Title: Bayesian Plan Recognition for Brain-Computer Interfaces
Authors: Demeester, Eric
H√ľntemann, Alexander
del R. Millán, José del R. Millán
Van Brussel, Hendrik #
Issue Date: 12-May-2009
Host Document: IEEE International Conference on Robotics and Automation pages:653-658
Conference: ICRA 2009 location:Kobe, Japan date:12-17 May 2009
Abstract: For people with very severe motor dysfunctions,
Brain-Computer Interfaces (BCIs) may provide the solution to
regain mobility and manipulation capabilities. Unfortunately, BCIs are characterized by a limited bandwidth and uncertainty on the BCI output.
In the past, we have developed a Bayesian plan recognition
framework that estimates from uncertain human-robot interface signals the task a robot should execute. This paper extends our plan recognition framework to incorporate uncertain BCI signals. A benchmark test is proposed and adopted to evaluate both the plan recognition framework and the performance of the BCI user, for the concrete application of wheelchair driving.
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Production Engineering, Machine Design and Automation (PMA) Section
# (joint) last author

Files in This Item:

There are no files associated with this item.

Request a copy


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science