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IJCNN
2008
IEEE
14 years 2 months ago
Multifractal feature vectors for Brain-Computer interfaces
—This article introduces a new feature vector extraction for EEG signals using multifractal analysis. The validity of the approach is asserted on real data sets from the BCI comp...
Nicolas Brodu
ICASSP
2010
IEEE
13 years 6 months ago
Learning from other subjects helps reducing Brain-Computer Interface calibration time
A major limitation of Brain-Computer Interfaces (BCI) is their long calibration time, as much data from the user must be collected in order to tune the BCI for this target user. I...
Fabien Lotte, Cuntai Guan
ICPR
2008
IEEE
14 years 9 months ago
Pattern rejection strategies for the design of self-paced EEG-based Brain-Computer Interfaces
This paper deals with pattern rejection strategies for self-paced Brain-Computer Interfaces (BCI). First, it introduces two pattern rejection strategies not used yet for self-pace...
Fabien Lotte, Harold Mouchère, Anatole L&ea...
HCI
2009
13 years 6 months ago
A Novel Dry Electrode for Brain-Computer Interface
A brain-computer interface is a device that uses signals recorded from the brain to directly control a computer. In the last few years, P300-based braincomputer interfaces (BCIs) h...
Eric W. Sellers, Peter J. Turner, William A. Sarna...
AUSDM
2008
Springer
271views Data Mining» more  AUSDM 2008»
13 years 10 months ago
Classification of Brain-Computer Interface Data
In this paper we investigate the classification of mental tasks based on electroencephalographic (EEG) data for Brain Computer Interfaces (BCI) in two scenarios: off line and on-l...
Omar AlZoubi, Irena Koprinska, Rafael A. Calvo