Impact of an energy normalization transform on the performance of the LF-ASD brain computer interface

TitleImpact of an energy normalization transform on the performance of the LF-ASD brain computer interface
Publication TypeJournal Article
Year of Publication2004
AuthorsYu, Z., S. G. Mason, and G. E. Birch
Secondary AuthorsThrun, S., K. Saul, and B. Scholkopf
JournalAdvances in Neural Information Processing Systems 16
Volume16
Pagination725–732
ISSN1049-5258
Abstract

This paper presents an energy normalization transform as a method to reduce system errors in the LF-ASD brain-computer interface. The energy normalization transform has two major benefits to the system performance. First, it can increase class separation between the active and idle EEG data. Second, it can desensitize the system to the signal amplitude variability. For four subjects in the study, the benefits resulted in the performance improvement of the LF-ASD in the range from 7.7% to 18.9%, while for the fifth subject, who had the highest non-normalized accuracy of 90.5%, the performance did not change notably with normalization.

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