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An improved method of handling missing values in the analysis of sample entropy for continuous monitoring of physiological signals
Dong X.1,2; Chen C.3; Geng Q.4; Cao Z.5; Chen X.6; Lin J.6; Jin Y.3; Zhang Z.7; Shi Y.5,8; Zhang X.D.9
2019
Source PublicationEntropy
ISSN1099-4300
Volume21Issue:3
Abstract

Medical devices generate huge amounts of continuous time series data. However, missing values commonly found in these data can prevent us from directly using analytic methods such as sample entropy to reveal the information contained in these data. To minimize the influence of missing points on the calculation of sample entropy, we propose a new method to handle missing values in continuous time series data. We use both experimental and simulated datasets to compare the performance (in percentage error) of our proposed method with three currently used methods: skipping the missing values, linear interpolation, and bootstrapping. Unlike the methods that involve modifying the input data, our method modifies the calculation process. This keeps the data unchanged which is less intrusive to the structure of the data. The results demonstrate that our method has a consistent lower average percentage error than other three commonly used methods in multiple common physiological signals. For missing values in common physiological signal type, different data size and generating mechanism, our method can more accurately extract the information contained in continuously monitored data than traditional methods. So it may serve as an effective tool for handling missing values and may have broad utility in analyzing sample entropy for common physiological signals. This could help develop new tools for disease diagnosis and evaluation of treatment effects.

KeywordComplexity Medical Information Missing Values Physiological Data Sample Entropy
DOI10.3390/e21030274
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaPhysics
WOS SubjectPhysics, Multidisciplinary
WOS IDWOS:000464390400001
The Source to ArticleScopus
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Cited Times [WOS]:7   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionFaculty of Health Sciences
Corresponding AuthorZhang X.D.
Affiliation1.School of Software Engineering, South China University of Technology, Guangzhou, 510006, China;
2.Zhuhai Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Zhuhai College of Jilin University, Zhuhai, 519041, China;
3.Faculty of Health Sciences, University of Macau, Taipa, 999078, Macau;
4.Guangdong General Hospital, Guangdong Academy of Medical Science, Guangzhou, 510080, China;
5.Beijing Engineering Research Center of Diagnosis and Treatment of Respiratory and Critical Care Medicine, Beijing Chaoyang Hospital, Beijing, 100043, China;
6.Department of Endocrinology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, China;
7.School of Law, Washington University, St. Louis, MO 63130, United States;
8.Department of Mechanical and Electronic Engineering, Beihang University, Beijing, 100191, China;
9.BARDS, Merck Research Laboratories, Upper Gwynedd, PA 19454, United States
Recommended Citation
GB/T 7714
Dong X.,Chen C.,Geng Q.,et al. An improved method of handling missing values in the analysis of sample entropy for continuous monitoring of physiological signals[J]. Entropy,2019,21(3).
APA Dong X..,Chen C..,Geng Q..,Cao Z..,Chen X..,...&Zhang X.D..(2019).An improved method of handling missing values in the analysis of sample entropy for continuous monitoring of physiological signals.Entropy,21(3).
MLA Dong X.,et al."An improved method of handling missing values in the analysis of sample entropy for continuous monitoring of physiological signals".Entropy 21.3(2019).
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