MétaCan
Menu
Back to cohort
Record W4280608047 · doi:10.3357/amhp.5830.2022

Posture and Helmet Configuration Effects on Joint Reaction Loads in the Middle Cervical Spine

2022· article· en· W4280608047 on OpenAlexaboutno aff
Jeff M. Barrett, Colin D. McKinnon, Clark R. Dickerson, Andrew C. Laing, Jack P. Callaghan

Bibliographic record

VenueAerospace Medicine and Human Performance · 2022
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCervical spineKinematicsCompression (physics)MedicineCervical vertebraeOrthodonticsGround reaction forceAnatomyPhysical medicine and rehabilitationMaterials scienceSurgeryPhysics

Abstract

fetched live from OpenAlex

INTRODUCTION: Between 43 and 97% of helicopter pilots in the Canadian Armed Forces report neck pain. Potential contributing factors include the weight of their helmet, night vision goggles (NVG), and counterweight (CW) combined with deviated neck postures. Therefore, the purpose of this investigation was to quantify changes in neck loads associated with posture, helmet, NVG, and CW. METHODS: Eight male subjects volunteered. They undertook one of five deviated neck postures (flexion, extension, lateral bending, axial rotation) times four configurations (no helmet, helmet only, helmet and NVG, and helmet, NVG, and CW). 3D kinematics and EMG from 10 muscles (5 bilaterally) drove a 3D inverse dynamics, EMG-driven model of the cervical spine which calculated joint compression and shear at C5-C6. RESULTS: The compression in the neutral posture was 116.5 (5.7) N, which increased to 143.7 (11.4) N due to a 12.7 N helmet. NVGs, weighing 7.9 N, also generated this disproportionate increase, where the compression was 164.2 (3.7) N. In flexion or extension, the compression increased with increasing head-supported mass, with a maximum of 315.8 (67.5) N with the CW in flexion. Anteroposterior shear was highest in the lateral bending [34.0 (6.2) N] condition, but was generally low (< 30 N). Mediolateral shear was less than 5 N for all conditions. DISCUSSION: Repositioning the center of gravity of the helmet with either NVGs or CW resulted in posture-specific changes to loading. Posture demonstrated a greater potential to reposition the head segment’s center of gravity compared to the helmet design. Therefore, helmet designs which consider repositioning the center of gravity may reduce loads in one posture, but likely exacerbate loading in other postures. Barrett JM, McKinnon CD, Dickerson CR, Laing AC, Callaghan JP. Posture and helmet configuration effects on joint reaction loads in the middle cervical spine. Aerosp Med Hum Perform. 2022; 93(5):458–466.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.087
GPT teacher head0.386
Teacher spread0.299 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueAerospace Medicine and Human PerformanceSame topicOccupational Health and PerformanceFrench-language works237,207