Application of Ultrasound in Spine Kinematic Determination
Bibliographic record
Abstract
Spine kinematic determination is required to diagnose or rehabilitate back pain due to spinal instability. Ultrasound imaging, as a less harmful and cost-effective method, has been recently applied to kinematic analysis. This study reviews all available published articles to see how much progress has been made in spine kinematic measurement by ultrasound. In this regard, we searched PubMed, Scopus, and Google Scholar among all available studies until 2021, using keywords such as ultrasound, spine, kinematics, rotation, twist, flexion, and bending. Finally, after identifying and scanning 183 articles, only nine articles were included, which analyzed spine kinematics by ultrasound. Among these nine articles, three reported axial displacements, three reported flexion/extension, and three reported axial rotation. Although ultrasound is a suitable alternative to other kinematic measurement methods, very little research and progress have been made in this area. Today, this method is still not used practically for spine kinematic measurement because the bone scans via ultrasound imaging are challenging to understand, and no three-dimensional kinematic measurement technique has been reported. However, recent advances in converting ultrasound images into three-dimensional images can pave the way for further improvements.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 teacher head, 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".