Detection of atrial persistent rhythm based on P-wave recognition and RR interval variability

In order to improve a classification system for arrhythmia analysis, we developed an algorithm for automatic detection of ventricular response to atrial flutter and fibrillation episodes. As an intermediate step to differentiate these rhythms from the normal, the algorithm detects the presence of sinus P-waves, by analyzing single lead ECG. When P-waves are detected for six successive beats, the rhythm is labeled as normal. If this detection fails, the mean RR interval is computed and analyzed. The rhythm is labelled atrial fibrillation when the mean is between two thresholds. The algorithm identifies as atrial flutter, epochs with high cardiac frequency and low variability. All other rhythms are labeled as abnormal, requiring posterior QRS shape analysis for correct classification. The algorithm was tested with the MIT-BIH Arrhythmia Database.