Multiscale sample entropy analysis of wrist pulse blood flow signal for disease diagnosis

Lei Liu, Naimin Li, Wangmeng Zuo, Dapeng Zhang, Hongzhi Zhang

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

13 Citations (Scopus)


Recent study reported that wrist pulse blood flow signal is effective for disease diagnosis. The multiscale entropy, which was developed for quantifying the complexity of a time series of physiological signals over a range of scales, had been widely applied for feature extraction from medical signals. In this paper, using the multiscale sample entropy (Multi-SampEn) algorithm, we compute the value of SampEn of wrist pulse blood flow signal that includes 83 samples healthy persons, 45 samples of patients with liver diseases (LD), and 45 with sugar diabetes (SD). Then we use the values of SampEn as the feature input of the support vector machine classifier for disease diagnosis. Experimental results show that the proposed method could achieve the classification accuracy of 76.30% with the dimension m = 2 and the threshold r = 0.6, which is promising in diagnosing the healthy subjects, liver diseases, and sugar diabetes.
Original languageEnglish
Title of host publicationIntelligent Science and Intelligent Data Engineering - Third Sino-Foreign-Interchange Workshop, IScIDE 2012, Revised Selected Papers
Number of pages8
Publication statusPublished - 1 Dec 2013
Event3rd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2012 - Nanjing, China
Duration: 15 Oct 201217 Oct 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7751 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference3rd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2012


  • Feature extraction
  • Multiscale sample entropy
  • Pulse diagnosis
  • Wrist pulse blood flow signal

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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