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Record W4416854574 · doi:10.1139/tcsme-2023-0137

Spherical exoskeleton for the measurement of shoulder movement

2025· article· en· W4416854574 on OpenAlexvenueno aff
Jiaji Li, John Golden, Bailey E. Johnson, Edward J. Quilligan, Vance O. Gardner, Carlos A. Prietto, J. Michael McCarthy

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsnot available
Fundersnot available
KeywordsExoskeletonMovement (music)ScapulaMotion captureFunctional movementMotion (physics)RobotMovement control

Abstract

fetched live from OpenAlex

This paper presents the design, construction, and testing of a spherical shoulder exoskeleton that measures shoulder movement for use before and after reverse total shoulder arthroplasty. The device is designed for in-home use to facilitate remote physiotherapy. Embedded sensor data are converted to a robotic shoulder model to illustrate the measured movement and which is validated through ImageJ measurements. Unlike current motion capture and image processing measurement techniques, this device measures the movement of the upper arm relative to the scapula, excluding scapula movement, thereby focusing on movement provided by the shoulder prosthesis.

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: Methods · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.214
Teacher spread0.201 · 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
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicProsthetics and Rehabilitation RoboticsFrench-language works237,207