Bilateral actigraphic quantification of upper extremity movement in hemiparetic children with perinatal stroke: a case control study
Bibliographic record
Abstract
BACKGROUND: Hemiparetic cerebral palsy impacts millions of people worldwide. Assessment of bilateral motor function in real life remains a major challenge. We evaluated quantification of upper extremity movement in hemiparetic children using bilateral actigraphy. We hypothesized that movement asymmetry correlates with standard motor outcome measures. METHODS: Hemiparetic and control participants wore bilateral wrist Actiwatch2 (Philips) for 48 h with movement counts recorded in 15-s intervals. The primary outcome was a novel statistic of movement asymmetry, the Actigraphic Movement Asymmetry Index (AMAI). Relationships between AMAI and standard motor outcomes (Assisting Hand Assessment, Melbourne Assessment, and Box and Block Test [BB]) were explored with Pearson or Spearman correlation. RESULTS: 30 stroke (mean 11 years 2 months (3 years 10 months); 13 female, 17 male) and 23 control (mean 11 years 1 month (4 years 5 months); 8 female, 15 male) were enrolled. Stroke participants demonstrated higher asymmetry. Correlations between AMAI and standard tests were moderate and strongest during sleep (BB: r = 0.68, p < 0.01). CONCLUSIONS: Standard tests may not reflect the extent of movement asymmetry during daily life in hemiparetic children. Bilateral actigraphy may be a valuable complementary tool for measuring arm movement, potentially enabling improved evaluation of therapies with a focus on child participation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".