Investigating Arrhythmias using ecgAUTO software

In this application note, we explore a few studies conducted in 2024 and using ecgAUTO software for automated ECG data analysis, aiming to enhance our understanding of arrhythmias and develop targeted interventions:

• Ferrand, M.C., et al. (2024). Intracardiac electrophysiology to characterize susceptibility to ventricular arrhythmias in murine models. Front. Physiol. 15; https://doi.org/10.3389/fphys.2024.1326663
• Gandon-Renard, M., et al. (2024). Dual effect of cardiac FKBP12.6 overexpression on excitation-contraction coupling and the incidence of ventricular arrhythmia depending on its expression level. Journal of Molecular and Cellular Cardiology, Volume 188, Pages 15-29
• Nyman, M., et al. (2024). A comprehensive protocol combining in vivo and ex vivo electrophysiological experiments in an arrhythmogenic animal model. Heart and Circulatory Physiology, 326(1): H203-H215
• Selvakumar, D., et al. (2024). Cellular heterogeneity of pluripotent stem cell-derived cardiomyocyte grafts is mechanistically linked to treatable arrhythmias. Nature Cardiovascular Research, 3: 145-165