Combining detrended cross-correlation analysis with Riemannian geometry-based classification for improved brain-computer interface performance
Frigyes Samuel Racz,
Satyam Kumar,
Zalan Kaposzta
et al.
Abstract:Riemannian geometry-based classification (RGBC) gained popularity in the field of brain-computer interfaces (BCIs) lately, due to its ability to deal with non-stationarities arising in electroencephalography (EEG) data. Domain adaptation, however, is most often performed on sample covariance matrices (SCMs) obtained from EEG data, and thus might not fully account for components affecting covariance estimation itself, such as regional trends. Detrended cross-correlation analysis (DCCA) can be utilized to estima… Show more
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