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Farivar F, Jolfaei A, Manthouri M, Haghighi MS. Application of fuzzy learning in IoT-enabled remote healthcare monitoring and control of anesthetic depth during surgery. Inf Sci (N Y) 2023. [DOI: 10.1016/j.ins.2022.12.094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
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Optimized feedforward control of propofol for induction of hypnosis in general anesthesia. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102476] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Gonzalez-Cava JM, Carlson FB, Troeng O, Cervin A, van Heusden K, Dumont GA, Soltesz K. Robust PID control of propofol anaesthesia: Uncertainty limits performance, not PID structure. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 198:105783. [PMID: 33049452 DOI: 10.1016/j.cmpb.2020.105783] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 09/29/2020] [Indexed: 06/11/2023]
Abstract
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.
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Affiliation(s)
- Jose M Gonzalez-Cava
- Departamento de Ingeniería Informática y de Sistemas, Universidad de La Laguna, La Laguna 38200, Tenerife, Spain.
| | | | - Olof Troeng
- Department of Automatic Control, Lund University, Lund 221 00, Sweden
| | - Anton Cervin
- Department of Automatic Control, Lund University, Lund 221 00, Sweden
| | - Klaske van Heusden
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6H 3V4, Canada
| | - Guy A Dumont
- Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6H 3V4, Canada
| | - Kristian Soltesz
- Department of Automatic Control, Lund University, Lund 221 00, Sweden
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Patel B, Patel H, Shah D, Sarvaia A. Control strategy with multivariable fault tolerance module for automatic intravenous anesthesia. Biomed Eng Lett 2020; 10:555-578. [PMID: 33194248 DOI: 10.1007/s13534-020-00169-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2020] [Revised: 07/23/2020] [Accepted: 07/31/2020] [Indexed: 11/30/2022] Open
Abstract
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.
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Affiliation(s)
- Bhavina Patel
- Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India
| | - Hirenkumar Patel
- Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India
| | - Divyang Shah
- Surat Municipal Institute of Medical Education and Research (SMIMER), Surat, India
| | - Alpesh Sarvaia
- U. N. Mehta Institute of Cardiology and Research, Ahmedabad, India
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Estimating the Depth of Anesthesia During the Induction by a Novel Adaptive Neuro-Fuzzy Inference System: A Case Study. Neural Process Lett 2020. [DOI: 10.1007/s11063-020-10369-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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Angaroni F, Graudenzi A, Rossignolo M, Maspero D, Calarco T, Piazza R, Montangero S, Antoniotti M. An Optimal Control Framework for the Automated Design of Personalized Cancer Treatments. Front Bioeng Biotechnol 2020; 8:523. [PMID: 32548108 PMCID: PMC7270334 DOI: 10.3389/fbioe.2020.00523] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Accepted: 05/01/2020] [Indexed: 12/17/2022] Open
Abstract
One of the key challenges in current cancer research is the development of computational strategies to support clinicians in the identification of successful personalized treatments. Control theory might be an effective approach to this end, as proven by the long-established application to therapy design and testing. In this respect, we here introduce the Control Theory for Therapy Design (CT4TD) framework, which employs optimal control theory on patient-specific pharmacokinetics (PK) and pharmacodynamics (PD) models, to deliver optimized therapeutic strategies. The definition of personalized PK/PD models allows to explicitly consider the physiological heterogeneity of individuals and to adapt the therapy accordingly, as opposed to standard clinical practices. CT4TD can be used in two distinct scenarios. At the time of the diagnosis, CT4TD allows to set optimized personalized administration strategies, aimed at reaching selected target drug concentrations, while minimizing the costs in terms of toxicity and adverse effects. Moreover, if longitudinal data on patients under treatment are available, our approach allows to adjust the ongoing therapy, by relying on simplified models of cancer population dynamics, with the goal of minimizing or controlling the tumor burden. CT4TD is highly scalable, as it employs the efficient dCRAB/RedCRAB optimization algorithm, and the results are robust, as proven by extensive tests on synthetic data. Furthermore, the theoretical framework is general, and it might be applied to any therapy for which a PK/PD model can be estimated, and for any kind of administration and cost. As a proof of principle, we present the application of CT4TD to Imatinib administration in Chronic Myeloid leukemia, in which we adopt a simplified model of cancer population dynamics. In particular, we show that the optimized therapeutic strategies are diversified among patients, and display improvements with respect to the current standard regime.
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Affiliation(s)
- Fabrizio Angaroni
- Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
| | - Alex Graudenzi
- Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
- Institute of Molecular Bioimaging and Physiology, Consiglio Nazionale delle Ricerche (IBFM-CNR), Segrate, Milan, Italy
| | - Marco Rossignolo
- Center for Integrated Quantum Science and Technologies, Institute for Quantum Optics, Universitat Ulm, Ulm, Germany
- Istituto Nazionale di Fisica Nucleare (INFN), Padova, Italy
| | - Davide Maspero
- Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
- Institute of Molecular Bioimaging and Physiology, Consiglio Nazionale delle Ricerche (IBFM-CNR), Segrate, Milan, Italy
- Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Tommaso Calarco
- Forschungszentrum Jülich, Institute of Quantum Control (PGI-8), Jülich, Germany
| | - Rocco Piazza
- Department of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
- Hematology and Clinical Research Unit, San Gerardo Hospital, Monza, Italy
| | - Simone Montangero
- Istituto Nazionale di Fisica Nucleare (INFN), Padova, Italy
- Department of Physics and Astronomy “G. Galilei”, University of Padova, Padova, Italy
| | - Marco Antoniotti
- Department of Informatics, Systems and Communication, University of Milan-Bicocca, Milan, Italy
- Bicocca Bioinformatics Biostatistics and Bioimaging Centre - B4, Milan, Italy
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Neckebroek M, Ghita M, Ghita M, Copot D, Ionescu CM. Pain Detection with Bioimpedance Methodology from 3-Dimensional Exploration of Nociception in a Postoperative Observational Trial. J Clin Med 2020; 9:E684. [PMID: 32143327 PMCID: PMC7141233 DOI: 10.3390/jcm9030684] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 02/13/2020] [Accepted: 02/29/2020] [Indexed: 12/21/2022] Open
Abstract
Although the measurement of dielectric properties of the skin is a long-known tool for assessing the changes caused by nociception, the frequency modulated response has not been considered yet. However, for a rigorous characterization of the biological tissue during noxious stimulation, the bioimpedance needs to be analyzed over time as well as over frequency. The 3-dimensional analysis of nociception, including bioimpedance, time, and frequency changes, is provided by ANSPEC-PRO device. The objective of this observational trial is the validation of the new pain monitor, named as ANSPEC-PRO. After ethics committee approval and informed consent, 26 patients were monitored during the postoperative recovery period: 13 patients with the in-house developed prototype ANSPEC-PRO and 13 with the commercial device MEDSTORM. At every 7 min, the pain intensity was measured using the index of Anspec-pro or Medstorm and the 0-10 numeric rating scale (NRS), pre-surgery for 14 min and post-anesthesia for 140 min. Non-significant differences were reported for specificity-sensitivity analysis between ANSPEC-PRO (AUC = 0.49) and MEDSTORM (AUC = 0.52) measured indexes. A statistically significant positive linear relationship was observed between Anspec-pro index and NRS (r2 = 0.15, p < 0.01). Hence, we have obtained a validation of the prototype Anspec-pro which performs equally well as the commercial device under similar conditions.
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Affiliation(s)
- Martine Neckebroek
- Department of Anesthesia, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium;
| | - Mihaela Ghita
- Research group of Dynamical Systems and Control, Ghent University, Tech Lane Science Park 125, 9052 Ghent, Belgium (D.C.); (C.M.I.)
- EEDT—Core Lab on Decision and Control, Flanders Make Consortium, Tech Lane Science Park 131, 9052 Ghent, Belgium
| | - Maria Ghita
- Research group of Dynamical Systems and Control, Ghent University, Tech Lane Science Park 125, 9052 Ghent, Belgium (D.C.); (C.M.I.)
- EEDT—Core Lab on Decision and Control, Flanders Make Consortium, Tech Lane Science Park 131, 9052 Ghent, Belgium
| | - Dana Copot
- Research group of Dynamical Systems and Control, Ghent University, Tech Lane Science Park 125, 9052 Ghent, Belgium (D.C.); (C.M.I.)
- EEDT—Core Lab on Decision and Control, Flanders Make Consortium, Tech Lane Science Park 131, 9052 Ghent, Belgium
| | - Clara M. Ionescu
- Research group of Dynamical Systems and Control, Ghent University, Tech Lane Science Park 125, 9052 Ghent, Belgium (D.C.); (C.M.I.)
- EEDT—Core Lab on Decision and Control, Flanders Make Consortium, Tech Lane Science Park 131, 9052 Ghent, Belgium
- Department of Automatic Control, Technical University of Cluj Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania
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Savoca A, Manca D. A physiologically-based approach to model-predictive control of anesthesia and analgesia. Biomed Signal Process Control 2019. [DOI: 10.1016/j.bspc.2019.04.030] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Patel B, Patel H, Vachhrajani P, Shah D, Sarvaia A. Adaptive smith predictor controller for total intravenous anesthesia automation. Biomed Eng Lett 2019; 9:127-144. [PMID: 30956886 PMCID: PMC6431314 DOI: 10.1007/s13534-018-0090-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 11/09/2018] [Accepted: 12/04/2018] [Indexed: 11/30/2022] Open
Abstract
Anesthetic agent propofol needs to be administered at an appropriate rate to prevent hypotension and postoperative adverse reactions. To comprehend more suitable anesthetic drug rate during surgery is a crucial aspect. The main objective of this proposal is to design robust automated control system that work efficiently in most of the patients with smooth BIS and minimum variations of propofol during surgery to avoid adverse post reactions and instability of anesthetic parameters. And also, to design advanced computer control system that improves the health of patient with short recovery time and less clinical expenditures. Unlike existing research work, this system administrates propofol as a hypnotic drug to regulate BIS, with fast bolus infusion in induction phase and slow continuous infusion in maintenance phase of anesthesia. The novelty of the paper lies in possibility to simplify the drug sensitivity-based adaption with infusion delay approach to achieve closed-loop control of hypnosis during surgery. Proposed work uses a brain concentration as a feedback signal in place of the BIS signal. Regression model based estimated sensitivity parameters are used for adaption to avoid BIS signal based frequent adaption procedure and large offset error. Adaptive smith predictor with lead-lag filter approach is applied on 22 different patients' model identified by actual clinical data. The actual BIS and propofol infusion signals recorded during clinical trials were used to estimate patient's sensitivity parameters EC 50 and λ. Simulation results indicate that patient's drug sensitivity parameters based adaptive strategy facilitates optimal controller performance in most of the patients. Results are obtained with proposed scheme having less settling time, BIS oscillations and small offset error leads to adequate depth of anesthesia. A comparison with manual control mode and previously reported system shows that proposed system achieves reduction in the total variations of the propofol dose. Proposed adaptive scheme provides better performance with less oscillation in spite of computation delay, surgical stimulations and patient variability. Proposed scheme also provides improvement in robustness and may be suitable for clinical practices.
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Affiliation(s)
- Bhavina Patel
- Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India
| | - Hiren Patel
- Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India
| | - Pragna Vachhrajani
- Surat Municipal Institute of Medical Education and Research (SMIMER), Surat, India
| | - Divyang Shah
- Surat Municipal Institute of Medical Education and Research (SMIMER), Surat, India
| | - Alpesh Sarvaia
- U. N. Mehta Institute of Cardiology and Research, Ahmedabad, India
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10
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Neckebroek M, Ionescu CM, van Amsterdam K, De Smet T, De Baets P, Decruyenaere J, De Keyser R, Struys MMRF. A comparison of propofol-to-BIS post-operative intensive care sedation by means of target controlled infusion, Bayesian-based and predictive control methods: an observational, open-label pilot study. J Clin Monit Comput 2018; 33:675-686. [PMID: 30311073 PMCID: PMC6602998 DOI: 10.1007/s10877-018-0208-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2018] [Accepted: 10/04/2018] [Indexed: 11/25/2022]
Abstract
Purpose We evaluated the feasibility and robustness of three methods for propofol-to-bispectral index (BIS) post-operative intensive care sedation, a manually-adapted target controlled infusion protocol (HUMAN), a computer-controlled predictive control strategy (EPSAC) and a computer-controlled Bayesian rule-based optimized control strategy (BAYES). Methods Thirty-six patients undergoing short lasting sedation following cardiac surgery were included to receive propofol to maintain a BIS between 40 and 60. Robustness of control for all groups was analysed using prediction error and spectrographic analysis. Results Although similar time courses of measured BIS were obtained in all groups, a higher median propofol effect-site concentration (CePROP) was required in the HUMAN group compared to the BAYES and EPSAC groups. The time course analysis of the remifentanil effect-site concentration (CeREMI) revealed a significant increase in CeREMI in the EPSAC group compared to BAYES and HUMAN during the case. Although similar bias and divergence in control was found in all groups, larger control inaccuracy was observed in HUMAN versus EPSAC and BAYES. Spectrographic analysis of the system behavior shows that BAYES covers the largest spectrum of frequencies, followed by EPSAC and HUMAN. Conclusions Both computer-based control systems are feasible to be used during ICU sedation with overall tighter control than HUMAN and even with lower required CePROP. EPSAC control required higher CeREMI than BAYES or HUMAN to maintain stable control. Clinical trial number: NCT00735631. Electronic supplementary material The online version of this article (10.1007/s10877-018-0208-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- M Neckebroek
- Department of Anesthesia and Perioperative Medicine, Ghent University Hospital, 9000, Ghent, Belgium
| | - C M Ionescu
- Research Group on Dynamical Systems and Control (DySC), Department of Electrical Energy, Mechanical Constructions and Systems, Ghent University, Metals, Ghent, Belgium
| | - K van Amsterdam
- Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands
| | | | - P De Baets
- Department of Anesthesia and Perioperative Medicine, Ghent University Hospital, 9000, Ghent, Belgium
| | - J Decruyenaere
- Department of Intensive Care Medicine, Ghent University, Ghent, Belgium
| | - R De Keyser
- Research Group on Dynamical Systems and Control (DySC), Department of Electrical Energy, Mechanical Constructions and Systems, Ghent University, Metals, Ghent, Belgium
| | - M M R F Struys
- Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9700 RB, Groningen, The Netherlands. .,Department of Anesthesia and Perioperative Medicine, Ghent University, Ghent, Belgium.
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Fractional-Order Closed-Loop Model Reference Adaptive Control for Anesthesia. ALGORITHMS 2018. [DOI: 10.3390/a11070106] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The design of a fractional-order closed-loop model reference adaptive control (FOCMRAC) for anesthesia based on a fractional-order model (FOM) is proposed in the paper. This proposed model gets around many difficulties, namely, unknown parameters, lack of state measurement, inter and intra-patient variability, and variable time-delay, encountered in controller designs based on the PK/PD model commonly used for control of anesthesia, and allows to design a simple adaptive controller based on the Lyapunov analysis. Simulations illustrate the effectiveness and robustness of the proposed control.
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Merigo L, Padula F, Pawlowski A, Dormido S, Guzmán Sánchez JL, Latronico N, Paltenghi M, Visioli A. A model-based control scheme for depth of hypnosis in anesthesia. Biomed Signal Process Control 2018. [DOI: 10.1016/j.bspc.2018.01.023] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Khaqan A, Hasan QU, Malik SA, Bilal M, Butt MFU, Riaz RA. Comparison of Two Nonlinear Control Strategies for Hypnosis Regulation. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2017. [DOI: 10.1007/s13369-017-2610-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Nașcu I, Oberdieck R, Pistikopoulos EN. Explicit hybrid model predictive control strategies for intravenous anaesthesia. Comput Chem Eng 2017. [DOI: 10.1016/j.compchemeng.2017.01.033] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Merigo L, Beschi M, Padula F, Latronico N, Paltenghi M, Visioli A. Event-Based control of depth of hypnosis in anesthesia. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2017; 147:63-83. [PMID: 28734531 DOI: 10.1016/j.cmpb.2017.06.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2016] [Revised: 06/10/2017] [Accepted: 06/20/2017] [Indexed: 06/07/2023]
Abstract
BACKGROUND AND OBJECTIVE In this paper, we propose the use of an event-based control strategy for the closed-loop control of the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable. METHODS A new event generator with high noise-filtering properties is employed in addition to a PIDPlus controller. The tuning of the parameters is performed off-line by using genetic algorithms by considering a given data set of patients. RESULTS The effectiveness and robustness of the method is verified in simulation by implementing a Monte Carlo method to address the intra-patient and inter-patient variability. A comparison with a standard PID control structure shows that the event-based control system achieves a reduction of the total variation of the manipulated variable of 93% in the induction phase and of 95% in the maintenance phase. CONCLUSIONS The use of event based automatic control in anesthesia yields a fast induction phase with bounded overshoot and an acceptable disturbance rejection. A comparison with a standard PID control structure shows that the technique effectively mimics the behavior of the anesthesiologist by providing a significant decrement of the total variation of the manipulated variable.
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Affiliation(s)
- Luca Merigo
- Dipartimento di Ingegneria dell'Informazione, University of Brescia, Italy.
| | - Manuel Beschi
- Istituto di Tecnologie Industriali e Automazione, National Research Council Milan, Italy.
| | - Fabrizio Padula
- Department of Mathematics and Statistics, Curtin University, Australia.
| | - Nicola Latronico
- Department of Surgery, Radiology, and Public Health,University of Brescia, Italy.
| | | | - Antonio Visioli
- Dipartimento di Ingegneria Meccanica e Industriale, University of Brescia, Italy.
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Padula F, Ionescu C, Latronico N, Paltenghi M, Visioli A, Vivacqua G. Optimized PID control of depth of hypnosis in anesthesia. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2017; 144:21-35. [PMID: 28495004 DOI: 10.1016/j.cmpb.2017.03.013] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2015] [Revised: 03/03/2017] [Accepted: 03/15/2017] [Indexed: 06/07/2023]
Abstract
BACKGROUND AND OBJECTIVE This paper addresses the use of proportional-integral-derivative controllers for regulating the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable. In fact, introducing an automatic control system might provide significant benefits for the patient in reducing the risk for under- and over-dosing. METHODS In this study, the controller parameters are obtained through genetic algorithms by solving a min-max optimization problem. A set of 12 patient models representative of a large population variance is used to test controller robustness. The worst-case performance in the considered population is minimized considering two different scenarios: the induction case and the maintenance case. RESULTS Our results indicate that including a gain scheduling strategy enables optimal performance for induction and maintenance phases, separately. Using a single tuning to address both tasks may results in a loss of performance up to 102% in the induction phase and up to 31% in the maintenance phase. Further on, it is shown that a suitably designed low-pass filter on the controller output can handle the trade-off between the performance and the noise effect in the control variable. CONCLUSIONS Optimally tuned PID controllers provide a fast induction time with an acceptable overshoot and a satisfactory disturbance rejection performance during maintenance. These features make them a very good tool for comparison when other control algorithms are developed.
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Affiliation(s)
- Fabrizio Padula
- Department of Mathematics and Statistics, Curtin University, Australia.
| | - Clara Ionescu
- Department of Electrical Energy, Metals, Mechanical Constructions and Systems, Ghent University, Belgium.
| | - Nicola Latronico
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Italy; Department of Anesthesiology, Critical Care and Emergency Spedali Civili University Hospital, Brescia, Italy.
| | - Massimiliano Paltenghi
- Department of Anesthesiology, Critical Care and Emergency Spedali Civili University Hospital, Brescia, Italy.
| | - Antonio Visioli
- Dipartimento di Ingegneria Meccanica e Industriale, University of Brescia, Italy.
| | - Giulio Vivacqua
- Dipartimento di Ingegneria Meccanica e Industriale, University of Brescia, Italy.
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Naşcu I, Pistikopoulos EN. A multiparametric model-based optimization and control approach to anaesthesia. CAN J CHEM ENG 2016. [DOI: 10.1002/cjce.22634] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Ioana Naşcu
- Department of Chemical Engineering, Centre for Process Systems Engineering (CPSE); Imperial College London SW7 2AZ; London UK
- Artie McFerrin Department of Chemical Engineering; Texas A&M, College Station; TX USA
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Soltesz K, Sturk C, Paskevicius A, Liao Q, Qin G, Sjoberg T, Steen S. Closed-Loop Prevention of Hypotension in the Heartbeating Brain-Dead Porcine Model. IEEE Trans Biomed Eng 2016; 64:1310-1317. [PMID: 27576237 DOI: 10.1109/tbme.2016.2602228] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Objective: The purpose of this paper is to demonstrate feasibility of a novel closed-loop controlled therapy for prevention of hypertension in the heartbeating brain-dead porcine model. METHODS Dynamic modeling and system identification were based on in vivo data. A robust controller design was obtained for the identified models. Disturbance attenuation properties and reliability of operation of the resulting control system were evaluated in vivo. RESULTS The control system responded both predictably and consistently to external disturbances. It was possible to prevent mean arterial pressure to fall below a user-specified reference throughout 24 h of completely autonomous operation. CONCLUSION Parameter variability in the identified models confirmed the benefit of closed-loop controlled administration of the proposed therapy. The evaluated robust controller was able to mitigate both process uncertainty and external disturbances. SIGNIFICANCE Prevention of hypertension is critical to the care of heartbeating brain-dead organ donors. Its automation would likely increase the fraction of organs suitable for transplantation from this patient group.
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Savvopoulos S, Misener R, Panoskaltsis N, Pistikopoulos EN, Mantalaris A. A Personalized Framework for Dynamic Modeling of Disease Trajectories in Chronic Lymphocytic Leukemia. IEEE Trans Biomed Eng 2016; 63:2396-2404. [PMID: 26929022 DOI: 10.1109/tbme.2016.2533658] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Chronic lymphocytic leukemia (CLL) is the most common peripheral blood and bone marrow cancer in the developed world. This manuscript proposes mathematical model equations representing the disease dynamics of B-cell CLL. We interconnect delay differential cell cycle models in each of the tumor-involved disease centers using physiologically relevant cell migration. We further introduce five hypothetical case studies representing CLL heterogeneity commonly seen in clinical practice and demonstrate how the proposed CLL model framework may capture disease pathophysiology across patient types. We conclude by exploring the capacity of the proposed temporally- and spatially distributed model to capture the heterogeneity of CLL disease progression. By using global sensitivity analysis, the critical parameters influencing disease trajectory over space and time are: 1) the initial number of CLL cells in peripheral blood, the number of involved lymph nodes, the presence and degree of splenomegaly; 2) the migratory fraction of nonproliferating as well as proliferating CLL cells from bone marrow into blood and of proliferating CLL cells from blood into lymph nodes; and 3) the parameters inducing nonproliferative cells to proliferate. The proposed model offers a practical platform that may be explored in future personalized patient protocols once validated.
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