Rethinking BCI Paradigm and Machine Learning Algorithm as a Symbiosis: Zero Calibration, Guaranteed Convergence and High Decoding Performance
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Klaus-Robert Müller | Michael Tangermann | David Hübner | Pieter-Jan Kindermans | Thibault Verhoeven | K. Müller | Pieter-Jan Kindermans | D. Hübner | M. Tangermann | T. Verhoeven
[1] Yijun Wang,et al. Visual and Auditory Brain–Computer Interfaces , 2014, IEEE Transactions on Biomedical Engineering.
[2] Benjamin Schrauwen,et al. A Bayesian Model for Exploiting Application Constraints to Enable Unsupervised Training of a P300-based BCI , 2012, PloS one.
[3] Stefan Haufe,et al. Optimizing event-related potential based brain-computer interfaces: a systematic evaluation of dynamic stopping methods. , 2013, Journal of neural engineering.
[4] Klaus-Robert Müller,et al. Subject-independent mental state classification in single trials , 2009, Neural Networks.
[5] Klaus-Robert Müller,et al. Learning from label proportions in brain-computer interfaces: Online unsupervised learning with guarantees , 2017, PloS one.
[6] Rajesh P. N. Rao,et al. Towards adaptive classification for BCI , 2006, Journal of neural engineering.
[7] Zafer Aydin,et al. A signal processing application in genomic research: protein secondary structure prediction , 2006 .
[8] B. Blankertz,et al. A New Auditory Multi-Class Brain-Computer Interface Paradigm: Spatial Hearing as an Informative Cue , 2010, PloS one.
[9] Michael Tangermann,et al. Mixing two Unsupervised estimators for Event-Related potential decoding: an Online Evaluation , 2017, GBCIC.
[10] Klaus-Robert Müller,et al. Towards Zero Training for Brain-Computer Interfacing , 2008, PloS one.
[11] Klaus-Robert Müller,et al. Learning From More Than One Data Source: Data Fusion Techniques for Sensorimotor Rhythm-Based Brain–Computer Interfaces , 2015, Proceedings of the IEEE.
[12] Michael Tangermann,et al. Listen, You are Writing! Speeding up Online Spelling with a Dynamic Auditory BCI , 2011, Front. Neurosci..
[13] S. Luck. An Introduction to the Event-Related Potential Technique , 2005 .
[14] T Verhoeven,et al. Towards a symbiotic brain–computer interface: exploring the application–decoder interaction , 2015, Journal of neural engineering.
[15] A. Kübler,et al. Flashing characters with famous faces improves ERP-based brain–computer interface performance , 2011, Journal of neural engineering.
[16] Roderick Murray-Smith,et al. Optimized stimulation events for a visual ERP BCI , 2011 .
[17] Motoaki Kawanabe,et al. Toward Unsupervised Adaptation of LDA for Brain–Computer Interfaces , 2011, IEEE Transactions on Biomedical Engineering.
[18] E. Donchin,et al. Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. , 1988, Electroencephalography and clinical neurophysiology.
[19] Klaus-Robert Müller,et al. True Zero-Training Brain-Computer Interfacing – An Online Study , 2014, PloS one.
[20] Klaus-Robert Müller,et al. Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller , 2014, Journal of neural engineering.
[21] Bernhard Schölkopf,et al. Transfer Learning in Brain-Computer Interfaces , 2015, IEEE Computational Intelligence Magazine.
[22] M Congedo,et al. A review of classification algorithms for EEG-based brain–computer interfaces , 2007, Journal of neural engineering.
[23] Tao Liu,et al. N200-speller using motion-onset visual response , 2009, Clinical Neurophysiology.
[24] Michael Tangermann,et al. Improving Learning from Label proportions by Reducing the Feature Dimensionality , 2017, GBCIC.
[25] Alexander J. Smola,et al. Estimating labels from label proportions , 2008, ICML '08.
[26] Ricardo Chavarriaga,et al. To Err Is Human: Learning from Error Potentials in Brain-Computer Interfaces , 2007 .
[27] C. Neuper,et al. Combining Brain–Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges , 2010, Front. Neurosci..
[28] Tzyy-Ping Jung,et al. High-speed spelling with a noninvasive brain–computer interface , 2015, Proceedings of the National Academy of Sciences.
[29] Klaus Gramann,et al. Neuroadaptive technology enables implicit cursor control based on medial prefrontal cortex activity , 2016, Proceedings of the National Academy of Sciences.
[30] T Verhoeven,et al. Improving zero-training brain-computer interfaces by mixing model estimators , 2017, Journal of neural engineering.
[31] Fabien Lotte,et al. Towards improved BCI based on human learning principles , 2015, The 3rd International Winter Conference on Brain-Computer Interface.
[32] G. Pfurtscheller,et al. Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.
[33] N. Birbaumer,et al. Brain-computer communication: self-regulation of slow cortical potentials for verbal communication. , 2001, Archives of physical medicine and rehabilitation.
[34] Jaime Gómez Gil,et al. Brain Computer Interfaces, a Review , 2012, Sensors.
[35] Klaus-Robert Müller,et al. Toward noninvasive brain-computer interfaces , 2006, IEEE Signal Process. Mag..
[36] Ricardo Chavarriaga,et al. Teaching brain-machine interfaces as an alternative paradigm to neuroprosthetics control , 2015, Scientific Reports.
[37] Yijun Wang,et al. A high-speed BCI based on code modulation VEP , 2011, Journal of neural engineering.
[38] Klaus-Robert Müller,et al. Classifying Single Trial EEG: Towards Brain Computer Interfacing , 2001, NIPS.
[39] Gert Pfurtscheller,et al. Motor imagery and direct brain-computer communication , 2001, Proc. IEEE.
[40] Benjamin Blankertz,et al. Data driven neuroergonomic optimization of BCI stimuli , 2011 .
[41] Stefan Haufe,et al. Single-trial analysis and classification of ERP components — A tutorial , 2011, NeuroImage.
[42] K.-R. Muller,et al. Optimizing Spatial filters for Robust EEG Single-Trial Analysis , 2008, IEEE Signal Processing Magazine.
[43] J. Wolpaw,et al. A novel P300-based brain–computer interface stimulus presentation paradigm: Moving beyond rows and columns , 2010, Clinical Neurophysiology.
[44] Klaus-Robert Müller,et al. Machine learning for real-time single-trial EEG-analysis: From brain–computer interfacing to mental state monitoring , 2008, Journal of Neuroscience Methods.