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A machine learning approach to classify vigilance states in rats
2011
Expert systems with applications
Identifying the vigilance states of the mammalian is an important research topic to bioscience in recently years, which the vigilance states is usually categorized as slow wave sleep, rapid eye movement sleep, and awake, etc. To discriminate difference vigilance states, a well-trained expert needs spend a long time to analyze a mass of physiological record data. In this paper, we proposed an automatic sleep stages classification system by analyzing rat's EEG signal. The rat's EEG signal is
doi:10.1016/j.eswa.2011.02.076
fatcat:7kztuoucuffjtcb4lptnpyxmu4