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Record W7132869215

Investigating the Orthotic and Acute Therapeutic Effects of a Novel Upright Balance Therapy for Individuals with iSCI and Developing a New Clinical Version

2023· dissertation· W7132869215 on OpenAlexaff
Ziyuan Pei

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsTherapeutic effectFunctional electrical stimulationBalance (ability)Spinal cord injuryTherapeutic approachAnkle
DOInot available

Abstract

fetched live from OpenAlex

Individuals with incomplete spinal cord injury (iSCI) experience an increased rate of falls due to decreased sensorimotor function. We demonstrated in a prior longitudinal pilot study that a therapeutic system using functional electrical stimulation and visual feedback balance training (FES+VFBT), produced therapeutic effects in individuals with iSCI. However, the exact role and mechanism FES in the system is not understood. Additionally, hardware and software limitations make clinical application of the system difficult. In this thesis, I determined the orthotic and acute therapeutic effect of FES in the FES+VFBT system and developed a new clinical version of the system. The FES demonstrated an orthotic effect by increasing ankle stiffness and an acute therapeutic effect by increasing corticospinal excitability. A new clinical version of the system was successfully recreated using the Wii Balance Board and Unity game engine and was proven to perform at least on par with the lab-based system.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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)0.0030.000

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 head0.046
GPT teacher head0.396
Teacher spread0.350 · 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 designNon-randomized trial
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
Published2023
Admission routes1
Has abstractyes

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