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Record W4405678752 · doi:10.22306/atec.v10i4.230

Design of an affordable dynamic arm support for motorized wheelchairs

2024· article· en· W4405678752 on OpenAlexfundno aff
Alexandre Campeau‐Lecours, Charles Doyon, Simon Latour, Thierry Laliberté, Jean‐Sébastien Roy, Véronique H. Flamand

Bibliographic record

VenueActa Tecnología · 2024
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsnot available
FundersInnovation, Science and Economic Development Canada
KeywordsAdaptabilityComputer scienceAssistive technologyMechanism (biology)Linkage (software)Focus (optics)SimulationFour-bar linkagePhysical medicine and rehabilitationHuman–computer interactionArtificial intelligenceMotion (physics)Medicine

Abstract

fetched live from OpenAlex

Upper limb impairments, resulting from various neurological and neuromuscular conditions, significantly impact daily activities and limit social participation. Assistive technologies, particularly dynamic arm supports, offer promising solutions to enhance independence for individuals facing these challenges. This paper presents the development of an affordable dynamic arm support, designed with a focus on static balancing. The support utilizes a four-bar linkage mechanism to allow smooth vertical movement while maintaining the orientation of the armrest. Furthermore, the integration of rotational and prismatic joints enhances the device's adaptability, enabling horizontal movements. Through comprehensive mathematical modeling and prototype testing, we introduce a cost-effective arm support that effectively counterbalances the arm's weight, ensuring ease of movement and stability across various spatial orientations.

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 score0.003
Threshold uncertainty score0.009

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 science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.244
Teacher spread0.232 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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