Titlebook: Brain-Computer Interface Research; A State-of-the-Art S Christoph Guger,Theresa Vaughan,Brendan Allison Book 2014 The Author(s) 2014 2013 B

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Macht und Demokratie in der CDUeen achieved using electrodes embedded on a customized earpiece as typically used in hearing aids (Ear-EEG). We illustrate the potential of Ear-EEG as an enabling technology for a number of uses beyond traditional BCI, which are currently limited by the inconvenience of standard EEG recording method

STELL

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Ausgew?hlte Schriften von Claus Offeinimizing the invasiveness of the electrode implantation is critical. In this study, we advanced our recently proposed ‘N200 speller’ BCI paradigm that utilizes the attentional modulation of visual motion response. Non-invasive functional magnetic resonance imaging (fMRI) was employed to localize th

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Two Logics of Collective Action (1980)m. Six and ten head position setups are used to evoke combined somatosensory and auditory (via bone-conduction effect) brain responses, in order to define a multimodal tactile and bone-conduction-auditory brain computer interface (tbcaBCI) suitable for ALS-TLS patients with bad vision and suffering

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2191-8112 how these reflect general trends in BCI development. Each project summary includes an introduction, description of methods, results, and also includes newer work completed after the project was entered for the 978-3-319-09978-1978-3-319-09979-8Series ISSN 2191-8112 Series E-ISSN 2191-8120

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An Accurate, Versatile, and Robust Brain Switch for Neurorehabilitation,er output. Stefan et al. (Brain J Neurol 123(pt 3):572–584, .) were the first to investigate this concept non-invasively in humans, and it has now become accepted that it closely matches what occurs during motor learning. With this knowledge, we developed a BCI system where the user’s movement inten

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Passive Brain-Computer Interfaces for Robot-Assisted Rehabilitation,omic nervous system responses and that adaptive estimation methods can further improve accuracy. However, the number of electrode sites needs to be reduced and issues such as motion artefacts must be resolved before passive brain-computer interfaces can be used in motor rehabilitation.

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A Concurrent Brain-Machine Interface for Enhanced Sequential Motor Function,ion encoded either only currently held or only newly added target information regardless of the exact sequence. Capitalizing on this stable representation, we developed a BMI that concurrently decodes a full motor sequence in advance of movement and can then accurately execute it as desired.