FUNCTIONAL UTILITY OF WEARING A MYOELECTRIC ORTHOSIS FOR UPPER EXTREMITY PARALYSIS DUE TO SPINAL CORD INJURY
Bibliographic record
Abstract
INTRODUCTION Spinal cord injury (SCI) remains a leading cause of long-term disability in the United States with the majority of injuries resulting in incomplete quadriplegia due to cervical lesions.1 This leads to significant neurological impairment including upper extremity (UE) weakness and decreased independence with self-care activities of daily living (ADLs). Previous work demonstrated that using a myoelectric elbow-wrist-hand orthosis as a therapeutic adjunct to a multi-week rehabilitation regimen resulted in decreased UE motor impairment and increased function in stroke survivors with moderate UE hemiparesis.2 The purpose of this case study was to determine if wearing a myoelectric elbow-wrist-hand orthosis reduces upper extremity motor impairment and increases functional ability in an individual with chronic, incomplete spinal cord injury and resultant quadriplegia. Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32021/24439 How to cite: Wengerd L. FUNCTIONAL UTILITY OF WEARING A MYOELECTRIC ORTHOSIS FOR UPPER EXTREMITY PARALYSIS DUE TO SPINAL CORD INJURY. CANADIAN PROSTHETICS & ORTHOTICS JOURNAL, VOLUME 1, ISSUE 2, 2018; ABSTRACT, POSTER PRESENTATION AT THE AOPA’S 101ST NATIONAL ASSEMBLY, SEPT. 26-29, VANCOUVER, CANADA, 2018. DOI: https://doi.org/10.33137/cpoj.v1i2.32021 Abstracts were Peer-reviewed by the American Orthotic Prosthetic Association (AOPA) 101st National Assembly Scientific Committee. http://www.aopanet.org/
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".