The goal of this project has been to develop, execute and implement contractility measurements for the study of mammalian cardiac cells, also known as cardiomyocytes or cardiocytes. This project seeks to examine, question and test existing methods for the assessment of contractility in adult and neonatal cardiocytes. Based on the evaluated designs, strengths, and weaknesses of such methods we have developed two computational frameworks that comprehensively assess contractile responses of isolated cardiocytes. We have developed these methods taking advantage of the technological and computational tools at our disposal. Our methods have been developed in response to the need for an effective method for the analysis of neonatal cardiac myocytes, and the opportunity to develop a novel adult cardiomyocyte method that is comprehensive and takes advantage of existing image analysis techniques. Both of our new approaches have met our expectations; the neonatal cardiocyte method is able to obtain a strong and consistent contractile signal and in the case of the adult cardiocyte methodology, improves signal quality by eliminating possible sources of error and resolves concerns resulting from the application of other more widely used assays. The different components of our two frameworks are variants of well established, mathematically sound, and computationally robust algorithms. The neonatal myocyte contractility assessment methodology uses shape representation by Fourier descriptors with a polar grid to track internal myocyte movements during contraction. Our adult myocyte contractility assessment methodology comprises edge preserving total variation-based image smoothing, segmentation of the smoothed images, contour extraction from the segmented images, shape representation by Fourier descriptors, and assessment of contractility parameters. To complement our developed computational protocols and provide cardiovascular researchers a practical, user friendly product, the neonatal and adult method- ologies have been deployed using Matlab as a platform in the form of two toolboxes. The developed toolboxes simplify the execution, automate, and provide a front-end to the developed computational frameworks. We have developed the software needed to perform the necessary computational manipulations to assess the contraction signals of the cardiocytes. The automation of such steps by the toolboxes allow an expedited processing of large amounts of video and image data. Data analysis routines have been created and tailored exclusively to the characteristics and needs of cellular cardiovascular research investigators. The analytical protocols created are used to nd the onset of contraction, perform signal averaging, and acquire statistical information of functional data. The new methods and tool- boxes have been used to analyze correlations of contractility parameters with changes in the expression of key genes responsible for enhanced contractility (e.g., calcium pathway genes like those for the ryanodine receptor, sodium-calcium exchanger and sarco/endoplasmic reticulum Ca²⁺ATPase). We feel that our developments provide researchers interested in the assessment of contractile activities in cardiomyocytes an opportunity to assess their cells in a relatively inexpensive, practical, and effective manner.