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Reducing Muscle Fatigue Due to Functional Electrical Stimulation Using Random Modulation of Stimulation Parameters

2005· article· en· W2165920325 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueArtificial Organs · 2005
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIsometric exerciseStimulationFunctional electrical stimulationMuscle fatiguePulse (music)Biomedical engineeringAmplitudePulse-amplitude modulationPulse-width modulationPhysical medicine and rehabilitationMaterials scienceElectromyographyMedicineRandomized controlled trialPhysical therapyPhysicsSurgeryInternal medicineVoltageOptics

Abstract

fetched live from OpenAlex

A major limitation of many functional electrical stimulation (FES) applications is that muscles tend to fatigue very rapidly. It was hypothesized that FES-induced muscle fatigue could be reduced by randomly modulating the pulse frequency, amplitude, and pulse width in a range of +/-15%. Seven subjects with spinal-cord injuries participated in this study. FES was applied to quadriceps and tibialis anterior muscles using surface electrodes. Isometric force was measured, and the time for the force to drop by 3 dB (fatigue time) was compared between trials. Four different modes of FES were applied in random order: constant stimulation, randomized frequency, randomized amplitude, and randomized pulse width. There was no significant difference between the fatigue-time measurements for the four modes of stimulation (P=0.329). Therefore, random modulation appeared to have no effect. Based on an observed correlation between maximum force measurements and trial order, we concluded that having 10-min rest periods between trials was insufficient.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.040
GPT teacher head0.256
Teacher spread0.216 · 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