Classification of awake, REM, and NREM from EEG via singular spectrum analysis
Conference item
Mohammadi, SM, Enshaeifar, S, Ghavami, M and Sanei, S (2015). Classification of awake, REM, and NREM from EEG via singular spectrum analysis. International Conference of the IEEE Engineering in Medicine and Biology Society. Milan, Italy 25 - 29 Aug 2015 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/EMBC.2015.7319460
Authors | Mohammadi, SM, Enshaeifar, S, Ghavami, M and Sanei, S |
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Abstract | © 2015 IEEE. 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. |
Keywords | Brain; Humans; Electroencephalography; Wakefulness; Sleep; Sleep, REM; Signal Processing, Computer-Assisted; Support Vector Machine; Brain; Electroencephalography; Humans; Signal Processing, Computer-Assisted; Sleep; Sleep, REM; Support Vector Machine; Wakefulness |
Year | 2015 |
Journal | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Journal citation | 2015-N, pp. 4769-4772 |
ISSN | 1557-170X |
Digital Object Identifier (DOI) | https://doi.org/10.1109/EMBC.2015.7319460 |
Accepted author manuscript | License |
Publication dates | |
04 Nov 2015 | |
Publication process dates | |
Deposited | 27 Jun 2018 |
Accepted | 04 Nov 2015 |
ISBN | 9781424492718 |
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