Literature DB >> 26737360

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

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.

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Year:  2015        PMID: 26737360     DOI: 10.1109/EMBC.2015.7319460

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  5 in total

1.  Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal.

Authors:  Shanzhi Xu; Hai Hu; Linhong Ji; Peng Wang
Journal:  Sensors (Basel)       Date:  2018-02-26       Impact factor: 3.576

2.  A flexible and accurate method for electroencephalography rhythms extraction based on circulant singular spectrum analysis.

Authors:  Hai Hu; Zihang Pu; Peng Wang
Journal:  PeerJ       Date:  2022-03-23       Impact factor: 2.984

3.  An adaptive singular spectrum analysis method for extracting brain rhythms of electroencephalography.

Authors:  Hai Hu; Shengxin Guo; Ran Liu; Peng Wang
Journal:  PeerJ       Date:  2017-06-28       Impact factor: 2.984

4.  Removal of EMG Artifacts from Multichannel EEG Signals Using Combined Singular Spectrum Analysis and Canonical Correlation Analysis.

Authors:  Qingze Liu; Aiping Liu; Xu Zhang; Xiang Chen; Ruobing Qian; Xun Chen
Journal:  J Healthc Eng       Date:  2019-12-30       Impact factor: 2.682

5.  A study on EEG feature extraction and classification in autistic children based on singular spectrum analysis method.

Authors:  Jie Zhao; Jiajia Song; Xiaoli Li; Jiannan Kang
Journal:  Brain Behav       Date:  2020-10-30       Impact factor: 2.708

  5 in total

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