A sedation patient simulator for patient-individualised optimal drug dosing in general anaesthesia

Research grant awarded by UEFISCDI Romania www.uefiscdi.gov.ro, project code: PN-III-P2-2.1-PED-2019-0322, 552PED/2020


A patient’s well-being during/after surgery is drastically affected by the application of general anaesthesia. Some components of anaesthesia are well characterised and described in the literature ( hypnosis and neuromuscular blockade), however the analgesia model is missing entirely. Research upon the influence of the surgical stimulus on the patient and how it affects anaesthesia is also at its early beginning. A combined full model of these subsystems within the general anaesthesia paradigm is not yet investigated. Novel is also the multivariable predictive controller envisaged for the automatic control of anaesthesia. Both the full model and the controller are necessary to produce the final result of this project. The demonstration model to be developed and validated consists in a sedation patient simulator for patient-individualised optimal drug dosing in general anaesthesia. This simulator will be used as a benchmark to systematically allow the community for simulating various situations and testing various control algorithms and to create awareness and introduce the concept for practitioners in health institutions worldwide. It will also enable small and medium enterprises to pick up new technological advances necessary for commercial production of such sedation patient simulator for drug delivery medical applications. At least two benefits result from the development of such a sedation patient simulator. An optimal drug dosing system for sedation can significantly reduce costs due to two reasons: lower drug costs, as well as lower hospitalisation times. Finally, it has to be stated that for some of the benefits, it is hard to calculate cost, such as increased patient’s well-being when reducing Intensive Care Unit stay and a decreased nursing workload. All in all, the delivery of this demonstrator will enable further medical-engineering research towards anaesthesia regulatory paradigm.


The present project aims to address the issue of personalised medicine by applying readily available know-how to obtain an experimental, proof of concept patient- specific targeted drug delivery system to be used in both open, as well as closed loop analysis with applications to anesthesia paradigm. The demonstration model to be developed and validated consists in a sedation patient simulator for patient-individualised optimal drug dosing in general anaesthesia.




1. to characterize the effects of physiological time delays in the complete system, and the consequences for control performance and requirements for control algorithms/architecture.
2. to deliver a simulator of the complete system at hand, with mixed real-data and mimicked signals from real life situations.
3. to deliver a bullet-proof analysis of a complete regulatory dynamic system for controlling general anesthesia by means of all its three components: hypnosis, analgesia and neuromuscular blockade, also under surgical stimulus (acting as disturbance).


  1. Ghita, M. Neckebroek, C. Muresan, D. Copot (2020), Closed-Loop Control of Anesthesia: Survey on Actual Trends, Challenges and Perspectives,” inIEEE Access, vol. 8, pp. 206264-206279, 2020, doi: 10.1109/ACCESS.2020.3037725 (ISI impact factor 3.745)
  2. A. C. Diaz, M. Ghita, D. Copot, I. R. Birs, C. Muresan and C. Ionescu (2020), Context Aware Control Systems: An Engineering Applications Perspective, IEEE Access, vol. 8, pp. 215550-215569, doi: 10.1109/ACCESS.2020.3041357 (ISI impact factor 3.745)
  3. Ghita, M.; Neckebroek, M.; Juchem, J.; Copot, D.; Muresan, C.I.; Ionescu, C.M. (2020), Bioimpedance Sensor and Methodology for Acute Pain Monitoring, Sensors20, 6765, Doi: 10.3390/s20236765 (ISI impact factor 3.275)
  4. Birs, I.R., Muresan, C.I., Nascu, I., Ionescu, C. (2021), A Comparison between Fractional Order Control Strategies for a Submerged Nanorobot, The 29th Mediterranean Conference on Control and Automation (MED 2021), Bari, Italy, June 22-25, 2021, under review


Dr. Eng. Clara Ionescu– principal investigator

Dr. Eng. Cristina I. Muresan

Dr. Eng. Ioan Nascu

Dr. Eng. Eva H. Dulf

Dr. Eng. Ovidiu Prodan

Msc. Eng. Isabela Birs