Backgrounds and aims: Rapid atrial arrhythmias such as atrial tachycardia and atrial fibrillation (AF) predispose to ventricular arrhythmias, sudden cardiac death and stroke (1). Associated with ectopic and re-entrant activity, the presence of such arrhythmias is reflected in alteration to the P-wave morphology (PWM). Identifying the origin of ectopic atrial activity from a more complete electrocardiogram (ECG) lead configuration can help to diagnose the early onset of AF in a cost effective manner (2). In this study we developed a new algorithm, from a biophysically detailed computational model of the human atria and torso, to investigate the correlation between PWM and origins of atrial ectopic activity.Methods: We apply a recently developed 3D human atrial model (3) to simulate electrical activity during normal sinus rhythm and ectopic pacing. The atrial model is placed into a newly developed torso model, taken from the visible human dataset with consideration for the lungs, liver and spinal cord. A boundary element method is used to compute the body-surface potential (BSP) resulting from atrial excitation. Elements of the torso mesh corresponding to the locations of the electrode placement are selected to simulate 12 and 64 ECG systems. PWM associated with ectopic activity from a variety of regions throughout the atria were analysed. An algorithm to obtain the location of the stimulus from a 64 lead ECG system was developed.Results: During sinus rhythm, the simulated P-waves of 12 and 64 leads ECG and BSP dipole direction show strong agreement with experimental data. Marked changes in PWM are associated with ectopic atrial activity, with some areas of the torso being more sensitive to specific activity than others. The success rate of the algorithm was 93%.Conclusion: Our simulation data suggested that atrial ectopic activity can be reflected in changes of PWM. This study established a correlation between PWM and ectopic activity. An algorithm to identify the location of this ectopic activity has been developed, with 93% accuracy.