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Updated: Sep 22, 2025

Electrophysiological Analysis of human Pluripotent Stem Cell-derived Cardiomyocytes hPSC-CMs Using Multi-electrode Arrays MEAs
Published on: May 12, 2017
Cardio PyMEA: A user-friendly, open-source Python application for cardiomyocyte microelectrode array analysis
Christopher S Dunham1, Madelynn E Mackenzie2, Haruko Nakano3
1Department of Chemistry and Biochemistry, University of California, Los Angeles, California, United States of America.
Abstract:
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.
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