Hybrid Therapeutic Device (CUHK-OA-M2) for Relieving Symptoms Induced by Knee Osteoarthritis
Bibliographic record
Abstract
The symptoms of knee osteoarthritis (KOA) severely affect the life quality of the elderly population. Low-level laser therapy, heat therapy, and massage therapy are widely used as independent treatments for joint disorders. However, there are very limited reports of a combination of these therapies into an integrated device for KOA so far. This study aims to develop a novel hybrid therapeutic device that can meet various requirements for knee therapy. Our hybrid therapeutic device (CUHK-OA-M2) integrated with low-level laser therapy, heat therapy, and local massage therapy can effectively provide patients with KOA with relief from their clinical symptoms. A pilot test of 50 community-dwelling elderly volunteers with KOA was performed. Finally, 43 volunteers completed two treatment periods (30 days each) and two post-treatment periods (30 days each). The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores were collected and analyzed after each period. The outputs of the low-level laser, heating, and massage therapies significantly decreased the WOMAC scores in terms of pain, stiffness, function and total WOMAC after two treatment periods (p < 0.05). Although the score increased slightly after the post-treatment period, it was still lower than the baseline, indicating the treatment outcome could last for an extended period. Therefore, our CUHK-OA-M2 device, as an integrated multi-functional hybrid therapeutic device, is therapeutically significant for treating osteoarthritis symptoms on the knee joints of elderly subjects.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".