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

By Christoph Guger, Brendan Z. Allison, Günter Edlinger

Brain-computer interfaces (BCIs) are swiftly constructing right into a mainstream, world wide study activity. With such a lot of new teams and tasks, it may be tough to spot the easiest ones. This publication summarizes ten major tasks from around the globe. approximately 60 submissions have been bought in 2011 for the hugely aggressive BCI examine Award, and a world jury chosen the pinnacle ten. This short supplies a concise yet conscientiously illustrated and entirely updated description of every of those tasks, including an creation and concluding bankruptcy by way of the editors.

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E. oxygenated hemoglobin (O2Hb) and deoxygenated hemoglobin (HHb). By measuring the attenuation of the injected light of at least two discrete wavelengths, changes in O2Hb and HHb can locally be determined. Changes in local brain activity can be inferred based on the phenomenon called neurovascular coupling (Pasley and Freeman 2008). It describes the relation between increased neuronal activity and the resulting increase in metabolic demand, which is met by a regional increase in cerebral blood flow.

In order to increase the probability that novel insights translate into actual benefits for BCI users, we consider it important to focus on variables that are likely to be actual causes, rather than mere correlates, of performance. We denote a variable as a cause of BCI performance if a) it is conceivable to construct a setup that experimentally sets the value of this variable, and b) if setting this variable to different values would result in statistically significant changes in performance. While ultimately only randomized controlled trials can establish such causal relations, the field of causal inference provides powerful tools that support the identification of causal relations from non-interventional data (cf.

It is worth mentioning a small but important difference between frontal measurements and recordings over motor regions. Often, the scalp over frontal brain areas is free of hair, unlike over motor regions. Since an efficient coupling between light sources or detectors and the scalp is of great importance, hair that obscures the optics can lead to poor signal quality (Coyle et al. 2007). Furthermore, the hair roots might absorb reflected light, further reducing the detected signal level. Not only different tasks and measurement locations have been explored, but also numerous strategies in processing the data prior to the classification.

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