The ability to quantitatively assess dynamic knee joint stability is a major need among biomechanics researchers, orthopaedic surgeons, and physical therapists. For example, following a tear of the anterior cruciate ligament (ACL), surgeons will often perform a manual examination called the pivot-shift test to evaluate the mechanical stability of the knee. Unfortunately the test qualitative, subjective, and dicult to reproduce. Biomechanics researchers have been developing ways to reproduce the pivot-shift in a laboratory setting. However, current approaches involve the application of mechanical loads that are either static or poorly defined. In addition to manual examinations, observational movement analysis is often used by physical therapists to assess the functional stability of the knee during tasks such as a single leg squat. However, the qualitative and subjective nature of observation makes it dicult to reliably document and monitor patient progress. Researchers can use multi-camera motion capture systems to extract quantitative information from functional tests in a laboratory setting. However, these systems are prohibitively expensive and cumbersome for routine use in the clinic.

In this dissertation we present novel techniques for quantitatively assessing dynamic knee joint stability in laboratory and clinical settings. First, we provide the mathematical foundation for describing knee joint motion (kinematics) and forces and moments (kinetics). This work extends the concept of a non-orthogonal joint coordinate system to include what’s known as the dual Euler basis, which as we show, is particularly useful for representing constraint moments acting at the knee. Next, we present a novel mechanical device for mimicking the pivot-shift test in a laboratory setting. Our device improves upon previous loading devices because it applies knee loads that are dynamic, well-defined, and reproducible to within a 10% tolerance. Using this device, we then compare the ability of several pediatric ACL reconstruction techniques to restore stability to the knee in a cadaveric model. Finally, we present a novel marker-based motion capture technique that leverages low-cost consumer 3D cameras like the Microsoft Kinect. We show that, using this technique, the position of markers placed on the body can be measured with 1-2 cm accuracy and precision. Hopefully the work presented in this dissertation will benefit biomechanics researchers, surgeons, and physical therapists who face the increasingly important problem of quantifying knee joint function and stability