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Multiscale Entropy: Recent Advances

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Complexity and Nonlinearity in Cardiovascular Signals

Abstract

Multiscale entropy is a widely used metric for characterizing the complexity of physiological time series. The fundamental difference to classical entropy measures is it enables quantification of nonlinear dynamics underlying physiological processes over multiple time scales. The basic idea of multiscale entropy was initially developed in 2002 and has since witnessed considerable progress in methodological expansions along with growing applications. Here, we provide an overview of some recent developments in the theory, identify some methodological constraints of the originally introduced multiscale entropy analysis, and discuss some improvements that we, and others, have made regarding the definition of the time scales, its multivariate extension and improved methods for estimating the basic technique. Finally, the application of multiscale entropy to the analysis of cardiovascular data is summarized.

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Authors and Affiliations

  1. School of Biomedical Engineering, Drexel University, Philadelphia, PA, 19104, USA

    Meng Hu & Hualou Liang

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  1. Meng Hu
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Correspondence to Hualou Liang .

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Editors and Affiliations

  1. Department of Electronics, Informatics and Bioengineering, Politecnico di Milano, Milan, Italy

    Riccardo Barbieri

  2. Department of Information Engineering & Bioengineering and Robotics Research Center “E. Piaggio”, University of Pisa, School of Engineering, Pisa, Italy

    Enzo Pasquale Scilingo

  3. Department of Information Engineering & Bioengineering and Robotics Research Center “E. Piaggio”, University of Pisa, School of Engineering, Pisa, Italy

    Gaetano Valenza

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Hu, M., Liang, H. (2017). Multiscale Entropy: Recent Advances. In: Barbieri, R., Scilingo, E., Valenza, G. (eds) Complexity and Nonlinearity in Cardiovascular Signals. Springer, Cham. https://doi.org/10.1007/978-3-319-58709-7_4

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