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Record W2541813653 · doi:10.1109/iembs.1991.684276

A Simultaneous Comparison Of Vibromyography With Electromyography During Isometric Contraction Of The Human Quadriceps Muscles

2005· article· en· W2541813653 on OpenAlexafffund
Yuan‐Ting Zhang, Cy Frank, Rangaraj M. Rangayyan, G.D. BeIl

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of Calgary
FundersArthritis Society
KeywordsIsometric exerciseElectromyographyContraction (grammar)Root mean squareMuscle contractionHuman muscleQuadriceps muscleMuscle fatigueAnatomyBiomedical engineeringMedicineMathematicsOrthodonticsPhysical medicine and rehabilitationPhysicsPhysical therapyInternal medicineSkeletal muscle

Abstract

fetched live from OpenAlex

and electromyography (EMG) were compared during isometric contraction of the human quadriceps muscles, by evaluating the averaged root mean squared (RhlS) value, peak frequency, and mean frequency (MF) of simultaneously recorded VMG and EMG signals for four levels of muscle contraction on a Cybex 11 machine at 60° of knee joint flexion angle. It was found that the VMG and EMG signals were in general equally sensitive to the levels of muscle contraction. Results show that the RMS values of the VMG and the EMG signals increase linearly, in a similar manner, with increasing muscle contraction levels. Furthermore, the study indicates that the averaged mean frequency (C25 Hz) of VMG signals is much lower than that (>70 Hz) of EMG signals, and that the slopes of MF/moment curves for VMG and EMG are approximately the same. The frequency difference and the slope similarity may he explained using electro-physiological findings reported in the literature.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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 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
Published2005
Admission routes2
Has abstractyes

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