Decision Support System for Anesthetists

Anesthesia

General Anesthesia, Anesthesia Awareness, Anesthesia overdose

The balanced anesthesia process contains three main parts: the control of hypnosis, analgesia, and neuromuscular blockade. For the induction phase, the anesthesiologist performs protocols based on prior planning specific to each patient and usually performs these controls by monitoring the classic vital signs and other clinical signs for the maintenance phase. In a way, this professional is the controller in a control system that acts on the plant (the patient) through the infusion of hypnotic drugs, analgesics and neuromuscular blockers. In addition, the anesthesiologist estimates the state of consciousness, the level of analgesia and the level of neuromuscular blockage through other indirect measures, as well as a state observer. There are different techniques for direct monitoring of these three anesthesia variables (DoA, NMB and NoL), such as BIS and Narcotrend, but all have some disadvantages, especially when the anesthesia process combines different drugs. This work proposes a new way of evaluating DoA, NMB and NoL using data fusion techniques to combine classical clinical signs with advanced EEG monitoring techniques to provide a decision support system for the anesthesiologist.

The balanced anesthesia process contains three main parts: the control of hypnosis, the analgesia and neuromuscular blockade. For the induction phase, the anesthesiologist performs protocols based on prior planning specific to each patient. Normally, the anesthesiologist controls the process by monitoring the classical vital signs and other clinical most common signs during the maintenance phase. In a way, this professional is the controller in a control system that acts on the plant (the patient) through the infusion of hypnotic and analgesic drugs and neuromuscular blockers. In addition, the anesthesiologist estimates the the level of consciousness, of nociception and the level of neuromuscular blockade through these indirect measurements, just as a state observer in a control system would do. There are different techniques for the direct monitoring of these three variables of anesthesia (DoA, NMB and NoL), such as BIS and Narcotrend, but all of them present a few disadvantages and mis-measurements, especially when the anesthesia process combines different drugs. This work proposes a new way of evaluating DoA, NMB and NoL, using techniques to combine classical clinical signs with advanced EEG monitoring, to provide a decision support system for the anesthesiologist. For this, we will perform data acquisition from the equipment usually used in surgical procedures with general anesthesia, such as ECG, EEG, blood pressure, mechanical ventilation, among others. In short, all data of the patient's vital signs during the procedure and the actions taken by the anesthesiologist and surgeons. The data will be concentrated on a specific equipment, and will be analyzed together with the data of other patients to improve the mathematical models involved in the process.

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