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Mathematical Problems in Engineering
Volume 2016, Article ID 1435321, 12 pages
http://dx.doi.org/10.1155/2016/1435321
Research Article

User Adapted Motor-Imaginary Brain-Computer Interface by means of EEG Channel Selection Based on Estimation of Distributed Algorithms

1Department of Computer Science and Artificial Intelligence, University of the Basque Country UPV/EHU, Computer Science Faculty, 20018 Donostia-San Sebastian, Spain
2Department of Computer Architecture and Technology, University of the Basque Country UPV/EHU, Computer Science Faculty, 20018 Donostia-San Sebastian, Spain

Received 4 June 2014; Accepted 19 November 2014

Academic Editor: Yudong Zhang

Copyright © 2016 Aitzol Astigarraga et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Brain-Computer Interfaces (BCIs) have become a research field with interesting applications, and it can be inferred from published papers that different persons activate different parts of the brain to perform the same action. This paper presents a personalized interface design method, for electroencephalogram- (EEG-) based BCIs, based on channel selection. We describe a novel two-step method in which firstly a computationally inexpensive greedy algorithm finds an adequate search range; and, then, an Estimation of Distribution Algorithm (EDA) is applied in the reduced range to obtain the optimal channel subset. The use of the EDA allows us to select the most interacting channels subset, removing the irrelevant and noisy ones, thus selecting the most discriminative subset of channels for each user improving accuracy. The method is tested on the IIIa dataset from the BCI competition III. Experimental results show that the resulting channel subset is consistent with motor-imaginary-related neurophysiological principles and, on the other hand, optimizes performance reducing the number of channels.