Bioimpedance Measurement of Knee Injuries using Bipolar Electrode Configuration
Bibliographic record
Abstract
Abstract Currently, there is no suitable solution for the point-of-care of knee injuries. A potential portable and low-cost technique for accessing and monitoring knee injuries is bioimpedance measurement. This study validated the feasibility of the bipolar electrode configuration for knee bioimpedance measurements with two electrodes placed on a fixed pair of knee acupuncture locations called Xiyan. Then, the study collected 82 valid samples to investigate the relationship between bioimpedance and knee injuries, among whom 45 patients, each with one healthy knee and one injured knee, and 37 individuals all with healthy knees. The self-contrast results indicated that knee injuries caused a reduction of bioimpedance of the knee by about 5% on average, which was detectable at around 100 kHz (p ≈ 0.001). Furthermore, the results analyzed by principal component analysis and support vector machines show that the detection sensitivity can reach 91.11% using the leave-one-out cross-validation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".