Experimental validation of a computational knee model of TKR implant placement

Aaron Henry, Gordon Goodchild, Jon Greenwald, Morteza Meftah, Michael Moreno, Andrew Robbins

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The goal of this work was to experimentally validate a computational model for TKRs to improve implant alignment accuracy and assess potential implant misalignment during preoperative planning. Initial validation of the model was achieved by comparing ligament strain energies between the computational model and a physical knee model comprised of bone and ligament analogues. Experimental validation would be considered met when the computational model strain energies were within 10% of the measured values for all six physical knees. Physical and computational knee models were created with six variations of implant alignment to test the robustness of the computational model. Strain energy errors were well within the 10% threshold across knee range of motion.

Original languageEnglish (US)
Title of host publicationProceedings of the 2023 Design of Medical Devices Conference, DMD 2023
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791886731
DOIs
StatePublished - 2023
Event2023 Design of Medical Devices Conference, DMD 2023 - Minneapolis, United States
Duration: Apr 17 2023Apr 21 2023

Publication series

NameProceedings of the 2023 Design of Medical Devices Conference, DMD 2023

Conference

Conference2023 Design of Medical Devices Conference, DMD 2023
Country/TerritoryUnited States
CityMinneapolis
Period4/17/234/21/23

Keywords

  • Arthroplasty
  • Computational model
  • Knee

ASJC Scopus subject areas

  • Biomedical Engineering
  • Medicine (miscellaneous)

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