2016, Number 3
Rev Cubana Invest Bioméd 2016; 35 (3)
González RT, Marañon REJ, Rodríguez AY, Montoya PA
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ABSTRACTIntroduction: During surgery a patient under general anesthesia must remain unconscious and insensitive to pain. However, cases have been reported of intraoperative awareness. Due to the incidence of this phenomenon and the adverse effects it causes, the Center for Neuroscience and Image and Signal Processing Studies of the University of Oriente, Cuba, is developing a prototype for an anesthesia monitor allowing detection of changes in anesthetic status based on automated recognition of Anesthetic Depth Levels in electroencephalographic signals.
Objective: Automatically detect anesthetic sedation states in electroencephalographic signals as a support system for intraoperative monitoring.
Methods: Recording was conducted of electroencephalographic signals from 27 patients undergoing general abdominal surgery. The channel selected for the study was F4. Detection of anesthetic depth levels was performed using Artificial Intelligence computer methods.
Results: The anesthetic depth scale was reduced to three levels. Recognition effectiveness was 90.24 % for the light level, 90.06 % for the moderate level, and 12 % for the deep level.
Conclusions: Three anesthetic depth levels are proposed, which were detected with above 90 % accuracy in electroencephalographic signals. The daily work of anesthesiologists will be improved with the use of the monitor being developed at the above mentioned study center. Results show that F4 derivation is representative of the effect of anesthetics upon brain activity.