P-wave Detection by the Application of Spatio Temporal Filtering and Statistical Metrics

Cardiovascular diseases are the leading cause of death in the world, and among them Atrial Fibrillation is the most common cardiac arrhythmia affecting up to 2% of the world population.During the early stage of Atrial Fibrillation, the events appear and disappear randomly which makes the diagnosis challenging.Many approaches are based on the R-R variability to perform the mostion of the signal as Atrial Fibrillation, but it is well known the R-R variability is a common feature in most of the arrhythmias and it can lead to a miss-classifications. Instead, Atrial activity (P wave) contains the most relevant information about the atrial conduction, and therefore approaches based on extracting features from P wave are more reliable in the diagnosis of atrial arrhythmias.In this work, a robust methodology for the detection of the P wave is presented.The approach is based on exploiting spatial and temporal information contained in 12-lead ECG when the atrial and ventricular activity is correlated.The result shows a positive predictive value of 100% in the 70% of the cases and a minimum of 90% for a few cases in normal sinus rhythm signals.