Brain–Computer Interfaces - Index of

Brain–Computer Interface
in Neurorehabilitation
Niels Birbaumer and Paul Sauseng
1 Introduction
Brain–computer interfaces (BCI) are using brain signals to drive an external device
outside the brain without activation of motor output channels. Different types of
BCIs were described during the last 10 years with an exponentially increasing number
of publications devoted to Brain–computer interface research [32]. Most of the
literature describes mathematical algorithms capable of translating brain signals online
and real-time into signals for an external device, mainly computers or peripheral
prostheses or orthoses. Publications describing applications to human disorders are
relatively sparse with very few controlled studies available on the effectiveness of
BCIs in treatment and rehabilitation (for a summary see [8, 20]).
Historically, BCIs for human research developed mainly out of the neurofeedback
literature devoted to operant conditioning and biofeedback of different types
of brain signals to control seizures [16], to treat attention deficit disorder [34], stroke
and other neuro-psychiatric disorders ([28]; for a review see [31]). Brain–computer
interface research departed from neurofeedback by applying advanced mathematical
classification algorithms and using basic animal research with direct recording
of spike activity in the cortical network to regulate devices outside the brain.
Brain–computer interface research in animals and humans used many different
brain signals: in animals spike trains from multiple microelectrode recordings (for
a summary see Schwartz and Andrasik (2003) and chapter “Intracortical BCIs: A
Brief History of Neural Timing” in this book), but also in humans. One study [14]
reported “Neural ensemble control of prosthetic devices by a human with tetraplegia”.
In human research mainly non-invasive EEG recordings using sensory motor
rhythm [18], slow cortical potentials [3] and the P300 event-related evoked brain
potential [13] were described.
N. Birbaumer (B)
Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen,
Germany
e-mail: niels.birbaumer@uni-tuebingen.de
B. Graimann et al. (eds.), Brain–Computer Interfaces, The Frontiers Collection,
DOI 10.1007/978-3-642-02091-9_9, C○ Springer-Verlag Berlin Heidelberg 2010
155