Analysis of Blood Flow Velocity and Pressure Signals using the Multipulse Method

  • Received: 01 January 2006 Accepted: 29 June 2018 Published: 01 February 2006
  • MSC : 92D30.

  • This paper shows how the multipulse method from digital signal processing can be used to accurately synthesize signals obtained from blood pressure and blood flow velocity sensors during posture change from sitting to standing. The multipulse method can be used to analyze signals that are composed of pulses of varying amplitudes. One of the advantages of the multipulse method is that it is able to produce an accurate and efficient representation of the signals at high resolution. The signals are represented as a set of input impulses passed through an autoregressive (AR) filter. The parameters that define the AR filter can be used to distinguish different conditions. In addition, the AR coefficients can be transformed to tube radii associated with digital wave guides, as well as pole-zero representation. Analysis of the dynamics of the model parameters have potential to provide better insight and understanding of the underlying physiological control mechanisms. For example, our data indicate that the tube radii may be related to the diameter of the blood vessels.

    Citation: Derek H. Justice, H. Joel Trussell, Mette S. Olufsen. Analysis of Blood Flow Velocity and Pressure Signals using the Multipulse Method[J]. Mathematical Biosciences and Engineering, 2006, 3(2): 419-440. doi: 10.3934/mbe.2006.3.419

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  • This paper shows how the multipulse method from digital signal processing can be used to accurately synthesize signals obtained from blood pressure and blood flow velocity sensors during posture change from sitting to standing. The multipulse method can be used to analyze signals that are composed of pulses of varying amplitudes. One of the advantages of the multipulse method is that it is able to produce an accurate and efficient representation of the signals at high resolution. The signals are represented as a set of input impulses passed through an autoregressive (AR) filter. The parameters that define the AR filter can be used to distinguish different conditions. In addition, the AR coefficients can be transformed to tube radii associated with digital wave guides, as well as pole-zero representation. Analysis of the dynamics of the model parameters have potential to provide better insight and understanding of the underlying physiological control mechanisms. For example, our data indicate that the tube radii may be related to the diameter of the blood vessels.


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  • © 2006 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
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