![[PDF]](/pb-assets/Icons/adobe-pdf-icon-1498649896243.png){kind=icon}
Abstract
Cardiac variability can be assessed from two perspectives: beat-to-beat performance and continuous performance during the cardiac cycle. Linear analysis techniques assess cardiac variability by measuring the physical attributes of a signal, whereas nonlinear techniques evaluate signal dynamics. This study sought to determine if recurrence quantification analysis (RQA), a nonlinear technique, could detect pharmacologically induced autonomic changes in the continuous left ventricular pressure (LVP) and electrographic (EC) signals from an isolated rat heart—a model that theoretically contains no inherent variability. LVP and EC signal data were acquired simultaneously during Langendorff perfusion of isolated rat hearts before and after the addition of acetylcholine (n = 11), norepinephrine (n = 12), or no drug (n = 12). Two-minute segments of the continuous LVP and EC signal data were analyzed by RQA. Findings showed that%recurrence,%determinism, entropy, maxline, and trend from the continuous LVP signal significantly increased in the presence of both acetylcholine and norepinephrine, although systolic LVP significantly increased only with norepinephrine. In the continuous EC signal, the RQA trend variable significantly increased in the presence of norepinephrine. These results suggest that when either the sympathetic or parasympathetic division of the autonomic nervous system overwhelms the other, the dynamics underlying cardiac variability become stationary. This study also shows that information concerning inherent variability in the isolated rat heart can be gained via RQA of the continuous cardiac signal. Although speculative, RQA may be a tool for detecting alterations in cardiac variability and evaluating signal dynamics as a nonlinear indicator of cardiac pathology.
|
Akay, M. (2001). Nonlinear biomedical signal processing. Volume II. Dynamic analysis and modeling. New York: IEEE Press. Google Scholar | |
|
Balaji, S. , Ellenby, M. , McNames, J. , & Goldstein, B. (2002). Update on intensive care ECG and cardiac event monitoring. Cardiac Electrophysiology Review, 6, 190-195. Google Scholar | Crossref | Medline | |
|
Berntson, G. G. , Bigger, J. T. , Eckberg, D. L. , Grossman, P. , Kaufmann, P. G. , Malik, M. , et al. (1997). Heart rate variability: Origins, methods and interpretive caveats. Psychophysiology, 34, 623-648. Google Scholar | Crossref | Medline | |
|
Dabire, H. , Mestivier, D. , Jarnet, J. , Safar, M. E. , & Chau, N. P. (1998). Quantification of sympathetic and parasympathetic tones by nonlinear indexes in normotensive rats. American Journal of Physiology. Heart and Circulatory Physiology, 275, H1290-H1297. Google Scholar | Crossref | |
|
Fawzi, A. B. (1997). The Langendorff heart. In J. H. McNeill (Ed.), Measurement of cardiac function (pp. 1-9). Boca Raton, FL: CRC. Google Scholar | |
|
Galinanes, M. , & Hearse, D. J. (1990). Assessment of ischemic injury and protective interventions: The Langendorff versus the working rat heart preparation. Canadian Journal of Cardiology, 6(2), 83-91. Google Scholar | Medline | |
|
Giuliani, A. , Piccirillo, G. , Marigliano, V. , & Colosimo, A. (1998). A nonlinear explanation of aging-induced changes in heartbeat dynamics. American Journal of Physiology. Heart and Circulatory Physiology, 75, H1455-H1461. Google Scholar | Crossref | |
|
Gonzalez, J. J. , Cordero, J. J. , Feria, M. , & Pereda, E. (2000). Detection and sources of nonlinearity in the variability of cardiac R-R intervals and blood pressure in rats. American Journal of Physiology. Heart and Circulatory Physiology, 279, H3040-H3046. Google Scholar | Crossref | Medline | |
|
Iwanski, J. S. , & Bradley, E. (1998). Recurrence plots of experimental data: To embed or not to embed? Chaos, 8(4), 861-871. Google Scholar | Crossref | Medline | |
|
Kantz, H. , & Schreiber, T. (1997). Nonlinear time series analysis. Cambridge, UK: Cambridge University Press. Google Scholar | |
|
Khoo, M. C. K. (2000). Physiological control systems: Analysis, simulation and estimation. New York: IEEE Press. Google Scholar | |
|
Kim, S. D. , Beck, J. , Bieniarz, T. , Schumacher, A. , & Piano, M. R. (2001). A rodent model of alcoholic heart muscle disease and its evaluation by echocardiography. Alcoholism: Clinical and Experimental Research, 25(3), 457-463. Google Scholar | Crossref | Medline | |
|
Liu, Y. , Kankaanpaa, M. , Zbilut, J. P. , & Webber, C. L., Jr. (2004). EMG recurrence quantifications in dynamic exercise. Biological Cybernetics, 90, 337-348. Google Scholar | Crossref | Medline | |
|
Mansfield, M. , & O’Sullivan, C. (1998). Understanding physics. New York: John Wiley. Google Scholar | |
|
Marwan, N. , Wessel, N. , Meyerfeldt, U. , Schirdewan, A. , & Kurths, J. (2002). Recurrence-plot-based measures of complexity and their application to heart-rate-variability data. Physical Review E, 66, 026702.1-026702.8. Google Scholar | Crossref | |
|
Neely, J. R. , Liebermeister, H. , Battersby, E. J. , & Morgan, H. E. (1967). Effect of pressure development on oxygen consumption by isolated rat heart. American Journal of Physiology, 212(4), 804-814. Google Scholar | Crossref | Medline | |
|
Opie, L. H. (1965). Coronary flow rate and perfusion pressure as determinants of mechanical function and oxidative metabolism of isolated perfused rat heart. Journal of Physiology, 180, 529-541. Google Scholar | Crossref | Medline | |
|
Sahambi, J. S. , Tandon, S. N. , & Bhatt, R. K. P. (1997, January/February). Using wavelet transforms for ECG characterization. IEEE Engineering in Medicine and Biology, pp. 77-83. Google Scholar | Crossref | Medline | |
|
Schulz, S. , Bauernschmitt, R. , Schwarzhaupt, A. , Vahl, C. F. , & Kiencke, U. (2001). Ventriculo-arterial interaction after acute increase of the aortic input impedance: Description of using recurrence plot analysis. In M. Akay (Ed.), Nonlinear biomedical signal processing. Volume II. Dynamic analysis and modeling (pp. 214-227). New York: IEEE Press. Google Scholar | |
|
Schumacher, A. (2004). Linear and nonlinear approaches to the analysis of R-R interval variability. Biological Research for Nursing, 5(3), 211-221. Google Scholar | SAGE Journals | |
|
Strogatz, S. H. (1994). Nonlinear dynamics and chaos. With applications to physics, biology, chemistry and engineering. Reading, MA: Addison-Wesley. Google Scholar | |
|
Thomasson, N. , Hoeppner, T. J. , Webber, C. L., Jr. , & Zbilut, J. P. (2001). Recurrence quantification in epileptic EEGs. Physics Letters A, 279, 94-101. Google Scholar | Crossref | |
|
Webber, C. L., Jr. (2005). The meaning and measurement of cardiac variability? Critical Care Medicine, 33(3), 677-678. Google Scholar | Crossref | Medline | |
|
Webber, C. L., Jr. , & Zbilut, J. P. (1994). Dynamical assessment of physiological systems and states using recurrence plot strategies. Journal of Applied Physiology, 76(2), 965-973. Google Scholar | Crossref | Medline | |
|
Webber, C. L., Jr. , & Zbilut, J. P. (2005). Recurrence quantification analysis of nonliner dynamical systems. In M. A. Riley & G. Van Orden (Eds.), Tutorials in contemporary nonlinear methods for the behavioral sciences (pp. 26-94). Retrieved January 25, 2006, from http://www.nsf.gov/sbe/bcs/pac/nmbs/nmbs.pdf Google Scholar | |
|
Zbilut, J. P. , Mayer-Kress, G. , Sobotka, P. A. , O’Toole, M. , & Thomas, J. X., Jr. (1989). Bifurcations and intrinsic chaotic and 1/f dynamics in an isolated perfused rat heart. Biological Cybernetics, 61, 371-378. Google Scholar | Crossref | Medline | |
|
Zbilut, J. P. , Thomasson, N. , & Webber, C. L., Jr. (2002). Recurrence quantification analysis as a tool for nonlinear exploration of nonstationary cardiac signals. Medical Engineering & Physics, 24, 53-60. Google Scholar | Crossref | Medline | |
|
Zimatore, G. , Hatzopoulos, S. , Giuliani, A. , Martini, A. , & Colosimo, A. (2002). Comparison of transient otoacoustic emission responses from neonatal and adults ears. Journal of Applied Physiology, 92, 2521-2528. Google Scholar | Crossref | Medline | |
|
Zipes, D. P. , Libby, P. , Bonow, B. O. , & Braunwald, E. (Eds.). (2005). Braunwald’s heart disease. A textbook of cardiovascular medicine (7th ed.). Philadelphia: Elsevier Sanders. Google Scholar |
