title: Analysis of Uncertainty and Variability in Finite Element Computational Models for Biomedical Engineering: Characterization and Propagation.
abstract: Computational modeling has become a powerful tool in biomedical engineering thanks to its potential to simulate coupled systems. However, real parameters are usually not accurately known, and variability is inherent in living organisms. To cope with this, probabilistic tools, statistical analysis and stochastic approaches have been used. This article aims to review the analysis of uncertainty and variability in the context of finite element modeling in biomedical engineering. Characterization techniques and propagation methods are presented, as well as examples of their applications in biomedical finite element simulations. Uncertainty propagation methods, both non-intrusive and intrusive, are described. Finally, pros and cons of the different approaches and their use in the scientific community are presented. This leads us to identify future directions for research and methodological development of uncertainty modeling in biomedical engineering.
authors.affiliation: Simbiosys Group, Universitat Pompeu Fabra , Barcelona , Spain.
authors.forename: Nerea
authors.initials: N
authors.lastname: Mangado
authors.affiliation: Simbiosys Group, Universitat Pompeu Fabra , Barcelona , Spain.
authors.forename: Gemma
authors.initials: G
authors.lastname: Piella
authors.affiliation: Simbiosys Group, Universitat Pompeu Fabra , Barcelona , Spain.
authors.forename: Jérôme
authors.initials: J
authors.lastname: Noailly
authors.affiliation: International Center for Numerical Methods in Engineering (CIMNE) , Barcelona , Spain.
authors.forename: Jordi
authors.initials: J
authors.lastname: Pons-Prats
authors.affiliation: Simbiosys Group, Universitat Pompeu Fabra, Barcelona, Spain; Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain.
authors.forename: Miguel Ángel González
authors.initials: MÁ
authors.lastname: Ballester
keywords: computational modeling; finite element models; intrusive and non-intrusive methods; random variables; sampling techniques; uncertainty quantification