Data Archive

Data collected by the consortium will be curated by the Center for Integrative Biomedical Computing at the University of Utah and stored for easy access in the EDGAR database. Datasets are all open-access and will be available to all registered users of the database. Registration is free.

Connect to EDGAR database.

For additional information regarding access to, and structure of, the EDGAR database, please refer to the following documents.

Demo: New EDGAR interface (Presented at CinC 2016)

The EDGAR framework

New to EDGAR? Read the manual here.

Don't forget to cite the EDGAR paper!

Aras, Kedar & Good, Wilson & Tate, Jess & Burton, Brett & Brooks, Dana & Coll-Font, Jaume & Doessel, Olaf & Schulze, Walther H W & Potyagaylo, Danila & Wang, Linwei & Dam, Peter & MacLeod, Rob. (2015). Experimental Data and Geometric Analysis Repository-EDGAR. Journal of electrocardiology. 48. https://doi.org/10.1016/j.jelectrocard.2015.08.008


The EDGAR database is free and open to the public. All we ask is that proper acknowledgement be given to the groups and individuals whose efforts led to the creation and dissemination of such unique datasets. For convenience, technical summaries of some of the dataset and corresponding acknowledgement statements are listed below.

  • Liryc/Bordeaux Torso Tank experiments

    • Technical Summary: Torso tank and epicardial ventricular sock recordings of RV paced, LV paced, and sinus rhythm after LBBB induction through ablation. Geometries were generated from MRI of the tank.

    • Acknowledgments: These experiments were performed by the Electrophysiology and Heart Modeling Institute (IHU-LIRYC) at the Université de Bordeaux with funding from La fondation Coeur et Artères (FCA14T2), the French National Research Agency 4 (ANR-10-IAHU04-LIRYC), and the Leducq foundation transatlantic network of excellence RHYTHM.

  • Bratislava Human Mapping Data

    • Technical Summary: Torso recordings and MRI geometries of the heart, lungs, and torso. Signals recorded during apex pacing and spontaneous PVCs. Patient 56 years old male with cardiostimulator and spontateous ventricular extrasystoles after large anterior myocardial infarction.

    • Acknowledgments: The data were recorded within the cooperation of the laboratory of Biomeasurements, Institute of Measurement Science, Slovak Academy of Sciences, Bratislava with the National Institute for Cardiovascular Diseases, Bratislava, Slovakia.

  • CVRTI/Utah Torso Tank experiments

    • Technical Summary: Torso tank experiment where potentials are simultaneously recorded transmurally, epicardially, and on the torso tank itself. The heart was paced from the high right atrium while ischemia was induced via an occlusion to the LAD.

    • Acknowledgment: These experiments were performed by the Cardiovascular Research and Training Institute (CVRTI) and the Scientific Computing and Imaging (SCI) Institute at the University of Utah with funding from the Nora Eccles Treadwell foundation and the NIH/NIGMS Center of Integrative Biomedical Computing under grant P41 GM103545-17.

  • KIT/Karlsruhe, Germany simulation data

    • Technical Summary: Six (6) datasets are available in the KIT repository. Five (5) datasets provide results from simulated forward simulation results from paced ventricular beats on a human patient model. Sources for these simulations are transmembrane voltages. In the simplified models for inverse calculations the sources are represented as:: A) extracellular potential source on the pericardium only, B) extracellular potential source on the pericardial and endocardial surfaces, C) transmembrane voltage source on the pericardial and endocardial surfaces, and D) transmembrane voltage source throughout FEM heart mesh. The sixth study provides clinical data from 63 BSPM electrodes as recorded during ablation procedure to provide known PVC recordings. Paced beats from a catheter were also recorded.

    • Acknowledgment: These studies were performed in a joint research project between the First Department of Medicine (Cardiology), University Medical Centre Mannheim and the Karlsruhe Institute of Technology (KIT). For the simulation study, please refer to the handout at http://doi.org/10.13140/RG.2.1.1946.8568.

  • Petr Stovicek (Charles University)/Prague human mapping data

    • Technical Summary: Three (3) datasets are available in the Charles University repository. Each contains clinical data from pacing localization experiments consisting of a series of body surface recordings acquired during endocardial pacing at various CARTO locations of healthy patient ventricles.

    • Acknowledgment: The authors also gratefully acknowledge the data collection performed by Petr Štovíćek, Š. Havránek and J. Šimek, from the Second Department of Medicine—Department of Cardiovascular Medicine, First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Czech Republic, as well as D. Wichterle, from the Department of Cardiology, Institute for Clinical and Experimental Medicine-IKEM, Prague, Czech Republic.

  • Maastricht University, Netherlands Dog epicardial/torso mapping data

    • Technical Summary: Simultaneously recorded body-surface potentials and epicardial potentials. Dataset contains a sinus beat and a paced beat (paced from the epicardial left ventricular apex). A geometry, consisting of the body-surface electrodes and the epicardial surface, was extracted from a CT scan obtained just before the potential data were acquired.

    • Acknowledgement: This dataset was provided by Maastricht University in collaboration with Paul Volders, Ralf Peeters, Ronald Westra, JoÎl Karel, Pietro Bonizzi, Monique de Jong, Frits Prinzen, Lars van Middendorp, Marc Strik, Marion Kuiper, Sophie Bosch, Rob Wiegerinck, Marco Das, and Bas Kietselaer. Please cite: Cluitmans, M. J.; de Jong, M. M.; Volders, P. G.; Peeters, R. L. & Westra, R. L. Physiology-based Regularization Improves Noninvasive Reconstruction and Localization of Cardiac Electrical Activity. Computing in Cardiology, 2014, 41, 1-4.

  • Dalhousie University body surface mapping data

    • Technical Summary: Body surface mapping (BSPM) and endocardial catheter recordings of paced beats. Multiple pacing sites were tested. In addition to BSPM, bipolar amplitudes and activation times recorded from the endocardium are available. Geometries were generated from CT of the patient.

    • Acknowledgement: This dataset was made available by John Sapp and Milan Horáček and their research collaboration from Dalhousie University. Please cite the following paper: Inverse Solution Mapping of Epicardial Potentials: Quantitative Comparison With Epicardial Contact Mapping. John L. Sapp, Fady Dawoud, John C. Clements, and B. Milan Horáček. Circ Arrhythm Electrophysiol. 2012;5:1001-1009, doi:10.1161/CIRCEP.111.970160. url: http://circep.ahajournals.org/content/5/5/1001.long.

  • Auckland University pig mapping data

    • Technical Summary: Simultaneous torso and cardiac surface recordings in a pig. An epicardial sock, endocardial catheter recordings, and body surface recordings during sinus and epicardial pacing.

    • Acknowledgement: This dataset was made available by Laura Bear and Bruce Smaill and their research group at Auckland University. Please cite: Bear, L. R., Cheng, L. K., LeGrice, I. J., Sands, G. B., Lever, N. A., Paterson, D. J., & Smaill, B. H. (2015). Forward Problem of Electrocardiography. Circulation: Arrhythmia and Electrophysiology, 8(3), 677ñ684. doi:10.1161/CIRCEP.114.001573.

  • Valencia Polytechnic University human atrial fibrillation mapping with body surface mapping.

    • Technical Summary: Two datasets of simultaneous atrial endocardial recordings and body surface mapping in atrial fibrillation patients. Adenosine was used to suppress ventricular activity during recordings.

    • Acknowledgement: This dataset made available by researchers at the Hospital General Universitario Gregorio Marañón, Madrid, Spain, and the Universitat Politècnica de València, Valencia, Spain. Please cite: Pedrón Torrecilla J, et al. Noninvasive Estimation of Epicardial Dominant High Frequency Regions during Atrial Fibrillation. J Cardiovasc Electrophysiol 2016.

  • Valencia Polytechnic University atrial fibrillation simulation.

    • Technical Summary: Simulated endocardial potentials during atrial fibrillation with and without fibrosis with simulated body surface potentials.

    • Acknowledgement: Supported in part by: Instituto de Salud CarlosIII (Ministry of Economy and Competitiveness, Spain PI12/00993-00407; PI13-01882, PI13-00903 and PI14/00857); Spanish Society of Cardiology (Grant for Clinical Research in Cardiology 2015) Please cite: Pedrón Torrecilla J, et al. Noninvasive Estimation of Epicardial Dominant High Frequency Regions during Atrial Fibrillation. J Cardiovasc Electrophysiol 2016.

  • Nijmegen University human body surface mapping with and without MEG room shielding.

    • Technical Summary: A patient body surface mapping protocol recording in a normal noisy room and in an MEG shielded room.

    • Acknowledgement: This data has been contributed by the University of Nijmegen.