Effects of upper limb vibratory stimulation training on motor symptoms in Parkinson’s disease: an observational study
Bibliographic record
Abstract
OBJECTIVES: Parkinson's disease is characterized by motor and non-motor symptoms. Tremor is one of the motor symptoms that can affect manual skills and have an impact on daily activities. The aim of the current study is to investigate the effect of upper limb training provided by a specific vibratory device (Armshake®, Move It GmbH - Bochum, Germany) on tremor and motor functionality in patients with Parkinson's disease. Furthermore, the training effect on global cognitive functioning is assessed. DESIGN: An uncontrolled before-after clinical trial. PATIENTS: Individuals with diagnosis of Parkinson's disease, motor upper limbs deficits, and absence of dementia. METHODS: Participants underwent a 3-week programme (3 times a week) and was evaluated before, after, and at 1 month follow-up by motor (Fahn Tolosa Marin Tremor Rating Scale, Unified Parkinson's Disease Rating Scale - part III, Purdue Pegboard Test, Disability of the Arm, Shoulder and Hand Questionnaire) and cognitive (Montreal Cognitive Assessment) scales. RESULTS: Twenty subjects are included. After treatment a statistically significant improvement in tremor, manual dexterity and activities of daily living was found. The data indicated no effects on global cognitive functioning. CONCLUSION: These findings suggest positive effects of vibratory stimulation training on upper limb motor symptoms in Parkinson's disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".