MétaCan
Menu
Back to cohort

Functional electrical stimulation in neurological disorders

2008· review· en· W2048939338 on OpenAlexaff
O.K. Sujith

Bibliographic record

VenueEuropean Journal of Neurology · 2008
Typereview
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of British Columbia Hospital
Fundersnot available
KeywordsFunctional electrical stimulationMedicinePhysical medicine and rehabilitationStimulationParkinsonismParaplegiaDeep brain stimulationGaitNeuroscienceMovement disordersPhysical therapySpinal cordDiseaseParkinson's diseasePsychologyInternal medicine

Abstract

fetched live from OpenAlex

Functional electrical stimulation (FES) refers to electrical stimulation of muscles in order to improve the impaired motor function. This is achieved by activating skeletal muscles with constant frequency trains of stimulations. This method has been found useful in various neurological disorders like hemiplegia, foot drop and paraplegia including spinal cord injuries. The first half of this review focuses on the broad clinical applications of functional electrical stimulation, its mechanism of action and the complications of this mode of therapy. Advanced Parkinson's disease (PD) is characterized by marked slowing of gait and frequent freezing episodes. Medical and surgical treatments are often ineffective in managing freezing episodes. The second half of this review discusses briefly the gait abnormalities in PD and the available treatment options. The possible role of FES in improving gait in parkinsonism and the importance of future research in this direction are highlighted.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.246
Teacher spread0.212 · 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 designOther design
Domainnot available
GenreReview

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

Citations47
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of NeurologySame topicMuscle activation and electromyography studiesFrench-language works237,207