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Communication Dans Un Congrès Année : 2023

Data-based Extended Moving Horizon Estimation for MISO Anesthesia Dynamics

Résumé

This paper presents an extended moving horizon observer to estimate both the states and the pharmacodynamic (PD) parameters of an anesthesia model, based on real data. The inputs of this model are the injection rates of Propofol and Remifentanil. The states represent the concentration of the anesthetic agents in different compartments of the human body (muscles, fat, blood) and in the effect site. The considered output is the Bispectral index (BIS) which is derived from the electroencephalogram (EEG). The observer is designed such that the parameters are estimated during the anesthesia induction phase, and then almost frozen for the rest of the surgery. The estimator is validated on real data that were extracted from the VitalDB database [12].
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Dates et versions

hal-04295820 , version 1 (20-11-2023)

Identifiants

  • HAL Id : hal-04295820 , version 1

Citer

Kaouther Moussa, Bob Aubouin-Pairault, Mazen Alamir, Thao Dang. Data-based Extended Moving Horizon Estimation for MISO Anesthesia Dynamics. CDC 2023 - 62nd IEEE Conference on Decision and Control, Dec 2023, Singapore, Singapore. ⟨hal-04295820⟩
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