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Record W2899322553 · doi:10.1115/detc2018-85234

Electromechanical Design of Robotic Transfemoral Prostheses

2018· article· en· W2899322553 on OpenAlexaff
Jan Andrysek

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
Fundersnot available
KeywordsActuatorPneumatic actuatorWearable computerRobotMechanical systemEngineeringMechanical engineeringMechanical energyComputer scienceControl engineeringPower (physics)Electrical engineeringArtificial intelligenceEmbedded system

Abstract

fetched live from OpenAlex

Alongside promising advances in biomechatronics, the following research presents the first documented investigation reviewing the electromechanical system designs of energetically-powered (i.e., robotic) prostheses for patients with transfemoral amputations. The technical review begins with examining the material and mechanical designs, and electrical batteries incorporated into robotic transfemoral prostheses. The actuation systems have encompassed electromagnetic actuators (i.e., occasionally featuring series elastic elements), pneumatic actuators (i.e., pneumatic cylinders and pneumatic artificial muscles), and hydraulic actuators. Various wearable sensors have been utilized to provide closed-loop feedback control, including electromechanical sensors, surface electromyography, and bioinspired machine vision systems. The Össur Power Knee (i.e., the only commercially-available powered transfemoral prosthesis) is additionally discussed. The technical review concludes with suggesting prospective future directions for innovation, specifically lower-limb prostheses capability of electrical energy regeneration.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score0.219

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 head0.017
GPT teacher head0.221
Teacher spread0.204 · 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 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

Citations21
Published2018
Admission routes1
Has abstractyes

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