(Associate Professor Michael Skipper Andersen, Aalborg University, Denmark, 07. April, 2021 )
Ligaments are important joint stabilizers but assessing their mechanical properties remain challenging. In vivo, the mechanical properties cannot be measured directly and, therefore, have to be estimated from indirect measurements. A common approach to this end is to perform laxity tests on the knee, e.g. anterior and posterior drawer, varus/valgus and internal/external rotation tests and record the knee kinematics under these externally applied loads. By utilizing computation knee models, the ligament properties of the knee model are optimized until the laxity profile of the model matches the measured laxity profile and hereby estimates of the ligament properties are obtained. However, when performing the laxity tests, measurement uncertainties will arise both in the measured kinematics as well as in the applied forces and moments.
In this webcast, Associate Professor Michael Skipper Andersen from Aalborg University will present a methodology to investigate the effects of kinematic measurement uncertainty during laxity tests on optimization-based estimates of ligament properties. We will apply this methodology to a subject-specific knee model with known ligament properties on which we virtually perform laxity tests to obtain noise free knee laxity profiles. To the resulting laxity profile, we add random kinematic noise and estimate the ligament properties from the noisy data. These estimates are then compared to the known knee ligament properties that were input to the model and the effects of the kinematic noise on the estimated ligament properties can hereby be quantified.