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Volumn 105, Issue 1, 2012, Pages 40-49

Prediction of paroxysmal atrial fibrillation based on non-linear analysis and spectrum and bispectrum features of the heart rate variability signal

Author keywords

Bispectrum; Heart rate variability; Non linear analysis; Paroxysmal atrial fibrillation; Prediction; Spectrum; Support vector machines

Indexed keywords

ATRIAL FIBRILLATION; BISPECTRUM; HEART RATE VARIABILITY; SPECTRUM; SUPPORT VECTOR;

EID: 84855203264     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2010.07.011     Document Type: Article
Times cited : (105)

References (49)
  • 4
    • 0030889582 scopus 로고    scopus 로고
    • Acute effects of dual site right atrial pacing in patients with spontaneous and inducible atrial flutter and fibrillation
    • Prakash A., Saksena S., Hill M., Krol R.B., Munsif A.N., Giorgberidze I., Mathew P., Mehra R. Acute effects of dual site right atrial pacing in patients with spontaneous and inducible atrial flutter and fibrillation. J. Am. Coll. Cardiol. 1997, 29(5):1007-1014.
    • (1997) J. Am. Coll. Cardiol. , vol.29 , Issue.5 , pp. 1007-1014
    • Prakash, A.1    Saksena, S.2    Hill, M.3    Krol, R.B.4    Munsif, A.N.5    Giorgberidze, I.6    Mathew, P.7    Mehra, R.8
  • 5
    • 0034096030 scopus 로고    scopus 로고
    • Management of atrial fibrillation: therapeutic options and clinical decisions
    • Prystowsky E.N. Management of atrial fibrillation: therapeutic options and clinical decisions. Am. J. Cardiol. 2000, 85(10A):3D-11D.
    • (2000) Am. J. Cardiol. , vol.85 , Issue.10 A
    • Prystowsky, E.N.1
  • 6
    • 0036161878 scopus 로고    scopus 로고
    • Older age is the strongest predictor of postoperative atrial fibrillation
    • Amar D., Zhang H., Leung D.H., Roistacher N., Kadish A.H. Older age is the strongest predictor of postoperative atrial fibrillation. Anesthesiology 2002, 96(2):352-356.
    • (2002) Anesthesiology , vol.96 , Issue.2 , pp. 352-356
    • Amar, D.1    Zhang, H.2    Leung, D.H.3    Roistacher, N.4    Kadish, A.H.5
  • 7
    • 0036128687 scopus 로고    scopus 로고
    • Incidence of chronic atrial fibrillation in general practice and its treatment pattern
    • Ruigomez A., Johansson S., Wallander M.A., Garcia Rodriguez L.A. Incidence of chronic atrial fibrillation in general practice and its treatment pattern. J. Clin. Epidemiol. 2002, 55(4):358-363.
    • (2002) J. Clin. Epidemiol. , vol.55 , Issue.4 , pp. 358-363
    • Ruigomez, A.1    Johansson, S.2    Wallander, M.A.3    Garcia Rodriguez, L.A.4
  • 8
    • 0035887425 scopus 로고    scopus 로고
    • Modes of initiation of paroxysmal atrial fibrillation from analysis of spontaneously occurring episodes using a 12-lead holter monitoring system
    • Kolb C., Nurnberger S., Ndrepepa G., Zrenner B., Schomig A., Schmitt C. Modes of initiation of paroxysmal atrial fibrillation from analysis of spontaneously occurring episodes using a 12-lead holter monitoring system. Am. J. Cardiol. 2001, 88(8):853-857.
    • (2001) Am. J. Cardiol. , vol.88 , Issue.8 , pp. 853-857
    • Kolb, C.1    Nurnberger, S.2    Ndrepepa, G.3    Zrenner, B.4    Schomig, A.5    Schmitt, C.6
  • 9
    • 0035718242 scopus 로고    scopus 로고
    • A methodology for predicting paroxysmal atrial fibrillation based on ECG arrhythmia feature analysis
    • Zong W., Mukkamala R., Mark R.G. A methodology for predicting paroxysmal atrial fibrillation based on ECG arrhythmia feature analysis. Proceedings of the Computers in Cardiology 2001, 125-128.
    • (2001) Proceedings of the Computers in Cardiology , pp. 125-128
    • Zong, W.1    Mukkamala, R.2    Mark, R.G.3
  • 10
    • 1642354443 scopus 로고    scopus 로고
    • Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes
    • Thong T., McNames J., Aboy M., Goldstein B. Prediction of paroxysmal atrial fibrillation by analysis of atrial premature complexes. IEEE Trans. Biomed. Eng. 2004, 51(4):561-569.
    • (2004) IEEE Trans. Biomed. Eng. , vol.51 , Issue.4 , pp. 561-569
    • Thong, T.1    McNames, J.2    Aboy, M.3    Goldstein, B.4
  • 14
    • 44349119093 scopus 로고    scopus 로고
    • Complexity and spectral analysis of the heart rate variability dynamics for distant prediction of paroxysmal atrial fibrillation with artificial intelligence methods
    • Chesnokov Y.V. Complexity and spectral analysis of the heart rate variability dynamics for distant prediction of paroxysmal atrial fibrillation with artificial intelligence methods. Artif. Intell. Med. 2008, 43(2):151-165.
    • (2008) Artif. Intell. Med. , vol.43 , Issue.2 , pp. 151-165
    • Chesnokov, Y.V.1
  • 16
    • 0034012293 scopus 로고    scopus 로고
    • Bispectrum analysis of focal ischemic cerebral EEG signal using third-order recursion method
    • Zhang J.W., Zheng C.-X., Xie A. Bispectrum analysis of focal ischemic cerebral EEG signal using third-order recursion method. IEEE Trans. Biomed. Eng. 2000, 47(3):352-359.
    • (2000) IEEE Trans. Biomed. Eng. , vol.47 , Issue.3 , pp. 352-359
    • Zhang, J.W.1    Zheng, C.-X.2    Xie, A.3
  • 17
    • 38349077304 scopus 로고    scopus 로고
    • Classifying mental tasks based on features of higher-order statistics from EEG signals in brain-computer interface
    • Zhuo S.M., Gan J.Q., Sepulveda F. Classifying mental tasks based on features of higher-order statistics from EEG signals in brain-computer interface. Inf. Sci. 2008, 178(6):1629-1640.
    • (2008) Inf. Sci. , vol.178 , Issue.6 , pp. 1629-1640
    • Zhuo, S.M.1    Gan, J.Q.2    Sepulveda, F.3
  • 18
    • 0034254548 scopus 로고    scopus 로고
    • Characterization of sleep spindles using higher order statistics and spectra
    • Akgul T., Sun M., Sclahassi R.J., Cetin A.E. Characterization of sleep spindles using higher order statistics and spectra. IEEE Trans. Biomed. Eng. 2000, 47(8):997-1009.
    • (2000) IEEE Trans. Biomed. Eng. , vol.47 , Issue.8 , pp. 997-1009
    • Akgul, T.1    Sun, M.2    Sclahassi, R.J.3    Cetin, A.E.4
  • 19
    • 27644465212 scopus 로고    scopus 로고
    • A quantitative analysis approach for cardiac arrhythmia classification using higher order spectral techniques
    • Khadra L., Al-Fahoum A.S., Binajjaj S. A quantitative analysis approach for cardiac arrhythmia classification using higher order spectral techniques. IEEE Trans. Biomed. Eng. 2005, 52(11):1840-1845.
    • (2005) IEEE Trans. Biomed. Eng. , vol.52 , Issue.11 , pp. 1840-1845
    • Khadra, L.1    Al-Fahoum, A.S.2    Binajjaj, S.3
  • 21
    • 34347378883 scopus 로고    scopus 로고
    • Recognition of electromyographic signals using cascaded kernel learning machine
    • Liu Y.H., Huang H.P., Weng C.H. Recognition of electromyographic signals using cascaded kernel learning machine. IEEE/ASME Trans. Mechatron. 2007, 12(3):253-264.
    • (2007) IEEE/ASME Trans. Mechatron. , vol.12 , Issue.3 , pp. 253-264
    • Liu, Y.H.1    Huang, H.P.2    Weng, C.H.3
  • 22
    • 34248592215 scopus 로고    scopus 로고
    • A cascade learning system for classification of diabetes disease: generalized discriminant analysis and least square support vector machine
    • Polat K., Günes S., Arslan A. A cascade learning system for classification of diabetes disease: generalized discriminant analysis and least square support vector machine. Expert Syst. Appl. 2008, 34(1):482-487.
    • (2008) Expert Syst. Appl. , vol.34 , Issue.1 , pp. 482-487
    • Polat, K.1    Günes, S.2    Arslan, A.3
  • 23
    • 34250618313 scopus 로고    scopus 로고
    • A novel approach to estimation of E. coli promoter gene sequences: combining feature selection and least square support vector machine (FS_LSSVM)
    • Polat K., Günes S. A novel approach to estimation of E. coli promoter gene sequences: combining feature selection and least square support vector machine (FS_LSSVM). Appl. Math. Comput. 2007, 190(2):1574-1582.
    • (2007) Appl. Math. Comput. , vol.190 , Issue.2 , pp. 1574-1582
    • Polat, K.1    Günes, S.2
  • 25
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
    • Burges J.C. A tutorial on support vector machines for pattern recognition. Data Min. Knowl. Discov. 1998, 2:121-167.
    • (1998) Data Min. Knowl. Discov. , vol.2 , pp. 121-167
    • Burges, J.C.1
  • 26
    • 84855203453 scopus 로고    scopus 로고
    • Physionet AFPDB database,
    • Physionet AFPDB database, http://www.physionet.org/physiobank/database/afpdb.
  • 27
    • 0021892137 scopus 로고
    • A real time QRS detection algorithm
    • Pan J., Tompkins W.J. A real time QRS detection algorithm. IEEE Trans. Biomed. Eng. 1985, 32(3):230-236.
    • (1985) IEEE Trans. Biomed. Eng. , vol.32 , Issue.3 , pp. 230-236
    • Pan, J.1    Tompkins, W.J.2
  • 28
    • 0022929617 scopus 로고
    • Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database
    • Hamilton P.S., Tompkins W.J. Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database. IEEE Trans. Biomed. Eng. 1986, 33(12):1157-1165.
    • (1986) IEEE Trans. Biomed. Eng. , vol.33 , Issue.12 , pp. 1157-1165
    • Hamilton, P.S.1    Tompkins, W.J.2
  • 29
    • 0029988782 scopus 로고    scopus 로고
    • Heart rate variability-standards of measurements, physiological interpretation, and clinical use
    • Task force of the European society of cardiology and the North American society of pacing and electrophysiology
    • Task force of the European society of cardiology and the North American society of pacing and electrophysiology Heart rate variability-standards of measurements, physiological interpretation, and clinical use. Eur. Heart J. 1996, 17(3):354-381.
    • (1996) Eur. Heart J. , vol.17 , Issue.3 , pp. 354-381
  • 31
    • 0036112612 scopus 로고    scopus 로고
    • A study on the optimum order of autoregressive models for heart rate variability
    • Boardman A., Schlindwein F.S., Rocha A.P., Leite A. A study on the optimum order of autoregressive models for heart rate variability. Physiol. Meas. 2002, 23:324-336.
    • (2002) Physiol. Meas. , vol.23 , pp. 324-336
    • Boardman, A.1    Schlindwein, F.S.2    Rocha, A.P.3    Leite, A.4
  • 32
    • 1542360768 scopus 로고    scopus 로고
    • Study on the optimal order for the auto-regressive time-frequency analysis of heart rate variability
    • Carvalho J.L.A., et al. Study on the optimal order for the auto-regressive time-frequency analysis of heart rate variability. Proceedings of the EMBC 2003, 2621-2624.
    • (2003) Proceedings of the EMBC , pp. 2621-2624
    • Carvalho, J.L.A.1
  • 33
    • 54849380800 scopus 로고    scopus 로고
    • Automatic identification of cardiac health using modeling techniques: a comparative study
    • Acharya R.U., Sankaranarayanan M., Nayak J., Xiang C., Tamura T. Automatic identification of cardiac health using modeling techniques: a comparative study. Inf. Sci. 2008, 178:4571-4582.
    • (2008) Inf. Sci. , vol.178 , pp. 4571-4582
    • Acharya, R.U.1    Sankaranarayanan, M.2    Nayak, J.3    Xiang, C.4    Tamura, T.5
  • 34
    • 4644303235 scopus 로고    scopus 로고
    • Bicoherence analysis of new cardiovascular spectral components observed in heart-transplant patients: statistical approach for bicoherence thresholding
    • Pinhas I., Toledo E., Aravot D., Akselrod S. Bicoherence analysis of new cardiovascular spectral components observed in heart-transplant patients: statistical approach for bicoherence thresholding. IEEE Trans. Biomed. Eng. 2004, 51(10):1774-1783.
    • (2004) IEEE Trans. Biomed. Eng. , vol.51 , Issue.10 , pp. 1774-1783
    • Pinhas, I.1    Toledo, E.2    Aravot, D.3    Akselrod, S.4
  • 37
    • 39749182703 scopus 로고    scopus 로고
    • Cardiac state diagnosis using higher order spectra of heart rate variability
    • Chua K.C., Chandran V., Acharya U.R., Lim C.M. Cardiac state diagnosis using higher order spectra of heart rate variability. J. Med. Eng. Technol. 2008, 32(2):145-155.
    • (2008) J. Med. Eng. Technol. , vol.32 , Issue.2 , pp. 145-155
    • Chua, K.C.1    Chandran, V.2    Acharya, U.R.3    Lim, C.M.4
  • 38
    • 0033949457 scopus 로고    scopus 로고
    • Physiological time-series analysis using approximate entropy and sample entropy
    • Richman J.S., Moorman J.R. Physiological time-series analysis using approximate entropy and sample entropy. Am. J. Physiol. Heart Circ. Physiol. 2000, 278(6):2039-2049.
    • (2000) Am. J. Physiol. Heart Circ. Physiol. , vol.278 , Issue.6 , pp. 2039-2049
    • Richman, J.S.1    Moorman, J.R.2
  • 39
    • 0028355806 scopus 로고
    • Physiological time series analysis: what does regularity quantify?
    • Pincus S.M., Goldberger A.L. Physiological time series analysis: what does regularity quantify?. Am. J. Physiol. Heart Circ. Physiol. 1994, 266(4):1643-1656.
    • (1994) Am. J. Physiol. Heart Circ. Physiol. , vol.266 , Issue.4 , pp. 1643-1656
    • Pincus, S.M.1    Goldberger, A.L.2
  • 41
    • 50049126632 scopus 로고    scopus 로고
    • Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal
    • Mohammadzadeh-Asl B., Setarehdan S.K., Mohebbi M. Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal. Artif. Intel. Med. 2008, 44(1):51-64.
    • (2008) Artif. Intel. Med. , vol.44 , Issue.1 , pp. 51-64
    • Mohammadzadeh-Asl, B.1    Setarehdan, S.K.2    Mohebbi, M.3
  • 42
    • 0036950935 scopus 로고    scopus 로고
    • Screening for paroxysmal atrial fibrillation using atrial premature contractions and spectral measures
    • Hickey B., Heneghan C. Screening for paroxysmal atrial fibrillation using atrial premature contractions and spectral measures. Proceedings of the Computers in Cardiology 2002, 217-220.
    • (2002) Proceedings of the Computers in Cardiology , pp. 217-220
    • Hickey, B.1    Heneghan, C.2
  • 44
    • 34250886271 scopus 로고    scopus 로고
    • Atrial fibrillation classification with artificial neural networks
    • Kara S., Okandan M. Atrial fibrillation classification with artificial neural networks. Pattern Recognit. 2007, 40(11):2967-2973.
    • (2007) Pattern Recognit. , vol.40 , Issue.11 , pp. 2967-2973
    • Kara, S.1    Okandan, M.2
  • 48
    • 0031836722 scopus 로고    scopus 로고
    • Simple electrocardiographic markers for the prediction of paroxysmal idiopathic atrial fibrillation
    • Dilaveris P.E., Gialafos E., Sideris S. Simple electrocardiographic markers for the prediction of paroxysmal idiopathic atrial fibrillation. Am. Heart J. 1998, 135:73-78.
    • (1998) Am. Heart J. , vol.135 , pp. 73-78
    • Dilaveris, P.E.1    Gialafos, E.2    Sideris, S.3
  • 49
    • 28444445614 scopus 로고    scopus 로고
    • Prediction of atrial fibrillation after coronary artery bypass grafting: the role of chemoreflexsitivity and p wave signal averaged ECG
    • Budeus M., et al. Prediction of atrial fibrillation after coronary artery bypass grafting: the role of chemoreflexsitivity and p wave signal averaged ECG. Int. J. Cardiol. 2006, 106:67-74.
    • (2006) Int. J. Cardiol. , vol.106 , pp. 67-74
    • Budeus, M.1


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