Detection of false arrhythmia alarms with emphasis on ventricular tachycardia

Our approach to detecting false arrhythmia alarms in the intensive care unit breaks down into several tasks. It involves beat detection on different signals: electrocardiogram, photoplethysmogram and arterial blood pressure. The quality of each channel has to be estimated in order to evaluate the reliability of obtained beat detections. The information about the heart rate from the different channels must be integrated in order to find a final conclusion. Some alarm types require particular detectors as is the case of ventricular fibrillation. To identify false ventricular tachycardia alarms we needed to classify heart beats as normal/ventricular. For that purpose we introduce a new feature, QRS polarity type. This feature was important in order to reduce misclassification of ventricular beats: there was an improvement in the ventricular tachycardia alarm true positive rate from 69% to 81%. However, the true negative rate was reduced from 95% to 69% and our global challenge score (real-time event) dropped from 79.02 to 74.28. Our challenge algorithm achieved the third best score in the 2015 PhysioNet/CinC challenge event 1 (real time).