
doi: 10.1007/bf00770885
pmid: 3819797
In this article we present the choices that the designers of any QRS detector must make and explain the constraints we adopted. We outline the signal processing that precedes and the beat analysis that follows QRS detection in our single-channel, arrhythmia-monitoring algorithm and then expound the QRS detection algorithm in detail. Finally, we present the results of a QRS detector performance evaluation and comment on their importance. This article can be read to three depths: the text affords an overview of QRS detection for on-patient, ambulatory arrhythmia analysis; the commented pseudocode documents the logic of our QRS detector; and the pseudocode "footnotes" supply technical detail.
Electrocardiography, Software Design, Humans, Arrhythmias, Cardiac, Algorithms, Decision Making, Computer-Assisted, Monitoring, Physiologic
Electrocardiography, Software Design, Humans, Arrhythmias, Cardiac, Algorithms, Decision Making, Computer-Assisted, Monitoring, Physiologic
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
