Open Access

ARTICLE

Intelligent Networked Control of Vasoactive Drug Infusion for Patients with Uncertain Sensitivity

Mohamed Esmail Karar^1,2,*, Amged Sayed A. Mahmoud^2,3

1 College of Computing and Information Technology (CCIT), Shaqra University, Shaqra, 11961, Saudi Arabia
2 Department of Industrial Electronics and Control Engineering, Faculty of Electronic Engineering (FEE), Menoufia University, Menouf, 32952, Egypt
3 Department of Electrical Energy Engineering, College of Engineering & Technology, Arab Academy for Science Technology & Maritime Transport, P.O. Box 12577, Smart Village, Smart Village-B 2401, Egypt

* Corresponding Author: Mohamed Esmail Karar. Email:

(This article belongs to the Special Issue: Explainable AI and Cybersecurity Techniques for IoT-Based Medical and Healthcare Applications)

Computer Systems Science and Engineering 2023, 47(1), 721-739. https://doi.org/10.32604/csse.2023.039235

Received 16 January 2023; Accepted 20 March 2023; Issue published 26 May 2023

Abstract

Abnormal high blood pressure or hypertension is still the leading risk factor for death and disability worldwide. This paper presents a new intelligent networked control of medical drug infusion system to regulate the mean arterial blood pressure for hypertensive patients with different health status conditions. The infusion of vasoactive drugs to patients endures various issues, such as variation of sensitivity and noise, which require effective and powerful systems to ensure robustness and good performance. The developed intelligent networked system is composed of a hybrid control scheme of interval type-2 fuzzy (IT2F) logic and teaching-learning-based optimization (TLBO) algorithm. This networked IT2F control is capable of managing the uncertain sensitivity of the patient to anti-hypertensive drugs successfully. To avoid the manual selection of control parameter values, the TLBO algorithm is mainly used to automatically find the best parameter values of the networked IT2F controller. The simulation results showed that the optimized networked IT2F achieved a good performance under external disturbances. A comparative study has also been conducted to emphasize the outperformance of the developed controller against traditional PID and type-1 fuzzy controllers. Moreover, the comparative evaluation demonstrated that the performance of the developed networked IT2F controller is superior to other control strategies in previous studies to handle unknown patients’ sensitivity to infused vasoactive drugs in a noisy environment.

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Keywords

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