Wearable sensor performance for clinical motion tracking of the lumbar spine
Bibliographic record
Abstract
Inertial measurement units (IMUs) have potential to be integrated into clinical assessments of movement-related disorders of the spine. This study evaluated 2 Mbientlab MetaMotionR IMUs relative to Vicon motion capture equipment in tracking 3D spine motion during 35 cycles of constrained repetitive spine flexion-extension (FE) in 10 participants. Root-mean-square error (RMSE) was low in all anatomical planes (RMSE ≤ 2.43°). Pearson’s correlation coefficient was strong in the FE and lateral bend (LB) planes (R ≥ 0.746), and weak-to-moderate in the axial twist (AT) plane (0.343 ≤ R ≤ 0.679). Additionally, there was very strong correlation between range of motion measurements in the FE plane (ICC2,1 = 0.99), and a wide range from weak to strong in the LB and AT planes (0.239 ≤ ICC2,1 ≤ 0.980). This study reveals that the IMUs perform well in tracking motion in the primary movement plane, and can be used for planar assessments of movement quality.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".