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Constructing a control-ready model of EEG signal during general anesthesia in humans.
- Source :
-
IFAC-PapersOnLine [IFAC Pap OnLine] 2020; Vol. 53 (2), pp. 15870-15876. Date of Electronic Publication: 2021 Apr 14. - Publication Year :
- 2020
-
Abstract
- Significant effort toward the automation of general anesthesia has been made in the past decade. One open challenge is in the development of control-ready patient models for closed-loop anesthesia delivery. Standard depth-of-anesthesia tracking does not readily capture inter-individual differences in response to anesthetics, especially those due to age, and does not aim to predict a relationship between a control input (infused anesthetic dose) and system state (commonly, a function of electroencephalography (EEG) signal). In this work, we developed a control-ready patient model for closed-loop propofol-induced anesthesia using data recorded during a clinical study of EEG during general anesthesia in ten healthy volunteers. We used principal component analysis to identify the low-dimensional state-space in which EEG signal evolves during anesthesia delivery. We parameterized the response of the EEG signal to changes in propofol target-site concentration using logistic models. We note that inter-individual differences in anesthetic sensitivity may be captured by varying a constant cofactor of the predicted effect-site concentration. We linked the EEG dose-response with the control input using a pharmacokinetic model. Finally, we present a simple nonlinear model predictive control in silico demonstration of how such a closed-loop system would work.
Details
- Language :
- English
- ISSN :
- 2405-8971
- Volume :
- 53
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- IFAC-PapersOnLine
- Publication Type :
- Academic Journal
- Accession number :
- 34184002
- Full Text :
- https://doi.org/10.1016/j.ifacol.2020.12.243