A compact matrix model for atrial electrograms for tissue conductivity estimation

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Finding the hidden parameters of the cardiac electrophysiological model would help to gain more insight on the mechanisms underlying atrial fibrillation, and subsequently, facilitate the diagnosis and treatment of the disease in later stages. In this work, we aim to estimate tissue conductivity from recorded electrograms as an indication of tissue (mal)functioning. To do so, we first develop a simple but effective forward model to replace the computationally intensive reaction-diffusion equations governing the electrical propagation in tissue. Using the simplified model, we present a compact matrix model for electrograms based on conductivity. Subsequently, we exploit the simplicity of the compact model to solve the ill-posed inverse problem of estimating tissue conductivity. The algorithm is demonstrated on simulated data as well as on clinically recorded data. The results show that the model allows to efficiently estimate the conductivity map. In addition, based on the estimated conductivity, realistic electrograms can be regenerated demonstrating the validity of the model.

Original languageEnglish
Pages (from-to)284-291
Number of pages8
JournalComputers in Biology and Medicine
Publication statusPublished - 2019


  • Atrial fibrillation
  • Conductivity estimation
  • Electrode array
  • Electrograms
  • Electrophysiological model
  • Inverse problem
  • Reaction-diffusion equation


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