Minute by Minute Differences in Co-activation during Treadmill Walking in Cerebral Palsy
Bibliographic record
Abstract
1872 PURPOSE: To determine, in children with spastic cerebral palsy (CP), minute-byminute differences in co-activation and stride length (SL) during treadmill walking following 12–15 minutes of treadmill walking practice. In addition, to determine if co-activation is affected by lower limb dominance. METHODS: Following 12–15 minutes of treadmill walking practice during an introductory visit, 3 girls and 5 boys (mean, SD; 11.9 ± 2.5 y; 146.8 ± 14.7 cm; 37.4 ± 13.1 kg) with mild spastic cerebral palsy (5 diplegic, 3 hemiplegic) walked on the treadmill for 3 minutes at 90% their of individually determined fastest treadmill walking speed. Electromyographic (EMG) activity from antagonist muscles at the thigh (quadriceps and hamstrings) and lower leg (tibialis anterior and triceps surae), bilaterally, was collected for the entire 3 minutes of each walk. Thigh and lower leg antagonist muscle co-activation was subsequently quantified using a co-activation index where peak or maximum EMG activity was defined as 100. RESULTS: Non-dominant thigh co-activation decreased between minute 1 and minute 2 (6%), and minute 3 (7.2%). Co-activation for the dominant lower leg decreased between minute 1 and minute 3 (11.3%). Non-dominant thigh co-activation was on average 27.3% higher than the dominant thigh. Thigh coactivation was on average 27.7% greater than the lower leg, independent of dominance or time. SL decreased between minute 1 and minute 3 by 2.1%. CONCLUSIONS: Fifteen minutes of treadmill walking practice may be sufficient time to obtain stable co-activation and SL values by minute 2 of a fast treadmill walk. Dominance and site affect the magnitude of co-activation. Supported by a grant from the Bloorview Children's Foundation.
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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 | 0.000 | 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".