Extraction of ocular artifacts from EEG using
Independent Component Analysis

Ricardo Nuno Vigário
Laboratory of Computer and Information Science,
Helsinki University of Technology, FIN-02150 Espoo, Finland

Abstract:

Eye activity is one of the main sources of artifacts in EEG and MEG recordings. Here I present a new approach to the correction of these disturbances, using the statistical technique of independent component analysis. This technique separates components by the kurtosis of their amplitude distribution over time, this way distinguishing between strictly periodical signals, regularly occurring signals, and irregularly occurring signals. The latter category is usually formed by artifacts. Through this approach, it is possible to isolate ``pure'' eye activity in the EEG recordings (including EOG channels), and so reduce the amount of brain activity that is subtracted from the measurements, when extracting from them portions of the EOG signals.

Keywords: EEG; EOG; Ocular artifact correction; Independent Component Analysis (ICA); Blind source separation (BSS)

Includes:  

• Introduction
• Independent Component Analysis
  • The model
  • The algorithm
• Simulated data
• Experimental data
• Results
• Discussion
• Acknowledgment
• References
• List of Figures
• About this document ...