Computational Intelligence for automatic monitoring and control of drug delivery during surgery

These systems need to control the infusion and concentration rates of different drugs into the patient’s body, Different patients have different physiological characteristics, medical conditions and and would be undergoing different types of surgical procedures.

Such systems need to monitor and maintain safe operational physiological set points for patients while contending with different uncertainties such as:

• Physiological differences in age, gender and pre-operative health condition.
• Individual pharmacokinetics and pharmacodynamic effects of the drugs.
• Dynamic multi variable physiological interactions.
• Noise and variability in signals sensed and monitored from the human body.

This project has developed new adaptive soft computing approaches based on Type-2 Self Organising Fuzzy Logic Controllers (SOFLCs) and in combination with other computational intelligence techniques.

We have already applied our approach to simulate a multivariable aesthesia monitoring and drug delivery system. Such a system can be used as part of an embedded methodology for autonomous drug delivery and training.

Partners

This research project is in collaboration with Department of Mechanical Engineering, Yuan Ze University and the Department of Anesthesiology, National Taiwan University Hospital, Taiwan.

Publications

• Z. Wei, F. Doctor, Y. Liu, S. Fan and J. Shieh, "An Optimized Type-2 Self-Organizing Fuzzy Logic Controller Applied in Anesthesia for Propofol Dosing to Regulate BIS" in IEEE Transactions on Fuzzy Systems, vol. 28, no. 6, pp. 1062-1072, June 2020.