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Record W2153101614 · doi:10.1109/icorr.2011.5975360

On the development of a walking rehabilitation device with a large workspace

2011· article· en· W2153101614 on OpenAlexaff
Clément Gosselin, Thierry Laliberté

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsWorkspaceOverhead (engineering)Computer scienceContext (archaeology)Routing (electronic design automation)SimulationArchitectureHuman–computer interactionEmbedded systemArtificial intelligenceRobot

Abstract

fetched live from OpenAlex

Rehabilitation therapy aiming at helping a person to regain or improve the ability to walk is a labour-intensive activity. In this context, the patient is often limited to very restricted walking spaces. This paper presents a device that can support the weight of a person walking freely over a large workspace. The device is based on an overhead gantry mechanism combined with a cable routing that decouples the vertical motion from the horizontal displacements of the person. The mechanical architecture is first presented and it is shown that the principle can be applied to the design of a completely passive device in which the portion of the weight to be supported can be adjusted. A simplified dynamic model is also derived in order to highlight the characteristics of the device. A powered version of the device is then discussed. Finally, a prototype of a passive device built at full scale is presented and discussed. A video accompanying the paper illustrates the experimental tests underway with the prototype.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.013

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 communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.201
Teacher spread0.187 · 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
GenreMethods

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
Published2011
Admission routes1
Has abstractyes

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