterion is substantially above proposed threshold levels. A prototype wheelchair head restraint was developed and tested together with an existing commercial head restraint (Rolko; Borgholzhausen, Germany) in the same 10 g (16 km/h) rear impact. Both head restraints reduced the injury scores substantially. NIC test scores for the head restraints with no gap ranged from 18 to 24 (approximately 20%-30% chance of neck injury symptoms of duration >1 month) compared with test scores for no head restraints that ranged from 34 to 37 (approximately 95% chance of neck injury). The corresponding extension-posterior Nkm scores with no gap ranged from 0.30 to 0.35 (approximately 5% chance of neck injury) compared with no head restraint of 1.16 (approximately 45% chance of neck injury symptoms). However, the number of sled tests performed was small (three with no head restraint and six with a head restraint), and these results should be considered mainly trends. Preliminary results also showed that the horizontal gap between the head and the wheelchair head-restraint cushion should be as small possible.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".