@inbook {2139,
	title = {Brain Computer Interfaces for Communication in Paralysis: a Clinical-Experimental Approach.},
	year = {2007},
	publisher = {Virtual Library of Psychology at Saarland University and State Library, GERMANY, PsyDok [http://psydok.sulb.uni-saarland.de/phpoai/oai2.php] (Germany)},
	organization = {Virtual Library of Psychology at Saarland University and State Library, GERMANY, PsyDok [http://psydok.sulb.uni-saarland.de/phpoai/oai2.php] (Germany)},
	abstract = {<p><span style="color: $\#$333333; font-family: sans-serif; font-size: 15px; line-height: 24px;">An overview of different approaches to brain-computer interfaces (BCIs) developed in our laboratory is given. An important clinical application of BCIs is to enable communication or environmental control in severely paralyzed patients. The BCI {\textquotedblleft}Thought-Translation Device (TTD){\textquotedblright} allows verbal communication through the voluntary self-regulation of brain signals (e.g., slow cortical potentials (SCPs)), which is achieved by operant feedback training. Humans{\textquoteright} ability to self-regulate their SCPs is used to move a cursor toward a target that contains a selectable letter set. Two different approaches were followed to developWeb browsers that could be controlled with binary brain responses. Implementing more powerful classification methods including different signal parameters such as oscillatory features improved our BCI considerably. It was also tested on signals with implanted electrodes. Most BCIs provide the user with a visual feedback interface. Visually impaired patients require an auditory feedback mode. A procedure using auditory (sonified) feedback of multiple EEG parameters was evaluated. Properties of the auditory systems are reported and the results of two experiments with auditory feedback are presented. Clinical data of eight ALS patients demonstrated that all patients were able to acquire efficient brain control of one of the three available BCI systems (SCP, {\textmu}-rhythm, and P300), most of them used the SCP-BCI. A controlled comparison of the three systems in a group of ALS patients, however, showed that P300-BCI and the {\textmu}-BCI are faster and more easily acquired than SCP-BCI, at least in patients with some rudimentary motor control left. Six patients who started BCI training after entering the completely locked-in state did not achieve reliable communication skills with any BCI system. One completely locked-in patient was able t o communicate shortly with a ph-meter, but lost control afterward.</span></p>},
	keywords = {brain-computer interfaces, EEG, experiment, Medical sciences Medicine, paralyzed patients, slow cortical potentials, Thought-Translation Device},
	isbn = {9780262256049},
	url = {http://psydok.sulb.uni-saarland.de/volltexte/2008/2154/},
	author = {Hinterberger, T. and Nijboer, F and K{\"u}bler, A. and Matuz, T. and Adrian Furdea and Mochty, Ursula and Jordan, M. and Lal, T.N and Jeremy Jeremy Hill and Mellinger, J{\"u}rgen and Bensch, M and Tangermann, Michael and Widmann, G. and Elger, Christian and Rosenstiel, W. and Sch{\"o}lkopf, B and Niels Birbaumer}
}
@article {3222,
	title = {The BCI Competition 2003: progress and perspectives in detection and discrimination of EEG single trials.},
	journal = {IEEE transactions on bio-medical engineering},
	volume = {51},
	year = {2004},
	month = {06/2004},
	pages = {1044{\textendash}1051},
	abstract = {Interest in developing a new method of man-to-machine communication{\textendash}a brain-computer interface (BCI){\textendash}has grown steadily over the past few decades. BCIs create a new communication channel between the brain and an output device by bypassing conventional motor output pathways of nerves and muscles. These systems use signals recorded from the scalp, the surface of the cortex, or from inside the brain to enable users to control a variety of applications including simple word-processing software and orthotics. BCI technology could therefore provide a new communication and control option for individuals who cannot otherwise express their wishes to the outside world. Signal processing and classification methods are essential tools in the development of improved BCI technology. We organized the BCI Competition 2003 to evaluate the current state of the art of these tools. Four laboratories well versed in EEG-based BCI research provided six data sets in a documented format. We made these data sets (i.e., labeled training sets and unlabeled test sets) and their descriptions available on the Internet. The goal in the competition was to maximize the performance measure for the test labels. Researchers worldwide tested their algorithms and competed for the best classification results. This paper describes the six data sets and the results and function of the most successful algorithms.},
	keywords = {augmentative communication, BCI, beta-rhythm, brain-computer interface, EEG, ERP, imagined hand movements, lateralized readiness potential, mu-rhythm, P300, Rehabilitation, single-trial classification, slow cortical potentials},
	issn = {0018-9294},
	doi = {10.1109/TBME.2004.826692},
	url = {http://www.ncbi.nlm.nih.gov/pubmed/15188876},
	author = {Benjamin Blankertz and M{\"u}ller, Klaus-Robert and Curio, Gabriel and Theresa M Vaughan and Gerwin Schalk and Jonathan Wolpaw and Schl{\"o}gl, Alois and Neuper, Christa and Pfurtscheller, Gert and Hinterberger, Thilo and Schr{\"o}der, Michael and Niels Birbaumer}
}
