Complexity Analysis is a subset of Signal Analysis which focuses on chaotic systems and the study of their internal dynamics. Many biomedical systems can be considered as chaotic, and the understanding of their hidden laws has become a topic of interest in literature. Entropy is a tool created to evaluate the complexity of a signal, biomedical or not. Since the introduction of Shannon Entropy in 1948, many Entropy definitions were developed creating a wide set of Entropy-based features being available for Complexity Analysis. This thesis evaluated the performance of these complexity features compared with some linear features, in order to understand whether Entropy can provide a statistically significant improvement to the Analysis of three different databases.