Step Length Variability at Gait Initiation in Elderly Fallers and Non-Fallers, and Young Adults
Bibliographic record
Abstract
BACKGROUND: Normal aging is characterized by functional changes in the sensory, neurological and musculoskeletal systems. These changes affect several motor tasks including postural balance and gait. Gait variability has been suggested to be an important predictor of the risk of falling: the age-related increased variability may result of errors in the control of foot placement and/or center of mass displacement. Falls occur most frequently in elderly populations who scored poorly during transfer of quasi-static to dynamic situations, turning and reaching tasks in clinical tests. This suggests that gait initiation, which is a transient phase between standing and walking, could contribute to an increase in variability because, for elderly, muscular synergies associated with gait initiation occur less frequently than for young adults. OBJECTIVE: To examine if gait initiation and more particularly the variability of the first step length and the duration of the first double support period are more important for elderly fallers than for eldery non-fallers and young adults. METHODS: Elderly fallers, elderly non-fallers, and young adults were asked to initiate gait and walk at least 3 strides. Spatio-temporal characteristics of the first step and following strides were collected and across-trials variability analysed. RESULTS: Elderly fallers showed a much smaller first step length and a longer duration of the double support period. The first step length variability of elderly fallers was more than twice greater than that observed for elderly non-fallers. CONCLUSION: Considering the importance of proper initial foot placement for gait initiation and for stepping recovery responses, the first step length variability observed for the elderly fallers may be an important predictor of postural problems.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".