Abstract
The contribution of nonlinear dynamics to heart rate variability in healthy humans was examined using surrogate data analysis. Several measures of heart rate variability were used and compared. Heart rates were recorded for three hours and original data sets of 8192 R-R intervals created. For each original data set (n=34), three surrogate data sets were made by shuffling the order of the R-R intervals while retaining their linear correlations. The difference in heart rate variability between the original and surrogate data sets reflects the amount of nonlinear structure in the original data set. Heart rate variability was analyzed by two different nonlinear methods, point correlation dimension and approximate entropy. Nonlinearity, though under 10 percent, could be detected with both types of heart rate variability measures. More importantly, not only were the correlations between these measures and the standard deviation of the R-R intervals weak, the correlation among the nonlinear measures themselves was also weak (generally less than 0.6). This suggests that in addition to standard linear measures of heart rate variability, the use of multiple nonlinear measures of heart rate variability might be useful in monitoring heart rate dynamics.
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Bigger, J.T., Jr., Fleiss, J.L., Rolnitzky, L.M., and Steinman, R.C. (1993). The ability of several short-term measures of R-R variability to predict mortality after myocardial infarction.Circulation 88:927–934.
Elbert, T., Ray, W.J., Kowalik, Z.J., Skinner, J.E., Graf, C.E., and Birbaumer, N. (1994). Chaos and physiology: Deterministic chaos in excitable cell assemblies.Physiological Reviews 74: 1–47.
Fleisher, L.A., Pincus, S.M., and Rosenbaum, S.H. (1993). Approximate entropy of heart rate as a correlate of postoperative ventricular dysfunction.Anesthesiology 78: 683–692.
Goldberger, A.L. (1992). Fractal mechanisms in the electrophysiology of the heart.IEEE in Medicine and Biology June: 47–52.
Kanters, J.K., Højgaard, M., Agner, E., and Holstein-Rathlou, N.H. (1996). Short- and long-term variations in non-linear dynamics of heart rate variability.Cardiovascular Research 31: 400–409.
Kanters, J.K., Holstein-Rathlou, N.H., and Agner, E. (1994). Lack of evidence of low-dimensional chaos in heart rate variability in healthy human subjects.Journal of Cardiovascular Electrophysiology 5: 591–601.
Kaplan, D.T., and Talajic, M. (1992). Dynamics of heart rate.Chaos 1: 251–256.
Latson, T.W. (1994). Principles and applications of heart rate variability analysis. In C. Lynch III (ed.),Clinical Cardiac Electrophysiology: Perioperative Considerations, 307–349. Philadelphia: JB Lippincott.
Pincus, S.M., Gladstone, I.M., and Ehrenkranz, R.A. (1991). A regularity statistic for medical data analysis.Journal of Clinical Monitoring 7(4): 335–345.
Pincus, S.M., and Goldberger, A.L. (1994). Physiological time-series analysis: What does regularity quantify?Journal of Clinical Monitoring 7(4): 335–345.
Pincus, S.M., and Goldberger, A.L. (1994). Physiological time-series analysis: What does regularity quantify?American Journal of Physiology (Heart Circ Physiol 35) 266: H1643-H1656.
Skinner, J.E., Molnar, M., and Tomberg, C. (1994). The point correlation dimension: Performance with nonstationary surrogate data and noise.Integrative Physiological and Behavioral Science 29: 217–234.
Storella, R.J., Kandell, R.B., Horrow, J.C., Ackerman, T.S., Polansky, M., and Zietz, S. (1995). Nonlinear measures of heart rate variability following opioid anesthesia.Anesthesia and Analgesia 81: 1292–1294.
Theiler, J., Galdrikian, B., Longtin, A., Eubank, S., and Farmer, J.D. (1992). Using surrogate data to detect nonlinearity in time series. In Casdagli, M., Eubank, S. (eds.), Nonlinear Modeling and Forecasting, SFI Studies in the Sciences of Complexity 163–188. Addison-Wesley: Reading, MA.
Vybiral, T., and Skinner, J.E. (1993). The point correlation dimension of R-R intervals predicts sudden cardiac death among high-risk patients.Computers in Cardiology 257–260.
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Storella, R.J., Wood, H.W., Mills, K.M. et al. Approximate entropy and point correlation dimension of heart rate variability in healthy subjects. Integrative Physiological and Behavioral Science 33, 315–320 (1998). https://doi.org/10.1007/BF02688699
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DOI: https://doi.org/10.1007/BF02688699