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Record W2068764467 · doi:10.1177/0309364613489145

Forces and moments in knee–ankle–foot orthoses while walking on irregular surfaces

2013· article· en· W2068764467 on OpenAlexafffund
Jan Andrysek, Susan Klejman, John van Kooy

Bibliographic record

VenueProsthetics and Orthotics International · 2013
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsAnklePhysical medicine and rehabilitationGround reaction forceKnee flexionPreferred walking speedKnee JointExoskeletonComputer scienceMedicinePhysicsKinematicsAnatomySurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Kinetic data provide important information about the mobility performance of individuals with lower limb impairments and their assistive devices; however, there is limited understanding of this in real-life environments. OBJECTIVE: To evaluate the effect of real-life irregular surfaces on forces and moments in knee-ankle-foot orthoses. METHODS: In this case series study, a load cell was used to measure the forces and moments at the knee joint of knee-ankle-foot orthoses of individuals with unilateral muscle weakness as a result of poliomyelitis while walking on different ground surfaces and at different speeds. RESULTS: Significantly higher shear forces and external peak knee flexion moments were found when walking on irregular surfaces. In individual cases, certain irregular ground conditions elicited large increases in peak flexion moments (>50%) when compared to walking on smooth level ground. Forces and moments were significantly higher at faster walking speeds. CONCLUSIONS: Higher external peak knee flexion moments during the stance phase suggest that greater demands for support and stability are placed on individuals and their assistive devices when negotiating real-life ground surfaces. Clinical relevance This study demonstrates that walking on irregular surfaces alters the loads placed on knee-ankle-foot orthoses and that the requirements for knee stabilization increase. This has important clinical implications on the design, prescription, and use of such devices given the structural and functional demands placed on them.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.630

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 head0.008
GPT teacher head0.213
Teacher spread0.205 · 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 designObservational
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

Citations6
Published2013
Admission routes2
Has abstractyes

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