The Fukuda stepping test is associated with various patterns of displacement
Bibliographic record
Abstract
Abstract Objective: This study was to characterize individual path trajectories during the 50-step Fukuda stepping test (FST) and to determine the impact of step height on these trajectories. Methods: Kinematic data from the shoulders and feet were recorded in 12 young healthy adults while performing the FST at a comfortable step height (CoStep) and while stepping with lifting the knees high (HiStep). Path trajectories were depicted by step-by-step displacement of the right and left toes, and body rotation was obtained from the rotation of the shoulders. The effect of step height on the distance traveled and the final anteroposterior (AP) and mediolateral displacements and rotation were determined with paired t -tests. Results: Path trajectories were composed of various combinations of forward displacement, lateral deviation, and rotation to the left or right. In comparison with CoStep, the mean AP displacement and mean distance traveled were significantly shorter in HiStep ( P < 0.05) while the mean rotation was significantly larger in HiStep ( P < 0.05), but the displacement patterns were not modified. Conclusion: We found that the path trajectories vary greatly among participants, and that step height has a significant impact on the magnitude of displacements and rotation during the FST.
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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 | 0.002 |
| 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) | 0.002 | 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".