A Pilot Study to Determine the Consistency of Simultaneous Sleep Actigraphy Measurements Comparing All Four Limbs of Patients with Parkinson Disease
Bibliographic record
Abstract
Wrist actigraphy is a form of objective sleep measurement that has gained a central role in sleep research and clinical settings. Guidelines for actigraphy recommend placing the monitor on the non-dominant wrist, however, this potentially will be the most involved limb for someone with Parkinson disease, and so alternative placement would be preferred. To-date, there is little published about sleep actigraphy use in Parkinson disease (PD). This study examines the degree of sleep actigraphy score variation in persons with PD when monitors are placed simultaneously on all four limbs. In this study, four participants wore a sleep actigraph on each limb for seven nights. Data from the four actigraphs was compared within each participant to determine the degree of consistency. We found that all of the participants' sleep efficiency and total sleep time scores were higher in the lower limb than upper limb. There was no notable difference in sleep variables between the dominant arm and non-dominant arm. We concluded that simultaneous actigraphy measurement did not notably vary between dominant and non-dominant arms. However, a discrepancy was seen between upper limbs and lower limbs actigraph scores. Further study is warranted to develop guidelines for sleep actigraphy use in this population.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".