Intelligent embedded system for physiological control of ventricular assist devices in health 4.0 Background

Abstract

The use of Left Ventricular Assist Devices (LVADs) has proven to be an effective treatment option for Congestive Heart Failure (CHF) patients who are not eligible for heart transplantation. These devices can serve as a bridge to heart transplantation (BTT) or as destination therapy (DT). While LVADs operate at a constant flow, this can affect the patient's quality of life and survival rate. To address this issue, Health 4.0 (H4) has developed new technological resources to personalize control systems and integrate medical devices into treatment. In this effort, a Physiological Control of LVAD (PC-LVAD) system was implemented within the H4 platform, using an Intelligent Embedded System (IES). The IES was developed using the MyRIO® development platform and tools such as LabVIEW® FPGA and RT, Quartus II® EDA, and MATLAB®. To evaluate its performance, preliminary criteria were assessed in experimental tests, analyzing the Internet of Things (IoT) characterization and applying best practices for information security. The results of the experimental tests showed that the IES could store and transmitting data in real-time to a graphical interface, and the data were found to be consistent with external measuring instruments.

Embedded Cyber-Physical System for Physiological Control of Ventricular Assist Devices

“…However, in this case, the MOPC-EIS shows an advantage in accuracy with two fewer points outside the 5% error range and smaller error values, while the MOPC-PC shows a slight tendency to overestimate the flow. The percentage error of the flow estimator was 3.33 ± 0.92%, in agreement with Leao et al [28] and other estimators [30][31][32][33][34][35][36][37][38][39][40][41][42]. The percentage error of the differential pressure estimator was 1.93 ± 0.7%, in agreement with Leao et al [28] and other estimators.…”

“…However, on the other hand, in vitro testing presents significantly more complex adversities than those that may be encountered in a virtual environment. Therefore, the error obtained in the proposal of this study can be considered satisfactory considering the specialized literature in this field [30][31][32][33][34][35][36][37][38][39][40][41][42]. Nevertheless, in vivo testing also presents even higher levels of complexity that cannot be replicated in an in vitro study, and new studies under these conditions will always be necessary.…”

“…Fass and Gechter [32] introduced a framework for modeling systems, classifying system dimensions into structural elements, shapes/forms, and dynamics. A PC LVAD was presented within a Health 4.0 framework running on an embedded system [33].…”

“…In line with this paradigm, our research group has introduced a PC-LVAD within a Health 4.0 framework. This PC-LVAD, running on an embedded system, represents a practical implementation model for intelligent controllers within this emerging line of research [33]. By integrating the principles of the isomorphic framework with the capabilities of Health 4.0 technologies, our work aims to improve the functionality and adaptability of mechanical circulatory support systems, ultimately improving patient outcomes and advancing the field of personalized medicine.…”