Characterization of sample entropy in the context of biomedical signal analysis

Mateo Aboy, David Cuesta-Frau, Daniel Austin, Pau Micó-Tormos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Scopus citations

Abstract

Entropy (SampEn) has been proposed as a method to overcome limitations associated with approximate entropy (ApEn). The initial paper describing the SampEn metric included a characterization study comparing both ApEn and SampEn against theoretical results and concluded that SampEn is both more consistent and agrees more closely with theory for known random processes than ApEn. SampEn has been used in several studies to analyze the regularity of clinical and experimental time series. However, questions regarding how to interpret SampEn in certain clinical situations and its relationship to classical signal parameters remain unanswered. In this paper we report the results of a characterization study intended to provide additional insights regarding the interpretability of SampEn in the context of biomedical signal analysis.

Original languageEnglish (US)
Title of host publication29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Pages5942-5945
Number of pages4
DOIs
StatePublished - 2007
Externally publishedYes
Event29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 - Lyon, France
Duration: Aug 23 2007Aug 26 2007

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
ISSN (Print)0589-1019

Other

Other29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Country/TerritoryFrance
CityLyon
Period8/23/078/26/07

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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