Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms

✍ Scribed by Dornhege, G.; Blankertz, B.; Curio, G.; Muller, K.-R.

• Book ID: 114602721
• Publisher: IEEE
• Year: 2004
• Tongue: English
• Weight: 400 KB
• Volume: 51
• Category: Article
• ISSN: 0018-9294
• DOI: 10.1109/tbme.2004.827088

✦ Synopsis

Noninvasive electroencephalogram (EEG) recordings provide for easy and safe access to human neocortical processes which can be exploited for a brain-computer interface (BCI). At present, however, the use of BCIs is severely limited by low bit-transfer rates. We systematically analyze and develop two recent concepts, both capable of enhancing the information gain from multichannel scalp EEG recordings: 1) the combination of classifiers, each specifically tailored for different physiological phenomena, e.g., slow cortical potential shifts, such as the premovement Bereitschaftspotential or differences in spatio-spectral distributions of brain activity (i.e., focal event-related desynchronizations) and 2) behavioral paradigms inducing the subjects to generate one out of several brain states (multiclass approach) which all bare a distinctive spatio-temporal signature well discriminable in the standard scalp EEG. We derive information-theoretic predictions and demonstrate their relevance in experimental data. We will show that a suitably arranged interaction between these concepts can significantly boost BCI performances.