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Wavelet-based Multifractal Analysis of Heartbeat Dynamics: Non-Gaussian Expansion vs. Cumulants

Abstract : Nonlinear and non-Gaussian analysis contributes to a comprehensive characterization of autonomic nervous system control on heartbeat dynamics. Nevertheless, a statistical comparison between non-Gaussian features and cumulants in the frame of a wavelet-based multifractal analysis of heartbeat dynamics has not been performed yet. Here we exploit a multifractal features formulation based on wavelet p-leaders spectrum applied to instantaneous heartbeat estimates from inhomogeneous point processes. We then perform a non-Gaussian multiscale expansion and analyze physiologically-meaningful differences between resting state and cold-pressure test in 30 healthy subjects. Results show that nonlinear and non-Gaussian features are associated with statistical differences between physiological states, whereas cumulants from the multifractal spectrum, till the third order, were not statistically different.
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Contributor : Herwig Wendt Connect in order to contact the contributor
Submitted on : Tuesday, December 1, 2020 - 4:05:33 PM
Last modification on : Friday, December 2, 2022 - 5:50:05 PM
Long-term archiving on: : Tuesday, March 2, 2021 - 7:52:49 PM


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Vincenzo Catrambone, Herwig Wendt, Riccardo Barbieri, Patrice Abry, Gaetano Valenza. Wavelet-based Multifractal Analysis of Heartbeat Dynamics: Non-Gaussian Expansion vs. Cumulants. 11th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO 2020), Jul 2020, Pisa, Italy. ⟨10.1109/ESGCO49734.2020.9158011⟩. ⟨hal-03034103⟩



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