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Record W2335671545 · doi:10.1152/jn.00719.2013

Balance-corrective responses to unexpected perturbations at the arms during treadmill walking

2014· article· en· W2335671545 on OpenAlexaff
Juan Forero, John E. Misiaszek

Bibliographic record

VenueJournal of Neurophysiology · 2014
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBalance (ability)Physical medicine and rehabilitationTreadmillPsychologyTask (project management)Displacement (psychology)MedicinePhysical therapyEngineering

Abstract

fetched live from OpenAlex

The arms have been shown to be involved in the regulation of balance during walking. The use of a walking aid enhances balance by increasing the base of support and reducing the load on the legs by partly transferring it to the arms. However, when actively engaged during a balance task, perturbations to the arms can destabilize balance. Previous studies have investigated postural adjustments associated with focal arm movements during standing and walking. However, balance-corrective reactions to unexpected perturbations to the arms during walking have not been well studied. In the present study, subjects walked on a treadmill while grasping a pair of handles when sudden perturbations were delivered by displacing the handles in the forward or backward direction. Instructing subjects to oppose the displacement of the handles resulted in strong responses in the arms that were accompanied by activation of muscles in the legs, comparable to those observed in other balance disturbance studies. Conversely, when subjects were instructed to allow the handles to move when displaced, no responses were observed in the arms. However, similar responses were observed in the legs whether subjects opposed the displacement of the handles or not when perturbations were applied at heel strike. The results from this study show that balance reactions can be elicited in the legs in response to perturbations applied at the arms, and that the expression of these responses is affected by the task engaged in by the arms.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.023
GPT teacher head0.333
Teacher spread0.310 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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