Spatiotemporal characteristics of gait when walking on an uneven surface in children with cerebral palsy
Bibliographic record
Abstract
For children with cerebral palsy (CP), walking on uneven surfaces (US) is a challenging task essential for their engagement in their daily lives. This study aims to compare spatiotemporal parameters of multiple domains of walking (pace, rhythm, stability, variability) in children with spastic CP between gait on an uneven surface (US) and an even surface (ES) and assess differences against their typically developing (TD) peers. A total of 34 children (17CP/17TD) walked at a self-selected speed on an US and an ES. Gait speed, stride length, stride time, walk ratio, cadence, double and single support time, and stride width were calculated. For each parameter, stride-to-stride variability was calculated using the coefficient of variation. A 2-way ANOVA (group, surface) was conducted on each parameter. Stride width, and variability of gait speed, cadence, and walk ratio presented a group × surface interaction (p ≤ 0.042). Post-hoc tests revealed a greater stride width, and variability of gait speed, and walk ratio in the CP, compared to the TD group (p ≤ 0.005) only on an US, and on both surfaces for cadence variability (p = 0.017). Gait analysis on an US reveals gait changes in children with CP, highlighting the importance of using more ecological approaches for gait assessment.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".