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In this thesis, important aspects for personalizing atrial simulations have been investigated. First, a minimal electrophysiological cell model has been implemented. It was originally supplied only with parameter sets to reproduce ventricular excitation properties. In the course of this work, the model parameters have been adapted to reproduce atrial properties as given by the Courtemanche-Ramirez-Nattel model. Besides the physiological case, a parameter set for atrial remodeling during chronic AF has been created. Second, the influence of tissue conductivities on simulated electrocardiograms (ECGs) and body surface potential maps (BSPMs) has been evaluated. Finally, patient specific simulations were performed. In summary, it was shown that important limitations in the personalization of atrial models can be overcome with the presented methods. This opens up the possibility for studying atrial model personalization in larger groups of patients. Furthermore, the analysis methods developed for intracardiac electrograms can be directly applied to clinical measurements without additional modeling steps. These results will hopefully lead to a better understanding of the underlying mechanisms and an improvement of the treatment. This way, personalized models could reduce examination times, improve success rates and significantly reduce both the overall treatment costs and most important the patients' burden.