Motion analysis method for determining cardiomyocyte beating properties based on digital image correlation and templates

Video-based analysis of cardiomyocytes provides a non-invasive and label-free method of analyzing their beating characteristics. Here, we aim to demonstrate that defining averaged signal templates can improve the determination of cardiomyocyte beating characteristics. Video recordings of human iPSC derived cardiomyocytes were performed Beating patterns from different sectors of the cell were calculated from displacement vector fields using our in-house developed digital image correlation based video analysis method. A cross-correlation template based average waveform was computed for individual cell sectors, representing their beating characteristics. We also studied the effect of video sampling frequency and video duration on template formation to optimize the recording process. By comparing the average waveforms from different sectors, we observed the fusiform nature of iPSC derived cardiomyocytes. Our results indicate that using templates allows minimizing measurement time. However, then the sampling frequency should be at least 60 Hz, for high quality single cell dynamics. To conclude, the sector approach is beneficial for analysis of iPSC derived cardiomyocytes. Also, the presented methods improve the parameterization of the signal.