• Corpus ID: 60166242

Functional Magnetic Resonance Imaging based BCI for Neurorehabilitation

  title={Functional Magnetic Resonance Imaging based BCI for Neurorehabilitation},
  author={Ranganatha Sitaram and Veit R Caria A and K{\^a}mil Uludağ and Tilman Gaber and Andrea K{\"u}bler and Niels Birbaumer},
Towards passive brain-computer interfaces: applying brain-computer interface technology to human-machine systems in general.
A unifying categorization of BCI-based applications, including the novel approach of passive BCI is proposed, which focuses on applications for healthy users, and the specific requirements and demands of this user group.
Metabolic Brain-Computer Interfaces
fMRI-BCI: a Review
An overview to fMRI-BCI is presented, mainly put on the methods of signal acquisition, signal preprocessing, and signal analysis of basic fMRI -BCI structure.
Analysis of nonstationarities in EEG signals for improving brain-computer interface performance
A new framework for nonstationary data analy sis is presented, which encompasses methods for the quantification and visualization of non stationary p rocesses, and some neurophysiological evidence for the sources of the nonstationarity is shown.
fMRI Brain-Computer Interfaces
A general architecture of an fMRI-BCI is presented, with descriptions of each of its subsystems, and factors influencing their performance, and a variety of approaches toward signal acquisition, preprocessing, analysis, and feedback are described.
BioSig - an open source software library for BCI research
This chapter provides an overview of the current status and an outline of future possibilities of BioSig, an open-source software library for biomedical signal processing that includes several classification methods for single-trial classification of EEG.