A High Fidelity and High Frequency Physical Simulator for Mitral Annulus Kinematics

Thomas W. Secord, Marija Vukicevic, Carter J. Gaulke, Charlie L. Eldredge, Erin I. Westman, Kelly A. Coyne, Drew J. Winkoski, Stephen H. Little

Research output: Contribution to journalArticlepeer-review

Abstract

Cardiovascular medical devices that operate within the heart are subjected to millions of loading cycles that can compromise the structural integrity of the implant over time. Accelerated structural testing is a major challenge in the design of implantable cardiac devices, particularly in the emerging realm of catheter-based devices used to treat conditions like mitral valve regurgitation (MR). In this work, we design a bench-top simulator for accelerated structural testing of devices that operate in or near the mitral valve. We first use four-dimensional computed tomography (4DCT) data to create a molded replica of the mitral valve and identify the most deformation-inducing time points in the cardiac cycle. We then kinematically analyze the motion of the mitral annulus using screw theory and create an electromechanical simulation device that mimics this motion at high frequencies. The final apparatus allows for multiple patient-specific scenarios and accurate closed loop displacement control of the screw-based kinematics of the mitral annulus. The test apparatus operates with less than 1 dB of passband ripple up to its 25.7 Hz bandwidth. The proposed device moves toward a desirable paradigm in accelerated structural testing that is less reliant on computational models, animal models, and high-risk early feasibility clinical trials.

Original languageEnglish (US)
Pages (from-to)708-719
Number of pages12
JournalIEEE Transactions on Medical Robotics and Bionics
Volume4
Issue number3
DOIs
StatePublished - Aug 1 2022

Keywords

  • Cardiology
  • mitral annulus
  • screw theory
  • structural testing

ASJC Scopus subject areas

  • Biomedical Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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