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Integrated Cardiac Electromechanics:...
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Mao, Hongda.
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Integrated Cardiac Electromechanics: Modeling and Personalization.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Integrated Cardiac Electromechanics: Modeling and Personalization./
作者:
Mao, Hongda.
面頁冊數:
120 p.
附註:
Source: Dissertation Abstracts International, Volume: 76-10(E), Section: B.
Contained By:
Dissertation Abstracts International76-10B(E).
標題:
Biomedical engineering. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3706921
ISBN:
9781321811681
Integrated Cardiac Electromechanics: Modeling and Personalization.
Mao, Hongda.
Integrated Cardiac Electromechanics: Modeling and Personalization.
- 120 p.
Source: Dissertation Abstracts International, Volume: 76-10(E), Section: B.
Thesis (Ph.D.)--Rochester Institute of Technology, 2015.
Cardiac disease remains the leading cause of morbidity and mortality in the world. A variety of heart diagnosis techniques have been developed during the last century, and generally fall into two groups. The first group evaluates the electrical function of the heart using electrophysiological data such as electrocardiogram (ECG), while the second group aims to assess the mechanical function of the heart through medical imaging data. Nevertheless, the heart is an integrated electromechanical organ, where its cyclic pumping arises from the synergy of its electrical and mechanical function which requires first to be electrically excited in order to contract. At the same time, cardiac electrical function experiences feedback from mechanical contraction. This inter-dependent relationship determines that neither electrical function nor mechanical function alone can completely reflect the pathophysiological conditions of the heart.
ISBN: 9781321811681Subjects--Topical Terms:
535387
Biomedical engineering.
Integrated Cardiac Electromechanics: Modeling and Personalization.
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Cardiac disease remains the leading cause of morbidity and mortality in the world. A variety of heart diagnosis techniques have been developed during the last century, and generally fall into two groups. The first group evaluates the electrical function of the heart using electrophysiological data such as electrocardiogram (ECG), while the second group aims to assess the mechanical function of the heart through medical imaging data. Nevertheless, the heart is an integrated electromechanical organ, where its cyclic pumping arises from the synergy of its electrical and mechanical function which requires first to be electrically excited in order to contract. At the same time, cardiac electrical function experiences feedback from mechanical contraction. This inter-dependent relationship determines that neither electrical function nor mechanical function alone can completely reflect the pathophysiological conditions of the heart.
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The aim of this thesis is working towards building an integrated framework for heart diagnosis through evaluation of electrical and mechanical functions simultaneously. The basic rational is to obtain quantitative interpretation of a subject-specific heart system by combining an electromechanical heart model and individual clinical measurements of the heart. To this end, we first develop a biologically-inspired mathematical model of the heart that provides a general, macroscopic description of cardiac electromechanics. The intrinsic electromechanical coupling arises from both excitation-induced contraction and deformation-induced mechano-electrical feedback. Then, as a first step towards a fully electromechanically integrated framework, we develop a model-based approach for investigating the effect of cardiac motion on noninvasive transmural imaging of cardiac electrophysiology. Specifically, we utilize the proposed heart model to obtain updated heart geometry through simulation, and further recover the electrical activities of the heart from body surface potential maps (BSPMs) by solving an optimization problem.
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Various simulations of the heart have been performed under healthy and abnormal conditions, which demonstrate the physiological plausibility of the proposed integrated electromechanical heart model. What's more, this work presents the effect of cardiac motion to the solution of noninvasive estimation of cardiac electrophysiology and shows the importance of integrating cardiac electrical and mechanical functions for heart diagnosis. This thesis also paves the road for noninvasive evaluation of cardiac electromechanics.
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