• Jukka Kortelainen, Eero Väyrynen, Xiaofeng Jia, Tapio Seppänen, and Nitish Thakor.
• Department of Computer Science and Engineering, BOX 4500, FIN-90014 University of Oulu, Finland. jukka.kortelainen@ee.oulu.fi
• Conf Proc IEEE Eng Med Biol Soc. 2012 Jan 1; 2012: 4279-82.

AbstractIn animal studies, reliable measures for depth of anesthesia are frequently required. Previous findings suggest that the continuous depth of anesthesia indices developed for humans might not be adequate for rats whose EEG changes during anesthesia represent more of quick transitions between discrete states. In this paper, the automatic EEG-based detection of awakening from anesthesia was studied in rats. An algorithm based on Bayesian Information Criterion (BIC) is proposed for the assessment of the switch-like change in the signal characteristics occurring just before the awakening. The method was tested with EEGs recorded from ten rats recovering from isoflurane anesthesia. The algorithm was shown to be able to detect the sudden change in the EEG related to the moment of awakening with a precision comparable to careful visual inspection. Our findings suggest that monitoring such signal changes may offer an interesting alternative to the application of continuous depth of anesthesia indices when avoiding the awakening of the animal during e.g. a clinical experiment.

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