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Record W2795014366 · doi:10.1080/15389588.2018.1426917

Trunk muscle recruitment patterns in simulated precrash events

2018· article· en· W2795014366 on OpenAlexafffund
Jóna Marín Ólafsdóttir, Jason B. Fice, Daniel W. H. Mang, Karin Brolin, Johan Davidsson, Jean‐Sébastien Blouin, Gunter P. Siegmund

Bibliographic record

VenueTraffic Injury Prevention · 2018
Typearticle
Languageen
FieldPsychology
TopicErgonomics and Musculoskeletal Disorders
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchTrafikverket
KeywordsIsometric exerciseTrunkElectromyographyTorsoAnatomyAccelerationPhysical medicine and rehabilitationMuscle contractionMotor unit recruitmentMedicineBiologyPhysicsPhysical therapy

Abstract

fetched live from OpenAlex

OBJECTIVES: To quantify trunk muscle activation levels during whole body accelerations that simulate precrash events in multiple directions and to identify recruitment patterns for the development of active human body models. METHODS: Four subjects (1 female, 3 males) were accelerated at 0.55 g (net Δv = 4.0 m/s) in 8 directions while seated on a sled-mounted car seat to simulate a precrash pulse. Electromyographic (EMG) activity in 4 trunk muscles was measured using wire electrodes inserted into the left rectus abdominis, internal oblique, iliocostalis, and multifidus muscles at the L2-L3 level. Muscle activity evoked by the perturbations was normalized by each muscle's isometric maximum voluntary contraction (MVC) activity. Spatial tuning curves were plotted at 150, 300, and 600 ms after acceleration onset. RESULTS: EMG activity remained below 40% MVC for the three time points for most directions. At the 150- and 300 ms time points, the highest EMG amplitudes were observed during perturbations to the left (-90°) and left rearward (-135°). EMG activity diminished by 600 ms for the anterior muscles, but not for the posterior muscles. CONCLUSIONS: These preliminary results suggest that trunk muscle activity may be directionally tuned at the acceleration level tested here. Although data from more subjects are needed, these preliminary data support the development of modeled trunk muscle recruitment strategies in active human body models that predict occupant responses in precrash scenarios.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0030.001

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.

Opus teacher head0.044
GPT teacher head0.367
Teacher spread0.323 · 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.

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

Citations1
Published2018
Admission routes2
Has abstractyes

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