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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Cites
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Self-citationOptimal spatial filtering of single trial EEG during imagined hand movement
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A spelling device for the paralysed
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Cited by
A review of classification algorithms for EEG-based brain–computer interfaces: A 10 year update
Lotte, F., Bougrain, L., Cichocki, A., Clerc, M., Congedo, M., Rakotomamonjy, A., & Yger, F. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aab2f2 · Cited by 2,239
Optimizing Spatial filters for Robust EEG Single-Trial Analysis
Blankertz, B., Tomioka, R., Lemm, S., Kawanabe, M., & Muller, K.-R. (2008) · IEEE Signal Processing Magazine · doi:10.1109/msp.2008.4408441 · Cited by 2,080
Self-citationFilter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface
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Review of the BCI Competition IV
Tangermann, M., Müller, K.-R., Aertsen, A., Birbaumer, N., Braun, C., Brunner, C., Leeb, R., Mehring, C., Miller, K. J., Müller-Putz, G. R., et al. (2012) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00055 · Cited by 1,288
Self-citationFilter Bank Common Spatial Pattern Algorithm on BCI Competition IV Datasets 2a and 2b
Ang, K. K., Chin, Z. Y., Wang, C., Guan, C., & Zhang, H. (2012) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00039 · Cited by 1,264
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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