Differentiating Motor Coordination and Position Sense in Children with Cerebral Palsy and Typically Developing Populations Through Robotic Assessments
Bibliographic record
Abstract
Motor function and coordination improve as children age. Robotic assessments of motor function and coordination have been shown to be repeatable, objective, and accurate. Additionally, robotic assessments have been used to measure and quantify deficits in motor function and coordination in children with cerebral palsy (CP). Normative models of motor function and coordination based on age have not been used widely to differentiate impaired performance from typical performance. This study presents preliminary results of identifying deficits in motor function and coordination assessed with a robotic reaching task and using a normative model of typical performance that accounts for age, sex, and handedness. The models were compared with data from three participants with CP to evaluate whether the models could be used to identify deficits in motor function. The models indicated motor deficits in one participant when performing a visually guided reaching task with respect to initial speed and distance ratios. There was no evidence of motor control deficits in the other two participants. Future work will refine the models to be able to better identify and quantify motor control impairments with the potential to target therapy around quantifiable goals.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".