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121 related items for PubMed ID: 18003370

  • 1. Mutual nonlinear prediction of cardiovascular variability series: comparison between exogenous and autoregressive exogenous models.
    Faes L, Porta A, Nollo G.
    Annu Int Conf IEEE Eng Med Biol Soc; 2007; 2007():5955-8. PubMed ID: 18003370
    [Abstract] [Full Text] [Related]

  • 2. Assessment of Granger causality by nonlinear model identification: application to short-term cardiovascular variability.
    Faes L, Nollo G, Chon KH.
    Ann Biomed Eng; 2008 Mar; 36(3):381-95. PubMed ID: 18228143
    [Abstract] [Full Text] [Related]

  • 3. Bivariate nonlinear prediction to quantify the strength of complex dynamical interactions in short-term cardiovascular variability.
    Faes L, Nollo G.
    Med Biol Eng Comput; 2006 May; 44(5):383-92. PubMed ID: 16937180
    [Abstract] [Full Text] [Related]

  • 4. The strength of QT-RR coupling decreases during graded head-up tilt.
    Porta A, Tobaldini E, Montano N, Gnecchi-Ruscone T.
    Annu Int Conf IEEE Eng Med Biol Soc; 2007 May; 2007():5959-62. PubMed ID: 18003371
    [Abstract] [Full Text] [Related]

  • 5. Precursors of syncope in linear and non-linear parameters of heart rate variability during pediatric head-up tilt test.
    Maier C, Khalil M, Ulmer H, Dickhaus H.
    Biomed Tech (Berl); 2008 Jun; 53(3):145-55. PubMed ID: 18601623
    [Abstract] [Full Text] [Related]

  • 6. Prediction of short cardiovascular variability signals based on conditional distribution.
    Porta A, Baselli G, Guzzetti S, Pagani M, Malliani A, Cerutti S.
    IEEE Trans Biomed Eng; 2000 Dec; 47(12):1555-64. PubMed ID: 11125590
    [Abstract] [Full Text] [Related]

  • 7. Complexity and nonlinearity in short-term heart period variability: comparison of methods based on local nonlinear prediction.
    Porta A, Guzzetti S, Furlan R, Gnecchi-Ruscone T, Montano N, Malliani A.
    IEEE Trans Biomed Eng; 2007 Jan; 54(1):94-106. PubMed ID: 17260860
    [Abstract] [Full Text] [Related]

  • 8. Assessing causality in normal and impaired short-term cardiovascular regulation via nonlinear prediction methods.
    Nollo G, Faes L, Antolini R, Porta A.
    Philos Trans A Math Phys Eng Sci; 2009 Apr 13; 367(1892):1423-40. PubMed ID: 19324717
    [Abstract] [Full Text] [Related]

  • 9. Mixed predictability and cross-validation to assess non-linear Granger causality in short cardiovascular variability series.
    Faes L, Cucino R, Nollo G.
    Biomed Tech (Berl); 2006 Oct 13; 51(4):255-9. PubMed ID: 17061952
    [Abstract] [Full Text] [Related]

  • 10. Assessment of cardiac autonomic modulation during graded head-up tilt by symbolic analysis of heart rate variability.
    Porta A, Tobaldini E, Guzzetti S, Furlan R, Montano N, Gnecchi-Ruscone T.
    Am J Physiol Heart Circ Physiol; 2007 Jul 13; 293(1):H702-8. PubMed ID: 17308016
    [Abstract] [Full Text] [Related]

  • 11. Detection of nonlinearity in cardiovascular variability signals using cyclostationary analysis.
    Seydnejad S.
    Ann Biomed Eng; 2007 May 13; 35(5):744-54. PubMed ID: 17372836
    [Abstract] [Full Text] [Related]

  • 12. Are Nonlinear Model-Free Conditional Entropy Approaches for the Assessment of Cardiac Control Complexity Superior to the Linear Model-Based One?
    Porta A, De Maria B, Bari V, Marchi A, Faes L.
    IEEE Trans Biomed Eng; 2017 Jun 13; 64(6):1287-1296. PubMed ID: 27541327
    [Abstract] [Full Text] [Related]

  • 13. Baroreflex sensitivity, blood pressure buffering, and resonance: what are the links? Computer simulation of healthy subjects and heart failure patients.
    van de Vooren H, Gademan MG, Swenne CA, TenVoorde BJ, Schalij MJ, Van der Wall EE.
    J Appl Physiol (1985); 2007 Apr 13; 102(4):1348-56. PubMed ID: 17185500
    [Abstract] [Full Text] [Related]

  • 14. Mutual nonlinear prediction as a tool to evaluate coupling strength and directionality in bivariate time series: comparison among different strategies based on k nearest neighbors.
    Faes L, Porta A, Nollo G.
    Phys Rev E Stat Nonlin Soft Matter Phys; 2008 Aug 13; 78(2 Pt 2):026201. PubMed ID: 18850915
    [Abstract] [Full Text] [Related]

  • 15. Spectral and symbolic analysis of heart rate data during the tilt test.
    Cammarota C, Rogora E.
    Phys Rev E Stat Nonlin Soft Matter Phys; 2006 Oct 13; 74(4 Pt 1):042903. PubMed ID: 17155117
    [Abstract] [Full Text] [Related]

  • 16. A differential autoregressive modeling approach within a point process framework for non-stationary heartbeat intervals analysis.
    Chen Z, Purdon PL, Brown EN, Barbieri R.
    Annu Int Conf IEEE Eng Med Biol Soc; 2010 Oct 13; 2010():3567-70. PubMed ID: 21096829
    [Abstract] [Full Text] [Related]

  • 17. Short-term cardiovascular responses to rapid whole-body tilting during exercise.
    Sundblad P, Haruna Y, Tedner B, Linnarsson D.
    Eur J Appl Physiol; 2000 Mar 13; 81(4):259-70. PubMed ID: 10664083
    [Abstract] [Full Text] [Related]

  • 18. Non-linear regularity of arterial blood pressure variability in patient with atrial fibrillation in tilt-test procedure.
    Cerutti S, Corino VD, Mainardi L, Lombardi F, Aktaruzzaman M, Sassi R.
    Europace; 2014 Nov 13; 16 Suppl 4():iv141-iv147. PubMed ID: 25362165
    [Abstract] [Full Text] [Related]

  • 19. Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability series.
    Faes L, Nollo G, Porta A.
    Comput Biol Med; 2012 Mar 13; 42(3):290-7. PubMed ID: 21419400
    [Abstract] [Full Text] [Related]

  • 20. Dynamic assessment of spontaneous baroreflex sensitivity by means of time-frequency analysis using either RR or pulse interval variability.
    Orini M, Mainardi LT, Gil E, Laguna P, Bailon R.
    Annu Int Conf IEEE Eng Med Biol Soc; 2010 Mar 13; 2010():1630-3. PubMed ID: 21096388
    [Abstract] [Full Text] [Related]

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