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Author:

Gao, Bin (Gao, Bin.) | Gu, Kaiyun (Gu, Kaiyun.) | Zeng, Yi (Zeng, Yi.) | Chang, Yu (Chang, Yu.) (Scholars:常宇)

Indexed by:

Scopus SCIE PubMed

Abstract:

With the extensive use of the left ventricular assist device (LVAD) as a treatment of heart failure, suction detection has become a key issue that directly affects the treatment. To detect the phenomenon of suction, a blood assistant index (BAI) is defined, which reflects the unloading level of the pump. The BAI is a ratio of the external work of LVAD and the input power of cardiovascular system. Using the theory of model-free adaptive control algorithm, an anti-suction controller, which chooses the heart rate and BAI as control variables, is designed. As a key feature, the proposed control algorithm adjusts the pump speed according to not only the blood demand of circulatory system but also the function of the native heart. Subsequently, the performance and robustness of the controller are evaluated using a numerical simulation of the assisted circulation and an in vitro experiment. The simulation and experimental results demonstrate that the BAI detects the suction occur accurately, and the controller can maintain the heart rate and BAI tracking the reference values with a response time of less than 6 s.

Keyword:

Heart rate Anti-suction control Model-free adaptive control Blood assistant index Intra-aortic pump

Author Community:

  • [ 1 ] [Gao, Bin]Beijing Univ Technol, Sch Life Sci & BioEngn, Beijing 100124, Peoples R China
  • [ 2 ] [Gu, Kaiyun]Beijing Univ Technol, Sch Life Sci & BioEngn, Beijing 100124, Peoples R China
  • [ 3 ] [Zeng, Yi]Beijing Univ Technol, Sch Life Sci & BioEngn, Beijing 100124, Peoples R China
  • [ 4 ] [Chang, Yu]Beijing Univ Technol, Sch Life Sci & BioEngn, Beijing 100124, Peoples R China

Reprint Author's Address:

  • 常宇

    [Chang, Yu]Beijing Univ Technol, Sch Life Sci & BioEngn, Beijing 100124, Peoples R China

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Source :

ARTIFICIAL ORGANS

ISSN: 0160-564X

Year: 2012

Issue: 3

Volume: 36

Page: 275-U183

2 . 4 0 0

JCR@2022

ESI Discipline: CLINICAL MEDICINE;

JCR Journal Grade:2

CAS Journal Grade:3

Cited Count:

WoS CC Cited Count: 17

SCOPUS Cited Count: 20

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

Online/Total:1648/10960036
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