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A Comprehensive Review of Computer-based Techniques for R-Peaks/QRS Complex Detection in ECG Signal

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Abstract

Electrocardiogram (ECG) signal, which is composite of multiple segments such as P-wave, QRS complex and T-wave, plays a crucial role in the treatment of cardiovascular disease. For an analysis of cardiac diagnosis, it is required that clinicians scan the ECG signal for QRS complex or R-peaks (the highest peak of the QRS complex) detection, which relies on their expertise and takes enormous time. In order to provide more realistic treatment of cardiovascular diseases, so many computer-based techniques detecting R-peaks/QRS complex in the ECG signal with noises and different characteristics have been actively developed in research article for many years. Moreover, researchers have created various data sets for R-peaks/QRS complex detection. Although R-peaks/QRS complex detection is one of the notable research areas with so many computer-based techniques and ECG data sets, no comprehensive review paper have been published recently. The main aim of this study is to present a wide range of computer-based techniques proposed for detection of R-peaks/QRS complex. First of all, in this study, computer-based techniques proposed in the literature for the detection of R-peaks/QRS complex and their stages are introduced in detail. The generalization ability of these techniques is investigated deeply. Details are given about the most preferred ECG data sets produced in the literature for the analysis of computer-based techniques. Finally, the performances of computer-based techniques and generalization abilities are analyzed for each data set created in the literature by giving the results of the evaluation metrics.

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  1. Department of Software Engineering, Karadeniz Technical University, Trabzon, Türkiye

    Hulya Dogan

  2. Department of Software Engineering, Gumushane University, Gumushane, Türkiye

    Ramazan Ozgur Dogan

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Dogan, H., Dogan, R.O. A Comprehensive Review of Computer-based Techniques for R-Peaks/QRS Complex Detection in ECG Signal. Arch Computat Methods Eng 30, 3703–3721 (2023). https://doi.org/10.1007/s11831-023-09916-x

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