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Record W2157762244 · doi:10.1093/geronb/62.3.p171

Effects of Balance Status and Age on Muscle Activation While Walking Under Divided Attention

2007· article· en· W2157762244 on OpenAlexafffund
Sarah Fraser, Karen Li, Richard DeMont, Virginia B. Penhune

Bibliographic record

VenueThe Journals of Gerontology Series B · 2007
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsConcordia University
FundersCanadian Institutes of Health ResearchConcordia University
KeywordsTask (project management)Balance (ability)TreadmillPhysical medicine and rehabilitationGaitCognitionElectromyographyDual (grammatical number)PsychologyAudiologyMedicinePhysical therapyNeuroscienceEngineering

Abstract

fetched live from OpenAlex

We examined the role of attention during different phases of the gait cycle by using a dual-task paradigm. Younger and older adults performed a self-paced treadmill walking task, a semantic judgment task, and both tasks simultaneously. We recorded vocal reaction time for the judgment task, and we recorded muscle activity by the use of electromyography. We derived dual-task costs from difference scores (single vs dual task). Our analysis of the judgment task showed that both groups responded more quickly during dual-task conditions than during single-task conditions. In five of eight muscle groups, stance-phase muscle activity decreased significantly from dual to single task. For older adults, individuals with poor balance increased their muscle activity during dual-task performance. These results suggest that, during moderately demanding walking and cognitive performance, poor balancers can compensate successfully for their motoric vulnerability.

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)0.002
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.046
GPT teacher head0.369
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 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

Citations35
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueThe Journals of Gerontology Series BSame topicBalance, Gait, and Falls PreventionFrench-language works237,207