A Split-Belt Instrumented Treadmill with Uneven Terrain
Bibliographic record
Abstract
Abstract The biomechanics of walking are far less understood for uneven terrain than flat or even surfaces. This is due in part to a lack of ground reaction force and moment recordings from each leg. These are often obtained with split-belt instrumented treadmills, which are currently incompatible with uneven terrain, making it difficult to perform biomechanics analyses such as inverse dynamics. Here we show how a standard split-belt instrumented treadmill (Bertec, Inc., Columbus, OH) can be modified to accommodate a variety of uneven terrains. The principal design considerations are structural clearance to allow passage of an uneven treadmill belt and fabrication of the terrain. We designed mechanical components with sufficient clearance for terrains up to 0.045 m high, and formed the terrain from uneven strips of polystyrene. Measured ground reaction forces from each leg at typical walking speeds agreed well with an intact benchmark treadmill (minimum interclass cross correlation score = 0.97). The modifications had negligible effect on the treadmill’s structural strength. The terrain produced some noise-like vibrations, but at much higher frequencies than fundamental to human locomotion. The uneven terrain treadmill can record many steps of the full complement of ground reaction forces and moments from individual legs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".