Recent advancement of sensing technology has fueled increasing interests in the development of cardiac monitoring systems. However, existing devices are limited in their ability to effectively characterize different disease patterns in a 3D way. An ECG sensing device with high visualizability can assist in the decision-making process of cardiovascular disease treatments. In this undergraduate project, we designed and developed a new device to characterize and visualize single-channel ECG signals in a 3D LED cube. Collected signals are processed using signal processing techniques, e.g., smoothing, gradient, and Laplacian. Processed signals are then used as inputs to control the hue, saturation and brightness of LEDs in a 3D LED cube. As such, disease characteristics of ECG signals are dynamically represented by colored patterns in the LED cube. This device shows strong potentials to increase the visibility and interpretability of information pertinent to the underlying complex cardiac activity.