Event-Based control of depth of hypnosis in anesthesia

Improved Individualized Patient-Oriented Depth-of-Hypnosis Measurement Based on Bispectral Index

Total intravenous anesthesia is an anesthesiologic technique where all substances are injected intravenously. The main task of the anesthesiologist is to assess the depth of anesthesia, or, more specifically, the depth of hypnosis (DoH), and accordingly adjust the dose of intravenous anesthetic agents. However, it is not possible to directly measure the anesthetic agent concentrations or the DoH, so the anesthesiologist must rely on various vital signs and EEG-based measurements, such as the bispectral (BIS) index. The ability to better measure DoH is directly applicable in clinical practice-it improves the anesthesiologist's assessment of the patient state regarding anesthetic agent concentrations and, consequently, the effects, as well as provides the basis for closed-loop control algorithms. This article introduces a novel structure for modeling DoH, which employs a residual dynamic model. The improved model can take into account the patient's individual sensitivity to the anesthetic agent, which is not the case when using the available population-data-based models. The improved model was tested using real clinical data. The results show that the predictions of the BIS-index trajectory were improved considerably. The proposed model thus seems to provide a good basis for a more patient-oriented individualized assessment of DoH, which should lead to better administration methods that will relieve the anesthesiologist's workload and will benefit the patient by providing improved safety, individualized treatment, and, thus, alleviation of possible adverse effects during and after surgery.

A modified PID-based control scheme for depth-of-hypnosis control: Design and experimental results

BACKGROUND AND OBJECTIVE

Many methodologies have been proposed for the control of total intravenous anesthesia in general surgery, as this yields a reduced stress for the anesthesiologist and an increased safety for the patient. The objective of this work is to design a PID-based control system for the regulation of the depth of hypnosis by propofol and remifentanil coadministration that takes into account the clinical practice.

METHODS

With respect to a standard PID control system, additional functionalities have been implemented in order to consider specific requirements related to the clinical practice. In particular, suitable boluses are determined and used in the induction phase and a nonzero baseline infusion is used in the maintenance phase when the predicted effect-site concentration drops below a safety threshold.

RESULTS

The modified controller has been experimentally assessed on a group of 10 patients receiving general anesthesia for elective plastic surgery. The control system has been able to induce and maintain adequate anesthesia without any manual intervention from the anesthesiologist.

CONCLUSIONS

Results confirm the effectiveness of the overall design approach and, in particular, highlight that the new version of the control system, with respect to a standard PID controller, provides significant advantages from a clinical standpoint.

Robust PID control of propofol anaesthesia: Uncertainty limits performance, not PID structure

BACKGROUND AND OBJECTIVE

New proposals to improve the regulation of hypnosis in anaesthesia based on the development of advanced control structures emerge continuously. However, a fair study to analyse the real benefits of these structures compared to simpler clinically validated PID-based solutions has not been presented so far. The main objective of this work is to analyse the performance limitations associated with using a filtered PID controller, as compared to a high-order controller, represented through a Youla parameter.

METHODS

The comparison consists of a two-steps methodology. First, two robust optimal filtered PID controllers, considering the effect of the inter-patient variability, are synthesised. A set of 47 validated paediatric pharmacological models, identified from clinical data, is used to this end. This model set provides representative inter-patient variability Second, individualised filtered PID and Youla controllers are synthesised for each model in the set. For fairness of comparison, the same performance objective is optimised for all designs, and the same robustness constraints are considered. Controller synthesis is performed utilising convex optimisation and gradient-based methods relying on algebraic differentiation. The worst-case performance over the patient model set is used for the comparison.

RESULTS

Two robust filtered PID controllers for the entire model set, as well as individual-specific PID and Youla controllers, were optimised. All considered designs resulted in similar frequency response characteristics. The performance improvement associated with the Youla controllers was not significant compared to the individually tuned filtered PID controllers. The difference in performance between controllers synthesized for the model set and for individual models was significantly larger than the performance difference between the individual-specific PID and Youla controllers. The different controllers were evaluated in simulation. Although all of them showed clinically acceptable results, the robust solutions provided slower responses.

CONCLUSION

Taking the same clinical and technical considerations into account for the optimisation of the different controllers, the design of individual-specific solutions resulted in only marginal differences in performance when comparing an optimal Youla parameter and its optimal filtered PID counterpart. The inter-patient variability is much more detrimental to performance than the limitations imposed by the simple structure of the filtered PID controller.

Control strategy with multivariable fault tolerance module for automatic intravenous anesthesia

In the anesthesia automation, an automatic propofol infusion system uses Bi-spectral Index Signal (BIS) as a primary feedback signal to manipulate propofol dose. However, the BIS signal may be suspended for some time due to poor EEG signal quality, noise, and many other factors. Therefore, BIS signal failure may be the main cause of inadequate propofol infusion. This fact motivates the need for integration of multivariable fault tolerance module (MFTM) and fractional-order Smith predictor controller to avoid adverse reactions of inadequate propofol dosing during BIS failure. Smith Predictor control strategy is sufficiently robust to predict feedback BIS during BIS failure via patient pharmacological modeled BIS. However, modeled BIS may not provide a guarantee of adequate propofol infusion during BIS failure and especially in the presence of hypotension and hypertension. Thus, the proposed control strategy is designed with MFTM to detect BIS sensor fault and to estimate feedback BIS during BIS failure. Further, the proposed control strategy is designed with a multivariable pharmacological patient model to analyze the cross effect of propofol infusion on BIS and hemodynamic variables. The robustness of the proposed control strategy is tested in the presence of noxious surgical stimulation, BIS sensor fault and heavy hemodynamic disturbance. The pharmacological parameters and recorded signals of 30 patients during various surgeries have been used to validate simulated results. The performance of the proposed control strategy assures optimization and smooth propofol infusion during BIS failure. The proposed system provides stability for a wide range of physiological parameters range. The proposed scheme maintains smooth BIS and MAP signal despite the delay, BIS sensor fault, and surgical disturbances.