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Modeling and simulation of speed selection on left ventricular assist devices
Alexandros T Tzallas1, Nikolaos S Katertsidis1, Evaggelos C Karvounis1
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.
The SensorART Speed Selection Module (SSM) enhances left ventricular assist device (LVAD) management by improving patient treatment and specialist workflow. It offers tools for suction detection and pump speed selection, aiding in better clinical decisions.
Area of Science:
- Biomedical Engineering
- Medical Devices
- Cardiovascular Technology
Background:
- Current left ventricular assist devices (LVADs) lack closed-loop control for activity-based adjustments.
- Effective LVAD management requires precise pump speed settings for physiological ranges.
- Specialist decision-making in LVAD therapy can be improved with advanced support systems.
Purpose of the Study:
- To introduce the SensorART Speed Selection Module (SSM) for enhanced LVAD management.
- To present the Suction Detection Tool and Speed Selection Tool within the Specialist Decision Support System (SDSS).
- To evaluate the accuracy of the Suction Detection Tool and the utility of the Speed Selection Tool for LVAD therapy planning.
Main Methods:
- Integration of hardware and software components into the SensorART SSM.
- Development of the Specialist Decision Support System (SDSS) with specialized tools.
- Utilizing a VAD Heart Simulation Platform (VHSP) for simulating patient circulatory systems.
- Analysis of simulation sessions using the Suction Detection Tool for phenomenon identification.
Main Results:
- The Suction Detection Tool achieved 93% accuracy in identifying suction-related issues during simulations.
- The Speed Selection Tool provides significant support for planning optimal LVAD pump speed settings.
- Preliminary assessments demonstrate the integration and utility of the Suction Detection Tool with the VHSP.
Conclusions:
- The SensorART SSM, including its SDSS tools, improves patient treatment quality and specialist workflow.
- Accurate suction detection and informed speed selection are crucial for effective LVAD therapy.
- The developed system offers a promising approach for optimizing LVAD management and patient outcomes.
