Improving the performance of the LF-ASD brain computer interface by means of genetic algorithm

TitleImproving the performance of the LF-ASD brain computer interface by means of genetic algorithm
Publication TypeConference Paper
Year of Publication2004
AuthorsFatourechi, M., A. Bashashati, J. F. Borisoff, G. E. Birch, and R. K. Ward
Conference NameSignal Processing and Information Technology, 2004. Proceedings of the 4th IEEE International Symposium on
Pagination38 - 41
Date Publisheddec.
KeywordsBCI system, brain, direct asynchronous brain computer interface, energy normalization transform, ENT, genetic algorithm, genetic algorithms, human computer interaction, LF-ASD, low frequency-asynchronous switch design, medical computing, user interfaces

The low frequency-asynchronous switch design (the LF-ASD) was introduced as a direct asynchronous brain computer interface (BCI) system. An asynchronous BCI system is activated only when a user intends control and maintains an inactive state output when a user is not meaning to control the device. Results from the LF-ASD evaluations have shown promise, although the reported error rates are still high for most practical applications. One reason is that, so far, no user customization has been done on the LF-ASD. In this paper genetic algorithms are applied to automatically customize the length of the energy normalization transform (ENT) in the LF-ASD. In a previous design, it has been shown that the ENT is probably the greatest source of improvement, so tuning it would probably yield the best short term results. Results for three subjects show encouraging results for the proposed algorithm with respect to the previous designs.


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