Periodic Reporting for period 1 - ACTAN (Automatic Control of Anaesthesia)
Periodo di rendicontazione: 2020-09-01 al 2022-08-31
The ACTAN project addressed the automatic control of anesthesia, and the objective was to develop an efficient and robust solution to increase patient safety and reduce post-operative complications. Automatic anesthesia 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 anesthesiologist’s workload, limiting the influence of the human factor and minimizing (i.e. personalizing) the amount of drugs used. In this context, patient safety can be improved thus tackling both a severe public health problem and the significant economic burden on limited health resources. In this project a novel event-based model predictive control approach for the anesthesia process was proposed, 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 proposed event-based approach. The main objective was to develop new control approaches and optimize their performance in order to meet clinical requirements. Through the presented research, it was possible to push the theoretical developments to the next stage, making them valuable milestones in the extensive implementation of automatic control techniques in the anesthesia process.
Under ACTAN project the main defined objective was to develop an event-based model predictive control framework for the anesthesia process. For this, the automated anesthesia process was addressed as a whole, while considering each of the subsystems involved and their specific requirements and limitations. A correct understanding of the anesthesia process requires a multidisciplinary approach incorporating various scientific disciplines, thus providing a common framework to achieve the desired goals and to ascertain any possible limitations.
In the executed research, special emphasis was placed on the depth of hypnosis and analgesia - the most important factors in the anesthesia procedure. The control system for the depth of hypnosis uses propofol administration as the control variable and the BIS index as the controlled variable. For this, several control system configurations were developed including Model Predictive Control (MPC) algorithm extended with event-based approaches. The development of the control structure was performed using a nonlinear model representing the propofol effect on the BIS index. Applying such a control structure makes the use of a linear MPC algorithm possible, exploiting the constraint handling mechanism with low computational complexity. The main objective of this novel control system was the effective use of control resources (the propofol dosage), keeping performance within the desired limits. To take full advantage of automatic control in anesthesia, there is also the need for the simultaneous control of co-administrated drugs since they have the influence on the depth of hypnosis due to mutual interaction. For this, it was necessary to design a novel robust control scheme able to handle the nonlinear response profile as well as the inter- and intra-patient variations in the patient’s analgesic state to analgesic drug infusion (e.g. reminfetanil). In this way, the developed advanced control approaches provide an efficient tool for automated anesthesia, reducing the risks of intra- and post-operative complications. It should be highlighted that the selected control system configurations were practically evaluated on real patients. The developed control algorithms were adapted and embedded on existing medical, clinical or health available infrastructures/devices/software. In the context of the project goals, the control strategies developed under ACTAN project were validated at Brescia Hospital. The practical evaluation is a big step forward in developing anesthesia process automation, demonstrating its feasibility especially in the context of model predictive control approaches.
Another goal of the MSCA Individual Fellowship is to foster the development of the individual researcher. The opportunity to manage a scientific project such as this one gave me indeed the knowledge, experience, skills, and required competency in scientific project leadership and management which will be indispensable in my future career. The ACTAN project allowed me to gain further experience in academic activities since I was involved in research initiation and coordination, and I participated in the supervision of a PhD student. These tasks provided me with additional experience in communication skills, know-how sharing and research expertise with other members of the host and collaborating institutions. Throughout the ACTAN project, I have gained research experience in the interdisciplinary collaboration thorough integration with the host research group, developed project management skills as well as learned new methodologies and techniques for organization and communication. Moreover, I have gained international experience that completes my track record, giving me an advantage in permanent position opportunities. In addition, the experience and knowledge gained in this action significantly increased my chances of attaining future funding opportunities. Considering all of these advantages, I have acquired versatile competencies allowing me to reach professional maturity. Moreover, it needs to be highlighted that outcomes from ACTAN project funded the basis for further research on MPC approach for automation in anesthesia process that undoubtedly will be continued in my future research.
In the executed research, special emphasis was placed on the depth of hypnosis and analgesia - the most important factors in the anesthesia procedure. The control system for the depth of hypnosis uses propofol administration as the control variable and the BIS index as the controlled variable. For this, several control system configurations were developed including Model Predictive Control (MPC) algorithm extended with event-based approaches. The development of the control structure was performed using a nonlinear model representing the propofol effect on the BIS index. Applying such a control structure makes the use of a linear MPC algorithm possible, exploiting the constraint handling mechanism with low computational complexity. The main objective of this novel control system was the effective use of control resources (the propofol dosage), keeping performance within the desired limits. To take full advantage of automatic control in anesthesia, there is also the need for the simultaneous control of co-administrated drugs since they have the influence on the depth of hypnosis due to mutual interaction. For this, it was necessary to design a novel robust control scheme able to handle the nonlinear response profile as well as the inter- and intra-patient variations in the patient’s analgesic state to analgesic drug infusion (e.g. reminfetanil). In this way, the developed advanced control approaches provide an efficient tool for automated anesthesia, reducing the risks of intra- and post-operative complications. It should be highlighted that the selected control system configurations were practically evaluated on real patients. The developed control algorithms were adapted and embedded on existing medical, clinical or health available infrastructures/devices/software. In the context of the project goals, the control strategies developed under ACTAN project were validated at Brescia Hospital. The practical evaluation is a big step forward in developing anesthesia process automation, demonstrating its feasibility especially in the context of model predictive control approaches.
Another goal of the MSCA Individual Fellowship is to foster the development of the individual researcher. The opportunity to manage a scientific project such as this one gave me indeed the knowledge, experience, skills, and required competency in scientific project leadership and management which will be indispensable in my future career. The ACTAN project allowed me to gain further experience in academic activities since I was involved in research initiation and coordination, and I participated in the supervision of a PhD student. These tasks provided me with additional experience in communication skills, know-how sharing and research expertise with other members of the host and collaborating institutions. Throughout the ACTAN project, I have gained research experience in the interdisciplinary collaboration thorough integration with the host research group, developed project management skills as well as learned new methodologies and techniques for organization and communication. Moreover, I have gained international experience that completes my track record, giving me an advantage in permanent position opportunities. In addition, the experience and knowledge gained in this action significantly increased my chances of attaining future funding opportunities. Considering all of these advantages, I have acquired versatile competencies allowing me to reach professional maturity. Moreover, it needs to be highlighted that outcomes from ACTAN project funded the basis for further research on MPC approach for automation in anesthesia process that undoubtedly will be continued in my future research.
The ACTAN project explored several engineering areas that were combined in order to understand particular problems that fit into the EU Work Program for Horizon Europe (and previously by Horizon 2020). Based on the conclusions, it also has provided the methodology that advances the state-of-the-art of automatic control in the anesthesia process. The proposed research was based both on simulations - providing theoretical fundamentals, and on real patients providing practical validation and feasibility of the proposed methodology. The (theoretical and practical) developments and studies of the predictive control algorithms were published (or submitted for evaluation) in 5 high impact journal papers. Moreover, a study on the process noise issue was presented at an international conference. Furthermore, a thematic workshop dedicated to the automatic control of the anesthesia system was co-organized by dr. Andrzej Pawlowski (grant holder) and prof. Antonio Visioli (supervisor). Additionally, concepts for further clinical implementations for personalized cardiological interventions were elaborated in a chapter for a forthcoming book on personalized medicine. Moreover, it was shown that the automatic control system can limit the influence of the human factor and provide a more unified solution for the anesthesia process based on novel approaches. Activities developed under this action provided the 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.