Enhancement of rigidity in Parkinson's disease with activation
Bibliographic record
Abstract
Rigidity, a cardinal symptom of Parkinson's disease (PD), increases with movement of a contralateral limb. It is unclear whether this effect is specific for movement of a contralateral limb. The goal of this study was to test the hypothesis that ipsilateral or contralateral movement would enhance rigidity but that bilateral limb movements would maximally increase rigidity in people with PD. We assessed rigidity in 12 people with PD off meds, 12 matched controls, and 10 young controls, using a Rigidity Analyzer (Neurokinetics, Alberta, Canada). The elbow was passively moved repetitively into flexion and extension by the examiner, while the subjects engaged in different toe tapping conditions: no tapping, ipsilateral tapping, contralateral tapping, and bilateral tapping. Three 50-second trials were done for each condition and the order of the trials was randomized. A 2-way repeated measures ANOVA and Holm-Sidak post hoc tests were used to determine differences across conditions and groups. There was a significant effect of group, tapping conditions and an interaction of the two. Post hoc tests revealed that for the PD group, all tapping conditions were significantly different from the no tapping condition but not different from each other. There were no differences across conditions for the controls. We conclude that movement of either the contralateral or ipsilateral lower extremity can increase arm rigidity in people with PD but the effects from left and right are apparently not additive. Further, activation did not enhance muscle tone in controls suggesting that this procedure may help distinguish people with PD from controls.
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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) | 0.000 | 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) | 0.001 | 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".