Deciphering the "Art" in Modeling and Simulation of the Knee Joint: Variations in Model Development. Academic Article uri icon

Overview

abstract

  • The use of computational modeling to investigate knee joint biomechanics has increased exponentially over the last few decades. Developing computational models is a creative process where decisions have to be made, subject to the modelers' knowledge and previous experiences, resulting in the "art" of modeling. The long-term goal of the KneeHub project is to understand the influence of subjective decisions on the final outcomes and the reproducibility of computational knee joint models. In this paper, we report on the model development phase of this project, investigating model development decisions and deviations from initial modeling plans. Five teams developed computational knee joint models from the same dataset, and we compared each teams' initial uncalibrated models and their model development workflows. Variations in the software tools and modeling approaches were found, resulting in differences such as the representation of the anatomical knee joint structures in the model. The teams consistently defined the boundary conditions and used the same anatomical coordinate system convention. However, deviations in the anatomical landmarks used to define the coordinate systems were present, resulting in a large spread in the kinematic outputs of the uncalibrated models. The reported differences and similarities in model development and simulation presented here illustrate the importance of the "art" of modeling and how subjective decision-making can lead to variation in model outputs. All teams deviated from their initial modeling plans, indicating that model development is a flexible process and difficult to plan in advance, even for experienced teams.

publication date

  • June 1, 2021

Research

keywords

  • Knee Joint

Identity

PubMed Central ID

  • PMC8086182

Scopus Document Identifier

  • 85102577030

Digital Object Identifier (DOI)

  • 10.1115/1.4050028

PubMed ID

  • 33537727

Additional Document Info

volume

  • 143

issue

  • 6