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Record W2101667242 · doi:10.1115/1.4031329

Biomechanical Analysis of a Dynamic Stability Test System to Evoke Sway and Step Recovery

2015· article· en· W2101667242 on OpenAlexaff
Anne Gildenhuys, Payam Zandiyeh, Gregor Kuntze, Peter Goldsmith, Janet L. Ronsky

Bibliographic record

VenueJournal of Biomechanical Engineering · 2015
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of CalgaryCochrane
Fundersnot available
KeywordsAccelerationRepeatabilityDisplacement (psychology)SimulationForce platformDynamic balanceControl theory (sociology)Stability (learning theory)KinematicsComputer scienceBalance (ability)Dynamic testingWaistTracking (education)Provocation testMathematicsPhysical medicine and rehabilitationArtificial intelligenceEngineeringPhysicsPsychologyMechanical engineeringMedicineClassical mechanicsStatisticsMachine learning

Abstract

fetched live from OpenAlex

This paper reports on the dynamic analysis and experimental validation of a method to perturb the balance of subjects in quiet standing. Electronically released weights pull the subject's waist through a specified displacement sensed by a photoelectric sensor. A dynamic model is derived that computes the force applied to the subject as a function of waist acceleration. This model accurately predicts the acceleration of mock subjects (suspended masses) with high repeatability. The validity and simplicity of this model suggest that this method can provide a standard for provocation testing on stable surfaces. Proof-of-concept trials on human subjects demonstrate that the device can be used with a force platform and motion tracking and that the device can induce both sway and step recoveries in healthy male adults.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.989
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.025
GPT teacher head0.318
Teacher spread0.293 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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