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Editorial

Assessing Complexity in Physiological Systems through Biomedical Signals Analysis

1
IRCCS Fondazione Don Carlo Gnocchi, 20148 Milan, Italy
2
Department of Engineering, University of Palermo, 90128 Palermo, Italy
3
Department of Information Engineering and Research Center “E. Piaggio”, University of Pisa, 56122 Pisa, Italy
*
Author to whom correspondence should be addressed.
Entropy 2020, 22(9), 1005; https://doi.org/10.3390/e22091005
Received: 7 September 2020 / Accepted: 8 September 2020 / Published: 9 September 2020
Note: In lieu of an abstract, this is an excerpt from the first page.

The idea that most physiological systems are complex has become increasingly popular in recent decades [...] View Full-Text
Keywords: entropy; multifractality; multiscale; cardiovascular system; brain; information flow entropy; multifractality; multiscale; cardiovascular system; brain; information flow
MDPI and ACS Style

Castiglioni, P.; Faes, L.; Valenza, G. Assessing Complexity in Physiological Systems through Biomedical Signals Analysis. Entropy 2020, 22, 1005. https://doi.org/10.3390/e22091005

AMA Style

Castiglioni P, Faes L, Valenza G. Assessing Complexity in Physiological Systems through Biomedical Signals Analysis. Entropy. 2020; 22(9):1005. https://doi.org/10.3390/e22091005

Chicago/Turabian Style

Castiglioni, Paolo, Luca Faes, and Gaetano Valenza. 2020. "Assessing Complexity in Physiological Systems through Biomedical Signals Analysis" Entropy 22, no. 9: 1005. https://doi.org/10.3390/e22091005

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