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Signal Processing Techniques for Computational Health Informatics pp 123–143Cite as

Entropy Analysis in Health Informatics

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Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 192))

Abstract

This chapter aims at presenting entropy measures that are now widely used in health informatics. Entropy measures have been introduced in 1990s and are derived from the theory of chaos. The traditional entropy-based analysis methods evaluate the degree of regularity of signals. We therefore present, first, the very well-known entropy measures used in the biomedical field: their theoretical background is detailed and some medical applications are presented. Then, more and very recent entropy measures are exposed and some of their used in health informatics are listed. This is performed from two points of view: for time series (uni-dimensional data) and for images (bi-dimensional data).

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Authors and Affiliations

  1. Univ Angers, LARIS—Laboratoire Angevin de Recherche en Ingénierie des Systèmes, 62 Avenue Notre-Dame du Lac, 49000, Angers, France

    Anne Humeau-Heurtier

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  1. Anne Humeau-Heurtier
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Correspondence to Anne Humeau-Heurtier .

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Editors and Affiliations

  1. Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, Bangladesh

    Md Atiqur Rahman Ahad

  2. Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, Bangladesh

    Mosabber Uddin Ahmed

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Humeau-Heurtier, A. (2021). Entropy Analysis in Health Informatics. In: Ahad, M.A.R., Ahmed, M.U. (eds) Signal Processing Techniques for Computational Health Informatics. Intelligent Systems Reference Library, vol 192. Springer, Cham. https://doi.org/10.1007/978-3-030-54932-9_5

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