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conference paper
Augmenting Information from Brain-Computer Interfaces through Bayesian Plan Recognition
2009
Proceedings of 17th European Symposium on Artificial Neural Networks
For severely disabled people, Brain-Computer Interfaces (BCIs) may provide the means to regain mobility and manipulation capabilities. However, information obtained from current BCIs is uncertain and of limited bandwidth and resolution. This paper presents a Bayesian framework that estimates from uncertain BCI signals a richer representation of the task a robotic mobility or manipulation device should execute, such that these devices can be operated more safely, accurately and efficiently. The framework has been evaluated on a simulated robotic wheelchair.
Type
conference paper
Authors
Publication date
2009
Published in
Proceedings of 17th European Symposium on Artificial Neural Networks
Peer reviewed
REVIEWED
Event name | Event place | Event date |
Bruges, Belgium | April, 22-24, 2009 | |
Available on Infoscience
January 26, 2010
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