Design and Evaluation of an Orthotic Knee-Extension Assist
Bibliographic record
Abstract
Individuals with quadriceps muscle weakness often have difficulty generating the knee-extension moments required to complete common mobility tasks. A new device that provides knee-extension moments through a range of knee angles was designed to help individuals perform stand-to-sit and sit-to-stand tasks. The novel knee-extension assist (KEA) was designed as a modular component to be incorporated into existing knee-ankle-foot orthoses or used in a knee orthosis. During stand-to-sit, a set of springs is loaded as the knee flexes under bodyweight and the KEA thus provides a knee-extension moment that aids in achieving a smoothly controlled knee flexion. The springs can be locked in place at the end of knee flexion to prevent unwanted knee extension while the user is seated. The entire knee extension assist can be disengaged to allow free joint motion anytime the affected leg is unloaded. During sit-to-stand, the KEA assists knee extension by returning the energy stored in the springs as an extension moment. In mechanical testing of a prototype of the new KEA, a mean maximum extension moment of 42.9 ± 0.46 Nm was provided by the device during flexion and 28.4 ± 0.28 Nm during extension. A biomechanical evaluation with two able-bodied individuals demonstrated the effectiveness of the KEA in successfully assisting stand-to-sit and sit-to-stand tasks. During stand-to-sit, the KEA provided 82% and 75% of the total (muscle and KEA) knee-extension moment required by the braced leg for the task for the two subjects, respectively; and during sit-to-stand, the KEA provided 56% and 50% of the total knee-extension moment for the two subjects, respectively. This KEA performance exceeded 50% knee-extension moment assistance for a 70 kg person.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".