| Literature DB >> 26737360 |
Sara Mahvash Mohammadi, Shirin Enshaeifar, Mohammad Ghavami, Saeid Sanei.
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.Entities:
Mesh:
Year: 2015 PMID: 26737360 DOI: 10.1109/EMBC.2015.7319460
Source DB: PubMed Journal: Conf Proc IEEE Eng Med Biol Soc ISSN: 1557-170X