Analysis of heart rate variability using fuzzy measure entropy

Chengyu Liu; Ke  Li; Lina  Zhao; Feng  Liu; Dingchang Zheng; Changchun Liu; Shutang  Liu

doi:10.1016/j.compbiomed.2012.11.005

Analysis of heart rate variability using fuzzy measure entropy

Chengyu Liu, Ke Li, Lina Zhao, Feng Liu, Dingchang Zheng, Changchun Liu, Shutang Liu

Research output: Contribution to journal › Article › peer-review

124 Citations (Scopus)

Abstract

This paper proposed a new entropy measure, Fuzzy Measure Entropy (FuzzyMEn), for the analysis of heart rate variability (HRV) signals. FuzzyMEn was calculated based on the fuzzy set theory and improved the poor statistical stability in the approximate entropy (ApEn) and sample entropy (SampEn). The simulation results also demonstrated that the FuzzyMEn had better algorithm discrimination ability when compared with the recently published fuzzy entropy (FuzzyEn), The validity of FuzzyMEn was tested for clinical HRV analysis on 120 subjects (60 heart failure and 60 healthy control subjects). It is concluded that FuzzyMEn could be considered as a valid and reliable method for a clinical HRV application.

Original language	English
Pages (from-to)	100-108
Number of pages	8
Journal	Computers in Biology and Medicine
Volume	43
Issue number	2
Early online date	27 Dec 2012
DOIs	https://doi.org/10.1016/j.compbiomed.2012.11.005
Publication status	Published - 1 Feb 2013
Externally published	Yes

Keywords

Fuzzy measure entropy
Heart rate variability
Entropy measure
Electrocardiogram
RR sequence
Fuzzy entropy

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10.1016/j.compbiomed.2012.11.005

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title = "Analysis of heart rate variability using fuzzy measure entropy",

abstract = "This paper proposed a new entropy measure, Fuzzy Measure Entropy (FuzzyMEn), for the analysis of heart rate variability (HRV) signals. FuzzyMEn was calculated based on the fuzzy set theory and improved the poor statistical stability in the approximate entropy (ApEn) and sample entropy (SampEn). The simulation results also demonstrated that the FuzzyMEn had better algorithm discrimination ability when compared with the recently published fuzzy entropy (FuzzyEn), The validity of FuzzyMEn was tested for clinical HRV analysis on 120 subjects (60 heart failure and 60 healthy control subjects). It is concluded that FuzzyMEn could be considered as a valid and reliable method for a clinical HRV application.",

keywords = "Fuzzy measure entropy, Heart rate variability, Entropy measure, Electrocardiogram, RR sequence, Fuzzy entropy",

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T1 - Analysis of heart rate variability using fuzzy measure entropy

AU - Liu, Chengyu

AU - Li, Ke

AU - Zhao, Lina

AU - Liu, Feng

AU - Zheng, Dingchang

AU - Liu, Changchun

AU - Liu, Shutang

PY - 2013/2/1

Y1 - 2013/2/1

N2 - This paper proposed a new entropy measure, Fuzzy Measure Entropy (FuzzyMEn), for the analysis of heart rate variability (HRV) signals. FuzzyMEn was calculated based on the fuzzy set theory and improved the poor statistical stability in the approximate entropy (ApEn) and sample entropy (SampEn). The simulation results also demonstrated that the FuzzyMEn had better algorithm discrimination ability when compared with the recently published fuzzy entropy (FuzzyEn), The validity of FuzzyMEn was tested for clinical HRV analysis on 120 subjects (60 heart failure and 60 healthy control subjects). It is concluded that FuzzyMEn could be considered as a valid and reliable method for a clinical HRV application.

AB - This paper proposed a new entropy measure, Fuzzy Measure Entropy (FuzzyMEn), for the analysis of heart rate variability (HRV) signals. FuzzyMEn was calculated based on the fuzzy set theory and improved the poor statistical stability in the approximate entropy (ApEn) and sample entropy (SampEn). The simulation results also demonstrated that the FuzzyMEn had better algorithm discrimination ability when compared with the recently published fuzzy entropy (FuzzyEn), The validity of FuzzyMEn was tested for clinical HRV analysis on 120 subjects (60 heart failure and 60 healthy control subjects). It is concluded that FuzzyMEn could be considered as a valid and reliable method for a clinical HRV application.

KW - Fuzzy measure entropy

KW - Heart rate variability

KW - Entropy measure

KW - Electrocardiogram

KW - RR sequence

KW - Fuzzy entropy

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JO - Computers in Biology and Medicine

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Analysis of heart rate variability using fuzzy measure entropy

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