Phase I design and evaluation of an isometric muscle reeducation device for knee osteoarthritis rehabilitation03/40/2/PDF/goldman.pdf
Bibliographic record
Abstract
Our long-term goal is to improve adherence to a home-based isometric program for rehabilitation of knee osteoarthritis (OA) using a force-biofeedback device (Isopad). Our goal for Phase I was to design and evaluate an Isopad-based program in a supervised clinical setting. Our subjects were five patients with knee OA of Kellgren stage II or greater. A capacitive force sensor was tested for accuracy, repeatability, and durability. An Arthritis Foundation home-based isometric program inspired the Isopad design. The Isopad provided visual and auditory feedback instantaneously and continuously about force generated between the ankles. The five subjects completed a supervised 8-week progressive isometric program using the Isopad. Absolute isolated quadriceps and hamstring torques were quantified with a dynamometer, and patients completed a self-assessment of symptoms (Western Ontario and McMaster Universities Osteoarthritis Index). The capacitive sensor accuracy error averaged 10% and repeatability 4%. Cognitively intact subjects used the Isopad successfully for isometric progressive resistance training. Quadriceps and hamstrings absolute torques increased an average of 30%. Patients reported decreased functional complaints (Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index). All changes were trends. The Isopad helped subjects with knee OA adhere to a supervised isometric program and meet progressive strength targets. The next-generation Isopad will be employed in a home-based program.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".