Wearable wrist activity monitor as an indicator of functional hand use in children with cerebral palsy
Bibliographic record
Abstract
AIM: New tools that capture hand function in everyday activities and contexts are needed for assessing children with hemiplegic cerebral palsy. This study evaluates a wearable wrist monitor and tests the hypothesis that wrist extension frequency (FreqE) is an appropriate indicator of functional hand use. METHOD: Fifteen children (four females, 11 males; age range 6-12y; mean age 10y [SD 2y]) with hemiplegia (seven at level I and eight at level II on the Manual Ability Classification System) participated in the Assisting Hand Assessment (AHA) while wearing the wrist monitor. FreqEs were captured via the wrist monitor and validated using video analysis. Correlations between FreqE and AHA scores were calculated and a multivariate linear regression was conducted to explore other measures of wrist activity. RESULTS: Wrist extensions observed in video analyses were reliably detected by the wrist monitor (intraclass correlation coefficient, r=0.88; p<0.001) and were strongly correlated with the AHA scores (r=0.93; p<0.001). AHA scores were significantly correlated with FreqE (r=0.80; p=0.001) and the range of wrist extensions/flexions (r=0.70; p=0.008). The multivariate linear regression combining the FreqE and range of wrist extensions/flexions yielded a strong correlation with AHA scores (r=0.84; p=0.0043). INTERPRETATION: The wearable wrist monitor may offer a convenient, valid alternative to observer reports for functional assessments of the hemiplegic hand in everyday contexts.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".