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

Asensio-Cubero, J., Gan, J.Q., Palaniappan, Ramaswamy (2014) Multiresolution analysis of an information based EEG graph representation for motor imagery brain computer interfaces. In: PhyCS 2014 - Proceedings of the International Conference on Physiological Computing Systems. . pp. 5-12. SciTePress ISBN 978-989-758-006-2. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
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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.

Item Type: Conference or workshop item (Paper)
Additional information: Unmapped bibliographic data: LA - English [Field not mapped to EPrints] J2 - PhyCS - Proc. Int. Conf. Physiol. Comput. Syst. [Field not mapped to EPrints] AD - University of Essex, Wivenhoe Park, Colchester, Essex CO4 3SQ, United Kingdom [Field not mapped to EPrints] AD - University of Wolverhampton, Shifnal Road, Telford, TF2 9NT, United Kingdom [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Conference Paper [Field not mapped to EPrints] A4 - Information, Control and Communication (INSTICC); Institute for Systems and Technologies of [Field not mapped to EPrints] C3 - PhyCS 2014 - Proceedings of the International Conference on Physiological Computing Systems [Field not mapped to EPrints]
Uncontrolled keywords: Brain computer interfacing, EEG data graph representation, Motor imagery, Multiresolution analysis, Mutual information, Wavelet lifting, Brain computer interface, Physiology, Brain-computer interfacing, Eeg datum, Motor imagery, Mutual informations, Wavelet lifting, Multiresolution analysis
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 15 Dec 2018 17:53 UTC
Last Modified: 30 May 2019 08:28 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70691 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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