Optimal relative timing of stance push-off and swing leg retraction
Bibliographic record
Abstract
Swing leg retraction, the backward rotation of the swing leg prior to heel-strike, is known to have several advantages in legged locomotion. To achieve this motion, a hip torque is required at the end of the swing phase to brake the forward rotation of the leg and/or accelerate its backward motion. In walking, pre-emptive push-off of the stance leg also occurs at the end of the swing, so its relative timing with late-swing retracting torque influences gait energetics. To find the best relative timing between the stance leg's push-off force and the swing leg retraction torque, we calculate their work-based energetics in a simple bipedal model using impulsive approximations and with the aid of the so-called overlap parameter that quantifies the relative order and the percentage overlap of the push-off and retraction impulses. By minimizing the energetic cost of the gait, we found that it is energetically favorable to start with the push-off force, and postpone braking the leg swing until completely after the push-off (impulsive force/torque). The implication for the more realistic non-impulsive cases is to apply the retraction torque at the very end of the push-off before heel-strike. We show that the results are valid for many other bipedal models, for both periodic and aperiodic gaits, and regardless of the actuator efficiencies for positive and negative work.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Simulation or modeling | high |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.001 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".