Mechanics and Energetics of Human Feet: A Contemporary Perspective for Understanding Mobility Impairments in Older Adults
Bibliographic record
Abstract
Much of our current understanding of age-related declines in mobility has been aided by decades of investigations on the role of muscle-tendon units spanning major lower extremity joints (e.g., hip, knee and ankle) for powering locomotion. Yet, mechanical contributions from foot structures are often neglected. This is despite the emerging evidence for their critical importance in youthful locomotion. With rapid growth in the field of human foot biomechanics over the last decade, our theoretical knowledge of young asymptomatic feet has transformed, from long-held views of a stiff lever and a shock-absorber to a versatile system that can modulate mechanical power and energy output to accommodate various locomotor task demands. In this perspective review, we predict that the next set of impactful discoveries related to locomotion in older adults will emerge by integrating the novel tools and approaches that are currently transforming the field of human foot biomechanics. By illuminating the functions of feet in older adults, we envision that future investigations will refine our mechanistic understanding of mobility deficits affecting our aging population, which may ultimately inspire targeted interventions to rejuvenate the mechanics and energetics of locomotion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".