Simulation studies of cardiac arrhythmias at the whole heart level with electrocardiogram (ECG) gives an understanding of how the underlying cell and tissue level changes manifest as rhythm disturbances in the ECG. We present a 2D whole heart model (WHM2D) which can accommodate variations at the cellular level and can generate the ECG waveform. It is shown that, by varying cellular-level parameters like the gap junction conductance (GJC), excitability, action potential duration (APD) and frequency of oscillations of the auto-rhythmic cell in WHM2D a large variety of cardiac arrhythmias can be generated including sinus tachycardia, sinus bradycardia, sinus arrhythmia, sinus pause, junctional rhythm, Wolf Parkinson White syndrome and all types of AV conduction blocks. WHM2D includes key components of the electrical conduction system of the heart like the SA (Sino atrial) node cells, fast conducting intranodal pathways, slow conducting atriovenctricular (AV) node, bundle of His cells, Purkinje network, atrial, and ventricular myocardial cells. SA nodal cells, AV nodal cells, bundle of His cells, and Purkinje cells are represented by the Fitzhugh-Nagumo (FN) model which is a reduced model of the Hodgkin-Huxley neuron model. The atrial and ventricular myocardial cells are modeled by the Aliev-Panfilov (AP) two-variable model proposed for cardiac excitation. WHM2D can prove to be a valuable clinical tool for understanding cardiac arrhythmias.

Heart Rate Variability (HRV) is the subtle beat to beat changes in heart rate. Autonomic Nervous System (ANS) regulates heart rate by controlling the neurotransmitters, mainly Norepinephrine (NE) and Acetyl choline (Ach) from sympathetic and parasympathetic branches respectively. HRV analysis is a noninvasive tool for assessing the integrity of ANS. HRV changes are observed in the onset of heart disease and in a number of disease conditions like sleep apnea, psychiatric disorders, diabetes, hypertension etc. An understanding of the relationship between kinetics at sympathetic and parasympathetic sites and HRV helps to identify biological changes associated with various autonomic imbalance conditions and hence help in targeted diagnosis and therapy. A computational model of ANS for heart rate regulation is proposed in this study. Fitzhugh Nagumo (FHN) model is used as the successive stage of proposed model to generate a discrete time heart beat interval series. HRV data from a group of healthy individuals having balanced sympathetic and parasympathetic activities were studied. The results were in agreement with parameters derived from model synthesized data for the same autonomic state.