MétaCan
Menu
Back to cohort

Assist-as-Needed Impedance and Admittance Switching Control for an Upper-Limb Compliant Rehabilitation Orthosis

2025· article· en· W4416960935 on OpenAlexafffund
Carolane Guay-Tanguay, Jean‐Sébastien Plante, Gilbert Pradel, David Orlikowski, Dominic Létourneau, François Michaud

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
FundersFonds de recherche du Québec
KeywordsAdmittanceController (irrigation)RehabilitationRehabilitation roboticsImpedance controlMotor controlSpasticityActivities of daily livingLimit (mathematics)

Abstract

fetched live from OpenAlex

Individuals affected by stroke often experience spasticity, which limits movement and impact activities of daily living. Physical therapy is essential for improving voluntary movement; however, therapists often face time constraints that limit their ability to provide optimal care for patients with spasticity. To address this issue, an assist-as-needed admittance and impedance-switching controller has been developed for an upper-limb compliant rehabilitation orthosis currently in development. This controller allows patients with spasticity to perform exercises independently while complementing therapist-provided care, enabling both autonomy and assistance during rehabilitation. This paper presents the controller and simulation results, demonstrating the ability to accurately track the patient's voluntary movements and follow a therapist-prescribed trajectory, even in case of impaired motor function or spasticity-related challenges like increased muscle tone.

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: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 integrity0.0000.000
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 head0.006
GPT teacher head0.259
Teacher spread0.252 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same topicProsthetics and Rehabilitation RoboticsFrench-language works237,207