Modeling and Control Considerations for Powered Lower-Limb Orthoses: A Design Study for Assisted STS
Bibliographic record
Abstract
Lower-limb orthotic devices may be used to aid or restore mobility to the impaired user. Powered orthoses, in particular, hold great potential in improving the quality of life for individuals with locomotor difficulties because active control of an orthosis can aid limb movement in common tasks that may even be impossible if unaided. However, these devices have primarily remained the products of research labs with the number of effective commercial applications for the laity being nearly nonexistent. This paper provides an overview of the current status of powered orthoses and goes on to discuss key issues in modeling and control of powered orthoses so that designers can have a unified framework in developing user-oriented devices. Key concepts are demonstrated for a powered knee-orthosis intended for assisting the sit-to-stand task, and both pneumatic muscle and dc motor actuators are considered in this conceptual design study. In the final analysis, we conclude that the ability to provide sit-to-stand assistance is profoundly dependent on the type of control signal employed to control the actuator from the user–orthosis interface.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".