The influence of headform orientation and flooring systems on impact dynamics during simulated fall-related head impacts
Why this work is in the frame
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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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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 | 0.000 | 0.000 |
| 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 it