An Adaptive Monitoring Scheme for Automatic Control of Anaesthesia in dynamic surgical environments based on Bispectral Index and Blood Pressure
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During surgical procedures, bispectral index (BIS) is a well-known measure used to determine the patient’s depth of anesthesia (DOA). However, BIS readings can be subject to interference from many factors during surgery, and other parameters such as blood pressure (BP) and heart rate (HR) can provide more stable indicators. However, anesthesiologist still consider BIS as a primary measure to determine if the patient is correctly anaesthetized while relaying on the other physiological parameters to monitor and ensure the patient’s status is maintained. The automatic control of administering anesthesia using intelligent control systems has been the subject of recent research in order to alleviate the burden on the anesthetist to manually adjust drug dosage in response physiological changes for sustaining DOA. A system proposed for the automatic control of anesthesia based on type-2 Self Organizing Fuzzy Logic Controllers (T2-SOFLCs) has been shown to be effective in the control of DOA under simulated scenarios while contending with uncertainties due to signal noise and dynamic changes in pharmacodynamics (PD) and pharmacokinetic (PK) effects of the drug on the body. This study considers both BIS and BP as part of an adaptive automatic control scheme, which can adjust to the monitoring of either parameter in response to changes in the availability and reliability of BIS signals during surgery. The simulation of different control schemes using BIS data obtained during real surgical procedures to emulate noise and interference factors have been conducted. The use of either or both combined parameters for controlling the delivery Propofol to maintain safe target set points for DOA are evaluated. The results show that combing BIS and BP based on the proposed adaptive control scheme can ensure the target set points and the correct amount of drug in the body is maintained even with the intermittent loss of BIS signal that could otherwise disrupt an automated control system.
KeywordsAnesthesia Bispectral index Blood pressure Depth of anesthesia Propofol Type-2 Self Organizing Fuzzy Logic Controllers Pharmacodynamics and pharmacokinetic
This study was funded by National Chung-Shan Institute of Science & Technology in Taiwan (Grant Numbers: CSIST-095-V201 and CSIST-095-V202).
Compliance with ethical standards
Conflict of interest
Yu-Ning Yu, Faiyaz Doctor, Shou-Zen Fan, Jiann-Shing Shieh each declare that they has no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- 1.Kee, W. D. N., Lee, A., Khaw, K. S., Ng, F. F., Karmakar, M. K., and Gin, T., A randomized double-blinded comparison of phenylephrine and ephedrine infusion combinations to maintain blood pressure during spinal anesthesia for cesarean delivery: the effects on fetal acid-base status and hemodynamic control. Anesth. Analg. 107:1295–1302, 2008.CrossRefGoogle Scholar
- 2.Nunes, C. S., Mendonca, T., Bras, S., Ferreira, D. A., and Amorim, P., Modeling anesthetic drugs' pharmacodynamic interaction on the bispectral index of the EEG: the influence of heart rate. In: Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, 2007, pp. 6479–6482.Google Scholar
- 4.da Silva, M. M., Mendonça, T., and Wigren, T., Online nonlinear identification of the effect of drugs in anaesthesia using a minimal parameterization and BIS measurements. In: American Control Conference (ACC), 2010, 2010, pp. 4379–4384.Google Scholar
- 6.Purdon, P. L., Pierce, E. T., Bonmassar, G., Walsh, J., Harrell, P. G., Kwo, J., Deschler, D., Barlow, M., Merhar, R. C., Lamus, C., Mullaly, C. M., Sullivan, M., Maginnis, S., Skoniecki, D., Higgins, H. A., and Brown, E. N., Simultaneous electroencephalography and functional magnetic resonance imaging of general anesthesia. Ann. N. Y. Acad. Sci. 1157:61–70, 2009.CrossRefPubMedPubMedCentralGoogle Scholar
- 7.Velly, L. J., Rey, M. F., Bruder, N. J., Gouvitsos, F. A., Witjas, T., Regis, J. M., Peragut, J. C., and Gouin, F. M., Differential dynamic of action on cortical and subcortical structures of anesthetic agents during induction of anesthesia. Anesthesiology 107:202–212, 2007.CrossRefPubMedGoogle Scholar
- 11.Shieh, J., Abbod, M., Hsu, C., Huang, S., Han, Y., and Fan, S., Monitoring and control of anesthesia using multivariable selforganizing fuzzy logic structure. In: Fuzzy Systems in Bioinformatics and Computational Biology. Berlin, Germany: Springer, 2009, pp. 273–295.Google Scholar
- 15.Kumar, M. L., Harikumar, R., Vasan, A. K., Sudhaman, V., Fuzzy controller for auto-matic drug infusion in cardiac patients. In: Proceedings of the International MultiConference of Engineers and Computer Scientists (IMECS 2009), Citeseer, 2009.Google Scholar
- 19.Esmaeili, V., Assareh, A., Shamsollahi, M. B., Moradi, M. H., and Arefian, N. M., Estimating the depth of anesthesia using fuzzy soft computation applied to EEG features. Intell. Data Anal. 12(4):393–407, 2008.Google Scholar
- 20.Shieh, J.-S., Chang, L.-W., Fan, S.-Z., Liu, C.-C., and Huang, H.-P., Automatic control of anaesthesia using hierarchical structure. Biomed. Eng.-Appl. Basis Commun. 10:195–202, 1998.Google Scholar
- 21.Liu, N., Chazot, T., Genty, A., Landais, A., Restoux, A., McGee, K. et al., Titration of propofol for anesthetic induction and maintenance guided by the bispectral index: closed-loop versus manual control: a prospective, randomized, multicenter study. Anesthesiology 104:686–695, 2006.CrossRefPubMedGoogle Scholar
- 24.Diwase, D. S., and Jasutkar, R. W., Expert controller for estimating dose of isoflurane. Int. J. Adv. Eng. Sci. Technol. 9:218–221, 2011.Google Scholar
- 25.Jiming, C., Kejie, C., Youxian, S., and Yang, X., Continuous drug infusion for diabetestherapy: a closed-loop control system design. EURASIP J. Wirel. Commun. Netw. 2008, 2008.Google Scholar
- 29.Shieh, J.-S., Chang, L.-W., Yang, T.-C., and Liu, C.-C., An enhanced patient controlled analgesia (EPCA) for the extracorporeal shock wave lithotripsy (ESWL). Biomed. Eng.: Appl. Basis Commun. 19:7–17, 2007.Google Scholar
- 30.Shieh, J.-S., Abbod, M. F., Krishna, E. D., Chou, Y.-C., and Fan, S.-Z., The simulation of con-trolling of anesthesia using a novel multivariable fuzzy logic and self-organizing fuzzy logic controller. In: Hertzog, M., Kuhn, Z. (Eds), General anesthesia research developments. New York: Nova Science Publishers Inc., 2009.Google Scholar
- 31.Liu, Y.-X., Doctor, F., Fan, S.-Z., and Shieh, J.-S., Performance Analysis of Extracted Rule-Based Multivariable Type-2 Self-Organizing Fuzzy Logic Controller Applied to Anesthesia. Biomed. Res. Int. 2014:1–19, 2014.Google Scholar
- 34.Chuang, C.-T., Fan, S.-Z., and Shieh, J.-S., Muscle relaxation controlled by automated administration of cisatracurium. Biomed. Eng.: Appl. Basis Commun. 18:284–295, 2006.Google Scholar
- 36.Ingole, D., and Kvasnica, M., FPGA Implementation of Explicit Model Predictive Control for Closed Loop Control of Depth of Anesthesia⋆, 2015.Google Scholar
- 40.Liu, Y.-X., Doctor, F., Shieh, J.-S., Fan, S.-Z., and Jen, K.-K., Multivariable type-2 self-organizing fuzzy logic controllers for regulating anesthesia with rule base extraction. In: Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, Taipei, Taiwan, 2013.Google Scholar
- 42.Araujo, H., Xiao, B., Liu, C., Zhao, Y., and Lam, H., Design of Type-1 and Interval Type-2 Fuzzy PID Control for Anesthesia Using Genetic Algorithms. J. Intell. Learn. Syst. Appl. 6:70, 2014.Google Scholar
- 43.Bras, S., Ribeiro, L., Ferreira, D., Antunes, L. H. M., and Nunes, C. S., Controlling the hypnotic drug (propofol) to maintain a stable depth of anesthesia, in dogs. In: Medical Measurements and Applications (MeMeA), 2014 I.E. International Symposium on, 2014, pp. 1–5.Google Scholar
- 46.Struys, M., De Smet, T., Versichelen, L., Van de Velde, S., Van den Broecke, R., and Mortier, E. P., Comparison of closed-loop controlled administration of propofol using Bispectral Index as the controlled variable versus" standard practice" controlled administration. Anesthesiology 95:6–17, 2001.CrossRefPubMedGoogle Scholar