Because of the importance of the medical domain, the combination of health care and advancements in artificial intelligence is a research area of high interest. In this case, deep learning networks are employed to process ECG (Electrocardiography) signals. More precisely, the objective is to investigate what neural networks can learn from a cardiac signal and visualize this representation in the best possible way. The used approach is to look at different autoencoders and decide which architecture is best suited for this task. This work could possibly lay the groundwork to build a classification network with the purpose of detecting the health of patients’ hearts in an automated manner.