Development of an ergonomic musculoskeletal model to estimate muscle forces during vertical jumping
Bibliographic record
Abstract
This study investigated a musculoskeletal model that includes the function of the antagonistic muscles and biarticular muscles and models muscles acting across the hip, knee and ankle joints, simultaneously. Furthermore, this study can be applied to dynamic motions. One vertical jump trials were conducted to validate the proposed model. Electromyograms (EMGs) of tibials anterior, gastrocnemius, soleus, rectus femoris, vastus lateralis, semimembranosus, biceps femoris, short head and gluteus maximus were used to compare with the estimated muscle forces. The results showed that the muscle forces estimated by the proposed method had a stronger correlation with EMGs than those of an optimization method. The correlations of the proposed method and the optimization method were 0.4 and 0.01 of TA, 0.95 and 0.86 of GAS, 0.95 and 0.93 of SOL, 0.94 and 0.01 of RF, 0.93 and 0.97 of VAS, 0.83 and 0.91 of SM, 0.75 and 0.01 of BFSH and 0.95 and 0.92 of GMAX. Thus, the proposed method was considered to successfully estimate the muscle forces during vertical jumping.
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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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".