Evaluation of Fluid Resuscitation Control Algorithms via a Hardware-in-the-Loop Test Bed
Evaluation of Fluid Resuscitation Control Algorithms via a Hardware-in-the-Loop Test Bed
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DOI：
10.1109/tbme.2019.2915526
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发表时间：
2020-02-01
影响因子：
4.6
通讯作者：
Scully, Christopher G.
中科院分区：
文献类型：
--
作者：
Mirinejad, Hossein;Parvinian, Bahram;Scully, Christopher G.
目的：本文提出了一个硬件在环（HIL）测试平台，用于评估液体复苏控制算法的性能。所提出的平台是一个网络物理系统，它将物理设备与计算模型和基于计算机的算法集成在一起。方法：根据计算机和体内数据对 HIL 测试台进行评估，以确保在所提出的平台中正确预测血流动力学变量。然后，该测试台用于研究两种液体复苏控制算法的性能：决策表（基于规则）和比例积分微分 (PID) 控制器。结果：测试台的统计评估表明，在 HIL 测试台、计算机实施和体内数据中观察到类似的结果，验证了 HIL 测试台可以充分预测血流动力学响应。两种液体复苏控制器的比较表明，两种控制器都能随着时间的推移稳定血流动力学变量，并且具有相似的速度来有效地达到血流动力学终点的目标水平。然而，对于 HIL 平台中测试的场景，PID 控制器的精度高于基于规则的控制器。结论：结果证明了 HIL 测试台通过将物理设备与生理学和干扰计算模型相结合来实际测试生理控制器的潜力。意义：这种类型的测试能够相对快速地评估生理闭环控制系统，以帮助迭代设计过程，并为现有技术（例如计算机、体内和临床研究）提供补充手段，以针对各种干扰和场景测试此类系统。
Objective: This paper presents a hardware-in-the-loop (HIL) testing platform for evaluating the performance of fluid resuscitation control algorithms. The proposed platform is a cyber-physical system that integrates physical devices with computational models and computer-based algorithms. Methods: The HIL test bed is evaluated against in silico and in vivo data to ensure the hemodynamic variables are appropriately predicted in the proposed platform. The test bed is then used to investigate the performance of two fluid resuscitation control algorithms: a decision table (rule-based) and a proportional-integral-derivative (PID) controller. Results: The statistical evaluation of test bed indicates that similar results are observed in the HIL test bed, in silico implementation, and the in vivo data, verifying that the HIL test bed can adequately predict the hemodynamic responses. Comparison of the two fluid resuscitation controllers reveals that both controllers stabilized hemodynamic variables over time and had similar speed to efficiently achieve the target level of the hemodynamic endpoint. However, the accuracy of the PID controller was higher than the rule-based for the scenarios tested in the HIL platform. Conclusion: The results demonstrate the potential of the HIL test bed for realistic testing of physiologic controllers by incorporating physical devices with computational models of physiology and disturbances. Significance: This type of testing enables relatively fast evaluation of physiologic closed-loop control systems to aid in iterative design processes and offers complementary means to existing techniques (e.g., in silico, in vivo, and clinical studies) for testing of such systems against a wide range of disturbances and scenarios.