This paper provides a visionary perspective on human-machine collaboration in a medical cyber-physical system (MCPS) during the 2020 pandemic context. For the time being, medical specialists in the operating room (OR) or Intensive Care Units (ICU) face special responsibilities when the procedures involve a patient with an infectious disease (e.g., COVID-19) that can cause several complications. The added workload of the anesthesiologist can be diminished by the context-aware pervasive assistance in the decision- making process for maintaining the optimal anesthesia and hemodynamics of the patient. A self-aware control system, with feedback from patient's monitored parameters and several surgical/ICU contextual data, is able to adapt his action accordingly, increasing treatment accuracy. The three main parts of general anesthesia (neuromuscular blockade, hypnosis and analgesia) and the hemodynamics (cardiac output, blood pressure) are perused from a global objective viewpoint, while intersecting the anesthesiologist's action upon his request. The integrative anesthesiologist-in-the-loop cyber-physical system (CPS) is emerging as an intelligent solution for hybrid control of anesthesia's depth, instead of total autonomous closed-loop controllers. This paper aims to create awareness throughout the anesthesiologists about the usefulness of integrating automation and data exchange in their clinical practice for providing increased attention to alarming situations. Moreover, it proposes an opening horizon for multi-disciplinary research. Hence, the connection between clinical and engineering frameworks envisages significant patient safety.

Perspectives on hybrid control of the anesthesia-hemodynamic system in the pandemic context

Visioli A.;
2021-01-01

Abstract

This paper provides a visionary perspective on human-machine collaboration in a medical cyber-physical system (MCPS) during the 2020 pandemic context. For the time being, medical specialists in the operating room (OR) or Intensive Care Units (ICU) face special responsibilities when the procedures involve a patient with an infectious disease (e.g., COVID-19) that can cause several complications. The added workload of the anesthesiologist can be diminished by the context-aware pervasive assistance in the decision- making process for maintaining the optimal anesthesia and hemodynamics of the patient. A self-aware control system, with feedback from patient's monitored parameters and several surgical/ICU contextual data, is able to adapt his action accordingly, increasing treatment accuracy. The three main parts of general anesthesia (neuromuscular blockade, hypnosis and analgesia) and the hemodynamics (cardiac output, blood pressure) are perused from a global objective viewpoint, while intersecting the anesthesiologist's action upon his request. The integrative anesthesiologist-in-the-loop cyber-physical system (CPS) is emerging as an intelligent solution for hybrid control of anesthesia's depth, instead of total autonomous closed-loop controllers. This paper aims to create awareness throughout the anesthesiologists about the usefulness of integrating automation and data exchange in their clinical practice for providing increased attention to alarming situations. Moreover, it proposes an opening horizon for multi-disciplinary research. Hence, the connection between clinical and engineering frameworks envisages significant patient safety.
2021
978-1-6654-2258-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/550008
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