Split-Belt Treadmill Training to Rehabilitate Freezing and Gait Instability in Parkinson’s Disease
Bibliographic record
Abstract
Freezing of gait (FOG) and postural instability, which tend to occur together, are often the mostdisabling and treatment-resistant symptoms in Parkinson’s disease (PD). Progressive asymmetry of gait precedes a freezing episode, so targeting this symptom could potentially reduce the frequency of FOG and falls. We use a split-belt treadmill (SBTM), which has two belts that can modulate spatiotemporal parameters of each leg, to potentially rehabilitate and restore symmetrical gait in PD. Our research supports that individuals with PD+FOG can adapt to gait patterns induced by the SBTM. However, cognitive function is pertinent to gait adaptation (working memory; p<0.001) and retention of after-effects (working memory and visuospatial function; p<0.001 for both). We subsequently used intact working memory as an inclusion criterion in a randomized control trial to assess the effects of prolonged SBTM training. SBTM did not meet the a priori 20% superiority threshold for falls prevention. Several gait parameters (asymmetry index: p<0.01; temporal asymmetry: p<0.01; stance time: p<0.01; swing time: p<0.05) and questionnaire scores (Activities-specific Balance Confidence: p0.01; Freezing of gait questionnaire: p0.01) improved with SBTM training, but effects were not sustained three months after training. Conventional TM training also improved gait parameters (asymmetry index: p=0.04; temporal asymmetry: p<0.01; stance time: p<0.01; swing time: p<0.05), which replicates previously published literature. Without additional cuing strategies, conventional TM training also improved FOG. Over-ground cadence reduced with both interventions (p0.01, sustained at three months, p=0.05), but other parameters including gait velocity, stride length, double-support time improved with TM training only. This thesis briefly explored the role of Nucleus Basalis of Meynert deep brain stimulation, a cholinergic nucleus implicated in cognitive function in PD. Our results suggest that intermittent rather than continuous stimulation improves sustained attention (p=0.01), although spatiotemporal gait variables remain unaffected. This might indicate that cholinergic projections from the pedunculopontine, and not the basal forebrain, affect locomotor function in PD. SBTM training could be a cost-effective rehabilitation strategy, but its implementation is limitedby the heterogeneity of reported protocols. Future studies will also need to consider the specific needs of the PD+FOG population as they take longer to adapt, might benefit from alternate training protocols (eg. alternating belt velocities) and repeated exposure due to the progressive nature of PD.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".