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A Method for the Detection of Singularity in Pulse

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Advances on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC 2016)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 1))

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Abstract

The principle of wavelet transform (WT) about the singularity detection was used to reveal the rich cardiovascular physiological and pathological information of the pulse in this paper. The heart systole and diastole were determined accurately by the acquired WT modulus maxima figures and the detected breakpoints of the pulses. It is found that there are obvious differences in the rate of pulse wave and the ratio of the diastole and systole between the normal and the heart patient through a large number of the experimental analysis and statistics of signals, which provides a quantitative reference for some diagnosis of cardiac diseases.

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Author information

Authors and Affiliations

  1. Department of Information Engineering, Engineering University of the Chinese People’s Armed Police, Xi’an, 710086, China

    Wei Qi

  2. College of Equipment Engineering, Engineering University of the Chinese People’s Armed Police, Xi’an, 710086, China

    Hongwei Zhuang

  3. Department of Electronic Technology, Engineering University of the Chinese People’s Armed Police, Xi’an, 710086, China

    Liqiong Zhang

Authors
  1. Wei Qi
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  2. Hongwei Zhuang
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  3. Liqiong Zhang
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Corresponding author

Correspondence to Wei Qi .

Editor information

Editors and Affiliations

  1. Campus Nord,Ed. Omega (Room 109), Technical University of Catalonia Campus Nord,Ed. Omega (Room 109), Barcelona, Spain

    Fatos Xhafa

  2. Fukuoka Institute of Technology , Fukuoka, Japan

    Leonard Barolli

  3. Federico II, Università degli Studi di Napoli Federico II, Napoli, Italy

    Flora Amato

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Qi, W., Zhuang, H., Zhang, L. (2017). A Method for the Detection of Singularity in Pulse. In: Xhafa, F., Barolli, L., Amato, F. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2016. Lecture Notes on Data Engineering and Communications Technologies, vol 1. Springer, Cham. https://doi.org/10.1007/978-3-319-49109-7_51

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  • DOI: https://doi.org/10.1007/978-3-319-49109-7_51

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49108-0

  • Online ISBN: 978-3-319-49109-7

  • eBook Packages: EngineeringEngineering (R0)

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