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Record W2937975742

Individual limb contributions to mediolateral stability during gait

2018· article· en· W2937975742 on OpenAlexaffabout
Yash Rawal, Jonathan C. Singer

Bibliographic record

VenueJournal of Exercise, Movement, and Sport (SCAPPS refereed abstracts repository) · 2018
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPhysical medicine and rehabilitationKinematicsGround reaction forceGaitBiomechanicsDisplacement (psychology)LimitingMedicinePhysical therapyPsychologyAnatomyPhysicsEngineering
DOInot available

Abstract

fetched live from OpenAlex

Mediolateral dynamic stability control is challenging for older-adults (OA) and is associated with lateral falls and hip fracture. Previous research examining the eccentricity of the net ground reaction force (GRFnet) and individual-limb GRFs have helped elucidate why OA exhibit greater mediolateral instability during stepping responses. The present work sought to understand the individual-limb contributions to mediolateral stability during gait, by examining whole-body kinematics and eccentricity of individual-limb GRFs. 28 younger-adults (YA) (18-31 years) and 28 OA (>65 years) completed 10 walking trials at a self-selected speed and step placement, all were right-limb dominant. Whole-body COM kinematics and individual-limb GRFs were quantified. The minimum distance between the COM and the lateral aspect of the BOS during each step was quantified (dmin) as a measure of kinematic instability. The eccentricity of individual-limb GRFs relative to the COM were calculated (?d) throughout the stance-phase. Positive and negative eccentricities of the individual-limb GRF were quantified using the mean difference (MD). Positive values are believed to be restabilizing (MDpos), limiting lateral COM displacement; negative values are destabilizing (MDneg). OA exhibited significantly greater dominant-side dmin and MDneg than YA. Larger dominant-side dmin among OA may suggest this is a strategy to maintain a larger margin of stability. The lack of no age-related differences on the non-dominant side may indicate OA inappropriately scale, which could increase the risk of lateral falls towards this side. Larger dominant-side MDneg could be restabilizing if caused by a larger medially directed GRF component, limiting the lateral linear acceleration of the COM.Acknowledgments: Support for this research was provided by the Manitoba Medical Service Foundation and the Natural Sciences and Engineering Research Council of Canada (NSERC).

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.312
Teacher spread0.292 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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