title: Classification of awake, REM, and NREM from EEG via singular spectrum analysis.
abstract: In this study, a single-channel electroencephalography (EEG) analysis method has been proposed for automated 3-state-sleep classification to discriminate Awake, NREM (non-rapid eye movement) and REM (rapid eye movement). For this purpose, singular spectrum analysis (SSA) is applied to automatically extract four brain rhythms: delta, theta, alpha, and beta. These subbands are then used to generate the appropriate features for sleep classification using a multi class support vector machine (M-SVM). The proposed method provided 0.79 agreement between the manual and automatic scores.
authors.forename: Sara Mahvash
authors.initials: SM
authors.lastname: Mohammadi
authors.forename: Shirin
authors.initials: S
authors.lastname: Enshaeifar
authors.forename: Mohammad
authors.initials: M
authors.lastname: Ghavami
authors.forename: Saeid
authors.initials: S
authors.lastname: Sanei
mesh_terms: D001921:Brain / Q000502:physiology; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D012815:Signal Processing, Computer-Assisted; D012890:Sleep / Q000502:physiology*; D012895:Sleep, REM / Q000502:physiology; D060388:Support Vector Machine; D014851:Wakefulness / Q000502:physiology*