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Journal Abstract Search

129 related items for PubMed ID: 21051039

  • 1. Towards automatic detection of atrial fibrillation: A hybrid computational approach.
    Yaghouby F, Ayatollahi A, Bahramali R, Yaghouby M, Alavi AH.
    Comput Biol Med; 2010; 40(11-12):919-30. PubMed ID: 21051039
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  • 2. A novel method for detection of the transition between atrial fibrillation and sinus rhythm.
    Huang C, Ye S, Chen H, Li D, He F, Tu Y.
    IEEE Trans Biomed Eng; 2011 Apr; 58(4):1113-9. PubMed ID: 21134807
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  • 3. Time-varying coherence function for atrial fibrillation detection.
    Lee J, Nam Y, McManus DD, Chon KH.
    IEEE Trans Biomed Eng; 2013 Oct; 60(10):2783-93. PubMed ID: 23708769
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  • 4. Development of a toolbox for electrocardiogram-based interpretation of atrial fibrillation.
    Abächerli R, Leber R, Lemay M, Vesin JM, van Oosterom A, Schmid HJ, Kappenberger L.
    J Electrocardiol; 2009 Oct; 42(6):517-21. PubMed ID: 19698953
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  • 7. A simple method to detect atrial fibrillation using RR intervals.
    Lian J, Wang L, Muessig D.
    Am J Cardiol; 2011 May 15; 107(10):1494-7. PubMed ID: 21420064
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  • 9. Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal.
    Asl BM, Setarehdan SK, Mohebbi M.
    Artif Intell Med; 2008 Sep 15; 44(1):51-64. PubMed ID: 18585905
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  • 10. Frequency tracking of atrial fibrillation using hidden Markov models.
    Sandberg F, Stridh M, Sörnmo L.
    IEEE Trans Biomed Eng; 2008 Feb 15; 55(2 Pt 1):502-11. PubMed ID: 18269985
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  • 12. Sampling frequency of the RR interval time series for spectral analysis of heart rate variability.
    Singh D, Vinod K, Saxena SC.
    J Med Eng Technol; 2004 Feb 15; 28(6):263-72. PubMed ID: 15513744
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  • 14. Classification of cardiac rhythm using heart rate dynamical measures: validation in MIT-BIH databases.
    Carrara M, Carozzi L, Moss TJ, de Pasquale M, Cerutti S, Lake DE, Moorman JR, Ferrario M.
    J Electrocardiol; 2015 Feb 15; 48(6):943-6. PubMed ID: 26320371
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  • 15. Spatiotemporal blind source separation approach to atrial activity estimation in atrial tachyarrhythmias.
    Castells F, Rieta JJ, Millet J, Zarzoso V, Associate.
    IEEE Trans Biomed Eng; 2005 Feb 15; 52(2):258-67. PubMed ID: 15709663
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  • 16. Prediction of paroxysmal Atrial Fibrillation: A machine learning based approach using combined feature vector and mixture of expert classification on HRV signal.
    Ebrahimzadeh E, Kalantari M, Joulani M, Shahraki RS, Fayaz F, Ahmadi F.
    Comput Methods Programs Biomed; 2018 Oct 15; 165():53-67. PubMed ID: 30337081
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