Git repository to study the control loop of porpofol and remifentanil to BIS in the context of Genreal Anesthesia.
To reproduce the results of the journal paper please used the version tagged here. If you use the code for research please cite B. Aubouin–Pairault, M. Fiacchini, and T. Dang, “Online identification of pharmacodynamic parameters for closed-loop anesthesia with model predictive control,” Computers & Chemical Engineering, vol. 191, p. 108837, Dec. 2024, doi: 10.1016/j.compchemeng.2024.108837.
Use the Python Anesthesia Simulator to run the simulation and compute the performances metrics.
Abstract: In this paper, a controller is proposed to automate the injection of propofol and remifentanil during general anesthesia using bispectral index (BIS) measurement. To handle the parameter uncertainties due to inter- and intra-patient variability, an extended estimator is used coupled with a Model Predictive Controller (MPC). Two methods are considered for the estimator: the first one is a multiple extended Kalman filter (MEKF), and the second is a moving horizon estimator (MHE). The state and parameter estimations are then used in the MPC to compute the next drug rates. The methods are compared with a PID from the literature. The robustness of the controller is evaluated using Monte-Carlo simulations on a wide population, introducing uncertainties in all parts of the model. Results both on the induction and maintenance phases of anesthesia show the potential interest in using this adaptive method to handle parameter uncertainties.
Install all the required packages with the command:
pip install .
Launch each study located in the scripts/studies folder.
Caution: The simulation scripts may take time to run (approx 5h on a 32 thread server for the MPC ones).
The results can be found in the plot results notebook.
The package can be used to simulate the anesthesia induction phase with the MPC and PID controllers. A simple example is given in the test notebook, for more in depth change the files of the package can be modified.
Bob Aubouin--Pairault, Mirko Fiacchini, Thao Dang
GPL-3.0