Predicting the Functional Roles of Knee Joint Muscles from Internal Joint Moments
Bibliographic record
Abstract
INTRODUCTION: Knee muscles are commonly labeled as flexors or extensors and aptly stabilize the knee against sagittal plane loads. However, how these muscles stabilize the knee against adduction-abduction and rotational loads remains unclear. Our study sought 1) to classify muscle roles as they relate to joint stability by quantifying the relationship between individual muscle activation patterns and internal net joint moments in all three loading planes and 2) to determine whether these roles change with increasing force levels. METHODS: A standing isometric force matching protocol required subjects to modulate ground reaction forces to elicit various combinations and magnitudes of sagittal, frontal, and transverse internal joint moments. Surface EMG measured activities of 10 lower limb muscles. Partial least squares regressions determined which internal moment(s) were significantly related to the activation of individual muscles. RESULTS: Rectus femoris and tensor fasciae latae were classified as moment actuators for knee extension and hip flexion. Hamstrings were classified as moment actuators for hip extension and knee flexion. Gastrocnemius and hamstring muscles were classified as specific joint stabilizers for knee rotation. Vastii were classified as general joint stabilizers because activation was independent of moment generation. Muscle roles did not change with increasing effort levels. CONCLUSIONS: Our findings indicate muscle activation is not dependent on anatomical orientation but perhaps on its role in maintaining knee joint stability in the frontal and transverse loading planes. This is useful for delineating the roles of biarticular knee joint muscles and could have implications in robotics, musculoskeletal modeling, sports sciences, and rehabilitation.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".