Split‐Belt Treadmill for Falls, Gait Asymmetry, and Freezing in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Individuals with Parkinson's disease (PD) can adapt to new gait patterns on a split-belt treadmill (SBTM), a tool previously used to rehabilitate gait asymmetry because of stroke. OBJECTIVES: The goal was to determine whether SBTM rehabilitation is superior to conventional "tied" treadmill (TM) in reducing falls, freezing of gait (FOG), and improving gait asymmetry. METHODS: Twenty-eight participants with idiopathic PD and treatment-resistant FOG underwent 18 sessions of SBTM and TM training. Primary outcome was the incidence of falls 3 months after training, and secondary measures included spatiotemporal gait variables (treadmill and over-ground), motor scores, and performance on FOG and balance questionnaires. RESULTS: Treadmill training improved falls regardless of intervention (SBTM: P < 0.05; TM: P < 0.01), although benefits were not sustained at 3 months. SBTM did not meet the a priori 20% superiority threshold for falls prevention. Asymmetry index, temporal asymmetry, and stance time (P ≤ 0.01 in both groups) reduced after training. Swing time increased after training with both interventions (P ≤ 0.01). FOG and ABC scores also improved (P ≤ 0.01 in both groups), however, these improvements were not sustained at 3 months. Cadence and over-ground asymmetry index improved with both interventions (P ≤ 0.01), although only reduced cadence was sustained at 3 months (P = 0.05). Other over-ground parameters including gait velocity, stride length, double-support time improved with TM training only. CONCLUSIONS: SBTM was not superior to TM training in improving incidence of falls. Both interventions improved FOG and spatiotemporal gait parameters, although TM training translated better to over-ground walking.
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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 | 0.004 | 0.008 |
| 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 | 0.001 |
| 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".