Bibliographic record
Abstract
Objective: The study aimed to propose the role of a newly developed Stand-up Assistive Device for the elderly to provide a comfortable, convenient, and safe way of standing from various sitting conditions. Methods: A Stand-up Assistive Device was developed for research tool by overcoming such issues as heavy weight, bulky size and high costs. Total of 90 elderlies over 65 years old participated in the study to evaluate the developed device by administering Rapid Entire Body Assessment(REBA), sit-to-stand performance analysis(standing stages and motor skills) and Quebec User Evaluation of Satisfaction with assistive Technology(QUEST) which were used as assessment tools. Results: Statistical significance(p<.05) were observed between with/without using developed device in the scores of REBA. Sit-to-stand performance analysis also revealed statistical significance in the mean score of stage 1 to stage 6 for the standing phase when the participants were standing with using the assistive device as compared to without using it(p<.05). It was also consistent for motor skills as there were statistically significant in flows, endures, paces and mean score of motor skill between two conditions. The results of usability test revealed that the participants were positively responded ‘satisfactory’ or above in general. Conclusion: Stand-up Assistive Device developed in this study demonstrated certain advantages in terms of convenience, efficiency and safety when it is used for the elderly. It is recommended that developed device could be broadly applied to potential users who are having problems of standing up from various sitting situations.
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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) | 0.003 | 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".