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Revista Cubana de Informática Médica

On-line version ISSN 1684-1859


GONZALEZ RUBIO, Tahimy et al. Automatic monitoring of sedation states in electroencephalographic signals. RCIM [online]. 2019, vol.11, n.1, pp.18-32.  Epub June 01, 2019. ISSN 1684-1859.

General anesthesia provide the patient states of unconsciousness, amnesia and analgesia, however, cases of intraoperative awareness are reported. Due to the incidence of this phenomenon and the psychosomatic effects it causes, the Neuroscience Studies Center, Images and Signals Processing at the University of Oriente, and the General Hospital "Juan Bruno Zayas Alfonso" both in Santiago de Cuba, Cuba, implement a methodology that allows the automatic detection of anesthetic sedation states applying Artificial Intelligence. For this, the signals recorded by the electroencephalographic channel F4, nine spectral parameters, the Support Vector Machines and the Neuro-Fuzzy Systems were used. In the automatic recognition of the Sedation States: Profound, Moderate and Mild an Accuracy of 96.12%, 90.06% and 90.24% respectively was achieved with the Support Vector Machines, so the use of the electroencephalographic channel F4 is proposed in the detection of anesthetic states.

Keywords : sedation states; electroencephalographic signal; artificial intelligence; intraoperative awakening.

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