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Record W2989470590 · doi:10.1109/tnsre.2019.2952004

Modeling and Design of the Automatic Stance Phase Lock (ASPL) Knee Joint Control Mechanism for Paediatric Users With Transfemoral Amputations

2019· article· en· W2989470590 on OpenAlexafffund
Calvin C. Ngan, Jan Andrysek

Bibliographic record

VenueIEEE Transactions on Neural Systems and Rehabilitation Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaBloorview Research InstituteUniversity of TorontoHolland Bloorview Kids Rehabilitation Hospital Foundation
KeywordsMedicinePhysical medicine and rehabilitationStairsMechanism (biology)Knee JointPhysical therapySurgeryEngineering

Abstract

fetched live from OpenAlex

The 2-axes Automatic Stance Phase Lock (ASPL) stance control mechanism has been demonstrated to improve adult amputees' mobility but has yet to be developed for the paediatric population. The overall objective for this work was to characterize the ASPL control mechanism with biomechanical modelling and design a 2-axes ASPL prosthetic knee joint suitable for children between the ages of 6 and 12 years. Paediatric anthropometric data and ASPL control mechanism performance characteristics established from adult ASPL knee users were utilized to develop paediatric-appropriate configurations of the ASPL stance control mechanism. Additional predefined design criteria were also included in the detailed knee design. Developed prototypes of the knee joint, Children-ASPL (CASPL) knee, were clinically validated using a single-subject cross-over study design, to assess control mechanism and overall knee functions. Faster walking speed, longer step and stride length with the CASPL knee suggest potential improvements in overall walking performance. The participant also felt confident walking with the CASPL knee and perceived the locking mechanism to be stable. Stemming from the findings here, future design revisions are aimed to improve the performance of the current prototype, including reliability of knee lock disengagement and performance of the swing phase control mechanism.

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: none
Teacher disagreement score0.589
Threshold uncertainty score0.550

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 head0.194
Teacher spread0.186 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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