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- BildiriYalnız künye2023An Efficient 1D Autoencoder-Based Approach for R-Peaks Detection in Electrocardiogram Signals
Dogan, Ramazan Ozgur; Dogan, Hulya; Kayikcioglu, Temel
Electrocardiogram (ECG) signal which is composition of multiple segments such as P-wave, QRS complex and T-wave plays a crucial role in evaluating human heart cardiac diagnosis. For an analysis of cardiac diagnosis, it is required that clinicians scan the ECG signal for 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 in the ECG signal with noises and different characteristics, computer-based R-peaks detection approaches have been actively developed in the research article for many years and generally compose of two major operations; preprocessing and decision. Contrary to previous approaches which require high computational costs and complexity, appropriate initial parameters, a novel CNN based approach is presented for R-peaks detection in this paper. Both qualitative and quantitative analysis are performed in the real ECG signal taken from typical MIT-BIH arrhythmia database. In order to validate the success of the recommended approach, total 18 different R-peaks detection approaches reported in the literature are compared by utilizing performance evaluation metrics. Average values of sensitivity, positive predictivity, error rate, accuracy and f-score are computed as 99,96%, 99,95%, 0,09%, 99,90% and 99,95% respectively, which are the best values among well-established studies for R-peaks detection. It is demonstrated with qualitative and quantitative results that better performance is achieved by our suggested approach.
- Derleme MakaleYalnız künye2023A Comprehensive Review of Computer-based Techniques for R-Peaks/QRS Complex Detection in ECG Signal
Dogan, Hulya; Dogan, Ramazan Ozgur
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.