Open source analytical software for the analysis of electrophysiological cardiomyocyte data offers a variety of new functionalities to complement closed-source, proprietary tools. Here, we present the Cardio PyMEA application, a free, modifiable, and open source program for the analysis of microelectrode array (MEA) data obtained from cardiomyocyte cultures. Major software capabilities include: beat detection; pacemaker origin estimation; beat amplitude and interval; local activation time, upstroke velocity, and conduction velocity; analysis of cardiomyocyte property-distance relationships; and robust power law analysis of pacemaker spatiotemporal instability. Cardio PyMEA was written entirely in Python 3 to provide an accessible, integrated workflow that possesses a user-friendly graphical user interface (GUI) written in PyQt5 to allow for performant, cross-platform utilization. This application makes use of object-oriented programming (OOP) principles to facilitate the relatively straightforward incorporation of custom functionalities, e.g. power law analysis, that suit the needs of the user. Cardio PyMEA is available as an open source application under the terms of the GNU General Public License (GPL). The source code for Cardio PyMEA can be downloaded from Github at the following repository: https://github.com/csdunhamUC/cardio_pymea.

Full MEA recordings and program executables for Windows 10 and Linux 5.16.16 can be found at this Box repository: https://ucla.box.com/s/vf13vjt8exxbqrsi96cd2wqkrk6otkn3. Use of the executables is not recommended; it is best to run cardio_pymea.py from the terminal and to use the Github file versions. Cardio PyMEA runs on MacOS when executed via terminal using the source files provided on Github.Funding provided by: National Institutes of HealthCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000002Award Number: R21HL124503

Dataset was collected in the manner described in the manuscript.