BCI2000: A General-Purpose Brain-Computer Interface (BCI) System

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.

Towards an independent brain–computer interface using steady state visual evoked potentials

“…Other articles have reported information throughput on the order of 30−40 bits per minute (for mu BCIs; Wolpaw and McFarland, 2004) or 68 bits per minute (for SSVEP BCIs; Gao et al 2003). However, these articles both allowed gaze shifting and used an elite subset of subjects.…”

“…Data were sampled at 160 Hz, band-pass filtered between 0.1−50 Hz, and amplified 20,000× on an SA Instruments biosignal amplifier. The BCI2000 software package (Schalk et al, 2004) was used for all data acquisition. Stimuli were presented using Presentation (Neurobehavioral Systems) and analyzed using BCI2ASCII (Wadsworth Center) and Matlab Release 12 (Mathworks).…”

“…Subjects run at the Wadsworth lab are first prescreened to evaluate their mu activity, and fewer than 20% are selected for further training (Vaughan, personal communication). Of these, only the best subjects were selected for the 2D training reported in Wolpaw and McFarland (2004). The performance reported in Gao et al (2003) was from the best subject found during that group's prior work (Cheng et al, 2002), which reported information throughput as low as .76 bits per minute.…”

Toward enhanced P300 speller performance

“…The EEG was bandpass filtered 0.1 -60 Hz and amplified with a SA Electronics amplifier (20,000X), digitized at a rate of 240 Hz, and stored. All aspects of data collection and experimental procedure were controlled by the BCI2000 system [16].…”

Non-invasive brain–computer interface system: Towards its application as assistive technology

“…This BCI system was based on detection of simple motor imagery (mediated by modulation of sensorimotor EEG rhythms) and was realized using the BCI2000 software system [17]. Users needed to learn to modulate their sensorimotor rhythms to achieve more robust control than the simple imagination of limb movements can produce.…”