Effects of 30-min of walking on knee total joint moment asymmetry in asymptomatic adults
Bibliographic record
Abstract
INTRODUCTION: Gait asymmetry is considered an indicator of healthy gait and used in clinical and research settings to assess movement. While walking is commonly prescribed to promote cardiovascular health and assess gait under controlled conditions, prolonged walking may disrupt gait asymmetry. This study examined changes in knee total joint moment (TJM) asymmetry following a 30-min treadmill walk in asymptomatic adults. METHODS: Participants completed five overground walking trials at a self-selected speed before and after a 30-min treadmill walk. Three-dimensional motion capture and ground reaction forces were used to calculate knee joint moments. The TJM was calculated as a composite measure of the net external knee frontal, sagittal, and transverse moments, and absolute inter-limb asymmetry in the TJM was calculated. Paired samples t-tests and 95 % bootstrapped confidence intervals were used to assess the expected change in TJM asymmetry following the 30-min walk. Statistical parametric mapping assessed differences in knee frontal, sagittal and transverse plane moments before and after the treadmill walk. RESULTS: Twenty-one asymptomatic adults (age 61 ± 10 years, 14 F/7 M) were recruited for this study. Following the treadmill walk TJM asymmetry increased by 10.1 % (95 %CI: 4.88-16.1, p = 0.005, d=0.73), with 76 % of participants increasing asymmetry post-walk driven primarily by an increase in the peak frontal plane moment (p = 0.013). CONCLUSIONS: This study provides a benchmark for clinicians and researchers to gauge the expected change in TJM asymmetry in healthy adults following a 30-min walking intervention. We observed that asymmetry increases by approximately 5-16 % in this population; however, high inter-individual variability was noted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".