Quantification of the Trade-Off Between Force Attenuation and Balance Impairment in the Design of Compliant Safety Floors
Bibliographic record
Abstract
Safety floors (also known as compliant floors) may reduce the risk of fall-related injuries by attenuating impact force during falls, but are only practical if they do not negatively affect balance and mobility. In this study, we evaluated seven safety surfaces based on their ability to attenuate peak femoral neck force during simulated hip impacts, and their influence on center of pressure (COP) sway during quiet and tandem stance. Overall, we found that some safety floors can attenuate up to 33.7% of the peak femoral impact force without influencing balance. More specifically, during simulated hip impacts, force attenuation for the safety floors ranged from 18.4 (SD 4.3)% to 47.2 (3.1)%, with each floor significantly reducing peak force compared with a rigid surface. For quiet stance, only COP root mean square was affected by flooring (and increased for only two safety floors). During tandem stance, COP root mean square and mean velocity increased in the medial-lateral direction for three of the seven floors. Based on the substantial force attenuation with no concomitant effects on balance for some floors, these results support the development of clinical trials to assess the effectiveness of safety floors at reducing fall-related injuries in high-risk settings.
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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 | 0.003 |
| 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 | 0.000 |
| 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".