Abstract Introduction Atrial fibrillation (AFIB) is a common arrhythmia that is prevalent in post-cardiovascular surgery patients. It has been clinically observed Several studies that focused on developing methods to predict AFIB are described in the literature. Many of them In addition to the above-mentioned ECG characteristics, clinical studies The overall goal of our research is to develop PAC based predictors of AFIB by analyzing the occurrences and patterns of PACs over a long duration. These predictors will be developed such that they can be clinically applied to monitor post-surgical patients who have undergone cardiac surgery. To achieve the above goal it is imperative that a method be developed to automatically detect and classify PACs in the ECG. This technique should function reliably and in real-time to be clinically applicable. The current paper describes the development and verification of such a technique. Using this technique it is demonstrated how ECG signals from Cardio-Vascular ICU (CVICU) patients can be analyzed to evaluate the occurrence of PACs before the onset of AFIB. Methods A Premature Atrial Contraction (PAC) is a stimulus from an ectopic atrial site that travels across the atria via atypical pathways. The PAC stimulus precedes the stimulus originating from the SA-node. A PAC that gets propagated through the AV node into the ventricular region thus triggering a ventricular contraction is called
