Safety Control Architecture for Ventricular Assist Devices
| Autor: | André C. M. Cavalheiro, Diolino J. Santos Filho, Jônatas C. Dias, Aron J. P. Andrade, José R. Cardoso, Marcos S. G. Tsuzuki |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Control and Optimization
Control and Systems Engineering safety instrumented system Mechanical Engineering ventricular assist device Bayesian network Computer Science (miscellaneous) TJ1-1570 cardiovascular diseases Petri net Mechanical engineering and machinery Electrical and Electronic Engineering Industrial and Manufacturing Engineering |
| Zdroj: | Machines, Vol 10, Iss 5, p 5 (2022) |
| ISSN: | 2075-1702 |
| Popis: | In patients with severe heart disease, the implantation of a ventricular assist device (VAD) may be necessary, especially in patients with an indication for heart transplantation. For this, the Institute Dante Pazzanese of Cardiology (IDPC) has developed an implantable centrifugal blood pump that will be able to help a diseased human heart to maintain physiological blood flow and pressure. This device will be used as a totally or partially implantable VAD. Therefore, performance assurance and correct specification of the VAD are important factors in achieving a safe interaction between the device and the patient’s behavior or condition. Even with reliable devices, some failures may occur if the pumping control does not keep up with changes in the patient’s behavior or condition. If the VAD control system has no fault tolerance and no system dynamic adaptation that occurs according to changes in the patient’s cardiovascular system, a number of limitations can be observed in the results and effectiveness of these devices, especially in patients with acute comorbidities. This work proposes the application of a mechatronic approach to this class of devices based on advanced control, instrumentation, and automation techniques to define a method to develop a hierarchical supervisory control system capable of dynamically, automatically, and safely VAD control. For this methodology, concepts based on Bayesian networks (BN) were used to diagnose the patient’s cardiovascular system conditions, Petri nets (PN) to generate the VAD control algorithm, and safety instrumented systems to ensure the safety of the VAD system. |
| Databáze: | OpenAIRE |
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