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Delta-Fuzzy Similarity Entropy to Discriminate Healthy from Sick Fetus

Souad Oudjemia 1, * Amira Zaylaa 2, 3 Jamal Charara 2, 3 Jean-Marc Girault 2
* Corresponding author
1 L2CSP - Laboratoire de Conception et Conduite des systèmes de Production
2 iBrain - Inserm U1253 - UNIV Tours - Imagerie et cerveau
3 Signal and Image Laboratory
Abstract : This paper deals with the discrimination between suffering and healthy fetuses, by means of a delta-fuzzy-similarity entropy. This new descriptor of complexity is based on the derivative of the fuzzy-similarity entropy. It was tested on fetal heart rate time-series and compared to the approximated and similarity entropies. The main outcome was the possibility to improve 10% the specificity and the sensitivity as compared to approximate entropy. This very good performance confirms that the new descriptor can be a valuable alternative as compared to other standard descriptors.
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https://www.hal.inserm.fr/inserm-00922140
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Submitted on : Thursday, February 13, 2014 - 4:08:19 PM
Last modification on : Tuesday, October 19, 2021 - 11:00:16 AM

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  • HAL Id : inserm-00922140, version 2

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Souad Oudjemia, Amira Zaylaa, Jamal Charara, Jean-Marc Girault. Delta-Fuzzy Similarity Entropy to Discriminate Healthy from Sick Fetus. 2nd International Conference on Advances in Biomedical Engineering, IEEE, Sep 2013, Lebanon. pp.1-4. ⟨inserm-00922140v2⟩

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