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Record W3201054218 · doi:10.32393/csme.2021.38

An Adaptive Feedforward Control Structure For Functional Electrical Stimulation Based Joint Position Control

2021· article· en· W3201054218 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.

Bibliographic record

VenueProgress in Canadian Mechanical Engineering. Volume 4 · 2021
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity Health NetworkUniversity of AlbertaToronto Rehabilitation InstituteUniversity of Waterloo
Fundersnot available
KeywordsFeed forwardFunctional electrical stimulationControl (management)Joint (building)Computer scienceAdaptive controlControl theory (sociology)Position (finance)StimulationControl engineeringEngineeringArtificial intelligenceNeurosciencePsychology

Abstract

fetched live from OpenAlex

Every year, between 250,000 and 500,000 people suffer from Spinal Cord Injury (SCI) around the world. Functional electrical stimulation (FES) is one of the assistive approaches that is developed to facilitate motor function movement. Usually researchers employ the FES to enforce the muscular system of SCI individuals and enable them to move. Accordingly, several methods have been presented to control the stimulation signals applied by the FES devices. However, due to the complexity of the human neuromuscular system and its time-varying nature, yielding an effective and practical control approach is still a challenge.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score1.000

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 head0.008
GPT teacher head0.203
Teacher spread0.194 · 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