xBCI: A Generic Platform for Development of an Online BCI System

A generic platform for realizing an online brain–computer interface (BCI) named xBCI was developed. The platform consists of several functional modules (components), such as data acquisition, storage, mathematical operations, signal processing, network communication, data visualization, experiment control, and real-time feedback presentation. Users can easily build their own BCI systems by combining the components on a graphical-user-interface (GUI) based diagram editor. They can also extend the platform by adding components as plug-ins or by creating components using a scripting language. The platform works on multiple operating systems and supports parallel (multi-threaded) data processing and data transfer to other PCs through a network transmission control protocol/internet protocol or user datagram protocol (TCP/IP or UDP). A BCI system based on motor imagery and a steady-state visual evoked potential (SSVEP) based BCI system were constructed and tested on the platform. The results show that the platform is able to process multichannel brain signals in real time. The platform provides users with an easy-to-use system development tool and reduces the time needed to develop a BCI system. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

[1]  M. Congedo,et al.  Open-ViBE: A Three Dimensional Platform for Real-Time Neuroscience , 2005 .

[2]  Gernot R. Müller-Putz,et al.  EURASIP Journal on Applied Signal Processing 2005:19, 3152–3155 c ○ 2005 Hindawi Publishing Corporation EEG-Based Asynchronous BCI Controls Functional Electrical Stimulation in a Tetraplegic Patient , 2004 .

[3]  G. R. Muller,et al.  Brain oscillations control hand orthosis in a tetraplegic , 2000, Neuroscience Letters.

[4]  G. Pfurtscheller,et al.  Brain-Computer Interfaces for Communication and Control. , 2011, Communications of the ACM.

[5]  Cuntai Guan,et al.  Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain–computer interface , 2007, NeuroImage.

[6]  E Donchin,et al.  Brain-computer interface technology: a review of the first international meeting. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[7]  Steven G. Johnson,et al.  The Design and Implementation of FFTW3 , 2005, Proceedings of the IEEE.

[8]  N. Birbaumer.  Breaking the silence: brain-computer interfaces (BCI) for communication and motor control. , 2006, Psychophysiology.

[9]  Xiaorong Gao,et al.  Design and implementation of a brain-computer interface with high transfer rates , 2002, IEEE Transactions on Biomedical Engineering.

[10]  Reinhold Scherer,et al.  Steady-state visual evoked potential (SSVEP)-based communication: impact of harmonic frequency components , 2005, Journal of neural engineering.

[11]  H. Flor,et al.  The thought translation device (TTD) for completely paralyzed patients. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[12]  M. Nuttin,et al.  A brain-actuated wheelchair: Asynchronous and non-invasive Brain–computer interfaces for continuous control of robots , 2008, Clinical Neurophysiology.

[13]  Wolfgang Grodd,et al.  Principles of a brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI) , 2004, IEEE Transactions on Biomedical Engineering.

[14]  Klaus-Robert Müller,et al.  The Berlin Brain-Computer Interface (BBCI) – towards a new communication channel for online control in gaming applications , 2007, Multimedia Tools and Applications.

[15]  N. Birbaumer,et al.  BCI2000: a general-purpose brain-computer interface (BCI) system , 2004, IEEE Transactions on Biomedical Engineering.