Relation between arterial blood pressure and cerebral blood flow velocity in simulated sleep apnea

Gedaa Hassan, Raichel Alex, Gauri Bhave, Mohammad A. Al-Abed, Aditya Bashaboyina, Swathi Iyer, Donald E. Watenpaugh, Rong Zhang, Khosrow Behbehani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Obstructive Sleep Apnea (OSA) is one of the most common breathing disorder, affecting approximately 27% of U.S. adults. Limited data have suggested that OSA causes cerebral autoregulation impairment, thus being an important risk factor to stroke. The objective of this paper is to investigate and measure the relation between arterial blood pressure (BP) and cerebral blood flow velocity (CBFV) in simulated apnea. Sixteen healthy subjects (9 male, 7 female) of 29±4.89 yrs age and body mass index of 24.07±4.84 kg/m2 participated in the study. Four protocols were used; sitting 30 seconds, 90s, and supine 30s and 90s. Our results showed that systolic BP and peak CBFV were correlated with average r=0.672 +0.265. Also, CBFV exhibited a significantly higher percent rise than BP. Thus, our findings suggest that cerebral autoregulation may be impaired during apnea episodes.

Original languageEnglish (US)
Title of host publication2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2012
Pages6349-6352
Number of pages4
DOIs
StatePublished - 2012
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
CountryUnited States
CitySan Diego, CA
Period8/28/129/1/12

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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