Simulation and visual analysis of Neuromusculoskeletal models and data

Abstract

This work presents a novel medical decision support system for diseases related to the upper body neuromusculature. The backbone of the system is a simulation engine able to perform both forward and inverse simulation of upper limb motions. In forward mode neural signals are fed to the muscles that perform the corresponding motion. In the inverse mode, a specified motion trajectory is used as input and the neural signals that are the root cause of this particular motion are estimated and investigated. Due to the vast amount of information that results from even simple simulations, the results are presented to the expert using visual analytics metaphors and in particular both embodied and symbolic visualizations. Several use cases are presented so as to demonstrate the analytics potential of the proposed system.