Junbiao Liu1, 6, Duanpo Wu2, 3, Zimeng Wang2, Xinyu Jin1, *, Fang Dong4, Lurong Jiang5, Chenyi Cai6
CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.1, pp. 401-426, 2020, DOI:10.32604/cmes.2020.08731
Abstract In the field of medical informatics, sleep staging is a challenging and timeconsuming task undertaken by sleep experts. According to the new standard of the
American Academy of Sleep Medicine (AASM), the stages of sleep are divided into
wakefulness (W), rapid eye movement (REM) and non-rapid eye movement (NREM)
which includes three sleep stages (N1, N2 and N3) that describe the depth of sleep.
This study aims to establish an automatic sleep staging algorithm based on the improved
weighted random forest (WRF) and Hidden Markov Model (HMM) using only the features
extracted from double-channel EEG signals. The WRF classification model… More >
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