Pelvis-Thorax Coordination in the Transverse Plane During Walking in Persons With Nonspecific Low Back Pain
Bibliographic record
Abstract
STUDY DESIGN: Transverse pelvis and thorax rotations were studied during walking in 39 patients with nonspecific low back pain and 19 healthy participants. OBJECTIVES: To gain insight into the consequences of low back pain for gait and to identify clinically useful measures for characterizing the quality of walking in patients with low back pain. SUMMARY OF BACKGROUND DATA: Gait studies in patients with low back pain have reported a decrease in walking velocity. In normal gait, in-phase pelvis-thorax coordination (synchronicity) evolves toward antiphase coordination (counterrotation) as walking velocity increases. This study examined the effect of walking velocity on pelvis and thorax rotations in patients with low back pain. METHODS: Amplitudes of pelvis and thorax rotations were calculated, and spectral analyses were performed. Pelvis-thorax coordination was characterized in terms of relative Fourier phase, and coupling strength was assessed by means of cross-spectral analysis. RESULTS: In comparison with healthy participants, relative Fourier phase was significantly smaller in low back pain patients for walking velocities of 3.8 km/h and higher, whereas coupling strength was significantly higher for velocities from 1.4 to 3.0 km/h. No significant group differences were found in amplitude or spectral content of individual pelvis and thorax rotations. CONCLUSION: In comparison with healthy participants, the gait of patients with low back pain was characterized by a more rigid, less flexible pelvis-thorax coordination in the absence of significant differences in the kinematics of the component rotations. This result suggests that coordination measures are more adequate in assessing quality of walking in patients with low back pain than are kinematic measures pertaining to the individual segment rotations, and that conservative therapy should use methods aimed at improving intersegmental coordination.
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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 | 0.000 | 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".