Papers by Stephane Bibian
This thesis investigates the design and performance of a controller for the maintenance of anesth... more This thesis investigates the design and performance of a controller for the maintenance of anesthesia during surgery. The controller is designed to be robustly stable for a large population of patients. Even though anesthetic drugs are amongst the most dangerous drugs used in today's clinical setting, anesthesia procedures are known to be very safe. Hence, the impact of automation in anesthesia in terms of patients' safety cannot be clearly established. However, there are a number of significant clinical advantages to be gained by closing the loop: 1. Recent evidences suggest that most patients undergoing anesthesia procedures are overdosed. This is one of the main reasons for patients' discomfort and slow recovery. Literature suggests that closedloop systems can significantly reduce drug consumption and lessen recovery times, thus improving the patient outcome while reducing drug-associated costs and bed occupancy. Using a closed-loop controller would allow for an infusion-type titration that provides smoother transitions, thus avoiding the respiratory and hemodynamic depression observed in a bolus-based manual regimen. 3. Closed-loop controllers are also particularly well-suited for solving complex optimization problems. The profound synergy that exists between intravenous anesthetics and opioids could then be fully exploited. This could be a significant factor contributing to a reduction in drug usage and the improvement of patients' comfort. This project is particularly challenging. In particular: 1. There is no accepted measure of depth of anesthesia. Hence, it is necessary to work at the conceptual and sensor levels in order to define adequate feedback measures. 2. Drug effect modeling suffers from many shortcomings. In particular, published studies are often not in agreement regarding model parameters. 3. Uncertainty of dose/response models is daunting. Measuring this uncertainty is necessary in order to ensure stability of the control design. While the anesthesia closed-loop concept has already been investigated in the past, no breakthrough has yet been achieved. We feel it is necessary to investigate the anesthesia system from a control engineering perspective. This thesis is divided into two distinct parts. Part A contains the first 4 chapters and presents a thorough introduction to clinical anesthesia. The main concepts, terminology and issues are covered, including anesthesia monitors and basic pharmacology principles. A review of the prior closed-loop control attempts is presented in Chapter 4. Part B contains the chapters 5 to 8. In these chapters, we investigate a new sensor technology to quantify both cortical and autonomic activity. This technology is used to derive drug effect models, from which uncertainty bounds are derived. Based on this uncertainty analysis, we derive robustly stable controllers achieving clinically adequate performances. Finally, we invite the readers to refer to Chapter 9 for a complete synopsis and summary of this thesis.
2003 European Control Conference (ECC), 2003
The anesthesia community has recently witnessed numerous advances in the monitoring of the anesth... more The anesthesia community has recently witnessed numerous advances in the monitoring of the anesthetic state. This development has spurred a renewed interest in the automation of clinical anesthesia. While this subject was the apanage of researchers with strong clinical background, recently the control community became also involved. The collaborative studies which resulted have proven the feasibility of feedback-controlled anesthesia systems, while stressing out the many challenges this field imposes. This paper addresses its specificities in a familiar context for control engineers. Anesthesia concepts and terminology, monitoring issues, as well as drug properties and mechanisms of action, are covered. Prior attempts at closed loop anesthesia are reviewed.
Military Medicine, 2015
Objective: This article addresses the design of a robust autopilot for the delivery of intravenou... more Objective: This article addresses the design of a robust autopilot for the delivery of intravenous anesthesia drugs. Methods: A mathematical framework that expresses the pharmacological variability of a patient population into uncertainty bounds is proposed. These bounds can be effectively used to tune the parameters of a controller to ensure its stability, a key design aspect related to the safety of the overall system. Results: The proposed method is applied to the control of propofol, a powerful hypnotic agent used for sedation and anesthesia. Simulations show that the controller remains stable for all patients considered and that performance are clinically acceptable. Conclusion: This methodology can be an important step forward in the design and regulatory approval of such systems.
Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology
The electroencephalogram (EEG) gives researchers a non-invasive insight into the intricacy of the... more The electroencephalogram (EEG) gives researchers a non-invasive insight into the intricacy of the human brain. It is a valuable tool for clinicians in numerous applications, from the diagnosis of neurological disorders, to the clinical monitoring of depth of anesthesia. For awake ...
6th IFAC Symposium on Modeling and Control in Biomedical Systems, 2006, 2006
Abstract The outcome of any surgery is particularly dependent on the adequate delivery of anesthe... more Abstract The outcome of any surgery is particularly dependent on the adequate delivery of anesthetic drugs. Not surprisingly clinical researchers have been trying to automatize their delivery in order to provide anesthesiologists with titration tools that can target the exact needs of each individual patient. As compared to today's population-normed drug delivery strategy closed-loop drug delivery systems would provide patients with customized pharmacological action, thereby improving surgery outcome. While some anesthesia closed-loop designs have already shown promising results within controlled clinical protocols, the pharmacological variability that exists between patients needs to be addressed within a mathematical framework to prove the stability of the control laws, and gain faster and wider acceptance of these systems by the clinical community and regulatory committees. This paper is the first of a series of 2 papers addressing the issue of pharmacological variability, and how this variability translates into quantifiable system uncertainty. In this work, we focus essentially on deriving patient-specific models to assess inter-patient variability. These models will serve as basis for illustrating the uncertainty quantification approach proposed in the accompanying paper.
European Journal of Control, 2005
Control technology has been applied to a wide variety of industrial and domestic applications to ... more Control technology has been applied to a wide variety of industrial and domestic applications to improve performance, safety and efficiency. Anesthesia, a critical aspect of clinical and emergency medicine, has not yet benefited from such technological advances. The lack of dedicated feedback sensors, and the large inter-and intra-patient variability in terms of patients' response to drug administration, have seriously limited the effectiveness and reliability of closed-loop controllers in clinical settings. However, recent advances in sensing devices, along with robust nonlinear control theories, have generated new hopes that the gap between manual and automated control of anesthesia can finally be bridged. This paper addresses the pharmacological principles of clinical anesthesia in a context appropriate for control engineers. Concepts and terminology, monitoring issues, as well as drug dose vs. response relationships, are covered.
The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
A major challenge faced when designing controllers to automate anesthetic drug delivery is the la... more A major challenge faced when designing controllers to automate anesthetic drug delivery is the large variability that exists between and within patients. This intra- and inter-patient variability have been reported to lead to instability. Hence, defining and quantifying uncertainty bounds provides a mean to validate the control design, ensure its stability and assess performance. In this work, the intra- and inter-patient variability measured from thiopental induction data is used to define uncertainty bounds. It is shown that these bounds can be reduced by up to 40% when using a patient-specific model as compared to a population-normed model. It is also shown that identifying only the overall static gain of the patient system already decreases significantly this uncertainty.
APEC 2001. Sixteenth Annual IEEE Applied Power Electronics Conference and Exposition (Cat. No.01CH37181)
The modeling and control of PFC circuits is a non-trivial problem and was the subject of many wor... more The modeling and control of PFC circuits is a non-trivial problem and was the subject of many works [6-10]. A major difficulty is that the controller has to track a rectified sine ... Index terms - Digital control, predictive control, dead-beat con-trol, power factor correction circuits.
APEC '99. Fourteenth Annual Applied Power Electronics Conference and Exposition. 1999 Conference Proceedings (Cat. No.99CH36285), 1999
ABSTRACT Two predictive schemes based on a linear extrapolation technique are developed to compen... more ABSTRACT Two predictive schemes based on a linear extrapolation technique are developed to compensate the sampling time delay present in digital control, thus increasing the bandwidth of the control loop. Characterized by a low computational effort, these schemes are perfectly suited for fast systems such as high-performance DC switchmode power supplies. Results with and without the proposed prediction schemes are provided for comparison
Journal of Clinical Monitoring and Computing, 2011
Objective. Visual scoring of 30-s epochs of sleep data is not always adequate to show the dynamic... more Objective. Visual scoring of 30-s epochs of sleep data is not always adequate to show the dynamic structure of sleep in sufficient details. It is also prone to considerable interand intra-rater variability. Moreover, it involves considerable training and experience, and is very tedious, time-consuming, labor-intensive and costly. Hence, automatic sleep staging is needed to overcome these limitations. Since naturally occurring NREM sleep and anesthesia have been reported to possess various underlying neurophysiological similarities, EEG-based depth-of-anesthesia monitors have started to penetrate into sleep research. This study investigates the ability of WAV CNS index (as implemented in NeuroSENSE depth-of-anesthesia monitor) to detect NREM sleep stages and wake state for full overnight PSG data. Methods. Full overnight PSG sleep data, obtained from 24 adolescents, was scored by a registered PSG technologist for different sleep stages. Retrospective analysis was performed on a single frontal channel using the WAV CNS algorithm. Non-parametric descriptive statistics were used to examine the relationship between WAV CNS index and sleep stages. Results. A strong correlation (q = 0.9458) was found between the WAV CNS index and NREM sleep stages, with WAV CNS index values decreasing with increasing sleep stages. Moreover, there was no significant overlap between different NREM sleep stages as classified by the WAV CNS index, which was able to significantly differentiate (P < 0.001) between all pairs of Awake and different NREM stages. Conclusions. This study demonstrates that changes in the depth of natural NREM sleep are reflected sensitively by changes in the WAV CNS index. Hence, WAV CNS index may serve as an automatic real-time indicator of depth of natural sleep with high temporal resolution, and can possibly be of great use for automated sleep staging in routine/ postoperative somnographic studies.
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Papers by Stephane Bibian