Abstract
This paper presents the application of model-based predictive control (MPC) in combination with a sensor for the measurement of analgesia (pain relief) in an unconscious patient in order to control the level of anesthesia. The MPC strategy uses fractional-order impedance models (FOIMs) to model the diffusion process that occurs in the human body when an analgesic drug is taken up. Based on this control strategy an early dawn concept of the pain sensor is developed. The grand challenges that coincide with this development include identification of the patient model, validation of the pain sensor, and validation of the effect of the analgesic drug.
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References
Bailey JM, Haddad WM (2005) Drug dosing control in clinical pharmacology. IEEE Control Syst Mag N Y 25(2):35–51
Haddad WM, Hayakawa T, Bailey JM (2003) Nonlinear adaptive control for intensive care unit sedation and operating room hypnosis. Am Control Conf 2:1808–1813
O’Hara D, Bogen D, Noordergraaf A (1992) The use of computers for controlling the delivery of anesthesia. Anesthesiology 77:563–581
Greenhow SG, Linkens DA, Asbury AJ (1993) Pilot study of an expert system adviser for controlling general anesthesia. Br J Anaesth 71:359–365
Petersen-Felix S, Hacisalihzade S, Zbinden AM, Feigenwinter P (1995) Arterial pressure control with isoflurane using fuzzy logic. Br J Anaesth 74:66–72
Curatolo M, Derighetti M, Petersen-Felix S, Feigenwinter P, Fisher M, Zbinden AM (1996) Fuzzy logic control of inspired isoflurane and oxygen concentrations using minimal flow anesthesia. Br J Anaesth 76:245–250
Struys M, Vereecke H, Moerman A, Jensen EW, Verhaeghen D, De Neve N, Dumortier F, Mortier E (2003) Ability of the bispectral index, autoregressive modelling with exogenous input-derived auditory evoked potentials, and predicted propofol concentrations to measure patient responsiveness during anesthesia with propofol and remifentanil. Anesthesiology 99:802–814
Asbury AJ (1997) Feedback control in anesthesia. Int J Clin Monit Comput 14:1–10
Northrop RB (2000) Endogenous and exogenous regulation and control of physiological systems. CRC, Boca Raton
De Keyser R (2003) Model based predictive control for linear systems. UNESCO Encyclopaedia of Life Support Systems, Article contribution 6.43.16.1, EOLSS Publishers Co Ltd, Oxford, ISBN 0 9542 989 18-26-34, 30p
Kress J, Pohlman A, Hall J (2002) Sedation and analgesia in the intensive care unit. Am J Respir Crit Care Med 166:1024–1028
Steen-Knudsen O (2002) Biological membranes. Theory of transport, potentials and electric impulses. Cambridge University Press, Cambridge
Berg JM (ed) (2002) Biochemistry, 6th edn. W.H. Freeman and Company, New York
De Keyser R, Van Cauwenberghe A (1981) A self-tuning multistep predictor application. Automatica 17:167–174
Hemmerling TM, Salhab E, Aoun G, Charabati S, Mathieu P (2007) The Analgoscore: a novel score to monitor intraoperative pain and its use for Remifentanil closed loop application. In: Proceedings of the IEEE international conference on systems, man and cybernetics, pp 1494–1499
Riker RR, Picard JT, Fraser GL (1999) Prospective evaluation of the sedation-agitation scale for adult critically ill patients. Crit Care Med 27:1325–1329
Sessler CN, Gosnell M, Grap MJ, Brophy GT, O’Neal PV, Tesoro E, Elswick RK (2000) A new Agitation-Sedation Scale for critically ill patients: development and testing of validity and inter-rater reliability. Am J Respir Crit Care Med 161:A506
Glass PS, Bloom M, Kearse L, Rosow C, Sebel P, Manberg P (1997) Bispectral analysis measures sedation and memory effects of propofol, midazolam, isoflurane, and alfentanil in healthy volunteers. Anesthesiology 86:836–847
Losa GA, Merlini D, Nonnenmacher TF, Weibel ER (2005) Fractals in biology and medicine, vol IV. Birkhauser, Berlin
West BJ (1990) Fractal physiology and chaos in medicine, studies of nonlinear phenomena in life sciences, vol 1. World Scientific, Singapore
Benchellal A, Poinot T, Trigeassou JC (2005) Approximation and identification of diffusive interfaces by fractional models. Signal Process 86:2712–2727
Oustaloup A (1996) La derivation non entiere. Hermes, Paris (in French)
Podlubny I (1999) Fractional differential equations. Academic, San Diego
Ionescu CM, De Keyser R (2009) Relations between fractional order model parameters and lung pathology in chronic obstructive pulmonary disease. IEEE Trans Biomed Eng 56(4): 978–987
Ionescu CM, Machado JT, De Keyser R (2011) Modeling of the lung impedance using a fractional order ladder network with constant phase elements. IEEE Trans Biomed Circuits Syst 5(1):83–89
Ionescu CM, Hodrea R, De Keyser R (2011) Variable time-delay estimation for anesthesia control during intensive care. IEEE Trans Biomed Eng 58(2):363–369
Lundstrom B, Higgs M, Spain W, Fairhall A (2008) Fractional differentiation by neocortical pyramidal neurons. Nat Neurosci 11:1135–1342
Drew P, Abbot L (2003) Scale-invariant synaptic dynamics in a computational model of recognition memory. Soc Neurosci Abstr 28:89–99
Ionescu CM (2012) Phase constancy in a ladder model of neural dynamics. IEEE Trans Syst Man Cybern A Syst Hum 42(6):1543–1551
Dokoumetzidis A, Magin R, Macheras P (2010) A commentary on fractionalization of multi-compartmental models. J Pharmacokinet Pharmacodyn 37(2):203–207
Acknowledgements
Clara M. Ionescu acknowledges the Flanders Research Center (FWO) for its financial support.
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Chevalier, A., Copot, D., Ionescu, C.M., Machado, J.A.T., De Keyser, R. (2014). Emerging Tools for Quantifying Unconscious Analgesia: Fractional-Order Impedance Models. In: Machado, J., Baleanu, D., Luo, A. (eds) Discontinuity and Complexity in Nonlinear Physical Systems. Nonlinear Systems and Complexity, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-01411-1_8
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