A novel QRS complex detection algorithm combining two methods achieved 99.22% sensitivity and 99.73% positive predictivity when tested on the MIT/BIH Arrhythmia Database.
A QRS complex detection algorithm was developed using the available leads of the electrocardiogram (ECG). This detector is based on the combination of two improved versions of QRS detectors available in the literature. An important characteristic of this algorithm is the possibility of using two or more ECG channels for QRS detection. The first detection method is based on a cross number in a detection threshold defined by the authors. When a low reliability situation occurs in the first method, the output of the second detection method is used to confirm or reject the detection. The second method also uses an adaptive detection threshold defined by the authors and a candidate QRS is tested against some criteria that use features as amplitude, width and RR interval to validate the candidate as a QRS. Testing the algorithm with MIT/BIH Arrhythmia Database resulted in 99.22% sensitivity and 99.73% positive predictivity.
Moraes et al. (Wed,) conducted a other in Arrhythmia. QRS complex detection algorithm was evaluated on Sensitivity and positive predictivity for QRS detection. A novel QRS complex detection algorithm combining two methods achieved 99.22% sensitivity and 99.73% positive predictivity when tested on the MIT/BIH Arrhythmia Database.