Representation methods for cardiac motility were developed in this study. We estimated some parameters which have cardiac feature to model with an innovative scheme. The parameterized super quadric model to visualize the motion of a left ventricle was implemented with OpenGL and Visual C++. Myocardial wall thickening was displayed with super-ellipsoidal model. The measured count for thickening was changed as time frames in this model. And motility was parameterized additionally in the parameterized super quadric model. We made an experiment on analyzing the motility of left ventricle myocardium. The criterion was tested in the validation study in 7 normal subjects and 26 patients with prior myocardial infarction. In order to analyze the motility, we used mean and variance of the total motion during cardiac cycle. The average of normal subject has 0.46 and variance has 0.02. In the case of patients, the average and variance of motility has 0.59 and 0.08 respectively. Although the average value didn’t have the difference between normal and abnormal, the variance had them. In general, patients were 0.08 and normal subjects were 0.02 in variance. The difference between normal subjects and abnormal subjects was estimated. In abnormal subject, the motility was 128% higher than normal subject. The variance was also 328% high. In the patient study, the quantity of motion is decreased rapidly in stressed states. In the visualization for contractility, fifteen segment variables were displayed. The locations of all point could be rotation with mouse interface. The most of factors were visualized for cardiac motility and cardiac features. We expect that this model distinguishes between normal subjects and abnormal subjects. And an exact analysis of momentum utilizing this model could be evaluated.