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Emerging Tools for Quantifying Unconscious Analgesia: Fractional-Order Impedance Models

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Discontinuity and Complexity in Nonlinear Physical Systems

Part of the book series: Nonlinear Systems and Complexity ((NSCH,volume 6))

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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Acknowledgements

Clara M. Ionescu acknowledges the Flanders Research Center (FWO) for its financial support.

Author information

Authors and Affiliations

  1. Faculty of Engineering and Architecture, Ghent University, Technologiepark 913, 9052, Gent-Zwijnaarde, Belgium

    Amélie Chevalier, Dana Copot, Clara M. Ionescu & Robin De Keyser

  2. Department of Electrical Engineering, ISEP-Institute of Engineering, Polytechnic of Porto, Rua Dr. Antonio Bernardino de Almeida, 431, 4200-072, Porto, Portugal

    J. A. Tenreiro Machado

Authors
  1. Amélie Chevalier
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  2. Dana Copot
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  3. Clara M. Ionescu
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  4. J. A. Tenreiro Machado
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  5. Robin De Keyser
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Corresponding author

Correspondence to Amélie Chevalier .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Polytechnic Institute of Porto Institute of Engineering, Porto, Portugal

    J. A. Tenreiro Machado

  2. Faculty of Art and Sciences, Mathematics and Computer Sciences, Cankaya University, Ankara, Turkey

    Dumitru Baleanu

  3. Department of Mechanical Engineering, Southern Illinois University Edwardsville, Edwardsville, Illinois, USA

    Albert C J Luo

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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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  • DOI: https://doi.org/10.1007/978-3-319-01411-1_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01410-4

  • Online ISBN: 978-3-319-01411-1

  • eBook Packages: EngineeringEngineering (R0)

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