Fractional order impedance models as rising tools for quantification of unconscious analgesia

Author

Chevalier, Amelie ; Copot, Dana ; Ionescu, Clara Mihaela ; De Keyser, Robin

Author_Institution

Dept. of Electr. Energy, Ghent Univ., Ghent, Belgium

fYear

2013

fDate

25-28 June 2013

Firstpage

206

Lastpage

212

Abstract

This research focuses on modeling the diffusion process that occurs in the human body when an analgesic drug is taken up, by using fractional-order impedance models (FOIMs). We discuss the measurement of a suitable feedback signal that can be used in a model-based control strategy. With this knowledge an early dawn concept of a pain sensor is presented. The major challenges that are encountered during this development consist of identification of the patient model, validation of the pain sensor and validation of the effect of the analgesic drug.

Keywords

biomedical measurement; drugs; electric sensing devices; electroencephalography; patient care; predictive control; EEG; analgesic drug; diffusion process; feedback signal measurement; fractional order impedance model; model-based control strategy; pain sensor; patient model identification; rising tool; unconscious analgesia quantification; Anesthesia; Biological system modeling; Computational modeling; Diffusion processes; Drugs; Neurons; Pain; Analgesia; fractional-order impedance model (FOIM); model-based predictive control (MPC); non-invasive pain sensor; pain relief level;

fLanguage

English

Publisher

ieee

Conference_Titel

Control & Automation (MED), 2013 21st Mediterranean Conference on

Conference_Location

Chania

Print_ISBN

978-1-4799-0995-7

Type

conf

DOI

10.1109/MED.2013.6608723

Filename

6608723