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Record W2130598645 · doi:10.1109/iembs.2005.1617278

Selective Activation of Small Nerve Fibers for Assessing Carpal Tunnel Syndrome

2005· article· en· W2130598645 on OpenAlexaff
Swarna Sundar, José A. González-Cueto

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neural Engineering
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCarpal tunnel syndromeCarpal tunnelStimulus (psychology)Nerve conduction velocityNerve fiberMedian nerveNerve fibreNerve conductionMaterials scienceAmplitudeElectrophysiologyMedicineBiomedical engineeringAnatomyInternal medicineSurgeryOpticsPsychology

Abstract

fetched live from OpenAlex

Carpal tunnel syndrome (CTS) diagnosis could be improved by selectively activating the different types of nerve fibers traversing the carpal tunnel. The objective of this study is to assess the potential of an anodal blocking technique using tripolar surface electrodes for achieving selective fiber activation and evaluating the severity of CTS. Simulations were performed using McNeal's model to determine the stimulating and blocking thresholds for different diameter/conduction velocity groups of nerve fibers. At 9.36 mA stimulus amplitude all nerve fibers from 9 mum to 20 mum were activated. When the current amplitude was increased further, large nerve fibers started getting blocked while small nerve fibers remained active. By gradually increasing the current amplitude small nerve fibers can be selectively activated without the activation of large fibers. The severity of CTS generally progresses from large to small nerve fibers, hence by comparing normal values of amplitude and peak latency of different nerve fiber diameter groups to the CTS affected median nerve recordings of the patient, severity of this syndrome could be detected.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.372

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 communication0.0000.001
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 head0.054
GPT teacher head0.285
Teacher spread0.231 · 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 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

Citations2
Published2005
Admission routes1
Has abstractyes

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