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Record W2172107329 · doi:10.1109/tnsre.2006.881578

Design and Evaluation of a Stance-Control Knee-Ankle-Foot Orthosis Knee Joint

2006· article· en· W2172107329 on OpenAlexaff
Terris Yakimovich, Jonathan Kofman, Edward D. Lemaire

Bibliographic record

VenueIEEE Transactions on Neural Systems and Rehabilitation Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersAmerican Society of Biomechanics
KeywordsKnee JointAnkleGaitPhysical medicine and rehabilitationWeight-bearingSwingMedicineCadencePreferred walking speedKnee flexionPhysical therapyEngineeringSurgery

Abstract

fetched live from OpenAlex

Conventional knee-ankle-foot orthoses (KAFOs) are prescribed for people with knee-extensor muscle weakness. However, the orthoses lock the knee in full extension and, therefore, do not permit a natural gait pattern. A new electromechanical stance-control knee-ankle-foot orthosis (SCKAFO) knee joint that employs a novel friction-based belt-clamping mechanism was designed to enable a more natural gait. The SCKAFO knee joint allows free knee motion during swing and other non-weight-bearing activities and inhibits knee flexion while allowing knee extension during weight bearing. A prototype SCKAFO knee joint was mechanically tested to determine the moment at failure, loading behavior, and wear resistance. The mean maximum resisting moment of the SCKAFO knee joint over five loading trials was 69 Nm +/- 4.9 Nm. The SCKAFO knee-joint strength and performance were sufficient to allow testing on a 90 kg subject at normal walking cadence. Proper function of the new electromechanical knee joint was verified in walking trials of an able-bodied subject.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.700

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.208
Teacher spread0.194 · 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 teacher head, 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

Citations40
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Neural Systems and Rehabilitation EngineeringSame topicMuscle activation and electromyography studiesFrench-language works237,207