Use of a dual task paradigm to examine the effects of age on mobility and cognitive performances
Bibliographic record
Abstract
The increase in the aging population has become one of the most important problems of our society in last few decades. As people grow older, they are at risk of falling and consequent injuries due to the effects of aging. A fall may be the first indication of an undetected illness related to the effects of aging. This study demonstrates the effects of aging on balance, spatio-temporal gait parameters, gaze stability, and cognitive skills under single task conditions and during dual-tasks conditions. In the present study, we included following three groups: Group 1: 30 young healthy adults (aged 20 ± 3 years); Group 2: 30 adults (aged 61.4 ± 4.4 years); Group 3: 30 older adults (aged 75 ± 4.5 years). A computer game based rehabilitation platform has been developed and was used for the single and dual task performance in standing and during treadmill walking. We observed that there was a significant age effect while dual tasking on standing balance, spatial and temporal gait parameters, gaze performance, and cognitive task performance. To conclude, this study shows a vast decline in walking and standing balance and ability to divide attention during dual tasking between the age groups 55-70 years and 71- 85 years and compares both these age groups with the more normative, healthy, young and athletic, 20-30 years old population.
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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".