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A Stochastic Model of Knee Angle in Response to Electrical Stimulation of the Quadriceps and Hamstrings Muscles

2011· article· en· W1950991710 on OpenAlex
Cheryl L. Lynch, Miloš R. Popović

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.

Bibliographic record

VenueArtificial Organs · 2011
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of TorontoToronto Rehabilitation Institute
Fundersnot available
KeywordsFunctional electrical stimulationKnee flexionStimulationKnee JointQuadriceps muscleStochastic modellingStandard deviationPhysical medicine and rehabilitationControl theory (sociology)Computer scienceSimulationMathematicsMedicineStatisticsSurgery

Abstract

fetched live from OpenAlex

A novel stochastic model of knee angle in response to stimulation of the quadriceps and hamstrings muscle groups is presented. This model includes uncertainty due to fatigue and day-to-day changes in the stimulated muscles. The model consists of a normally distributed random variable whose mean and standard deviation vary with time and is characterized using data from a complete spinal cord injuries subject. The experimental data show a significant difference between the left and right legs under certain conditions, and suggest that fatigue-related and day-to-day variation may also be important. The purpose of this model is to generate more realistic electrically stimulated knee movements. This stochastic modeling technique could be incorporated into a comprehensive model of a joint actuated with electrical stimulation, and has great potential as a tool for analyzing closed-loop performance of electrically stimulated systems.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.218

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 head0.026
GPT teacher head0.214
Teacher spread0.188 · 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