Terapia por Contensão Induzida e Treino Mental na Função de Membro Superior Pós-AVC
Bibliographic record
Abstract
Introduction. Stroke is the second leading cause of disability and death in the world. The most common clinical sign is hemiparesis, which undermines the performance of activities of daily living (ADL’s). Objective. Analise the constraint-induced movement therapy and mental practice to improve arm function in stroke patients. Method. Twenty hemiparetic patients, post-stroke, 45-74 years, randomly randomized into three groups: Group I (mental training) with 6 patients, Group II (Therapy Constraint-induced movement-TCI) with 6 patients and control group (kinesiotherapy) with 8 patients. Before and after treatment of the groups were assessed with the Fulg Meyer Scale, goniometry and Functional Independence Measure (FIM). The intervention carried for 4 months, 2 times a week for 30 minutes. Results. In Fulg- Meyer, which measures motor impairment of the upper limb (UL) affected an improvement in mobility and upper limb motor function (intragroup) in all groups, but the mental training group achieved better scores (intergroup) in goniometry group kinesiotherapy best result obtained in hand/fingers (intragroup). In MIF, which evaluates the functionality ADL’S, the Mental Training group had the best results (intragroup/intergroup). Conclusion. The mental training group showed better results in rehabilitation.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".