EEG analyses with SOBI.
Author(s) -
Matthew Glickman,
Akaysha C. Tang
Publication year - 2009
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/978914
Subject(s) - electroencephalography , identification (biology) , computer science , component (thermodynamics) , signal (programming language) , psychology , neuroscience , artificial intelligence , biology , botany , physics , thermodynamics , programming language
The motivating vision behind Sandia's MENTOR/PAL LDRD project has been that of systems which use real-time psychophysiological data to support and enhance human performance, both individually and of groups. Relevant and significant psychophysiological data being a necessary prerequisite to such systems, this LDRD has focused on identifying and refining such signals. The project has focused in particular on EEG (electroencephalogram) data as a promising candidate signal because it (potentially) provides a broad window on brain activity with relatively low cost and logistical constraints. We report here on two analyses performed on EEG data collected in this project using the SOBI (Second Order Blind Identification) algorithm to identify two independent sources of brain activity: one in the frontal lobe and one in the occipital. The first study looks at directional influences between the two components, while the second study looks at inferring gender based upon the frontal component
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