@article {2190, title = {Using an EEG-based brain-computer interface for virtual cursor movement with BCI2000.}, journal = {J Vis Exp}, year = {2009}, month = {07/2009}, abstract = {

A brain-computer interface (BCI) functions by translating a neural signal, such as the electroencephalogram (EEG), into a signal that can be used to control a computer or other device. The amplitude of the EEG signals in selected frequency bins are measured and translated into a device command, in this case the horizontal and vertical velocity of a computer cursor. First, the EEG electrodes are applied to the user s scalp using a cap to record brain activity. Next, a calibration procedure is used to find the EEG electrodes and features that the user will learn to voluntarily modulate to use the BCI. In humans, the power in the mu (8-12 Hz) and beta (18-28 Hz) frequency bands decrease in amplitude during a real or imagined movement. These changes can be detected in the EEG in real-time, and used to control a BCI ([1],[2]). Therefore, during a screening test, the user is asked to make several different imagined movements with their hands and feet to determine the unique EEG features that change with the imagined movements. The results from this calibration will show the best channels to use, which are configured so that amplitude changes in the mu and beta frequency bands move the cursor either horizontally or vertically. In this experiment, the general purpose BCI system BCI2000 is used to control signal acquisition, signal processing, and feedback to the user [3].

}, keywords = {Brain, Calibration, Electrodes, Electroencephalography, Humans, User-Computer Interface}, issn = {1940-087X}, doi = {10.3791/1319}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19641479}, author = {Adam J Wilson and Gerwin Schalk and Walton, L{\'e}o M and Williams, Justin C} } @article {2118, title = {Technical features of a CCD video camera system to record cardiac fluorescence data.}, journal = {Ann Biomed Eng}, volume = {25}, year = {1997}, month = {07/1997}, pages = {713-25}, abstract = {

A charge-coupled device (CCD) camera was used to acquire movies of transmembrane activity from thin slices of sheep ventricular\ epicardial\ muscle stained with a voltage-sensitive dye. Compared with photodiodes, CCDs have high spatial resolution, but low temporal resolution. Spatial resolution in our system ranged from 0.04 to 0.14 mm/pixel; the acquisition rate was 60, 120, or 240 frames/sec. Propagating waves were readily visualized after subtraction of a background image. The optical signal had an amplitude of 1 to 6 gray levels, with signal-to-noise ratios between 1.5 and 4.4. Because CCD cameras integrate light over the frame interval, moving objects, including propagating waves, are blurred in the resulting movies. A computer model of such an integrating\ imaging\ system was developed to study the effects of blur, noise, filtering, and quantization on the ability to measure conduction velocity and action potential duration (APD). The model indicated that blurring, filtering, and quantization do not affect the ability to localize wave fronts in the optical data (i.e., no systematic error in determining spatial position), but noise does increase the uncertainty of the measurements. The model also showed that the low frame rates of the CCD camera introduced a systematic error in the calculation of APD: for cutoff levels \> 50\%, the APD was erroneously long. Both noise and quantization increased the uncertainty in the APD measurements. The optical measures of conduction velocity were not significantly different from those measured simultaneously with microelectrodes. Optical APDs, however, were longer than the electrically recorded APDs. This APD error could be reduced by using the 50\% cutoff level and the fastest frame rate possible.

}, keywords = {Action Potentials, Algorithms, Animals, Body Surface Potential Mapping, Calibration, Computer Simulation, Electric Conductivity, Fluorescent Dyes, Image Processing, Computer-Assisted, Models, Cardiovascular, Sheep, Ventricular Function, Video Recording}, issn = {0090-6964}, doi = {10.1007/BF02684848}, url = {http://www.ncbi.nlm.nih.gov/pubmed/9236983}, author = {Baxter, Bill and Davidenko, J M and Loew, L M and Wuskell, J P and Jalife, J} }