• DocumentCode
    307423
  • Title

    An adaptive algorithm for accurate estimation of pulse-wave velocity and attenuation

  • Author

    Jing, Wanc ; Liangjun, Wenc ; Jingzhi, Chenc

  • Author_Institution
    Dept. of Biomed. Eng., Xi´´an Jiaotong Univ., China
  • Volume
    1
  • fYear
    1995
  • fDate
    20-25 Sep 1995
  • Firstpage
    133
  • Abstract
    A new approach for accurate estimation of pulse wave velocity (PWV) and attenuation is introduced. PWV has been invoked as an important parameter for quantitatively assessment of the elasticity of arterial walls. By transforming the wave harmonic component from real to complex, the method described here can precisely extract the phase difference and the modulus difference between neighboring signals, thus ensures accurate estimation of the velocity and the attenuation of wave component. Analysis and simulation results reveal that the accuracy and the needed data amount of the algorithm are independent of sampling frequency, while convergence time shows dependence upon sampling frequency. The higher the sampling frequency, the shorter the convergence time. More importantly, within one or two sampled points, the estimation has already reached efficient accuracy
  • Keywords
    adaptive signal processing; algorithm theory; haemodynamics; medical signal processing; velocity measurement; accurate estimation; adaptive algorithm; arterial walls elasticity; convergence time; modulus difference; neighboring signals; pulse-wave attenuation; pulse-wave velocity; sampling frequency; wave component; Adaptive algorithm; Arteries; Attenuation; Convergence; Data mining; Elasticity; Frequency; Independent component analysis; Phase estimation; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 1995., IEEE 17th Annual Conference
  • Conference_Location
    Montreal, Que.
  • Print_ISBN
    0-7803-2475-7
  • Type

    conf

  • DOI
    10.1109/IEMBS.1995.575036
  • Filename
    575036