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
fDate :
7/7/1905 12:00:00 AM
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;
Journal_Title :
Access, IEEE
DOI :
10.1109/ACCESS.2015.2492945