EEG Classification by ICA Source Selection of Laplacian-Filtered Data

We studied the performance of a double-spatial filtering method for classification of single-trial electroencephalography (EEG) data that couples the spherical surface Laplacian (SL) and independent component analysis (ICA). This method was evaluated in the context of a binary classification experiment with brain states driven by mental imagery of auditory and visual stimuli. A statistically significant improvement was achieved with respect to the rates provided by raw data and by data filtered by either SL or ICA.

• Type: Conference
• Year: 2009
• Where: ISBI
• Authors: Claudio Carvalhaes, Marcos Perreau Guimaraes, Logan Grosenick, Patrick Suppes
• Keywords: Double-spatial filtering Method, Independent Component Analysis, ISBI 2009, Medical Imaging, Single-trial Electroencephalography