PERFORMANCE, PATIENT BENEFITS AND ACCEPTANCE OF A NEW GENERATION OF MICROPROCESSOR-CONTROLLED STANCE AND SWING CONTROL ORTHOSIS
Bibliographic record
Abstract
INTRODUCTION By enabling users to flex the orthotic leg during swing phase and safely lock it during stance phase, stance control orthosis (SCO) offers clear benefits compared to locked knee-ankle-foot-orthosis (KAFO)1. Since such orthoses do not offer dampened knee flexion in the weight-bearing condition, this represents a limitation in everyday activities such as ramp and stair descent. C-Brace, a microprocessor controlled stance and swing orthosis (SSCO), overcomes many of those problems. Maximum knee flexion angle in stance and swing phase during level walking are closer to physiological values with C-Brace compared to conventional KAFOs2. The patients are with C-Brace able to descend stairs and ramps reciprocally2. Furthermore, patients report of safer and easier ability to perform activities of daily living3. The main aim of next generation C-Brace is a reduction in size and an increase of adaptability to the patient’s anatomic structure. Due to technological changes, improvements especially for difficult ADLs (e.g. walking on uneven ground) are expected. Abstract PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/32020/24438 How to cite: Wismer N, Krebs A, Braatz F, Schmalz T, Kranzl A, Breuer C. PERFORMANCE, PATIENT BENEFITS AND ACCEPTANCE OF A NEW GENERATION OF MICROPROCESSOR-CONTROLLED STANCE AND SWING CONTROL ORTHOSIS. 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.v1i2.32020 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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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.
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".