An adaptive multi-critic neuro-fuzzy control framework for intravenous anesthesia administration

Mohammad Javad Khodaei, M. Hadi Balaghi I., Amin Mehrvarz, Nader Jalili (Corresponding author)

Research output: Contribution to journalConference articlepeer-review

8 Citations (Scopus)
57 Downloads (Pure)


Development of closed-loop control strategies for drug infusion and delivery is one of the most recent efforts of control engineers and clinicians. This can be used especially in anesthesia during different surgeries to stabilize the patient in the desired awareness condition. In this paper, an adaptive neuro-fuzzy controller is proposed to overcome the current challenges in closed-loop control of anesthesia such as inter and intra patient variability, complex and nonlinear dynamics, measurement noises and surgical disturbances as well as the presence of undershoot and overshoot in the induction phase. The results show an acceptable performance of the proposed controller in solving these problems by providing a learning scheme.

Original languageEnglish
Pages (from-to)202-207
Number of pages6
Issue number34
Publication statusPublished - 8 Feb 2019
Event2nd IFAC Conference on Cyber-Physical and Human Systems CPHS 2018 - Miami, United States
Duration: 13 Dec 201815 Dec 2018


  • Closed-loop drug infusion
  • Critic-based fuzzy controller
  • Inter
  • intra patient variability
  • Intravenous anesthesia
  • Surgical disturbances


Dive into the research topics of 'An adaptive multi-critic neuro-fuzzy control framework for intravenous anesthesia administration'. Together they form a unique fingerprint.

Cite this