The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms
Open accessAbstract
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 pre-movement 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.
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Metadata
- Authors
- Dornhege, G., Blankertz, B., Curio, G., & Muller, K.-R.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2004-06
- Volume
- 51
- Issue
- 6
- Pages
- 993-1002
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2163756472
- Cited by
- 631
- References
- 38
- FWCI
- 12.32
- Type
- journal article
- Language
- en
- Open access
- green
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