Spine-Straight Device for the Treatment of Kyphosis
Bibliographic record
Abstract
Kyphosis is an excessive rounding of the upper spine. Its treatment depends upon the severity, the age of the patient and the levels of the spine that are affected. Early diagnosis is a key to providing optimal treatment. In a skeletally immature patient, an exercise program or bracing is the most commonly used treatment. However, the compliance of bracing for adolescents is poor and exercise training is labor intensive. The purpose of this study is to determine whether a Spine-Straight device can help patients to correct their kyphosis themselves and there by reduce back pain without the biomechanical support of a brace. The Spine-Straight device consists of an accelerometer and a microcomputer unit. The accelerometer is used to measure the kyphotic angle and the microcomputer unit controls a pager vibrator to alert patients when their posture exceeds personalized thresholds. The system was tested in the laboratory before used by subjects. The results were compared to back data obtained from a laser scanner imaging system. The maximum angle deviation between the laser scanner and the Spine-Straight device was 1.5 degrees. Two volunteers tested the systems for 2 days. The accelerometer was placed at the T3 location and the microcomputer unit was carried during daily activities. The angle measurement was recorded at 1 minute intervals during daily activity over a period of 2 days. The preliminary trials demonstrate subjects can improve their posture when feedback signals were provided.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".