Using Wearable Technology to Measure Response to Deep Brain Stimulation in Children with Dystonia
Bibliographic record
Abstract
Introduction: Although dystonia is a common movement disorder in children, there are no objective means to quantify its severity. Aim: To evaluate actigraphy as a tool for the assessment of the motor and nonmotor manifestations of dystonia. Methods: Children with generalized dystonia and healthy controls were asked to wear the actigraphs for 14 consecutive days. Data on total sleep time (TST), physical activity patterns, and fractal regulation (FR) of the motor activity were extracted. Results: Eighteen children with dystonia and eleven healthy controls were included. The mean TST was comparable in both groups and was not correlated to Burke-Fahn-Marsden Dystonia Rating Scale-movement (BFMDRS-M). BFMDRS-M was positively correlated with time spent in sedentary activity. FR analysis in the dystonia group revealed more predictable motor fluctuations. No association was observed between the FR to BFMDRS. Conclusion: Actigraphy data are of limited utility as biomarkers of dystonia severity when benchmarked against currently available rating scales.
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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 | 0.001 | 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) | 0.002 | 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".