ElectroMap is a novel, open-source software that accurately processes, analyzes, and maps complex cardiac electrophysiology datasets across diverse experimental and clinical models.
ElectroMap is a novel, open-source, high-throughput software that accurately processes and maps complex cardiac electrophysiology data across diverse experimental and clinical modalities.
The ability to record and analyse electrical behaviour across the heart using optical and electrode mapping has revolutionised cardiac research. However, wider uptake of these technologies is constrained by the lack of multi-functional and robustly characterised analysis and mapping software. We present ElectroMap, an adaptable, high-throughput, open-source software for processing, analysis and mapping of complex electrophysiology datasets from diverse experimental models and acquisition modalities. Key innovation is development of standalone module for quantification of conduction velocity, employing multiple methodologies, currently not widely available to researchers. ElectroMap has also been designed to support multiple methodologies for accurate calculation of activation, repolarisation, arrhythmia detection, calcium handling and beat-to-beat heterogeneity. ElectroMap implements automated signal segmentation, ensemble averaging and integrates optogenetic approaches. Here we employ ElectroMap for analysis, mapping and detection of pro-arrhythmic phenomena in silico, in cellulo, animal model and in vivo patient datasets. We anticipate that ElectroMap will accelerate innovative cardiac research and enhance the uptake, application and interpretation of mapping technologies leading to novel approaches for arrhythmia prevention.
O’Shea et al. (Mon,) conducted a other in Cardiac electrophysiology. ElectroMap software vs. Standard analysis methods was evaluated on Validation of electrophysiological parameter quantification (e.g., conduction velocity, action potential duration, calcium decay). ElectroMap is a novel, open-source software that accurately processes, analyzes, and maps complex cardiac electrophysiology datasets across diverse experimental and clinical models.