DescriptionThe sinoatrial (SA) node, located in the right atrium wall, is the heart's biological pacemaker and determines heart rate due to the generation of repetitive and spontaneous action potentials for rhythmic contractions of pacemaker cells. This rhythm is conducted via the atrioventricular (AV) node of cardiac cells in the myocardium. The funny current (If) and sinoatrial node (SAN), combined with regulation by the sympathetic and parasympathetic nervous systems, modulate the frequency of SAN-generated action potentials. Abnormalities in this system can result in cardiac arrhythmias, including partial block, complete block, tachycardia, bradycardia, and cardiac arrest. Additionally, sinus rhythm, another variety of arrhythmia, is considered normal and is defined as heart rate variability (HRV). HRV is of current interest in cardiology due to its possible value as a diagnostic indicator of the cardiac system. Notably, the dynamic beat-to-beat changes in the heart rate often precede the more fatal rhythms of tachycardia and fibrillation. Noble has developed a cellular model for a single cardiac pacemaker cell. While the Noble model successfully modeled pacemaker activity, it does not exhibit HRV or any arrhythmia by itself. Further research suggests that HRV arises from parasympathetic and sympathetic neural action on the SA pacemaker, although this concept does not explain the different varieties of arrhythmia. Currently, a single model that generally represents an array of known arrhythmia does not exist. The ideas proposed in this thesis convey multiple pacemaker cell interactions that may explain many known arrhythmias. To achieve this, this thesis studies the problem of arrhythmia by developing a computational model of dual Noble pacemaker cells that are capable of interacting with one another. All computations resulted in a MATLAB model of cell-to-cell pacemaker interaction, in which cellular parameters were adjusted to reveal the various block arrhythmias and HRV. Comparisons with natural human data pertaining to HRV were related to the standard mean R-R value measured from the generated model data. Furthermore, Fourier spectrum analysis of HRV and heart rate dynamics were presented in the form of delay plots and depicted in a bifurcation plot. The results obtained through this thesis, including results for both HRV and various types of arrhythmia, were compared to the effects of previous works and validated. It was concluded that a dual auto-arrhythmic cell interaction model could model all fatal cardiac arrhythmias and HRV. In particular, the cell-to-cell coupling was valuable in creating the various rhythms. The model developed in this thesis can be useful in providing more detailed diagnostic information of human cardiac rhythm data at the cellular level.