The spatiotemporal gait parameters among people with visual impairment: A literature review study
Bibliographic record
Abstract
Gait is an individual's walking pattern, and it is a significant part of daily living activities. Quantitative gait assessments, like spatiotemporal parameters (STPs), are related to the functional conditions to provide useful information. This study reviewed the comprehensive differences in spatiotemporal gait variability measures between visually impaired people and the sighted. The search strategy was performed in three databases (PubMed/MEDLINE, Web of Science, and Scopus) from the start date to October 2022, and the utilized keywords for this search are related to gait and blindness. This review considered only those studies that evaluated gait parameters in people with visual impairment and blind people without any limitations in age and gender. In this review, studies without a control group (sighted people) were excluded. The Newcastle-Ottawa Scale (NOS) was applied for critical appraisal. Six full manuscripts were included. The sample size ranged from 19 to 91. The mean modified NOS critical appraisal scores for cross-sectional studies were 6.0. In these studies, among nine STPs: stride length, walking speed, stance and swing phase, step width, cadence, step length, double support, and single support, at least five and at most seven factors were examined. The gait pattern of blind and low-vision people is characterized by a slower walking speed, shorter stride length, increased step width, decreased cadence, prolonged duration of double support, and reduced single support compared to the controls.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".