Stem cell derived cardiomyocytes provide a platform for analysing the effect of different physiological conditions and drugs on the function of cardiac cells in vitro. Typically, the electrical function and calcium exchange of these cells have been studied extensively by traditional measurements of electrophysiology. However, their contractile function has not been as thoroughly characterized. We have previously shown optical flow-based video microscopy to be capable of quantifying the biomechanics of these cells, and signals calculated from the obtained velocity vector fields to be able to characterize genetic cardiac disease. Assessing the connectivity on a multi-cell level, however, requires the estimation of synchronization and propagation of contraction. This analysis is implemented in CellVisus software tool, combining temporal characterization of contraction, spatial analysis of contraction propagation, and generation of biomechanics visualizations. CellVisus uses minimum quadratic difference-based block matching to determine distributions of displacements from subsequent video frames, and different signal processing algorithms to derive signals characterizing the motion related to contraction-relaxation cycle. For measuring the extent of contraction, deformations at each frame are calculated with respect to a pre-contraction reference frame. The time points in which cell culture areas reach defined contraction threshold maximum values indicate synchronization and contraction propagation. The software can generate visual representations of contraction profiles, intensity- and propagation maps, as well as video overlays with quantified data. Video microscopy-based measurement is label-free and non-toxic, making it a feasible option for quantifying stem cell derived cardiomyocyte functionality in long term cultures. The obtained data can be analysed in multiple ways depending on the study and type of culture. Thus far the options for analysis tools have been for specific uses, whereas CellVisus software provides several modes of operation in MATLAB environment. The method can be used as standalone, or to augment traditional cellular electrophysiology measurements.