MétaCan
Menu
Back to cohort
Record W2420186642 · doi:10.1109/syscon.2016.7490531

Recurrent dynamic neural network model for myoelectric-based control of a prosthetic hand

2016· article· en· W2420186642 on OpenAlexaff
Teodor-Adrian Teban, Radu‐Emil Precup, Emil-Ioan Voisan, Thiago Eustaquio Alves de Oliveira, Emil M. Petriu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsNonlinear autoregressive exogenous modelAutoregressive modelRecurrent neural networkComputer scienceArtificial neural networkNonlinear systemMean squared errorControl theory (sociology)Artificial intelligenceNonlinear modelControl (management)Pattern recognition (psychology)Speech recognitionMathematicsStatistics

Abstract

fetched live from OpenAlex

This paper discusses a novel nonlinear autoregressive network with exogenous inputs (NARX) neural network (NN) model of the nonlinear dynamic mechanisms occurring in the myoelectric-based control of prosthetic hand fingers. The experimental results demonstrate the good performance of the NN architecture in terms of output response and mean squared error. The comparison of experimental results also shows that the proposed NARX recurrent NN outperforms a linear recurrent NN with the same training algorithm.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations15
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicMuscle activation and electromyography studiesFrench-language works237,207