The influence of headform orientation and flooring systems on impact dynamics during simulated fall-related head impacts
Bibliographic record
Abstract
Novel compliant flooring systems are a promising approach for reducing fall-related injuries in seniors, as they may provide up to 50% attenuation in peak force during simulated hip impacts while eliciting only minimal influences on balance. This study aimed to determine the protective capacity of novel compliant floors during simulated 'high severity' head impacts compared to common flooring systems. A headform was impacted onto a common Commercial-Carpet at 1.5, 2.5, and 3.5 m/s in front, back, and side orientations using a mechanical drop tower. Peak impact force applied to the headform (F(max)), peak linear acceleration of the headform (g(max)) and Head Injury Criterion (HIC) were determined. For the 3.5 m/s trials, backwards-oriented impacts were associated with the highest F(max) and HIC values (p<0.001); accordingly, this head orientation was used to complete additional trials on three common floors (Resilient Rubber, Residential-Loop Carpet, Berber Carpet) and six novel compliant floors at each impact velocity. ANOVAs indicated that flooring type was associated with all parameters at each impact velocity (p<0.001). Compared to impacts on the Commercial Carpet, Dunnett's post hoc indicated all variables were smaller (25-80%) for the novel compliant floors (p<0.001), but larger for Resilient Rubber (31-159%, p<0.01). This study demonstrates that during 'high severity' simulated impacts, novel compliant floors can substantially reduce the forces and accelerations applied to a headform compared to common floors including carpet and resilient rubber. In combination with reports of minimal balance impairments, these findings support the promise of novel compliant floors as a biomechanically effective strategy for reducing fall-related injuries including traumatic brain injuries and skull fractures.
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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 | 0.001 |
| 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) | 0.001 | 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".