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The aim of this work is to propose an automatic sleep stage classification technique of electroencephalogram's signals (EEG) using Hilbert-Huang transform. EEG signals are analyzed with the Hilbert-Huang transform, instantaneous frequency with the physical meaning is obtained; The energy-frequency distribution of EEG was used as features parameters for each sleep stage; Ultimately using nearest neighbor...
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