Online removal of muscle artifact from electroencephalogram signals based on canonical correlation analysis

Clinical EEG and Neuroscience

Volumn 41, Issue 1, 2010, Pages 53-59

  Gao, Junfeng ^a   Zheng, Chongxun ^a   Wang, Pei ^a  

^a XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

Canonical correlation analysis; Electroencephalography; Electromyography; Independent component analysis

Indexed keywords

ADOLESCENT; ADULT; ARTICLE; ARTIFACT REDUCTION; CHILD; CORRELATION ANALYSIS; ELECTROENCEPHALOGRAM; ELECTROMYOGRAM; ELECTROOCULOGRAM; FEMALE; HUMAN; HUMAN EXPERIMENT; INDEPENDENT COMPONENT ANALYSIS; MALE; NORMAL HUMAN; ONLINE ANALYSIS; PRIORITY JOURNAL; SCHOOL CHILD; SIMULATION; TASK PERFORMANCE;

EID: 77749243297     PISSN: 15500594     EISSN: None     Source Type: Journal    
DOI: 10.1177/155005941004100111     Document Type: Article

References (23)

1. Gratton G, Coles MG, Donchin E. A new method for off-line removal of oucular artifact. Electroencephalogr Clin Neurophysiol 1983; 55: 486-484.
2. Comon P. Independent component analysis, a new concept? Signal Process 1994; 36: 287-314.
3. Jung T-P, Makeig S, Humphries C, Lee T-W, McKeown MJ, Iragui V, Sejnowski TJ. Removing electroencephalographic artifacts by blind source separation. Psychophysiology 2000; 37: 163-178.
4. Lee T-W. Independent Component Analysis. Theory and Applications. Hingham, MA: Kluwer Academic; 1998.
5. Hyvärinen A, Oja E. Independent component analysis: algorithms and applications. Neural Networks 2000; 13:411-430.
6. Vigario R, Särelä J, Jousmäki V, Hämäläinen M, Oja E. Independent component approach to the analysis of EEG and MEG recordings.IEEE Trans Biomed Eng 2000; 47: 589-593.
7. Ille N, Berg P, Scherg M. Artifact correction on the ongoing EEG using spatial filters based on artifact and brain signal topographies. J Clin Neurophysiol 2002; 19: 113-124.
8. Urrestarazu E, Iriarte J, Alegre M, Valencia M, Viteri C, Artieda J. Independent component analysis removing artifacts in ictal recordings. Epilepsia 2004; 45: 1071-1078.
9. Nam H, Yim TG, Han SK Oh JB, Lee SK. Independent component analysis of ictal EEG in medial temporal lobe epilepsy. Epilepsia 2002; 43: 160-164.
10. Iriarte J, Urrestarazu E, Valencia M. Independent component analysis as a tool to eliminate artifacts in EEG: a quantitative study. J Clin Neurophysiol 2003; 20: 249-257.
11. Halder S, Bensch M, Mellinger J, Bogdan M, Kubler A, Birbaumer N, Rosenstiel W. Online artifact removal for brain-computer interfaces using support VectorMachines and blind source separation. Comp Intell Neurosci 2007: 1155-1165.
12. Makeig S, Bell AJ, Jung T-P, Sejnowski TJ. Independent Component Analysis of Electroencephalgraphic Data. Advance in Neural Information Processing Systems 8. Cambridge MA: MIT Press; 1996: 145-151.
13. Delorme A, Sejnowski TJ, Makeig S. Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis. NeuroImage 2007; 34: 1443-1449.
14. Hotelling H. Relations between two sets of variates: Biometrika. New York: Columbia UniversityPress; 1936; 28: 321-377.
15. Friman O, Borga M, Lundberg P, Knutsson H. Exploratory fMRI analysis by autocorrelation maximization. NeuroImage 2002; 16: 454-464.
16. Borga M. Canonical Correlation a tutorial. January 12, 2001. (http://people.imt.liu.se/~magnus/cca/).
17. Clercq WD, Vergult A, Vanrumste B, Huffel SV, Kokarakis M, Hees JV, et al. Canonical correlation analysis applied to remove muscle artifacts from the electroencephalogram. IEEE Trans Biomed Eng 2006; 2583-2587.
18. Vergult A, Clercq WD, Palmini A, Vanrumste B. Improving the interpretation of ictal scalp EEG: BSS-CCA algorithm for muscle artifact removal. Epilepsia 2007; 48: 950-958.
19. Fatourechi M, Bashashati A, Ward RK, Birch GE. EMG and EOG artifacts in brain computer interface system: a survey. Clin Neurophysiology 2007; 118: 480-494.
20. Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Meth 2004; 134: 9-21.
21. Amari S, Cichocki A, Yang HH. A new learning algorithm for blind signal separation. In: Touretzky D, Mozer M, Hasselmo M, (eds). Advances in Neural Information Processing Systems 8. Cambridge MA: MIT Press; 1996: 757-763.
22. Bell AJ, Sejnowski TJ. An information-maximization approach to blind separation and blind deconvolution. Neural Comput 1995; 7: 1129-1159.
23. Lee T-W, Bell AJ, Sejnowski TJ. A Unifying information-theoretic framework for independent component analysis. Comput Math Applic 2000; 39: 1-21.