Patient-specific model of atrial fibrillation

WATCH: Patient-specific model of atrial fibrillation


Programme Director
Professor Nicholas Peters
+44 (0)20 7594 1880

Explore our publications

What we do

The ElectroCardioMaths programme of the BHF Centre of Research Excellence is an interdisciplinary initiative bringing together research leaders from clinical electrophysiology, biological sciences and physical sciences to address key challenges in the diagnosis and treatment of cardiac rhythm disturbances. The diverse nature of the group enables a distinctive multi-faceted approach to addressing these problems, providing unique insight into the initiation and perpetuation of arrhythmias and subsequently the development of novel theraputic solutions. 

How it can benefit patients

The programme spans an integrated spectrum of research, translating novel mathematical, engineering and biological techniques into improvements in clinical practice and patient care. With extensive combined expertise in medical imaging, computational modelling, signal processing, data analysis and a range of cell-scale and tissue-scale laboratory techniques, the ElectroCardioMaths programme is able to deliver a true “chip to cell to bedside” approach.

Current research topics include:

  • understanding the structural and functional relationships in myocardium, by integrating in-vivo, ex-vivo, in-vitro and in-silico approaches;
  • analysing and modelling the morphology of the extracellular electrogram and its connection to the electrophysiological activity in the underlying tissue;
  • using cutting-edge numerics to develop high-performance computer models of the heart, personalised through the integration of electroanatomic and imaging data, to aid diagnosis and improve the accuracy of intervention;
  • design and implement novel algorithms for analysing the spatiotemporal dynamics of action potential propagation using optical mapping and electro-anatomic data modalities;
  • create novel approaches for analysing electro-anatomic and imaging data to support interpretation and clinical diagnosis.

A cross-faculty research group

The group includes academics from the NHLIDepartment of BioengineeringDepartment of AeronauticsDepartment of ComputingDepartment of Physics and the Data Science Institute. Read more about them and their individual work below: