Gait analysis using a force-measuring gangway: intrasession repeatability in healthy adults.
Bibliographic record
Abstract
OBJECTIVES: The goal of the present study was to determine the repeatability of gait parameters measured by a force plate gait analysis system (Leonardo Mechanograph® GW). METHODS: Fifteen healthy adult participants walked at a self-selected speed on a 10 m long walkway. Vertical ground reaction forces were measured in the central 6 m of the walkway. Each participant performed three trials while walking barefoot and three trials while wearing shoes, each trial consisting of three 10 m walks. RESULTS: There were minimal differences between trials at each condition. All primary force, time, distance and velocity parameters had intraclass correlation coefficients above 0.90 and coefficients of variation in the order of 2% to 4%. Compared to walking barefoot, walking in shoes resulted in 14% lower maximal vertical ground reaction force, 5% longer step length and 2% higher average velocity and caused less lateral translation of the center of force. CONCLUSIONS: In this group of healthy adults, gait analysis with a force plate system produced repeatable intra-day results. The observation that barefoot and shod walking yield different results indicates that it is important to standardize test conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| 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".