Treadmill-Based Locomotor Training with Leg Weights to Enhance Functional Ambulation in People with Chronic Stroke: A Pilot Study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Novel locomotor training strategies for individuals with disorders of the central nervous system have been associated with improved locomotor function. The purpose of this study was to investigate the effects of treadmill-based locomotor training combined with leg weights on functional ambulation in individuals with chronic stroke. We assessed functional ambulation and muscle activity in ambulatory individuals with chronic stroke. METHODS: We used a pre/posttest design. Six individuals with chronic stroke who were community ambulators were recruited. Participants underwent a 30-minute treadmill-based locomotor training sessions three times per week for four to 12 weeks. The training program involved treadmill walking for 30 minutes with partial body weight support as needed. Leg weights, equivalent to 5% of body weight, were affixed around the paretic leg. Outcome measures consisted of the 10-m walk test, the modified Emory Functional Ambulation Profile, and temporal gait parameters. RESULTS: Improvements were observed in functional ambulation measures, particularly the stairs subscore of the modified Emory Functional Ambulation Profile. Participants also exhibited an increase in the proportion of time the paretic leg spent in swing. No significant improvements were observed in the 10-m walk test. CONCLUSIONS: This pilot study demonstrates that the combination of leg weights and treadmill training is a feasible approach, that is well tolerated by participants. This approach may have the potential to improve some aspects of functional ambulation and the performance of activities requiring hip and knee flexion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".