By Christoph Guger, Brendan Allison, Junichi Ushiba
This publication stories at the most recent examine and advancements within the box of brain-computer interfaces (BCIs). It introduces ten amazing and cutting edge BCI initiatives, nominated as finalists for the BCI award 2012 by means of a jury of confirmed researchers and discusses how all of the nominated initiatives displays normal around the globe traits in BCI improvement. on the middle of the e-book, 9 of those ten tasks are defined in unique person chapters. those contain a concentrated creation to every venture, a simple to understand description of the tools and a well timed document at the most modern advancements completed because the submission to the award. therefore, this booklet offers a state of the art evaluation of the latest BCI learn tendencies, from best specialists, in a simple to learn structure supported through explanatory photographs, graphs and figures.
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As the authors noted, the work could also benefit other users by sensing heart rate variability or other physiological signals, thus providing continuous brain monitoring for many different applications. References 1. : The Berlin brain-computer interface: Nonmedical uses of BCI technology. Front. Neuroscience 4(198) (2010) 2. : New horizons in ambulatory electroencephalography. IEEE Eng. Med. Biol. Mag. 22(3), 74–80 (2003) 3. : Wearable electroencephalography. IEEE Eng. Med. Biol. Mag. 29(3), 44–56 (2010) 4.
A future system could also use other kinds of haptic assistance. Indeed, adapting the damping level proportionally to the user’s mental workload or toggling inverted damping  only if the user presents a high mental workload are options that should be studied. Concerning the measurements of the mental workload, a combination of EEG with other modalities such as Galvanic Skin Response in a multi-modal measurement system could increase the reliability of the mental workload index. Finally, it would also be interesting to evaluate the role of BCI-based adaptation in real applications such as medical training systems notably in terms of learning performance.
Overall, the jury felt that this work could make a major contribution to helping persons with visual deficits. After the BCI Award, the group published work that further described and extended their Argus II system and yielded 89% accuracy when detecting single letters . Z. Lauritzen et al. which could facilitate future applied research as well as fundamental issues in retinal function and vision [17, 18]. Therefore, this group’s ongoing work could lead to both direct and indirect benefits to persons with visual disabilities, and improve our understanding of the visual system and how it differs in persons who have trouble seeing.