By Topic

Closed-Loop Anesthetic Drug Concentration Estimation Using Clinical-Effect Feedback

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Jin-Oh Hahn ; Dept. of Mech. Eng., Univ. of Alberta, Edmonton, AB, Canada ; Dumont, G.A. ; Ansermino, J.M.

This letter presents a novel closed-loop approach to anesthetic drug concentration estimation using clinical-effect measurement feedback. Compared with the open-loop prediction used in current target-controlled infusion systems, closed-loop estimation exploits the discrepancy between the measured and predicted clinical effects to make corrections to the drug-concentration estimate, achieving improved robustness against variability in the patient pharmacokinetics and pharmacodynamics. A robust estimator, which processes drug administration and clinical-effect measurements to estimate the plasma- and effect-site drug concentrations, is designed using -synthesis theory. Initial proof of principle of the closed-loop estimation is demonstrated using the Monte Carlo simulation of surgical procedures with a wide range of patient models. Closed-loop estimation results in statistically significant reductions in median percentage, median absolute percentage, and maximum absolute percentage drug-concentration errors compared to open-loop prediction.

Published in:

Biomedical Engineering, IEEE Transactions on  (Volume:58 ,  Issue: 1 )