Automated quantification and comparison of spatio-temporal GAIT parameters during treadmill and overground walking
Bibliographic record
Abstract
A critical part of rehabilitation is providing effective ways to document changes in balance and mobility restrictions/limitations. For overground walking, spatio-temporal gait parameters are widely collected using the GAITRite instrumented carpet. In addition to overground walking, treadmill walking has been shown to be an important tool in rehabilitation. An important advantage of treadmill walking is control over gait speed, which is essential when comparing most gait parameters over time and between participants, as speed can significantly influence the gait patterns. Thus, in this research, software was developed to analyze pressure data and calculate spatio-temporal gait parameters during treadmill walking. A flexible pressure mat was placed under the belt of any treadmill in order to record the foot pressures while the participant was walking. The calculated treadmill parameters were compared to the parameters obtained during overground walking on the GAITRite carpet at a similar speed and to treadmill walking at a fast speed, with and without hand support. Results showed that the spatio-temporal parameters which described the treadmill gait were similar to those describing overground gait. In addition, speed and hand support was shown to cause substantial changes in all parameters.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".