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Adaptive smith predictor controller for total intravenous anesthesia automation

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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 efficiently 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 closed-loop 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 offset error. Adaptive smith predictor with lead–lag filter approach is applied on 22 different patients’ model identified 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 offset 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.

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Acknowledgements

The authors would like to thank to anesthesia department team of the SMIMER hospital, Surat for providing the clinical environment facility and drug dose combination as per proposed scheme. The authors are grateful to anonymous reviewers for their useful suggestions to improve the manuscript.

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Authors and Affiliations

  1. Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India

    Bhavina Patel & Hiren Patel

  2. Surat Municipal Institute of Medical Education and Research (SMIMER), Surat, India

    Pragna Vachhrajani & Divyang Shah

  3. U. N. Mehta Institute of Cardiology and Research, Ahmedabad, India

    Alpesh Sarvaia

Authors
  1. Bhavina Patel
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  2. Hiren Patel
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  3. Pragna Vachhrajani
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  4. Divyang Shah
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  5. Alpesh Sarvaia
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Correspondence to Bhavina Patel.

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Not applicable.

Ethical Approval

All procedures performed in study involving human participants were in accordance with the ethical standards of the Surat Municipal Institute of Medical Education and Research (SMIMER), India and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Appendix

Appendix

See Tables 8 and 9

Table 8 PK parameters calculation of bolus and continuous
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Table 9 Physiological parameters of the population (n = number of patients (22))
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Patel, B., Patel, H., Vachhrajani, P. et al. Adaptive smith predictor controller for total intravenous anesthesia automation. Biomed. Eng. Lett. 9, 127–144 (2019). https://doi.org/10.1007/s13534-018-0090-3

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  • DOI: https://doi.org/10.1007/s13534-018-0090-3

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