Validating Determinants for an Alternate Foot Placement Selection Algorithm During Human Locomotion in Cluttered Terrain
Bibliographic record
Abstract
The goal of this study was to validate dynamic stability and forward progression determinants for the alternate foot placement selection algorithm. Participants were asked to walk on level ground and avoid stepping, when present, on a virtual white planar obstacle. They had a one-step duration to select an alternate foot placement, with the task performed under two conditions: free (participants chose the alternate foot placement that was appropriate) and forced (a green arrow projected over the white planar obstacle cued the alternate foot placement). To validate the dynamic stability determinant, the distance between the extrapolated center of mass (COM) position, which incorporates the dynamics of the body, and the limits of the base of support was calculated in both anteroposterior (AP) and mediolateral (ML) directions in the double support phase. To address the second determinant, COM deviation from straight ahead was measured between adaptive and subsequent steps. The results of this study showed that long and lateral choices were dominant in the free condition, and these adjustments did not compromise stability in both adaptive and subsequent steps compared with the short and medial adjustments, which were infrequent and adversely affected stability. Therefore stability is critical when selecting an alternate foot placement in a cluttered terrain. In addition, changes in the plane of progression resulted in small deviations of COM from the endpoint goal. Forward progression of COM was maintained even for foot placement changes in the frontal plane, validating this determinant as part of the selection algorithm.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".