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Updated: Oct 12, 2025

Creating a Structurally Realistic Finite Element Geometric Model of a Cardiomyocyte to Study the Role of Cellular Architecture in Cardiomyocyte Systems Biology
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Controllability and state feedback control of a cardiac ionic cell model.

Ryan Vogt1, Anthony Guzman2, Clar Charron3

  • 1School of Mathematics, School of Physics and Astronomy, University of Minnesota, Minneapolis, MN, 55455, USA.

Computers in Biology and Medicine
|November 24, 2021
PubMed
Summary

This study assessed the controllability of a higher-dimensional cardiac model to suppress alternans, a precursor to fatal arrhythmias. Perturbations to calcium-ion concentrations were most effective in controlling alternans.

Keywords:
Action potentialCardiac electrophysiologyComputational scienceControl systemsControllabilityElectrical alternansMathematical biosciencesState feedback

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Area of Science:

  • Cardiac Electrophysiology
  • Computational Biology
  • Nonlinear Dynamics

Background:

  • Beat-to-beat alternation in action potential (AP) duration, known as alternans, can precede fatal cardiac arrhythmias.
  • Electrical stimulus protocols can suppress alternans by perturbing cardiac models.
  • Previous controllability analyses primarily used low-dimensional models.

Purpose of the Study:

  • To assess the controllability of a higher-dimensional cardiac model, the Luo Rudy dynamic (LRd) model.
  • To investigate the influence of ionic concentrations on cardiac alternans control.
  • To identify optimal perturbation timings and strategies for suppressing cardiac alternans.

Main Methods:

  • Computed modal controllability measures for a linearized LRd model.
  • Assessed controllability by perturbing various model variables, including calcium-ion concentrations and membrane potential.
  • Developed and simulated alternans-suppressing state feedback controllers.

Main Results:

  • Higher-dimensional models offer insights into the impact of ionic concentrations on controllability.
  • Perturbations to calcium-ion concentrations showed stronger control over larger eigenvalues compared to other variables.
  • Optimal perturbation timing for membrane potential adjustments was near the AP peak for shorter cycle lengths.
  • Controllability results were consistent across default and alternans-promoting parameter sets.
  • Controllability measures accurately predicted the performance of feedback controllers.

Conclusions:

  • Controllability analysis of higher-dimensional models is crucial for understanding cardiac arrhythmia mechanisms.
  • Targeting calcium-ion dynamics offers a promising strategy for suppressing cardiac alternans.
  • The findings support the use of controllability measures to guide the development of effective anti-arrhythmic therapies.