Characterization of sample entropy in the context of biomedical signal analysis.

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

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Sample 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)
Pages (from-to)5943-5946
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
StatePublished - 2007
Externally publishedYes

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Signal analysis
Entropy
Random processes
Time series

ASJC Scopus subject areas

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

Cite this

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abstract = "Sample 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.",
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