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Record W7065174297

The development of a hand motor recovery device for stroke patient rehabilitation

2010· dissertation· en· W7065174297 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2010
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationThumbStroke (engine)Test (biology)RepeatabilityWork (physics)Reliability (semiconductor)
DOInot available

Abstract

fetched live from OpenAlex

This thesis presents the research work conducted to develop a rehabilitation device that can be used to help stroke patients recover control over their injured hands. Stroke is one of the leading causes of disability in the world. Robot rehabilitation aims to improve its treatment. This device is developed to complement an existing arm rehabilitation robot built at the University of Guelph. The hand rehabilitation device developed is lightweight and highly adjustable and can train patients on fingers and thumb extension using various exercises. A pilot study was conducted in order to test the device on human participants. 52 participants were recruited into four age groups. The pilot study included a survey as well as a repeatability measure test. The survey aimed to collect user feedback while the repeatability measure test examined device reliability. Based on results of the study, the design proved satisfactory in meeting all of its requirements.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.223
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2010
Admission routes1
Has abstractyes

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