Eiko Furutani

A Model-Predictive Hypnosis Control System Under Total Intravenous Anesthesia

In ambulatory surgery, anesthetic drugs must be administered at a suitable rate to prevent adverse reactions after discharge from the hospital. To realize more appropriate anesthesia, we have developed a hypnosis control system, which administers propofol as an anesthetic drug to regulate the bispectral index (BIS), an electroencephalography (EEG)-derived index reflecting the hypnosis of a patient. This system consists of three functions: 1) a feedback controller using a model-predictive control method, which can adequately accommodate the effects of time delays; 2) a parameter estimation function of individual differences; and 3) a risk control function for preventing undesirable states such as drug overinfusion or intraoperative arousal. With the approval of the ethics committee of our institute, 79 clinical trials took place since July 2002. The results show that our system can reduce the total amount of propofol infusion and maintain the BIS more accurately than anesthesiologists manual adjustment.

Shifted Popov criterion and stability analysis of fuzzy control systems

The authors derive a shifted Popov criterion, which bridges the gap between the Popov and circle criteria. This criterion is applicable to nonlinear feedback systems whose nonlinearity consists of the main term and deviation term, where the main term is time-invariant and depends only on the output of the linear part, but the deviation term is time-varying and/or depends on variables other than the output. The proof of the theorem uses a lemma obtained in the composite-system analysis as well as a special form of the positive-real lemma. To show the practical significance of the new criterion, a certain type of fuzzy control system is analyzed.<<ETX>>

Novel control system for blood glucose using a model predictive method.

We developed a novel blood glucose control system, using a model predictive method, to achieve optimal control of the blood glucose level in severely diabetic or pancreatectomized patients. This system is designed to predict glucose level changes in advance, considering delayed response time and the administered doses of insulin. This method is also designed to calculate the most appropriate insulin infusion rate by considering differences in individual response to insulin. In this study, we compared our system with a conventional proportional and differential controller (PD controller) to determine whether the new system could regulate the glucose level efficiently in pancreatectomized dogs. The model predictive control method resulted in a significant reduction of mean insulin infusion rate compared with the conventional PD controller (0.71 mU/kg per min vs. 1.81 mU/kg per min, p = 0.0005), when the glucose level in both methods reached the planned target level (100 mg/dl). The new system also tended to have a reduced mean glucose infusion rate for compensating for overshooting of the glucose level compared with the PD controller (0.7 mg/kg per min vs. 1.1 mg/kg per min, p = 0.16). These results indicate that the new system should be a useful tool for regulating the glucose level in severely diabetic patients.

A hypnosis control system using a model predictive controller with online identification of individual parameters

For the purpose of maintaining hypnosis level of patients during general anesthesia appropriately, we have developed a hypnosis control system with a function of online identification of individual parameters. As the control strategy, model predictive control, which can take the dead time included in the bispectral index (BIS) response to propofol infusion into account rigorously, is used. The online identification function obtains pharmacodynamic parameters and the dead time for each individual patient from the BIS response for the first few minutes of anesthesia induction. With the approval by the Ethics Committee of Kyoto University Hospital, the system was applied clinically, and its effectiveness in maintaining hypnosis level accurately and reducing the amount of propofol infusion was confirmed

Clinical Application of a Blood Pressure Autoregulation System during Hypotensive Anesthesia

Abstract. A blood pressure autoregulation system based on the state-predictive control method was developed to minimize intraoperative blood loss and hence avoid blood transfusion. In this report, the system is further improved by incorporating fuzzy logic with a fail-safe function and an individual parameter-identifying function. The safety and stability of this system had been confirmed by preclinical experiments with dogs. Thereafter clinical application with 17 patients was conducted to maintain their mean arterial pressure at around 60 mmHg during major surgery. The use of this system resulted in decreased blood loss and more speedy and accurate surgery due to a clearer surgical field. Unwanted effects of hypotension were not observed clinically or in laboratory tests. This system is therefore safe, stable, and effective in reducing the blood loss during major surgery that otherwise might cause substantial blood loss.

A model predictive sedation control system under total intravenous anesthesia

In ambulatory surgery, anesthetic drug must be administered at an appropriate rate to prevent side effects after discharge from hospital. In this study, we have been developing a sedation control system using a model predictive controller, which uses propofol as the anesthetic drug and the bispectral index (BIS) as the index of sedation, and has an identification function of the individual response and a risk control function for preventing drug over-infusion and intra-operative arousal. After obtaining the approval from the Ethics Committee of Kyoto University Hospital, 80 clinical trials were made from July 2002. The results show that our system can reduce propofol infusion dose, and can maintain the BIS more accurately than manual administration.

Two-degree-of-freedom design method of linear-quadratic servo systems with an integral compensator: analysis of the performance deterioration by the introduction of an observer

This paper studies a two-degree-of-freedom (2DOF) design method of robust servo systems for step references and disturbances in the setting of output feedback. Specifically, we consider the introduction of a state observer and show that the fundamental desirable properties (i.e. 2DOF nature) attained in the state feedback case are inherited, qualitatively speaking, to the output feedback case. At the same time, we quantitatively clarify the performance deterioration about disturbance rejection caused by the introduction of an observer.

How to control blood glucose under continuous glucose challenge

A newly improved method for controlling blood glucose was compared with the standard model predictive controller under continuous glucose infusion. Continuous intravenous glucose infusion at rates of 50 or 100 mg/kg/hour was conducted on pancreatectomized dogs. An improved blood glucose control method using a combination of the proportional controller in the initial stage and the model predictive controller in the later stage was compared with the simple model predictive controller. The parameters of the controller were determined by identifying individual responses to the infused insulin during the first 60 minutes. The parameters of the proportional controller were changed at 60, 90, and 120 minutes to reflect the response to the infused insulin. The simple model predictive controller was able to reach the target level in the usual manner under the low infusion rate of glucose. However, under glucose infusion rates of 100 mg/kg/hour and more, it was difficult to reach the target level within 8 hours. In contrast, the improved system could reach the target level within 5 to 8 hours even under continuous glucose challenge. Addition of the modified proportional controller to the model predictive controller can stabilize the blood glucose control even under continuous glucose infusion.

Comparison of Pharmacokinetic Models for Hypnosis Control Based on Effect-Site Propofol Concentration to Maintain Appropriate Hypnosis

This paper studies an appropriate pharmacokinetic (PK) model for hypnosis control based on effect-site anesthetic concentration. For maintaining hypnosis, methods to keep plasma or effect-site concentration of propofol, an anesthetic drug, calculated using PK models at a target level are often used. In order to realize a desirable hypnosis control by such methods an accurate estimation of propofol concentration corresponding to the threshold of unconsciousness is critical. Since time variation of the calculated propofol concentration depends on the PK model, the performance of maintaining hypnosis also depends on it. In this paper, we compare the existing PK models of propofol focusing on sensitivity and specificity for detecting consciousness during anesthesia by a criterion based on cal ulated propofol concentration and measured aepEX, a hypnosis index. The results show that Barr model provides the highest sensitivity and specificity, and that Marsh, modified Marsh, and Schnider models, which are often used in target controlled infusion systems give fairly high sensitivity and specificity.

Stability condition of a class of nonlinear feedback systems: reduction to a convex problem

This paper gives a new criterion for input-output stability of a class of nonlinear feedback systems. It is most useful in such a practical situation where the nonlinearity in the system is almost time-invariant and memoryless but with slight time-variations and dynamics. It involves two free parameters, and contains the circle criterion and the Popov criterion as special cases. In fact, it extends these two famous criteria in such a way that the conservatism of the circle criterion can be reduced when the time-variations and dynamics of the nonlinearity are relatively small. It is also shown that the existence of the free parameters that fulfill the stability condition can be checked exactly, by reducing it to a convex problem in the frequency domain.