Assessing effect of beat detector on detection dependent signal quality indices

Abstract

Patient monitoring algorithms which use multimodal physiological waveforms are needed to reduce alarm fatigue by alarming only for physiologic events and not signal artifacts. When combining information from multiple ECG signals, computational approaches that automatically identify artifacts in ECG signals play an important role. Signal quality indices (SQIs) have been derived which can differentiate between ECG signal artifacts and normal QRS morphology. Some of these SQIs are derived using beat detections and might be affected by the beat detector used. Using ECG signals from the PhysioNet/Computing in Cardiology Challenge 2015 training set, we studied the effect of beat detector on previously reported ECG SQIs derived using beat detections. We found that, while being affected by the beat detector, some of these SQIs can predict beat detector failure. Using beat detector specific SQIs can improve the designs of robust monitoring algorithms.