R-R interval based paroxysmal atrial fibrillation analysis

Detection and classification of Atrial complexes from the ECG is of considerable importance in critical patient care monitoring of dangerous heart conditions. Accurate detection of Paroxysmal Atrial Fibrillation (PAF) using Atrial Premature Complexes(APC) is particularily important in relation to life threatening arrhythmias. PAF is a type of progressive cardiac arrhythmia that poses severe health risks, sometimes leading to ventricular arrhythmia. The electrocardiogram (ECG) data from the PhysioNet Online Database is used to develop a technique to screen, detect, and predict the onset of PAF. By considering a set of feature derived from RR intervals and P wave morphology it is possible to discriminate between PAF patients and healthy individuals. Result demonstrated that feature based on RR intervals is most successful. The RR based algorithm could be incorporated into medical devices with the potential of contributing to new healthcare technology.