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Closed-Loop Administration of Propofol Guided by the NeuroSense: Clinical Evaluation Using Robust Proportional- Integral-Derivative Design
... In this problem setting, with large variability, relatively simple drug dynamics and low performance criteria, robust PID control can be expected to perform adequately. We have shown feasibility of robust PID control of propofol in both adults and children [14]- [16]. We have demonstrated that uncertainty is indeed an important factor limiting the performance, and that limited performance improvement can be expected from controllers with more complexity, unless strategies that reduce the uncertainty are implemented [17]. ...
... The minimal and maximal Bode magnitude of the set scaled with w a lo is shown for patients aged 6-10 in red, and patients aged 11-16 in blue. The minimal and maximal magnitudes for the model set scaled with body weight are shown in black (aged 6-10) and grey (aged[11][12][13][14][15][16]. ...
Objective:
The goal of this paper was to optimize robust PID control for propofol anesthesia in children aged 5-10 years to improve performance, particularly to decrease the time of induction of anesthesia while maintaining robustness.
Methods:
We analyzed results of a previous study conducted by our group to identify opportunities for system improvement. Allometric scaling was introduced to reduce the interpatient variability and a new robust PID controller was designed using an optimization-based method. We evaluated this optimized design in a clinical study involving 16 new cases.
Results:
The optimized controller design achieved the performance predicted in simulation studies in the design stage. Time of induction of anesthesia was median [Q1, Q3] 3.7 [2.3, 4.1] min and the achieved global score was 13.4 [9.9, 16.8].
Conclusion:
Allometric scaling reduces the interpatient variability in this age group and allows for improved closed-loop performance. The uncertainty described by the model set, the predicted closed-loop responses, and the predicted robustness margins are realistic. The system meets the design objectives of improved speed of induction of anesthesia while maintaining robustness and improving clinically relevant system behavior.
Significance:
Control system optimization and ongoing system improvements are essential to the development of a clinically relevant commercial device. This paper demonstrates the validity of our approach, including system modeling, controller optimization, and pre-clinical testing in simulation.
... The following examples are taken from 45 cases of closedloop controlled propofol infusion guided by the W AV CN S measure provided by the NeuroSENSE monitor (Neu-roWave Systems Inc., Cleveland Heights, USA). The system is described in Dumont et al. [2011]. The software was approved by Health Canada for clinical evaluation. ...
... In these scenarios propofol infusion is controlled by the PID controller used in the clinical study discussed in Section 2.2 and described in Dumont et al. [2011]. The setpoint is fixed to 50 , monitor dynamics are included in the simulation (see Bibian et al. [2006]). ...
Feasibility of closed-loop anesthesia has been shown in a number of clinical studies. Demonstration of patient safety will be essential to convince regulatory authorities of the benefits of such systems. This paper considers safety constraints for closed-loop propofol anesthesia based on its therapeutic range. Simulation scenarios are proposed for evaluation of control strategies in the presence of these constraints. The scenarios reproduce realistic situations encountered in clinical practice. Using the proposed scenarios, the performance of L2 anti-windup is compared to sliding mode reference conditioning and to back-calculation anti-windup. It is concluded that L2 anti-windup might not be appropriate for this problem. The sliding mode solution results in behaviour comparable to the Hanus conditioned controller and there seems to be no need for fast switching. The back-calculation anti-windup performs well in a variety of situations.
... Studies with adult patients have shown that closed-loop control of intravenous propofol administration is clinically feasible for the maintenance of anesthesia (3)(4)(5)(6)(7)(8)(9), and closed-loop induction of anesthesia has been demonstrated (7). We have previously reported the feasibility of automating both induction and maintenance of propofol anesthesia in adults using a simple robustly tuned proportional-integral-derivative (PID) controller (10). ...
... Response to verbal commands occurred at a median of 12 min (IQR [8][9][10][11][12][13][14][15][16][17][18][19] and discharge from PACU at a median of 30 min (IQR 25-38) following termination of the propofol infusion. ...
During closed-loop control, a drug infusion is continually adjusted according to a measure of clinical effect (e.g., an electroencephalographic depth of hypnosis (DoH) index). Inconsistency in population-derived pediatric pharmacokinetic/pharmacodynamic models and the large interpatient variability observed in children suggest a role for closed-loop control in optimizing the administration of intravenous anesthesia.
To clinically evaluate a robustly tuned system for closed-loop control of the induction and maintenance of propofol anesthesia in children undergoing gastrointestinal endoscopy.
One hundred and eight children, aged 6–17, ASA I-II, were enrolled. Prior to induction of anesthesia, NeuroSENSE™ sensors were applied to obtain the WAVCNS DoH index. An intravenous cannula was inserted and lidocaine (0.5 mg·kg−1) administered. Remifentanil was administered as a bolus (0.5 μg·kg−1), followed by continuous infusion (0.03 μg·kg−1·min−1). The propofol infusion was closed-loop controlled throughout induction and maintenance of anesthesia, using WAVCNS as feedback.
Anesthesia was closed-loop controlled in 102 cases. The system achieved and maintained an adequate DoH without manual adjustment in 87/102 (85%) cases. Induction of anesthesia (to WAVCNS ≤ 60) was completed in median 3.8 min (interquartile range (IQR) 3.1–5.0), culminating in a propofol effect-site concentration (Ce) of median 3.5 μg·ml−1 (IQR 2.7–4.5). During maintenance of anesthesia, WAVCNS was measured within 10 units of the target for median 89% (IQR 79–96) of the time. Spontaneous breathing required no manual intervention in 91/102 (89%) cases.
A robust closed-loop system can provide effective propofol administration during induction and maintenance of anesthesia in children. Wide variation in the calculated Ce highlights the limitation of open-loop regimes based on pharmacokinetic/pharmacodynamic models.
... Fig. 2 shows the block diagram of the simulated closed-loop anesthesia control system which includes the extended safety system. The PID controller tuned by Dumont et al. (2011) for closed-loop anesthesia is employed. Moreover, the back-calculation anti-windup strategy as suggested by van Heusden et al. (2014) is included in this scheme. ...
Closed-loop anesthesia drug delivery systems can reduce the effect of inter-patient variability, minimize variability in desired clinical effects, and ultimately improve patient safety. Feasibility of closed-loop anesthesia has been clinically evaluated in a number of studies. To obtain regulatory approval to use closed-loop anesthesia as a clinical device, patient safety must be demonstrated. Safety systems for closed-loop anesthesia have been proposed to limit anesthetic concentrations in the plasma and effect-site. Such safety systems minimize the risk of drug under/overdosing. Anesthetic drugs have serious side effects and can significantly reduce blood pressure, thereby jeopardizing patient safety. This paper discusses a safety system that includes safety constraints on blood pressure in addition to the plasma and effect-site concentrations. The proposed safety system is formalized using formal model verification techniques. The performance of closed-loop anesthesia in the presence of constraints on the plasma and effect-site concentrations as well as blood pressure is shown using simulation results. The effectiveness of the proposed safety system is also illustrated in simulation using a realistic clinical scenario. This paper shows that maintaining blood pressure within safety constraints increases the time for anesthesia induction, especially for patients whose blood pressure is more sensitive to anesthetics. For this population, clinical intervention such as administration of vasoactive drugs may be required to counter the effect of propofol on blood pressure during closed-loop anesthesia to achieve a safe yet sufficiently fast induction. This paper extends a previously published formalized safety system which guarantees that the plasma and effect-site concentrations remain within safety limits (Yousefi et al., 2017).
... We employ the PID controller robustly tuned by Dumont et al. [48] to achieve the closed-loop goal. We include backcalculation anti-windup suggested by van Heusden et al. [1] to improve the performance of the PID controller when the safety constraints are active. ...
This work provides a formalized model-invariant safety system for closed-loop anesthesia that uses feedback from measured data for model falsification to reduce conservatism. The safety system maintains predicted propofol plasma concentrations, as well as the patient's blood pressure, within safety bounds despite uncertainty in patient responses to propofol. Model-invariant formal verification is used to formalize the safety system. This technique requires a multi-model description of model-uncertainty. Model-invariant verification considers all possible dynamics of an uncertain system, and the resulting safety system may be conservative for systems that do not exhibit the worst-case dynamical response. In this work, we employ model falsification to reduce conservatism of the model-invariant safety system. Members of a model set that characterizes model- uncertainty are falsified if discrepancy between predictions of those models and measured responses of the uncertain system is established, thereby reducing model uncertainty. We show that including falsification in a model-invariant safety system reduces conservatism of the safety system.
... The feasibility of closed-loop propofol anesthesia has been shown in several clinical studies [1], [2], [3]. An appropriately designed anesthesia closed-loop system is robust to inter-patient variability [4], [5] and provides less variability in desired clinical effects than manual adjustment of anesthesia performed by anesthesiologists [6].Although several experimental systems have been reported [1], [2], [3], these systems have not been certified. To obtain regulatory approval for anesthesia control systems, patient safety must be established. ...
... Controller. In both study phases, the propofol infusion rate was controlled using a robustly tuned PID control algorithm, 18 with input from the measured WAV CNS value and the setpoint defined by the anesthesiologist; default WAV CNS setpoint was 50. During phase I, remifentanil was administered as a target-controlled infusion (TCI), based on the model by Minto et al, 22 with the target controlled by the anesthesiologist. ...
Background:
Closed-loop control of anesthesia involves continual adjustment of drug infusion rates according to measured clinical effect. The NeuroSENSE monitor provides an electroencephalographic measure of depth of hypnosis (wavelet-based anesthetic value for central nervous system monitoring [WAVCNS]). It has previously been used as feedback for closed-loop control of propofol, in a system designed using robust control engineering principles, which implements features specifically designed to ensure patient safety. Closed-loop control of a second drug, remifentanil, may be added to improve WAVCNS stability in the presence of variable surgical stimulation. The objective of this study was to design and evaluate the feasibility of a closed-loop system for robust control of propofol and remifentanil infusions using WAVCNS feedback, with an infusion safety system based on the known pharmacological characteristics of these 2 drugs.
Methods:
With Health Canada authorization, research ethics board approval, and informed consent, American Society of Anesthesiologists I-III adults, requiring general anesthesia for elective surgery, were enrolled in a 2-phase study. In both phases, infusion of propofol was controlled in closed loop during induction and maintenance of anesthesia, using WAVCNS feedback, but bounded by upper- and lower-estimated effect-site concentration limits. In phase I, remifentanil was administered using an adjustable target-controlled infusion and a controller was designed based on the collected data. In phase II, remifentanil was automatically titrated to counteract rapid increases in WAVCNS.
Results:
Data were analyzed for 127 patients, of median (range) age 64 (22-86) years, undergoing surgical procedures lasting 105 (9-348) minutes, with 52 participating in phase I and 75 in phase II. The overall control performance indicator, global score, was a median (interquartile range) 18.3 (14.2-27.7) in phase I and 14.6 (11.6-20.7) in phase II (median difference, -3.25; 95% confidence interval, -6.35 to -0.52). The WAVCNS was within ±10 of the setpoint for 84.3% (76.6-90.6) of the maintenance of anesthesia in phase I and 88.2% (83.1-93.4) in phase II (median difference, 3.7; 95% confidence interval, 0.1-6.9). The lower propofol safety bound was activated during 30 of 52 (58%) cases in phase I and 51 of 75 (68%) cases in phase II.
Conclusions:
Adding closed-loop control of remifentanil improved overall controller performance. This controller design offers a robust method to optimize the control of 2 drugs using a single sensor. The infusion safety system is an important component of a robust automated anesthesia system, but further research is required to determine the optimal constraints for these safe conditions.
... iControl has successfully been used to automate hypnotic drug (propofol) delivery in adults [15] and children [16,17] , and is currently used in a study on adults controlling both hypnotic and analgesic drug (remifentanil) delivery concurrently. ...
A modular framework for the development of medical applications that promotes deterministic, robust and correct code is presented. The system is based on the portable Gambit Scheme programming language and provides a flexible cross-platform environment for developing graphical applications on mobile devices as well as medical instrumentation interfaces running on embedded platforms. Real world applications of this framework for mobile diagnostics, telemonitoring and automated drug infusions are reported. The source code for the core framework is open source and available at: https://github.com/part-cw/lambdanative.
... The first version of the iControl system provided closedloop control of the anesthetic drug (propofol). Subsequent to extensive testing and health authority approvals, clinical trials in adults [29,30] and children [31,32] have been undertaken successfully, and the system has been found to work within specifications. To date iControl has been used on more than 200 patients in a wide variety of surgical situations. ...
Many aspects of modern medicine, including the administration of anesthetic agents during general surgery, remain unautomated and reliant on the vigilance of the attending clinicians. In other fields where failures can have catastrophic consequences, such as the aviation and nuclear power industry, automated control regimens have been adopted to reduce the risks and improve performance.
In this paper we discuss many aspects of the implementation of a complete automated system for intravenous anesthetic drug infusion based on feedback from electroencephalography (EEG) readings. The system software in its entirety consists of approximately 22K lines of Scheme code and features a client-server implementation interfacing medical devices with a portable graphical user interface. The user interface runs on both mobile devices and dedicated medical flat panel displays.
The strengths of the Scheme functional language have been leveraged to build a robust maintainable modular system with extensive testing facilities to mitigate the inherent safety hazards associated with the application.
... Multiple clients can run against the server simulta- neously. iControl has successfully been used to automate hypnotic drug (propofol) delivery in adults [15] and children [16, 17] , and is currently used in a study on adults controlling both hypnotic and analgesic drug (remifentanil) delivery concurrently. ...
A modular framework for the development of medical applications that promotes deterministic, robust and correct code is presented. The system is based on the portable Gambit Scheme program-ming language and provides a flexible cross-platform environment for developing graphical applications on mobile devices as well as medical instrumentation interfaces running on embedded plat-forms. Real world applications of this framework for mobile diag-nostics, telemonitoring and automated drug infusions are reported.
In this paper we investigate a novel tuning methodology for a patient-individualized selection of the parameters of a proportional-integral-derivative (PID) controller that regulates the maintenance phase of general anesthesia. In particular, the knowledge of demographic data is exploited to determine the values of the parameters for each specific patient. The proposed approach is focused on the closed-loop administration of propofol by using the Bispectral Index Scale as controlled variable. Simulation results suggest that, with respect to a previously devised population-based PID tuning approach, the new methodology is more robust with respect to both intra-patient and inter-patient variability, at the cost of a slight decrement in the controller bandwidth.
This paper studies application of different constrained control concepts for the control of Depth of Hypnosis (DOH) in closed-loop anesthesia to guarantee patient safety, while ensuring acceptable tracking performance. The core idea is to formulate Overdosing (OD) prevention and Blood Pressure Decrease (BPD) prevention as operational constraints, and then use a constrained control scheme to enforce the constraints satisfaction at all times. In this paper, three methods are studied: (1) Explicit Reference Governor (ERG), (2) Safety Preserving Control (SPC), and (3) Model Predictive Control (MPC). The performance of the methods is assessed with respect to a simulated surgical procedure for 44 patients whose models have been identified using clinical data. In particular, three realistic clinical scenarios are studied in this paper: (1) normal mode, (2) stimulation, and (3) low clearance. The results demonstrate cons and pros of each method in closed-loop anesthesia according to clinically relevant assessments.
This brief introduces a novel safety-preserving control scheme with minimal conservatism for uncertain systems. We have recently introduced the model-invariant safety verification technique that provides a formal guarantee of safety for systems with multiplicative model uncertainty. This approach requires a multi-model description of model uncertainty. The resulting safety system may be conservative for systems that do not exhibit the worst case dynamical response. In this brief, we employ model falsification to reduce conservatism of the model-invariant safety verification technique. Members of a model set that characterizes model uncertainty are falsified if discrepancy between predictions of those models and measured responses of the uncertain system is established, thereby reducing model uncertainty. To demonstrate the effectiveness of the proposed technique, we formalize a model-invariant safety system for closed-loop propofol anesthesia. The safety system maintains predicted propofol concentration in plasma as well as the patient's blood pressure within safety bounds despite uncertainty in patient responses to propofol.
Control of propofol anesthesia is characterized by large variability in individual responses to drug infusion, relatively simple system dynamics and relatively low performance criteria. Robust PID control can be expected to provide adequate control given these characteristics. While feasibility of robust PID control of propofol anesthesia has been shown in clinical trials, controllers that use an explicit model might provide additional valuable characteristics. This paper examines the performance achieved with a manually tuned robust PID controller and a higher-order Q-design controller. The additional degrees of freedom in the Q-design allow an increase in the robustness margin, at the cost of decreased gain at low frequencies and corresponding increased time to induction of anesthesia. These results indicate that the uncertainty introduced by interpatient variability is an important factor limiting closed-loop performance. Performance improvement from increased controller complexity may therefore be limited, unless strategies aimed at reducing the uncertainty are implemented.
The benefits of closed-loop control of anesthesia in terms of drug usage, robustness to inter-patient variability and postoperative outcomes have been demonstrated in a number of clinical studies. However, to obtain regulatory approval for such systems to be employed as medical devices in operating rooms, patient safety must be demonstrated. This paper formalizes a previously published safety system for closed-loop anesthesia using formal model verification techniques. This safety system specifies safety constraints on the patient states based on the therapeutic window of propofol. To verify feasibility of the safety constraints in all situations, a finite number of simulation scenarios can be performed. However, the formal methods verify the feasibility problem for all possible admissible inputs and states without the need for simulation. The formalized safety system for closed-loop anesthesia guarantees that the patient states stay within safety constraints.
This paper describes the design and evaluation of a controller for multi-input single-output (MISO) propofol-remifentanil anesthesia, guided by feedback from a measure of depth-of-hypnosis (DOH). DOH monitors are commonly used in clinical practice to guide anesthetic dosing, however, there is currently no widely accepted nociception monitor to guide remifentanil (analgesic) infusion. Variability in the DOH measure has been associated with insufficient analgesia, and feasibility of closed-loop control of both propofol and remifentanil infusion using DOH feedback has been demonstrated. However, DOH variability does not provide a measure of analgesia in the absence of stimulation. Consequently, control of the opioid-hypnotic balance is lost in control systems relying on DOH feedback alone. The proposed design overcomes this limitation by introducing a second, indirect control objective. This paper defines clinical design specifications to achieve adequate anesthesia in a wide range of clinical cases, proposes a modification of the habituating control framework, and presents methods to translate the clinical objectives into control objectives within this framework. The developed design methodology provides a controller that: 1) meets the clinical objectives; 2) is robust to interpatient variability, both in single-input single-output and MISO operation; 3) is robust to nonlinear drug interactions; 4) gives the user control of the opioid-hypnotic balance in the absence of stimulation and in the presence of input saturation; and 5) improves disturbance rejection following nociceptive stimulation. The MISO system performed as designed in 80 clinical cases.
Feasibility of closed-loop anesthesia has been shown in a number of clinical studies. Demonstration of patient safety will be essential to convince regulatory authorities of the benefits of such systems. This paper considers safety constraints for closed-loop propofol anesthesia based on its therapeutic range. Simulation scenarios are proposed for evaluation of control strategies in the presence of these constraints. The scenarios reproduce realistic situations encountered in clinical practice. Using the proposed scenarios, the performance of ℒ 2 anti-windup is compared to sliding mode reference conditioning and to back-calculation anti-windup. It is concluded that ℒ 2 anti-windup might not be appropriate for this problem. The sliding mode solution results in behaviour comparable to the Hanus conditioned controller and there seems to be no need for fast switching. The back-calculation anti-windup performs well in a variety of situations.
In safety-critical control systems, such as closed-loop control of anesthesia, it is of utmost importance to guarantee the ability of a control approach to maintain states of the systems within a safe region. In this paper, we address the problem by applying a safety-preserving control technique to anesthesia control. The approach relies on a conservative approximation of the viability set. The set specifies initial states for which there exists an input that keeps the trajectory emanating from those states within the safe region. This approach can be applied to any type of controller which satisfies the performance criteria. Furthermore, it prevents the performance controller from taking the states out of the safe region.
In many fields of human endeavour, ranging from the mundane such as DVD players to the technologically advanced such as space flight, control systems have become ubiquitous, to the point that control technology has been termed by Karl Astr"om the "hidden technology". However, in the field of anesthesia, despite efforts going back to 1950, closed-loop control is rarely used to automate the delivery of drugs to safely achieve and maintain a desired clinical effect. This might be because of the complexity of physiological systems, the poor understanding of anesthetic drug mechanisms, the large inter-patient variability, and the difficulty in sensing. Following a brief introduction to general anesthesia, those challenges will be reviewed from a control engineering perspective. Recent developments in sensing and monitoring have resulted in renewed interest in automatic control of anesthesia. These developments will be discussed, and then recent research in control of depth of anesthesia, as well as in analgesia, neuromuscular blockade will be reviewed. The appropriateness of various control methodologies for this problem will also be discussed.
Feedback control is ubiquitous in nature and engineering and has revolutionized safety in fields from space travel to the automobile. In anesthesia, automated feedback control holds the promise of limiting the effects on performance of individual patient variability, optimizing the workload of the anesthesiologist, increasing the time spent in a more desirable clinical state, and ultimately improving the safety and quality of anesthesia care. The benefits of control systems will not be realized without widespread support from the health care team in close collaboration with industrial partners. In this review, we provide an introduction to the established field of control systems research for the everyday anesthesiologist. We introduce important concepts such as feedback and modeling specific to control problems and provide insight into design requirements for guaranteeing the safety and performance of feedback control systems. We focus our discussion on the optimization of anesthetic drug administration.
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