Computer control systems and pharmacological drug administration: a survey

Individualized model discovery: the case of anemia patients

The universal sequel to chronic kidney condition (CKD) is anemia. Patients of anemia have kidneys that are incapable of performing certain basic functions such as sensing of oxygen levels to secrete erythropoietin when red blood cell counts are low. Under such conditions, external administration of human recombinant erythropoietin (EPO) is administered as alternative to improve conditions of CKD patients by increasing their hemoglobin (Hb) levels to a given therapeutic range. Presently, EPO dosing strategies extensively depend on packet inserts and on "average" responses to the medication from previous patients. Clearly dosage strategies based on these approaches are, at best, nonoptimal to EPO medication and potentially dangerous to patients that do not adhere to the notion of expected "average" response. In this work, a technique called semi-blind robust identification is provided to uniquely identify models of the individual patients of anemia based on their actual Hb responses and EPO administration. Using the a priori information and the measured input-output data of the individual patients, the procedure identifies a unique model consisting of a nominal model and the associated model uncertainty for the patients. By incorporating the effects of unknown system initial conditions, considerably small measurement samples can be used in the modeling process.

A cascade control approach for a class of biomedical systems

An approach for the robust feedback control of a class of biomedical systems in chained form is presented. The control approach is based on modeling error compensation techniques and a recursive cascade scheme. Numerical simulations on three biomedical models of VIH-1, cancer and glucose systems are provided to illustrate our findings.

Feasibility of closed-loop titration of propofol guided by the Bispectral Index for general anaesthesia induction

BACKGROUND

This study was designed to evaluate the feasibility of propofol infusion by a closed-loop system for the titration of anaesthetic induction guided by Bispectral Index.

METHODS

Forty patients were prospectively and randomly allocated into two groups: the target control infusion (TCI) group, where propofol titration was performed manually guided by the Bispectral Index using a commercial pharmacokinetic model (Diprifusor device) and the closed-loop group where titration was performed using a proportional differential algorithm. For both groups, the objective was to achieve a Bispectral Index of 50. Remifentanil TCI was infused at a target of 2 ng mL-1 and was maintained constant throughout the study. Feasibility of automatic induction was evaluated with performance error and haemodynamic data.

RESULTS

Bispectral Index overshoot (-9 +/- 13% vs. -16 +/- 20%, P = 0.035) and mean duration of induction (381 +/- 106 s vs. 490 +/- 131 s, P = 0.004) were lower in the closed-loop group than in the TCI group. Haemodynamic data were similar between groups with a similar use of ephedrine bolus.

CONCLUSION

The system was able to allow induction clinically for all patients. Automated titration guided by Bispectral Index for propofol infusion was feasible without increase in haemodynamic adverse effects.

A cascade feedback control approach for hypnosis

This article studies the problem of controlling the drug administration during an anesthesia process, where muscle relaxation, analgesia, and hypnosis are regulated by means of monitored administration of specific drugs. On the basis of a seventh-order nonlinear pharmacokinetic-pharmacodynamic representation of the hypnosis process dynamics, a cascade (master/slave) feedback control structure for controlling the bispectral index (BIS) is proposed. The master controller compares the measured BIS with its reference value to provide the expired isoflurane concentration reference to the slave controller. In turn, the slave controller manipulates the anesthetic isoflurane concentration entering the anesthetic system to achieve the reference from the master controller. The advantage of the proposed cascade control structure with respect to its noncascade counterpart is that the former provides operation protection against BIS measurement failures. In fact, under a BIS measurement fault, the master control feedback is broken and the slave controller operates under a safe reference value. Extensive numerical simulations are used to illustrate the functioning of the proposed cascade control structure.

Experimental studies on multiple-model predictive control for automated regulation of hemodynamic variables

A model-based control methodology was developed for automated regulation of mean arterial pressure and cardiac output in critical care subjects using inotropic and vasoactive drugs. The control algorithm used a multiple-model adaptive approach in a model predictive control framework to account for variability and explicitly handle drug rate constraints. The controller was experimentally evaluated on canines that were pharmacologically altered to exhibit symptoms of hypertension and depressed cardiac output. The controller performed better as compared to experiments on manual regulation of the hemodynamic variables. After the model bank was determined, mean arterial pressure was held within +/- 5 mm Hg 88.9% of the time with a standard deviation of 3.9 mm Hg. The cardiac output was held within +/- 1 l/min 96.1% of the time with a standard deviation of 0.5 l/min. The manual runs maintain mean arterial pressure only 82.3% of the time with a standard deviation of 5 mm Hg, and cardiac output 92.2% of the time with a standard deviation of 0.6 l/min.

Modeling and closed-loop control of hypnosis by means of bispectral index (BIS) with isoflurane

A model-based closed-loop control system is presented to regulate hypnosis with the volatile anesthetic isoflurane. Hypnosis is assessed by means of the bispectral index (BIS), a processed parameter derived from the electroencephalogram. Isoflurane is administered through a closed-circuit respiratory system. The model for control was identified on a population of 20 healthy volunteers. It consists of three parts: a model for the respiratory system, a pharmacokinetic model and a pharmacodynamic model to predict BIS at the effect compartment. A cascaded internal model controller is employed. The master controller compares the actual BIS and the reference value set by the anesthesiologist and provides expired isoflurane concentration references to the slave controller. The slave controller maneuvers the fresh gas anesthetic concentration entering the respiratory system. The controller is designed to adapt to different respiratory conditions. Anti-windup measures protect against performance degradation in the event of saturation of the input signal. Fault detection schemes in the controller cope with BIS and expired concentration measurement artifacts. The results of clinical studies on humans are presented.

Automated infusion of vasoactive and inotropic drugs to control arterial and pulmonary pressures during cardiac surgery

OBJECTIVE

To evaluate the feasibility of a closed-loop system for simultaneous control of systemic arterial and pulmonary artery blood pressures during cardiac surgery.

DESIGN

Feasibility study.

SETTING

The cardiac surgery operating room.

PATIENTS

The performance of the multiple-drug closed-loop system was evaluated during cardiac surgery in 30 patients who required treatment with more than one vasoactive or inotropic drug.

INTERVENTIONS

A multiple-drug closed-loop system integrated five single-drug blood pressure controllers. Arterial hypertension was controlled using sodium nitroprusside or nitroglycerin, arterial hypotension was controlled using noradrenaline or dobutamine, and pulmonary hypertension was controlled using nitroglycerin. The anesthesiologist selected target pressures and single-drug blood pressure controllers. The multiple-drug closed-loop system had a set of priority rules that automatically activated from the selected single-drug controllers the optimum single-drug controller for each hemodynamic state. Drug infusion rates of the nonactive controllers were kept constant. The initial knowledge that was used to construct the priority rules was obtained from standard anesthetic protocols on perioperative management of cardiac surgical patients. A supervisory computer program defined the actions to be taken in cases of infusion pump problems, invalid pressure measurements, and during unexpected increases and decreases in systemic arterial pressure.

MEASUREMENTS AND MAIN RESULTS

The activation of single-drug controllers by the priority rules was accurate and fast. On average, a different single-drug controller was activated once every 7.2 mins. As a measure of variability, the average deviation of mean arterial pressure and mean pulmonary artery pressure from their target values was evaluated and was 8.6+/-4.0 and 4.4+/-4.0 mm Hg, respectively, before cardiopulmonary bypass and 8.0+/-3.6 and 2.4+/-0.9 mm Hg, respectively, after cardiopulmonary bypass. None of the single-drug controllers showed any signs of unstable response.

CONCLUSION

Closed-loop control of both arterial and pulmonary pressures using multiple drugs is feasible during cardiac surgery.

Computer-controlled heart rate increase by isoproterenol infusion: mathematical modeling of the system

The purpose of this study was mathematical modeling of the heart rate (HR) response to isoproterenol (Iso) infusion. We developed a computerized system for the controlled increase of HR by Iso, based on a modified proportional-integral controller. HR was measured in conscious, freely moving rats. We found that the steady-state HR can be described as a hyperbolic power function of the steady-state Iso flow rate. This dependence was coupled with a first-order difference equation to form a pharmacodynamic model that reliably describes the relationship between HR and Iso flow for any arbitrary form of Iso flow function. In simulation studies, we showed that the model continued to follow the HR curve from real-time experiments far beyond the initial "learning interval" from which its parameters were calculated. Our results suggest that the predictive ability and the simplicity of calculating the parameters render this pharmacodynamic model appropriate for use within future advanced, model-based, adaptive control systems and as a part of larger cardiovascular models.

Closed-loop controlled administration of propofol using bispectral analysis

Ten patients, undergoing elective orthopaedic surgery under spinal anaesthesia, were sedated with propofol using a closed-loop feedback control system. The bispectral index (BIS), a new processed EEG parameter, was used as control variable. Propofol administration was controlled by a patient individualised adaptive model-based controller incorporating target-controlled infusion technology combined with a pharmacokinetic-dynamic model. This feedback control system for propofol administration proved to be adequate and safe. BIS was found to be well suited as control variable.

Self-learning fuzzy control of atracurium-induced neuromuscular block during surgery

Self-learning fuzzy logic control has the important property of accommodating uncertain, non-linear and time-varying process characteristics. This intelligent control scheme starts with no fuzzy control rules and learns how to control each process presented to it in real time, without the need for detailed process modelling. A suitable medical application to investigate this control strategy is atracurium-induced neuromuscular block (NMB) of patients in the operating theatre. Here, the patient response exhibits high non-linearity, and individual patient dose requirements can vary five-fold during an operating procedure. A portable control system was developed to assess the clinical performance of a simplified self-learning fuzzy controller in this application. A Paragraph (Vital Signs) NMB device monitored T1, the height of the first twitch in a train-of-four nerve stimulation mode. Using a T1 setpoint = 10% of baseline in ten patients undergoing general surgery, a mean T1 error of 0.45% (SD = 0.44%) is found while a 0.13-0.70 mg k-1 h-1 range in the mean atracurium infusion rate is accommodated. The result compares favourably with more complex and computationally-intensive model-based control strategies for the infusion of atracurium.

Correction for respiration artifact in pulmonary blood pressure signals of ventilated patients

OBJECTIVE

To develop an algorithm that corrects pulmonary artery pressure signals of ventilated patients for the respiration artifact. The algorithm should test the validity of the pulmonary pressure signal and differentiate between the cyclic respiration artifact and true measurement artifacts.

METHODS

The shape of each pulmonary pressure beat is described by eight characteristic features, including mean pressure value and the systolic and diastolic timing and pressure values. The features are corrected for the respiration artifact by fitting them in a least-squares sense on the first and second harmonics of the ventilator frequency. The corrected features are used by a signal validation algorithm, which adds a validity flag to each pressure beat. The validation algorithm rejects pressure beats with sudden changes in their shape but adapts itself when the changes persist.

RESULTS

The performance of the correction and validation technique was evaluated using pulmonary artery pressure signals of 30 patients who were scheduled for open heart surgery. The algorithm correctly recognized as invalid data those pressure signals disturbed by coagulation, surgical manipulations, or flushes of the pressure line. The algorithm marked on average 77 +/- 11% of the pulmonary pressure beats as valid.

CONCLUSIONS

The validation algorithm marked sufficient pressure beats as valid to update a trend display every 5 sec. The correction algorithm enabled the validation algorithm to differentiate between true measurement artifacts and the respiration artifact.

Evaluation of a long-range adaptive predictive controller for computerized drug delivery systems

A closed-loop adaptive control system, based on the generalized predictive control law with a terminal matching condition, has been developed for computerized drug delivery. The control law is a minimization of the squares of prediction errors over a small future prediction horizon plus weighted square of the prediction error at steady-state. A control-relevant, long-range identification algorithm is used for on-line parameter estimation. Since the control and identification are mutually compatible, the system truly satisfies the approximate dual control criterion. The system has been applied to the control of mean arterial pressure (MAP) by automatic infusion of sodium nitroprusside in the presence of physical and physiological constraints. Experimental evaluation on six mongrel dogs, in an ethics-approved manner, included setpoint tracking and regulation of MAP in the presence of unpredictable disturbances. The system was found to be capable of inducing hypotension in an average of 2.44 +/- 0.31 min (mean +/- standard error of mean) after probing without any overshoots in mean arterial pressure. The nitroprusside infusion was also free of any ringing. When the subjects were not disturbed, 96.2% of mean arterial pressure remained within 5 mm Hg of the target pressure. A series of disturbances introduced in the presence and absence of closed-loop control affirms the robustness and effectiveness of this control system.

Neural networks and nonlinear regression modelling and control of depth of anaesthesia for spontaneously breathing and ventilated patients

Various attempts have been made to control the depth of anaesthesia by observing different variables. In some studies, depth of anaesthesia has been correlated with inferential parameters and the control has been made through these inferred parameters. No single system has been reported which provides a fully developed architecture to control the depth of anaesthesia. This study is concerned with the development of controllers and patient models via Artificial Neural Networks and regression analysis. Two types of data sets were used for the training and development of models and controllers. The first set was for spontaneously breathing and the second set for ventilated patients. All of the controllers and patient models gave satisfactory results when tested individually. Later these two sets of controllers and patient models were studied in closed-loop modes. The robustness to the sensitivity of the regression patient model was also investigated. Various tests were performed with these closed-loop situations. Results and performance of these tests are discussed in the paper.

Control strategies for arterial blood pressure regulation

This paper reviews the theoretical development of automatic control strategies for arterial blood pressure regulation. The literature is classified by control strategy. Proportional-integral-derivative controllers, optimal controllers, adaptive controllers, and rule-based controllers are the most commonly encountered strategies in the literature. A brief description of each control scheme is given, followed by examples of each from the literature. Validation methods for the control performance vary from computer simulations to clinical tests on human patients. A number of reports of clinical success support the feasibility of advanced control systems in this problem. Issues on control systems in the clinical environment are also discussed.

PUMPSIM: a software package for simulating computer-controlled drug infusion pumps

Advances in microcomputer technology have lead to the development of volumetric infusion pumps which can be controlled by a remote computer. Such pumps offer powerful capabilities for the administration of medications and fluids. Complex control strategies can be preprogrammed and the pump allowed to run with a minimum of supervision. The safety of patients is of the utmost importance. Therefore, great care must be taken to implement robust error avoidance, detection and correction protocols in the host control program. This paper describes a software simulator of a commercial infusion pump (Abbott Lifecare Model 4). Using the simulator in the development and debugging of control programs has several advantages over using the real pump: it provides detailed pump status information and it can stimulate various error and alarm conditions to comprehensively test the error recovery procedures of the control program.