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Multiclass Brain-Computer Interface Classification by Riemannian Geometry
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Machine learning for signal processing : applications to Brain Computer Inter...
Brain Computer Interfaces (BCI) require the use of statistical learning methods for signal recognition. In this thesis we propose a general approach using prior... -
Two Brains, One Game: Design and Evaluation of a Multi-User BCI Video Game Ba...
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BCI Research at Inria Bordeaux: making BCI designs usable outside the lab
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Review of "Brain-Computer Interfaces, principles and practise", edited by Jon...
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Classification of covariance matrices using a Riemannian-based kernel for BCI...
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Combining ERD and ERS features to create a system-paced BCI
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Towards next generation human-computer interaction -- brain-computer interfac...
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Subject-specific channel selection for classification of motor imagery electr...
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Brain-Machine Interfaces based on brief imaginary movements: towards brain-co...
Brain Computer Interfaces are a new type of device, allowing direct communication between a user's brain and a machine. Such devices have been proposed based on... -
Verbal Communication through Brain Computer Interfaces
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Flaws in current human training protocols for spontaneous Brain-Computer Inte...
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Brain-machine coadaptation for optimal interaction: application to P300-Speller
Brain-computer interfaces (BCI) aim at enabling the brain to directly control an artificial device. In particular, the P300-Speller could offer patients who cannot... -
Optimizing P300-speller sequences by RIP-ping groups apart
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Wavelet-based semblance methods to enhance single-trial ERP detection
Brain-Computer Interfaces (BCI) are control and communication systems which were initially developed for people with disabilities. The idea behind BCI is to translate... -
KEOPS: KErnels Organized into PyramidS
International audience
