Analysis of Multifibre Renal Sympathetic Nerve Recordings

  • Dong Li
  • Yingxiong Jin
  • Zhuo Yang
  • Tao Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)


Multifibre renal sympathetic nerve activity (RSNA) recordings represent a nonlinear dynamic system with high dimensionality. In this paper, an effort has been made to effectively remove noises and reduce the dynamics of the multifibre RSNA signals to a simpler form. For this purpose, an improved cluster method combined with the wavelet-transform-based denoising approach is proposed. The outcomes of the present work show that wavelet denoising approach is a useful tool for analyzing multifibre RSNA in rats. Furthermore, compared to the original algorithm of the cluster method, the improved one reduces some aspects of bias.


Sympathetic Nerve Sample Entropy Renal Sympathetic Nerve Activity Nerve Signal Renal Nerve 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Dong Li
    • 1
  • Yingxiong Jin
    • 1
  • Zhuo Yang
    • 2
  • Tao Zhang
    • 1
  1. 1.Key Lab of Bioactive Materials, Ministry of Education and College of Life ScienceNankai UniversityTianjinP.R. China
  2. 2.College of Medicine ScienceNankai UniversityTianjinP.R. China

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