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Published on: August 2, 2016
Mechanistic Assessment of Cardiovascular State Informed by Vibroacoustic Sensors
Ali Zare1, Emily Wittrup1, Kayvan Najarian1,2,3,4
1Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48103, USA.
Abstract:
Monitoring blood pressure, a parameter closely related to cardiovascular activity, can help predict imminent cardiovascular events. In this paper, a novel method is proposed to customize an existing mechanistic model of the cardiovascular system through feature extraction from cardiopulmonary acoustic signals to estimate blood pressure using artificial intelligence. As various factors, such as drug consumption, can alter the biomechanical properties of the cardiovascular system, the proposed method seeks to personalize the mechanistic model using information extracted from vibroacoustic sensors. Simulation results for the proposed approach are evaluated by calculating the error in blood pressure estimates compared to ground truth arterial line measurements, with the results showing promise for this method.
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Preparation of Equipment:
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S1 (First Heart Sound)-
S1 is made by the closure of the mitral and tricuspid valves (atrioventricular valves), marking the beginning of systole.
S2 (Second Heart Sound)-
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