The Multiscale Entropy Algorithm and Its Variants: A Review

By Anne Humeau-Heurtier. Entropy, 2015

307 citations recorded by the source corpus.

Multiscale entropy (MSE) analysis was introduced in the 2002 to evaluate the complexity of a time series by quantifying its entropy over a range of temporal scales. The algorithm has been successfully applied in different research fields. Since its introduction, a number of modifications and refinements have been proposed, some aimed at increasing the accuracy of the entropy estimates, others at exploring alternative coarse-graining procedures. In this review, we first describe the original MSE algorithm. Then, we review algorithms that have been introduced to improve the estimation of MSE. We also report a recent generalization of the method to higher moments.

Subfields: Computer Networks and Communications, Economics and Econometrics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/814d3223e134fba919c9fc3c2cd10ca10ff00e7f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Anne Humeau-Heurtier
2. Dominique Makowski

In Statistical and Nonlinear Physics

1. Z. J. Lau
2. Anne Humeau-Heurtier
3. Tam Pham
4. Shen-Hsing Annabel Chen
5. Dominique Makowski

Citations in the corpus

• Texture Feature Extraction Methods: A Survey (2019, background): “Many papers have been published on the use of these entropy measures [251].”
• Heart Rate Variability in Psychology: A Review of HRV Indices and an Analysis Tutorial (2021, background): “Research also suggests a lower HRV with reduced RMSSD, HF, ApEn and SampEn in patients suffering from schizophrenia [149,155–158], and a correlation with symptoms such as apathy, withdrawal and delusions [159], suggesting a relationship between psychotic symptoms and cardiac autonomic function [149,”