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Nonlinear adaptive control of the NeuroMuscular Blockade in anesthesia.

, , and . CDC/ECC, page 41-46. IEEE, (2011)

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Preface., , , and . Comput. Methods Programs Biomed., (2019)Adaptive predictive control with mean-square input constraint., , , and . Autom., 28 (3): 593-597 (1992)Neuro-fuzzy techniques to model pharmacodynamic interactions between anesthetic drugs on the bispectral index: A preliminary study., , , , and . J. Intell. Fuzzy Syst., 16 (1): 15-22 (2005)PH2 - A dermoscopic image database for research and benchmarking., , , , and . EMBC, page 5437-5440. IEEE, (2013)An optimal control approach to reference level tracking in general anesthesia., , , and . MED, page 124-129. IEEE, (2015)Hopfield neural networks for on-line parameter estimation., , and . Neural Networks, 22 (4): 450-462 (2009)Nonlinear Identification of a Minimal Neuromuscular Blockade Model in Anesthesia., , and . IEEE Trans. Contr. Sys. Techn., 20 (1): 181-188 (2012)A set-valued observer approach to multiple-model adaptive control of neuromuscular blockade., , , and . ACC, page 5598-5603. IEEE, (2012)Observer design in switching control of neuromuscular blockade: clinical cases., , , , , and . EMBC, page 5436-5439. IEEE, (2006)Exactly linearizing adaptive control of propofol and remifentanil using a reduced Wiener model for the depth of anesthesia., , and . CDC, page 368-373. IEEE, (2012)