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Deriving the Time-Course of the Dominant Frequency of Atrial Fibrillation from a Long Term in vivo Sheep Model using QRST Removal Techniques

Price, Nicholas F.
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1319763800

Abstract Details

2011, Master of Science in Engineering, University of Toledo, College of Engineering.
This thesis document introduces an approach taken to the study of atrial fibrillation (AF) – which is a serious and common heart disorder – using sheep as an in-vivo – inside of the animal – model. The hypothesis that the dominant frequency (DF) of AF increases gradually resulting in self-sustained AF with a persistent left-to-right atrium (LA, RA) DF difference was tested. Induction of AF was achieved using fast atrial pacing (N=8). In-vivo traces were obtained from a lead in the RA and an implantable loop recorder (ILR) in proximity to the LA. Electrocardiogram (ECG) traces were collected from weekly interrogations during 9 to 24 weeks of tachypaced – fast pacing – induced AF, which needed to be processed first by image processing algorithms to transform the traces into a form in which they could be operated on by signal analysis algorithms and then by QRST cancellation algorithms – algorithms designed to remove ventricular activity (VA) – before the fast Fourier transform was applied to obtain the DF values. To evaluate the effectiveness and compare and characterize the strengths and weaknesses of different QRST cancellation algorithms, a series of tests were performed on synthesized ECG traces. The results of these tests demonstrated that a technique based on principal component analysis was the most effective. Using this technique, it was shown that when the first AF episode was detected, the DF increased over a 2-week period (7±0.21 to 9.92±0.31 Hz. N=6, p<0.05) and the DF values obtained from the ILR were significantly higher than those obtained from the RA lead (10.6±0.08 vs. 9.3±0.1 Hz, respectively. N=7, p<0.05). This approach gave insight into the in-vivo time-course and left-to-right gradients during long-term persistent AF, of which little was known about before. These results will help provide a greater understanding of the effects of electrical and structural remodeling that occur during the transition from paroxysmal AF to chronic AF. This research was done in collaboration with the University of Michigan Center for Arrhythmia Research, complied with the National Institute of Health guidelines and was approved by the University of Michigan Committee on Use and Care of Animals.
Vijay Devabhaktuni, PhD (Committee Chair)
Omer Berenfeld, PhD (Committee Member)
Makarand Deo, PhD (Committee Member)
Mansoor Alam, PhD (Committee Member)
Brent Cameron, PhD (Committee Member)
100 p.
Computer Science; Electrical Engineering; Medicine
atrial fibrillation; electrocardiogram; dominant frequency; QRST cancellation; QRST removal; principal component analysis

Recommended Citations

Citations

  • Price, N. F. (2011). Deriving the Time-Course of the Dominant Frequency of Atrial Fibrillation from a Long Term in vivo Sheep Model using QRST Removal Techniques [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1319763800

    APA Style (7th edition)

  • Price, Nicholas. Deriving the Time-Course of the Dominant Frequency of Atrial Fibrillation from a Long Term in vivo Sheep Model using QRST Removal Techniques. 2011. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1319763800.

    MLA Style (8th edition)

  • Price, Nicholas. "Deriving the Time-Course of the Dominant Frequency of Atrial Fibrillation from a Long Term in vivo Sheep Model using QRST Removal Techniques." Master's thesis, University of Toledo, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1319763800

    Chicago Manual of Style (17th edition)

toledo1319763800
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© 2011, all rights reserved.
This open access ETD is published by University of Toledo and OhioLINK.