Assessing the Global Cognition of Community-Dwelling Older Adults Using Motor and Sensory Factors: A Cross-Sectional Feasibility Study
Bibliographic record
Abstract
Impairments in gait, postural stability, and sensory functions were proved to be strongly associated with severe cognitive impairment such as in dementia. However, to prevent dementia, it is necessary to detect cognitive deterioration early, which requires a deeper understanding of the connections between the aforementioned functions and global cognition. Therefore, the current study measured gait, postural, auditory, and visual functions and, using principal component analysis, explored their individual and cumulative association with global cognition. The global cognitive function of 82 older Korean males was determined using the Montreal Cognitive Assessment. The motor and sensory functions were summarized into seven independent factors using factor analysis, followed by age and education-level-adjusted linear regression model analysis. The seven factors obtained using factor analysis were gait speed, gait stability, midstance, general auditory ability, auditory recognition, overall visual ability, and postural stability. The linear regression model included years of education, gait stability, postural stability, and auditory recognition, and was able to explain more than half of the variability in cognitive score. This shows that motor and sensory parameters, which are obtainable through wearable sensors and mobile applications, could be utilized in detecting cognitive fluctuations even in the early stages of cognitive deterioration.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".