Uncertainty modeling of input data for a biomechanical system of systems

Biomechanical models simulating pathologies need assumptions and often have to deal with data from different sources. We proposed a biomechanical system of systems (BSoS) including two modeling (biomechanics and knowledge-based) approaches to understand the impact of musculoskeletal pathologies leading to propose better diagnosis and appropriate treatment prescription. Moreover, uncertainty of input data was modeled leading to quantify their impact on the simulation results. The architecture of our BSoS including different constituent systems was presented and discussed. Novel knowledge-based fusion p-boxes were developed for uncertainty modeling purpose. Case study was performed on the musculoskeletal simulation. Discussion was addressed.