• DocumentCode
    3608547
  • Title

    Compartmental and Data-Based Modeling of Cerebral Hemodynamics: Linear Analysis

  • Author

    Henley, Brandon C. ; Shin, Dae C. ; Zhang, Rong ; Marmarelis, Vasilis Z.

  • Author_Institution
    Dept. of Biomed. Eng., Univ. of Southern California, Los Angeles, CA, USA
  • Volume
    3
  • fYear
    2015
  • fDate
    7/7/1905 12:00:00 AM
  • Firstpage
    2317
  • Lastpage
    2332
  • Abstract
    Compartmental and data-based modeling of cerebral hemodynamics are alternative approaches that utilize distinct model forms and have been employed in the quantitative study of cerebral hemodynamics. This paper examines the relation between a compartmental equivalent circuit and a data-based input-output model of dynamic cerebral autoregulation (DCA) and dynamic CO2-vasomotor reactivity (DVR). The compartmental model is constructed as an equivalent circuit utilizing putative first principles and previously proposed hypothesis-based models. The linear input-output dynamics of this compartmental model are compared with the data-based estimates of the DCA-DVR process. This comparative study indicates that there are some qualitative similarities between the two-input compartmental model and experimental results.
  • Keywords
    brain; haemodynamics; DCA-DVR process; cerebral hemodynamics; data-based input-output model; data-based modeling; dynamic CO2-vasomotor reactivity; dynamic cerebral autoregulation; hypothesis-based models; linear analysis; linear input-output dynamics; two-input compartmental model; Biomedical monitoring; Brain modeling; Cerebral hemodynamics; Compartmental modeling; Data models; Parametric modeling; Cerebral autoregulation; compartmental modeling; nonparametric modeling; vasomotor reactivity;
  • fLanguage
    English
  • Journal_Title
    Access, IEEE
  • Publisher
    ieee
  • ISSN
    2169-3536
  • Type

    jour

  • DOI
    10.1109/ACCESS.2015.2492945
  • Filename
    7300387