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Regulation of hypnosis in Propofol anesthesia administration based on non-linear control strategy

Overview of attention for article published in Brazilian Journal of Anesthesiology, May 2016
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Title
Regulation of hypnosis in Propofol anesthesia administration based on non-linear control strategy
Published in
Brazilian Journal of Anesthesiology, May 2016
DOI 10.1016/j.bjane.2015.08.011
Pubmed ID
Authors

Muhammad Ilyas, Ali Khaqan, Jamshed Iqbal, Raja Ali Riaz

Abstract

Continuous adjustment of Propofol in manual delivery of anesthesia for conducting a surgical procedure overburdens the workload of an anesthetist who is working in a multi-tasking scenario. Going beyond manual administration and Target Controlled Infusion, closed-loop control of Propofol infusion has the potential to offer several benefits in terms of handling perturbations and reducing the effect of inter-patient variability. This paper proposes a closed-loop automated drug administration approach to control Depth Of Hypnosis in anesthesia. In contrast with most of the existing research on anesthesia control which makes use of linear control strategies or their improved variants, the novelty of the present research lies in applying robust control strategy i.e. Sliding Mode Control to accurately control drug infusion. Based on the derived patient's model, the designed controller uses measurements from EEG to regulate DOH on Bispectral Index by controlling infusion rate of Propofol. The performance of the controller is investigated and characterized with real dataset of 8 patients undergoing surgery. Results of this in silico study indicate that for all the patients, with 0% overshoot observed, the steady state error lies in between ±5. Clinically, this implies that in all the cases, without any overdose, the controller maintains the desired DOH level for smooth conduction of surgical procedures.

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The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Turkey 1 4%
Unknown 23 96%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 21%
Student > Master 3 13%
Student > Doctoral Student 2 8%
Lecturer 2 8%
Researcher 2 8%
Other 4 17%
Unknown 6 25%
Readers by discipline Count As %
Medicine and Dentistry 6 25%
Computer Science 2 8%
Engineering 2 8%
Social Sciences 2 8%
Psychology 1 4%
Other 3 13%
Unknown 8 33%