A pilot study of the impact of the electro-suit Mollii® on body functions, activity, and participation in children with cerebral palsy
Bibliographic record
Abstract
Electrical stimulation has been used to treat spasticity in children with cerebral palsy. Building on the benefits of electrical stimulation, a new assistive device, electro-suit Mollii® with imbedded electrodes has been tested. The aim of the study was to evaluate the possible effect of Mollii® on body function, activity and participation in self-selected activities. Six children, five to ten years of age, used the electro-suit for one hour, every other day for three months. The impact was evaluated after four weeks and after three months by measuring passive range of motion (ROM), muscle tone, pain, gross motor function and participation. All participants improved in the total score for Canadian Occupational Performance Measure (COPM), three of them showed significant clinical improvements. Pain was reduced for children who estimated pain when the study started. There were also small changes in Electro-suit Mollii® had a positive impact on activity and participation in self-selected activities among the children in this study. Further studies with more children over a longer time are necessary to evaluate the impact and usefulness over time.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".