Adaptive optimal target controlled infusion algorithm to prevent hypotension associated with labor epidural: An adaptive dynamic programming approach

Sherwin Davoud, Weinan Gao, Efrain Riveros-Perez

Research output: Contribution to journalArticle

Abstract

Patients receiving labor epidurals commonly experience arterial hypotension as a complication of neuraxial block. The purpose of this study was to design an adaptive optimal controller for an infusion system to regulate mean arterial pressure. A state–space model relating mean arterial pressure to Norepinephrine (NE) infusion rate was derived for controller design. A data-driven adaptive optimal control algorithm was developed based on adaptive dynamic programming (ADP). The stability and disturbance rejection ability of the closed-loop system were tested via a simulation model calibrated using available clinical data. Simulation results indicated that the settling time was six minutes and the system showed effective disturbance rejection. The results also demonstrate that the adaptive optimal control algorithm would achieve individualized control of mean arterial pressure in pregnant patients with no prior knowledge of patient parameters.

Original languageEnglish (US)
Pages (from-to)74-81
Number of pages8
JournalISA Transactions
Volume100
DOIs
StatePublished - May 2020

Keywords

  • Adaptive dynamic programming (ADP)
  • Adaptive optimal control
  • Norepinephrine pharmacokinetics
  • Obstetric anesthesia
  • Pregnancy
  • Target controlled infusion

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Instrumentation
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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