Feasibility of delivering feedback through a virtual reality system for motor learning in children with cerebral palsy: a case study
Bibliographic record
Abstract
recommend it to others.The operative technique for the procedure and postop course is discussed. Study Participants & Setting:The group consisted of 6 males and 6 females who presented to our Brachial Plexus Program.The average age at surgery was 14 years 8 months, ranging from 11 years 11 months to 17 years 6 months.The initial plexus lesion was global in 10 patients and Erb's palsy in 2. Materials/Methods: Each patient had operative correction of their flexion contracture, utilizing a modified distal humeral arthrolysis, combined with an anterior approach that consisted of soft tissue release and median nerve neurolysis.Post-operatively, the patients were immobilized in a well padded plaster cast in gravity extension for 2 weeks.Then each had serial casting for 4 weeks using a long arm drop out casting technique.Patients were instructed in home exercise program, consisting of range of motion and strengthening exercises.Night splinting in full extension was recommended for a year.Results: Pre-operative flexion contractures averaged 49.6 degrees (À35 to À60).Post-operative flexion contractures averaged À21.1 degrees (À15 to À27).Average pre-op active elbow flexion was 130.8 degrees (130 to 150).Average post-op active flexion was 124.2 (90 to 140).Of these patients, 4 had no change in active flexion, 4 had loss of flexion, and 4 had gain of some flexion.All twelve patients were pleased with their results and stated that they would recommend the procedure.Of the 10 patients with recorded DASH scores, the average pre-op was 37.4, and the average post-op was 13.7.No patient showed a worse post-operative DASH score.All twelve patients were satisfied with their result and would recommend it to other patients.Conclusions/Significance: These are the preliminary results of a novel approach to significant problem of form and body image referable to the elbow.The modified Outerbridge-Kashiwagi procedure, as developed by the authors, provided significant, permanent gains in elbow extension.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".