Robot-assisted therapy for upper limb impairments in cerebral palsy: A scoping review and suggestions for future research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract A growing number of studies investigate the use of robotics therapy for motor (re)habilitation with children with cerebral palsy (CP). Most of these studies use functional robots in very repetitive sessions. While the therapy is effective, very few studies employ social robots, which appears to be a missed opportunity to design more compelling and enjoyable sessions for the children. In this article, we will review robot-assisted upper limb motor (re)habilitation for children with CP. Previous reviews of robot-assisted therapy for CP had mostly focused on lower limbs, or the review was made from a medical point of view, with the sole concern being the therapy’s effectiveness. Here, we focus our review on robot-assisted upper limb (re)habilitation and address human–robot interaction considerations. We searched PubMed, Scopus, and IEEE databases and argue that although this area of research is promising and already effective, it would benefit from the inclusion of social robots for a more engaging and enjoyable experience. We suggest four scenarios that could be developed in this direction. The goal of this article is to highlight the relevance of the past work and encourage the development of new ideas where therapy will socially engage and motivate children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it