Cross-spectral analysis quantifies the segmental coordination in unstable sitting
Bibliographic record
Abstract
Abstract Introduction: Low back pain(LBP) affects many individuals and is known to be associated with impaired trunk control. While LBP can be associated by treating underlying trunk impairments, a better understandinf of the mechanistic origin of the disorder is required. Trunk control has been commonly studied via an unstable sitting paradigm. Knowledge on how the base of support and body segments work together to complete the unstable sitting task, and how this is modified in individuals with LBP, could be utilized when designing interventions for this population. Our obiective was to characterize the segmental coordination in non-impaired unstable sitting as elicited via a wobble board(WB) paradigm. Methods: WB, pelvis, and trunk motion were recorded in fifteen non-disabled participants sitting on a wobble board. We used cross-spectral analysis to quantify the coordination of the anterior-posterior angular kinematics of the wobble board, pelvis, and trunk. Results: During unstable sitting, the motion of the pelvis was followed by that of the trunk(one-eighth-cycle delay) and wobble board(half-cyclw delay) at frequenties between 1 and 2 Hz. Conclusion: Future work should utilize the knowledge gained in this study when creating rehabilitation interventions for individuals with LBP.
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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) | 0.003 | 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".