Detection of synchrony in biosignals using cross fuzzy entropy

Hong Bo Xie, Yongping Zheng, Jing Yi Guo

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

A new method, namely Cross fuzzy entropy (C-FuzzyEn) analysis, that could enable the measurement of the synchrony or similarity of patterns between two distinct signals, was presented in this study. Tests on simulated data sets showed that C-FuzzyEn was superior to the conventional cross sample entropy (C-SampEn) in several aspects, including giving entropy definition in case of small parameters, better relative consistency, and less dependence on record length. The proposed C-FuzzyEn was then applied for the analysis of simultaneously recorded electromyography (EMG) and mechanomyography (MMG) signals during sustained isometric contraction for monitoring local muscle fatigue. The results showed that the C-FuzzyEn of EMG-MMG decreased significantly during the development of muscle fatigue. The time-decrease trend of C-FuzzyEn is similar to the mean frequency (MNF) of EMG, the commonly used muscle fatigue indicator.
Original languageEnglish
Title of host publicationProceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationEngineering the Future of Biomedicine, EMBC 2009
PublisherIEEE Computer Society
Pages2971-2974
Number of pages4
ISBN (Print)9781424432967
DOIs
Publication statusPublished - 1 Jan 2009
Event31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009 - Minneapolis, MN, United States
Duration: 2 Sept 20096 Sept 2009

Conference

Conference31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Country/TerritoryUnited States
CityMinneapolis, MN
Period2/09/096/09/09

ASJC Scopus subject areas

  • Cell Biology
  • Developmental Biology
  • Biomedical Engineering
  • General Medicine

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