Multi-model generalised predictive control for intravenous anaesthesia under inter-individual variability
Author:
Publisher
Springer Science and Business Media LLC
Subject
Anesthesiology and Pain Medicine,Critical Care and Intensive Care Medicine,Health Informatics
Link
https://link.springer.com/content/pdf/10.1007/s10877-020-00581-0.pdf
Reference28 articles.
1. Shafer S, Flood S, Schwinn DA. Basic principles of pharmacology. In: Miller RD, Eriksson L, Fleisher L, Kronish JW, Young WL, editors. Miller’s anesthesia, Chap 19. 7th ed. Philadelphia: Elsevier; 2010. p. 479.
2. Patel B, Patel H, Vachhrajani P, Shah D, Sarvaia A. Adaptive smith predictor controller for total intravenous anesthesia automation. Biomed Eng Lett. 2019;9:127–44.
3. Navarro-Guerrero G, Tang Y. Fractional-order closed-loop model reference adaptive control for anesthesia. Algorithms. 2018;11(7):106.
4. Naşcu I, Oberdieck R, Pistikopoulos EN. Explicit hybrid model predictive control strategies for intravenous anaesthesia. Comput Chem Eng. 2017;106:814–25. https://doi.org/10.1016/j.compchemeng.2017.01.033.
5. Krieger A, Pistikopoulos EN. Model predictive control of anesthesia under uncertainty. Comput Chem Eng. 2014;71:699–707. https://doi.org/10.1016/j.compchemeng.2014.07.025.
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