The effect of handrail cross-sectional design and age on applied handrail forces during reach-to-grasp balance reactions
Bibliographic record
Abstract
Abstract Handrails have been shown to reduce the likelihood of falls. Despite common use, little is known about how handrail shape and size affect the forces that people can apply after balance loss, and how these forces and the corresponding ability to recover balance depend on age. Following rapid platform translations, 16 older adults and 16 sex-matched younger adults recovered their balance using seven handrail cross-sections varying in shape and size. Younger adults were able to withstand higher perturbations, but did not apply higher forces, than older adults. However, younger adults achieved their peak resultant force more quickly, which may reflect slower rates of force generation with older adults. Considering handrail design, the 38mm round handrails allowed participants to successfully recover from the largest perturbations and enabled the highest force generation. Conversely, tapered handrails had the poorest performance, resulting in the lowest force generation and withstood perturbation magnitudes. Our findings suggest that the handrail cross-sectional design affects the magnitude of force generation and may impact the success of recovery. Our findings can inform handrail design recommendations that support effective handrail use in demanding, balance recovery scenarios.
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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 | 0.006 |
| 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) | 0.004 | 0.001 |
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".