Muscle-driven simulations and experimental data of cycling
Bibliographic record
Abstract
Muscle-driven simulations have provided valuable insights in studies of walking and running, but a set of freely available simulations and corresponding experimental data for cycling do not exist. The aim of this work was to develop a set of muscle-driven simulations of cycling and to validate them by comparison with experimental data. We used direct collocation to generate simulations of 16 participants cycling over a range of powers (40-216 W) and cadences (75-99 RPM) using two optimization objectives: a baseline objective that minimized muscle effort and a second objective that additionally minimized tibiofemoral joint forces. We tested the accuracy of the simulations by comparing the timing of active muscle forces in our baseline simulation to timing in experimental electromyography data. Adding a term in the objective function to minimize tibiofemoral forces preserved cycling power and kinematics, improved similarity between active muscle force timing and experimental electromyography, and decreased tibiofemoral joint reaction forces, which better matched previously reported in vivo measurements. The musculoskeletal models, muscle-driven simulations, simulation software, and experimental data are freely shared at https://simtk.org/projects/cycling_sim for others to reproduce these results and build upon this research.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".