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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-fc366354-e545-4e9f-8fb8-df9847cd6945

Czasopismo

Biocybernetics and Biomedical Engineering

Tytuł artykułu

An efficient wavelet-based automated R-peaks detection method using Hilbert transform

Autorzy Rakshit, M.  Das, S. 
Treść / Zawartość http://www.ibib.waw.pl/pl/wydawnictwa/biocybernetics-and-biomedical-enginering-bbe/bbe-tomy http://www.journals.elsevier.com/biocybernetics-and-biomedical-engineering/
Warianty tytułu
Języki publikacji EN
Abstrakty
EN Machine-aided detection of R-peaks is becoming a vital task to automate the diagnosis of critical cardiovascular ailments. R-peaks in Electrocardiogram (ECG) is one of the key segments for diagnosis of the cardiac disorder. By recognizing R-peaks, heart rate of the patient can be computed and from that point onwards heart rate variability (HRV), tachycardia, and bradycardia can also be determined. Most of the R-peaks detectors suffer due to non-stationary behaviors of the ECG signal. In this work, a wavelet transform based automated R-peaks detection method has been proposed. A wavelet-based multiresolution approach along with Shannon energy envelope estimator is utilized to eliminate the noises in ECG signal and enhance the QRS complexes. Then a Hilbert transform based peak finding logic is used to detect the R-peaks without employing any amplitude threshold. The efficiency of the proposed work is validated using all the ECG signals of MIT-BIH arrhythmia database, and it attains an average accuracy of 99.83%, sensitivity of 99.93%, positive predictivity of 99.91%, error rate of 0.17% and an average F-score of 0.9992. A close observation of the simulation and validation indicates that the suggested technique achieves superior performance indices compared to the existing methods for real ECG signal.
Słowa kluczowe
PL elektrokardiogram   transformata falkowa   transformacja Hilberta  
EN electrocardiogram   R-peak detection   wavelet transform   Hilbert transform   MIT-BIH database  
Wydawca Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences
Elsevier
Czasopismo Biocybernetics and Biomedical Engineering
Rocznik 2017
Tom Vol. 37, no. 3
Strony 566--577
Opis fizyczny Bibliogr. 26 poz., rys., tab., wykr.
Twórcy
autor Rakshit, M.
  • Signal Processing & Communication Lab, Department of Electrical Engineering, National Institute of Technology Rourkela, Odisha 769008, India, rakshitmanas09@gmail.com
autor Das, S.
  • Department of Electrical Engineering, National Institute of Technology Rourkela, Odisha, India, sdas@nitrkl.ac.in
Bibliografia
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Uwagi
PL Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-fc366354-e545-4e9f-8fb8-df9847cd6945
Identyfikatory
DOI 10.1016/j.bbe.2017.02.002