@article {3199, title = {A P300-based brain-computer interface for people with amyotrophic lateral sclerosis.}, journal = {Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology}, volume = {119}, year = {2008}, month = {08/2008}, pages = {1909{\textendash}1916}, abstract = {OBJECTIVE: The current study evaluates the efficacy of a P300-based brain-computer interface (BCI) communication device for individuals with advanced ALS. METHODS: Participants attended to one cell of a N x N matrix while the N rows and N columns flashed randomly. Each cell of the matrix contained one character. Every flash of an attended character served as a rare event in an oddball sequence and elicited a P300 response. Classification coefficients derived using a stepwise linear discriminant function were applied to the data after each set of flashes. The character receiving the highest discriminant score was presented as feedback. RESULTS: In Phase I, six participants used a 6 x 6 matrix on 12 separate days with a mean rate of 1.2 selections/min and mean online and offline accuracies of 62\% and 82\%, respectively. In Phase II, four participants used either a 6 x 6 or a 7 x 7 matrix to produce novel and spontaneous statements with a mean online rate of 2.1 selections/min and online accuracy of 79\%. The amplitude and latency of the P300 remained stable over 40 weeks. CONCLUSIONS: Participants could communicate with the P300-based BCI and performance was stable over many months. SIGNIFICANCE: BCIs could provide an alternative communication and control technology in the daily lives of people severely disabled by ALS.}, keywords = {Amyotrophic Lateral Sclerosis, brain-computer interface, electroencephalogram, event-related potentials, P300, Rehabilitation}, issn = {1388-2457}, doi = {10.1016/j.clinph.2008.03.034}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18571984}, author = {Nijboer, F. and Sellers, E. W. and Mellinger, J. and Jordan, M. A. and Matuz, T. and Adrian Furdea and S Halder and Mochty, U. and Krusienski, D. J. and Theresa M Vaughan and Jonathan Wolpaw and Niels Birbaumer and K{\"u}bler, A.} } @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 = {

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.

}, 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 {2181, title = {An MEG-based brain-computer interface (BCI).}, journal = {Neuroimage}, volume = {36}, year = {2007}, month = {07/2007}, pages = {581-93}, abstract = {

Brain-computer interfaces (BCIs) allow for communicating intentions by mere brain activity, not involving muscles. Thus, BCIs may offer patients who have lost all voluntary muscle control the only possible way to communicate. Many recent studies have demonstrated that BCIs based on\ electroencephalography(EEG) can allow healthy and severely paralyzed individuals to communicate. While this approach is safe and inexpensive, communication is slow. Magnetoencephalography (MEG) provides signals with higher spatiotemporal resolution than\ EEG\ and could thus be used to explore whether these improved signal properties translate into increased BCI communication speed. In this study, we investigated the utility of an MEG-based BCI that uses voluntary amplitude modulation of sensorimotor mu and beta rhythms. To increase the signal-to-noise ratio, we present a simple spatial filtering method that takes the geometric properties of signal propagation in MEG into account, and we present methods that can process artifacts specifically encountered in an MEG-based BCI. Exemplarily, six participants were successfully trained to communicate binary decisions by imagery of limb movements using a feedback paradigm. Participants achieved significant mu rhythm self control within 32 min of feedback training. For a subgroup of three participants, we localized the origin of the amplitude modulated signal to the motor cortex. Our results suggest that an MEG-based BCI is feasible and efficient in terms of user training.

}, keywords = {Adult, Algorithms, Artifacts, Brain, Electroencephalography, Electromagnetic Fields, Electromyography, Feedback, Female, Foot, Hand, Head Movements, Humans, Magnetic Resonance Imaging, Magnetoencephalography, Male, Movement, Principal Component Analysis, Signal Processing, Computer-Assisted, User-Computer Interface}, issn = {1053-8119}, doi = {10.1016/j.neuroimage.2007.03.019}, url = {http://www.ncbi.nlm.nih.gov/pubmed/17475511}, author = {Mellinger, J{\"u}rgen and Gerwin Schalk and Christoph Braun and Preissl, Hubert and Rosenstiel, W. and Niels Birbaumer and K{\"u}bler, A.} } @article {2143, title = {Classifying EEG and ECoG signals without subject training for fast BCI implementation: comparison of nonparalyzed and completely paralyzed subjects.}, journal = {IEEE Trans Neural Syst Rehabil Eng}, volume = {14}, year = {2006}, month = {06/2006}, pages = {183-6}, abstract = {

We summarize results from a series of related studies that aim to develop a motor-imagery-basedbrain-computer interface\ using a single recording session of electroencephalogram (EEG) or electrocorticogram (ECoG) signals for each subject. We apply the same experimental and analytical methods to 11 nonparalysed subjects (eight EEG, three ECoG), and to five paralyzed subjects (four EEG, one ECoG) who had been unable to communicate for some time. While it was relatively easy to obtain classifiable signals quickly from most of the nonparalyzed subjects, it proved impossible to classify the signals obtained from the paralyzed patients by the same methods. This highlights the fact that though certain BCI paradigms may work well with healthy subjects, this does not necessarily indicate success with the target user group. We outline possible reasons for this failure to transfer.

}, keywords = {Algorithms, Artificial Intelligence, Cluster Analysis, Computer User Training, Electroencephalography, Evoked Potentials, Female, Humans, Imagination, Male, Middle Aged, Paralysis, Pattern Recognition, Automated, User-Computer Interface}, issn = {1534-4320}, doi = {10.1109/TNSRE.2006.875548}, url = {http://www.ncbi.nlm.nih.gov/pubmed/16792289}, author = {Jeremy Jeremy Hill and Lal, T.N and Schr{\"o}der, Michael and Hinterberger, T. and Wilhelm, Barbara and Nijboer, F and Mochty, Ursula and Widman, Guido and Elger, Christian and Sch{\"o}lkopf, B and K{\"u}bler, A. and Niels Birbaumer} } @article {3220, title = {Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface.}, journal = {Neurology}, volume = {64}, year = {2005}, month = {05/2005}, pages = {1775{\textendash}1777}, abstract = {People with severe motor disabilities can maintain an acceptable quality of life if they can communicate. Brain-computer interfaces (BCIs), which do not depend on muscle control, can provide communication. Four people severely disabled by ALS learned to operate a BCI with EEG rhythms recorded over sensorimotor cortex. These results suggest that a sensorimotor rhythm-based BCI could help maintain quality of life for people with ALS.}, keywords = {User-Computer Interface}, issn = {1526-632X}, doi = {10.1212/01.WNL.0000158616.43002.6D}, url = {http://www.ncbi.nlm.nih.gov/pubmed/15911809}, author = {K{\"u}bler, A. and Nijboer, F. and Mellinger, J. and Theresa M Vaughan and Pawelzik, H. and Gerwin Schalk and Dennis J. McFarland and Niels Birbaumer and Jonathan Wolpaw} } @article {2169, title = {Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface.}, journal = {Neurology}, volume = {64}, year = {2005}, month = {05/2005}, pages = {1775-7}, abstract = {

People with severe motor disabilities can maintain an acceptable quality of life if they can communicate.\ Brain-computer interfaces\ (BCIs), which do not depend on muscle control, can provide communication. Four people severely disabled by ALS learned to operate a BCI with EEG rhythms recorded over sensorimotor cortex. These results suggest that a sensorimotor rhythm-based\ BCI could help maintain quality of life for people with ALS.

}, keywords = {Aged, Amyotrophic Lateral Sclerosis, Electroencephalography, Evoked Potentials, Motor, Evoked Potentials, Somatosensory, Female, Humans, Imagination, Male, Middle Aged, Motor Cortex, Movement, Paralysis, Photic Stimulation, Prostheses and Implants, Somatosensory Cortex, Treatment Outcome, User-Computer Interface}, issn = {1526-632X}, doi = {10.1212/01.WNL.0000158616.43002.6D}, url = {http://www.ncbi.nlm.nih.gov/pubmed/15911809}, author = {K{\"u}bler, A. and Nijboer, F and Mellinger, J{\"u}rgen and Theresa M Vaughan and Pawelzik, H and Gerwin Schalk and Dennis J. McFarland and Niels Birbaumer and Jonathan Wolpaw} } @article {3230, title = {Brain-computer communication: unlocking the locked in.}, journal = {Psychological bulletin}, volume = {127}, year = {2001}, month = {05/2001}, pages = {358{\textendash}375}, abstract = {With the increasing efficiency of life-support systems and better intensive care, more patients survive severe injuries of the brain and spinal cord. Many of these patients experience locked-in syndrome: The active mind is locked in a paralyzed body. Consequently, communication is extremely restricted or impossible. A muscle-independent communication channel overcomes this problem and is realized through a brain-computer interface, a direct connection between brain and computer. The number of technically elaborated brain-computer interfaces is in contrast with the number of systems used in the daily life of locked-in patients. It is hypothesized that a profound knowledge and consideration of psychological principles are necessary to make brain-computer interfaces feasible for locked-in patients.}, keywords = {User-Computer Interface}, issn = {0033-2909}, doi = {10.1037/0033-2909.127.3.358}, url = {http://www.ncbi.nlm.nih.gov/pubmed/11393301}, author = {K{\"u}bler, A. and Kotchoubey, B. and Kaiser, J. and Jonathan Wolpaw and Niels Birbaumer} }