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Record W4287220116 · doi:10.3390/sports10080111

Higher Leg and Trunk Muscle Activation during Balance Control in Copers versus People with Chronic Ankle Instability and Healthy Female Athletes

2022· article· en· W4287220116 on OpenAlexaff
Mina Karbalaeimahdi, Mohammad Hossein Alizadeh, Hooman Minoonejad, David G. Behm, Shahab Alizadeh

Bibliographic record

VenueSports · 2022
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsMemorial University of Newfoundland
FundersUniversity of Tehran
KeywordsAthletesBalance (ability)TrunkMedicineElectromyographyAnkleAnkle sprainPhysical medicine and rehabilitationPhysical therapySurgery

Abstract

fetched live from OpenAlex

More than 70% of people with ankle sprain experience chronic ankle instability. However, some people are well adapted to this damage (copers) and do not suffer from chronic ankle instability (CAI). This cross-sectional study involved 34 female athletes, who were classified into three groups (athletes with CAI, copers, and healthy athletes) and tested on a Biodex Balance System. Surface electromyography (EMG) and balance scores were monitored. The coper and healthy group exhibited higher medial gastrocnemius (MG) EMG activity during unstable balance conditions. The rectus abdominus (RA) in the coper group and rectus femoris (RF) in the healthy group showed greater EMG activity compared to CAI during unstable conditions. During stable conditions, the coper group showed greater RA EMG activity compared to CAI, as well as higher tibialis anterior (TA) EMG activity compared to the healthy group. Additionally, balance error scores were higher in the CAI group than those in the healthy group under unstable conditions. In conclusion, decreased EMG activity of the MG, RF, and RA in CAI athletes may contribute to impaired balance in these individuals. The increased EMG activity of the MG, TA, and RA in copers might result in more trunk and ankle stability.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.341

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)0.0000.000

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 head0.010
GPT teacher head0.229
Teacher spread0.219 · 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 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

Citations10
Published2022
Admission routes1
Has abstractyes

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