The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Machine learning for real-time single-trial EEG-analysis: From brain–computer interfacing to mental state monitoring
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Nature of Statistical Learning Theory
Vapnik, V. N. (1995) · doi:10.1007/978-1-4757-2440-0 · Cited by 39,138
Brain–computer interfaces for communication and control
Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., & Vaughan, T. M. (2002) · Clinical Neurophysiology · doi:10.1016/s1388-2457(02)00057-3 · Cited by 7,927
Learning to control a brain–machine interface for reaching and grasping by primates
Carmena, J. M., Lebedev, M. A., Crist, R. E., O'Doherty, J. E., Santucci, D. M., Dimitrov, D. F., Patil, P. G., Henriquez, C. S., & Nicolelis, M. A. L. (2003) · PLoS Biology · doi:10.1371/journal.pbio.0000042 · Cited by 1,761 · cited 1×
“…communication that is solely based on brain signals, independent from muscles or peripheral nerves (see Wolpaw et al. (2002); Kübler et al. (2001); Curran and Stokes (2003); Kübler and Müller (2007); Dornhege et al. (2007a); Carmena et al. (2003) for a broader overview and background information).”
The thought translation device (TTD) for completely paralyzed patients
Birbaumer, N., Kubler, A., Ghanayim, N., Hinterberger, T., Perelmouter, J., Kaiser, J., Iversen, I., Kotchoubey, B., Neumann, N., & Flor, H. (2000) · IEEE Transactions on Rehabilitation Engineering · doi:10.1109/86.847812 · Cited by 493
Curran, E. (2003) · Brain and Cognition · doi:10.1016/s0278-2626(03)00036-8 · Cited by 417
A Note on Brain Actuated Spelling with the Berlin Brain-Computer Interface
Blankertz, B., Krauledat, M., Dornhege, G., Williamson, J., Murray-Smith, R., & Müller, K.-R. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-73281-5_83 · Cited by 106
Self-citation
Cited by
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-citationSingle-trial analysis and classification of ERP components — A tutorial
Blankertz, B., Lemm, S., Treder, M., Haufe, S., & Müller, K.-R. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.06.048 · Cited by 1,138
Self-citationConvolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces
Cecotti, H., & Graser, A. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.125 · Cited by 778
Neurophysiological predictor of SMR-based BCI performance
Blankertz, B., Sannelli, C., Halder, S., Hammer, E. M., Kübler, A., Müller, K.-R., Curio, G., & Dickhaus, T. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.022 · Cited by 674
Self-citationIntroduction to machine learning for brain imaging
Lemm, S., Blankertz, B., Dickhaus, T., & Müller, K.-R. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.11.004 · Cited by 630
Self-citation
Metadata
- Authors
- Müller, K.-R., Tangermann, M., Dornhege, G., Krauledat, M., Curio, G., & Blankertz, B.
- Venue
- Journal of Neuroscience Methods
- Publisher
- Elsevier BV
- Published
- 2008-01
- Volume
- 167
- Issue
- 1
- Pages
- 82-90
- ISSN
- 0165-0270 (ISSN-L)
- OpenAlex
- W2121682721
- Cited by
- 474
- References
- 6
- FWCI
- 9.59
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Machine learning for real-time single-trial EEG-analysis: From brain–computer interfacing to mental state monitoring. https://app.cochat.ai/papers/10.1016/j.jneumeth.2007.09.022
- The paper
- Müller, K.-R., Tangermann, M., Dornhege, G., Krauledat, M., Curio, G., & Blankertz, B. (2008). Machine learning for real-time single-trial EEG-analysis: From brain–computer interfacing to mental state monitoring. Journal of Neuroscience Methods. https://doi.org/10.1016/j.jneumeth.2007.09.022
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.