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Arrhythmic pulses detection using Lempel-Ziv complexity analysis

  • Lisheng Xu*
  • , David Zhang
  • , Kuanquan Wang
  • , Lu Wang
  • *Corresponding author for this work
  • School of Computer Science and Technology, Harbin Institute of Technology
  • Biomedical Engineering Society of Heilongjiang Province
  • Hong Kong Polytechnic University
  • Biometrics Technology Center (UGC/CRC
  • Tsinghua University
  • Shanghai Jiao Tong University
  • Beihang University
  • Harbin Institute of Technology
  • University of Waterloo
  • Southwest University
  • IEEE
  • The University of Hong Kong

Research output: Contribution to journalArticlepeer-review

Abstract

Computerized pulse analysis based on traditional Chinese medicine (TCM) is relatively new in the field of automatic physiological signal analysis and diagnosis. Considerable researches have been done on the automatic classification of pulse patterns according to their features of position and shape, but because arrhythmic pulses are difficult to identify, until now none has been done to automatically identify pulses by their rhythms. This paperproposes a novel approach to the detection of arrhythmic pulses using the Lempel-Ziv complexity analysis. Four parameters, one lemma, and two rules, which are the results of heuristic approach, are presented. This approach is applied on 140 clinic pulses for detecting seven pulse patterns, not only achieving a recognition accuracy of 97.1% as assessed by experts in TCM, but also correctly extracting the periodical unit of the intermittent pulse.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalEurasip Journal on Applied Signal Processing
Volume2006
DOIs
StatePublished - 2006

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