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Comput Biol Med. 2014 Aug;51:128-39. doi: 10.1016/j.compbiomed.2014.04.013. Epub 2014 May 9.

Modeling and simulation of speed selection on left ventricular assist devices.

Author information

  • 1Biomedical Research Institute-FORTH, GR 45110 Ioannina, Greece; Unit of Medical Technology and Intelligent Information Systems, Dept. of Material Science and Engineering, University of Ioannina, PO Box 1186, GR 45110 Ioannina, Greece.
  • 2Biomedical Research Institute-FORTH, GR 45110 Ioannina, Greece; Department of Economics, University of Ioannina, GR 45110 Ioannina, Greece.
  • 3Nalecz Institute of Biocybernetics and Biomedical Engineering, PAS, Ks. Trojdena 4, 02109 Warsaw, Poland.
  • 4Nalecz Institute of Biocybernetics and Biomedical Engineering, PAS, Ks. Trojdena 4, 02109 Warsaw, Poland; Institute of Clinical Physiology, Section of Pisa, CNR, Via Moruzzi 1 Area di Ricerca San Cataldo, 56124 Pisa, Italy; Institute of Clinical Physiology, Section of Rome, CNR, Via San Martino della Battaglia 44, 00185 Rome, Italy.
  • 5Institute of Clinical Physiology, Section of Pisa, CNR, Via Moruzzi 1 Area di Ricerca San Cataldo, 56124 Pisa, Italy; Institute of Clinical Physiology, Section of Rome, CNR, Via San Martino della Battaglia 44, 00185 Rome, Italy.
  • 63rd Cardiology Department, School of Medicine, University of Athens, Athens, Greece.
  • 7Biomedical Research Institute-FORTH, GR 45110 Ioannina, Greece; Unit of Medical Technology and Intelligent Information Systems, Dept. of Material Science and Engineering, University of Ioannina, PO Box 1186, GR 45110 Ioannina, Greece. Electronic address: fotiadis@cc.uoi.gr.

Abstract

The control problem for LVADs is to set pump speed such that cardiac output and pressure perfusion are within acceptable physiological ranges. However, current technology of LVADs cannot provide for a closed-loop control scheme that can make adjustments based on the patient's level of activity. In this context, the SensorART Speed Selection Module (SSM) integrates various hardware and software components in order to improve the quality of the patients' treatment and the workflow of the specialists. It enables specialists to better understand the patient-device interactions, and improve their knowledge. The SensorART SSM includes two tools of the Specialist Decision Support System (SDSS); namely the Suction Detection Tool and the Speed Selection Tool. A VAD Heart Simulation Platform (VHSP) is also part of the system. The VHSP enables specialists to simulate the behavior of a patient׳s circulatory system, using different LVAD types and functional parameters. The SDSS is a web-based application that offers specialists with a plethora of tools for monitoring, designing the best therapy plan, analyzing data, extracting new knowledge and making informative decisions. In this paper, two of these tools, the Suction Detection Tool and Speed Selection Tool are presented. The former allows the analysis of the simulations sessions from the VHSP and the identification of issues related to suction phenomenon with high accuracy 93%. The latter provides the specialists with a powerful support in their attempt to effectively plan the treatment strategy. It allows them to draw conclusions about the most appropriate pump speed settings. Preliminary assessments connecting the Suction Detection Tool to the VHSP are presented in this paper.

Copyright © 2014 Elsevier Ltd. All rights reserved.

KEYWORDS:

Gaussian mixture model; Heart failure; Speed selection; Suction detection; Ventricular assist device

PMID:
24907416
[PubMed - in process]
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