Automation empowers self-sustainable adaptive processes and personalized services in
many industries. The implementation of the integrated healthcare paradigm built on Health …

Over the past decade, there has been an unprecedented international focus on improved
quality and availability of medical care, which has reignited interest in clinical automation …

In the last three decades, artificial intelligence (AI) has been increasingly and vigorously
utilized for process control in chemical, biochemical, and biomedical engineering. These …

In this work, we present a robust Model Predictive Control (MPC) strategy based on linear
matrix inequalities (LMIs) for the intravenous administration of Propofol, a drug which is used …

This paper presents an adaptive neural network acting like a proportional-integral-derivative
(PID) controller that uses an intelligent meta-heuristic technique to improve the drug infusion …

Anesthesia, a clinical procedure used daily on millions of people worldwide, can be prone to
error because of inter-and intrapatient variability, despite being a familiar routine for …

The safe and personalized administration of anesthetic drugs is a significant concern in
clinical practice, and automated control of anesthesia can address this issue by reducing …

General anesthesia has improved considerably over the years due to the automation of drug
perfusion through closed-loop control which provided numerous advantages regarding …

This document describes the implementation of a neuro-fuzzy adaptive system MIMO
(Multiple Input Multiple Output), using two neuro-fuzzy MIMO systems: one for control and …

In this paper, a novel neural network based iterative learning controller for a hybrid
exoskeleton is presented. The control allocation between functional electrical stimulation …