PhysioMEA: Signal processing platform for rate and rhythm analysis of multi-electrode array cardiac electrophysiological recordings

Cardiac organoids serve as a valuable model for studying physiological and pathophysiological processes affecting heart rate and rhythm. Multi-electrode arrays (MEA) are widely used for high-throughput electrophysiological assessments. Despite the widespread use of MEA technology in cardiac research, current analysis tools primarily focus on one dimensional (1D) electrophysiological biomarkers and on average interbeat intervals. We aim to develop innovative algorithms to expand cardiac electrophysiological analysis by enabling standardized biomarker calculation, spatiotemporal biomarker dynamics assessment, and comprehensive beat rate variability (BRV) analysis of cardiac organoids. Electrograms were recorded from spontaneously beating cardiac organoids (n = 15), generated from human-induced pluripotent stem cell-derived cardiomyocytes, using 8 × 8 electrode MEA plates. Novel algorithms were developed for R-, S-, and T-peak detection, as well as advanced two dimensions (2D) electrical signal processing of these biomarkers. All algorithms were implemented on the PhysioMEA platform. Biomarker distributions in cardiac organoids exhibited a high degree of similarity in 1D under basal conditions, as indicated by their coefficients of variation (p-value >0.209). In 2D, R- to S-peaks amplitude, maximal slope, peak-to-peak duration and field potential duration coefficients of variation were 39.04 %, 46.95 %, 22.76 %, and 25.00 %, respectively. Additionally, comprehensive analysis of BRV revealed primarily very low frequency content (63.42 %) in cardiac organoid interbeat interval spectra compared to low- and high-frequency components (15.57 % and 21.02 %, respectively). Thus, 1D and 2D electrophysiological analysis and BRV assessment of cardiac organoids using the open-source PhysioMEA platform, shows high similarities in 1D, but not in 2D, between different physiological biomarkers.