Title

A New Method For Detecting Aortic Valve Dynamics During Control Of The Rotary Left Ventricular Assist Device Support

Keywords

Biological systems; Biomedical; Simulation

Abstract

The rotary Left Ventricular Assist Device (LVAD) has largely been used as a destination therapy device for patients with congestive heart failure who are awaiting heart transplantation. In recent years, however, the device has also been used as a bridge to recovery device for patients whose heart condition might recover as a result of the LVAD support. In this latter case, the aortic valve dynamics under normal physiological conditions (i.e. continuously opening and closing in each cardiac cycle) plays an important role in the LVAD accomplishing its role as a bridge to recovery device. Serious complications can result if the aortic valve closes permanently during the LVAD support. Therefore, a reliable technique for detecting the aortic valve dynamics is crucial. This paper presents a new method that can predict working patterns of the aortic valve, based on an indicator derived from the systemic vascular current signal in the circulatory system to make a decision about whether the aortic valve is open or permanently closed. The proposed method has been tested using a nonlinear mathematical model of the combined cardiovascular-LVAD system. The simulation results show that the proposed method can detect the aortic valve dynamics effectively. The ability of the proposed method to detect the aortic valve dynamics provides a reliable platform for the development of a feedback control system to control the power, and hence rotational speed, of the LVAD, to ensure that the aortic valve opens and closes properly within each cardiac cycle to allow blood to flow from the left ventricle into the aorta. © 2014 American Automatic Control Council.

Publication Date

1-1-2014

Publication Title

Proceedings of the American Control Conference

Number of Pages

5471-5476

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/ACC.2014.6858842

Socpus ID

84905707071 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84905707071

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