Characterisation of human AV-nodal properties using a network model

Research output: Contribution to journalArticle


Characterisation of the AV-node is an important step in determining the optimal form of treatment for supraventricular tachycardias. To integrate and analyse patient-specific measurements, mathematical modelling has emerged as a valuable tool. Here we present a model of the human AV-node, consisting of a series of interacting nodes, each with separate dynamics in refractory time and conduction delay. The model is evaluated in several scenarios, including atrial fibrillation (AF) and clinical pacing, using simulated and measured data. The model is able to replicate signals derived from clinical ECG data as well as from invasive measurements, both under AF and pacing. To quantify the uncertainty in parameter estimation, 1000 parameter sets were sampled, showing that model output similar to data corresponds to limited regions in the model parameter space. The model is the first human AV-node model to capture both spatial and temporal dynamics while being efficient enough to allow interactive use on clinical timescales, as well as parameter estimation and uncertainty quantification. As such, it fills a new niche in the current set of published models and forms a valuable tool for both understanding and clinical research.


External organisations
  • Fraunhofer-chalmers Research Centre For Industrial Mathematics
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Medical Laboratory and Measurements Technologies
Original languageEnglish
Pages (from-to)247-259
JournalMedical & Biological Engineering & Computing
Issue number2
Early online date2017
Publication statusPublished - 2018 Feb
Publication categoryResearch

Related projects

Frida Sandberg & Mikael Wallman

Swedish Research Council


Project: Research

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