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

DOĞAN H., Dogan R. O.

Archives of Computational Methods in Engineering, cilt.30, sa.6, ss.3703-3721, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 30 Sayı: 6
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1007/s11831-023-09916-x
  • Dergi Adı: Archives of Computational Methods in Engineering
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC, MathSciNet, zbMATH, DIALNET
  • Sayfa Sayıları: ss.3703-3721
  • Anahtar Kelimeler: R-peaks detection, QRS complex detection, Electrocardiogram signal, Machine learning, Computer aided diagnosis, Generalization ability, Cardiovascular disease, PEAK DETECTION METHOD, QRS DETECTION, AUTOMATIC DETECTION, WAVELET TRANSFORM, HILBERT TRANSFORM, SHANNON ENERGY, DATABASE, FILTER, WIRELESS, STANDARD
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

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.