title: Enhancing uncertainty tolerance in modelling creep of ligaments.
abstract: The difficulty in performing biomechanical tests and the scarcity of biomechanical experimental databases necessitate extending the current knowledge base to allow efficient modelling using limited data sets. This study suggests a framework to reduce uncertainties in biomechanical systems using limited data sets. The study also shows how sparse data and epistemic input can be exploited using fuzzy logic to represent biomechanical relations. An example application to model collagen fibre recruitment in the medial collateral ligaments during time-dependent deformation under cyclic loading (creep) is presented. The study suggests a quality metric that can be employed to observe and enhance uncertainty tolerance in the modelling process.
authors.affiliation: Department of Civil Engineering, The University of New Mexico, Albuquerque, USA.
authors.forename: M M
authors.initials: MM
authors.lastname: Reda Taha
authors.forename: J
authors.initials: J
authors.lastname: Lucero
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D017143:Fuzzy Logic; D006801:Humans; D008022:Ligaments / Q000033:anatomy & histology* / Q000502:physiology*; D008954:Models, Biological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity