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Detection of movement-related patterns in ongoing single-channel electrocorticogram

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5 Author(s)
Graimann, B. ; Dept. of Med. Informatics, Graz Univ. of Technol., Austria ; Huggins, J.E. ; Schlogl, A. ; Levine, S.P.
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Adaptive autoregressive parameters and a linear classifier were used to detect movement related desynchronization and synchronization patterns in single-channel electrocorticogram (ECoG) obtained from implanted electrode grids. The best classification accuracies found had more than 90% hits and less than 10% false positives. The findings show that the detection of event-related desynchronization and synchronization in ECoG data can be used to reliably provide switch control directly by the brain and is therefore very suitable as the basis of a direct brain interface.

Published in:

Neural Systems and Rehabilitation Engineering, IEEE Transactions on  (Volume:11 ,  Issue: 3 )

Date of Publication:

Sept. 2003

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