Date of Award


Degree Name

MS in Mechanical Engineering


Mechanical Engineering


College of Agriculture, Food, and Environmental Sciences


Stephen Klisch

Advisor Department

Mechanical Engineering

Advisor College

College of Engineering


Human motion capture technology is a powerful tool for advancing the understanding of human motion biomechanics (Andriacchi and Alexander, 2000). This is most readily accomplished by applying retroreflective markers to a participant’s skin and tracking the position of the markers during motion. Skin and adipose tissue move independently of the underlying bone during motion creating error known as soft tissue artifact (STA), the primary source of error in human motion capture (Leardini et al., 2005).

(Solav et al., 2014) proposed and (Solav et al., 2015) expanded the triangular Cosserat point element (TCPE) method to reduce the effect of STA on derived kinematics through application of a marker cluster analyzed as a set of triangular Cosserat point elements. This method also provides metrics for three different modes of STA.

Here the updated TCPE method (Solav et al., 2015) was compared to the established point cluster (PC) method of (Andriacchi et al., 1998) and the marker position error minimizing Procrustes solution (PS) method of (Söderkvist and Wedin, 1993) in two implant-based simulations, providing quantitative measures of error, and standard gait analysis, providing qualitative comparisons of each method’s determined kinematics. Both of these experiments allowed the TCPE method to generate observed STA parameters, informing the efficacy of the simulation.

The TCPE method’s performance was similar to the PS method’s in the implant simulations and in standard gait. The PC method’s results seemed to be affected by numerical instability: simulation trial errors were larger and standard gait results were only similar to the other methods’ in general terms. While the PS and TCPE results were comparable, the TCPE method’s physiological basis provided the added benefit of non-rigid behavior quantization through its STA parameters. In this study, these parameters were on the same order of v magnitude between the standard gait experiments and the simulations, suggesting that implant simulations could be valuable substitutes when invasive methods are not available.