TY - JOUR T1 - Voluntary brain regulation and communication with electrocorticogram signals. JF - Epilepsy Behav Y1 - 2008 A1 - Hinterberger, T. A1 - Widman, Guido A1 - Lal, T.N A1 - Jeremy Jeremy Hill A1 - Tangermann, Michael A1 - Rosenstiel, W. A1 - Schölkopf, B A1 - Elger, Christian A1 - Niels Birbaumer KW - Adult KW - Biofeedback, Psychology KW - Cerebral Cortex KW - Communication Aids for Disabled KW - Dominance, Cerebral KW - Electroencephalography KW - Epilepsies, Partial KW - Female KW - Humans KW - Imagination KW - Male KW - Middle Aged KW - Motor Activity KW - Motor Cortex KW - Signal Processing, Computer-Assisted KW - Software KW - Somatosensory Cortex KW - Theta Rhythm KW - User-Computer Interface KW - Writing AB -

Brain-computer interfaces (BCIs) can be used for communication in writing without muscular activity or for learning to control seizures by voluntary regulation of brain signals such as the electroencephalogram (EEG). Three of five patients with epilepsy were able to spell their names with electrocorticogram (ECoG) signals derived from motor-related areas within only one or two training sessions. Imagery of finger or tongue movements was classified with support-vector classification of autoregressive coefficients derived from the ECoG signals. After training of the classifier, binary classification responses were used to select letters from a computer-generated menu. Offline analysis showed increased theta activity in the unsuccessful patients, whereas the successful patients exhibited dominant sensorimotor rhythms that they could control. The high spatial resolution and increased signal-to-noise ratio in ECoG signals, combined with short training periods, may offer an alternative for communication in complete paralysis, locked-in syndrome, and motor restoration.

VL - 13 UR - http://www.ncbi.nlm.nih.gov/pubmed/18495541 IS - 2 ER - TY - JOUR T1 - Brain-computer interface technology: a review of the first international meeting. JF - IEEE Trans Rehabil Eng Y1 - 2000 A1 - Jonathan Wolpaw A1 - Niels Birbaumer A1 - Heetderks, W J A1 - Dennis J. McFarland A1 - Peckham, P H A1 - Gerwin Schalk A1 - Emanuel Donchin A1 - Quatrano, L A A1 - Robinson, C J A1 - Theresa M Vaughan KW - Algorithms KW - Cerebral Cortex KW - Communication Aids for Disabled KW - Disabled Persons KW - Electroencephalography KW - Evoked Potentials KW - Humans KW - Neuromuscular Diseases KW - Signal Processing, Computer-Assisted KW - User-Computer Interface AB -

Over the past decade, many laboratories have begun to explore brain-computer interface (BCI) technology as a radically new communication option for those with neuromuscular impairments that prevent them from using conventional augmentative communication methods. BCI's provide these users with communication channels that do not depend on peripheral nerves and muscles. This article summarizes the first international meeting devoted to BCI research and development. Current BCI's use electroencephalographic (EEG) activity recorded at the scalp or single-unit activity recorded from within cortex to control cursor movement, select letters or icons, or operate a neuroprosthesis. The central element in each BCI is a translation algorithm that converts electrophysiological input from the user into output that controls external devices. BCI operation depends on effective interaction between two adaptive controllers, the user who encodes his or her commands in the electrophysiological input provided to the BCI, and the BCI which recognizes the commands contained in the input and expresses them in device control. Current BCI's have maximum information transfer rates of 5-25 b/min. Achievement of greater speed and accuracy depends on improvements in signal processing, translation algorithms, and user training. These improvements depend on increased interdisciplinary cooperation between neuroscientists, engineers, computer programmers, psychologists, and rehabilitation specialists, and on adoption and widespread application of objective methods for evaluating alternative methods. The practical use of BCI technology depends on the development of appropriate applications, identification of appropriate user groups, and careful attention to the needs and desires of individual users. BCI research and development will also benefit from greater emphasis on peer-reviewed publications, and from adoption of standard venues for presentations and discussion.

VL - 8 UR - http://www.ncbi.nlm.nih.gov/pubmed/10896178 IS - 2 ER -