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Biocybernetics and Biomedical Engineering

Tytuł artykułu

Characterization of cardiac arrhythmias by variational mode decomposition technique

Autorzy Maji, U.  Mitra, M.  Pal, S. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
EN Automatic detection of cardiac abnormalities in early stage is a popular area of research for decades. In this work a novel algorithm for detection of cardiac arrhythmia is proposed using variational mode decomposition (VMD). Arrhythmia is a crucial abnormality of heart in which the rhythmic disorder may lead to sudden cardiac arrest. Existing algorithms for arrhythmia detection are based on accuracy of detection of fiducial points, parameter selection and extraction, quality of classifier and other factors. Unlike other works, proposed method tries to characterize both atrial and ventricular arrhythmias simultaneously and independently from the segmented sections of the signal. VMD, being able to separate closely spaced frequencies, has a good potential to be useful to provide significant features in transformed domain. Unique feature combinations are also proposed to characterize different arrhythmic events.
Słowa kluczowe
PL elektrokardiogram   arytmia serca   częstotliwość środkowa  
EN electrocardiogram   cardiac arrhythmia   ventricular mode decomposition   variational mode decomposition   centre frequency  
Wydawca Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences
Czasopismo Biocybernetics and Biomedical Engineering
Rocznik 2017
Tom Vol. 37, no. 3
Strony 578--589
Opis fizyczny Bibliogr. 56 poz., rys., tab., wykr.
autor Maji, U.
  • Department of Applied Electronics and Instrumentation Engineering, Haldia Institute of Technology, Haldia, West Bengal, India,
autor Mitra, M.
  • Department of Applied Physics, University of Calcutta, Kolkata, West Bengal, India
autor Pal, S.
  • Department of Applied Physics, University of Calcutta, Kolkata, West Bengal, India
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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-c05e7caf-588e-4234-9c96-180413125670
DOI 10.1016/j.bbe.2017.04.007