We believe that strong prior models are a pre-requisite for reliable spatio-temporal cardiac image analysis. While several cardiac models have been presented in the past, many of them are either too complex for their parameters to be estimated on the sole basis of MR Images, or overly simplified. In this paper, we present a novel bio-inspired dynamic model, based on the equation of dynamics for elastic materials. The explicit use of dynamics allows us to enforce periodicity and temporal smoothness constraints. We study two different methods for solving the resulting equations, and show them to be equivalent. We show how temporal filtering can help to remove noise and ensure the periodicity and smoothness of solutions. Finally, we show some results in 1D and on a synthetic model to illustrate the benefits of our new dynamic model and to show how it can be used to analyze cardiac MR images.