Brain computer interface via stereoscopic images in CAVE

Authors:
Hideaki Touyama;Michitaka Hirose
Affiliations:
Graduate School of Information Science and Technology, University of Tokyo;Graduate School of Information Science and Technology, University of Tokyo
Venue:
Proceedings of the 2007 conference on Human interface: Part I
Year:
2007

Citing 2
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Abstract

The electroencephalogram signals of steady-state visual evoked potentials were recorded for three subjects in immersive virtual environment. A machine learning technique of support vector machine with single trial EEG data for 1.0 seconds resulted in 92.1 % of averaged recognition rate in selecting a virtual button among two. The online demonstrations in CAVE showed good performance in position control of a simple 3D object.