user adapted motor-imaginary brain-computer interface by means of eeg channel selection based on estimation of distributed algorithms

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ID: 232988
2016
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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.
Reference Key
astigarraga2016mathematicaluser Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Aitzol Astigarraga;Andoni Arruti;Javier Muguerza;Roberto Santana;Jose I. Martin;Basilio Sierra
Journal journal of power sources
Year 2016
DOI
10.1155/2016/1435321
URL
http://dx.doi.org/10.1155/2016/1435321
Keywords
civil engineering (general)mathematics engineering (general)

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