Review and Analysis of Frontal Plane Stability Assistance for Elderly Individuals
Bibliographic record
Abstract
Gait assistance for the elderly population is crucial for promoting the longevity of individuals within the aging Canadian population. Elderly individuals have greatly benefited from the recent development of walking assist devices to maintain their ability to commute and partake in daily activities; however, falls still represent an enormous factor in geriatric injury and injury-related death tolls. Frontal plane instability has been reported to be a principal culprit of elderly falls. Degenerative muscle loss in the lower limbs, primarily hip abductor/adductor muscles and ankle invertor/evertor muscles, as well as deteriorating neurological balance control are often to blame for one’s inability to stabilize their center of mass and control lateral pelvic motion throughout gait. While various solutions for potential frontal plane balance assist exoskeletons are currently being developed, they remain in early-stage development and are unfeasible for day-to-day usage. Furthermore, minimal research has been conducted on the optimization of exoskeleton designs using evidence-based approaches for increasing and/or regaining an individual’s frontal stability. This paper discusses frontal plane stability, and age-related musculoskeletal and balance coordination challenges surrounding frontal plane stability in elderly gait. Thereafter, current ambulatory devices and novel mediolateral stabilization assist exoskeletons are reviewed based on their impact on frontal stability for elderly individuals focussing on their effectiveness and feasibility for daily use.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".