R. Bharath Kumar 1 , P. Suresh This email address is being protected from spambots. You need JavaScript enabled to view it.1, and Hemakumar V.S. 1

1Dept of ECE, Vel Tech Rangarajan Dr.Sagunthala RD Institute of Science and Technology, Chennai, Tamil Nadu 600062


 

Received: February 1, 2021
Accepted: March 22, 2021
Publication Date: October 1, 2021

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.6180/jase.202110_24(5).0009  


ABSTRACT


In this present paper we had implemented an actual control and monitoring of anesthesia level given to the patients during surgery. To achieve this FUZZY LOGIC controller has been developed. It includes monitoring of patient’s body variable such as heart rate, diastolic and systolic pressure precisely and dynamically. Controlling is done by switching ON or OFF the pump using relay when there are any conflicts in set point values of the patient’s body parameters. By using Fuzzy Logic, we can continuously monitor and measure three different parameters they are pulse rate, systolic diastolic blood pressure and the dosage of stupor given to the patient varies linearly with measured input parameters.


Keywords: Fuzzy Logic; Stupor; Systolic; Diastolic


REFERENCES


  1. [1] T Dalkara, K Irikura, Z Huang, N Panahian, and MA Moskowitz. Cerebrovascular responses under controlled and monitored physiological conditions in the anesthetized mouse. Journal of Cerebral Blood Flow & Metabolism, 15(4):631–638, 1995.
  2. [2] B Wayne Bequette, Ramesh R Rao, B Wayne Bequette, and Rob J Roy. Control of Hemodynamic and Anesthetic States in Critical Care Patients Control of Hemodynamic and Anesthetic States in Critical Care Patients. rpi.edu, (APRIL 1999), 2016.
  3. [3] Kurt Becker, Bernhard Thull, Horst Käsmacher-Leidinger, Johannes Stemmer, Günther Rau, Günther Kalff, and Hans Jürgen Zimmermann. Design and validation of an intelligent patient monitoring and alarm system based on a fuzzy logic process model. Artificial Intelligence in Medicine, 11(1):33–53, 1997. ISSN 09333657.
  4. [4] M Dojat, F Pachet, Z Guessoum, D Touchard, A Harf, and L Brochard. NéoGanesh: A working system for the automated control of assisted ventilation in ICUs. Artificial Intelligence in Medicine, 11(2):97–117, 1997. ISSN 09333657.
  5. [5] Jiann Shing Shieh, Derek Arthur Linkens, and John E. Peacock. Hierarchical rule-based and self-organizing fuzzy logic control for depth of anaesthesia. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews, 29(1):98–109, 1999. ISSN 10946977.
  6. [6] Andrew Lowe, Michael J. Harrison, and Richard W Jones. Diagnostic monitoring in anaesthesia using fuzzy trend templates for matching temporal patterns. Artificial Intelligence in Medicine, 16(2):183–199, 1999. ISSN 09333657.
  7. [7] R Meier, J Nieuwland, S. Hacisalihzade, D. Steck, and A. Zbinden. Fuzzy control of blood pressure during anesthesia with isoflurane. In ieeexplore.ieee.org, pages 981–987, 1992. ISBN 0780302362.
  8. [8] Peter Samuelsson, Lars Brudin, and Rolf H Sandin. Late psychological symptoms after awareness among consecutively included surgical patients. Anesthesiology, 106(1): 26–32, 2007. ISSN 00033022.
  9. [9] PF White, JB Negus Journal of clinical Anesthesia, and undefined 1991. Sedative infusions during local and regional anesthesia: a comparison of midazolarn and propofol. Elsevier.
  10. [10] Ishwari Ingale. Study of Automatic Anesthesia Controller. IJIRT, 6(11), 2020.
  11. [11] A.J. Asbury. Fuzzy logic: new ways of thinking for anesthesia. British Journal of Anaesthesia, 75(1), 1995.
  12. [12] Rahim F, Deshpande A, and Hosseini A. Fuzzy Expert System for Fluid Management in General. Management, (4):256–267, 2007.
  13. [13] Ms. Dipti and S. Diwase. Expert Controller for Estimating Dose of Isoflurane. International Journal of Advanced Engineering Sciences and Technologies, 9(2):218–221, 2011.