An Electromyographically Driven Cervical Spine Model in OpenSim
Bibliographic record
Abstract
Relatively few biomechanical models exist aimed at quantifying the mechanical risk factors associated with neck pain. In addition, there is a need to validate spinal-rhythm techniques for inverse dynamics spine models. Therefore, the present investigation was 3-fold: (1) the development of a cervical spine model in OpenSim, (2) a test of a novel spinal-rhythm technique based on minimizing the potential energy in the passive tissues, and (3) comparison of an electromyographically driven approach to estimating compression and shear to other cervical spine models. The authors developed ligament force-deflection and intervertebral joint moment-angle curves from published data. The 218 Hill-type muscle elements, representing 58 muscles, were included and their passive forces validated against in vivo data. Our novel spinal-rhythm technique, based on minimizing the potential energy in the passive tissues, disproportionately assigned motion to the upper cervical spine that was not physiological. Finally, using kinematics and electromyography collected from 8 healthy male volunteers, the authors calculated the compression at C7-T1 as a function of the head-trunk Euler angles. Differences from other models varied from 25.5 to 368.1 N. These differences in forces may result in differences in model geometry, passive components, number of degrees of freedom, or objective functions.
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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 | 0.000 |
| 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".