Protocol for semi-automatic EEG preprocessing incorporating independent component analysis and principal component analysis
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1Complex Neural Signals Decoding Lab, Faculty of Education, The University of Hong Kong, Hong Kong, China.
Abstract:
Preprocessing is a critical yet challenging step in electroencephalography (EEG) research due to its significant potential impact on results. We present a protocol for semi-automatic EEG preprocessing incorporating independent component analysis (ICA) and principal component analysis (PCA) with step-by-step quality checking to ensure removal of large-amplitude artifacts. We describe steps for interpolating bad channels, removal of major artifacts by ICA and PCA correction, and exporting processed data. This protocol produced consistent results from users with a broad range of experience.

