Using gait robotics to improve symptoms of Parkinson's disease: an open-label, pilot randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: People with Parkinson's Disease (PD) have difficulty participating in exercise. AIM: The primary objective of this pilot randomized controlled trial (RCT) was to determine if 8 weeks (2x per week) of bilateral exoskeleton (Exo) exercise results in positive changes in cognition and participation in adults with PD compared to exercising without an exoskeleton (Nxo) or wait-list control (Con). DESIGN: Open-label, parallel, pilot randomized controlled trial. SETTING: Neurorehabilitation clinic in a large urban center. POPULATION: Adults 50-85 years old with a confirmed diagnosis of PD. METHODS: Eight weeks of twice-weekly combined aerobic, strength and mobility exercise or wait-list control. Participants were randomly assigned to exercise with no exoskeleton (Nxo), exercise with the exoskeleton (Exo), or waitlist control (Con). Primary endpoints were change in cognitive function (SCOPA-COG) and mood. Secondary endpoints were change in gait speed, six-minute walk test (6MWT), freezing of gait, balance, and PD-specific health and quality of life outcomes. Safety endpoint was analysis of adverse events (AE). RESULTS: Forty participated in the trial (Exo, N.=13; Nxo, N.=14; Con, N.=13). Significant improvement in the Memory & Learning domain of the SCOPA-COG (P=0.014) and 6MWT (P=0.008) were detected for the Exo group compared to the Nxo and/or Con group. No other statistically significant between-groups effects were found. There were no serious or unanticipated AE. CONCLUSIONS: Functional exercise with a low-profile overground exoskeleton showed promising results for improving memory and gait endurance in people with PD across HY stages I-IV. CLINICAL REHABILITATION IMPACT: Exoskeletons can improve participation in high-intensity exercise.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".