The Effect of Extra Functional Exercises with and without Functional Muscle Stimulation on the Lumbar Lordosis in Women Aged 20-30 Years in Tabriz
Bibliographic record
Abstract
Objective Increased lordosis in the lumbar is one of the causes of poor posture and back pain.The purpose of this research is to investigate the effectiveness of extrafunctional exercises with and without functional stimulation of the muscles around the lumbar joints in women with increased lumbar lordosis. MethodsThe conducted research is quasi-experimental and applied.The statistical population consisted of 46 women divided into two equal groups within the age group of 20 to 30 years in Tabriz city, each having a lordosis angle of 40 degrees.Evaluation of lordosis angles (control and experimental groups) was measured using a flexible ruler, tilt meter, and McGill test (pre-test).Then, for 6 weeks, the experimental group performed three sessions of exercise protocol and muscle functional stimulation per week, while the control group only received exercises similar to those of the experimental group (post-test).Statistical analysis was conducted using independent t-tests and paired t-tests at a significance level of 0.05. ResultsIn the experimental group compared to the control group, there was a significant difference in lumbar lordosis and anterior pelvic tilt components in the post-test (P<0.05).Conclusion Based on the obtained results, it can be acknowledged that central stability exercises (Extra Functional) along with muscle functional stimulation can yield beneficial results in improving lumbar biomechanics in cases of lordosis and hyperlordosis disorders within the statistical population.
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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 | 0.001 |
| 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".