ACTAN - Automatic Control of Anaesthesia

Objectives:  This project addresses the automatic control of anaesthesia and the objective of developing an efficient and robust solution to increase patient safety and reduce post-operative complications. Automatic anaesthesia control is seen as one of the most important ways of achieving this goal. The control system should be able to provide significant benefits such as reducing the anaesthesiologist’s workload, limiting the influence of the human factor and minimizing the amount of drugs used. In this context, patient safety will be improved thus tackling both a severe public health problem and the significant economic burden on limited health resources. This project will use a novel event-based model predictive control approach for the anaesthesia process, addressing the key questions of efficient drug use, robustness regarding inter/intra-patient variability as well as considering its implementation and evaluation on real patients. The proposed approach has many advantages that can be useful in clinical practice such as adapting the actuation rate to the state of the patient, thanks to its predictive capabilities and event-based approach. The main objective is to develop new control approaches and optimize their performance in order to meet clinical requirements. Through the presented research, it will be possible to push the theoretical developments to the next stage, making them valuable milestones in the extensive implementation of automatic control techniques in the anaesthesia process. Moreover, an automatic control system can limit the influence of the human factor and provide a more unified solution for the anaesthesia process based on novel approaches. Activities developed under this proposal provide a unique opportunity to improve the quality of life of EU citizens and to reinforce the EU position as a central player in the global context through the high quality innovative multidisciplinary research.

This project has received funding from the European Union’s Horizon 2020 research and innovation 

programme under the Marie Skłodowska-Curie grant agreement No 837912

Project data :

Fellowship holder: Andrzej Pawlowski, PhD

Funding: H2020-MSCA-IF-2018

Project ID: 837912

UniBS responsable : Prof. Antonio Visioli – Dipartimento di Ingegneria Meccanica e Industriale

Execution period: 01/05/2021 – 31/04/2023

EU contributtoin: € 183.473,28