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Biomedical Signal Processing and Control

ISSN 1746-8094

1 paper in the library · publishing 2021

Papers

Differentiating propofol-induced altered states of consciousness using features of EEG microstates

Biomedical Signal Processing and Control February 1, 2021 Haidong Wang, Yubo Wang, Yun Zhang et al.

During propofol-induced unconsciousness, the brain's electrical activity patterns—EEG microstates—change in ways that can distinguish between resting, light, and deep anesthesia. Analyzing 60-channel EEG from 31 male subjects, the study identified 7 common and 2 anesthesia-specific microstate templates. Features such as the occurrence and duration of certain microstates decreased as consciousness suppression deepened. Machine learning models using these features classified the three consciousness levels with a mean accuracy of 85.6%. The findings suggest that microstate analysis may help reveal the neural mechanisms underlying propofol anesthesia and could provide useful markers for quantifying levels of consciousness.