Identification and Classification of Electroencephalogram Signals Based on Independent Component Analysis

被引：2
|
作者：
Zhang, Chao [1 ]
Xu, Jing [1 ]
Pan, Su [2 ,3 ]
Yang, Yudan
机构：
[1] Changchun Univ, Changchun 130022, Jilin, Peoples R China
[2] Jilin Univ, Hosp 2, Dept Orthoped, Changchun 130041, Jilin, Peoples R China
[3] Jilin Univ, China Japan Union Hosp, Sci Res Ctr, Changchun 130033, Jilin, Peoples R China
来源：
NEUROQUANTOLOGY | 2018年 / 16卷 / 05期
关键词：
Electroencephalogram (EEG); Brain Computer Interface (BCI); Independent Component Analysis (ICA); Support Vector Machine (SVM);
D O I：
10.14704/nq.2018.16.5.1392
中图分类号：
Q189 [神经科学];
学科分类号：
071006 ;
摘要：
This paper aims to develop a desirable EEG-based classification algorithm. For this purpose, the discrete wavelet transform was applied to denoise the EEG signals. Then, the brain's left and right hand movement features were extracted from the denoised signals by the independent component analysis (ICA). Finally, the support vector machine (SVM) classifier was adopted to recognize and classify the movement of the left and right hand actions. The experimental results show that our method achieves the recognition accuracy of 89.5% and 90.6% respectively. The research findings provide a valuable reference for the future research into the BCI system.
引用
收藏
页码：832 / 838
页数：7
相关论文
共 50 条
  • [1] Modulation Classification of Mixed Signals using Independent Component Analysis
    Gao, Qian
    Huang, Sai
    Wang, Lu
    Wang, Kun
    Zhang, Yifan
    Feng, Zhiyong
    2015 IEEE/CIC INTERNATIONAL CONFERENCE ON COMMUNICATIONS IN CHINA (ICCC), 2015,
  • [2] A Novel Method Based on Combination of Independent Component Analysis and Ensemble Empirical Mode Decomposition for Removing Electrooculogram Artifacts From Multichannel Electroencephalogram Signals
    Teng, Chao-Lin
    Zhang, Yi-Yang
    Wang, Wei
    Luo, Yuan-Yuan
    Wang, Gang
    Xu, Jin
    FRONTIERS IN NEUROSCIENCE, 2021, 15
  • [3] Detection of electroencephalogram rhythms in schizophrenia by independent component analysis and wavelet transformation
    Wang, Y
    Lee, YJ
    Zhu, YS
    Wang, Z
    IEEE-EMBS ASIA PACIFIC CONFERENCE ON BIOMEDICAL ENGINEERING - PROCEEDINGS, PTS 1 & 2, 2000, : 183 - 184
  • [4] Independent component analysis of electroencephalographic signals
    Shen, MF
    Zhang, XJ
    Li, XH
    2002 6TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, VOLS I AND II, 2002, : 1548 - 1551
  • [5] Extraction and Classification of Electroencephalogram signals
    Upadhyay, R.
    Kankar, P. K.
    Padhy, P. K.
    Gupta, V. K.
    2012 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (ICCIC), 2012, : 135 - 138
  • [6] Fast removal of ocular artifacts from electroencephalogram signals using spatial constraint independent component analysis based recursive least squares in brain-computer interface
    Bang-hua Yang
    Liang-fei He
    Lin Lin
    Qian Wang
    Frontiers of Information Technology & Electronic Engineering, 2015, 16 : 486 - 496
  • [7] Fast removal of ocular artifacts from electroencephalogram signals using spatial constraint independent component analysis based recursive least squares in brain-computer interface
    Yang, Bang-hua
    He, Liang-fei
    Lin, Lin
    Wang, Qian
    FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING, 2015, 16 (06) : 486 - 496
  • [8] Independent Component Analysis of Sparse-transformed EEG Signals for ADHD/Normal Adults' Classification
    Taymourtash, Athena
    Ghassemi, Farnaz
    2015 23RD IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE), 2015, : 151 - 155
  • [9] A switchable scheme for ECG beat classification based on independent component analysis
    Yu, Sung-Nien
    Chou, Kuan-To
    EXPERT SYSTEMS WITH APPLICATIONS, 2007, 33 (04) : 824 - 829
  • [10] Denoising Satellite Gravity Signals by Independent Component Analysis
    Frappart, F.
    Ramillien, G.
    Maisongrande, P.
    Bonnet, M. -P.
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2010, 7 (03) : 421 - 425
12345