Clemens Brunner

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We studied the reactivity of EEG rhythms (mu rhythms) in association with the imagination of right hand, left hand, foot, and tongue movement with 60 EEG electrodes in nine able-bodied subjects. During hand motor imagery, the hand mu rhythm blocked or desynchronized in all subjects, whereas an enhancement of the hand area mu rhythm was observed during foot(More)
Nowadays, everybody knows what a hybrid car is. A hybrid car normally has two engines to enhance energy efficiency and reduce CO2 output. Similarly, a hybrid brain-computer interface (BCI) is composed of two BCIs, or at least one BCI and another system. A hybrid BCI, like any BCI, must fulfill the following four criteria: (i) the device must rely on signals(More)
Software development is a key issue in brain-computer interface (BCI) research. Software can show the similarities and differences of different data processing methods. It can also make clear which hyperparameters must be determined for particular algorithms. And it can demonstrate whether certain concepts are compatible or not. With BioSig's comprehensive(More)
Brain-Computer Interface (BCI) research has become a growing field of interest in the last years. The work presented ranges from machine learning approaches in offline results to the application of a BCI in patients. However, reliable classification of brain activity is a crucial issue in BCI research. In contrast to most articles which present methods to(More)
This paper compares different ICA preprocessing algorithms on cross-validated training data as well as on unseen test data. The EEG data were recorded from 22 electrodes placed over the whole scalp during motor imagery tasks consisting of four different classes, namely the imagination of right hand, left hand, foot and tongue movements. Two sessions on(More)
Brain-computer interface (BCI) systems do not work for all users. This article introduces a novel combination of tasks that could inspire BCI systems that are more accurate than conventional BCIs, especially for users who cannot attain accuracy adequate for effective communication. Subjects performed tasks typically used in two BCI approaches, namely(More)
Advances in cognitive neurosci- ence and brain-imaging technologies give us the unprecedented ability to interface directly with brain activity. These technologies let us monitor the physical processes in the brain that correspond with certain forms of thought. Driven by society's growing recognition of the needs of people with physical disabilities,(More)
Currently, almost all brain-computer interfaces (BCIs) ignore the relationship between phases of electroencephalographic signals detected from different recording sites (i.e., electrodes). The vast majority of BCI systems rely on feature vectors derived from e.g., bandpower or univariate adaptive autoregressive (AAR) parameters. However, ample evidence(More)
We investigated the behavior of short-lasting beta bursts (beta rebound, beta ERS) induced after imagination of hand, foot or tongue movement. Nine able-bodied subjects were asked to imagine one type of movement following the presentation of a visual cue stimulus. EEG was recorded from 60 closely spaced electrodes placed over frontal, central and parietal(More)