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Optimising the number of channels in EEG-augmented image search

Healy, Graham and Smeaton, Alan F. (2011) Optimising the number of channels in EEG-augmented image search. In: THe 25th BCS Conference on Human-Computer Interaction (HCI), 4th - 8th July 2011, Newcastle-upon-Tyne, UK.

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Recent proof-of-concept research has appeared showing the applicability of Brain Computer Interface (BCI) technology in combination with the human visual system, to classify images. The basic premise here is that images that arouse a participant’s attention generate a detectable response in their brainwaves, measurable using an electroencephalograph (EEG). When a participant is given a target class of images to search for, each image belonging to that target class presented within a stream of images should elicit a distinctly detectable neural response. Previous work in this domain has primarily focused on validating the technique on proof of concept image sets that demonstrate desired properties and on examining the capabilities of the technique at various image presentation speeds. In this paper we expand on this by examining the capability of the technique when using a reduced number of channels in the EEG, and its impact on the detection accuracy.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:Brain computer interface; BCI; image search; electroencephalograph; EEG; P300
Subjects:Computer Science > Image processing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Official URL:
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:16387
Deposited On:17 Jun 2011 11:09 by Alan Smeaton. Last Modified 08 Feb 2013 10:52

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