Gait Parameters Associated With Responsiveness to Treadmill Training With Body-Weight Support After Stroke: An Exploratory Study
Bibliographic record
Abstract
BACKGROUND: Task-specific training programs after stroke improve walking function, but it is not clear which biomechanical parameters of gait are most associated with improved walking speed. OBJECTIVE: The purpose of this study was to identify gait parameters associated with improved walking speed after a locomotor training program that included body-weight-supported treadmill training (BWSTT). DESIGN: A prospective, between-subjects design was used. METHODS: Fifteen people, ranging from approximately 9 months to 5 years after stroke, completed 1 of 3 different 6-week training regimens. These regimens consisted of 12 sessions of BWSTT alternated with 12 sessions of: lower-extremity resistive cycling; lower-extremity progressive, resistive strengthening; or a sham condition of arm ergometry. Gait analysis was conducted before and after the 6-week intervention program. Kinematics, kinetics, and electromyographic (EMG) activity were recorded from the hemiparetic lower extremity while participants walked at a self-selected pace. Changes in gait parameters were compared in participants who showed an increase in self-selected walking speed of greater than 0.08 m/s (high-response group) and in those with less improvement (low-response group). RESULTS: Compared with participants in the low-response group, those in the high-response group displayed greater increases in terminal stance hip extension angle and hip flexion power (product of net joint moment and angular velocity) after the intervention. The intensity of soleus muscle EMG activity during walking also was significantly higher in participants in the high-response group after the intervention. LIMITATIONS: Only sagittal-plane parameters were assessed, and the sample size was small. CONCLUSIONS: Task-specific locomotor training alternated with strength training resulted in kinematic, kinetic, and muscle activation adaptations that were strongly associated with improved walking speed. Changes in both hip and ankle biomechanics during late stance were associated with greater increases in gait speed.
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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 | 0.001 | 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) | 0.001 | 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".