18
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Analysis of Uncertainty and Variability in Finite Element Computational Models for Biomedical Engineering: Characterization and Propagation

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          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.

          Related collections

          Most cited references99

          • Record: found
          • Abstract: not found
          • Article: not found

          Level Set Methods: An Overview and Some Recent Results

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Genetic algorithms: a survey

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Galerkin methods for linear and nonlinear elliptic stochastic partial differential equations

                Bookmark

                Author and article information

                Contributors
                URI : http://frontiersin.org/people/u/377113
                URI : http://frontiersin.org/people/u/383139
                URI : http://frontiersin.org/people/u/59318
                URI : http://frontiersin.org/people/u/387469
                URI : http://frontiersin.org/people/u/215634
                Journal
                Front Bioeng Biotechnol
                Front Bioeng Biotechnol
                Front. Bioeng. Biotechnol.
                Frontiers in Bioengineering and Biotechnology
                Frontiers Media S.A.
                2296-4185
                07 November 2016
                2016
                : 4
                : 85
                Affiliations
                [1] 1Simbiosys Group, Universitat Pompeu Fabra , Barcelona, Spain
                [2] 2International Center for Numerical Methods in Engineering (CIMNE) , Barcelona, Spain
                [3] 3Catalan Institution for Research and Advanced Studies (ICREA) , Barcelona, Spain
                Author notes

                Edited by: Tien Tuan Dao, University of Technology of Compiègne, France

                Reviewed by: Henrique De Amorim Almeida, Polytechnic Institute of Leiria, Portugal; André P. G. Castro, University of Sheffield, UK; Emiliano Votta, Politecnico di Milano, Italy

                *Correspondence: Nerea Mangado, nerea.mangado@ 123456upf.edu

                Specialty section: This article was submitted to Biomechanics, a section of the journal Frontiers in Bioengineering and Biotechnology

                Article
                10.3389/fbioe.2016.00085
                5097915
                0b8c0fe4-8ca0-4e66-b34d-61a7f97b0d6a
                Copyright © 2016 Mangado, Piella, Noailly, Pons-Prats and González Ballester.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 09 September 2016
                : 19 October 2016
                Page count
                Figures: 7, Tables: 2, Equations: 6, References: 129, Pages: 17, Words: 13677
                Categories
                Bioengineering and Biotechnology
                Review

                uncertainty quantification,finite element models,random variables,intrusive and non-intrusive methods,sampling techniques,computational modeling

                Comments

                Comment on this article