Movement Optimization Through Musculoskeletal Modeling and Multidimensional Surface Interpolation

Abstract

In an effort to enhance medical decision-making and precision treatment, biomechanical musculoskeletal modeling and computer simulations originating from observations of human movements are being implemented. Such a combination allows for the establishment of cause-and-effect relationships providing a unique, non-invasive method of evaluation into internal joint and muscle force function, as well as athletic performance and neuromuscular coordination. While these are beneficial, current musculoskeletal models lack the ability to give insight into the mechanical stimuli required to prevent physiological deconditioning (i.e., muscle atrophy, bone decalcification, and poor cardiovascular health). This is seen on the International Space Station (ISS) as astronauts still experience deconditioning symptoms even with strict exercise regimes. Therefore, this study overviews the development of a multidimensional surface interpolation, which uses a radial basis function derived from the proper orthogonal decomposition). Inputs to the interpolation scheme are biomechanical responses found by solving an inverse dynamic problem using the ISS’s Advanced Resistive Exercise Device model and simulation within OpenSim. A comparison of 41 lower extremity muscle forces between the interpolation and the static optimization analysis in OpenSim was made. Results highlighted a 1.30% average deviation, with errors concentrated at fluctuating data regions in the minimum force production category. The interpolation scheme shows promise in aiding researchers in the development of an optimized singular exercise movement versus the three exercise machines currently used on the ISS.