TY - GEN
T1 - Model Predictive Control with Exponential Cost Function to Regulate the Propofol Infusion Rate
AU - Falcón, Fernanda
AU - Ramírez-Barrios, Miguel
AU - Sandre, Omar
AU - Mera, Manuel
AU - Ordaz, Patricio
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The anesthesia infusion process has been a topic of study for years due to the dangers that can lead to anesthesia management during general surgery. Therefore, the automation of the anesthesia delivery process is still a relevant problem; the automation problem consists of computing a reasonable infusion rate of the anesthetic drug so that the desired hypnosis level is reached. Most of the approaches are based on a mathematical model of the process, which can be assumed as LTI system with a static nonlinearity in the output. This model considers the drug infusion rate as the input, and the output is the bispectral index (BIS), which measures the hypnosis in the patient. Furthermore, these plant dynamics are based on a compartmental model and consider pharmacokinetics and pharmacodynamics effects. In the present contribution, a description of this mathematical model is presented wherewith a model predictive control (MPC) with exponential cost function is designed to regulate the hypnosis state in the patient. Finally, the proposed algorithm is simulated for a group of virtual patients.
AB - The anesthesia infusion process has been a topic of study for years due to the dangers that can lead to anesthesia management during general surgery. Therefore, the automation of the anesthesia delivery process is still a relevant problem; the automation problem consists of computing a reasonable infusion rate of the anesthetic drug so that the desired hypnosis level is reached. Most of the approaches are based on a mathematical model of the process, which can be assumed as LTI system with a static nonlinearity in the output. This model considers the drug infusion rate as the input, and the output is the bispectral index (BIS), which measures the hypnosis in the patient. Furthermore, these plant dynamics are based on a compartmental model and consider pharmacokinetics and pharmacodynamics effects. In the present contribution, a description of this mathematical model is presented wherewith a model predictive control (MPC) with exponential cost function is designed to regulate the hypnosis state in the patient. Finally, the proposed algorithm is simulated for a group of virtual patients.
KW - Closed-loop anesthesia
KW - Model Predictive Control
UR - http://www.scopus.com/inward/record.url?scp=85143974107&partnerID=8YFLogxK
U2 - 10.1109/COMRob57154.2022.9962254
DO - 10.1109/COMRob57154.2022.9962254
M3 - Contribución a la conferencia
AN - SCOPUS:85143974107
T3 - Proceedings of the 24th Robotics Mexican Congress, COMRob 2022
SP - 89
EP - 94
BT - Proceedings of the 24th Robotics Mexican Congress, COMRob 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th Robotics Mexican Congress, COMRob 2022
Y2 - 9 November 2022 through 11 November 2022
ER -