Effect of compliant flooring on impact force during falls on the hip
Bibliographic record
Abstract
Compliant flooring represents a promising but understudied strategy for reducing impact force and hip fracture risk due to falls in high-risk environments such as nursing homes, hospitals, gymnasiums, and senior centers. We conducted "pelvis release experiments" with young women (n=15) to determine whether floor stiffness influences peak hip impact force during safe, low-height falls. During the trials, we used a pelvic sling and electromagnet to lift and instantly release the participant from a height of 5 cm above a force plate, which measured the force applied to the hip region during impact. Trials were conducted for rigid floor conditions and with layers of ethylene vinyl acetate foam rubber overlying the floor that we regarded as firm (1.5-cm thick; stiffness=263 kN/m), semifirm (4.5-cm thick; stiffness=95 kN/m), semisoft (7.5-cm thick; stiffness=67 kN/m), and soft (10.5-cm thick; stiffness=59 kN/m). When compared to the rigid condition, peak hip impact force averaged 8% lower in the firm condition and 15% lower in the semifirm condition. Peak forces were not significantly different between the semifirm, semisoft, and soft floor conditions, indicating that a 4.5 cm-thick foam mat provides nearly the same force attenuation as a 10.5 cm-thick mat. These results support the need for laboratory experiments to measure the effect of floor stiffness on postural stability and for clinical trials to determine the effect of compliant flooring on hip fracture incidence in high-risk environments.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".