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Record W3209385312 · doi:10.1177/20556683211050357

Impact attenuation provided by older adult protective headwear products during simulated fall-related head impacts

2021· article· en· W3209385312 on OpenAlexafffund
Daniel R. Martel, Michelle R. Tanel, Andrew C. Laing

Bibliographic record

VenueJournal of Rehabilitation and Assistive Technologies Engineering · 2021
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceCanada Foundation for InnovationAGE-WELL
KeywordsAttenuationHead (geology)Hybrid IIIEnvironmental scienceDrop impactPoison controlPhysical medicine and rehabilitationMedicineMaterials scienceGeologyPhysicsComposite materialEnvironmental healthOptics

Abstract

fetched live from OpenAlex

Introduction While protective headwear products (PHP) are designed to protect older adults from fall-related head injuries, there are limited data on their protective capacity. This study’s goal was to assess the impact attenuation provided by commercially available PHP during simulated head impacts. Methods A drop tower and Hybrid III headform measured the decrease in peak linear acceleration ( g atten ) provided by 12 PHP for front- and back-of-head impacts at low (clinically relevant: 3.5 m/s) and high (5.7 m/s) impact velocities. Results The range of g atten across PHP was larger at the low velocity (56% and 41% for back and frontal impacts, respectively) vs. high velocity condition (27% and 38% for back and frontal impacts, respectively). A significant interaction between impact location and velocity was observed ( p < .05), with significantly greater g atten for back-of-head compared to front-of-head impacts at the low impact velocity (19% mean difference). While not significant, there was a modest positive association between g atten and product padding thickness for back-of-head impacts ( p = .095; r = 0.349). Conclusion This study demonstrates the wide range in impact attenuation across commercially available PHP, and suggests that existing products provide greater impact attenuation during back-of-head impacts. These data may inform evidence-based decisions for clinicians and consumers and help drive industry innovation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.266
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2021
Admission routes2
Has abstractyes

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Same venueJournal of Rehabilitation and Assistive Technologies EngineeringSame topicAutomotive and Human Injury BiomechanicsFrench-language works237,207