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Towards BCI-Based Interfaces for Augmented Reality: Feasibility, Design and Evaluation.

, , , , , , , , and . IEEE Trans. Vis. Comput. Graph., 26 (3): 1608-1621 (2020)

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2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets., , , , , , , , , and 11 other author(s). NeurIPS (Competition and Demos), volume 176 of Proceedings of Machine Learning Research, page 205-219. PMLR, (2021)A physical learning companion for Mental-Imagery BCI User Training., , , , , and . Int. J. Hum. Comput. Stud., (2020)Towards BCI-Based Interfaces for Augmented Reality: Feasibility, Design and Evaluation., , , , , , , , and . IEEE Trans. Vis. Comput. Graph., 26 (3): 1608-1621 (2020)"Do You Feel in Control?": Towards Novel Approaches to Characterise, Manipulate and Measure the Sense of Agency in Virtual Environments., , , and . IEEE Trans. Vis. Comput. Graph., 24 (4): 1486-1495 (2018)Towards improved BCI based on human learning principles., and . BCI, page 1-4. IEEE, (2015)Peanut: Personalised Emotional Agent for Neurotechnology User-Training., , , , , and . GBCIC, Verlag der Technischen Universitaet Graz, (2017)Are users' traits informative enough to predict/explain their mental-imagery based BCI performances?, , and . GBCIC, Verlag der Technischen Universitaet Graz, (2019)Detecting System Errors in Virtual Reality Using EEG Through Error-Related Potentials., , , , , , , , and . VR, page 653-661. IEEE, (2020)2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets., , , , , , , , , and 11 other author(s). CoRR, (2022)Assessing The Relevance Of Neurophysiological Patterns To Predict Motor Imagery-based BCI Users' Performance., , , and . SMC, page 2490-2495. IEEE, (2020)