Effects of physiotherapy associated to virtual games in pain perception and heart rate variability in cases of low back pain
Bibliographic record
Abstract
Introduction: The virtual games when appropriately used can stimulate brain activity and excite the creative energy. Therefore, it is important to assess the implications of their use in pain perception in individuals with low back pain (LBP), a disease that affects about 80% of the world’s population. Objective: was to evaluate the effects of virtual games combined with a physiotherapy program on the pain perception and Heart Rate Variability (HRV) in people with LBP. Method: the participants were 21 adults with clinical diagnosis of LBP, aged 24-61 years, of both sexes, divided into two groups. Five weekly meetings were provided. Group 1 participated in a physical therapy program and group 2 participated in the same physical therapy program plus joint sessions with virtual games. The instruments used were a heart rate monitor; a tablet for games; a shortwave equipment; visual analogue scale (VAS); and McGill’s Pain Questionnaire. The measurements were performed before and after the program. Results: Reduction in pain was observed in both groups, being higher in group 2, the one that used the games. Conclusion: There was a decrease in parasympathetic activity in group 2, which indicates that the distraction factor promoted by the games influenced the pain perception.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".