Biomed Eng Lett.  2019 Feb;9(1):127-144. 10.1007/s13534-018-0090-3.

Adaptive smith predictor controller for total intravenous anesthesia automation

Affiliations
  • 1Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India. bhavina.patel@scet.ac.in, hgp.eed@svnit.ac.in
  • 2Surat Municipal Institute of Medical Education and Research (SMIMER), Surat, India.
  • 3U. N. Mehta Institute of Cardiology and Research, Ahmedabad, India.

Abstract

Anesthetic agent propofol needs to be administered at an appropriate rate to prevent hypotension and postoperative adverse reactions. To comprehend more suitable anesthetic drug rate during surgery is a crucial aspect. The main objective of this proposal is to design robust automated control system that work effi ciently in most of the patients with smooth BIS and minimum variations of propofol during surgery to avoid adverse post reactions and instability of anesthetic parameters. And also, to design advanced computer control system that improves the health of patient with short recovery time and less clinical expenditures. Unlike existing research work, this system administrates propofol as a hypnotic drug to regulate BIS, with fast bolus infusion in induction phase and slow continuous infusion in maintenance phase of anesthesia. The novelty of the paper lies in possibility to simplify the drug sensitivity-based adaption with infusion delay approach to achieve closedloop control of hypnosis during surgery. Proposed work uses a brain concentration as a feedback signal in place of the BIS signal. Regression model based estimated sensitivity parameters are used for adaption to avoid BIS signal based frequent adaption procedure and large off set error. Adaptive smith predictor with lead-lag fi lter approach is applied on 22 diff erent patients' model identifi ed by actual clinical data. The actual BIS and propofol infusion signals recorded during clinical trials were used to estimate patient's sensitivity parameters EC50 and λ. Simulation results indicate that patient's drug sensitivity parameters based adaptive strategy facilitates optimal controller performance in most of the patients. Results are obtained with proposed scheme having less settling time, BIS oscillations and small off set error leads to adequate depth of anesthesia. A comparison with manual control mode and previously reported system shows that proposed system achieves reduction in the total variations of the propofol dose. Proposed adaptive scheme provides better performance with less oscillation in spite of computation delay, surgical stimulations and patient variability. Proposed scheme also provides improvement in robustness and may be suitable for clinical practices.

Keyword

Adaptive smith predictor with lead–lag fi lter (ASP); Electroencephalography (EEG); Intra venous (IV); Target control infusion (TCI); Propofol

MeSH Terms

Anesthesia
Anesthesia, Intravenous*
Automation*
Brain
Health Expenditures
Humans
Hypnosis
Hypotension
Propofol
Propofol
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