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BCI2000: a general-purpose brain-computer interface (BCI) system.
Literature Information
| DOI | 10.1109/TBME.2004.827072 |
|---|---|
| PMID | 15188875 |
| Journal | IEEE transactions on bio-medical engineering |
| Impact Factor | 4.5 |
| JCR Quartile | Q2 |
| Publication Year | 2004 |
| Times Cited | 654 |
| Keywords | Brain-Computer Interface, BCI2000, Signal Processing |
| Literature Type | Comparative Study, Evaluation Study, Journal Article, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, P.H.S. |
| ISSN | 0018-9294 |
| Pages | 1034-43 |
| Issue | 51(6) |
| Authors | Gerwin Schalk, Dennis J McFarland, Thilo Hinterberger, Niels Birbaumer, Jonathan R Wolpaw |
TL;DR
This paper introduces BCI2000, a versatile brain-computer interface (BCI) research platform designed to support systematic evaluations and comparisons across various brain signals, processing methods, and output devices, addressing the limitations of traditional BCI systems tailored for specific methods. The findings demonstrate that BCI2000 effectively meets real-time operational requirements, significantly reducing costs and labor, thereby enhancing the development and implementation of diverse BCI systems for researchers and educators.
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Brain-Computer Interface · BCI2000 · Signal Processing
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.
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Primary Questions Addressed
- What are the specific advantages of using BCI2000 over other BCI systems in research settings?
- How does BCI2000 accommodate different brain signal types and processing methods in practical applications?
- What challenges have researchers faced when implementing BCI2000 in various experimental setups?
- Can you provide examples of innovative applications that have successfully utilized BCI2000 in clinical or rehabilitation contexts?
- How does the open-source nature of BCI2000 impact collaboration among researchers in the field of brain-computer interfaces?
Key Findings
Key Insights on BCI2000: A General-Purpose Brain-Computer Interface System
Research Background and Purpose: The development of brain-computer interface (BCI) systems has gained momentum as a means to facilitate communication and control for individuals with severe motor disabilities. However, the field faces challenges due to the diversity of brain signals, recording methods, processing algorithms, output formats, and operational protocols. Current BCI systems tend to be designed for specific methodologies, limiting their utility in systematic evaluations that are necessary for advancing the field. The purpose of this study is to introduce BCI2000, a versatile and documented platform that supports the integration of various components in BCI research, enabling broader comparisons and evaluations within the field.
Main Methods and Findings: BCI2000 is designed as a flexible research and development platform that can accommodate various brain signals, signal processing techniques, output devices, and operational protocols. The system has been successfully implemented in multiple BCI applications, demonstrating its adaptability and effectiveness. Through practical examples, the report showcases how BCI2000 meets the stringent real-time requirements necessary for effective BCI operation. The findings indicate that the platform can significantly streamline the development process for different BCI systems, providing robust performance in online settings.
Core Conclusions: BCI2000 stands out as a general-purpose platform that not only simplifies the integration of diverse BCI components but also enhances the overall efficiency of BCI research. By reducing both labor and financial costs, it enables researchers to explore various methodologies without being constrained by the limitations of specialized systems. The positive performance outcomes further affirm BCI2000's viability as an essential tool for advancing BCI technology.
Research Significance and Impact: The introduction of BCI2000 is a pivotal advancement in the BCI research landscape, offering a foundational tool that supports systematic investigations and comparisons of BCI methodologies. By providing an open-access platform with comprehensive documentation, BCI2000 democratizes BCI research, making it accessible to a wider range of researchers, engineers, and scientists. The implications of this work extend beyond academic inquiry, potentially leading to improved communication and control solutions for individuals with disabilities, thereby contributing to their quality of life. Furthermore, the platform's adaptability could accelerate innovation in related fields, such as neuroengineering and psychophysiology, making it a cornerstone for future BCI development.
Literatures Citing This Work
- Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. - Jonathan R Wolpaw;Dennis J McFarland - Proceedings of the National Academy of Sciences of the United States of America (2004)
- When mind meets machine. - Vicki Brower - EMBO reports (2005)
- An enhanced time-frequency-spatial approach for motor imagery classification. - Nobuyuki Yamawaki;Christopher Wilke;Zhongming Liu;Bin He - IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society (2006)
- Spectral changes in cortical surface potentials during motor movement. - Kai J Miller;Eric C Leuthardt;Gerwin Schalk;Rajesh P N Rao;Nicholas R Anderson;Daniel W Moran;John W Miller;Jeffrey G Ojemann - The Journal of neuroscience : the official journal of the Society for Neuroscience (2007)
- An MEG-based brain-computer interface (BCI). - Jürgen Mellinger;Gerwin Schalk;Christoph Braun;Hubert Preissl;Wolfgang Rosenstiel;Niels Birbaumer;Andrea Kübler - NeuroImage (2007)
- Toward enhanced P300 speller performance. - D J Krusienski;E W Sellers;D J McFarland;T M Vaughan;J R Wolpaw - Journal of neuroscience methods (2008)
- Towards an independent brain-computer interface using steady state visual evoked potentials. - Brendan Z Allison;Dennis J McFarland;Gerwin Schalk;Shi Dong Zheng;Melody Moore Jackson;Jonathan R Wolpaw - Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology (2008)
- Think to move: a neuromagnetic brain-computer interface (BCI) system for chronic stroke. - Ethan Buch;Cornelia Weber;Leonardo G Cohen;Christoph Braun;Michael A Dimyan;Tyler Ard;Jurgen Mellinger;Andrea Caria;Surjo Soekadar;Alissa Fourkas;Niels Birbaumer - Stroke (2008)
- Online artifact removal for brain-computer interfaces using support vector machines and blind source separation. - Sebastian Halder;Michael Bensch;Jürgen Mellinger;Martin Bogdan;Andrea Kübler;Niels Birbaumer;Wolfgang Rosenstiel - Computational intelligence and neuroscience (2007)
- Two-dimensional movement control using electrocorticographic signals in humans. - G Schalk;K J Miller;N R Anderson;J A Wilson;M D Smyth;J G Ojemann;D W Moran;J R Wolpaw;E C Leuthardt - Journal of neural engineering (2008)
... (644 more literatures)
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