Neuromechanics

Cadaver Knee Movement Simulator

Knee ligament injury is among the most common sports injuries and is associated with long recovery periods and low return to-sport rates. Unfortunately, the mechanics of ligament injury are difficult to study in vivo, and computational studies provide limited insight. The objective of this study was to implement and validate a robotic system capable of reproducing natural six degree-of-freedom clamped-kinematic trajectories on human cadaver knees (meaning that positions and orientations are rigidly controlled and resultant loads are measured). To accomplish this, we leveraged the field’s recent access to high-fidelity bone kinematics from dynamic biplanar radiography (DBR), and implemented these kinematics in a coordinate frame built around the knee’s natural flexion–extension axis. We assessed our system’s capabilities in the context of ACL injury, by moving seven cadaveric knee specimens through kinematics derived from walking, running, drop jump, and ACL injury. We then used robotically simulated clinical stability tests to evaluate the hypothesis that knee stability would be only reduced by the motions intended to injure the knee.

• Project Lead: Ophelie Herve
• Surgical Collaborator: Drs. David McAllister and Thomas Kremen (Orthopaedic Surgery, UCLA)
• Project Team: Will Flanagan, Sean Thomas, Jake Kanetis (Alumnus), Bailey Mooney (Alumnus)