Time-Varying Modeling of Cerebral Hemodynamics

The scientific and clinical importance of cerebral hemodynamics has generated considerable interest in their quantitative understanding via computational modeling. In particular, two aspects of cerebral hemodynamics, cerebral flow autoregulation (CFA) and CO 2 vasomotor reactivity (CVR), have attrac...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:IEEE transactions on biomedical engineering Ročník 61; číslo 3; s. 694 - 704
Hlavní autori: Marmarelis, Vasilis Z., Shin, Dae C., Orme, Melissa, Zhang, Rong
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States IEEE 01.03.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Alzheimer's disease
Blood Pressure
Cerebral flow autoregulation (CFA)
cerebral hemodynamics
Cerebrovascular Circulation - physiology
CO _{2} vasomotor reactivity (CVR)
Cognitive ability
Computational modeling
Data models
Dementia disorders
Hemodynamics
Hemodynamics - physiology
Humans
Hypertension
Kernel
Medical research
Models, Cardiovascular
Photoplethysmography
Physiology
Predictive models
Signal Processing, Computer-Assisted
time-varying modeling
Time-varying systems
Ultrasonography, Doppler, Transcranial
ISSN:0018-9294, 1558-2531, 1558-2531
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:The scientific and clinical importance of cerebral hemodynamics has generated considerable interest in their quantitative understanding via computational modeling. In particular, two aspects of cerebral hemodynamics, cerebral flow autoregulation (CFA) and CO 2 vasomotor reactivity (CVR), have attracted much attention because they are implicated in many important clinical conditions and pathologies (orthostatic intolerance, syncope, hypertension, stroke, vascular dementia, mild cognitive impairment, Alzheimer's disease, and other neurodegenerative diseases with cerebrovascular components). Both CFA and CVR are dynamic physiological processes by which cerebral blood flow is regulated in response to fluctuations in cerebral perfusion pressure and blood CO 2 tension. Several modeling studies to date have analyzed beat-to-beat hemodynamic data in order to advance our quantitative understanding of CFA-CVR dynamics. A confounding factor in these studies is the fact that the dynamics of the CFA-CVR processes appear to vary with time (i.e., changes in cerebrovascular characteristics) due to neural, endocrine, and metabolic effects. This paper seeks to address this issue by tracking the changes in linear time-invariant models obtained from short successive segments of data from ten healthy human subjects. The results suggest that systemic variations exist but have stationary statistics and, therefore, the use of time-invariant modeling yields "time-averaged models" of physiological and clinical utility.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0018-9294
1558-2531
1558-2531
DOI:10.1109/TBME.2013.2287120