Šajić Jasmina Lozanović, Langthaler Sonja, Schröttner Jörg, Baumgartner Christian
Institute of Health Care Engineering with European Testing Center of Medical Devices, Graz University of Technology, Austria.
Innovation Center of the Faculty of Mechanical Engineering, University of Belgrade, Kraljice Marije 16, Belgrade, Serbia.
IFAC Pap OnLine. 2022;55(4):19-24. doi: 10.1016/j.ifacol.2022.06.003. Epub 2022 Jul 20.
This paper presents applications of control system theory in biomedical engineering. These methodologies are used in engineering sciences to obtain a mathematical model of systems, but system identification as scientific methodology is rarely used in biomedical engineering. The paper presents exemplarily control theory and system identification as methods for obtaining a mathematical model of the spread SARS-CoV-2 virus. The models obtained in the course of this are data-driven and strongly data-dependent. The available dataset allowed us to consider a model of a pandemic spread in the context of both the number of tested individuals and the number of infected individuals and with a resultant model that is nonlinear. We also considered a mathematical model for the dependence between the number of confirmed infected individuals and the number of deaths caused by the disease. The resulting model is linear given with the transfer function corresponding to the second-order differential equation. The mathematical models developed were additionally analyzed in accordance with controllability and observability.
本文介绍了控制系统理论在生物医学工程中的应用。这些方法在工程科学中用于获取系统的数学模型，但作为科学方法的系统识别在生物医学工程中很少使用。本文示例性地介绍了控制理论和系统识别，作为获取SARS-CoV-2病毒传播数学模型的方法。在此过程中获得的模型是数据驱动的，并且强烈依赖数据。可用数据集使我们能够在检测个体数量和感染个体数量的背景下考虑大流行传播模型，并且得到的模型是非线性的。我们还考虑了确诊感染个体数量与该疾病导致的死亡数量之间相关性的数学模型。得到的模型是线性的，由对应于二阶微分方程的传递函数给出。此外，还根据可控性和可观测性对所开发的数学模型进行了分析。
