Download Brain-Computer Interface Research: A State-of-the-Art by Christoph Guger, Brendan Allison, Günter Edlinger (auth.), PDF

By Christoph Guger, Brendan Allison, Günter Edlinger (auth.), Christoph Guger, Brendan Z. Allison, Günter Edlinger (eds.)

Brain-computer interfaces (BCIs) are quickly constructing right into a mainstream, world wide study undertaking. With such a lot of new teams and tasks, it may be tricky to spot the easiest ones. This booklet summarizes ten best initiatives from all over the world. approximately 60 submissions have been obtained in 2011 for the hugely aggressive BCI learn Award, and a global jury chosen the head ten. This short supplies a concise yet rigorously illustrated and completely up to date description of every of those initiatives, including an creation and concluding bankruptcy by means of the editors.

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Extra resources for Brain-Computer Interface Research: A State-of-the-Art Summary

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State of the Art in fNIRS-Based BCIs Several different tasks elicit signal patterns in the brain that can be used to control fNIRS-based BCIs. g. finger tapping or pinching) (Ward et al. 2007; Cui et al. 2010) and the kinesthetic imagery of the execution of a motor task (motor imagery, MI) (Sitaram et al. 2007; Coyle et al. 2007; Holper and Wolf 2011), signal patterns arising from more Detecting Movement Intention for Stroke Rehabilitation 27 cognitive tasks have been successfully classified. Examples for the latter include arithmetic (Naito et al.

Jun, Performance predictor using the neuro-physiological factors of an ERD-based brain computer interface. Adv. Sci. Lett. Z. Allison, C. Neuper, in Could Anyone Use a BCI? ed. by D. S. Tan, A. Nijholt. BrainComputer Interfaces, Human Computer Interaction Series (Springer, London, 2010), pp. 35–54 A. Barachant, S. Bonnet, M. Congedo, C. Jutten, Multi-class brain computer interface classification by riemannian geometry. IEEE Trans. Biomed. Eng. 59(4), 920–928 (2011) Á. Barbero, M. Grosse-Wentrup, Biased feedback in brain-computer interfaces.

Z. Allison, C. Neuper, in Could Anyone Use a BCI? ed. by D. S. Tan, A. Nijholt. BrainComputer Interfaces, Human Computer Interaction Series (Springer, London, 2010), pp. 35–54 A. Barachant, S. Bonnet, M. Congedo, C. Jutten, Multi-class brain computer interface classification by riemannian geometry. IEEE Trans. Biomed. Eng. 59(4), 920–928 (2011) Á. Barbero, M. Grosse-Wentrup, Biased feedback in brain-computer interfaces. J NeuroEng. Rehabil. 7(34), 1–4 (2010) N. Birbaumer, A. Kübler, N. Ghanayim, T.

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