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Multiresolution analysis of an information based EEG graph representation for motor imagery brain computer interfaces

Asensio-Cubero, J and Gan, JQ and Palaniappan, R (2014) Multiresolution analysis of an information based EEG graph representation for motor imagery brain computer interfaces. In: UNSPECIFIED, ? - ?.

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Abstract

Brain computer interfaces are control systems that allow the interaction with electronic devices by analysing the user's brain activity. The analysis of brain signals, more concretely, electroencephalographic data, represents a big challenge due to its noisy and low amplitude nature. Many researchers in the field have applied wavelet transform in order to leverage the signal analysis benefiting from its temporal and spectral capabilities. In this study we make use of the so-called second generation wavelets to extract features from temporal, spatial and spectral domains. The complete multiresolution analysis operates over an enhanced graph representation of motor imaginary trials, which uses per-subject knowledge to optimise the spatial links among the electrodes and to improve the filter design. As a result we obtain a novel method that improves the performance of classifying different imaginary limb movements without compromising the low computational resources used by lifting transform over graphs. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: PhyCS 2014 - Proceedings of the International Conference on Physiological Computing Systems
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Clare Chatfield
Date Deposited: 12 Sep 2014 12:00
Last Modified: 17 Aug 2017 17:52
URI: http://repository.essex.ac.uk/id/eprint/9229

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