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Performance analysis of multi-frequency SSVEP-BCI using clear and frosted colour LED stimuli

Mouli, S., Palaniappan, Ramaswamy, Sillitoe, I.P., Gan, J.Q. (2013) Performance analysis of multi-frequency SSVEP-BCI using clear and frosted colour LED stimuli. In: Proceedings of the 13th IEEE International Conference on BioInformatics and BioEngineering. . IEEE ISBN 978-1-4799-3163-7. (doi:10.1109/BIBE.2013.6701552) (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)
Official URL
http://dx.doi.org/10.1109/BIBE.2013.6701552

Abstract

Among the many paradigms used in brain-computer interface (BCI), steady state visual evoked potential (SSVEP) offers the quickest response; however it is disadvantageous from the point of view of visual fatigue, which prevents subjects from prolonged usage of visual stimuli especially when LEDs are used. In this paper, we propose a visual stimulator using readily available RGB LEDs with clear and frosted glass, with the latter being tested for performance and qualitative user comfort using electroencephalogram (EEG) data from four subjects. Furthermore, we also compare frosted and clear stimuli for three colours Red, Green and Blue with frequency values of 7, 8, 9 and 10 Hz. The results using band-pass filtering and Fast Fourier Transform showed that 7 Hz Green clear LED stimuli gave the highest response in general, although all the subjects indicated that they were more comfortable with frosted LED stimuli.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/BIBE.2013.6701552
Additional information: Unmapped bibliographic data: C7 - 6701552 [EPrints field already has value set] LA - English [Field not mapped to EPrints] J2 - IEEE Int. Conf. BioInformatics BioEng., IEEE BIBE [Field not mapped to EPrints] AD - Dept. of Engineering, University of Wolverhampton, Telford, United Kingdom [Field not mapped to EPrints] AD - School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Conference Paper [Field not mapped to EPrints] A4 - Institute of Electrical and Electronic Engineers (IEEE); Artificial Intelligence Foundation (BAIF) [Field not mapped to EPrints] C3 - 13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013 [Field not mapped to EPrints]
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 15 Dec 2018 18:54 UTC
Last Modified: 30 May 2019 08:28 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70698 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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