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).