Effects of age on dynamic balance measures and their correlation during walking across the adult lifespan
Bibliographic record
Abstract
In this study, we aimed to discover (1) the effects of age on dynamic balance measures, including the margin of stability (MOS), whole-body angular momentum (H), and misalignment of the desired and measured centers of pressure (dCOP and mCOP, respectively) in the anteroposterior (AP) and mediolateral (ML) directions, (2) the relationship between gait parameters and these balance measures, and (3) the relationships between these balance measures. We used the kinetic and kinematic data of 151 participants aged 20-77 years from a publicly available database. Participants were divided into three groups: young, middle-aged, and old. The step width of the old group was higher than that of the young group. Age-related differences in dynamic measures were found in the ML direction and not in the AP direction: MOS, peak-to-peak range of H, and dCOP-mCOP in the old group were greater than in the young group. ML MOS positively correlated with the frontal peak-to-peak range of H. The ML peak-to-peak range of H positively correlated with ML dCOP-mCOP across the adult lifespan. Our findings provide new insights for understanding the effects of age on dynamic balance and the relationships between the metrics. Older adults walked with a larger step width, resulting in a large stability margin in the ML direction, although with increased moment and momentum around the center of mass in the frontal plane.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".