Modeling and simulation of speed selection on left ventricular assist devices

Alexandros T. Tzallas, Nikolaos S. Katertsidis, Evaggelos C. Karvounis, Markos G. Tsipouras, George Rigas, Yorgos Goletsis, Krzysztof Zielinski, Libera Fresiello, Arianna Di Molfetta, Gianfranco Ferrari, John V. Terrovitis, Maria Giovanna Trivella, Dimitrios I. Fotiadis*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)128-139
Number of pages12
JournalComputers in biology and medicine
Volume51
DOIs
Publication statusPublished - 1 Aug 2014
Externally publishedYes

Keywords

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

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