Are headforms a poor surrogate for helmet fit?
Bibliographic record
Abstract
International standards organizations require ice hockey helmets to be impact tested while mounted to a surrogate headform, with anthropometrics of a 50th percentile male. However, human head shapes are not identical, nor are there consistent guidelines for fitting a helmet to the ordinary user. The interaction between head shape and helmet fit impacts helmet safety: the contact area between a headform and helmet interior has been identified as a critical determinant of protection afforded by a helmet. The objective of this study was to compare quantitative measures of helmet fit between an adult male sample and three 50th percentile male headforms. This study recruited 42 adult male participants who wore a medium-sized ice hockey helmet (560–600 mm interior circumference) in an attempt to compare their quantitative helmet fit to those of three 50th percentile adult male headforms. Through three-dimensional modeling, fit was quantified by assessing dimensional differences in two transverse cross-sectional planes of the head and using principal component analysis to determine the largest components of fit. Significant differences were found between the headforms and the participants’ heads in anthropometrics and dimensional differences. The headforms were smaller than the participants’ heads, demonstrating average gapping with the interior of the helmet. The principal components of fit extracted included mediolateral deformation, gapping/compression at the rear aspect of the head-helmet interface, and general congruence of the head shape to the helmet liner. These findings demonstrated a vast discrepancy between helmet fit on the 50th percentile headforms and the ordinary helmet user.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".