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Towards a gaze-independent hybrid-BCI based on SSVEPs, alpha-band modulations and the P300

Loughnane, Gerard M., Meade, Emma, Reilly, Richard B. and Lalor, Edmund C. (2014) Towards a gaze-independent hybrid-BCI based on SSVEPs, alpha-band modulations and the P300. In: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, pp. 1322-1325. ISBN 9781424479290

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/EMBC.2014.6943842

Abstract

In recent years it has been shown to be possible to create a Brain Computer Interface (BCI) using non-invasive electroencephalographic (EEG) measurements of covert visual spatial attention. For example, that both Steady-State Visual Evoked Potentials (SSVEP) and parieto-occipital alpha band activity have been shown to be sensitive to covert attention and this has been exploited to provide simple communication control without the need for any physical movement. In this study, potential improvements in the speed and accuracy of such a BCI are investigated by exploring the possibility of incorporating a P300 task into an SSVEP covert attention paradigm. Should this be possible it would pave the way for a gaze-independent hybrid BCI based on three somewhat independent EEG signals. Within a well-established SSVEP-based attention paradigm we show that it is possible to make a binary classification of covert attention using just the P300 with an average accuracy of 71% across three subjects. We also validate previously published research by showing robust attention effects on the SSVEP and alpha band activity within this paradigm. In future work, it is hoped that by integrating the three signals into a hybrid BCI a significant improvement in performance will be forthcoming leading to an easily usable real time communication device for patients with severe disabilities such as Locked-In Syndrome (LIS).

Item Type: Book Section
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions: School of Business > Staff Research and Publications
Depositing User: Caoimhe Ní Mhaicín
Date Deposited: 03 Jan 2020 13:01
Last Modified: 03 Jan 2020 13:01
URI: https://norma.ncirl.ie/id/eprint/4123

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