[Development of a new closed-loop system for controlling mivacurium-induced neuromuscular blockade]

Closed loops in anaesthesia

Closed-loop systems are able to make their own decisions and to try to reach and maintain a preset target. As a result, they might help the anaesthetist to optimise the titration of drug administration without any overshoot, controlling physiological functions and guiding monitoring variables. Thanks to the development of fast computer technology and more reliable pharmacological effect measures, the study of automation in anaesthesia has regained popularity. This short review focuses on the most recently developed and tested feedback systems in anaesthesia. Various new approaches for controlling the administration of intravenous and inhaled hypnotic-anaesthetic drugs have recently been published. For analgesics, a framework for further research has been presented in the literature. For other drugs, such as muscle relaxants and haemodynamic agents, only short reviews can be found. Until now, most of these systems have had to be under development. The challenge is now fully to establish the safety, efficacy, reliability and utility of closed-loop anaesthesia so that it can be adopted in the clinical setting. Besides, their role in optimising the controlled variables and control models, these systems have to be tested in extreme circumstances in order to test their robustness.

[Artificial neural networks. Theory and applications in anesthesia, intensive care and emergency medicine]

Artificial neural networks (ANN) are constructed to simulate processes of the central nervous system of higher creatures. An ANN consists of a set of processing units (nodes) which simulate neurons and are interconnected via a set of "weights" (analogous to synaptic connections in the nervous system) in a way which allows signals to travel through the network in parallel. The nodes (neurons) are simple computing elements. They accumulate input from other neurons by means of a weighted sum. If a certain threshold is reached the neuron sends information to all other connected neurons otherwise it remains quiescent. One major difference compared with traditional statistical or rule-based systems is the learning aptitude of an ANN. At the very beginning of a training process an ANN contains no explicit information. Then a large number of cases with a known outcome are presented to the system and the weights of the inter-neuronal connections are changed by a training algorithm designed to minimise the total error of the system. A trained network has extracted rules that are represented by the matrix of the weights between the neurons. This feature is called generalisation and allows the ANN to predict cases that have never been presented to the system before. Artificial neural networks have shown to be useful predicting various events. Especially complex, non-linear, and time depending relationships can be modelled and forecasted. Furthermore an ANN can be used when the influencing variables on a certain event are not exactly known as it is the case in financial or weather forecasts. This article aims to give a short overview on the function of ANN and their previous use and possible future applications in anaesthesia, intensive care, and emergency medicine.

Closed-loop control of anaesthesia

PURPOSE OF REVIEW

Closed-loop systems are able to make decisions on their own and try to reach and maintain a preset target. As a result, they might help the anaesthesiologist in optimizing the titration of drug administration without overshooting, controlling physiological functions and guiding monitoring variables. Thanks to the development of fast computer technology and more reliable pharmacological effect measures, the study of automation in anaesthesia has regained popularity.

RECENT FINDINGS

This short review focuses on the most recently developed and tested feed-back systems in anaesthesia. Various new approaches for controlling the administration of intravenous and inhaled hypnotic-anaesthetic drugs have been published recently. For analgesics, a framework for further research has been presented in the literature. For other drugs, such as muscle relaxants and haemodynamics, a short review can be found.

SUMMARY

Until now, most of these systems are still under development. The challenge is now to establish fully the safety, efficacy, reliability and utility of closed-loop anaesthesia for its adoption into the clinical setting. Besides the optimization of controlled variables and control models, these systems have to be tested in extreme circumstances.