Modeling and simulation of speed selection on left ventricular assist devices Alexandros T. Tzallas a,b , Nikolaos S. Katertsidis a,b , Evaggelos C. Karvounis a,b , Markos G. Tsipouras a,b , George Rigas a,b , Yorgos Goletsis a,c , Krzysztof Zielinski d , Libera Fresiello d,e,f , Arianna Di Molfetta e,f , Gianfranco Ferrari e,f , John V. Terrovitis g , Maria Giovanna Trivella e,f , Dimitrios I. Fotiadis a,b,n a Biomedical Research Institute-FORTH, GR 45110 Ioannina, Greece b Unit of Medical Technologyand Intelligent Information Systems, Dept. of Material Science and Engineering, University of Ioannina, PO Box 1186, GR 45110 Ioannina, Greece c Department of Economics, University of Ioannina, GR 45110 Ioannina, Greece d Nalecz Institute of Biocybernetics and Biomedical Engineering, PAS, Ks. Trojdena 4, 02109 Warsaw, Poland e Institute of Clinical Physiology, Section of Pisa, CNR, Via Moruzzi 1 Area di Ricerca San Cataldo, 56124 Pisa, Italy f Institute of Clinical Physiology, Section of Rome, CNR, Via San Martino della Battaglia 44, 00185 Rome, Italy g 3rd Cardiology Department, School of Medicine, University of Athens, Athens, Greece article info Article history: Received 13 January 2014 Accepted 16 April 2014 Keywords: Heart failure Ventricular assist device Speed selection Suction detection Gaussian mixture model 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. & 2014 Elsevier Ltd. All rights reserved. 1. Introduction Heart failure (HF) is affecting millions of people in Western Countries every year, and is characterized by impaired ventricular performance, exercise intolerance, and shortened life expectancy. Despite significant advancements in drug therapy, mortality of the disease remains excessively high, as heart transplantation is the only accepted method to treat severe cases. Unfortunately, heart transplantation is limited by the number of donor organs, and therefore Left Ventricular Assist Device (LVAD) support is nowa- days considered an alternative for many cases of end-stage heart failure [1]. In addition, two other roles have recently appeared: “bridge to recovery” and “destination therapy” which guarantee an acceptable quality of life. As the patient recovers and his level of activity increases, the body’s demand for cardiac output increases. The control problem for LVADs is to set the pump speed such that cardiac output (pump Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/cbm Computers in Biology and Medicine http://dx.doi.org/10.1016/j.compbiomed.2014.04.013 0010-4825/& 2014 Elsevier Ltd. All rights reserved. n Corresponding author at: Unit of Medical Technology and Intelligent Informa- tion Systems, Dept. of Material Science and Engineering, University of Ioannina, GR 45110 Ioannina, Greece. Tel.: þ30 26510 08803; fax: þ30 26510 07092. E-mail address: fotiadis@cc.uoi.gr (D.I. Fotiadis). Computers in Biology and Medicine 51 (2014) 128–139