Lower limb joint moments on the fast belt contribute to a reduction of step length asymmetry over ground after split-belt treadmill training in stroke: A pilot study
Bibliographic record
Abstract
The main goal was to investigate changes in muscle activity and joint moments related to step length (SL) symmetry improvements in individuals poststroke following repeated split-belt treadmill (SBT) walking. Twelve individuals with a first unilateral cerebral stroke presenting initial SL asymmetry (ratio = 1.10–2.05), and mean time post stroke 23 (SD 24.7 months) were included. Participants were trained during six sessions of SBT walking using an error-augmentation protocol. The training resulted in a reduction in SL asymmetry during walking over ground retained over 1-month post-training (p = 0.002). Significant increases in SL and joint moments (plantarflexors: 20–60%, knee flexors: 20–60% and hip extensors: 0–20% of the gait cycle) were observed on the side trained on the fast belt (effect size from 0.41 to 0.60). The improvement in SL symmetry was observed with an increase in plantarflexion joint moment symmetry. Changes in muscle activity varied among participants. In contrast to previous findings with a single exposure to SBT-training, our results showed no negative effects on paretic plantarflexors when walking over ground after repeated exposure to SBT walking. These findings justify larger trials to gain more solid information on the current protocol which appears as an efficient training for long-term recovery on SL asymmetry and on affected plantarflexors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".