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Enabling computer decisions based on EEG input (2003)

Culpepper, Benjamin J. ; Keller, Robert M.

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Publication Date: 2011-08-24

Description: Multilayer neural networks were successfully trained to classify segments of 12-channel electroencephalogram (EEG) data into one of five classes corresponding to five cognitive tasks performed by a subject. Independent component analysis (ICA) was used to segregate obvious artifact EEG components from other sources, and a frequency-band representation was used to represent the sources computed by ICA. Examples of results include an 85% accuracy rate on differentiation between two tasks, using a segment of EEG only 0.05 s long and a 95% accuracy rate using a 0.5-s-long segment.

Keywords: Man/System Technology and Life Support

Type: IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society (ISSN 1534-4320); Volume 11; 4; 354-60

Format: text

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