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A comprehensive comparison and overview of R packages for calculating sample entropy
Chen C.1; Sun S.1; Cao Z.2,3,4; Shi Y.5; Sun B.6; Zhang X.D.1,7
2019
Source PublicationBiology Methods and Protocols
ISSN2396-8923
Volume4Issue:1
Abstract

Sample entropy is a powerful tool for analyzing the complexity and irregularity of physiology signals which may be associated with human health. Nevertheless, the sophistication of its calculation hinders its universal application. As of today, the R language provides multiple open-source packages for calculating sample entropy. All of which, however, are designed for different scenarios. Therefore, when searching for a proper package, the investigators would be confused on the parameter setting and selection of algorithms. To ease their selection, we have explored the functions of five existing R packages for calculating sample entropy and have compared their computing capability in several dimensions. We used four published datasets on respiratory and heart rate to study their input parameters, types of entropy, and program running time. In summary, NonlinearTseries and CGManalyzer can provide the analysis of sample entropy with different embedding dimensions and similarity thresholds. CGManalyzer is a good choice for calculating multiscale sample entropy of physiological signal because it not only shows sample entropy of all scales simultaneously but also provides various visualization plots. MSMVSampEn is the only package that can calculate multivariate multiscale entropies. In terms of computing time, NonlinearTseries, CGManalyzer, and MSMVSampEn run significantly faster than the other two packages. Moreover, we identify the issues in MVMSampEn package. This article provides guidelines for researchers to find a suitable R package for their analysis and applications using sample entropy.

KeywordComparison Nonlinear Dynamics r Package Sample Entropy Time Series
DOI10.1093/biomethods/bpz016
URLView the original
Language英語English
The Source to ArticleScopus
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Cited Times [WOS]:7   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorZhang X.D.
Affiliation1.Faculty of Health Sciences, University of Macau, Taipa, Macau;
2.Department of Respiratory and Critical Care Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China;
3.Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China;
4.Beijing Engineering Research Center of Respiratory and Critical Care Medicine, Beijing, China;
5.School of Automation Science and Electrical Engineering, Beihang University, Beijing, China;
6.State Key Laboratory of Respiratory Disease, 1st Affiliated Hospital of Guangzhou Medical University, Guangzhou, China;
7.Department of Biostatistics, Yale University, New Haven, CT 06511, United States
First Author AffilicationFaculty of Health Sciences
Corresponding Author AffilicationFaculty of Health Sciences
Recommended Citation
GB/T 7714
Chen C.,Sun S.,Cao Z.,et al. A comprehensive comparison and overview of R packages for calculating sample entropy[J]. Biology Methods and Protocols,2019,4(1).
APA Chen C.,Sun S.,Cao Z.,Shi Y.,Sun B.,&Zhang X.D..(2019).A comprehensive comparison and overview of R packages for calculating sample entropy.Biology Methods and Protocols,4(1).
MLA Chen C.,et al."A comprehensive comparison and overview of R packages for calculating sample entropy".Biology Methods and Protocols 4.1(2019).
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