Bibliographic record
Abstract
Objectives: The rate of growth of the elderly population is very high due to lower birth rates and increased health and medical progress, especially in developing countries, and should seek new technologybased solutions for the community, especially the elderly.The aim of this study was to improve the equilibrium parameters in the elderly and the effectiveness of the telex training program.Materials and Methods: In this semi-experimental study in Isfahan, in 2017, 40 healthy elderly men with the ability to perform exercise activities were selected by random sampling and randomly assigned to the experimental group and one control group Divided.The experimental exercise group (Tele-Exercise) was given as a training intervention for 8 weeks, 3 sessions per week, and 90 minutes each session.The equilibrium parameters were performed through a motion analyzer with seven cameras and a power plate connected to it.Descriptive statistics were used for data analysis and their homogeneity and ANOVA for repeated measurements for data analysis.Results: The use of a sports program as a tele-exercise significantly increased the equilibrium of parameters relative to the pre-exercise program (P <0.05), while in the same period, in the group that received the exercise program There was no significant change in the parameters of the correlation with equilibrium (P> 0.05).Conclusion: According to the findings of the research, it can be concluded that the use of a regular and continuous trapezoidal training program can be due to the improvement of equilibrium parameters as a suitable alternative for field training programs with direct supervision.In addition, tele-exercise exercises seem to be more effective in the elderly age group because of the reduction of dangers outside the home and placement in matched groups, and pave the way for healthy aging and good health in this life span.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.996 | 0.997 |
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; both teacher heads agree on what is shown here.
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".