Handwriting at Different Paces and Sizes With Visual Cues in Persons With Parkinson’s Disease
Bibliographic record
Abstract
Background: Persons with Parkinson’s disease (PD) typically have small handwriting, especially when writing faster and/or larger. However, visual cues can help persons with PD increase their handwriting size. This study tested if lined paper would improve handwriting in persons with PD, even when writing faster and/or larger. Secondarily, we wanted determine if persons with PD perceived handwriting as stressful, and if perceived stress was associated with writing performance. Methods: The study included 22 subjects with Parkinson’s disease and 11 age-gender-matched controls. Participants completed eight trials (2 × 2 × 2) of printing a “P” and “d”, at a comfortable speed and also as fast as possible in two different sizes (1, 2 cm). The participants wrote with a ballpoint pen on lined paper. Bipolar electromyography (EMG) sensors recorded muscle activity from the index finger extensor (extensor digitorum communis (EDC)) and flexor (first dorsal interosseous (FDI)). Participants completed all of the trials for a particular pace (conditions were randomized) before completing all the trials of the other pace (order was counterbalanced). Results: Handwriting height was smaller for persons with PD when required to write fast. There was also a trend for patients with PD to write slower and have smaller peak pen accelerations, but these were not statistically significant. Persons with PD found handwriting to be more stressful than healthy older adults did; and perceived stress negatively correlated with letter height and EMG activity. Conclusions: Our study found that visual cues did not normalize handwriting height in persons with PD when writing large and/or fast. Persons with PD find handwriting to be stressful, and stress may negatively influence their handwriting. J Neurol Res. 2018;8(3):26-33 doi: https://doi.org/10.14740/jnr493w
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".