@article {3399, title = {Value of amplitude, phase, and coherence features for a sensorimotor rhythm-based brain-computer interface.}, journal = {Brain Res Bull}, volume = {87}, year = {2012}, month = {01/2012}, pages = {130-4}, abstract = {Measures that quantify the relationship between two or more brain signals are drawing attention as neuroscientists explore the mechanisms of large-scale integration that enable coherent behavior and cognition. Traditional Fourier-based measures of coherence have been used to quantify frequency-dependent relationships between two signals. More recently, several off-line studies examined phase-locking value (PLV) as a possible feature for use in brain-computer interface (BCI) systems. However, only a few individuals have been studied and full statistical comparisons among the different classes of features and their combinations have not been conducted. The present study examines the relative BCI performance of spectral power, coherence, and PLV, alone and in combination. The results indicate that spectral power produced classification at least as good as PLV, coherence, or any possible combination of these measures. This may be due to the fact that all three measures reflect mainly the activity of a single signal source (i.e., an area of sensorimotor cortex). This possibility is supported by the finding that EEG signals from different channels generally had near-zero phase differences. Coherence, PLV, and other measures of inter-channel relationships may be more valuable for BCIs that use signals from more than one distinct cortical source.}, keywords = {Algorithms, Brain, Electroencephalography, Humans, Motor Cortex, User-Computer Interface}, issn = {1873-2747}, doi = {10.1016/j.brainresbull.2011.09.019}, url = {http://www.ncbi.nlm.nih.gov/pubmed/21985984}, author = {Krusienski, Dean J and Dennis J. McFarland and Jonathan Wolpaw} } @article {2184, title = {Towards an independent brain-computer interface using steady state visual evoked potentials.}, journal = {Clin Neurophysiol}, volume = {119}, year = {2008}, month = {02/2008}, pages = {399-408}, abstract = {

OBJECTIVE:\ 

Brain-computer interface (BCI) systems using steady state visual evoked potentials (SSVEPs) have allowed healthy subjects to communicate. However, these systems may not work in severely disabled users because they may depend on gaze shifting. This study evaluates the hypothesis that overlapping stimuli can evoke changes in SSVEP activity sufficient to control a BCI. This would provide evidence that SSVEP BCIs could be used without shifting gaze.

METHODS:\ 

Subjects viewed a display containing two images that each oscillated at a different frequency. Different conditions used overlapping or non-overlapping images to explore dependence on gaze function. Subjects were asked to direct attention to one or the other of these images during each of 12 one-minute runs.

RESULTS:\ 

Half of the subjects produced differences in SSVEP activity elicited by overlapping stimuli that could support BCI control. In all remaining users, differences did exist at corresponding frequencies but were not strong enough to allow effective control.

CONCLUSIONS:\ 

The\ data\ demonstrate that SSVEP differences sufficient for BCI control may be elicited by selective attention to one of two overlapping stimuli. Thus, some SSVEP-based BCI approaches may not depend on gaze control. The nature and extent of any BCI{\textquoteright}s dependence on muscle activity is a function of many factors, including the display, task, environment, and user.

SIGNIFICANCE:\ 

SSVEP BCIs might function in severely disabled users unable to reliably control gaze. Further research with these users is necessary to explore the optimal parameters of such a system and validate online performance in a home environment.

}, keywords = {Adolescent, Adult, Attention, Brain, Brain Mapping, Dose-Response Relationship, Radiation, Electroencephalography, Evoked Potentials, Visual, Female, Humans, Male, Pattern Recognition, Visual, Photic Stimulation, Spectrum Analysis, User-Computer Interface}, issn = {1388-2457}, doi = {10.1016/j.clinph.2007.09.121}, url = {http://www.ncbi.nlm.nih.gov/pubmed/18077208}, author = {Brendan Z. Allison and Dennis J. McFarland and Gerwin Schalk and Zheng, Shi Dong and Moore-Jackson, Melody and Jonathan Wolpaw} } @article {2177, title = {The Wadsworth BCI Research and Development Program: At Home with BCI.}, journal = {IEEE Trans Neural Syst Rehabil Eng}, volume = {14}, year = {2006}, month = {06/2006}, pages = {229-33}, abstract = {

The ultimate goal of brain-computer interface (BCI) technology is to provide communication and control capacities to people with severe motor disabilities. BCI research at the Wadsworth Center focuses primarily on noninvasive,\ electroencephalography\ (EEG)-based BCI methods. We have shown that people, including those with severe motor disabilities, can learn to use sensorimotor rhythms (SMRs) to move a cursor rapidly and accurately in one or two dimensions. We have also improved P300-based BCI operation. We are now translating this laboratory-proven BCI technology into a system that can be used by severely disabled people in their homes with minimal ongoing technical oversight. To accomplish this, we have: improved our general-purpose BCI software (BCI2000); improved online adaptation and feature translation for SMR-based BCI operation; improved the accuracy and bandwidth of P300-based BCI operation; reduced the\ complexity\ of system hardware and software and begun to evaluate home system use in appropriate users. These developments have resulted in prototype systems for every day use in people{\textquoteright}s homes.

}, keywords = {Animals, Brain, Electroencephalography, Evoked Potentials, Humans, Neuromuscular Diseases, New York, Research, Switzerland, Therapy, Computer-Assisted, Universities, User-Computer Interface}, issn = {1534-4320}, doi = {10.1109/TNSRE.2006.875577}, url = {http://www.ncbi.nlm.nih.gov/pubmed/16792301}, author = {Theresa M Vaughan and Dennis J. McFarland and Gerwin Schalk and Sarnacki, William A and Krusienski, Dean J and Sellers, Eric W and Jonathan Wolpaw} } @article {2166, title = {BCI2000: a general-purpose brain-computer interface (BCI) system.}, journal = {IEEE Trans Biomed Eng}, volume = {51}, year = {2004}, month = {06/2004}, pages = {1034-43}, abstract = {Many laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Further progress and realization of practical applications depends on systematic evaluations and comparisons of different brain signals, recording methods, processing algorithms, output formats, and operating protocols. However, the typical BCI system is designed specifically for one particular BCI method and is, therefore, not suited to the systematic studies that are essential for continued progress. In response to this problem, we have developed a documented general-purpose BCI research and development platform called BCI2000. BCI2000 can incorporate alone or in combination any brain signals, signal processing methods, output devices, and operating protocols. This report is intended to describe to investigators, biomedical engineers, and computer scientists the concepts that the BC12000 system is based upon and gives examples of successful BCI implementations using this system. To date, we have used BCI2000 to create BCI systems for a variety of brain signals, processing methods, and applications. The data show that these systems function well in online operation and that BCI2000 satisfies the stringent real-time requirements of BCI systems. By substantially reducing labor and cost, BCI2000 facilitates the implementation of different BCI systems and other psychophysiological experiments. It is available with full documentation and free of charge for research or educational purposes and is currently being used in a variety of studies by many research groups.}, keywords = {Algorithms, Brain, Cognition, Communication Aids for Disabled, Computer Peripherals, Electroencephalography, Equipment Design, Equipment Failure Analysis, Evoked Potentials, Humans, Systems Integration, User-Computer Interface}, issn = {0018-9294}, doi = {10.1109/TBME.2004.827072}, author = {Gerwin Schalk and Dennis J. McFarland and Hinterberger, T. and Niels Birbaumer and Jonathan Wolpaw} } @article {2165, title = {The Wadsworth Center brain-computer interface (BCI) research and development program.}, journal = {IEEE Trans Neural Syst Rehabil Eng}, volume = {11}, year = {2003}, month = {06/2003}, pages = {204-7}, abstract = {

Brain-computer interface (BCI) research at the Wadsworth Center has focused primarily on using electroencephalogram (EEG) rhythms recorded from the scalp over sensorimotor cortex to\ control\ cursor movement in one or two dimensions. Recent and current studies seek to improve the speed and accuracy of this\ control\ by improving the selection of signal features and their translation into device commands, by incorporating additional signal features, and by optimizing the adaptive interaction between the user and system. In addition, to facilitate the evaluation, comparison, and combination of alternative BCI methods, we have developed a general-purpose BCI system called BCI-2000 and have made it available to other research\ groups. Finally, in collaboration with several other\ groups, we are developing simple BCI applications and are testing their practicality and long-term value for people with severe motor disabilities.

}, keywords = {Academic Medical Centers, Adult, Algorithms, Artifacts, Brain, Brain Mapping, Electroencephalography, Evoked Potentials, Visual, Feedback, Humans, Middle Aged, Nervous System Diseases, Research, Research Design, User-Computer Interface, Visual Perception}, issn = {1534-4320}, doi = {10.1109/TNSRE.2003.814442}, url = {http://www.ncbi.nlm.nih.gov/pubmed/12899275}, author = {Jonathan Wolpaw and Dennis J. McFarland and Theresa M Vaughan and Gerwin Schalk} }