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Record W2112777749 · doi:10.1115/1.4025493

On the Design of a Mechanically Programmable Underactuated Anthropomorphic Prosthetic Gripper

2013· article· en· W2112777749 on OpenAlexafffund
Mathieu Baril, Thierry Laliberté, Clément Gosselin, François Routhier

Bibliographic record

VenueJournal of Mechanical Design · 2013
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsUnderactuationGrippersLeverMechanism (biology)Compliant mechanismProsthetic handEngineeringComputer scienceClosing (real estate)SimulationMechanical engineeringRobotStructural engineeringArtificial intelligenceFinite element methodPhysics

Abstract

fetched live from OpenAlex

This paper introduces a novel underactuated anthropomorphic gripper for prosthetic applications. In order to extend the grasping capabilities of underactuated prosthetic grippers and improve the force transmission ratio, a mechanical lever is mounted inside the palm that allows a proper distribution of the forces and provides mechanical advantage. A static model is developed and the possibilities offered by the lever transmission are investigated. Also, a compact mechanism is introduced to synchronize the motion of the four fingers. Additionally, a mechanical selector is designed that functions as a means of mechanically programming the motion of the fingers by selectively blocking their closing motion. Finally, a prototype, including all the above features, is described and experimental validation is briefly reported.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.221
Teacher spread0.191 · 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 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

Citations100
Published2013
Admission routes2
Has abstractyes

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