TY - JOUR T1 - A P300-based brain-computer interface for people with amyotrophic lateral sclerosis. JF - Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Y1 - 2008 A1 - Nijboer, F. A1 - Sellers, E. W. A1 - Mellinger, J. A1 - Jordan, M. A. A1 - Matuz, T. A1 - Adrian Furdea A1 - S Halder A1 - Mochty, U. A1 - Krusienski, D. J. A1 - Theresa M Vaughan A1 - Jonathan Wolpaw A1 - Niels Birbaumer A1 - Kübler, A. KW - Amyotrophic Lateral Sclerosis KW - brain-computer interface KW - electroencephalogram KW - event-related potentials KW - P300 KW - Rehabilitation AB - 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. VL - 119 UR - http://www.ncbi.nlm.nih.gov/pubmed/18571984 ER - TY - CHAP T1 - Brain Computer Interfaces for Communication in Paralysis: a Clinical-Experimental Approach. Y1 - 2007 A1 - Hinterberger, T. A1 - Nijboer, F A1 - Kübler, A. A1 - Matuz, T. A1 - Adrian Furdea A1 - Mochty, Ursula A1 - Jordan, M. A1 - Lal, T.N A1 - Jeremy Jeremy Hill A1 - Mellinger, Jürgen A1 - Bensch, M A1 - Tangermann, Michael A1 - Widmann, G. A1 - Elger, Christian A1 - Rosenstiel, W. A1 - Schölkopf, B A1 - Niels Birbaumer KW - brain-computer interfaces KW - EEG KW - experiment KW - Medical sciences Medicine KW - paralyzed patients KW - slow cortical potentials KW - Thought-Translation Device AB -

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.

PB - Virtual Library of Psychology at Saarland University and State Library, GERMANY, PsyDok [http://psydok.sulb.uni-saarland.de/phpoai/oai2.php] (Germany) SN - 9780262256049 UR - http://psydok.sulb.uni-saarland.de/volltexte/2008/2154/ ER - TY - JOUR T1 - An MEG-based brain-computer interface (BCI). JF - Neuroimage Y1 - 2007 A1 - Mellinger, Jürgen A1 - Gerwin Schalk A1 - Christoph Braun A1 - Preissl, Hubert A1 - Rosenstiel, W. A1 - Niels Birbaumer A1 - Kübler, A. KW - Adult KW - Algorithms KW - Artifacts KW - Brain KW - Electroencephalography KW - Electromagnetic Fields KW - Electromyography KW - Feedback KW - Female KW - Foot KW - Hand KW - Head Movements KW - Humans KW - Magnetic Resonance Imaging KW - Magnetoencephalography KW - Male KW - Movement KW - Principal Component Analysis KW - Signal Processing, Computer-Assisted KW - User-Computer Interface AB -

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.

VL - 36 UR - http://www.ncbi.nlm.nih.gov/pubmed/17475511 IS - 3 ER - TY - JOUR T1 - Classifying EEG and ECoG signals without subject training for fast BCI implementation: comparison of nonparalyzed and completely paralyzed subjects. JF - IEEE Trans Neural Syst Rehabil Eng Y1 - 2006 A1 - Jeremy Jeremy Hill A1 - Lal, T.N A1 - Schröder, Michael A1 - Hinterberger, T. A1 - Wilhelm, Barbara A1 - Nijboer, F A1 - Mochty, Ursula A1 - Widman, Guido A1 - Elger, Christian A1 - Schölkopf, B A1 - Kübler, A. A1 - Niels Birbaumer KW - Algorithms KW - Artificial Intelligence KW - Cluster Analysis KW - Computer User Training KW - Electroencephalography KW - Evoked Potentials KW - Female KW - Humans KW - Imagination KW - Male KW - Middle Aged KW - Paralysis KW - Pattern Recognition, Automated KW - User-Computer Interface AB -

We summarize results from a series of related studies that aim to develop a motor-imagery-based brain-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.

VL - 14 UR - http://www.ncbi.nlm.nih.gov/pubmed/16792289 IS - 2 ER - TY - JOUR T1 - Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface. JF - Neurology Y1 - 2005 A1 - Kübler, A. A1 - Nijboer, F. A1 - Mellinger, J. A1 - Theresa M Vaughan A1 - Pawelzik, H. A1 - Gerwin Schalk A1 - Dennis J. McFarland A1 - Niels Birbaumer A1 - Jonathan Wolpaw KW - User-Computer Interface AB - 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. VL - 64 UR - http://www.ncbi.nlm.nih.gov/pubmed/15911809 ER - TY - JOUR T1 - Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface. JF - Neurology Y1 - 2005 A1 - Kübler, A. A1 - Nijboer, F A1 - Mellinger, Jürgen A1 - Theresa M Vaughan A1 - Pawelzik, H A1 - Gerwin Schalk A1 - Dennis J. McFarland A1 - Niels Birbaumer A1 - Jonathan Wolpaw KW - Aged KW - Amyotrophic Lateral Sclerosis KW - Electroencephalography KW - Evoked Potentials, Motor KW - Evoked Potentials, Somatosensory KW - Female KW - Humans KW - Imagination KW - Male KW - Middle Aged KW - Motor Cortex KW - Movement KW - Paralysis KW - Photic Stimulation KW - Prostheses and Implants KW - Somatosensory Cortex KW - Treatment Outcome KW - User-Computer Interface AB -

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.

VL - 64 UR - http://www.ncbi.nlm.nih.gov/pubmed/15911809 IS - 10 ER - TY - JOUR T1 - Brain-computer communication: unlocking the locked in. JF - Psychological bulletin Y1 - 2001 A1 - Kübler, A. A1 - Kotchoubey, B. A1 - Kaiser, J. A1 - Jonathan Wolpaw A1 - Niels Birbaumer KW - User-Computer Interface AB - 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. VL - 127 UR - http://www.ncbi.nlm.nih.gov/pubmed/11393301 ER -