Conference Proceeding

Real-Time Ocular Artifacts Suppression from EEG Signals Using an Unsupervised Adaptive Blind Source Separation

Dept. of Biomed. Eng., Iran Univ. of Sci. & Technol., Tehran
Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 10/2006; DOI:10.1109/IEMBS.2006.259611 pp.5269 - 5272 In proceeding of: Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Source: IEEE Xplore

ABSTRACT Independent component analysis (ICA) has been shown to be a powerful tool for artifactual suppression from electroencephalogram (EEG) recordings. However, the real-time application of this method for artifact rejection has not been considered so far. This article presents a method based on an unsupervised, self-normalizing, adaptive learning algorithm for on-line blind source separation. Simulation results are provided to show the validity and effectiveness of the technique with different distributions. The results from real-data demonstrate that the proposed scheme removes perfectly eye blink and eye movement artifacts from the EEG signals and is suitable for use during on-line EEG monitoring such as EEG-based brain computer interface

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Keywords

adaptive
 
different distributions
 
EEG-based brain computer interface
 
electroencephalogram
 
eye movement artifacts
 
Independent component analysis
 
on-line blind source separation
 
on-line EEG monitoring
 
powerful tool
 
proposed scheme
 
real-data
 
real-time application
 
Simulation results
 

F. Shayegh