Merigo Luca, Beschi Manuel, Padula Fabrizio, Latronico Nicola, Paltenghi Massimiliano, Visioli Antonio
Dipartimento di Ingegneria dell'Informazione, University of Brescia, Italy.
Istituto di Tecnologie Industriali e Automazione, National Research Council Milan, Italy.
Comput Methods Programs Biomed. 2017 Aug;147:63-83. doi: 10.1016/j.cmpb.2017.06.007. Epub 2017 Jun 23.
In this paper, we propose the use of an event-based control strategy for the closed-loop control of the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable.
A new event generator with high noise-filtering properties is employed in addition to a PIDPlus controller. The tuning of the parameters is performed off-line by using genetic algorithms by considering a given data set of patients.
The effectiveness and robustness of the method is verified in simulation by implementing a Monte Carlo method to address the intra-patient and inter-patient variability. A comparison with a standard PID control structure shows that the event-based control system achieves a reduction of the total variation of the manipulated variable of 93% in the induction phase and of 95% in the maintenance phase.
The use of event based automatic control in anesthesia yields a fast induction phase with bounded overshoot and an acceptable disturbance rejection. A comparison with a standard PID control structure shows that the technique effectively mimics the behavior of the anesthesiologist by providing a significant decrement of the total variation of the manipulated variable.
在本文中，我们提出使用基于事件的控制策略，通过丙泊酚给药以及将脑电双频指数作为控制变量，对麻醉中催眠深度进行闭环控制。
除了一个PIDPlus控制器外，还采用了一种具有高噪声过滤特性的新型事件发生器。通过使用遗传算法并考虑给定的患者数据集来离线进行参数调整。
通过实施蒙特卡罗方法以解决患者内和患者间的变异性，在模拟中验证了该方法的有效性和鲁棒性。与标准PID控制结构的比较表明，基于事件的控制系统在诱导期使操纵变量的总变化减少了93%，在维持期减少了95%。
在麻醉中使用基于事件的自动控制可产生具有有界超调的快速诱导期和可接受的抗干扰能力。与标准PID控制结构的比较表明，该技术通过显著减少操纵变量的总变化有效地模拟了麻醉医生的行为。
