Classification of awake, REM, and NREM from EEG via singular spectrum analysis

Sara Mahvash Mohammadi; Shirin Enshaeifar; Mohammad Ghavami; Saeid Sanei

doi:10.1109/EMBC.2015.7319460

Classification of awake, REM, and NREM from EEG via singular spectrum analysis

Annu Int Conf IEEE Eng Med Biol Soc. 2015:2015:4769-72. doi: 10.1109/EMBC.2015.7319460.

Authors

Sara Mahvash Mohammadi, Shirin Enshaeifar, Mohammad Ghavami, Saeid Sanei

PMID: 26737360
DOI: 10.1109/EMBC.2015.7319460

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.

MeSH terms

Brain / physiology
Electroencephalography / methods*
Humans
Signal Processing, Computer-Assisted*
Sleep / physiology*
Sleep, REM / physiology
Support Vector Machine
Wakefulness / physiology*