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Record W2923120804 · doi:10.1080/15389588.2018.1540867

Assessing the performance of motorcyclists’ impact protectors in simulated ATD knee and shoulder impacts

2019· article· en· W2923120804 on OpenAlexaff
Lauren Meredith, Bianca Albanese, Tom Whyte, Tom Gibson, Michael Fitzharris, Matthew Baldock, Julie Brown

Bibliographic record

VenueTraffic Injury Prevention · 2019
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsInternational Collaboration On Repair Discoveries
FundersAustralian Research Council
KeywordsPoison controlInjury preventionOccupational safety and healthForensic engineeringHuman factors and ergonomicsEngineeringPhysical medicine and rehabilitationMedicineAeronauticsMedical emergency

Abstract

fetched live from OpenAlex

OBJECTIVE: Fractures are a common injury among motorcycle riders and can have serious health implications. Impact protection (IP) has been designed to help prevent fractures, yet there are conflicting opinions as to whether this IP does in fact help prevent fractures in real-world crashes. This work aimed to (1) use simulated dummy impacts to examine whether existing types of IP could reduce the force transferred to the underlying bone to below fracture tolerance levels and (2) investigate whether current European Standard (EN 1621-1) test procedures for impact protectors designed for motorcyclists are sufficient to ensure fracture protection. METHOD: Twenty-three shoulder and 7 knee IP specimens were tested using a 23-kg impactor contacting axially along the clavicle and femur of an anthropomorphic test device (ATD) at an energy level corresponding to the fracture tolerance of these bones. Sixteen IP specimens were the same as those worn by motorcycle riders involved in crashes where injury outcome was known (knee: n = 3; shoulder: n = 13) and the IP had been previously tested to EN 1621-1. Other IP tested represented a wide range of IP available for purchase at a motorcycle accessory store. Double and triple layers of IP were also tested. Energy attenuated during the dummy impacts was compared to energy attenuated when tested to EN 1621-1. RESULTS: Of the 23 shoulder IP tested, the average percentage reduction of transferred force to the shoulder from the baseline test was 7.6 ± 4.8%. The percentage reduction of transferred force to the knee from the baseline was 43.9 ± 7.5%. The entire group of knee IP tested reduced the transferred force to the knee to below the 10-kN injury threshold for the femur. There was a positive but nonsignificant correlation between the ATD test and the EN 1621-1 impact test performance, suggesting that the European standard test method likely provides a good indication of IP performance. However, given the low correlation coefficient, the relationship between IP performance in the European standard test method and injury protection remains unclear. CONCLUSION: Though the energy attenuation test method in the European standard may be an appropriate approach, distinct differences in injury protection performance observed between knee and shoulder IP indicate that there may be a need for different performance criteria for IP designated to protect different body regions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.345
Teacher spread0.325 · 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 designObservational
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

Citations2
Published2019
Admission routes1
Has abstractyes

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