Development and Assessment of a Microcomputed Tomography Compatible Five Degrees-of-Freedom Knee Joint Motion Simulator
Bibliographic record
Abstract
Currently available knee joint kinematic tracking systems fail to nondestructively capture the subtle variation in joint and soft tissue kinematics that occur in native, injured, and reconstructed joint states. Microcomputed tomography (CT) imaging has the potential as a noninvasive, high-resolution kinematic tracking system, but no dynamic simulators exist to take advantage of this. The purpose of this work was to develop and assess a novel micro-CT compatible knee joint simulator to quantify the knee joint's kinematic and kinetic response to clinically (e.g., pivot shift test) and functionally (e.g., gait) relevant loading. The simulator applies closed-loop, load control over four degrees-of-freedom (DOF) (internal/external rotation, varus/valgus rotation, anterior/posterior translation, and compression/distraction), and static control over a fifth degree-of-freedom (flexion/extension). Simulator accuracy (e.g., load error) and repeatability (e.g., coefficient of variation) were assessed with a cylindrical rubber tubing structure and a human cadaveric knee joint by applying clinically and functionally relevant loads along all active axes. Micro-CT images acquired of the joint at a loaded state were then used to calculate joint kinematics. The simulator loaded both the rubber tubing and the cadaveric specimen to within 0.1% of the load target, with an intertrial coefficient of variation below 0.1% for all clinically relevant loading protocols. The resultant kinematics calculated from the acquired images agreed with previously published values, and produced errors of 1.66 mm, 0.90 mm, 4.41 deg, and 1.60 deg with respect to anterior translation, compression, internal rotation, and valgus rotation, respectively. All images were free of artifacts and showed knee joint displacements in response to clinically and functionally loading with isotropic CT image voxel spacing of 0.15 mm. The results of this study demonstrate that the joint-motion simulator is capable of applying accurate, clinically and functionally relevant loads to cadaveric knee joints, concurrent with micro-CT imaging. Nondestructive tracking of bony landmarks allows for the precise calculation of joint kinematics with less error than traditional optical tracking systems.
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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) | 0.001 | 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 | 0.000 | 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".