Authors:
Justus Eilers
;
Jonas Chromik
and
Bert Arnrich
Affiliation:
Hasso Plattner Institute, University of Potsdam, Rudolf-Breitscheid-Straße 187, Potsdam, Germany
Keyword(s):
Electrocardiography, QRS Detection, Heart Rate, Heart Rate Variability, Alarm Fatigue.
Abstract:
QRS detectors are used as the most basic processing tool for ECG signals. Thus, there are many situations and signals with a wide range of characteristics in which they shall show great performance. Despite the expected versatility, most of the published QRS detectors are not tested on a diverse dataset. Using 14 databases, 10,000 heartbeats for each different heartbeat type were extracted to show that there are notable performance differences for the tested eight algorithms. Besides the analysis on heartbeat types, this paper also tests the noise resilience regarding different noise combinations. Each of the tested QRS detectors showed significant differences depending on heartbeat type and noise combination. This leads to the conclusion that before choosing a QRS detector, one should consider its use case and test the detector on data representing it. For authors of QRS detectors, this means that every algorithm evaluation should employ a dataset that is as diverse as the one used
in this paper to assess the QRS detector’s performance in an objective and unbiased manner.
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