02112nas a2200289   4500008004100000022001400041245004800055210004100103260001200144300001200156490000800168520133600176653002201512653002901534653000801563653002001571653001501591653002401606100001901630700001901649700001601668700002301684700002601707700002101733700002001754856004801774       2008                        eng d  a0165-027000aAn auditory brain-computer interface (BCI).0 aauditory braincomputer interface BCI  c01/2008  a43–500 v1673 aBrain-computer interfaces (BCIs) translate brain activity into signals controlling external devices. BCIs based on visual stimuli can maintain communication in severely paralyzed patients, but only if intact vision is available. Debilitating neurological disorders however, may lead to loss of intact vision. The current study explores the feasibility of an auditory BCI. Sixteen healthy volunteers participated in three training sessions consisting of 30 2-3 min runs in which they learned to increase or decrease the amplitude of sensorimotor rhythms (SMR) of the EEG. Half of the participants were presented with visual and half with auditory feedback. Mood and motivation were assessed prior to each session. Although BCI performance in the visual feedback group was superior to the auditory feedback group there was no difference in performance at the end of the third session. Participants in the auditory feedback group learned slower, but four out of eight reached an accuracy of over 70% correct in the last session comparable to the visual feedback group. Decreasing performance of some participants in the visual feedback group is related to mood and motivation. We conclude that with sufficient training time an auditory BCI may be as efficient as a visual BCI. Mood and motivation play a role in learning to use a BCI.10aauditory feedback10abrain-computer interface10aEEG10alocked-in state10amotivation10asensorimotor rhythm1 aNijboer, Femke1 aFurdea, Adrian1 aGunst, Ingo1 aMellinger, Jürgen1 aMcFarland, Dennis, J.1 aBirbaumer, Niels1 aKübler, Andrea  uhttp://www.ncbi.nlm.nih.gov/pubmed/1739979703358nas a2200397   4500008004100000020001800041245009600059210006900155260015500224520204800379653003002427653000802457653001502465653003002480653002302510653002902533653003102562100002002593700001502613700001502628700001302643700001902656700001902675700001402694700001302708700002502721700002302746700001402769700002402783700001502807700002102822700001802843700001802861700002102879856006002900       2007                        eng d  a978026225604900aBrain Computer Interfaces for Communication in Paralysis: a Clinical-Experimental Approach.0 aBrain Computer Interfaces for Communication in Paralysis a Clini  bVirtual Library of Psychology at Saarland University and State Library, GERMANY, PsyDok [http://psydok.sulb.uni-saarland.de/phpoai/oai2.php] (Germany)3 a<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 “Thought-Translation Device (TTD)” 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' 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, µ-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 µ-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>10abrain-computer interfaces10aEEG10aexperiment10aMedical sciences Medicine10aparalyzed patients10aslow cortical potentials10aThought-Translation Device1 aHinterberger, T1 aNijboer, F1 aKübler, A1 aMatuz, T1 aFurdea, Adrian1 aMochty, Ursula1 aJordan, M1 aLal, T N1 aHill, Jeremy, Jeremy1 aMellinger, Jürgen1 aBensch, M1 aTangermann, Michael1 aWidmann, G1 aElger, Christian1 aRosenstiel, W1 aSchölkopf, B1 aBirbaumer, Niels  uhttp://psydok.sulb.uni-saarland.de/volltexte/2008/2154/02685nas a2200433   4500008004100000022001400041245011000055210006900165260001200234300001600246490000700262520140200269653003101671653000801702653001601710653002901726653000801755653000801763653002801771653003601799653001401835653000901849653001901858653003201877653002901909100002401938700002601962700001901988700002402007700001902031700002102050700002002071700002002091700002402111700002402135700002302159700002102182856004802203       2004                        eng d  a0018-929400aThe BCI Competition 2003: progress and perspectives in detection and discrimination of EEG single trials.0 aBCI Competition 2003 progress and perspectives in detection and   c06/2004  a1044–10510 v513 aInterest in developing a new method of man-to-machine communication–a brain-computer interface (BCI)–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.10aaugmentative communication10aBCI10abeta-rhythm10abrain-computer interface10aEEG10aERP10aimagined hand movements10alateralized readiness potential10amu-rhythm10aP30010aRehabilitation10asingle-trial classification10aslow cortical potentials1 aBlankertz, Benjamin1 aMüller, Klaus-Robert1 aCurio, Gabriel1 aVaughan, Theresa, M1 aSchalk, Gerwin1 aWolpaw, Jonathan1 aSchlögl, Alois1 aNeuper, Christa1 aPfurtscheller, Gert1 aHinterberger, Thilo1 aSchröder, Michael1 aBirbaumer, Niels  uhttp://www.ncbi.nlm.nih.gov/pubmed/15188876