In this paper, the viability of a second order system to characterize the oscillatory behavior of human heart of atrial fibrillation patient was monitored and analysed. Sampling were patients who experienced atrial fibrillation. This study used the MIT-BIH Atrial Fibrillation dataset (MIT-afdb) from the Physiobank ECG database. ECG recordings of normal sinus rhythm (N) and atrial fibrillation (AF) which occurred sequentially, were analyzed for both ECG's Lead I and Lead II. From here, the oscillatory behavior of human heart was characterized in accordance to the extracted parameters for each rhythm, i.e. natural frequency, damping coefficient and forcing input from the second order system. Results show that there were significant differences in mean value of natural frequency (�), ratios of natural frequency to damping coefficient (�/ζ), derivative of the natural frequency with respect to time (d�/dt) and derivative of the forcing input with respect to time (d�/dt), between N and AF from Lead I (P < 0.01). Each parameter provides more than 95 accuracy using artificial neural networks. © Springer International Publishing Switzerland 2015.