Abstract
Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and non-equilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools––multiscale entropy and multiscale time irreversibility––are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs.
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Acknowledgements
We gratefully acknowledge support from the NIH Research Resource for Complex Physiologic Signals (NIBIB and NIGMS), the G. Harold and Leila Y. Mathers Charitable Foundation, the James S. McDonnell Foundation, the Ellison Medical Foundation, and the Defense Advanced Research Projects Agency (HR0011-05-1-0057).
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Costa, M.D., Peng, CK. & Goldberger, A.L. Multiscale Analysis of Heart Rate Dynamics: Entropy and Time Irreversibility Measures. Cardiovasc Eng 8, 88–93 (2008). https://doi.org/10.1007/s10558-007-9049-1
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DOI: https://doi.org/10.1007/s10558-007-9049-1